-- MySQL dump 9.11 -- -- Host: localhost Database: suwiki -- ------------------------------------------------------ -- Server version 4.0.22-log -- -- Table structure for table `cur` -- CREATE TABLE cur ( cur_id int(8) unsigned NOT NULL auto_increment, cur_namespace tinyint(2) unsigned NOT NULL default '0', cur_title varchar(255) binary NOT NULL default '', cur_text mediumtext NOT NULL, cur_comment tinyblob NOT NULL, cur_user int(5) unsigned NOT NULL default '0', cur_user_text varchar(255) binary NOT NULL default '', cur_timestamp varchar(14) binary NOT NULL default '', cur_restrictions tinyblob NOT NULL, cur_counter bigint(20) unsigned NOT NULL default '0', cur_is_redirect tinyint(1) unsigned NOT NULL default '0', cur_minor_edit tinyint(1) unsigned NOT NULL default '0', cur_is_new tinyint(1) unsigned NOT NULL default '0', cur_random double unsigned NOT NULL default '0', cur_touched varchar(14) binary NOT NULL default '', inverse_timestamp varchar(14) binary NOT NULL default '', UNIQUE KEY cur_id (cur_id), KEY cur_title (cur_title(20)), KEY cur_timestamp (cur_timestamp), KEY cur_random (cur_random), KEY name_title_timestamp (cur_namespace,cur_title,inverse_timestamp), KEY user_timestamp (cur_user,inverse_timestamp), KEY usertext_timestamp (cur_user_text,inverse_timestamp), KEY namespace_redirect_timestamp (cur_namespace,cur_is_redirect,cur_timestamp), KEY jamesspecialpages (cur_is_redirect,cur_namespace,cur_title,cur_timestamp), KEY qry_checktouched (cur_id,cur_is_redirect,cur_namespace,cur_title,cur_touched) ) TYPE=InnoDB; -- -- Dumping data for table `cur` -- INSERT INTO cur VALUES (1,0,'Tepas','
\n

\n\'\'Kaula sukur ka Allah\'\'
\n\'\'Gusti anu sipat rahim\'\'
\n\'\'Saréh kersa nu kawasa\'\'
\n\'\'Sunda dihudangkeun deui\'\'
\n\'\'Upama anu gering, ayeuna eukeur mamayu\'\'
\n\'\'ngan tacan cageur pisan\'\'
\n\'\'Manawa sakeudeung deui\'\'
\n\'\'muga-muga sing tuluy jagjag waringkas\'\'
\n\n(tina \'\'Dongéng-dongéng Pieunteungeun\'\', [[Muhamad Musa]], 1867)\n

\n

\n[[Wikipédia:Wilujeng sumping|Wilujeng sumping]] di [http://en.wikipedia.org/wiki/Wikipedia Wikipédia]!
\n


\n

\nDikeureuyeuh ti Januari 2001, Wikipédia vérsi Inggris nepi ka ayeuna geus boga leuwih ti 480000 [[Wikipédia:Artikel téh naon?|artikel]], sedengkeun Wikipédia Sunda kakara boga \'\'\'{{NUMBEROFARTICLES}}\'\'\' artikel ({{CURRENTDAY}} {{CURRENTMONTHNAME}} {{CURRENTYEAR}}). Saupama geus leuwih ti \'\'\'100000\'\'\' artikel, Wikipédia Basa Sunda bisa jadi salasahiji Wikipédia utama.
\nNa Wikipédia, sing saha waé, kaasup anjeun, bisa ngamimitian, nambah, atawa [[Wikipédia:Cara ngédit kaca|ngédit artikel]] naon waé ayeuna ogé, tanpa perlu asup log. Tingali kaca [http://en.wikipedia.org/wiki/Wikipedia:FAQ FAQ (basa Inggris)], atawa [[:Wikipédia:NLD|NLD]] (basa Sunda) pikeun katerangan ngeunaan proyék ieu, ogé [[Pitulung: Eusi|kaca pitulung]] umumna. Pikeun coba-coba, gunakeun [[Wikipédia:Kotrétan|tempat ngotrét]]. Para pamaké dianjurkeun ogé ningali halaman [[:Wikipédia:Kasalahan umum|kasalahan umum]] Wikipédia.
\nHayu urang babarengan nyusun énsiklopédi multibasa nu bisa dimangpaatkeun ku sing saha baé kalawan bébas. \n

\n
\n{{Template:Browserstandar}}\n\n
\n

\nSungsi Wikipédia dumasar jejer

\n{{Template:KolomWikipédia}}\n
\n
\n\n
\n=== \'\'\'Wikipédia na basa séjén\'\'\' ===\n{{Template:Wikipedialang}}\n
\n
\n\n
\n=== \'\'\'Proyék dulur Wikipédia\'\'\' ===\n\n{{Template:Wikipediasister}}\n
\n
\n
\nInfo nu leuwih lengkep ngeunaan proyék Wikipédia bisa ditempo di jalaloka (\'\'website\'\') utama [http://en.wikipedia.org basa Inggris].\n
','',3,'Kandar','20050313153636','move=:edit=',0,0,1,0,0.797870382572,'20050313153636','79949686846363'); INSERT INTO cur VALUES (2,0,'HomePage','#REDIRECT [[Main_Page]]\n','moved to \"Main_Page\"',1,'Brion VIBBER','20040125144023','',0,1,0,1,0.779782248455828,'20040808225710','79959874855976'); INSERT INTO cur VALUES (3,8,'Categories','Kategori','',3,'Kandar','20040729045353','sysop',0,0,0,0,0.949109094170024,'20040729045353','79959270954646'); INSERT INTO cur VALUES (4,8,'Category','kategori','',3,'Kandar','20040728103700','sysop',0,0,0,0,0.406198756216279,'20040728103700','79959271896299'); INSERT INTO cur VALUES (5,8,'Category_header','Artikel-artikel na kategori \"$1\"','',3,'Kandar','20040802074714','sysop',0,0,0,0,0.183666529304969,'20040802074714','79959197925285'); INSERT INTO cur VALUES (6,8,'Subcategories','Subkategori','',3,'Kandar','20040729021039','sysop',0,0,0,0,0.699736408609651,'20040729021039','79959270978960'); INSERT INTO cur VALUES (7,8,'Linktrail','/^([a-z]+)(.*)$/sD','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.947682485866996,'20041223055408','79958776944591'); INSERT INTO cur VALUES (8,8,'Mainpage','Tepas','',3,'Kandar','20040728105904','sysop',0,0,0,0,0.639203234239671,'20040728105904','79959271894095'); INSERT INTO cur VALUES (9,8,'Mainpagetext','\'\'Software\'\' Wiki geus diinstal.','',3,'Kandar','20040728105804','sysop',0,0,0,0,0.35296874433101,'20040728105804','79959271894195'); INSERT INTO cur VALUES (10,8,'About','Ngeunaan','',3,'Kandar','20040728102837','sysop',0,0,0,0,0.847234049669685,'20040728102837','79959271897162'); INSERT INTO cur VALUES (11,8,'Aboutwikipedia','Ngeunaan Wikipédia','',3,'Kandar','20040728102910','sysop',0,0,0,0,0.177264046089038,'20040728102910','79959271897089'); INSERT INTO cur VALUES (12,8,'Aboutpage','Wikipédia:Ngeunaan','',3,'Kandar','20040728102856','sysop',0,0,0,0,0.344618112169782,'20040728102856','79959271897143'); INSERT INTO cur VALUES (13,8,'Help','Pitulung','',3,'Kandar','20040728104647','sysop',0,0,0,0,0.191298453315439,'20040728104647','79959271895352'); INSERT INTO cur VALUES (14,8,'Helppage','Pitulung: Eusi','',3,'Kandar','20050204070204','sysop',0,0,0,0,0.922637960801495,'20050204070204','79949795929795'); INSERT INTO cur VALUES (15,8,'Wikititlesuffix','Wikipédia','',3,'Kandar','20040729021826','sysop',0,0,0,0,0.0392944747948036,'20040729021826','79959270978173'); INSERT INTO cur VALUES (16,8,'Bugreports','Laporan kutu','',3,'Kandar','20040904050130','sysop',0,0,0,0,0.428558522303178,'20040904050130','79959095949869'); INSERT INTO cur VALUES (17,8,'Bugreportspage','Project:Bug_reports','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.0249092178651218,'20041223055405','79958776944594'); INSERT INTO cur VALUES (18,8,'Sitesupport','Sumbangan','',3,'Kandar','20040729020924','sysop',0,0,0,0,0.838870553149721,'20040729020924','79959270979075'); INSERT INTO cur VALUES (19,10,'Sitesupportpage','<sitesupportpage>','',0,'MediaWiki default','20040129151928','sysop',0,0,0,1,0.119625142886886,'20040603084252','79959870848071'); INSERT INTO cur VALUES (20,8,'Faq','NLD','',3,'Kandar','20040729051120','sysop',0,0,0,0,0.0815140857189094,'20040729051120','79959270948879'); INSERT INTO cur VALUES (21,8,'Faqpage','Wikipédia:NLD','',3,'Kandar','20040729051132','sysop',0,0,0,0,0.0486950306675351,'20040729051132','79959270948867'); INSERT INTO cur VALUES (22,8,'Edithelp','Pitulung ngédit','',3,'Kandar','20040728104320','sysop',0,0,0,0,0.998932926914592,'20040728104320','79959271895679'); INSERT INTO cur VALUES (23,8,'Edithelppage','Pitulung:Ngédit','',3,'Kandar','20040729045810','sysop',0,0,0,0,0.848579573304001,'20040729045810','79959270954189'); INSERT INTO cur VALUES (24,8,'Cancel','Batal','',3,'Kandar','20040728103908','sysop',0,0,0,0,0.246099116509873,'20040728103908','79959271896091'); INSERT INTO cur VALUES (25,8,'Qbfind','Panggihan','',3,'Kandar','20040729061008','sysop',0,0,0,0,0.684756893371005,'20040729061008','79959270938991'); INSERT INTO cur VALUES (26,8,'Qbbrowse','Sungsi','',3,'Kandar','20041030021759','sysop',0,0,0,0,0.685487148059054,'20041030021759','79958969978240'); INSERT INTO cur VALUES (27,8,'Qbedit','Édit','',3,'Kandar','20040728112416','sysop',0,0,0,0,0.373165090915901,'20040728112416','79959271887583'); INSERT INTO cur VALUES (28,8,'Qbpageoptions','Kaca ieu','',3,'Kandar','20040729015758','sysop',0,0,0,0,0.809364041135985,'20040729015758','79959270984241'); INSERT INTO cur VALUES (29,8,'Qbpageinfo','Kontéx','',3,'Kandar','20050126043903','sysop',0,0,0,0,0.92732496366587,'20050126043903','79949873956096'); INSERT INTO cur VALUES (30,8,'Qbmyoptions','Kaca kuring','',3,'Kandar','20040729061025','sysop',0,0,0,0,0.208532725655039,'20040729061025','79959270938974'); INSERT INTO cur VALUES (31,8,'Qbspecialpages','Kaca husus','',3,'Kandar','20040729015831','sysop',0,0,0,0,0.260688768011228,'20040729015831','79959270984168'); INSERT INTO cur VALUES (32,8,'Moredotdotdot','Deui...','',3,'Kandar','20041229065340','sysop',0,0,0,0,0.677845693824669,'20041229065340','79958770934659'); INSERT INTO cur VALUES (33,8,'Mypage','Kaca kuring','',3,'Kandar','20040728110742','sysop',0,0,0,0,0.607162195823306,'20040728110742','79959271889257'); INSERT INTO cur VALUES (34,8,'Mytalk','Omongan kuring','',3,'Kandar','20040728110751','sysop',0,0,0,0,0.00227392837616981,'20040728110751','79959271889248'); INSERT INTO cur VALUES (35,8,'Currentevents','Lumangsung kiwari','',3,'Kandar','20050131043843','sysop',0,0,0,0,0.189883085144575,'20050131043843','79949868956156'); INSERT INTO cur VALUES (36,8,'Disclaimers','Bantahan','',3,'Kandar','20040729045649','sysop',0,0,0,0,0.94259367132801,'20040729045649','79959270954350'); INSERT INTO cur VALUES (37,8,'Disclaimerpage','Wikipédia:Bantahan_umum','',3,'Kandar','20040729045747','sysop',0,0,0,0,0.143319131939969,'20040729045747','79959270954252'); INSERT INTO cur VALUES (38,8,'Errorpagetitle','Kasalahan','',3,'Kandar','20040924064209','sysop',0,0,0,0,0.888814676449462,'20040924064209','79959075935790'); INSERT INTO cur VALUES (39,8,'Returnto','Balik deui ka $1.','',3,'Kandar','20040803064022','sysop',0,0,0,0,0.0141160171610452,'20040803064022','79959196935977'); INSERT INTO cur VALUES (40,8,'Fromwikipedia','Ti Wikipédia','',3,'Kandar','20040802094838','sysop',0,0,0,0,0.404136087190487,'20040802094838','79959197905161'); INSERT INTO cur VALUES (41,8,'Whatlinkshere','Nu numbu ka dieu','',3,'Kandar','20040831041912','sysop',0,0,0,0,0.978332415202942,'20040831041912','79959168958087'); INSERT INTO cur VALUES (42,8,'Search','Téang','',3,'Kandar','20040729020734','sysop',0,0,0,0,0.679253845176896,'20040729020734','79959270979265'); INSERT INTO cur VALUES (43,8,'Go','Jung','',3,'Kandar','20040728104617','sysop',0,0,0,0,0.461272011009298,'20040728104617','79959271895382'); INSERT INTO cur VALUES (44,8,'History','Jujutan kaca','',3,'Kandar','20040728104824','sysop',0,0,0,0,0.268598550249449,'20040728104824','79959271895175'); INSERT INTO cur VALUES (45,8,'Printableversion','Vérsi citakeun','',3,'Kandar','20040728112435','sysop',0,0,0,0,0.959176748952993,'20040728112435','79959271887564'); INSERT INTO cur VALUES (46,8,'Editthispage','Édit kaca ieu','',3,'Kandar','20040728104211','sysop',0,0,0,0,0.990088124750264,'20040728104211','79959271895788'); INSERT INTO cur VALUES (47,8,'Deletethispage','Hapus kaca ieu','',3,'Kandar','20040802085003','sysop',0,0,0,0,0.0729104076259866,'20040802085003','79959197914996'); INSERT INTO cur VALUES (48,8,'Protectthispage','Konci kaca ieu','',3,'Kandar','20050221110802','sysop',0,0,1,0,0.394287694612786,'20050221110802','79949778889197'); INSERT INTO cur VALUES (49,8,'Unprotectthispage','Buka konci kaca ieu','',3,'Kandar','20050221111155','sysop',0,0,1,0,0.752707280919614,'20050221111155','79949778888844'); INSERT INTO cur VALUES (50,8,'Newpage','Kaca anyar','',3,'Kandar','20040728110909','sysop',0,0,0,0,0.58067335149336,'20040728110909','79959271889090'); INSERT INTO cur VALUES (51,8,'Talkpage','Sawalakeun kaca ieu','',3,'Kandar','20040729021104','sysop',0,0,0,0,0.645244945441601,'20040729021104','79959270978895'); INSERT INTO cur VALUES (52,8,'Postcomment','Kirim koméntar','',3,'Kandar','20040827085157','sysop',0,0,0,0,0.484204703461569,'20040827085157','79959172914842'); INSERT INTO cur VALUES (53,8,'Articlepage','Témbongkeun kaca eusi','',3,'Kandar','20040904050117','sysop',0,0,0,0,0.48528871171669,'20040904050117','79959095949882'); INSERT INTO cur VALUES (54,8,'Subjectpage','Témbongkeun subjék','',3,'Kandar','20040906062249','sysop',0,0,0,0,0.973829478932386,'20040906062249','79959093937750'); INSERT INTO cur VALUES (55,8,'Userpage','Témbongkeun kaca pamaké','',3,'Kandar','20040810065134','sysop',0,0,0,0,0.413281290245504,'20040810065134','79959189934865'); INSERT INTO cur VALUES (56,8,'Wikipediapage','Témbongkeun kaca proyék','',3,'Kandar','20040831063042','sysop',0,0,0,0,0.14491804516401,'20040831063042','79959168936957'); INSERT INTO cur VALUES (57,8,'Imagepage','Témbongkeun kaca gambar','',3,'Kandar','20040728105028','sysop',0,0,0,0,0.48474638581718,'20040728105028','79959271894971'); INSERT INTO cur VALUES (58,8,'Viewtalkpage','Témbongkeun sawala','',3,'Kandar','20040729021600','sysop',0,0,0,0,0.988977824327515,'20040729021600','79959270978399'); INSERT INTO cur VALUES (59,8,'Otherlanguages','Basa séjén','',3,'Kandar','20040728112039','sysop',0,0,0,0,0.490649994919682,'20040728112039','79959271887960'); INSERT INTO cur VALUES (60,8,'Redirectedfrom','(Dialihkeun ti $1)','',3,'Kandar','20040915060219','sysop',0,0,0,0,0.486316532349509,'20040915060219','79959084939780'); INSERT INTO cur VALUES (61,8,'Lastmodified','Kaca ieu panungtungan dirobah $1.','',3,'Kandar','20040802100510','sysop',0,0,0,0,0.959632707722143,'20040802100510','79959197899489'); INSERT INTO cur VALUES (62,8,'Viewcount','Kaca ieu geus dibuka $1 kali.','',3,'Kandar','20040906072806','sysop',0,0,0,0,0.339213972295834,'20040906072806','79959093927193'); INSERT INTO cur VALUES (63,10,'Gnunote','All text is available under the terms of the GNU Free Documentation License.','',0,'MediaWiki default','20040129151928','sysop',0,0,0,1,0.817171769046385,'20040603084251','79959870848071'); INSERT INTO cur VALUES (64,8,'Printsubtitle','(Ti http://su.wikipedia.org)','',3,'Kandar','20040728112450','sysop',0,0,0,0,0.0682169590780669,'20040728112450','79959271887549'); INSERT INTO cur VALUES (65,8,'Protectedpage','Kaca nu dikonci','',3,'Kandar','20050221110644','sysop',0,0,1,0,0.889569518984826,'20050221110644','79949778889355'); INSERT INTO cur VALUES (66,8,'Administrators','Wikipédia:Kuncén','',3,'Kandar','20041122092912','sysop',0,0,0,0,0.243196748423573,'20041122092912','79958877907087'); INSERT INTO cur VALUES (67,8,'Sysoptitle','Kudu ku kuncén','',3,'Kandar','20050208084347','sysop',0,0,0,0,0.547275215897034,'20050208084347','79949791915652'); INSERT INTO cur VALUES (68,8,'Sysoptext','Peta nu dipénta ku anjeun ngan bisa dipigawé ku pamaké nu statusna kuncén. Tempo $1.','',3,'Kandar','20050208084339','sysop',0,0,0,0,0.00678586494809563,'20050208084339','79949791915660'); INSERT INTO cur VALUES (69,8,'Developertitle','Kudu ku developer','',3,'Kandar','20040906100045','sysop',0,0,0,0,0.392103707783021,'20040906100045','79959093899954'); INSERT INTO cur VALUES (70,8,'Developertext','Peta nu dipénta ngan bisa dipigawé ku pamaké nu statusna \"developer\". Tempo $1.','',3,'Kandar','20040810060419','sysop',0,0,0,0,0.940160974804462,'20040810060419','79959189939580'); INSERT INTO cur VALUES (71,8,'Nbytes','$1 bait','',3,'Kandar','20041229065759','sysop',0,0,0,0,0.524493781406892,'20041229065759','79958770934240'); INSERT INTO cur VALUES (72,8,'Ok','Heug','',3,'Kandar','20040728112024','sysop',0,0,0,0,0.801986013354721,'20040728112024','79959271887975'); INSERT INTO cur VALUES (73,8,'Sitetitle','Wikipédia','',3,'Kandar','20040729020743','sysop',0,0,0,0,0.436448753286571,'20040729020743','79959270979256'); INSERT INTO cur VALUES (74,8,'Sitesubtitle','Énsiklopédi Bébas','',3,'Kandar','20040729020906','sysop',0,0,0,0,0.776285757102338,'20040729020906','79959270979093'); INSERT INTO cur VALUES (75,8,'Retrievedfrom','Retrieved from \"$1\"','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.572082556385624,'20041223055411','79958776944588'); INSERT INTO cur VALUES (76,8,'Newmessages','Anjeun boga $1.','',3,'Kandar','20040728110853','sysop',0,0,0,0,0.531555541354749,'20040728110853','79959271889146'); INSERT INTO cur VALUES (77,8,'Newmessageslink','pesen anyar','',3,'Kandar','20040728110900','sysop',0,0,0,0,0.941530068350518,'20040728110900','79959271889099'); INSERT INTO cur VALUES (78,8,'Editsection','édit','',3,'Kandar','20040728104116','sysop',0,0,0,0,0.112983748421989,'20040728104116','79959271895883'); INSERT INTO cur VALUES (79,8,'Toc','Daptar eusi','',3,'Kandar','20040729021451','sysop',0,0,0,0,0.740328567792036,'20040729021451','79959270978548'); INSERT INTO cur VALUES (80,8,'Showtoc','témbongkeun','',3,'Kandar','20040729020850','sysop',0,0,0,0,0.362691624427858,'20040729020850','79959270979149'); INSERT INTO cur VALUES (81,8,'Hidetoc','sumputkeun','',3,'Kandar','20040728104649','sysop',0,0,0,0,0.592472449496828,'20040728104649','79959271895350'); INSERT INTO cur VALUES (82,8,'Thisisdeleted','Témbongkeun atawa simpen deui $1?','',3,'Kandar','20040906062258','sysop',0,0,0,0,0.874287404934212,'20040906062258','79959093937741'); INSERT INTO cur VALUES (83,8,'Restorelink','$1 éditan dihapus','',3,'Kandar','20040803064006','sysop',0,0,0,0,0.59401970691422,'20040803064006','79959196935993'); INSERT INTO cur VALUES (84,8,'Nosuchaction','Teu aya peta kitu','',3,'Kandar','20040728111520','sysop',0,0,0,0,0.347236350502108,'20040728111520','79959271888479'); INSERT INTO cur VALUES (85,8,'Nosuchactiontext','Peta nu diketik na URL teu dipikawanoh ku wiki','',3,'Kandar','20040728111600','sysop',0,0,0,0,0.954122662501524,'20040728111600','79959271888399'); INSERT INTO cur VALUES (86,8,'Nosuchspecialpage','Teu aya kaca husus nu kitu','',3,'Kandar','20040728112000','sysop',0,0,0,0,0.728904291734942,'20040728112000','79959271887999'); INSERT INTO cur VALUES (87,8,'Nospecialpagetext','Anjeun geus ménta kaca husus nu teu dipikawanoh ku wiki.','',3,'Kandar','20040827074804','sysop',0,0,0,0,0.782153501903781,'20040827074804','79959172925195'); INSERT INTO cur VALUES (88,8,'Error','Kasalahan','',3,'Kandar','20040924064209','sysop',0,0,0,0,0.724054665047726,'20040924064209','79959075935790'); INSERT INTO cur VALUES (89,8,'Databaseerror','Kasalahan gudang data','',3,'Kandar','20041229060726','sysop',0,0,0,0,0.273812850260933,'20041229060726','79958770939273'); INSERT INTO cur VALUES (90,8,'Dberrortext','A database query syntax error has occurred.\nThis may indicate a bug in the software.\nThe last attempted database query was:\n
$1
\nfrom within function \"$2\".\nMySQL returned error \"$3: $4\".','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.19690028689513,'20041223055406','79958776944593'); INSERT INTO cur VALUES (91,8,'Dberrortextcl','A database query syntax error has occurred.\nThe last attempted database query was:\n\"$1\"\nfrom within function \"$2\".\nMySQL returned error \"$3: $4\".\n','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.163062914426497,'20041223055406','79958776944593'); INSERT INTO cur VALUES (92,8,'Noconnect','Punten! Wiki ngalaman sababaraha kasusah téhnis sarta teu bisa ngontak server database.','',3,'Kandar','20040827083559','sysop',0,0,0,0,0.22461374218074,'20040827083559','79959172916440'); INSERT INTO cur VALUES (93,8,'Nodb','Teu bisa milih database $1','',3,'Kandar','20040827084051','sysop',0,0,0,0,0.633879998357855,'20040827084051','79959172915948'); INSERT INTO cur VALUES (94,8,'Cachederror','Kanggo kaca nu dipénta, di handap ieu mangrupa salinan ti nu aya, tiasa waé tos tinggaleun jaman.','',3,'Kandar','20040802074628','sysop',0,0,0,0,0.495558795980698,'20040802074628','79959197925371'); INSERT INTO cur VALUES (95,8,'Readonly','Database dikonci','',3,'Kandar','20040902080100','sysop',0,0,0,0,0.576154015563572,'20040902080100','79959097919899'); INSERT INTO cur VALUES (96,8,'Enterlockreason','Asupkeun alesan pikeun ngonci, kaasup kira-kira iraha konci ieu rék dibuka','',3,'Kandar','20040802093133','sysop',0,0,0,0,0.394093720609409,'20040802093133','79959197906866'); INSERT INTO cur VALUES (97,8,'Readonlytext','database kiwar keur di konci pikeun éntri anyar sarta parobahan séjénna, meureun pikeun pangropéa database rutin, nu satutasna mah bakal normal deui. Kuncén nu ngonci ngécéskeun kieu:\n

$1','',3,'Kandar','20041122093224','sysop',0,0,0,0,0.242006587089977,'20041122093224','79958877906775'); INSERT INTO cur VALUES (98,8,'Missingarticle','Database teu manggihan téks kaca nu sakuduna aya, ngaranna \"$1\".\n\n

This is usually caused by following an outdated diff or history link to a\npage that has been deleted.\n\n

Mun lain kitu masalahna, jigana anjeun geus manggihan kutu na \'\'software\'\'na. Mangga wartoskeun ka kuncén, dugikeun ogé URLna.','',3,'Kandar','20041122093252','sysop',0,0,0,0,0.0277518043553008,'20041122093252','79958877906747'); INSERT INTO cur VALUES (99,8,'Internalerror','Kasalahan internal','',3,'Kandar','20041229063755','sysop',0,0,0,0,0.412739291240218,'20041229063755','79958770936244'); INSERT INTO cur VALUES (100,8,'Filecopyerror','Teu bisa nyalin koropak \"$1\" ka \"$2\".','',3,'Kandar','20040904050934','sysop',0,0,0,0,0.980441073868835,'20040904050934','79959095949065'); INSERT INTO cur VALUES (101,8,'Filerenameerror','Teu bisa ngaganti ngaran koropak \"$1\" jadi \"$2\".','',3,'Kandar','20040904051146','sysop',0,0,0,0,0.663987526357162,'20040904051146','79959095948853'); INSERT INTO cur VALUES (102,8,'Filedeleteerror','Teu bisa ngahapus koropak \"$1\".','',3,'Kandar','20040904050944','sysop',0,0,0,0,0.378614440912953,'20040904050944','79959095949055'); INSERT INTO cur VALUES (103,8,'Filenotfound','Teu bisa manggihan koropak \"$1\".','',3,'Kandar','20040904051137','sysop',0,0,0,0,0.901109656226923,'20040904051137','79959095948862'); INSERT INTO cur VALUES (104,8,'Unexpected','Unexpected value: \"$1\"=\"$2\".','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.369704989129403,'20041223055413','79958776944586'); INSERT INTO cur VALUES (105,8,'Formerror','Kasalahan: teu bisa ngirim formulir','',3,'Kandar','20041229061547','sysop',0,0,0,0,0.145196007699888,'20041229061547','79958770938452'); INSERT INTO cur VALUES (106,8,'Badarticleerror','Peta ieu teu bisa dipigawé na kaca ieu.','',3,'Kandar','20040729013534','sysop',0,0,0,0,0.616865101844878,'20040729013534','79959270986465'); INSERT INTO cur VALUES (107,8,'Cannotdelete','Teu bisa ngahapus kaca atawa gambar nu dimaksud (bisa jadi geus aya nu ngahapus saméméhna).','',3,'Kandar','20040802074940','sysop',0,0,0,0,0.648737516858371,'20040802074940','79959197925059'); INSERT INTO cur VALUES (108,8,'Badtitle','Judul goréng','',3,'Kandar','20040827075406','sysop',0,0,0,0,0.393092309490864,'20040827075406','79959172924593'); INSERT INTO cur VALUES (109,8,'Badtitletext','Judul kaca nu dipénta teu sah, kosong, atawa judul antarbasa atawa antarwikina salah tumbu.','',3,'Kandar','20040812031854','sysop',0,0,0,0,0.019249027612851,'20040812031854','79959187968145'); INSERT INTO cur VALUES (110,8,'Perfdisabled','Punten! Fungsi ieu pikeun samentawis ditumpurkeun sabab ngahambat database nepi ka titik di mana teu saurang ogé bisa migunakeun wiki.','',3,'Kandar','20041006090452','sysop',0,0,0,0,0.91696824032531,'20041006090452','79958993909547'); INSERT INTO cur VALUES (111,8,'Perfdisabledsub','Ieu salaku salinan nu diteundeun ti $1:','',3,'Kandar','20040728112337','sysop',0,0,0,0,0.52709414952164,'20040728112337','79959271887662'); INSERT INTO cur VALUES (112,8,'Wrong_wfQuery_params','Incorrect parameters to wfQuery()
\nFunction: $1
\nQuery: $2\n','',0,'MediaWiki default','20041223055414','sysop',0,0,0,0,0.884566057365915,'20041223055414','79958776944585'); INSERT INTO cur VALUES (113,8,'Viewsource','Témbongkeun sumber','',3,'Kandar','20040906062438','sysop',0,0,0,0,0.8415478689983,'20040906062438','79959093937561'); INSERT INTO cur VALUES (114,8,'Protectedtext','Kaca ieu dikonci tina ngédit; aya sababaraha alesan pangna dikonci, mangga tingal [[Wikipédia:Kaca nu dikonci|kaca nu dikonci]].\n\nAnjeun bisa muka sarta nyalin sumber kaca ieu:','',3,'Kandar','20050221110720','sysop',0,0,1,0,0.554041203627401,'20050221110720','79949778889279'); INSERT INTO cur VALUES (115,8,'Logouttitle','Kaluar log pamaké','',3,'Kandar','20050221094755','sysop',0,0,1,0,0.245562441875751,'20050221094755','79949778905244'); INSERT INTO cur VALUES (116,8,'Logouttext','Anjeun ayeuna geus kaluar log. Anjeun bisa neruskeun migunakeun Wikipédia bari anonim, atawa bisa asup log deui maké pamaké nu sarua atawa nu béda. Perlu dicatet yén sababaraha kaca bakal terus némbongan saolah-olah anjeun asup log kénéh nepi ka anjeun ngosongkeun \'\'cache\'\' panyungsi anjeun.','',3,'Kandar','20050221094513','sysop',0,0,1,0,0.565688629230194,'20050221094513','79949778905486'); INSERT INTO cur VALUES (117,8,'Welcomecreation','

Wilujeng sumping, $1!

Rekening anjeun geus dijieun. Tong hilap ngarobih préferénsi Wikipédia anjeun.','',3,'Kandar','20050203192222','sysop',0,0,0,0,0.0917558512573651,'20050203192222','79949796807777'); INSERT INTO cur VALUES (118,8,'Loginpagetitle','Asup log pamaké','',3,'Kandar','20050221094448','sysop',0,0,1,0,0.761713399329887,'20050221094448','79949778905551'); INSERT INTO cur VALUES (119,8,'Yourname','Ngaran pamaké anjeun','',3,'Kandar','20040810065333','sysop',0,0,0,0,0.533299473610986,'20040810065333','79959189934666'); INSERT INTO cur VALUES (120,8,'Yourpassword','Sandi anjeun','',3,'Kandar','20040729021913','sysop',0,0,0,0,0.381357200798911,'20040729021913','79959270978086'); INSERT INTO cur VALUES (121,8,'Yourpasswordagain','Ketik deui sandi anjeun','',3,'Kandar','20040729021925','sysop',0,0,0,0,0.306887613895245,'20040729021925','79959270978074'); INSERT INTO cur VALUES (122,8,'Newusersonly',' (pamaké anyar wungkul)','',3,'Kandar','20040810061945','sysop',0,0,0,0,0.390366497813134,'20040810061945','79959189938054'); INSERT INTO cur VALUES (123,8,'Remembermypassword','Inget sandi kuring liwat sési.','',3,'Kandar','20040803062047','sysop',0,0,0,0,0.0311696781135813,'20040803062047','79959196937952'); INSERT INTO cur VALUES (124,8,'Loginproblem','Aya masalah na \'\'login\'\' anjeun.
Coba deui!','',3,'Kandar','20040802101329','sysop',0,0,0,0,0.98474892786215,'20040802101329','79959197898670'); INSERT INTO cur VALUES (125,8,'Alreadyloggedin','Pamaké $1, anjeun geus asup log!
','',3,'Kandar','20050221093537','sysop',0,0,1,0,0.830235635703649,'20050221093537','79949778906462'); INSERT INTO cur VALUES (126,8,'Login','Asup log','',3,'Kandar','20040831025432','sysop',0,0,0,0,0.196931425665441,'20040831025432','79959168974567'); INSERT INTO cur VALUES (127,8,'Loginprompt','Anjeun kudu boga \'\'cookies\'\' sangkan bisa asup log ka {{SITENAME}}.','',3,'Kandar','20050221094352','sysop',0,0,1,0,0.493950251949905,'20050221094352','79949778905647'); INSERT INTO cur VALUES (128,8,'Userlogin','Nyieun rekening atawa asup log','',3,'Kandar','20050203191853','sysop',0,0,0,0,0.878957013486845,'20050203191853','79949796808146'); INSERT INTO cur VALUES (129,8,'Logout','Kaluar log','',3,'Kandar','20040831025617','sysop',0,0,0,0,0.912934342318153,'20040831025617','79959168974382'); INSERT INTO cur VALUES (130,8,'Userlogout','Kaluar log','',3,'Kandar','20040831025625','sysop',0,0,0,0,0.927800701863878,'20040831025625','79959168974374'); INSERT INTO cur VALUES (131,8,'Notloggedin','Can asup log','',3,'Kandar','20050221094818','sysop',0,0,1,0,0.900200513098576,'20050221094818','79949778905181'); INSERT INTO cur VALUES (132,8,'Createaccount','Jieun rekening anyar','',3,'Kandar','20050203192340','sysop',0,0,0,0,0.717600490634889,'20050203192340','79949796807659'); INSERT INTO cur VALUES (133,8,'Createaccountmail','ku surélék','',3,'Kandar','20040729083806','sysop',0,0,0,0,0.887400944612362,'20040729083806','79959270916193'); INSERT INTO cur VALUES (134,8,'Badretype','Sandi nu diasupkeun teu cocog.','',3,'Kandar','20040729013712','sysop',0,0,0,0,0.28420328189079,'20040729013712','79959270986287'); INSERT INTO cur VALUES (135,8,'Userexists','Ngaran pamaké nu diasupkeun ku anjeun geus aya nu maké. Mangga pilih ngaran nu séjén.','',3,'Kandar','20040810063255','sysop',0,0,0,0,0.758813606350509,'20040810063255','79959189936744'); INSERT INTO cur VALUES (136,8,'Youremail','Surélék anjeun*','',3,'Kandar','20040729021842','sysop',0,0,0,0,0.94145821681382,'20040729021842','79959270978157'); INSERT INTO cur VALUES (137,8,'Yournick','Landihan anjeun (pikeun tawis leungeun)','',3,'Kandar','20040906073258','sysop',0,0,0,0,0.430850295751216,'20040906073258','79959093926741'); INSERT INTO cur VALUES (138,8,'Emailforlost','Widang nu ditandaan béntang (*) sipatna pilihan. Neundeun alamat surélék bisa dimangpaatkeun ku nu séjén pikeun nepungan anjeun ngaliwatan website tanpa kudu mikeun alamat surélék urang ka maranéhna, sarta bisa ogé dipaké pikeun nepikeun sandi anyar mun anjeun poho.

Ngaran asli anjeun, mun anjeun milih nyadiakeun, bakal dipaké pikeun ngararangkénan anjeun ku karya-karya anjeun.','',3,'Kandar','20040802091617','sysop',0,0,0,0,0.329876859048267,'20040802091617','79959197908382'); INSERT INTO cur VALUES (139,8,'Loginerror','Kasalahan asup log','',3,'Kandar','20050221093812','sysop',0,0,1,0,0.35683343872133,'20050221093812','79949778906187'); INSERT INTO cur VALUES (140,8,'Nocookiesnew','Rekening pamaké geus dijieun, tapi anjeun can asup log. Wikipédia maké \'\'cookies\'\' pikeun ngasupkeun log pamaké. Anjeun boga \'\'cookies\'\' nu ditumpurkeun. Mangga fungsikeun, teras asup log migunakeun ngaran pamaké sarta sandi nu anyar.','',3,'Kandar','20050221094943','sysop',0,0,1,0,0.794536647195496,'20050221094943','79949778905056'); INSERT INTO cur VALUES (141,8,'Nocookieslogin','Wikipedia migunakeun \'\'cookies\'\' pikeun ngasupkeun pamaké kana log. Anjeun boga \'\'cookies\'\' nu ditumpurkeun. Mangga pungsikeun sarta cobian deui.','',3,'Kandar','20041006090339','sysop',0,0,0,0,0.902182950547135,'20041006090339','79958993909660'); INSERT INTO cur VALUES (142,8,'Noname','Anjeun teu nuliskeun ngaran pamaké nu sah.','',3,'Kandar','20040812032034','sysop',0,0,0,0,0.127304841882833,'20040812032034','79959187967965'); INSERT INTO cur VALUES (143,8,'Loginsuccesstitle','Asup log geus hasil','',3,'Kandar','20050221094503','sysop',0,0,1,0,0.929975388506404,'20050221094503','79949778905496'); INSERT INTO cur VALUES (144,8,'Loginsuccess','Anjeun ayeuna geus asup log ka Wikipédia salaku \"$1\".','',3,'Kandar','20050221093903','sysop',0,0,1,0,0.267962447617168,'20050221093903','79949778906096'); INSERT INTO cur VALUES (145,8,'Nosuchuser','Teu aya pamaké nu ngaranna \"$1\". Pariksa éjahanana, atawa paké formulir di handap pikeun nyieun rekening pamaké anyar.','',3,'Kandar','20050203192507','sysop',0,0,0,0,0.549886103300272,'20050203192507','79949796807492'); INSERT INTO cur VALUES (146,8,'Wrongpassword','Sandi nu diasupkeun teu cocog. Mangga cobian deui.','',3,'Kandar','20040906073222','sysop',0,0,0,0,0.945543204383499,'20040906073222','79959093926777'); INSERT INTO cur VALUES (147,8,'Mailmypassword','Kirim sandi anyar ngaliwatan surélék','',3,'Kandar','20040728105724','sysop',0,0,0,0,0.0780577427503259,'20040728105724','79959271894275'); INSERT INTO cur VALUES (148,8,'Passwordremindertitle','Pangéling sandi ti Wikipédia','',3,'Kandar','20040803050950','sysop',0,0,0,0,0.553659131334777,'20040803050950','79959196949049'); INSERT INTO cur VALUES (149,8,'Passwordremindertext','Aya (jigana anjeun ti alamat IP $1) nu ménta sangkan dikiriman sandi anyar asup log Wikipédia. Sandi keur pamaké \"$2\" ayeuna nyaéta \"$3\". Anjeun kudu asup log sarta ngarobah sandi anjeun ayeuna.','',3,'Kandar','20050221095149','sysop',0,0,1,0,0.534122459156553,'20050221095149','79949778904850'); INSERT INTO cur VALUES (150,8,'Noemail','Teu aya alamat surélék karékam pikeun \"$1\".','',3,'Kandar','20040728111222','sysop',0,0,0,0,0.00963493251207744,'20040728111222','79959271888777'); INSERT INTO cur VALUES (151,8,'Passwordsent','Sandi anyar geus dikirim ka alamat surélék nu kadaptar pikeun \"$1\". Mangga asup log deui satutasna katarima.','',3,'Kandar','20050221095157','sysop',0,0,1,0,0.445807315824374,'20050221095157','79949778904842'); INSERT INTO cur VALUES (152,8,'Loginend',' ','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.200131812319282,'20041223055408','79958776944591'); INSERT INTO cur VALUES (153,8,'Bold_sample','Téks kandel','',3,'Kandar','20040802074107','sysop',0,0,0,0,0.663237144856935,'20040802074107','79959197925892'); INSERT INTO cur VALUES (154,8,'Bold_tip','Téks kandel','',3,'Kandar','20040802074132','sysop',0,0,0,0,0.715790318060471,'20040802074132','79959197925867'); INSERT INTO cur VALUES (155,8,'Italic_sample','Tulisan déngdék','',3,'Kandar','20040729015125','sysop',0,0,0,0,0.589240186465196,'20040729015125','79959270984874'); INSERT INTO cur VALUES (156,8,'Italic_tip','Tulisan déngdék','',3,'Kandar','20040729015139','sysop',0,0,0,0,0.798830008878214,'20040729015139','79959270984860'); INSERT INTO cur VALUES (157,8,'Link_sample','Judul tumbu','',3,'Kandar','20040802100601','sysop',0,0,0,0,0.226429515729127,'20040802100601','79959197899398'); INSERT INTO cur VALUES (158,8,'Link_tip','Tumbu internal','',3,'Kandar','20040802100614','sysop',0,0,0,0,0.735657582744637,'20040802100614','79959197899385'); INSERT INTO cur VALUES (159,8,'Extlink_sample','Judul tumbu http://www.conto.com','',3,'Kandar','20040802094250','sysop',0,0,0,0,0.99899939726945,'20040802094250','79959197905749'); INSERT INTO cur VALUES (160,8,'Extlink_tip','Tumbu kaluar (inget awalan http://)','',3,'Kandar','20040802094011','sysop',0,0,0,0,0.788024268846982,'20040802094011','79959197905988'); INSERT INTO cur VALUES (161,8,'Headline_sample','Headline text','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.943123183160204,'20041223055407','79958776944592'); INSERT INTO cur VALUES (162,8,'Headline_tip','Level 2 headline','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.351543139993719,'20041223055407','79958776944592'); INSERT INTO cur VALUES (163,8,'Math_sample','Asupkeun rumus di dieu','',3,'Kandar','20040728105639','sysop',0,0,0,0,0.928346181221629,'20040728105639','79959271894360'); INSERT INTO cur VALUES (164,8,'Math_tip','Rumus matematis (LaTeX)','',3,'Kandar','20040729015554','sysop',0,0,0,0,0.587101516860632,'20040729015554','79959270984445'); INSERT INTO cur VALUES (165,8,'Nowiki_sample','Asupkeun téks nu teu diformat di dieu','',3,'Kandar','20050224110402','sysop',0,0,0,0,0.150469071371918,'20050224110402','79949775889597'); INSERT INTO cur VALUES (166,8,'Nowiki_tip','Ignore wiki formatting','',0,'MediaWiki default','20041223055410','sysop',0,0,0,0,0.991040837011338,'20041223055410','79958776944589'); INSERT INTO cur VALUES (167,8,'Image_sample','Conto.jpg','',3,'Kandar','20040802094901','sysop',0,0,0,0,0.503797001674582,'20040802094901','79959197905098'); INSERT INTO cur VALUES (168,8,'Image_tip','Embedded image','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.545862528072542,'20041223055407','79958776944592'); INSERT INTO cur VALUES (169,8,'Media_sample','Example.mp3','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.217921666072609,'20041223055409','79958776944590'); INSERT INTO cur VALUES (170,8,'Media_tip','Tumbu koropak média','',3,'Kandar','20040904051302','sysop',0,0,0,0,0.452020776879062,'20040904051302','79959095948697'); INSERT INTO cur VALUES (171,8,'Sig_tip','Tawis leungeun anjeun tur cap wanci','',3,'Kandar','20050126052456','sysop',0,0,0,0,0.606338916911128,'20050126052456','79949873947543'); INSERT INTO cur VALUES (172,8,'Hr_tip','Garis horizontal (use sparingly)','',3,'Kandar','20040831061917','sysop',0,0,0,0,0.675632284652099,'20040831061917','79959168938082'); INSERT INTO cur VALUES (173,8,'Infobox','Klik kancing pikeun nempo téks conto','',3,'Kandar','20040802095823','sysop',0,0,0,0,0.559144703260758,'20040802095823','79959197904176'); INSERT INTO cur VALUES (174,8,'Summary','Ringkesan','',3,'Kandar','20040729063539','sysop',0,0,0,0,0.768826693081136,'20040729063539','79959270936460'); INSERT INTO cur VALUES (175,8,'Subject','Jejer/Judul','',3,'Kandar','20041231061455','sysop',0,0,0,0,0.16669938635705,'20041231061455','79958768938544'); INSERT INTO cur VALUES (176,8,'Minoredit','Ieu éditan minor','',3,'Kandar','20041229065249','sysop',0,0,0,0,0.527016883275487,'20041229065249','79958770934750'); INSERT INTO cur VALUES (177,8,'Watchthis','Awaskeun kaca ieu','',3,'Kandar','20040729021632','sysop',0,0,0,0,0.134986288039932,'20040729021632','79959270978367'); INSERT INTO cur VALUES (178,8,'Savearticle','Simpen','',3,'Kandar','20040729075931','sysop',0,0,0,0,0.0938808211068444,'20040729075931','79959270924068'); INSERT INTO cur VALUES (179,8,'Preview','Sawangan','',3,'Kandar','20040729015844','sysop',0,0,0,0,0.0644452721480702,'20040729015844','79959270984155'); INSERT INTO cur VALUES (180,8,'Showpreview','Témbongkeun sawangan','',3,'Kandar','20040729020543','sysop',0,0,0,0,0.0405839281534626,'20040729020543','79959270979456'); INSERT INTO cur VALUES (181,8,'Blockedtitle','Pamaké dipeungpeuk','',3,'Kandar','20040810060304','sysop',0,0,0,0,0.00958385505674766,'20040810060304','79959189939695'); INSERT INTO cur VALUES (182,8,'Blockedtext','Ngaran pamaké atawa alamat IP anjeun dipeungpeuk ku $1. Alesanana:
\'\'$2\'\'

Anjeun bisa nepungan $1 atawa salasahiji [[Wikipédia:Kuncén|Kuncén]] séjén pikeun nyawalakeun hal ieu.\n\nCatet yén anjeun teu bisa maké fungsi \"surélékan pamaké ieu\" mun anjeun teu ngadaptarkeun alamat surélék nu sah kana [[Special:Preferences|préferénsi pamaké]] anjeun.\n\nAlamat IP anjeun $3, lampirkeun alamat ieu dina unggal \'\'query\'\' anjeun.','',3,'Kandar','20041122093036','sysop',0,0,0,0,0.926167521556995,'20050203183350','79958877906963'); INSERT INTO cur VALUES (183,8,'Whitelistedittitle','Perlu asup log sangkan bisa ngédit','',3,'Kandar','20050221100009','sysop',0,0,1,0,0.602086073348379,'20050221100009','79949778899990'); INSERT INTO cur VALUES (184,8,'Whitelistedittext','Anjeun kudu asup [[Special:Userlogin|log]] sangkan bisa ngédit.','',3,'Kandar','20040831062806','sysop',0,0,0,0,0.231927832804553,'20040831062806','79959168937193'); INSERT INTO cur VALUES (185,8,'Whitelistreadtitle','Perlu asup log pikeun maca','',3,'Kandar','20050221100113','sysop',0,0,1,0,0.353380974711274,'20050221100113','79949778899886'); INSERT INTO cur VALUES (186,8,'Whitelistreadtext','Anjeun kudu asup \'\'[[Special:Userlogin|log]]\'\' sangkan bisa maca.','',3,'Kandar','20040831063020','sysop',0,0,0,0,0.0711214058763547,'20040831063020','79959168936979'); INSERT INTO cur VALUES (187,8,'Whitelistacctitle','Anjeun teu diwenangkeun nyieun rekening','',3,'Kandar','20050203192244','sysop',0,0,0,0,0.295464135981597,'20050203192244','79949796807755'); INSERT INTO cur VALUES (188,8,'Whitelistacctext','Sangkan diwenangkeun nyieun rekening na wiki ieu, anjeun kudu asup [[Special:Userlogin|log]] sarta boga kawenangan nu cukup.','',3,'Kandar','20050203192241','sysop',0,0,0,0,0.263956493012567,'20050203192241','79949796807758'); INSERT INTO cur VALUES (189,8,'Accmailtitle','Sandi geus dikirim.','',3,'Kandar','20040728103019','sysop',0,0,0,0,0.433390087851686,'20040728103019','79959271896980'); INSERT INTO cur VALUES (190,8,'Accmailtext','Sandi keur \'$1\' geus dikirim ka $2.','',3,'Kandar','20040728103008','sysop',0,0,0,0,0.375080990954378,'20040728103008','79959271896991'); INSERT INTO cur VALUES (191,8,'Newarticle','(Anyar)','',3,'Kandar','20040728110623','sysop',0,0,0,0,0.575234721950474,'20040728110623','79959271889376'); INSERT INTO cur VALUES (192,8,'Newarticletext','Anjeun geus nuturkeun tumbu ka kaca nu can aya.\nPikeun nyieun kaca, mimitian ku ngetik jeroeun kotak di handap \n(tempo [[Wikipédia:Pitulung|kaca pitulung]] pikeun leuwih écés).\nMun anjeun ka dieu teu ngahaja, klik baé tombol \'\'\'back\'\'\' na panyungsi anjeun.','',3,'Kandar','20041030021749','sysop',0,0,0,0,0.750930667622882,'20050303214455','79958969978250'); INSERT INTO cur VALUES (193,8,'Anontalkpagetext','----\'\'Ieu mangrupa kaca sawala pikeun pamaké anonim nu can (henteu) nyieun rekening, kusabab kitu [[alamat IP]] dipaké dina hal ieu pikeun nyirikeun anjeunna. Alamat IP ieu bisa dipaké ku sababaraha urang. Mun anjeun salasahiji pamaké anonim sarta ngarasa aya koméntar nu teu pakait geus ditujukeun ka anjeun, leuwih hadé [[Special:Userlogin|nyieun rekening atawa asup log]] sangkan teu pahili jeung pamaké anonim séjén.\'\'','',3,'Kandar','20050221093642','sysop',0,0,1,0,0.0289492029966313,'20050221093642','79949778906357'); INSERT INTO cur VALUES (194,8,'Noarticletext','(Kiwari can aya téks na kaca ieu)','',3,'Kandar','20040827083430','sysop',0,0,0,0,0.891954042848157,'20040827083430','79959172916569'); INSERT INTO cur VALUES (195,8,'Updated','(Updated)','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.372922635984535,'20041223055413','79958776944586'); INSERT INTO cur VALUES (196,8,'Note','Catetan:','',3,'Kandar','20040915055428','sysop',0,0,0,0,0.18875108211185,'20040915055428','79959084944571'); INSERT INTO cur VALUES (197,8,'Previewnote','Inget yén ieu ukur sawangan, can disimpen!','',3,'Kandar','20040827072024','sysop',0,0,0,0,0.824987533339288,'20040827072024','79959172927975'); INSERT INTO cur VALUES (198,8,'Previewconflict','Sawangan ieu mangrupa eunteung pikeun téks na rohangan ngédit sakumaha bakal katémbong mun ku anjeun disimpen.','',3,'Kandar','20040803060754','sysop',0,0,0,0,0.558684451094535,'20040803060754','79959196939245'); INSERT INTO cur VALUES (199,8,'Editing','Ngédit $1','',3,'Kandar','20040728104328','sysop',0,0,0,0,0.318459686188455,'20040728104328','79959271895671'); INSERT INTO cur VALUES (200,8,'Sectionedit',' (bagian)','',3,'Kandar','20040924072001','sysop',0,0,0,0,0.916245108392318,'20040924072001','79959075927998'); INSERT INTO cur VALUES (201,8,'Commentedit',' (koméntar)','',3,'Kandar','20040924071303','sysop',0,0,0,0,0.625846514129868,'20040924071303','79959075928696'); INSERT INTO cur VALUES (202,8,'Editconflict','Edit conflict: $1','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.380497276206033,'20041223055407','79958776944592'); INSERT INTO cur VALUES (203,8,'Explainconflict','Aya nu geus ngarobah kaca ieu saprak anjeun mimiti ngédit. Téks béh luhur ngandung téks kaca nu aya kiwari, parobahan anjeun ditémbongkeun di béh handap. Anjeun kudu ngagabungkeun parobahan anjeun kana téks nu kiwari.\nNgan téks nu béh luhur nu bakal disimpen nalika anjeun mencét \"Simpen\".\n

','',3,'Kandar','20040802093516','sysop',0,0,0,0,0.0249468693742034,'20040802093516','79959197906483'); INSERT INTO cur VALUES (204,8,'Yourtext','Tulisan anjeun','',3,'Kandar','20040729021936','sysop',0,0,0,0,0.983242548986564,'20040729021936','79959270978063'); INSERT INTO cur VALUES (205,8,'Storedversion','Vérsi nu disimpen','',3,'Kandar','20040924072327','sysop',0,0,0,0,0.841372167543855,'20040924072327','79959075927672'); INSERT INTO cur VALUES (206,8,'Editingold','PERHATOSAN: Anjeun ngédit révisi kadaluwarsa kaca ieu. Mun ku anjeun disimpenIf you save it, any changes made since this revision will be lost.','',3,'Kandar','20040802090023','sysop',0,0,0,0,0.257133221493227,'20040802090023','79959197909976'); INSERT INTO cur VALUES (207,8,'Yourdiff','Béda','',3,'Kandar','20040906073227','sysop',0,0,0,0,0.761549635568214,'20040906073227','79959093926772'); INSERT INTO cur VALUES (208,8,'Copyrightwarning','Perhatikeun yén sadaya sumbangsih ka MediaWiki dianggap medal dina panangtayungan Lisénsi Dokumén Bébas GNU (tempo $1 pikeun jéntréna). Mun anjeun teu miharep tulisan anjeun dirobah sarta disebarkeun deui, ulah dilebetkeun ka dieu.
\nAnjeun ogé jangji yén tulisan ieu dijieun ku sorangan, atawa disalin ti \'\'domain\'\' umum atawa sumberdaya bébas séjénna. ULAH NGALEBETKEUN KARYA NU MIBANDA HAK CIPTA TANPA IDIN!','',3,'Kandar','20050316074906','sysop',0,0,1,0,0.0363485440950361,'20050316074906','79949683925093'); INSERT INTO cur VALUES (209,8,'Longpagewarning','PERHATOSAN: Kaca ieu panjangna $1 kilobytes; sababaraha panyungsi boga masalah dina ngédit kaca nu panjangna nepi ka 32kb. Please consider breaking the page into smaller sections.','',3,'Kandar','20041030021729','sysop',0,0,0,0,0.897093844504183,'20041030021729','79958969978270'); INSERT INTO cur VALUES (210,8,'Readonlywarning','PERHATOSAN: Database dikonci pikeun diropéa, anjeun moal bisa nyimpen éditan anjeun ayeuna. Cobi \'\'cut-n-paste\'\' téksna ka na koropak téks sarta simpen dina waktu séjén.','',3,'Kandar','20040904055952','sysop',0,0,0,0,0.376423620969452,'20040904055952','79959095944047'); INSERT INTO cur VALUES (211,8,'Protectedpagewarning','PERHATOSAN: Kaca ieu dikonci sahingga ngan bisa dirobah ku pamaké nu statusna kuncén. Pastikeun yén anjeun tumut kana [[Wikipedia:Protected_page_guidelines|tungtunan kaca nu dijaga]].','',3,'Kandar','20050221110750','sysop',0,0,1,0,0.190836602068354,'20050221110750','79949778889249'); INSERT INTO cur VALUES (212,8,'Revhistory','Jujutan révisi','',3,'Kandar','20040924071728','sysop',0,0,0,0,0.82491217816706,'20040924071728','79959075928271'); INSERT INTO cur VALUES (213,8,'Nohistory','Teu aya jujutan édit pikeun kaca ieu.','',3,'Kandar','20040827084229','sysop',0,0,0,0,0.552051115363884,'20040827084229','79959172915770'); INSERT INTO cur VALUES (214,8,'Revnotfound','Révisi teu kapanggih','',3,'Kandar','20040924071756','sysop',0,0,0,0,0.285519073051884,'20040924071756','79959075928243'); INSERT INTO cur VALUES (215,8,'Revnotfoundtext','Révisi heubeul kaca nu dipénta ku anjeun teu bisa kapanggih.\nPlease check the URL you used to access this page.','',3,'Kandar','20040924071953','sysop',0,0,0,0,0.771442049901413,'20040924071953','79959075928046'); INSERT INTO cur VALUES (216,8,'Loadhist','Keur ngamuat jujutan kaca','',3,'Kandar','20040728105827','sysop',0,0,0,0,0.000653061085057502,'20040728105827','79959271894172'); INSERT INTO cur VALUES (217,8,'Currentrev','Révisi kiwari','',3,'Kandar','20040729083907','sysop',0,0,0,0,0.688939186454694,'20040729083907','79959270916092'); INSERT INTO cur VALUES (218,8,'Revisionasof','Révisi nurutkeun $1','',3,'Kandar','20040924071742','sysop',0,0,0,0,0.442736779751942,'20040924071742','79959075928257'); INSERT INTO cur VALUES (219,8,'Cur','kiw','',3,'Kandar','20041229060551','sysop',0,0,0,0,0.146866370129275,'20041229060551','79958770939448'); INSERT INTO cur VALUES (220,8,'Next','salajengna','',3,'Kandar','20040827082903','sysop',0,0,0,0,0.406121542124191,'20040827082903','79959172917096'); INSERT INTO cur VALUES (221,8,'Last','ahir','',3,'Kandar','20040924071348','sysop',0,0,0,0,0.590008630966776,'20040924071348','79959075928651'); INSERT INTO cur VALUES (222,8,'Orig','asli','',3,'Kandar','20050126043357','sysop',0,0,0,0,0.731678559194951,'20050126043357','79949873956642'); INSERT INTO cur VALUES (223,8,'Histlegend','Pilihan béda: tandaan wadah buleud vérsina pikeun ngabandingkeun sarta pencét énter atawa tombol di handap.
\nKaterangan: (cur) = bédana jeung vérsi kiwari,\n(last) = bédana jeung vérsi nu harita, M = éditan minor.','',3,'Kandar','20040915054940','sysop',0,0,0,0,0.888366933808072,'20040915054940','79959084945059'); INSERT INTO cur VALUES (224,8,'Difference','(Béda antarrévisi)','',3,'Kandar','20040802085607','sysop',0,0,0,0,0.246799022189154,'20040802085607','79959197914392'); INSERT INTO cur VALUES (225,8,'Loadingrev','ngamuat béda révisi','',3,'Kandar','20041229064215','sysop',0,0,0,0,0.568894340255199,'20041229064215','79958770935784'); INSERT INTO cur VALUES (226,8,'Lineno','Garis $1:','',3,'Kandar','20040802100542','sysop',0,0,0,0,0.104074665442179,'20040802100542','79959197899457'); INSERT INTO cur VALUES (227,8,'Editcurrent','Édit vérsi kiwari kaca ieu','',3,'Kandar','20040802085640','sysop',0,0,0,0,0.81369033717894,'20040802085640','79959197914359'); INSERT INTO cur VALUES (228,8,'Searchresults','Hasil néangan','',3,'Kandar','20040729062606','sysop',0,0,0,0,0.75622772030181,'20040729062606','79959270937393'); INSERT INTO cur VALUES (229,8,'Searchhelppage','Wikipédia:Néangan','',3,'Kandar','20040729020532','sysop',0,0,0,0,0.340067620705876,'20040729020532','79959270979467'); INSERT INTO cur VALUES (230,8,'Searchingwikipedia','Néang Wikipédia','',3,'Kandar','20040729020705','sysop',0,0,0,0,0.431654973357595,'20040729020705','79959270979294'); INSERT INTO cur VALUES (231,8,'Searchresulttext','Pikeun iber nu leuwih lengkep ngeunaan néang di Wikipédia, tempo $1.','',3,'Kandar','20050223043449','sysop',0,0,1,0,0.138072035403989,'20050223043449','79949776956550'); INSERT INTO cur VALUES (232,8,'Searchquery','For query \"$1\"','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.395395287680808,'20041223055412','79958776944587'); INSERT INTO cur VALUES (233,8,'Badquery','Badly formed search query','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.562760362925716,'20041223055405','79958776944594'); INSERT INTO cur VALUES (234,8,'Badquerytext','Kami teu bisa ngolah \'\'query\'\' anjeun, biasana sabab anjeun nyoba néang kecap nu ukur hiji/dua aksara, nu mémang can dirojong; bisa ogé alatan anjeun salah ngetik. Mangga cobian deui.','',3,'Kandar','20041229055138','sysop',0,0,0,0,0.627615982319802,'20041229055138','79958770944861'); INSERT INTO cur VALUES (235,8,'Matchtotals','\'\'Query\'\' \"$1\" cocog jeung $2 judul kaca sarta tulisan na $3 kaca.','',3,'Kandar','20041229065220','sysop',0,0,0,0,0.449798853555507,'20041229065220','79958770934779'); INSERT INTO cur VALUES (236,8,'Nogomatch','Teu aya kaca nu judulna kitu\n\n\nCobaan téang na téks lengkep, atawa nyieun artikel nu judulna kitu atawa mundut dijieunna éta artikel.\n\nMangga sungsi Wikipédia saméméh nyieun artikel anyar, pikeun ngahindarkeun artikel ganda nu ukur béda éjahan/ngaran.\n','',3,'Kandar','20050224102027','sysop',0,0,1,0,0.366146351551773,'20050224102027','79949775897972'); INSERT INTO cur VALUES (237,8,'Titlematches','Judul artikel nu cocog','',3,'Kandar','20040803023323','sysop',0,0,0,0,0.481335227825991,'20040803023323','79959196976676'); INSERT INTO cur VALUES (238,8,'Notitlematches','Teu aya judul kaca nu cocog','',3,'Kandar','20040728112018','sysop',0,0,0,0,0.30823711520828,'20040728112018','79959271887981'); INSERT INTO cur VALUES (239,8,'Textmatches','Téks kaca nu cocog','',3,'Kandar','20040906065633','sysop',0,0,0,0,0.0971799232970736,'20040906065633','79959093934366'); INSERT INTO cur VALUES (240,8,'Notextmatches','Teu aya téks kaca nu cocog','',3,'Kandar','20040827073722','sysop',0,0,0,0,0.561188301594172,'20040827073722','79959172926277'); INSERT INTO cur VALUES (241,8,'Prevn','$1 saméméhna','',3,'Kandar','20040827085547','sysop',0,0,0,0,0.514401768813284,'20040827085547','79959172914452'); INSERT INTO cur VALUES (242,8,'Nextn','$1 salajengna','',3,'Kandar','20040827082927','sysop',0,0,0,0,0.888443970017549,'20040827082927','79959172917072'); INSERT INTO cur VALUES (243,8,'Viewprevnext','Témbongkeun ($1) ($2) ($3).','',3,'Kandar','20040906062426','sysop',0,0,0,0,0.899014574381536,'20040906062426','79959093937573'); INSERT INTO cur VALUES (244,8,'Showingresults','Di handap ieu némbongkeun $1 hasil tina #$2.','',3,'Kandar','20040906070605','sysop',0,0,0,0,0.829740992588681,'20040906070605','79959093929394'); INSERT INTO cur VALUES (245,8,'Showingresultsnum','Di handap ieu némbongkeun $3 hasil tina #$2.','',3,'Kandar','20040906070551','sysop',0,0,0,0,0.451661270532442,'20040906070551','79959093929448'); INSERT INTO cur VALUES (246,8,'Nonefound','Catetan: panéangan nu teu hasil mindeng disababkeun ku néang kecap umum kawas \"ti\" nu teu diasupkeun kana indéks, atawa alatan nangtukeun leuwih ti hiji istilah panéang (ngan kaca-kaca nu ngandung sakabéh istilah panéang nu bakal némbongan).','',3,'Kandar','20040827084544','sysop',0,0,0,0,0.769083405629809,'20040827084544','79959172915455'); INSERT INTO cur VALUES (247,8,'Powersearch','Téang','',3,'Kandar','20040728112738','sysop',0,0,0,0,0.490433247285367,'20040728112738','79959271887261'); INSERT INTO cur VALUES (248,8,'Powersearchtext','Téang na spasi-ngaran:
\n$1
\n$2 Daptarkeun alihan   Téang $3 $9','',3,'Kandar','20040915060207','sysop',0,0,0,0,0.144916050271053,'20040915060207','79959084939792'); INSERT INTO cur VALUES (249,8,'Searchdisabled','

Punten! Néangan téks lengkep di Wikipédia kanggo samentawis ditumpurkeun pikeun alesan kinerja. Jalaran kitu, saheulaanan anjeun bisa nyungsi di Google di handap ieu.\nCatet yén indéxna ngeunaan eusi Wikipédia bisa jadi teu mutahir.

','',3,'Kandar','20050224100952','sysop',0,0,0,0,0.253280540232808,'20050224100952','79949775899047'); INSERT INTO cur VALUES (250,8,'Blanknamespace','(Utama)','',3,'Kandar','20040827075419','sysop',0,0,0,0,0.831654581084526,'20040827075419','79959172924580'); INSERT INTO cur VALUES (251,8,'Preferences','Préferénsi','',3,'Kandar','20040803051004','sysop',0,0,0,0,0.39843131545785,'20040803051004','79959196948995'); INSERT INTO cur VALUES (252,8,'Prefsnologin','Can asup log','',3,'Kandar','20050221095245','sysop',0,0,1,0,0.497192864769318,'20050221095245','79949778904754'); INSERT INTO cur VALUES (253,8,'Prefsnologintext','Anjeun kudu asup log pikeun ngatur préferénsi pamaké.','',3,'Kandar','20040827085452','sysop',0,0,0,0,0.290670408206685,'20040827085452','79959172914547'); INSERT INTO cur VALUES (254,8,'Prefslogintext','Anjeun geus asup log salaku \"$1\". Nomer internal ID anjeun nyaéta $2.\n\nTempo [[Wikipédia:Pitulung préferénsi pamaké]] pikeun pitulung nangtukeun pilihan.','',3,'Kandar','20050221095240','sysop',0,0,1,0,0.961773477459115,'20050221095240','79949778904759'); INSERT INTO cur VALUES (255,8,'Prefsreset','Préferénsi geus disét ulang tina arsip.','',3,'Kandar','20040827085534','sysop',0,0,0,0,0.936856193409167,'20040827085534','79959172914465'); INSERT INTO cur VALUES (256,8,'Qbsettings','Quickbar settings','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.798960565402136,'20041223055411','79958776944588'); INSERT INTO cur VALUES (257,8,'Changepassword','Robah sandi','',3,'Kandar','20040728103805','sysop',0,0,0,0,0.184234277516822,'20040728103805','79959271896194'); INSERT INTO cur VALUES (258,8,'Skin','Kulit','',3,'Kandar','20040729020806','sysop',0,0,0,0,0.524289722111346,'20040729020806','79959270979193'); INSERT INTO cur VALUES (259,8,'Math','Rendering math','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.0687458087399097,'20041223055408','79958776944591'); INSERT INTO cur VALUES (260,8,'Dateformat','Format titimangsa','',3,'Kandar','20040729083931','sysop',0,0,0,0,0.770859908099156,'20040729083931','79959270916068'); INSERT INTO cur VALUES (261,8,'Math_failure','Failed to parse','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.648062145009695,'20041223055409','79958776944590'); INSERT INTO cur VALUES (262,8,'Math_unknown_error','unknown error','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.927731031484651,'20041223055409','79958776944590'); INSERT INTO cur VALUES (263,8,'Math_unknown_function','unknown function ','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.694468753127818,'20041223055409','79958776944590'); INSERT INTO cur VALUES (264,8,'Math_lexing_error','lexing error','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.68915070191878,'20041223055409','79958776944590'); INSERT INTO cur VALUES (265,8,'Math_syntax_error','syntax error','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.36234728094409,'20041223055409','79958776944590'); INSERT INTO cur VALUES (266,8,'Math_image_error','PNG conversion failed; check for correct installation of latex, dvips, gs, and convert','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.744284329697754,'20041223055409','79958776944590'); INSERT INTO cur VALUES (267,8,'Saveprefs','Simpen préferénsi','',3,'Kandar','20040803065336','sysop',0,0,0,0,0.634379836390149,'20040803065336','79959196934663'); INSERT INTO cur VALUES (268,8,'Resetprefs','Sét ulang préferénsi','',3,'Kandar','20040803063808','sysop',0,0,0,0,0.939046223591125,'20040803063808','79959196936191'); INSERT INTO cur VALUES (269,8,'Oldpassword','Sandi heubeul','',3,'Kandar','20040728111618','sysop',0,0,0,0,0.792091639518823,'20040728111618','79959271888381'); INSERT INTO cur VALUES (270,8,'Newpassword','Sandi anyar','',3,'Kandar','20040728110921','sysop',0,0,0,0,0.143319557554386,'20040728110921','79959271889078'); INSERT INTO cur VALUES (271,8,'Retypenew','Ketik ulang sandi','',3,'Kandar','20040803064027','sysop',0,0,0,0,0.340322899949106,'20040803064027','79959196935972'); INSERT INTO cur VALUES (272,8,'Textboxsize','Ukuran kotaktéks','',3,'Kandar','20040729063601','sysop',0,0,0,0,0.271655857816018,'20040729063601','79959270936398'); INSERT INTO cur VALUES (273,8,'Rows','Baris','',3,'Kandar','20040729062537','sysop',0,0,0,0,0.337310619966416,'20040729062537','79959270937462'); INSERT INTO cur VALUES (274,8,'Columns','Kolom','',3,'Kandar','20040729045451','sysop',0,0,0,0,0.871585557117672,'20040729045451','79959270954548'); INSERT INTO cur VALUES (275,8,'Searchresultshead','Aturan hasil néang','',3,'Kandar','20040906064637','sysop',0,0,0,0,0.345995956422757,'20040906064637','79959093935362'); INSERT INTO cur VALUES (276,8,'Resultsperpage','Hits to show per page','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.115223141494415,'20041223055411','79958776944588'); INSERT INTO cur VALUES (277,8,'Contextlines','Lines to show per hit','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.538127868937448,'20041223055406','79958776944593'); INSERT INTO cur VALUES (278,8,'Contextchars','Characters of context per line','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.344969950937638,'20041223055406','79958776944593'); INSERT INTO cur VALUES (279,8,'Stubthreshold','Threshold for stub display','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.110466178609492,'20041223055412','79958776944587'); INSERT INTO cur VALUES (280,8,'Recentchangescount','Jumlah judul na parobahan anyar','',3,'Kandar','20040831091156','sysop',0,0,0,0,0.517421070968193,'20040831091156','79959168908843'); INSERT INTO cur VALUES (281,8,'Savedprefs','Préferénsi anjeun geus disimpen.','',3,'Kandar','20040803065321','sysop',0,0,0,0,0.255706849746133,'20040803065321','79959196934678'); INSERT INTO cur VALUES (282,8,'Timezonetext','Asupkeun sabaraha jam bédana antara wanci di tempat anjeun jeung wanci server (UTC).','',3,'Kandar','20040803023308','sysop',0,0,0,0,0.726271066559731,'20040803023308','79959196976691'); INSERT INTO cur VALUES (283,8,'Localtime','Témbongan wanci lokal','',3,'Kandar','20040827081302','sysop',0,0,0,0,0.864234814293901,'20040827081302','79959172918697'); INSERT INTO cur VALUES (284,8,'Timezoneoffset','Offset','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.142360902523958,'20041223055412','79958776944587'); INSERT INTO cur VALUES (285,8,'Servertime','Waktu server ayeuna','',3,'Kandar','20040729062627','sysop',0,0,0,0,0.119100100471731,'20040729062627','79959270937372'); INSERT INTO cur VALUES (286,8,'Guesstimezone','Eusian ti panyungsi','',3,'Kandar','20041030021434','sysop',0,0,0,0,0.168417825520428,'20041030021434','79958969978565'); INSERT INTO cur VALUES (287,8,'Emailflag','Tumpurkeun surélék ti pamaké séjén','',3,'Kandar','20041006085956','sysop',0,0,0,0,0.48478885692059,'20041006085956','79958993914043'); INSERT INTO cur VALUES (288,8,'Defaultns','Téang ti antara spasingaran ieu dumasar \'\'default\'\':','',3,'Kandar','20040802085105','sysop',0,0,0,0,0.91869083877531,'20040802085105','79959197914894'); INSERT INTO cur VALUES (289,8,'Changes','robahan','',3,'Kandar','20040827080048','sysop',0,0,0,0,0.139087653848424,'20040827080048','79959172919951'); INSERT INTO cur VALUES (290,8,'Recentchanges','Parobahan anyar','',3,'Kandar','20040803031905','sysop',0,0,0,0,0.939365783649837,'20040803031905','79959196968094'); INSERT INTO cur VALUES (291,8,'Recentchangestext','Lacak parobahan ka wiki panganyarna na kaca ieu.','',3,'Kandar','20040803062026','sysop',0,0,0,0,0.279565987437559,'20040803062026','79959196937973'); INSERT INTO cur VALUES (292,8,'Rcloaderr','Ngamuat parobahan anyar','',3,'Kandar','20040803031846','sysop',0,0,0,0,0.579732616971929,'20040803031846','79959196968153'); INSERT INTO cur VALUES (293,8,'Rcnote','Di handap ieu $1 parobahan ahir na $2 poé ieu.','',3,'Kandar','20040902074956','sysop',0,0,0,0,0.0599651532806132,'20040902074956','79959097925043'); INSERT INTO cur VALUES (294,8,'Rcnotefrom','Di handap ieu parobahan saprak $2 (nu ditémbongkeun nepi ka $1).','',3,'Kandar','20040902075358','sysop',0,0,0,0,0.560627946220923,'20040902075358','79959097924641'); INSERT INTO cur VALUES (295,8,'Rclistfrom','Témbongkeun parobahan anyar nepi ka $1','',3,'Kandar','20040907061614','sysop',0,0,0,0,0.623244301996421,'20040907061614','79959092938385'); INSERT INTO cur VALUES (296,8,'Showhideminor','$1 éditan minor | $2 bot | $3 pamaké nu asup log','',3,'Kandar','20050221095259','sysop',0,0,1,0,0.434337702052982,'20050221095259','79949778904740'); INSERT INTO cur VALUES (297,8,'Rclinks','Témbongkeun $1 parobahan ahir dina $2 poé ahir
$3','',3,'Kandar','20050225042226','sysop',0,0,1,0,0.301955635009292,'20050225042226','79949774957773'); INSERT INTO cur VALUES (298,8,'Rchide','na $4 formulir; $1 éditan minor; $2 spasingaran sékundér; $3 éditan multipel.','',3,'Kandar','20040827090342','sysop',0,0,0,0,0.206765099621159,'20040827090342','79959172909657'); INSERT INTO cur VALUES (299,8,'Rcliu','; $1 éditan ti pamaké nu geus asup log','',3,'Kandar','20050221095249','sysop',0,0,1,0,0.127958623811564,'20050221095249','79949778904750'); INSERT INTO cur VALUES (300,8,'Diff','béda','',3,'Kandar','20041229061052','sysop',0,0,0,0,0.0194978509279879,'20041229061052','79958770938947'); INSERT INTO cur VALUES (301,8,'Hist','juj','',3,'Kandar','20041229061608','sysop',0,0,0,0,0.713613413938892,'20041229061608','79958770938391'); INSERT INTO cur VALUES (302,8,'Hide','sumputkeun','',3,'Kandar','20040728104641','sysop',0,0,0,0,0.509573547644144,'20040728104641','79959271895358'); INSERT INTO cur VALUES (303,8,'Show','témbongkeun','',3,'Kandar','20040729020845','sysop',0,0,0,0,0.407027527137685,'20040729020845','79959270979154'); INSERT INTO cur VALUES (304,8,'Tableform','tabel','',3,'Kandar','20040803022728','sysop',0,0,0,0,0.50641702348964,'20040803022728','79959196977271'); INSERT INTO cur VALUES (305,8,'Listform','daptar','',3,'Kandar','20040728105552','sysop',0,0,0,0,0.31100256676879,'20040728105552','79959271894447'); INSERT INTO cur VALUES (306,8,'Nchanges','$1 parobahan','',3,'Kandar','20040728110756','sysop',0,0,0,0,0.0357617941086756,'20040728110756','79959271889243'); INSERT INTO cur VALUES (307,8,'Minoreditletter','m','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.245801300970652,'20041223055409','79958776944590'); INSERT INTO cur VALUES (308,8,'Newpageletter','A','',3,'Kandar','20041229065824','sysop',0,0,0,0,0.12172115326088,'20041229065824','79958770934175'); INSERT INTO cur VALUES (309,8,'Upload','Muatkeun koropak','',3,'Kandar','20040904053305','sysop',0,0,0,0,0.871201894126089,'20040904053305','79959095946694'); INSERT INTO cur VALUES (310,8,'Uploadbtn','Muatkeun koropak','',3,'Kandar','20040904053315','sysop',0,0,0,0,0.99084604158145,'20040904053315','79959095946684'); INSERT INTO cur VALUES (311,8,'Uploadlink','Muat gambar','',3,'Kandar','20040729021553','sysop',0,0,0,0,0.340624556262628,'20040729021553','79959270978446'); INSERT INTO cur VALUES (312,8,'Reupload','Muat ulang','',3,'Kandar','20040803064043','sysop',0,0,0,0,0.730584687302434,'20040803064043','79959196935956'); INSERT INTO cur VALUES (313,8,'Reuploaddesc','Balik ka formulir muatan.','',3,'Kandar','20050224110759','sysop',0,0,1,0,0.63104979845793,'20050224110759','79949775889240'); INSERT INTO cur VALUES (314,8,'Uploadnologin','Can asup log','',3,'Kandar','20050221095613','sysop',0,0,1,0,0.963494961115993,'20050221095613','79949778904386'); INSERT INTO cur VALUES (315,8,'Uploadnologintext','Anjeun kudu [[Special:Userlogin|asup log]] pikeun ngamuat koropak.','',3,'Kandar','20050221095629','sysop',0,0,1,0,0.924325440939819,'20050221095629','79949778904370'); INSERT INTO cur VALUES (316,8,'Uploadfile','Ngamuat gambar, sora, dokumén, jsb.','',3,'Kandar','20040729021536','sysop',0,0,0,0,0.731142352084762,'20040729021536','79959270978463'); INSERT INTO cur VALUES (317,8,'Uploaderror','Kasalahan muat','',3,'Kandar','20041231060221','sysop',0,0,0,0,0.882735468337997,'20041231060221','79958768939778'); INSERT INTO cur VALUES (318,8,'Uploadtext','HEUP! Méméh anjeun ngamuat di dieu, pastikeun yén anjeun geus maca sarta tumut ka [[Special:Image_use_policy|kawijakan maké gambar]].\n

Mun geus aya koropak na wiki nu ngaranna sarua jeung nu disebutkeun ku anjeun, koropak nu geus lila bakal diganti otomatis. Mangka, iwal ti pikeun ngaropéa hiji koropak, tangtu leuwih hadé mun anjeun mariksa heula bisi koropak nu sarupa geus aya.\n

Pikeun némbongkeun atawa néang gambar-gambar nu pernah dimuat saméméhna, mangga lebet ka [[Special:Imagelist|daptar gambar nu dimuat]]. Muatan sarta hapusan kadaptar dina log [[Wikipedia:Upload_log|log muatan]].\n

Paké formulir di handap pikeun ngamuat koropak gambar anyar pikeun ilustrasi kaca anjeun. Na kalolobaan panyungsi, anjeun bakal manggihan tombol \"Sungsi/\'\'Browse\'\'...\", nu bakal nganteur ka dialog muka-koropak nu baku na sistim operasi anjeun. Milih hiji koropak bakal ngeusian ngaran koropakna kana rohangan téks gigireun tombol nu tadi. Anjeun ogé kudu nyontréng kotak nu nandakeun yén anjeun teu ngarumpak hak cipta batur ku dimuatna ieu koropak. Pencét tombol \"Muatkeun/\'\'Upload\'\'\" pikeun ngeréngsékeun muatan. Prosés ieu bisa lila mun anjeun migunakeun sambungan internét nu lambat.\n

Format nu dianjurkeun nyéta JPEG pikeun gambar fotografik, PNG pikeun hasil ngagambar sarta gambar séjénna, sarta OGG pikeun sora. Pilih ngaran koropak nu déskriptif sangkan teu ngalieurkeun. Pikeun ngasupkeun gambarna na kaca séjén, pigunakeun tumbu dina wujud [[Image:file.jpg]] atawa [[Image:file.ogg]] pikeun sora.\n

Catet yén salaku kaca wiki, nu séjén bisa ngarobah atawa ngahapus muatan anjeun mun maranéhna nganggap ieu saluyu jeung kapentingan proyék, sarta anjeun bisa waé dipeungpeuk ti ngamuat koropak mun anjeun ngaruksak/ngaganggu sistim.','',3,'Kandar','20050221095917','sysop',0,0,1,0,0.220250316169346,'20050221095917','79949778904082'); INSERT INTO cur VALUES (319,8,'Uploadlog','log muatan','',3,'Kandar','20050221095606','sysop',0,0,1,0,0.453045206566383,'20050221095606','79949778904393'); INSERT INTO cur VALUES (320,8,'Uploadlogpage','Log_muatan','',3,'Kandar','20040903034103','sysop',0,0,0,0,0.604475115057523,'20040903034103','79959096965896'); INSERT INTO cur VALUES (321,8,'Uploadlogpagetext','Di handap mangrupa daptar muatan koropak nu panganyarna. Titimangsa nu katémbong dumasar titimangsa server (UTC).\n

','',3,'Kandar','20040904053340','sysop',0,0,0,0,0.663239986322112,'20040904053340','79959095946659'); INSERT INTO cur VALUES (322,8,'Filename','Ngaran koropak','',3,'Kandar','20040904051129','sysop',0,0,0,0,0.502774617171636,'20040904051129','79959095948870'); INSERT INTO cur VALUES (323,8,'Filedesc','Ringkesna','',3,'Kandar','20040729051200','sysop',0,0,0,0,0.52415315762549,'20040729051200','79959270948799'); INSERT INTO cur VALUES (324,8,'Filestatus','Status hak cipta','',3,'Kandar','20040729051233','sysop',0,0,0,0,0.112441967346186,'20040729051233','79959270948766'); INSERT INTO cur VALUES (325,8,'Filesource','Sumber','',3,'Kandar','20040729051211','sysop',0,0,0,0,0.989750394588104,'20040729051211','79959270948788'); INSERT INTO cur VALUES (326,8,'Affirmation','Kuring mastikeun yén nu nyepeng hak cipta koropak ieu satuju ngalisénsikeun dina panangtayungan $1.','',3,'Kandar','20040904050848','sysop',0,0,0,0,0.611426101635607,'20040904050848','79959095949151'); INSERT INTO cur VALUES (327,8,'Copyrightpage','Wikipédia:Hak cipta','',3,'Kandar','20040728104232','sysop',0,0,0,0,0.0878793551473686,'20040728104232','79959271895767'); INSERT INTO cur VALUES (328,8,'Copyrightpagename','Hak cipta Wikipédia','',3,'Kandar','20040728104147','sysop',0,0,0,0,0.605118501563667,'20040728104147','79959271895852'); INSERT INTO cur VALUES (329,8,'Uploadedfiles','Koropak nu geus dimuat','',3,'Kandar','20040904053328','sysop',0,0,0,0,0.761954473109873,'20040904053328','79959095946671'); INSERT INTO cur VALUES (330,8,'Noaffirmation','Anjeun kudu mastikeun yén muatan anjeun teu ngarumpak hak cipta mana baé.','',3,'Kandar','20040728111122','sysop',0,0,0,0,0.994416891592012,'20040728111122','79959271888877'); INSERT INTO cur VALUES (331,8,'Ignorewarning','Ignore warning and save file anyway.','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.686221069364083,'20041223055407','79958776944592'); INSERT INTO cur VALUES (332,8,'Minlength','Ngaran gambar sahenteuna kudu tilu aksara.','',3,'Kandar','20040831062106','sysop',0,0,0,0,0.447854702778025,'20040831062106','79959168937893'); INSERT INTO cur VALUES (333,8,'Badfilename','Ngaran gambar geus dirobah jadi \"$1\".','',3,'Kandar','20040729013506','sysop',0,0,0,0,0.180610336531522,'20040729013506','79959270986493'); INSERT INTO cur VALUES (334,8,'Badfiletype','\".$1\" lain format koropak gambar nu dianjurkeun.','',3,'Kandar','20040904050900','sysop',0,0,0,0,0.55948760505718,'20040904050900','79959095949099'); INSERT INTO cur VALUES (335,8,'Largefile','Dianjurkeun sangkan ukuran gambar teu leuwih ti 100k.','',3,'Kandar','20040729015219','sysop',0,0,0,0,0.255607046424977,'20040729015219','79959270984780'); INSERT INTO cur VALUES (336,8,'Successfulupload','Ngamuat geus hasil','',3,'Kandar','20041231061431','sysop',0,0,0,0,0.599572447686989,'20041231061431','79958768938568'); INSERT INTO cur VALUES (337,8,'Fileuploaded','Koropak \"$1\" geus réngsé dimuat. Tuturkeun tumbu ieu: $2 pikeun kaca dadaran sarta iber ngeunaan koropakna, kayaning ti mana asalna, dijieun iraha jeung ku saha, sarta nu séjénna nu anjeun nyaho.','',3,'Kandar','20050223043535','sysop',0,0,1,0,0.231041129893662,'20050223043535','79949776956464'); INSERT INTO cur VALUES (338,8,'Uploadwarning','Pépéling ngamuat','',3,'Kandar','20050224112201','sysop',0,0,1,0,0.356488337140985,'20050224112201','79949775887798'); INSERT INTO cur VALUES (339,8,'Savefile','Simpen koropak','',3,'Kandar','20040904053258','sysop',0,0,0,0,0.0893183267575859,'20040904053258','79959095946741'); INSERT INTO cur VALUES (340,8,'Uploadedimage','\"$1\" geus dimuat','',3,'Kandar','20041231060239','sysop',0,0,0,0,0.377126653098619,'20041231060239','79958768939760'); INSERT INTO cur VALUES (341,8,'Uploaddisabled','Punten, ngamuat ayeuna ditumpurkeun.','',3,'Kandar','20041006090542','sysop',0,0,0,0,0.617678315953983,'20041006090542','79958993909457'); INSERT INTO cur VALUES (342,8,'Imagelist','Daptar gambar','',3,'Kandar','20040728104852','sysop',0,0,0,0,0.957011651207704,'20040728104852','79959271895147'); INSERT INTO cur VALUES (343,8,'Imagelisttext','Di handap ieu daptar $1 gambar nu disusun dumasar $2.','',3,'Kandar','20040802094941','sysop',0,0,0,0,0.932023338910214,'20040802094941','79959197905058'); INSERT INTO cur VALUES (344,8,'Getimagelist','fetching image list','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.789081771661604,'20041223055407','79958776944592'); INSERT INTO cur VALUES (345,8,'Ilshowmatch','Témbongkeun sakabéh gambar nu ngaranna cocog','',3,'Kandar','20040729060045','sysop',0,0,0,0,0.149338872311021,'20040729060045','79959270939954'); INSERT INTO cur VALUES (346,8,'Ilsubmit','Téang','',3,'Kandar','20040728104836','sysop',0,0,0,0,0.37944907730394,'20040728104836','79959271895163'); INSERT INTO cur VALUES (347,8,'Showlast','Témbongkeun $1 gambar ahir dumasar $2.','',3,'Kandar','20040906064604','sysop',0,0,0,0,0.44922880032028,'20040906064604','79959093935395'); INSERT INTO cur VALUES (348,8,'All','sadaya','',3,'Kandar','20040729081309','sysop',0,0,0,0,0.107796800423224,'20040729081309','79959270918690'); INSERT INTO cur VALUES (349,8,'Byname','dumasar ngaran','',3,'Kandar','20040728103842','sysop',0,0,0,0,0.191297631888928,'20040728103842','79959271896157'); INSERT INTO cur VALUES (350,8,'Bydate','dumasar titimangsa','',3,'Kandar','20040729075251','sysop',0,0,0,0,0.63309778890861,'20040729075251','79959270924748'); INSERT INTO cur VALUES (351,8,'Bysize','dumasar ukuran','',3,'Kandar','20040728103811','sysop',0,0,0,0,0.591596079609912,'20040728103811','79959271896188'); INSERT INTO cur VALUES (352,8,'Imgdelete','hap','',3,'Kandar','20041229063553','sysop',0,0,0,0,0.058687062057375,'20041229063553','79958770936446'); INSERT INTO cur VALUES (353,8,'Imgdesc','dad','',3,'Kandar','20041229063616','sysop',0,0,0,0,0.518647102190784,'20041229063616','79958770936383'); INSERT INTO cur VALUES (354,8,'Imglegend','Katerangan: (desc) = témbongkeun/édit dadaran gambar.','',3,'Kandar','20040802095513','sysop',0,0,0,0,0.417174355515441,'20040802095513','79959197904486'); INSERT INTO cur VALUES (355,8,'Imghistory','Jujutan gambar','',3,'Kandar','20040728105125','sysop',0,0,0,0,0.529930501738498,'20040728105125','79959271894874'); INSERT INTO cur VALUES (356,8,'Revertimg','rev','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.398129472879813,'20041223055411','79958776944588'); INSERT INTO cur VALUES (357,8,'Deleteimg','hap','',3,'Kandar','20041229061024','sysop',0,0,0,0,0.400855889917217,'20041229061024','79958770938975'); INSERT INTO cur VALUES (358,8,'Imghistlegend','Katerangan: (cur) = ieu salaku gambar kiwari, (del) = hapus vérsi heubeul ieu, (rev) = balikkeun ka vérsi heubeul ieu.\n
Klik na titimangsa pikeun nempo gambar nu dimuat poé éta.','',3,'Kandar','20040802095447','sysop',0,0,0,0,0.80989106168029,'20040802095447','79959197904552'); INSERT INTO cur VALUES (359,8,'Imagelinks','Tumbu gambar','',3,'Kandar','20040728104844','sysop',0,0,0,0,0.846887669383444,'20040728104844','79959271895155'); INSERT INTO cur VALUES (360,8,'Linkstoimage','Kaca di handap numbu ka gambar ieu:','',3,'Kandar','20040729015316','sysop',0,0,0,0,0.804765192609993,'20040729015316','79959270984683'); INSERT INTO cur VALUES (361,8,'Nolinkstoimage','Teu aya kaca nu numbu ka gambar ieu.','',3,'Kandar','20040728111327','sysop',0,0,0,0,0.483162985633279,'20040728111327','79959271888672'); INSERT INTO cur VALUES (362,8,'Statistics','Statistik','',3,'Kandar','20040729021037','sysop',0,0,0,0,0.00151938107006194,'20040729021037','79959270978962'); INSERT INTO cur VALUES (363,8,'Sitestats','Statistik situs','',3,'Kandar','20040906070646','sysop',0,0,0,0,0.558107979184117,'20040906070646','79959093929353'); INSERT INTO cur VALUES (364,8,'Userstats','Statistik pamaké','',3,'Kandar','20040810065146','sysop',0,0,0,0,0.785981783444045,'20040810065146','79959189934853'); INSERT INTO cur VALUES (365,8,'Sitestatstext','Jumlah-jamléh aya \'\'\'$1\'\'\' kaca na database, kaasup kaca \"omongan\", kaca-kaca ngeunaan MédiaWiki, kaca \"tukung\", alihan, sarta nu séjénna nu meureun teu kaasup artikel. Lian ti nu éta, aya \'\'\'$2\'\'\' kaca nu dianggap artikel nu bener.\n\njumlah-jamléh geus aya \'\'\'$3\'\'\' kaca ulasan sarta \'\'\'$4\'\'\' éditan ti saprak Wiki ieu ngadeg. Jadi hartina aya rata-rata \'\'\'$5\'\'\' éditan per kaca sarta \'\'\'$6\'\'\' ulasan per édit.','',3,'Kandar','20040915062822','sysop',0,0,0,0,0.255585010401518,'20040915062822','79959084937177'); INSERT INTO cur VALUES (366,8,'Userstatstext','Aya \'\'\'$1\'\'\' pamaké nu kadaptar.\n\'\'\'$2\'\'\' di antarana kuncén (tempo $3).','',3,'Kandar','20041122093302','sysop',0,0,0,0,0.919979732409101,'20041122093302','79958877906697'); INSERT INTO cur VALUES (367,8,'Maintenance','Kaca pamiaraan','',3,'Kandar','20040827081329','sysop',0,0,0,0,0.833143661574594,'20040827081329','79959172918670'); INSERT INTO cur VALUES (368,8,'Maintnancepagetext','Kaca ieu ngawengku sababaraha parabot praktis pikeun pamiaraan sapopoé. Sababaraha fungsina dimaksudkeun pikeun neken database, jadi punten ulah dimuat ulang (reload) unggal réngsé menerkeun \'\'item\'\' nu dikoréksi ;-)','',3,'Kandar','20040827081655','sysop',0,0,0,0,0.405779141379315,'20040827081655','79959172918344'); INSERT INTO cur VALUES (369,8,'Maintenancebacklink','Balik ka kaca pamiaraan','',3,'Kandar','20040827081340','sysop',0,0,0,0,0.529464752906435,'20040827081340','79959172918659'); INSERT INTO cur VALUES (370,8,'Disambiguations','Disambiguation pages','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.429986371127876,'20041223055406','79958776944593'); INSERT INTO cur VALUES (371,8,'Disambiguationspage','Project:Links_to_disambiguating_pages','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.56153762765372,'20041223055407','79958776944592'); INSERT INTO cur VALUES (372,8,'Disambiguationstext','The following pages link to a disambiguation page. They should link to the appropriate topic instead.
A page is treated as dismbiguation if it is linked from $1.
Links from other namespaces are not listed here.','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.517729055618615,'20041223055407','79958776944592'); INSERT INTO cur VALUES (373,8,'Doubleredirects','Alihan ganda','',3,'Kandar','20041229061102','sysop',0,0,0,0,0.904032425865561,'20041229061102','79958770938897'); INSERT INTO cur VALUES (374,8,'Doubleredirectstext','Attention: This list may contain false positives. That usually means there is additional text with links below the first #REDIRECT.
\nEach row contains links to the first and second redirect, as well as the first line of the second redirect text, usually giving the \"real\" target page, which the first redirect should point to.','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.966974993205606,'20041223055407','79958776944592'); INSERT INTO cur VALUES (375,8,'Brokenredirects','Alihan buntu','',3,'Kandar','20041229055738','sysop',0,0,0,0,0.122777719164991,'20041229055738','79958770944261'); INSERT INTO cur VALUES (376,8,'Brokenredirectstext','Alihan di handap numbu ka kaca nu teu aya.','',3,'Kandar','20041229055711','sysop',0,0,0,0,0.712963646941784,'20041229055711','79958770944288'); INSERT INTO cur VALUES (377,8,'Selflinks','Pages with Self Links','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.196485107947593,'20041223055412','79958776944587'); INSERT INTO cur VALUES (378,8,'Selflinkstext','Kaca-kaca di handap ieu ngandung tumbu ka kacana sorangan, nu teu sakuduna.','',3,'Kandar','20050224111007','sysop',0,0,1,0,0.843534629646255,'20050224111007','79949775888992'); INSERT INTO cur VALUES (379,8,'Mispeelings','Kaca nu ngandung salah éjah','',3,'Kandar','20041229065304','sysop',0,0,0,0,0.628217855122143,'20041229065304','79958770934695'); INSERT INTO cur VALUES (380,8,'Mispeelingstext','Kaca di handap ieu ngandung salah éjah ilahar nu didaptarkeun na $1. Éjahan nu bener meureun geus disadiakeun (kawas kieu).','',3,'Kandar','20040831062236','sysop',0,0,0,0,0.610485417405595,'20040831062236','79959168937763'); INSERT INTO cur VALUES (381,8,'Mispeelingspage','Daptar salah éjah nu ilahar','',3,'Kandar','20041229065324','sysop',0,0,0,0,0.167773552395192,'20041229065324','79958770934675'); INSERT INTO cur VALUES (382,8,'Missinglanguagelinks','Tumbu Basa Leungit','',3,'Kandar','20040827082550','sysop',0,0,0,0,0.00741154049282106,'20040827082550','79959172917449'); INSERT INTO cur VALUES (383,8,'Missinglanguagelinksbutton','Téangan tumbu basa nu leungit pikeun','',3,'Kandar','20040827082613','sysop',0,0,0,0,0.533737076012173,'20040827082613','79959172917386'); INSERT INTO cur VALUES (384,8,'Missinglanguagelinkstext','Kaca ieu teu numbu ka baturna na $1. Alihan jeung subkaca henteu ditémbongkeun.','',3,'Kandar','20040915060013','sysop',0,0,0,0,0.646450789316046,'20040915060013','79959084939986'); INSERT INTO cur VALUES (385,8,'Orphans','Kaca nunggelis','',3,'Kandar','20040827073450','sysop',0,0,0,0,0.631042749277356,'20040827073450','79959172926549'); INSERT INTO cur VALUES (386,8,'Lonelypages','Kaca-kaca nunggelis','',3,'Kandar','20040831061930','sysop',0,0,0,0,0.215861409172287,'20040831061930','79959168938069'); INSERT INTO cur VALUES (387,8,'Unusedimages','Gambar-gambar nu teu kapaké','',3,'Kandar','20040831111325','sysop',0,0,0,0,0.186178828763011,'20040831111325','79959168888674'); INSERT INTO cur VALUES (388,8,'Popularpages','Kaca-kaca kawentar','',3,'Kandar','20040827085041','sysop',0,0,0,0,0.283309947031839,'20040827085041','79959172914958'); INSERT INTO cur VALUES (389,8,'Nviews','$1 témbongan','',3,'Kandar','20050126043349','sysop',0,0,0,0,0.858013279603807,'20050126043349','79949873956650'); INSERT INTO cur VALUES (390,8,'Wantedpages','Kaca nu dipikabutuh','',3,'Kandar','20040906095007','sysop',0,0,0,0,0.440136587657162,'20040906095007','79959093904992'); INSERT INTO cur VALUES (391,8,'Nlinks','$1 tumbu','',3,'Kandar','20040728111041','sysop',0,0,0,0,0.626643130208033,'20040728111041','79959271888958'); INSERT INTO cur VALUES (392,8,'Allpages','Sadaya kaca','',3,'Kandar','20040729045023','sysop',0,0,0,0,0.812805918802326,'20040729045023','79959270954976'); INSERT INTO cur VALUES (393,8,'Randompage','Kaca acak','',3,'Kandar','20040729015843','sysop',0,0,0,0,0.184100234121178,'20040729015843','79959270984156'); INSERT INTO cur VALUES (394,8,'Shortpages','Kaca-kaca parondok','',3,'Kandar','20040907085251','sysop',0,0,0,0,0.482083444932553,'20040907085251','79959092914748'); INSERT INTO cur VALUES (395,8,'Longpages','Kaca-kaca paranjang','',3,'Kandar','20040831061942','sysop',0,0,0,0,0.858116553032879,'20040831061942','79959168938057'); INSERT INTO cur VALUES (396,8,'Deadendpages','Kaca buntu','',3,'Kandar','20040802075605','sysop',0,0,0,0,0.844332461100381,'20040802075605','79959197924394'); INSERT INTO cur VALUES (397,8,'Listusers','Daptar pamaké','',3,'Kandar','20040810060800','sysop',0,0,0,0,0.647312677136914,'20040810060800','79959189939199'); INSERT INTO cur VALUES (398,8,'Specialpages','Kaca husus','',3,'Kandar','20040729020723','sysop',0,0,0,0,0.703566033117069,'20040729020723','79959270979276'); INSERT INTO cur VALUES (399,8,'Spheading','Kaca husus pikeun sadaya pamaké','',3,'Kandar','20040810063044','sysop',0,0,0,0,0.575892164908249,'20040810063044','79959189936955'); INSERT INTO cur VALUES (400,8,'Sysopspheading','Ngan keur sysop','',3,'Kandar','20040729021053','sysop',0,0,0,0,0.768762755923683,'20040729021053','79959270978946'); INSERT INTO cur VALUES (401,8,'Developerspheading','Pikeun developer wungkul','',3,'Kandar','20040802085545','sysop',0,0,0,0,0.116137315627315,'20040802085545','79959197914454'); INSERT INTO cur VALUES (402,8,'Protectpage','Konci kaca','',3,'Kandar','20050221110808','sysop',0,0,1,0,0.274398341099171,'20050221110808','79949778889191'); INSERT INTO cur VALUES (403,8,'Recentchangeslinked','Parobahan nu patali','',3,'Kandar','20040729020820','sysop',0,0,0,0,0.0235797893475553,'20040729020820','79959270979179'); INSERT INTO cur VALUES (404,8,'Rclsub','(ka kaca nu numbu ti \"$1\")','',3,'Kandar','20040902075223','sysop',0,0,0,0,0.294703954173908,'20040902075223','79959097924776'); INSERT INTO cur VALUES (405,8,'Debug','Debug','',0,'MediaWiki default','20041223055406','sysop',0,0,0,0,0.402780433560517,'20041223055406','79958776944593'); INSERT INTO cur VALUES (406,8,'Newpages','Kaca anyar','',3,'Kandar','20040728110916','sysop',0,0,0,0,0.129790336014508,'20040728110916','79959271889083'); INSERT INTO cur VALUES (407,8,'Ancientpages','Kaca pangheubeulna','',3,'Kandar','20040729012449','sysop',0,0,0,0,0.440610410124632,'20040729012449','79959270987550'); INSERT INTO cur VALUES (408,8,'Intl','Tumbu antarbasa','',3,'Kandar','20040728105130','sysop',0,0,0,0,0.813681073313282,'20040728105130','79959271894869'); INSERT INTO cur VALUES (409,8,'Movethispage','Pindahkeun kaca ieu','',3,'Kandar','20040728110448','sysop',0,0,0,0,0.746574166926159,'20040728110448','79959271889551'); INSERT INTO cur VALUES (410,8,'Unusedimagestext','

Please note that other web sites may link to an image with\na direct URL, and so may still be listed here despite being\nin active use.','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.291827645424593,'20041223055413','79958776944586'); INSERT INTO cur VALUES (411,8,'Booksources','Sumber buku','',3,'Kandar','20040802074131','sysop',0,0,0,0,0.219415757078133,'20040802074131','79959197925868'); INSERT INTO cur VALUES (412,8,'Booksourcetext','Di handap ieu daptar tumbu ka situs séjén nu ngajual buku anyar tur urut, sarta bisa jadi boga iber ngeunaan buku nu ditéang. Wikipédia teu aya patalina jeung salasahiji bisnis ieu, sarta daptar ieu ulah dianggap salaku iklan.','',3,'Kandar','20050223043250','sysop',0,0,1,0,0.221595879850533,'20050223043250','79949776956749'); INSERT INTO cur VALUES (413,8,'Alphaindexline','$1 ka $2','',3,'Kandar','20040729081323','sysop',0,0,0,0,0.449732158751909,'20040729081323','79959270918676'); INSERT INTO cur VALUES (414,8,'Mailnologin','Euweuh alamat ngirim','',3,'Kandar','20040924071405','sysop',0,0,0,0,0.583873184941591,'20040924071405','79959075928594'); INSERT INTO cur VALUES (415,8,'Mailnologintext','Anjeun kudu [[Special:Userlogin|asup log]] sarta boga alamat surélék nu sah na [[Special:Preferences|préferénsi]] anjeun sangkan bisa nyurélékan pamaké séjén.','',3,'Kandar','20050221094825','sysop',0,0,1,0,0.570169479185873,'20050221094825','79949778905174'); INSERT INTO cur VALUES (416,8,'Emailuser','Surélékan pamaké ieu','',3,'Kandar','20040810060712','sysop',0,0,0,0,0.099227871838238,'20040810060712','79959189939287'); INSERT INTO cur VALUES (417,8,'Emailpage','Surélékan pamaké','',3,'Kandar','20040810060509','sysop',0,0,0,0,0.785630952367215,'20040810060509','79959189939490'); INSERT INTO cur VALUES (418,8,'Emailpagetext','Mun pamaké ieu ngasupkeun alamat surélék nu sah na préferénsi pamakéna, formulir di handap bakal ngirimkeun hiji pesen. Alamat surélék nu ku anjeun diasupkeun kana préferénsi pamaké anjeun bakal katémbong salaku alamat \"Ti\" surélékna, sahingga nu dituju bisa ngabales.','',3,'Kandar','20040812031925','sysop',0,0,0,0,0.630471177055008,'20040812031925','79959187968074'); INSERT INTO cur VALUES (419,8,'Noemailtitle','Teu aya alamat surélék','',3,'Kandar','20040728111140','sysop',0,0,0,0,0.795463058907039,'20040728111140','79959271888859'); INSERT INTO cur VALUES (420,8,'Noemailtext','Pamaké ieu teu méré alamat surélék nu sah atawa milih teu narima surélék ti pamaké séjén.','',3,'Kandar','20040812032024','sysop',0,0,0,0,0.0859017941038141,'20040812032024','79959187967975'); INSERT INTO cur VALUES (421,8,'Emailfrom','Ti','',3,'Kandar','20040728104335','sysop',0,0,0,0,0.0431198245315997,'20040728104335','79959271895664'); INSERT INTO cur VALUES (422,8,'Emailto','Ka','',3,'Kandar','20040802093033','sysop',0,0,0,0,0.957893771080201,'20040802093033','79959197906966'); INSERT INTO cur VALUES (423,8,'Emailsubject','Ngeunaan','',3,'Kandar','20040802090549','sysop',0,0,0,0,0.660109412539852,'20040802090549','79959197909450'); INSERT INTO cur VALUES (424,8,'Emailmessage','Pesen','',3,'Kandar','20040728104345','sysop',0,0,0,0,0.426865780192302,'20040728104345','79959271895654'); INSERT INTO cur VALUES (425,8,'Emailsend','Kirim','',3,'Kandar','20040802090502','sysop',0,0,0,0,0.1540006940756,'20040802090502','79959197909497'); INSERT INTO cur VALUES (426,8,'Emailsent','Surélék geus dikirim','',3,'Kandar','20040802090512','sysop',0,0,0,0,0.489406160534738,'20040802090512','79959197909487'); INSERT INTO cur VALUES (427,8,'Emailsenttext','Pesen surélék anjeun geus dikirim.','',3,'Kandar','20040802090531','sysop',0,0,0,0,0.985028751180534,'20040802090531','79959197909468'); INSERT INTO cur VALUES (428,8,'Watchlist','Awaskeuneun','',3,'Kandar','20040729021628','sysop',0,0,0,0,0.456925305032102,'20040729021628','79959270978371'); INSERT INTO cur VALUES (429,8,'Watchlistsub','(pikeun pamaké \"$1\")','',3,'Kandar','20040810065246','sysop',0,0,0,0,0.329540302352552,'20040810065246','79959189934753'); INSERT INTO cur VALUES (430,8,'Nowatchlist','Anjeun teu boga awaskeuneun.','',3,'Kandar','20040831062524','sysop',0,0,0,0,0.276925627400098,'20040831062524','79959168937475'); INSERT INTO cur VALUES (431,8,'Watchnologin','Can asup log','',3,'Kandar','20050221095958','sysop',0,0,1,0,0.39600726067648,'20050221095958','79949778904041'); INSERT INTO cur VALUES (432,8,'Watchnologintext','Anjeun kudu [[Special:Userlogin|asup log]] pikeun ngarobah awaskeuneun.','',3,'Kandar','20050221100049','sysop',0,0,1,0,0.149259451915752,'20050221100049','79949778899950'); INSERT INTO cur VALUES (433,8,'Addedwatch','Geus ditambahkeun ka awaskeuneun','',3,'Kandar','20040728103108','sysop',0,0,0,0,0.558275508282963,'20040728103108','79959271896891'); INSERT INTO cur VALUES (434,8,'Addedwatchtext','Kaca \"$1\" geus ditambahkeun ka [[Special:Watchlist|awaskeuneun]] anjeun.\nParobahan jaga kana kaca ieu katut kaca Omonganana bakal dibéréndélkeun di dinya, sarta kacana bakal katémbong \'\'\'dikandelan\'\'\' dina [[Special:Recentchanges|daptar parobahan anyar]] sangkan leuwih gampang nyokotna.\n\n

Mun jaga anjeun moal deui ngawaskeun parobahan na kaca éta, klik tumbu \"Eureun ngawaskeun\" na lajursisi.','',3,'Kandar','20040810065832','sysop',0,0,0,0,0.343599216401204,'20040810065832','79959189934167'); INSERT INTO cur VALUES (435,8,'Removedwatch','Dikaluarkeun ti awaskeuneun','',3,'Kandar','20040803063950','sysop',0,0,0,0,0.0431695878907755,'20040803063950','79959196936049'); INSERT INTO cur VALUES (436,8,'Removedwatchtext','Kaca \"$1\" geus dikaluarkeun ti awaskeuneun anjeun.','',3,'Kandar','20040803063835','sysop',0,0,0,0,0.185050320983911,'20040803063835','79959196936164'); INSERT INTO cur VALUES (437,8,'Watchthispage','Awaskeun kaca ieu','',3,'Kandar','20040831062613','sysop',0,0,0,0,0.795742871980875,'20040831062613','79959168937386'); INSERT INTO cur VALUES (438,8,'Unwatchthispage','Eureun ngawaskeun','',3,'Kandar','20040729021513','sysop',0,0,0,0,0.423563427686285,'20040729021513','79959270978486'); INSERT INTO cur VALUES (439,8,'Notanarticle','Sanés kaca eusi','',3,'Kandar','20040915055418','sysop',0,0,0,0,0.730588553222444,'20040915055418','79959084944581'); INSERT INTO cur VALUES (440,8,'Watchnochange','Sadaya awaseun anjeun taya nu diédit dina jangka wanci nu ditémbongkeun.','',3,'Kandar','20041231040522','sysop',0,0,0,0,0.382252513787013,'20041231040522','79958768959477'); INSERT INTO cur VALUES (441,8,'Watchdetails','($1 kaca diawaskeun, teu kaasup kaca omongan; jumlah-jamléh $2 kaca diédit saprak cutoff; $3...\ntémbongkeun jeung édit daptar lengkepna.)','',3,'Kandar','20041231040712','sysop',0,0,0,0,0.719496940001377,'20041231040712','79958768959287'); INSERT INTO cur VALUES (442,8,'Watchmethod-recent','mariksa parobahan anyar na kaca nu diawaskeun','',3,'Kandar','20040906073159','sysop',0,0,0,0,0.45072718937949,'20040906073159','79959093926840'); INSERT INTO cur VALUES (443,8,'Watchmethod-list','mariksa parobahan anyar na kaca nu diawaskeun','',3,'Kandar','20040906073151','sysop',0,0,0,0,0.0951451576269652,'20040906073151','79959093926848'); INSERT INTO cur VALUES (444,8,'Removechecked','Kaluarkeun nu dicontang tina awaskeuneun','',3,'Kandar','20050126044000','sysop',0,0,0,0,0.123544250730001,'20050126044000','79949873955999'); INSERT INTO cur VALUES (445,8,'Watchlistcontains','Anjeun ngawaskeun $1 kaca.','',3,'Kandar','20040906073042','sysop',0,0,0,0,0.332285811502753,'20040906073042','79959093926957'); INSERT INTO cur VALUES (446,8,'Watcheditlist','Ieu daptar nurutkeun abjad kaca-kaca awaskeuneun anjeun. Contréng kotak kaca nu teu moal deui diawaskeun, teras klik tombol \'piceun nu dicontréng\' na dadasar layar.','',3,'Kandar','20040906073013','sysop',0,0,0,0,0.290796336057406,'20040906073013','79959093926986'); INSERT INTO cur VALUES (447,8,'Removingchecked','Removing requested items from watchlist...','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.457124276512418,'20041223055411','79958776944588'); INSERT INTO cur VALUES (448,8,'Couldntremove','Teu bisa ngahapus \'$1\'...','',3,'Kandar','20041229060521','sysop',0,0,0,0,0.413232405123517,'20041229060521','79958770939478'); INSERT INTO cur VALUES (449,8,'Iteminvalidname','Masalah dina \'$1\', ngaran teu bener...','',3,'Kandar','20041229063926','sysop',0,0,0,0,0.694789226813977,'20041229063926','79958770936073'); INSERT INTO cur VALUES (450,8,'Wlnote','Di handap ieu mangrupa $1 robahan ahir salila $2 jam.','',3,'Kandar','20040831063129','sysop',0,0,0,0,0.234248949432977,'20040831063129','79959168936870'); INSERT INTO cur VALUES (451,8,'Wlshowlast','Témbongkeun $1 jam $2 poé $3 ahir','',3,'Kandar','20040831063244','sysop',0,0,0,0,0.0868770974566015,'20040831063244','79959168936755'); INSERT INTO cur VALUES (452,8,'Wlsaved','Ieu mangrupa vérsi simpenan awaskeuneun anjeun.','',3,'Kandar','20040831063159','sysop',0,0,0,0,0.73163866971772,'20040831063159','79959168936840'); INSERT INTO cur VALUES (453,8,'Deletepage','Hapus kaca','',3,'Kandar','20040802085020','sysop',0,0,0,0,0.397562086952442,'20040802085020','79959197914979'); INSERT INTO cur VALUES (454,8,'Confirm','Konfirmasi','',3,'Kandar','20040827080143','sysop',0,0,0,0,0.792894456342696,'20040827080143','79959172919856'); INSERT INTO cur VALUES (455,8,'Excontent','eusina nu heubeul:','',3,'Kandar','20040802093222','sysop',0,0,0,0,0.771786051589796,'20040802093222','79959197906777'); INSERT INTO cur VALUES (456,8,'Exbeforeblank','eusi méméh dikosongkeun nyéta:','',3,'Kandar','20040802093209','sysop',0,0,0,0,0.48024691965454,'20040802093209','79959197906790'); INSERT INTO cur VALUES (457,8,'Exblank','kaca ieu kosong','',3,'Kandar','20040802093217','sysop',0,0,0,0,0.0858764742369545,'20040802093217','79959197906782'); INSERT INTO cur VALUES (458,8,'Confirmdelete','Konfirmasi ngahapus','',3,'Kandar','20040827080253','sysop',0,0,0,0,0.988641642954798,'20040827080253','79959172919746'); INSERT INTO cur VALUES (459,8,'Deletesub','(Ngahapus \"$1\")','',3,'Kandar','20040802085025','sysop',0,0,0,0,0.685578822796772,'20040802085025','79959197914974'); INSERT INTO cur VALUES (460,8,'Historywarning','Perhatosan: Kaca nu rék dihapus mibanda jujutan:','',3,'Kandar','20040729051359','sysop',0,0,0,0,0.461969215853111,'20040729051359','79959270948640'); INSERT INTO cur VALUES (461,8,'Confirmdeletetext','Anjeun rék ngahapus hiji kaca atawa gambar katut jujutanana tina database, mangga yakinkeun yén anjeun mémang niat midamel ieu, yén anjeun ngartos kana sagala konsékuénsina, sarta yén anjeun ngalakukeun ieu saluyu jeung [[Wikipédia:Kawijakan|kawijakan Wikipédia]].','',3,'Kandar','20040831060945','sysop',0,0,0,0,0.253109641608884,'20040831060945','79959168939054'); INSERT INTO cur VALUES (462,8,'Confirmcheck','Leres pisan, kuring hayang ngahapus ieu.','',3,'Kandar','20040827080234','sysop',0,0,0,0,0.879640591218733,'20040827080234','79959172919765'); INSERT INTO cur VALUES (463,8,'Actioncomplete','Peta geus réngsé','',3,'Kandar','20040728103044','sysop',0,0,0,0,0.638874062000657,'20040728103044','79959271896955'); INSERT INTO cur VALUES (464,8,'Deletedtext','\"$1\" geus dihapus. Tempo $2 pikeun rékaman hapusan anyaran ieu.','',3,'Kandar','20040729084034','sysop',0,0,0,0,0.555448567080729,'20040729084034','79959270915965'); INSERT INTO cur VALUES (465,8,'Deletedarticle','ngahapus \"$1\"','',3,'Kandar','20040903035036','sysop',0,0,0,0,0.860620680135322,'20040903035036','79959096964963'); INSERT INTO cur VALUES (466,8,'Dellogpage','Log_hapusan','',3,'Kandar','20040827080711','sysop',0,0,0,0,0.636757730168065,'20040827080711','79959172919288'); INSERT INTO cur VALUES (467,8,'Dellogpagetext','Di handap ieu daptar hapusan nu ahir-ahir, sakabéh wanci dumasar wanci server (UTC).\n

','',3,'Kandar','20040802084948','sysop',0,0,0,0,0.601926641168005,'20040802084948','79959197915051'); INSERT INTO cur VALUES (468,8,'Deletionlog','log hapusan','',3,'Kandar','20040827080516','sysop',0,0,0,0,0.0993600460694731,'20040827080516','79959172919483'); INSERT INTO cur VALUES (469,8,'Reverted','Reverted to earlier revision','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.691020337576997,'20041223055411','79958776944588'); INSERT INTO cur VALUES (470,8,'Deletecomment','Alesan ngahapus','',3,'Kandar','20040729083956','sysop',0,0,0,0,0.15702158041021,'20040729083956','79959270916043'); INSERT INTO cur VALUES (471,8,'Imagereverted','Malikkeun deui ka vérsi nu saméméhna geus réngsé.','',3,'Kandar','20040802095033','sysop',0,0,0,0,0.712046920053705,'20040802095033','79959197904966'); INSERT INTO cur VALUES (472,8,'Rollback','Roll back edits','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.0891698897715378,'20041223055411','79958776944588'); INSERT INTO cur VALUES (473,8,'Rollbacklink','rollback','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.30970871943022,'20041223055412','79958776944587'); INSERT INTO cur VALUES (474,8,'Rollbackfailed','Rollback failed','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.281033958570132,'20041223055412','79958776944587'); INSERT INTO cur VALUES (475,8,'Cantrollback','Éditan teu bisa dibalikkeun; sumbangsih panungtung ngarupakeun hiji-hijina panulis kaca ieu.','',3,'Kandar','20041021050319','sysop',0,0,0,0,0.476043665293645,'20041021050319','79958978949680'); INSERT INTO cur VALUES (476,8,'Alreadyrolled','Teu bisa mulangkeun édit ahir [[$1]] ku [[User:$2|$2]] ([[User talk:$2|Omongan]]); geus aya nu ngédit atawa mulangkeun kacana. \n\nÉdit ahir ku [[User:$3|$3]] ([[User talk:$3|Omongan]]).','',3,'Kandar','20040729081757','sysop',0,0,0,0,0.537116481491473,'20040729081757','79959270918242'); INSERT INTO cur VALUES (477,8,'Editcomment','The edit comment was: \"$1\".','',0,'MediaWiki default','20041223055407','sysop',0,0,0,0,0.257451442310076,'20041223055407','79958776944592'); INSERT INTO cur VALUES (478,8,'Revertpage','Reverted edit of $2, changed back to last version by $1','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.675907797809604,'20041223055411','79958776944588'); INSERT INTO cur VALUES (479,8,'Protectlogpage','Log_koncian','',3,'Kandar','20050221110721','sysop',0,0,1,0,0.60718469285144,'20050221110721','79949778889278'); INSERT INTO cur VALUES (480,8,'Protectlogtext','Di handap ieu mangrupa daptar koncian kaca. Tempo [[Wikipédia:Kaca nu dikonci|kaca nu dikonci]] pikeun iber leuwih lengkep.','',3,'Kandar','20050221110722','sysop',0,0,1,0,0.00820010156203071,'20050221110722','79949778889277'); INSERT INTO cur VALUES (481,8,'Protectedarticle','ngonci $1','',3,'Kandar','20050221110642','sysop',0,0,1,0,0.219446459989479,'20050221110642','79949778889357'); INSERT INTO cur VALUES (482,8,'Unprotectedarticle','muka konci $1','',3,'Kandar','20050221110815','sysop',0,0,1,0,0.0726320259949491,'20050221110815','79949778889184'); INSERT INTO cur VALUES (483,8,'Undelete','Simpen deui kaca nu dihapus','',3,'Kandar','20040906071330','sysop',0,0,0,0,0.704820780739953,'20040906071330','79959093928669'); INSERT INTO cur VALUES (484,8,'Undeletepage','Témbongkeun atawa simpen deui kaca nu geus dihapus','',3,'Kandar','20040906062414','sysop',0,0,0,0,0.306207856448561,'20040906062414','79959093937585'); INSERT INTO cur VALUES (485,8,'Undeletepagetext','Kaca di handap ieu geus dihapus tapi masih kénéh aya na arsip sarta bisa disimpen deui. Arsip aya kalana dibersihan.','',3,'Kandar','20040906072111','sysop',0,0,0,0,0.416576970756591,'20040906072111','79959093927888'); INSERT INTO cur VALUES (486,8,'Undeletearticle','Simpen deui kaca nu dihapus','',3,'Kandar','20040906071350','sysop',0,0,0,0,0.164261315170919,'20040906071350','79959093928649'); INSERT INTO cur VALUES (487,8,'Undeleterevisions','$1 révisi diarsipkeun','',3,'Kandar','20040906072146','sysop',0,0,0,0,0.571575694318466,'20040906072146','79959093927853'); INSERT INTO cur VALUES (488,8,'Undeletehistory','Mun anjeun nyimpen deui kacana, sadaya révisi bakal disimpen deui dina jujutan. Mun aya kaca anyar nu ngaranna sarua dijieun deui satutasna dihapus, révisi nu disimpen tadi bakal némbongan salaku jujutan nu ti heula, sarta révisi kiwari kaca nu hirup moal otomatis kaganti.','',3,'Kandar','20040906071922','sysop',0,0,0,0,0.365094556813216,'20040906071922','79959093928077'); INSERT INTO cur VALUES (489,8,'Undeleterevision','Révisi nu dihapus sakumaha $1','',3,'Kandar','20040906072127','sysop',0,0,0,0,0.11074573184433,'20040906072127','79959093927872'); INSERT INTO cur VALUES (490,8,'Undeletebtn','Simpen deui!','',3,'Kandar','20040906071402','sysop',0,0,0,0,0.458445019515646,'20040906071402','79959093928597'); INSERT INTO cur VALUES (491,8,'Undeletedarticle','disimpen \"$1\"','',3,'Kandar','20040906071409','sysop',0,0,0,0,0.959987932778884,'20040906071409','79959093928590'); INSERT INTO cur VALUES (492,8,'Undeletedtext','[[$1]] has been successfully restored.\nSee [[Special:Log/delete]] for a record of recent deletions and restorations.','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.424604636081126,'20041223055413','79958776944586'); INSERT INTO cur VALUES (493,8,'Contributions','Sumbangsih pamaké','',3,'Kandar','20041021050111','sysop',0,0,0,0,0.243059412802625,'20041021050111','79958978949888'); INSERT INTO cur VALUES (494,8,'Mycontris','Sumbangsih kuring','',3,'Kandar','20041021050152','sysop',0,0,0,0,0.941483186503391,'20041021050152','79958978949847'); INSERT INTO cur VALUES (495,8,'Contribsub','Pikeun $1','',3,'Kandar','20040729045401','sysop',0,0,0,0,0.978237724842725,'20040729045401','79959270954598'); INSERT INTO cur VALUES (496,8,'Nocontribs','Taya robahan nu kapanggih cocog jeung patokan ieu.','',3,'Kandar','20040827083648','sysop',0,0,0,0,0.0667390954370975,'20040827083648','79959172916351'); INSERT INTO cur VALUES (497,8,'Ucnote','Di handap ieu mangrupa parobahan ahir $1 pamaké salila $2 poé ahir.','',3,'Kandar','20040810063156','sysop',0,0,0,0,0.398982333390957,'20040810063156','79959189936843'); INSERT INTO cur VALUES (498,8,'Uclinks','Témbongkeun $1 parobahan ahir; témbongkeun $2 poé ahir.','',3,'Kandar','20040906062349','sysop',0,0,0,0,0.794694411377138,'20040906062349','79959093937650'); INSERT INTO cur VALUES (499,8,'Uctop',' (tempo)','',3,'Kandar','20040924093233','sysop',0,0,0,0,0.776525087446463,'20040924093233','79959075906766'); INSERT INTO cur VALUES (500,8,'Notargettitle','Taya tujuleun','',3,'Kandar','20041229070309','sysop',0,0,0,0,0.498542233834548,'20041229070309','79958770929690'); INSERT INTO cur VALUES (501,8,'Notargettext','Anjeun can nangtukeun hiji targét atawa pamaké pikeun migawé sangkan fungsi ieu jalan.','',3,'Kandar','20040810062406','sysop',0,0,0,0,0.163135937566996,'20040810062406','79959189937593'); INSERT INTO cur VALUES (502,8,'Linklistsub','(Daptar tumbu)','',3,'Kandar','20040802100936','sysop',0,0,0,0,0.320053017064978,'20040802100936','79959197899063'); INSERT INTO cur VALUES (503,8,'Linkshere','Kaca di handap ieu numbu ka dieu:','',3,'Kandar','20040729015300','sysop',0,0,0,0,0.11085730335755,'20040729015300','79959270984699'); INSERT INTO cur VALUES (504,8,'Nolinkshere','Euweuh kaca nu numbu ka dieu.','',3,'Kandar','20040729015914','sysop',0,0,0,0,0.594127496326461,'20040729015914','79959270984085'); INSERT INTO cur VALUES (505,8,'Isredirect','Kaca alihan','',3,'Kandar','20040915055919','sysop',0,0,0,0,0.638065602293299,'20040915055919','79959084944080'); INSERT INTO cur VALUES (506,8,'Blockip','Peungpeuk pamaké','',3,'Kandar','20040810060311','sysop',0,0,0,0,0.407945553220758,'20040810060311','79959189939688'); INSERT INTO cur VALUES (507,8,'Blockiptext','Paké formulir di handap pikeun meungpeuk aksés nulis ti alamat IP atawa ngaran pamaké husus. Ieu sakuduna ditujukeun pikeun nyegah vandalisme, sarta saluyu jeung [[Wikipédia:Kawijakan|kawijakan]]. Eusi alesan nu jéntré (misal, ngarujuk kaca tinangtu nu geus diruksak).','',3,'Kandar','20040810060348','sysop',0,0,0,0,0.125530989957537,'20040810060348','79959189939651'); INSERT INTO cur VALUES (508,8,'Ipaddress','Alamat IP/ngaran pamaké','',3,'Kandar','20040810060720','sysop',0,0,0,0,0.403818320859054,'20040810060720','79959189939279'); INSERT INTO cur VALUES (509,8,'Ipbreason','Alesan','',3,'Kandar','20040728105319','sysop',0,0,0,0,0.642498665156307,'20040728105319','79959271894680'); INSERT INTO cur VALUES (510,8,'Ipbsubmit','Peungpeuk pamaké ieu','',3,'Kandar','20040810060740','sysop',0,0,0,0,0.00103839393801838,'20040810060740','79959189939259'); INSERT INTO cur VALUES (511,8,'Badipaddress','Alamat IP teu sah','',3,'Kandar','20040812031829','sysop',0,0,0,0,0.0776960049548149,'20040812031829','79959187968170'); INSERT INTO cur VALUES (512,8,'Noblockreason','Anjeun kudu méré alesan pikeun meungpeuk.','',3,'Kandar','20040827083455','sysop',0,0,0,0,0.385364873693664,'20040827083455','79959172916544'); INSERT INTO cur VALUES (513,8,'Blockipsuccesssub','Meungpeuk geus hasil','',3,'Kandar','20040729082212','sysop',0,0,0,0,0.693736384337522,'20040729082212','79959270917787'); INSERT INTO cur VALUES (514,8,'Blockipsuccesstext','\"$1\" dipeungpeuk.\n
Tempo [[Special:Ipblocklist|daptar peungpeuk IP]] pikeun nempoan deui peungpeuk.','',3,'Kandar','20040729082352','sysop',0,0,0,0,0.312587331340264,'20040729082352','79959270917647'); INSERT INTO cur VALUES (515,8,'Unblockip','Buka peungpeuk pamaké','',3,'Kandar','20040810064419','sysop',0,0,0,0,0.481727534422397,'20040810064419','79959189935580'); INSERT INTO cur VALUES (516,8,'Unblockiptext','Paké formulir di handap pikeun mulangkeun aksés nulis ka alamat IP atawa ngaran pamaké nu saméméhna dipeungpeuk.','',3,'Kandar','20040810064529','sysop',0,0,0,0,0.470875708824839,'20040810064529','79959189935470'); INSERT INTO cur VALUES (517,8,'Ipusubmit','Buka peungpeuk pikeun pamaké ieu','',3,'Kandar','20040810060751','sysop',0,0,0,0,0.909195971590649,'20040810060751','79959189939248'); INSERT INTO cur VALUES (518,8,'Ipusuccess','\"$1\" geus teu dipeungpeuk','',3,'Kandar','20040728105055','sysop',0,0,0,0,0.133352762212374,'20040728105055','79959271894944'); INSERT INTO cur VALUES (519,8,'Ipblocklist','Daptar alamat IP jeung ngaran pamaké nu dipeungpeuk','',3,'Kandar','20040810060728','sysop',0,0,0,0,0.939175927023567,'20040810060728','79959189939271'); INSERT INTO cur VALUES (520,8,'Blocklistline','$1, $2 dipeungpeuk $3 (kadaluwarsa $4)','',3,'Kandar','20040729082346','sysop',0,0,0,0,0.295821379214359,'20040729082346','79959270917653'); INSERT INTO cur VALUES (521,8,'Blocklink','peungpeuk','',3,'Kandar','20040729082327','sysop',0,0,0,0,0.661579145734738,'20040729082327','79959270917672'); INSERT INTO cur VALUES (522,8,'Unblocklink','buka peungpeuk','',3,'Kandar','20040906071313','sysop',0,0,0,0,0.420431621764257,'20040906071313','79959093928686'); INSERT INTO cur VALUES (523,8,'Contribslink','sumbang','',3,'Kandar','20041229060112','sysop',0,0,0,0,0.117420702350718,'20041229060112','79958770939887'); INSERT INTO cur VALUES (524,8,'Autoblocker','Otomatis dipeungpeuk sabab alamat IP anjeun sarua jeung \"$1\". Alesan \"$2\".','',3,'Kandar','20040802073924','sysop',0,0,0,0,0.325808677194462,'20040802073924','79959197926075'); INSERT INTO cur VALUES (525,8,'Blocklogpage','Log_peungpeuk','',3,'Kandar','20040827075557','sysop',0,0,0,0,0.276781309653801,'20040827075557','79959172924442'); INSERT INTO cur VALUES (526,8,'Blocklogentry','dipeungpeuk \"$1\" nepi ka $2','',3,'Kandar','20040827075448','sysop',0,0,0,0,0.406480547419265,'20040827075448','79959172924551'); INSERT INTO cur VALUES (527,8,'Blocklogtext','Ieu mangrupa log peta meungpeuk jeung muka peungpeuk pamaké, teu kaasup alamat IP nu dipeungpeukna otomatis. Tempo [[Special:Ipblocklist|daptar peungpeuk IP]] pikeun daptar cegahan jeung peungpeuk.','',3,'Kandar','20050221093610','sysop',0,0,1,0,0.202058838868569,'20050221093610','79949778906389'); INSERT INTO cur VALUES (528,8,'Unblocklogentry','unblocked \"$1\"','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.790852582818691,'20041223055413','79958776944586'); INSERT INTO cur VALUES (529,8,'Lockdb','Konci database','',3,'Kandar','20040803022653','sysop',0,0,0,0,0.348086428221396,'20040803022653','79959196977346'); INSERT INTO cur VALUES (530,8,'Unlockdb','Buka konci database','',3,'Kandar','20040906072233','sysop',0,0,0,0,0.36787442338455,'20040906072233','79959093927766'); INSERT INTO cur VALUES (531,8,'Lockdbtext','Ngonci gudang data bakal numpurkeun kabisa sakabéh pamaké pikeun ngédit kaca, ngarobah préferénsina, ngédit awaskeuneunana, sarta hal séjén nu merlukeun parobahan na gudang data. Konfirmasikeun yén ieu nu dimaksud ku anjeun, sarta anjeun bakal muka konci gudang data nalika pangropéa anjeun geus réngsé.','',3,'Kandar','20041229064533','sysop',0,0,0,0,0.795112862992206,'20041229064533','79958770935466'); INSERT INTO cur VALUES (532,8,'Unlockdbtext','Muka konci database bakal mulangkeun kabisa sakabéh pamaké pikeun ngédit kaca, ngarobah préferénsina, ngédit awaskeuneunana, sarta hal-hal séjén nu merlukeun parobahan na database. Pastikeun yén ieu ngarupakeun hal nu diniatkeun ku anjeun.','',3,'Kandar','20040810064725','sysop',0,0,0,0,0.871941075541024,'20040810064725','79959189935274'); INSERT INTO cur VALUES (533,8,'Lockconfirm','Leres pisan, simkuring hoyong ngonci database.','',3,'Kandar','20040802101037','sysop',0,0,0,0,0.974366819462149,'20040802101037','79959197898962'); INSERT INTO cur VALUES (534,8,'Unlockconfirm','Muhun, kuring hayang muka konci database.','',3,'Kandar','20040906072223','sysop',0,0,0,0,0.256010901421319,'20040906072223','79959093927776'); INSERT INTO cur VALUES (535,8,'Lockbtn','Konci database','',3,'Kandar','20040802101055','sysop',0,0,0,0,0.356954079453791,'20040802101055','79959197898944'); INSERT INTO cur VALUES (536,8,'Unlockbtn','Buka konci database','',3,'Kandar','20040906072202','sysop',0,0,0,0,0.0167377237386422,'20040906072202','79959093927797'); INSERT INTO cur VALUES (537,8,'Locknoconfirm','Anjeun teu nyontréngan kotak konfirmasi.','',3,'Kandar','20040802101257','sysop',0,0,0,0,0.0128264110654838,'20040802101257','79959197898742'); INSERT INTO cur VALUES (538,8,'Lockdbsuccesssub','Database geus hasil dikonci','',3,'Kandar','20040802101123','sysop',0,0,0,0,0.0139189148451378,'20040802101123','79959197898876'); INSERT INTO cur VALUES (539,8,'Unlockdbsuccesssub','Konci database geus dibuka','',3,'Kandar','20040906072248','sysop',0,0,0,0,0.0311153717628823,'20040906072248','79959093927751'); INSERT INTO cur VALUES (540,8,'Lockdbsuccesstext','Database dikonci.\n
Ulah poho muka konci mun maintenance geus bérés.','',3,'Kandar','20040802101225','sysop',0,0,0,0,0.113820145012643,'20040802101225','79959197898774'); INSERT INTO cur VALUES (541,8,'Unlockdbsuccesstext','Database geus teu dikonci.','',3,'Kandar','20040906072304','sysop',0,0,0,0,0.475754640508215,'20040906072304','79959093927695'); INSERT INTO cur VALUES (542,8,'Asksql','SQL query','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.0373127982367881,'20041223055405','79958776944594'); INSERT INTO cur VALUES (543,8,'Asksqltext','Pigunakeun formulir di handap pikeun nyieun \'\'query\'\' langsung kana gudang data. Pigunakeun curek tunggal (\'kawas kieu\') to delimit string literals. This can often add considerable load to the server, so please use this function sparingly.','',3,'Kandar','20041229054752','sysop',0,0,0,0,0.759300100392941,'20041229054752','79958770945247'); INSERT INTO cur VALUES (544,8,'Sqlislogged','Catet yén sadaya \'\'query\'\' asup kana log.','',3,'Kandar','20050221095601','sysop',0,0,1,0,0.684562137987988,'20050221095601','79949778904398'); INSERT INTO cur VALUES (545,8,'Sqlquery','Asupkeun \'\'query\'\'','',3,'Kandar','20041231061532','sysop',0,0,0,0,0.144910419494762,'20041231061532','79958768938467'); INSERT INTO cur VALUES (546,8,'Querybtn','Submit query','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.670865714243488,'20041223055411','79958776944588'); INSERT INTO cur VALUES (547,8,'Selectonly','Only read-only queries are allowed.','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.919597343466801,'20041223055412','79958776944587'); INSERT INTO cur VALUES (548,8,'Querysuccessful','Query successful','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.585389605337185,'20041223055411','79958776944588'); INSERT INTO cur VALUES (549,8,'Movepage','Pindahkeun kaca','',3,'Kandar','20040728110559','sysop',0,0,0,0,0.168156027019169,'20040728110559','79959271889440'); INSERT INTO cur VALUES (550,8,'Movepagetext','Migunakeun formulir di handap bakal ngaganti ngaran hiji kaca, mindahkeun sadaya jujutanana ka ngaran anyar.\nJudul nu heubeul bakal jadi kaca alihan ka judul nu anyar.\nTumbu ka judul kaca nu heubeul mola robah; pastikeun yén anjeun [[Special:Maintenance|marios]] alihan ganda atawa alihan nu buntu.\nAnjeun tanggel waler pikeun mastikeun yén tumbu-tumbu tetep nujul ka tempat nu sakuduna dituju.\n\nCatet yén kacana \'\'\'moal\'\'\' pindah mun geus aya kaca na judul nu anyar, iwal mun kosong atawa mangrupa alihan sarta teu mibanda jujutan éditan heubeul. Ieu ngandung harti yén anjeun bisa ngaganti ngaran hiji kaca balik deui ka nu cikénéh diganti ngaranna mun anjeun nyieun kasalahan, sarta anjeun teu bisa nimpah kaca nu geus aya.\n\nAWAS! This can be a drastic and unexpected change for a popular page;\nplease be sure you understand the consequences of this before\nproceeding.','',3,'Kandar','20040915061437','sysop',0,0,0,0,0.0846113498179348,'20040915061437','79959084938562'); INSERT INTO cur VALUES (551,8,'Movepagetalktext','Kaca omongan nu patali, mun aya, bakal sacara otomatis kapindahkeun \'\'\'iwal:\'\'\'\n*Anjeun mindahkeun kacana meuntas spasingaran nu béda,\n*Kaca omongan dina ngaran nu anyar geus aya eusian, atawa\n*Anjeun teu nyontréngan kotak di handap.\n\nDina kajadian kitu, mun hayang (jeung perlu) anjeun kudu mindahkeun atawa ngagabungkeun kacana sacara manual.','',3,'Kandar','20040729060724','sysop',0,0,0,0,0.918588698765811,'20040729060724','79959270939275'); INSERT INTO cur VALUES (552,8,'Movearticle','Pindahkeun kaca','',3,'Kandar','20040728110542','sysop',0,0,0,0,0.339109475108897,'20040728110542','79959271889457'); INSERT INTO cur VALUES (553,8,'Movenologin','Can asup log','',3,'Kandar','20050221094831','sysop',0,0,1,0,0.939781309980695,'20050221094831','79949778905168'); INSERT INTO cur VALUES (554,8,'Movenologintext','Anjeun kudu jadi pamaké nu kadaptar tur [[Special:Userlogin|asup log]] pikeun mindahkeun kaca.','',3,'Kandar','20050221094846','sysop',0,0,1,0,0.681578155310432,'20050221094846','79949778905153'); INSERT INTO cur VALUES (555,8,'Newtitle','Ka judul anyar','',3,'Kandar','20040728110934','sysop',0,0,0,0,0.588546877343717,'20040728110934','79959271889065'); INSERT INTO cur VALUES (556,8,'Movepagebtn','Pindahkeun kaca','',3,'Kandar','20040729060351','sysop',0,0,0,0,0.897999951520935,'20040729060351','79959270939648'); INSERT INTO cur VALUES (557,8,'Pagemovedsub','Mindahkeun geus hasil!','',3,'Kandar','20040803051032','sysop',0,0,0,0,0.724359156307168,'20040803051032','79959196948967'); INSERT INTO cur VALUES (558,8,'Pagemovedtext','Kaca \"[[$1]]\" dipindahkeun ka \"[[$2]]\".','',3,'Kandar','20040728112054','sysop',0,0,0,0,0.927795957706679,'20040728112054','79959271887945'); INSERT INTO cur VALUES (559,8,'Articleexists','Kaca nu ngaranna kitu geus aya, atawa ngaran nu dipilih ku anjeun teu sah. Mangga pilih ngaran séjén.','',3,'Kandar','20040812031819','sysop',0,0,0,0,0.465902350345536,'20040812031819','79959187968180'); INSERT INTO cur VALUES (560,8,'Talkexists','Kacana geus hasil dipindahkeun, ngan kaca omonganana teu bisa dipindahkeun sabab geus aya nu anyar na judul anyar. Mangga gabungkeun sacara manual.','',3,'Kandar','20040729021249','sysop',0,0,0,0,0.546123909341287,'20040729021249','79959270978750'); INSERT INTO cur VALUES (561,8,'Movedto','dipindahkeun ka','',3,'Kandar','20040728110514','sysop',0,0,0,0,0.332912526403472,'20040728110514','79959271889485'); INSERT INTO cur VALUES (562,8,'Movetalk','Mun bisa, kaca \"omongan\" ogé pindahkeun.','',3,'Kandar','20040728110732','sysop',0,0,0,0,0.0261909347271462,'20040728110732','79959271889267'); INSERT INTO cur VALUES (563,8,'Talkpagemoved','Kaca omonganana geus ogé dipindahkeun.','',3,'Kandar','20040729021318','sysop',0,0,0,0,0.132217125158959,'20040729021318','79959270978681'); INSERT INTO cur VALUES (564,8,'Talkpagenotmoved','Kaca omongan nu patali teu dipindahkeun.','',3,'Kandar','20040906071224','sysop',0,0,0,0,0.582512852347002,'20040906071224','79959093928775'); INSERT INTO cur VALUES (565,8,'1movedto2','$1 dipindahkeun ka $2','',3,'Kandar','20040728102742','sysop',0,0,0,0,0.515912916991779,'20040728102742','79959271897257'); INSERT INTO cur VALUES (566,8,'Export','Ékspor kaca','',3,'Kandar','20040802093809','sysop',0,0,0,0,0.832026058651531,'20040802093809','79959197906190'); INSERT INTO cur VALUES (567,8,'Exporttext','Anjeun bisa ngékspor téks sarta jujutan éditan ti kaca tinangtu atawa ti sababaraha kaca nu ngagunduk na sababaraha XML; ieu salajengna tiasa diimpor ka wiki séjén nu ngajalankeun software MediaWiki, ditransformasikeun, atawa ukur disimpen pikeun kaperluan anjeun pribadi.','',3,'Kandar','20040831061637','sysop',0,0,0,0,0.612391573015965,'20040831061637','79959168938362'); INSERT INTO cur VALUES (568,8,'Exportcuronly','Asupkeun ukur révisi kiwari, teu sakabéh jujutan','',3,'Kandar','20040802093854','sysop',0,0,0,0,0.565879719858877,'20040802093854','79959197906145'); INSERT INTO cur VALUES (569,8,'Allmessages','Sadaya pesen sistim','',3,'Kandar','20050316072429','sysop',0,0,1,0,0.992223910980135,'20050316072429','79949683927570'); INSERT INTO cur VALUES (570,8,'Allmessagestext','Ieu mangrupa daptar sadaya pesen sistim nu aya na MédiaWiki:spasingaran.','',3,'Kandar','20040729012430','sysop',0,0,0,0,0.263480426057689,'20040729012430','79959270987569'); INSERT INTO cur VALUES (571,8,'Thumbnail-more','Gedéan','',3,'Kandar','20040729063616','sysop',0,0,0,0,0.340730428081686,'20040729063616','79959270936383'); INSERT INTO cur VALUES (572,10,'All_messages','This is a list of all messages available in the MediaWiki: namespace\n\n
\n \'\'\'Name\'\'\'\n\n \'\'\'Default text\'\'\'\n\n \'\'\'Current text\'\'\'\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:1movedto2&action=edit 1movedto2]\n\n $1 moved to $2\n\n {{MSGNW:1movedto2}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:About&action=edit about]\n\n About\n\n {{MSGNW:about}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Aboutpage&action=edit aboutpage]\n\n Wikipedia:About\n\n {{MSGNW:aboutpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Aboutwikipedia&action=edit aboutwikipedia]\n\n About Wikipedia\n\n {{MSGNW:aboutwikipedia}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accmailtext&action=edit accmailtext]\n\n The Password for '$1' has been sent to $2.\n\n {{MSGNW:accmailtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accmailtitle&action=edit accmailtitle]\n\n Password sent.\n\n {{MSGNW:accmailtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Actioncomplete&action=edit actioncomplete]\n\n Action complete\n\n {{MSGNW:actioncomplete}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Addedwatch&action=edit addedwatch]\n\n Added to watchlist\n\n {{MSGNW:addedwatch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Addedwatchtext&action=edit addedwatchtext]\n\n The page "$1" has been added to your <a href="/wiki/Special:Watchlist">watchlist</a>.\nFuture changes to this page and its associated Talk page will be listed there,\nand the page will appear <b>bolded</b> in the <a href="/wiki/Special:Recentchanges">list of recent changes</a> to\nmake it easier to pick out.</p>\n\n<p>If you want to remove the page from your watchlist later, click "Stop watching" in the sidebar.\n\n {{MSGNW:addedwatchtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Administrators&action=edit administrators]\n\n Wikipedia:Administrators\n\n {{MSGNW:administrators}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Affirmation&action=edit affirmation]\n\n I affirm that the copyright holder of this file\nagrees to license it under the terms of the $1.\n\n {{MSGNW:affirmation}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:All&action=edit all]\n\n all\n\n {{MSGNW:all}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allmessages&action=edit allmessages]\n\n All_messages\n\n {{MSGNW:allmessages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allmessagestext&action=edit allmessagestext]\n\n This is a list of all messages available in the MediaWiki: namespace\n\n {{MSGNW:allmessagestext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allpages&action=edit allpages]\n\n All pages\n\n {{MSGNW:allpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alphaindexline&action=edit alphaindexline]\n\n $1 to $2\n\n {{MSGNW:alphaindexline}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alreadyloggedin&action=edit alreadyloggedin]\n\n <font color=red><b>User $1, you are already logged in!</b></font><br>\n\n\n {{MSGNW:alreadyloggedin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alreadyrolled&action=edit alreadyrolled]\n\n Cannot rollback last edit of [[$1]]\nby [[User:$2|$2]] ([[User talk:$2|Talk]]); someone else has edited or rolled back the article already. \n\nLast edit was by [[User:$3|$3]] ([[User talk:$3|Talk]]). \n\n {{MSGNW:alreadyrolled}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ancientpages&action=edit ancientpages]\n\n Oldest articles\n\n {{MSGNW:ancientpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Anontalkpagetext&action=edit anontalkpagetext]\n\n ---- ''This is the discussion page for an anonymous user who has not created an account yet or who does not use it. We therefore have to use the numerical [[IP address]] to identify him/her. Such an IP address can be shared by several users. If you are an anonymous user and feel that irrelevant comments have been directed at you, please [[Special:Userlogin|create an account or log in]] to avoid future confusion with other anonymous users.'' \n\n {{MSGNW:anontalkpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Articleexists&action=edit articleexists]\n\n A page of that name already exists, or the\nname you have chosen is not valid.\nPlease choose another name.\n\n {{MSGNW:articleexists}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Articlepage&action=edit articlepage]\n\n View article\n\n {{MSGNW:articlepage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Asksql&action=edit asksql]\n\n SQL query\n\n {{MSGNW:asksql}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Asksqltext&action=edit asksqltext]\n\n Use the form below to make a direct query of the\ndatabase.\nUse single quotes ('like this') to delimit string literals.\nThis can often add considerable load to the server, so please use\nthis function sparingly.\n\n {{MSGNW:asksqltext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Autoblocker&action=edit autoblocker]\n\n Autoblocked because you share an IP address with "$1". Reason "$2".\n\n {{MSGNW:autoblocker}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badarticleerror&action=edit badarticleerror]\n\n This action cannot be performed on this page.\n\n {{MSGNW:badarticleerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badfilename&action=edit badfilename]\n\n Image name has been changed to "$1".\n\n {{MSGNW:badfilename}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badfiletype&action=edit badfiletype]\n\n ".$1" is not a recommended image file format.\n\n {{MSGNW:badfiletype}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badipaddress&action=edit badipaddress]\n\n No user exists by that name\n\n {{MSGNW:badipaddress}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badquery&action=edit badquery]\n\n Badly formed search query\n\n {{MSGNW:badquery}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badquerytext&action=edit badquerytext]\n\n We could not process your query.\nThis is probably because you have attempted to search for a\nword fewer than three letters long, which is not yet supported.\nIt could also be that you have mistyped the expression, for\nexample "fish and and scales".\nPlease try another query.\n\n {{MSGNW:badquerytext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badretype&action=edit badretype]\n\n The passwords you entered do not match.\n\n {{MSGNW:badretype}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badtitle&action=edit badtitle]\n\n Bad title\n\n {{MSGNW:badtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badtitletext&action=edit badtitletext]\n\n The requested page title was invalid, empty, or\nan incorrectly linked inter-language or inter-wiki title.\n\n {{MSGNW:badtitletext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blanknamespace&action=edit blanknamespace]\n\n (Main)\n\n {{MSGNW:blanknamespace}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockedtext&action=edit blockedtext]\n\n Your user name or IP address has been blocked by $1.\nThe reason given is this:<br>''$2''<p>You may contact $1 or one of the other\n[[Wikipedia:Administrators|administrators]] to discuss the block.\n\nNote that you may not use the "email this user" feature unless you have a valid email address registered in your [[Special:Preferences|user preferences]].\n\nYour IP address is $3. Please include this address in any queries you make.\n\n==Note to AOL users==\nDue to continuing acts of vandalism by one particular AOL user, Wikipedia often blocks AOL proxies. Unfortunately, a single proxy server may be used by a large number of AOL users, and hence innocent AOL users are often inadvertently blocked. We apologise for any inconvenience caused.\n\nIf this happens to you, please email an administrator, using an AOL email address. Be sure to include the IP address given above.\n\n\n {{MSGNW:blockedtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockedtitle&action=edit blockedtitle]\n\n User is blocked\n\n {{MSGNW:blockedtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockip&action=edit blockip]\n\n Block user\n\n {{MSGNW:blockip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockipsuccesssub&action=edit blockipsuccesssub]\n\n Block succeeded\n\n {{MSGNW:blockipsuccesssub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockipsuccesstext&action=edit blockipsuccesstext]\n\n "$1" has been blocked.\n<br>See [[Special:Ipblocklist|IP block list]] to review blocks.\n\n {{MSGNW:blockipsuccesstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockiptext&action=edit blockiptext]\n\n Use the form below to block write access\nfrom a specific IP address or username.\nThis should be done only only to prevent vandalism, and in\naccordance with [[Wikipedia:Policy|policy]].\nFill in a specific reason below (for example, citing particular\npages that were vandalized).\n\n {{MSGNW:blockiptext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklink&action=edit blocklink]\n\n block\n\n {{MSGNW:blocklink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklistline&action=edit blocklistline]\n\n $1, $2 blocked $3\n\n {{MSGNW:blocklistline}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogentry&action=edit blocklogentry]\n\n blocked "$1"\n\n {{MSGNW:blocklogentry}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogpage&action=edit blocklogpage]\n\n Block_log\n\n {{MSGNW:blocklogpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogtext&action=edit blocklogtext]\n\n This is a log of user blocking and unblocking actions. Automatically \nblocked IP addresses are not be listed. See the [[Special:Ipblocklist|IP block list]] for\nthe list of currently operational bans and blocks.\n\n {{MSGNW:blocklogtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bold_sample&action=edit bold_sample]\n\n Bold text\n\n {{MSGNW:bold_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bold_tip&action=edit bold_tip]\n\n Bold text\n\n {{MSGNW:bold_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Booksources&action=edit booksources]\n\n Book sources\n\n {{MSGNW:booksources}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Booksourcetext&action=edit booksourcetext]\n\n Below is a list of links to other sites that\nsell new and used books, and may also have further information\nabout books you are looking for.\nWikipedia is not affiliated with any of these businesses, and\nthis list should not be construed as an endorsement.\n\n {{MSGNW:booksourcetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Brokenredirects&action=edit brokenredirects]\n\n Broken Redirects\n\n {{MSGNW:brokenredirects}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Brokenredirectstext&action=edit brokenredirectstext]\n\n The following redirects link to a non-existing article.\n\n {{MSGNW:brokenredirectstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bugreports&action=edit bugreports]\n\n Bug reports\n\n {{MSGNW:bugreports}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bugreportspage&action=edit bugreportspage]\n\n Wikipedia:Bug_reports\n\n {{MSGNW:bugreportspage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucratlog&action=edit bureaucratlog]\n\n Bureaucrat_log\n\n {{MSGNW:bureaucratlog}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucratlogentry&action=edit bureaucratlogentry]\n\n set $1: $2\n\n {{MSGNW:bureaucratlogentry}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucrattext&action=edit bureaucrattext]\n\n The action you have requested can only be\nperformed by sysops with "bureaucrat" status.\n\n {{MSGNW:bureaucrattext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucrattitle&action=edit bureaucrattitle]\n\n Bureaucrat access required\n\n {{MSGNW:bureaucrattitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bydate&action=edit bydate]\n\n by date\n\n {{MSGNW:bydate}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Byname&action=edit byname]\n\n by name\n\n {{MSGNW:byname}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bysize&action=edit bysize]\n\n by size\n\n {{MSGNW:bysize}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cachederror&action=edit cachederror]\n\n The following is a cached copy of the requested page, and may not be up to date.\n\n {{MSGNW:cachederror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cancel&action=edit cancel]\n\n Cancel\n\n {{MSGNW:cancel}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cannotdelete&action=edit cannotdelete]\n\n Could not delete the page or image specified. (It may have already been deleted by someone else.)\n\n {{MSGNW:cannotdelete}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cantrollback&action=edit cantrollback]\n\n Cannot revert edit; last contributor is only author of this article.\n\n {{MSGNW:cantrollback}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Categories&action=edit categories]\n\n Page categories\n\n {{MSGNW:categories}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Category&action=edit category]\n\n category\n\n {{MSGNW:category}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Category_header&action=edit category_header]\n\n Articles in category "$1"\n\n {{MSGNW:category_header}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Changepassword&action=edit changepassword]\n\n Change password\n\n {{MSGNW:changepassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Changes&action=edit changes]\n\n changes\n\n {{MSGNW:changes}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Columns&action=edit columns]\n\n Columns\n\n {{MSGNW:columns}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Commentedit&action=edit commentedit]\n\n (comment)\n\n {{MSGNW:commentedit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirm&action=edit confirm]\n\n Confirm\n\n {{MSGNW:confirm}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmcheck&action=edit confirmcheck]\n\n Yes, I really want to delete this.\n\n {{MSGNW:confirmcheck}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmdelete&action=edit confirmdelete]\n\n Confirm delete\n\n {{MSGNW:confirmdelete}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmdeletetext&action=edit confirmdeletetext]\n\n You are about to permanently delete a page\nor image along with all of its history from the database.\nPlease confirm that you intend to do this, that you understand the\nconsequences, and that you are doing this in accordance with\n[[Wikipedia:Policy]].\n\n {{MSGNW:confirmdeletetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contextchars&action=edit contextchars]\n\n Characters of context per line\n\n {{MSGNW:contextchars}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contextlines&action=edit contextlines]\n\n Lines to show per hit\n\n {{MSGNW:contextlines}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contribslink&action=edit contribslink]\n\n contribs\n\n {{MSGNW:contribslink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contribsub&action=edit contribsub]\n\n For $1\n\n {{MSGNW:contribsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contributions&action=edit contributions]\n\n User contributions\n\n {{MSGNW:contributions}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightpage&action=edit copyrightpage]\n\n Wikipedia:Copyrights\n\n {{MSGNW:copyrightpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightpagename&action=edit copyrightpagename]\n\n Wikipedia copyright\n\n {{MSGNW:copyrightpagename}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightwarning&action=edit copyrightwarning]\n\n Please note that all contributions to Wikipedia are\nconsidered to be released under the GNU Free Documentation License\n(see $1 for details).\nIf you don't want your writing to be edited mercilessly and redistributed\nat will, then don't submit it here.<br>\nYou are also promising us that you wrote this yourself, or copied it from a\npublic domain or similar free resource.\n<strong>DO NOT SUBMIT COPYRIGHTED WORK WITHOUT PERMISSION!</strong>\n\n {{MSGNW:copyrightwarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Couldntremove&action=edit couldntremove]\n\n Couldn't remove item '$1'...\n\n {{MSGNW:couldntremove}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Createaccount&action=edit createaccount]\n\n Create new account\n\n {{MSGNW:createaccount}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Createaccountmail&action=edit createaccountmail]\n\n by eMail\n\n {{MSGNW:createaccountmail}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cur&action=edit cur]\n\n cur\n\n {{MSGNW:cur}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Currentevents&action=edit currentevents]\n\n Current events\n\n {{MSGNW:currentevents}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Currentrev&action=edit currentrev]\n\n Current revision\n\n {{MSGNW:currentrev}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Databaseerror&action=edit databaseerror]\n\n Database error\n\n {{MSGNW:databaseerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dateformat&action=edit dateformat]\n\n Date format\n\n {{MSGNW:dateformat}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dberrortext&action=edit dberrortext]\n\n A database query syntax error has occurred.\nThis could be because of an illegal search query (see $5),\nor it may indicate a bug in the software.\nThe last attempted database query was:\n<blockquote><tt>$1</tt></blockquote>\nfrom within function "<tt>$2</tt>".\nMySQL returned error "<tt>$3: $4</tt>".\n\n {{MSGNW:dberrortext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dberrortextcl&action=edit dberrortextcl]\n\n A database query syntax error has occurred.\nThe last attempted database query was:\n"$1"\nfrom within function "$2".\nMySQL returned error "$3: $4".\n\n\n {{MSGNW:dberrortextcl}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deadendpages&action=edit deadendpages]\n\n Dead-end pages\n\n {{MSGNW:deadendpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Debug&action=edit debug]\n\n Debug\n\n {{MSGNW:debug}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Defaultns&action=edit defaultns]\n\n Search in these namespaces by default:\n\n {{MSGNW:defaultns}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Defemailsubject&action=edit defemailsubject]\n\n Wikipedia e-mail\n\n {{MSGNW:defemailsubject}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletecomment&action=edit deletecomment]\n\n Reason for deletion\n\n {{MSGNW:deletecomment}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletedarticle&action=edit deletedarticle]\n\n deleted "$1"\n\n {{MSGNW:deletedarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletedtext&action=edit deletedtext]\n\n "$1" has been deleted.\nSee $2 for a record of recent deletions.\n\n {{MSGNW:deletedtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deleteimg&action=edit deleteimg]\n\n del\n\n {{MSGNW:deleteimg}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletepage&action=edit deletepage]\n\n Delete page\n\n {{MSGNW:deletepage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletesub&action=edit deletesub]\n\n (Deleting "$1")\n\n {{MSGNW:deletesub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletethispage&action=edit deletethispage]\n\n Delete this page\n\n {{MSGNW:deletethispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletionlog&action=edit deletionlog]\n\n deletion log\n\n {{MSGNW:deletionlog}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dellogpage&action=edit dellogpage]\n\n Deletion_log\n\n {{MSGNW:dellogpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dellogpagetext&action=edit dellogpagetext]\n\n Below is a list of the most recent deletions.\nAll times shown are server time (UTC).\n<ul>\n</ul>\n\n\n {{MSGNW:dellogpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developerspheading&action=edit developerspheading]\n\n For developer use only\n\n {{MSGNW:developerspheading}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developertext&action=edit developertext]\n\n The action you have requested can only be\nperformed by users with "developer" status.\nSee $1.\n\n {{MSGNW:developertext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developertitle&action=edit developertitle]\n\n Developer access required\n\n {{MSGNW:developertitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Diff&action=edit diff]\n\n diff\n\n {{MSGNW:diff}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Difference&action=edit difference]\n\n (Difference between revisions)\n\n {{MSGNW:difference}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguations&action=edit disambiguations]\n\n Disambiguation pages\n\n {{MSGNW:disambiguations}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguationspage&action=edit disambiguationspage]\n\n Wikipedia:Links_to_disambiguating_pages\n\n {{MSGNW:disambiguationspage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguationstext&action=edit disambiguationstext]\n\n The following articles link to a <i>disambiguation page</i>. They should link to the appropriate topic instead.<br>A page is treated as dismbiguation if it is linked from $1.<br>Links from other namespaces are <i>not</i> listed here.\n\n {{MSGNW:disambiguationstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disclaimerpage&action=edit disclaimerpage]\n\n Wikipedia:General_disclaimer\n\n {{MSGNW:disclaimerpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disclaimers&action=edit disclaimers]\n\n Disclaimers\n\n {{MSGNW:disclaimers}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Doubleredirects&action=edit doubleredirects]\n\n Double Redirects\n\n {{MSGNW:doubleredirects}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Doubleredirectstext&action=edit doubleredirectstext]\n\n <b>Attention:</b> This list may contain false positives. That usually means there is additional text with links below the first #REDIRECT.<br>\nEach row contains links to the first and second redirect, as well as the first line of the second redirect text, usually giving the "real" taget article, which the first redirect should point to.\n\n {{MSGNW:doubleredirectstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editcomment&action=edit editcomment]\n\n The edit comment was: "<i>$1</i>".\n\n {{MSGNW:editcomment}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editconflict&action=edit editconflict]\n\n Edit conflict: $1\n\n {{MSGNW:editconflict}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editcurrent&action=edit editcurrent]\n\n Edit the current version of this page\n\n {{MSGNW:editcurrent}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Edithelp&action=edit edithelp]\n\n Editing help\n\n {{MSGNW:edithelp}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Edithelppage&action=edit edithelppage]\n\n Wikipedia:How_does_one_edit_a_page\n\n {{MSGNW:edithelppage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editing&action=edit editing]\n\n Editing $1\n\n {{MSGNW:editing}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editingold&action=edit editingold]\n\n <strong>WARNING: You are editing an out-of-date\nrevision of this page.\nIf you save it, any changes made since this revision will be lost.</strong>\n\n\n {{MSGNW:editingold}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editsection&action=edit editsection]\n\n edit\n\n {{MSGNW:editsection}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editthispage&action=edit editthispage]\n\n Edit this page\n\n {{MSGNW:editthispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailflag&action=edit emailflag]\n\n Disable e-mail from other users\n\n {{MSGNW:emailflag}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailforlost&action=edit emailforlost]\n\n * Entering an email address is optional. But it enables people to\ncontact you through the website without you having to reveal your \nemail address to them, and it also helps you if you forget your \npassword.\n\n {{MSGNW:emailforlost}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailfrom&action=edit emailfrom]\n\n From\n\n {{MSGNW:emailfrom}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailmessage&action=edit emailmessage]\n\n Message\n\n {{MSGNW:emailmessage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailpage&action=edit emailpage]\n\n E-mail user\n\n {{MSGNW:emailpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailpagetext&action=edit emailpagetext]\n\n If this user has entered a valid e-mail address in\nhis or her user preferences, the form below will send a single message.\nThe e-mail address you entered in your user preferences will appear\nas the "From" address of the mail, so the recipient will be able\nto reply.\n\n {{MSGNW:emailpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsend&action=edit emailsend]\n\n Send\n\n {{MSGNW:emailsend}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsent&action=edit emailsent]\n\n E-mail sent\n\n {{MSGNW:emailsent}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsenttext&action=edit emailsenttext]\n\n Your e-mail message has been sent.\n\n {{MSGNW:emailsenttext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsubject&action=edit emailsubject]\n\n Subject\n\n {{MSGNW:emailsubject}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailto&action=edit emailto]\n\n To\n\n {{MSGNW:emailto}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailuser&action=edit emailuser]\n\n E-mail this user\n\n {{MSGNW:emailuser}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Enterlockreason&action=edit enterlockreason]\n\n Enter a reason for the lock, including an estimate\nof when the lock will be released\n\n {{MSGNW:enterlockreason}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Error&action=edit error]\n\n Error\n\n {{MSGNW:error}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Errorpagetitle&action=edit errorpagetitle]\n\n Error\n\n {{MSGNW:errorpagetitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exbeforeblank&action=edit exbeforeblank]\n\n content before blanking was:\n\n {{MSGNW:exbeforeblank}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exblank&action=edit exblank]\n\n page was empty\n\n {{MSGNW:exblank}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Excontent&action=edit excontent]\n\n content was:\n\n {{MSGNW:excontent}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Explainconflict&action=edit explainconflict]\n\n Someone else has changed this page since you\nstarted editing it.\nThe upper text area contains the page text as it currently exists.\nYour changes are shown in the lower text area.\nYou will have to merge your changes into the existing text.\n<b>Only</b> the text in the upper text area will be saved when you\npress "Save page".\n<p>\n\n {{MSGNW:explainconflict}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Export&action=edit export]\n\n Export pages\n\n {{MSGNW:export}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exportcuronly&action=edit exportcuronly]\n\n Include only the current revision, not the full history\n\n {{MSGNW:exportcuronly}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exporttext&action=edit exporttext]\n\n You can export the text and editing history of a particular\npage or set of pages wrapped in some XML; this can then be imported into another\nwiki running MediaWiki software, transformed, or just kept for your private\namusement.\n\n {{MSGNW:exporttext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Extlink_sample&action=edit extlink_sample]\n\n http://www.example.com link title\n\n {{MSGNW:extlink_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Extlink_tip&action=edit extlink_tip]\n\n External link (remember http:// prefix)\n\n {{MSGNW:extlink_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Faq&action=edit faq]\n\n FAQ\n\n {{MSGNW:faq}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Faqpage&action=edit faqpage]\n\n Wikipedia:FAQ\n\n {{MSGNW:faqpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filecopyerror&action=edit filecopyerror]\n\n Could not copy file "$1" to "$2".\n\n {{MSGNW:filecopyerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filedeleteerror&action=edit filedeleteerror]\n\n Could not delete file "$1".\n\n {{MSGNW:filedeleteerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filedesc&action=edit filedesc]\n\n Summary\n\n {{MSGNW:filedesc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filename&action=edit filename]\n\n Filename\n\n {{MSGNW:filename}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filenotfound&action=edit filenotfound]\n\n Could not find file "$1".\n\n {{MSGNW:filenotfound}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filerenameerror&action=edit filerenameerror]\n\n Could not rename file "$1" to "$2".\n\n {{MSGNW:filerenameerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filesource&action=edit filesource]\n\n Source\n\n {{MSGNW:filesource}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filestatus&action=edit filestatus]\n\n Copyright status\n\n {{MSGNW:filestatus}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Fileuploaded&action=edit fileuploaded]\n\n File "$1" uploaded successfully.\nPlease follow this link: ($2) to the description page and fill\nin information about the file, such as where it came from, when it was\ncreated and by whom, and anything else you may know about it.\n\n {{MSGNW:fileuploaded}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Formerror&action=edit formerror]\n\n Error: could not submit form\n\n {{MSGNW:formerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Fromwikipedia&action=edit fromwikipedia]\n\n From Wikipedia, the free encyclopedia.\n\n {{MSGNW:fromwikipedia}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Getimagelist&action=edit getimagelist]\n\n fetching image list\n\n {{MSGNW:getimagelist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Gnunote&action=edit gnunote]\n\n All text is available under the terms of the <a class=internal href='/wiki/GNU_FDL'>GNU Free Documentation License</a>.\n\n {{MSGNW:gnunote}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Go&action=edit go]\n\n Go\n\n {{MSGNW:go}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Googlesearch&action=edit googlesearch]\n\n \n<!-- SiteSearch Google -->\n<FORM method=GET action="http://www.google.com/search">\n<TABLE bgcolor="#FFFFFF"><tr><td>\n<A HREF="http://www.google.com/">\n<IMG SRC="http://www.google.com/logos/Logo_40wht.gif"\nborder="0" ALT="Google"></A>\n</td>\n<td>\n<INPUT TYPE=text name=q size=31 maxlength=255 value="$1">\n<INPUT type=submit name=btnG VALUE="Google Search">\n<font size=-1>\n<input type=hidden name=domains value="http://su.wikipedia.org"><br><input type=radio name=sitesearch value=""> WWW <input type=radio name=sitesearch value="http://su.wikipedia.org" checked> http://su.wikipedia.org <br>\n<input type='hidden' name='ie' value='$2'>\n<input type='hidden' name='oe' value='$2'>\n</font>\n</td></tr></TABLE>\n</FORM>\n<!-- SiteSearch Google -->\n\n {{MSGNW:googlesearch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Guesstimezone&action=edit guesstimezone]\n\n Fill in from browser\n\n {{MSGNW:guesstimezone}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Headline_sample&action=edit headline_sample]\n\n Headline text\n\n {{MSGNW:headline_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Headline_tip&action=edit headline_tip]\n\n Level 2 headline\n\n {{MSGNW:headline_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Help&action=edit help]\n\n Help\n\n {{MSGNW:help}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Helppage&action=edit helppage]\n\n Wikipedia:Help\n\n {{MSGNW:helppage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hide&action=edit hide]\n\n hide\n\n {{MSGNW:hide}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hidetoc&action=edit hidetoc]\n\n hide\n\n {{MSGNW:hidetoc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hist&action=edit hist]\n\n hist\n\n {{MSGNW:hist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Histlegend&action=edit histlegend]\n\n Legend: (cur) = difference with current version,\n(last) = difference with preceding version, M = minor edit\n\n {{MSGNW:histlegend}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:History&action=edit history]\n\n Page history\n\n {{MSGNW:history}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Historywarning&action=edit historywarning]\n\n Warning: The page you are about to delete has a history: \n\n {{MSGNW:historywarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hr_tip&action=edit hr_tip]\n\n Horizontal line (use sparingly)\n\n {{MSGNW:hr_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ignorewarning&action=edit ignorewarning]\n\n Ignore warning and save file anyway.\n\n {{MSGNW:ignorewarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ilshowmatch&action=edit ilshowmatch]\n\n Show all images with names matching\n\n {{MSGNW:ilshowmatch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ilsubmit&action=edit ilsubmit]\n\n Search\n\n {{MSGNW:ilsubmit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Image_sample&action=edit image_sample]\n\n Example.jpg\n\n {{MSGNW:image_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Image_tip&action=edit image_tip]\n\n Embedded image\n\n {{MSGNW:image_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelinks&action=edit imagelinks]\n\n Image links\n\n {{MSGNW:imagelinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelist&action=edit imagelist]\n\n Image list\n\n {{MSGNW:imagelist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelisttext&action=edit imagelisttext]\n\n Below is a list of $1 images sorted $2.\n\n {{MSGNW:imagelisttext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagepage&action=edit imagepage]\n\n View image page\n\n {{MSGNW:imagepage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagereverted&action=edit imagereverted]\n\n Revert to earlier version was successful.\n\n {{MSGNW:imagereverted}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imgdelete&action=edit imgdelete]\n\n del\n\n {{MSGNW:imgdelete}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imgdesc&action=edit imgdesc]\n\n desc\n\n {{MSGNW:imgdesc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imghistlegend&action=edit imghistlegend]\n\n Legend: (cur) = this is the current image, (del) = delete\nthis old version, (rev) = revert to this old version.\n<br><i>Click on date to see image uploaded on that date</i>.\n\n {{MSGNW:imghistlegend}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imghistory&action=edit imghistory]\n\n Image history\n\n {{MSGNW:imghistory}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imglegend&action=edit imglegend]\n\n Legend: (desc) = show/edit image description.\n\n {{MSGNW:imglegend}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Infobox&action=edit infobox]\n\n Click a button to get an example text\n\n {{MSGNW:infobox}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Internalerror&action=edit internalerror]\n\n Internal error\n\n {{MSGNW:internalerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Intl&action=edit intl]\n\n Interlanguage links\n\n {{MSGNW:intl}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ip_range_invalid&action=edit ip_range_invalid]\n\n Invalid IP range.\n\n\n {{MSGNW:ip_range_invalid}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipaddress&action=edit ipaddress]\n\n IP Address/username\n\n {{MSGNW:ipaddress}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipb_expiry_invalid&action=edit ipb_expiry_invalid]\n\n Expiry time invalid.\n\n {{MSGNW:ipb_expiry_invalid}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbexpiry&action=edit ipbexpiry]\n\n Expiry\n\n {{MSGNW:ipbexpiry}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipblocklist&action=edit ipblocklist]\n\n List of blocked IP addresses and usernames\n\n {{MSGNW:ipblocklist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbreason&action=edit ipbreason]\n\n Reason\n\n {{MSGNW:ipbreason}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbsubmit&action=edit ipbsubmit]\n\n Block this user\n\n {{MSGNW:ipbsubmit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipusubmit&action=edit ipusubmit]\n\n Unblock this address\n\n {{MSGNW:ipusubmit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipusuccess&action=edit ipusuccess]\n\n "$1" unblocked\n\n {{MSGNW:ipusuccess}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Isredirect&action=edit isredirect]\n\n redirect page\n\n {{MSGNW:isredirect}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Italic_sample&action=edit italic_sample]\n\n Italic text\n\n {{MSGNW:italic_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Italic_tip&action=edit italic_tip]\n\n Italic text\n\n {{MSGNW:italic_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Iteminvalidname&action=edit iteminvalidname]\n\n Problem with item '$1', invalid name...\n\n {{MSGNW:iteminvalidname}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Largefile&action=edit largefile]\n\n It is recommended that images not exceed 100k in size.\n\n {{MSGNW:largefile}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Last&action=edit last]\n\n last\n\n {{MSGNW:last}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lastmodified&action=edit lastmodified]\n\n This page was last modified $1.\n\n {{MSGNW:lastmodified}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lineno&action=edit lineno]\n\n Line $1:\n\n {{MSGNW:lineno}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Link_sample&action=edit link_sample]\n\n Link title\n\n {{MSGNW:link_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Link_tip&action=edit link_tip]\n\n Internal link\n\n {{MSGNW:link_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linklistsub&action=edit linklistsub]\n\n (List of links)\n\n {{MSGNW:linklistsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linkshere&action=edit linkshere]\n\n The following pages link to here:\n\n {{MSGNW:linkshere}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linkstoimage&action=edit linkstoimage]\n\n The following pages link to this image:\n\n {{MSGNW:linkstoimage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linktrail&action=edit linktrail]\n\n /^([a-z]+)(.*)$/sD\n\n {{MSGNW:linktrail}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Listform&action=edit listform]\n\n list\n\n {{MSGNW:listform}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Listusers&action=edit listusers]\n\n User list\n\n {{MSGNW:listusers}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loadhist&action=edit loadhist]\n\n Loading page history\n\n {{MSGNW:loadhist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loadingrev&action=edit loadingrev]\n\n loading revision for diff\n\n {{MSGNW:loadingrev}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Localtime&action=edit localtime]\n\n Local time display\n\n {{MSGNW:localtime}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockbtn&action=edit lockbtn]\n\n Lock database\n\n {{MSGNW:lockbtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockconfirm&action=edit lockconfirm]\n\n Yes, I really want to lock the database.\n\n {{MSGNW:lockconfirm}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdb&action=edit lockdb]\n\n Lock database\n\n {{MSGNW:lockdb}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbsuccesssub&action=edit lockdbsuccesssub]\n\n Database lock succeeded\n\n {{MSGNW:lockdbsuccesssub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbsuccesstext&action=edit lockdbsuccesstext]\n\n The database has been locked.\n<br>Remember to remove the lock after your maintenance is complete.\n\n {{MSGNW:lockdbsuccesstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbtext&action=edit lockdbtext]\n\n Locking the database will suspend the ability of all\nusers to edit pages, change their preferences, edit their watchlists, and\nother things requiring changes in the database.\nPlease confirm that this is what you intend to do, and that you will\nunlock the database when your maintenance is done.\n\n {{MSGNW:lockdbtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Locknoconfirm&action=edit locknoconfirm]\n\n You did not check the confirmation box.\n\n {{MSGNW:locknoconfirm}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Login&action=edit login]\n\n Log in\n\n {{MSGNW:login}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginend&action=edit loginend]\n\n &lt;loginend&gt;\n\n {{MSGNW:loginend}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginerror&action=edit loginerror]\n\n Login error\n\n {{MSGNW:loginerror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginpagetitle&action=edit loginpagetitle]\n\n User login\n\n {{MSGNW:loginpagetitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginproblem&action=edit loginproblem]\n\n <b>There has been a problem with your login.</b><br>Try again!\n\n {{MSGNW:loginproblem}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginprompt&action=edit loginprompt]\n\n You must have cookies enabled to log in to Wikipedia.\n\n {{MSGNW:loginprompt}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginsuccess&action=edit loginsuccess]\n\n You are now logged in to Wikipedia as "$1".\n\n {{MSGNW:loginsuccess}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginsuccesstitle&action=edit loginsuccesstitle]\n\n Login successful\n\n {{MSGNW:loginsuccesstitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logout&action=edit logout]\n\n Log out\n\n {{MSGNW:logout}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logouttext&action=edit logouttext]\n\n You are now logged out.\nYou can continue to use Wikipedia anonymously, or you can log in\nagain as the same or as a different user. Note that some pages may\ncontinue to be displayed as if you were still logged in, until you clear\nyour browser cache\n\n\n {{MSGNW:logouttext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logouttitle&action=edit logouttitle]\n\n User logout\n\n {{MSGNW:logouttitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lonelypages&action=edit lonelypages]\n\n Orphaned pages\n\n {{MSGNW:lonelypages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Longpages&action=edit longpages]\n\n Long pages\n\n {{MSGNW:longpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Longpagewarning&action=edit longpagewarning]\n\n WARNING: This page is $1 kilobytes long; some\nbrowsers may have problems editing pages approaching or longer than 32kb.\nPlease consider breaking the page into smaller sections.\n\n {{MSGNW:longpagewarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailmypassword&action=edit mailmypassword]\n\n Mail me a new password\n\n {{MSGNW:mailmypassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailnologin&action=edit mailnologin]\n\n No send address\n\n {{MSGNW:mailnologin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailnologintext&action=edit mailnologintext]\n\n You must be <a href="/wiki/Special:Userlogin">logged in</a>\nand have a valid e-mail address in your <a href="/wiki/Special:Preferences">preferences</a>\nto send e-mail to other users.\n\n {{MSGNW:mailnologintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mainpage&action=edit mainpage]\n\n Main Page\n\n {{MSGNW:mainpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mainpagetext&action=edit mainpagetext]\n\n Wiki software successfully installed.\n\n {{MSGNW:mainpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintenance&action=edit maintenance]\n\n Maintenance page\n\n {{MSGNW:maintenance}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintenancebacklink&action=edit maintenancebacklink]\n\n Back to Maintenance Page\n\n {{MSGNW:maintenancebacklink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintnancepagetext&action=edit maintnancepagetext]\n\n This page includes several handy tools for everyday maintenance. Some of these functions tend to stress the database, so please do not hit reload after every item you fixed ;-)\n\n {{MSGNW:maintnancepagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopfail&action=edit makesysopfail]\n\n <b>User '$1' could not be made into a sysop. (Did you enter the name correctly?)</b>\n\n {{MSGNW:makesysopfail}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopname&action=edit makesysopname]\n\n Name of the user:\n\n {{MSGNW:makesysopname}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopok&action=edit makesysopok]\n\n <b>User '$1' is now a sysop</b>\n\n {{MSGNW:makesysopok}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopsubmit&action=edit makesysopsubmit]\n\n Make this user into a sysop\n\n {{MSGNW:makesysopsubmit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysoptext&action=edit makesysoptext]\n\n This form is used by bureaucrats to turn ordinary users into administrators. \nType the name of the user in the box and press the button to make the user an administrator\n\n {{MSGNW:makesysoptext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysoptitle&action=edit makesysoptitle]\n\n Make a user into a sysop\n\n {{MSGNW:makesysoptitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Matchtotals&action=edit matchtotals]\n\n The query "$1" matched $2 article titles\nand the text of $3 articles.\n\n {{MSGNW:matchtotals}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math&action=edit math]\n\n Rendering math\n\n {{MSGNW:math}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_failure&action=edit math_failure]\n\n Failed to parse\n\n {{MSGNW:math_failure}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_image_error&action=edit math_image_error]\n\n PNG conversion failed\n\n {{MSGNW:math_image_error}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_lexing_error&action=edit math_lexing_error]\n\n lexing error\n\n {{MSGNW:math_lexing_error}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_sample&action=edit math_sample]\n\n Insert formula here\n\n {{MSGNW:math_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_syntax_error&action=edit math_syntax_error]\n\n syntax error\n\n {{MSGNW:math_syntax_error}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_tip&action=edit math_tip]\n\n Mathematical formula (LaTeX)\n\n {{MSGNW:math_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_unknown_error&action=edit math_unknown_error]\n\n unknown error\n\n {{MSGNW:math_unknown_error}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_unknown_function&action=edit math_unknown_function]\n\n unknown function \n\n {{MSGNW:math_unknown_function}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Media_sample&action=edit media_sample]\n\n Example.mp3\n\n {{MSGNW:media_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Media_tip&action=edit media_tip]\n\n Media file link\n\n {{MSGNW:media_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minlength&action=edit minlength]\n\n Image names must be at least three letters.\n\n {{MSGNW:minlength}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minoredit&action=edit minoredit]\n\n This is a minor edit\n\n {{MSGNW:minoredit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minoreditletter&action=edit minoreditletter]\n\n M\n\n {{MSGNW:minoreditletter}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelings&action=edit mispeelings]\n\n Pages with misspellings\n\n {{MSGNW:mispeelings}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelingspage&action=edit mispeelingspage]\n\n List of common misspellings\n\n {{MSGNW:mispeelingspage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelingstext&action=edit mispeelingstext]\n\n The following pages contain a common misspelling, which are listed on $1. The correct spelling might be given (like this).\n\n {{MSGNW:mispeelingstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missingarticle&action=edit missingarticle]\n\n The database did not find the text of a page\nthat it should have found, named "$1".\n\n<p>This is usually caused by following an outdated diff or history link to a\npage that has been deleted.\n\n<p>If this is not the case, you may have found a bug in the software.\nPlease report this to an administrator, making note of the URL.\n\n {{MSGNW:missingarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinks&action=edit missinglanguagelinks]\n\n Missing Language Links\n\n {{MSGNW:missinglanguagelinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinksbutton&action=edit missinglanguagelinksbutton]\n\n Find missing language links for\n\n {{MSGNW:missinglanguagelinksbutton}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinkstext&action=edit missinglanguagelinkstext]\n\n These articles do <i>not</i> link to their counterpart in $1. Redirects and subpages are <i>not</i> shown.\n\n {{MSGNW:missinglanguagelinkstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Moredotdotdot&action=edit moredotdotdot]\n\n More...\n\n {{MSGNW:moredotdotdot}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movearticle&action=edit movearticle]\n\n Move page\n\n {{MSGNW:movearticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movedto&action=edit movedto]\n\n moved to\n\n {{MSGNW:movedto}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movenologin&action=edit movenologin]\n\n Not logged in\n\n {{MSGNW:movenologin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movenologintext&action=edit movenologintext]\n\n You must be a registered user and <a href="/wiki/Special:Userlogin">logged in</a>\nto move a page.\n\n {{MSGNW:movenologintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepage&action=edit movepage]\n\n Move page\n\n {{MSGNW:movepage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagebtn&action=edit movepagebtn]\n\n Move page\n\n {{MSGNW:movepagebtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagetalktext&action=edit movepagetalktext]\n\n The associated talk page, if any, will be automatically moved along with it '''unless:'''\n*You are moving the page across namespaces,\n*A non-empty talk page already exists under the new name, or\n*You uncheck the box below.\n\nIn those cases, you will have to move or merge the page manually if desired.\n\n {{MSGNW:movepagetalktext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagetext&action=edit movepagetext]\n\n Using the form below will rename a page, moving all\nof its history to the new name.\nThe old title will become a redirect page to the new title.\nLinks to the old page title will not be changed; be sure to\n[[Special:Maintenance|check]] for double or broken redirects.\nYou are responsible for making sure that links continue to\npoint where they are supposed to go.\n\nNote that the page will '''not''' be moved if there is already\na page at the new title, unless it is empty or a redirect and has no\npast edit history. This means that you can rename a page back to where\nit was just renamed from if you make a mistake, and you cannot overwrite\nan existing page.\n\n<b>WARNING!</b>\nThis can be a drastic and unexpected change for a popular page;\nplease be sure you understand the consequences of this before\nproceeding.\n\n {{MSGNW:movepagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movetalk&action=edit movetalk]\n\n Move "talk" page as well, if applicable.\n\n {{MSGNW:movetalk}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movethispage&action=edit movethispage]\n\n Move this page\n\n {{MSGNW:movethispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mycontris&action=edit mycontris]\n\n My contributions\n\n {{MSGNW:mycontris}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mypage&action=edit mypage]\n\n My page\n\n {{MSGNW:mypage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mytalk&action=edit mytalk]\n\n My talk\n\n {{MSGNW:mytalk}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nbytes&action=edit nbytes]\n\n $1 bytes\n\n {{MSGNW:nbytes}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nchanges&action=edit nchanges]\n\n $1 changes\n\n {{MSGNW:nchanges}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newarticle&action=edit newarticle]\n\n (New)\n\n {{MSGNW:newarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newarticletext&action=edit newarticletext]\n\n You've followed a link to a page that doesn't exist yet.\nTo create the page, start typing in the box below \n(see the [[Wikipedia:Help|help page]] for more info).\nIf you are here by mistake, just click your browser's '''back''' button.\n\n {{MSGNW:newarticletext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newmessages&action=edit newmessages]\n\n You have $1.\n\n {{MSGNW:newmessages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newmessageslink&action=edit newmessageslink]\n\n new messages\n\n {{MSGNW:newmessageslink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpage&action=edit newpage]\n\n New page\n\n {{MSGNW:newpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpageletter&action=edit newpageletter]\n\n N\n\n {{MSGNW:newpageletter}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpages&action=edit newpages]\n\n New pages\n\n {{MSGNW:newpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpassword&action=edit newpassword]\n\n New password\n\n {{MSGNW:newpassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newtitle&action=edit newtitle]\n\n To new title\n\n {{MSGNW:newtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newusersonly&action=edit newusersonly]\n\n (new users only)\n\n {{MSGNW:newusersonly}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Next&action=edit next]\n\n next\n\n {{MSGNW:next}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nextn&action=edit nextn]\n\n next $1\n\n {{MSGNW:nextn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nlinks&action=edit nlinks]\n\n $1 links\n\n {{MSGNW:nlinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noaffirmation&action=edit noaffirmation]\n\n You must affirm that your upload does not violate\nany copyrights.\n\n {{MSGNW:noaffirmation}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noarticletext&action=edit noarticletext]\n\n (There is currently no text in this page)\n\n {{MSGNW:noarticletext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noblockreason&action=edit noblockreason]\n\n You must supply a reason for the block.\n\n {{MSGNW:noblockreason}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noconnect&action=edit noconnect]\n\n Sorry! The wiki is experiencing some technical difficulties, and cannot contact the database server.\n\n {{MSGNW:noconnect}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocontribs&action=edit nocontribs]\n\n No changes were found matching these criteria.\n\n {{MSGNW:nocontribs}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocookieslogin&action=edit nocookieslogin]\n\n Wikipedia uses cookies to log in users. You have cookies disabled. Please enable them and try again.\n\n {{MSGNW:nocookieslogin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocookiesnew&action=edit nocookiesnew]\n\n The user account was created, but you are not logged in. Wikipedia uses cookies to log in users. You have cookies disabled. Please enable them, then log in with your new username and password.\n\n {{MSGNW:nocookiesnew}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nodb&action=edit nodb]\n\n Could not select database $1\n\n {{MSGNW:nodb}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemail&action=edit noemail]\n\n There is no e-mail address recorded for user "$1".\n\n {{MSGNW:noemail}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemailtext&action=edit noemailtext]\n\n This user has not specified a valid e-mail address,\nor has chosen not to receive e-mail from other users.\n\n {{MSGNW:noemailtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemailtitle&action=edit noemailtitle]\n\n No e-mail address\n\n {{MSGNW:noemailtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nogomatch&action=edit nogomatch]\n\n No page with this exact title exists, trying full text search.\n\n {{MSGNW:nogomatch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nohistory&action=edit nohistory]\n\n There is no edit history for this page.\n\n {{MSGNW:nohistory}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nolinkshere&action=edit nolinkshere]\n\n No pages link to here.\n\n {{MSGNW:nolinkshere}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nolinkstoimage&action=edit nolinkstoimage]\n\n There are no pages that link to this image.\n\n {{MSGNW:nolinkstoimage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noname&action=edit noname]\n\n You have not specified a valid user name.\n\n {{MSGNW:noname}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nonefound&action=edit nonefound]\n\n <strong>Note</strong>: unsuccessful searches are\noften caused by searching for common words like "have" and "from",\nwhich are not indexed, or by specifying more than one search term (only pages\ncontaining all of the search terms will appear in the result).\n\n {{MSGNW:nonefound}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nospecialpagetext&action=edit nospecialpagetext]\n\n You have requested a special page that is not\nrecognized by the wiki.\n\n {{MSGNW:nospecialpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchaction&action=edit nosuchaction]\n\n No such action\n\n {{MSGNW:nosuchaction}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchactiontext&action=edit nosuchactiontext]\n\n The action specified by the URL is not\nrecognized by the wiki\n\n {{MSGNW:nosuchactiontext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchspecialpage&action=edit nosuchspecialpage]\n\n No such special page\n\n {{MSGNW:nosuchspecialpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchuser&action=edit nosuchuser]\n\n There is no user by the name "$1".\nCheck your spelling, or use the form below to create a new user account.\n\n {{MSGNW:nosuchuser}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notanarticle&action=edit notanarticle]\n\n Not an article\n\n {{MSGNW:notanarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notargettext&action=edit notargettext]\n\n You have not specified a target page or user\nto perform this function on.\n\n {{MSGNW:notargettext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notargettitle&action=edit notargettitle]\n\n No target\n\n {{MSGNW:notargettitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Note&action=edit note]\n\n <strong>Note:</strong> \n\n {{MSGNW:note}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notextmatches&action=edit notextmatches]\n\n No article text matches\n\n {{MSGNW:notextmatches}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notitlematches&action=edit notitlematches]\n\n No article title matches\n\n {{MSGNW:notitlematches}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notloggedin&action=edit notloggedin]\n\n Not logged in\n\n {{MSGNW:notloggedin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowatchlist&action=edit nowatchlist]\n\n You have no items on your watchlist.\n\n {{MSGNW:nowatchlist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowiki_sample&action=edit nowiki_sample]\n\n Insert non-formatted text here\n\n {{MSGNW:nowiki_sample}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowiki_tip&action=edit nowiki_tip]\n\n Ignore wiki formatting\n\n {{MSGNW:nowiki_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nviews&action=edit nviews]\n\n $1 views\n\n {{MSGNW:nviews}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ok&action=edit ok]\n\n OK\n\n {{MSGNW:ok}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Oldpassword&action=edit oldpassword]\n\n Old password\n\n {{MSGNW:oldpassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Orig&action=edit orig]\n\n orig\n\n {{MSGNW:orig}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Orphans&action=edit orphans]\n\n Orphaned pages\n\n {{MSGNW:orphans}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Otherlanguages&action=edit otherlanguages]\n\n Other languages\n\n {{MSGNW:otherlanguages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Pagemovedsub&action=edit pagemovedsub]\n\n Move succeeded\n\n {{MSGNW:pagemovedsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Pagemovedtext&action=edit pagemovedtext]\n\n Page "[[$1]]" moved to "[[$2]]".\n\n {{MSGNW:pagemovedtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordremindertext&action=edit passwordremindertext]\n\n Someone (probably you, from IP address $1)\nrequested that we send you a new Wikipedia login password.\nThe password for user "$2" is now "$3".\nYou should log in and change your password now.\n\n {{MSGNW:passwordremindertext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordremindertitle&action=edit passwordremindertitle]\n\n Password reminder from Wikipedia\n\n {{MSGNW:passwordremindertitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordsent&action=edit passwordsent]\n\n A new password has been sent to the e-mail address\nregistered for "$1".\nPlease log in again after you receive it.\n\n {{MSGNW:passwordsent}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Perfdisabled&action=edit perfdisabled]\n\n Sorry! This feature has been temporarily disabled\nbecause it slows the database down to the point that no one can use\nthe wiki.\n\n {{MSGNW:perfdisabled}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Perfdisabledsub&action=edit perfdisabledsub]\n\n Here's a saved copy from $1:\n\n {{MSGNW:perfdisabledsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Popularpages&action=edit popularpages]\n\n Popular pages\n\n {{MSGNW:popularpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Postcomment&action=edit postcomment]\n\n Post a comment\n\n {{MSGNW:postcomment}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Powersearch&action=edit powersearch]\n\n Search\n\n {{MSGNW:powersearch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Powersearchtext&action=edit powersearchtext]\n\n \nSearch in namespaces :<br>\n$1<br>\n$2 List redirects &nbsp; Search for $3 $9\n\n {{MSGNW:powersearchtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Preferences&action=edit preferences]\n\n Preferences\n\n {{MSGNW:preferences}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefslogintext&action=edit prefslogintext]\n\n You are logged in as "$1".\nYour internal ID number is $2.\n\nSee [[Wikipedia:User preferences help]] for help deciphering the options.\n\n {{MSGNW:prefslogintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsnologin&action=edit prefsnologin]\n\n Not logged in\n\n {{MSGNW:prefsnologin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsnologintext&action=edit prefsnologintext]\n\n You must be <a href="/wiki/Special:Userlogin">logged in</a>\nto set user preferences.\n\n {{MSGNW:prefsnologintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsreset&action=edit prefsreset]\n\n Preferences have been reset from storage.\n\n {{MSGNW:prefsreset}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Preview&action=edit preview]\n\n Preview\n\n {{MSGNW:preview}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Previewconflict&action=edit previewconflict]\n\n This preview reflects the text in the upper\ntext editing area as it will appear if you choose to save.\n\n {{MSGNW:previewconflict}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Previewnote&action=edit previewnote]\n\n Remember that this is only a preview, and has not yet been saved!\n\n {{MSGNW:previewnote}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prevn&action=edit prevn]\n\n previous $1\n\n {{MSGNW:prevn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Printableversion&action=edit printableversion]\n\n Printable version\n\n {{MSGNW:printableversion}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Printsubtitle&action=edit printsubtitle]\n\n (From http://www.wikipedia.org)\n\n {{MSGNW:printsubtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedarticle&action=edit protectedarticle]\n\n protected [[$1]]\n\n {{MSGNW:protectedarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedpage&action=edit protectedpage]\n\n Protected page\n\n {{MSGNW:protectedpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedpagewarning&action=edit protectedpagewarning]\n\n WARNING: This page has been locked so that only\nusers with sysop privileges can edit it. Be sure you are following the\n<a href='/wiki/Wikipedia:Protected_page_guidelines'>protected page\nguidelines</a>.\n\n {{MSGNW:protectedpagewarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedtext&action=edit protectedtext]\n\n This page has been locked to prevent editing; there are\na number of reasons why this may be so, please see\n[[Wikipedia:Protected page]].\n\nYou can view and copy the source of this page:\n\n {{MSGNW:protectedtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectlogpage&action=edit protectlogpage]\n\n Protection_log\n\n {{MSGNW:protectlogpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectlogtext&action=edit protectlogtext]\n\n Below is a list of page locks/unlocks.\nSee [[Wikipedia:Protected page]] for more information.\n\n {{MSGNW:protectlogtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectpage&action=edit protectpage]\n\n Protect page\n\n {{MSGNW:protectpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectthispage&action=edit protectthispage]\n\n Protect this page\n\n {{MSGNW:protectthispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbbrowse&action=edit qbbrowse]\n\n Browse\n\n {{MSGNW:qbbrowse}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbedit&action=edit qbedit]\n\n Edit\n\n {{MSGNW:qbedit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbfind&action=edit qbfind]\n\n Find\n\n {{MSGNW:qbfind}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbmyoptions&action=edit qbmyoptions]\n\n My pages\n\n {{MSGNW:qbmyoptions}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbpageinfo&action=edit qbpageinfo]\n\n Context\n\n {{MSGNW:qbpageinfo}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbpageoptions&action=edit qbpageoptions]\n\n This page\n\n {{MSGNW:qbpageoptions}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbsettings&action=edit qbsettings]\n\n Quickbar settings\n\n {{MSGNW:qbsettings}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbspecialpages&action=edit qbspecialpages]\n\n Special pages\n\n {{MSGNW:qbspecialpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Querybtn&action=edit querybtn]\n\n Submit query\n\n {{MSGNW:querybtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Querysuccessful&action=edit querysuccessful]\n\n Query successful\n\n {{MSGNW:querysuccessful}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Randompage&action=edit randompage]\n\n Random page\n\n {{MSGNW:randompage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Range_block_disabled&action=edit range_block_disabled]\n\n The sysop ability to create range blocks is disabled.\n\n {{MSGNW:range_block_disabled}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rchide&action=edit rchide]\n\n in $4 form; $1 minor edits; $2 secondary namespaces; $3 multiple edits.\n\n {{MSGNW:rchide}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclinks&action=edit rclinks]\n\n Show last $1 changes in last $2 days; $3\n\n {{MSGNW:rclinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclistfrom&action=edit rclistfrom]\n\n Show new changes starting from $1\n\n {{MSGNW:rclistfrom}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcliu&action=edit rcliu]\n\n ; $1 edits from logged in users\n\n {{MSGNW:rcliu}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcloaderr&action=edit rcloaderr]\n\n Loading recent changes\n\n {{MSGNW:rcloaderr}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclsub&action=edit rclsub]\n\n (to pages linked from "$1")\n\n {{MSGNW:rclsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcnote&action=edit rcnote]\n\n Below are the last <strong>$1</strong> changes in last <strong>$2</strong> days.\n\n {{MSGNW:rcnote}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcnotefrom&action=edit rcnotefrom]\n\n Below are the changes since <b>$2</b> (up to <b>$1</b> shown).\n\n {{MSGNW:rcnotefrom}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonly&action=edit readonly]\n\n Database locked\n\n {{MSGNW:readonly}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonlytext&action=edit readonlytext]\n\n The database is currently locked to new\nentries and other modifications, probably for routine database maintenance,\nafter which it will be back to normal.\nThe administrator who locked it offered this explanation:\n<p>$1\n\n {{MSGNW:readonlytext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonlywarning&action=edit readonlywarning]\n\n WARNING: The database has been locked for maintenance,\nso you will not be able to save your edits right now. You may wish to cut-n-paste\nthe text into a text file and save it for later.\n\n {{MSGNW:readonlywarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchanges&action=edit recentchanges]\n\n Recent changes\n\n {{MSGNW:recentchanges}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangescount&action=edit recentchangescount]\n\n Number of titles in recent changes\n\n {{MSGNW:recentchangescount}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangeslinked&action=edit recentchangeslinked]\n\n Related changes\n\n {{MSGNW:recentchangeslinked}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangestext&action=edit recentchangestext]\n\n Track the most recent changes to the wiki on this page.\n\n {{MSGNW:recentchangestext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Redirectedfrom&action=edit redirectedfrom]\n\n (Redirected from $1)\n\n {{MSGNW:redirectedfrom}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Remembermypassword&action=edit remembermypassword]\n\n Remember my password across sessions.\n\n {{MSGNW:remembermypassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removechecked&action=edit removechecked]\n\n Remove checked items from watchlist\n\n {{MSGNW:removechecked}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removedwatch&action=edit removedwatch]\n\n Removed from watchlist\n\n {{MSGNW:removedwatch}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removedwatchtext&action=edit removedwatchtext]\n\n The page "$1" has been removed from your watchlist.\n\n {{MSGNW:removedwatchtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removingchecked&action=edit removingchecked]\n\n Removing requested items from watchlist...\n\n {{MSGNW:removingchecked}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Resetprefs&action=edit resetprefs]\n\n Reset preferences\n\n {{MSGNW:resetprefs}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Restorelink&action=edit restorelink]\n\n $1 deleted edits\n\n {{MSGNW:restorelink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Resultsperpage&action=edit resultsperpage]\n\n Hits to show per page\n\n {{MSGNW:resultsperpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Retrievedfrom&action=edit retrievedfrom]\n\n Retrieved from "$1"\n\n {{MSGNW:retrievedfrom}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Returnto&action=edit returnto]\n\n Return to $1.\n\n {{MSGNW:returnto}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Retypenew&action=edit retypenew]\n\n Retype new password\n\n {{MSGNW:retypenew}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reupload&action=edit reupload]\n\n Re-upload\n\n {{MSGNW:reupload}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reuploaddesc&action=edit reuploaddesc]\n\n Return to the upload form.\n\n {{MSGNW:reuploaddesc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reverted&action=edit reverted]\n\n Reverted to earlier revision\n\n {{MSGNW:reverted}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revertimg&action=edit revertimg]\n\n rev\n\n {{MSGNW:revertimg}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revertpage&action=edit revertpage]\n\n Reverted edit of $2, changed back to last version by $1\n\n {{MSGNW:revertpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revhistory&action=edit revhistory]\n\n Revision history\n\n {{MSGNW:revhistory}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revisionasof&action=edit revisionasof]\n\n Revision as of $1\n\n {{MSGNW:revisionasof}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revnotfound&action=edit revnotfound]\n\n Revision not found\n\n {{MSGNW:revnotfound}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revnotfoundtext&action=edit revnotfoundtext]\n\n The old revision of the page you asked for could not be found.\nPlease check the URL you used to access this page.\n\n\n {{MSGNW:revnotfoundtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollback&action=edit rollback]\n\n Roll back edits\n\n {{MSGNW:rollback}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollbackfailed&action=edit rollbackfailed]\n\n Rollback failed\n\n {{MSGNW:rollbackfailed}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollbacklink&action=edit rollbacklink]\n\n rollback\n\n {{MSGNW:rollbacklink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rows&action=edit rows]\n\n Rows\n\n {{MSGNW:rows}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savearticle&action=edit savearticle]\n\n Save page\n\n {{MSGNW:savearticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savedprefs&action=edit savedprefs]\n\n Your preferences have been saved.\n\n {{MSGNW:savedprefs}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savefile&action=edit savefile]\n\n Save file\n\n {{MSGNW:savefile}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Saveprefs&action=edit saveprefs]\n\n Save preferences\n\n {{MSGNW:saveprefs}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Search&action=edit search]\n\n Search\n\n {{MSGNW:search}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchdisabled&action=edit searchdisabled]\n\n <p>Sorry! Full text search has been disabled temporarily, for performance reasons. In the meantime, you can use the Google search below, which may be out of date.</p>\n\n<!-- SiteSearch Google -->\n<FORM method=GET action="http://www.google.com/search">\n<TABLE bgcolor="#FFFFFF"><tr><td>\n<A HREF="http://www.google.com/">\n<IMG SRC="http://www.google.com/logos/Logo_40wht.gif"\nborder="0" ALT="Google"></A>\n</td>\n<td>\n<INPUT TYPE=text name=q size=31 maxlength=255 value="$1">\n<INPUT type=submit name=btnG VALUE="Google Search">\n<font size=-1>\n<input type=hidden name=domains value="http://su.wikipedia.org"><br><input type=radio name=sitesearch value=""> WWW <input type=radio name=sitesearch value="http://su.wikipedia.org" checked> http://su.wikipedia.org <br>\n<input type='hidden' name='ie' value='$2'>\n<input type='hidden' name='oe' value='$2'>\n</font>\n</td></tr></TABLE>\n</FORM>\n<!-- SiteSearch Google -->\n\n {{MSGNW:searchdisabled}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchhelppage&action=edit searchhelppage]\n\n Wikipedia:Searching\n\n {{MSGNW:searchhelppage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchingwikipedia&action=edit searchingwikipedia]\n\n Searching Wikipedia\n\n {{MSGNW:searchingwikipedia}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchquery&action=edit searchquery]\n\n For query "$1"\n\n {{MSGNW:searchquery}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresults&action=edit searchresults]\n\n Search results\n\n {{MSGNW:searchresults}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresultshead&action=edit searchresultshead]\n\n Search result settings\n\n {{MSGNW:searchresultshead}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresulttext&action=edit searchresulttext]\n\n For more information about searching Wikipedia, see $1.\n\n {{MSGNW:searchresulttext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sectionedit&action=edit sectionedit]\n\n (section)\n\n {{MSGNW:sectionedit}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selectonly&action=edit selectonly]\n\n Only read-only queries are allowed.\n\n {{MSGNW:selectonly}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selflinks&action=edit selflinks]\n\n Pages with Self Links\n\n {{MSGNW:selflinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selflinkstext&action=edit selflinkstext]\n\n The following pages contain a link to themselves, which they should not.\n\n {{MSGNW:selflinkstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Servertime&action=edit servertime]\n\n Server time is now\n\n {{MSGNW:servertime}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Setbureaucratflag&action=edit setbureaucratflag]\n\n Set bureaucrat flag\n\n {{MSGNW:setbureaucratflag}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Shortpages&action=edit shortpages]\n\n Short pages\n\n {{MSGNW:shortpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Show&action=edit show]\n\n show\n\n {{MSGNW:show}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showhideminor&action=edit showhideminor]\n\n $1 minor edits\n\n {{MSGNW:showhideminor}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showingresults&action=edit showingresults]\n\n Showing below <b>$1</b> results starting with #<b>$2</b>.\n\n {{MSGNW:showingresults}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showingresultsnum&action=edit showingresultsnum]\n\n Showing below <b>$3</b> results starting with #<b>$2</b>.\n\n {{MSGNW:showingresultsnum}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showlast&action=edit showlast]\n\n Show last $1 images sorted $2.\n\n {{MSGNW:showlast}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showpreview&action=edit showpreview]\n\n Show preview\n\n {{MSGNW:showpreview}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showtoc&action=edit showtoc]\n\n show\n\n {{MSGNW:showtoc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sig_tip&action=edit sig_tip]\n\n Your signature with timestamp\n\n {{MSGNW:sig_tip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitestats&action=edit sitestats]\n\n Site statistics\n\n {{MSGNW:sitestats}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitestatstext&action=edit sitestatstext]\n\n There are <b>$1</b> total pages in the database.\nThis includes "talk" pages, pages about Wikipedia, minimal "stub"\npages, redirects, and others that probably don't qualify as articles.\nExcluding those, there are <b>$2</b> pages that are probably legitimate\narticles.<p>\nThere have been a total of <b>$3</b> page views, and <b>$4</b> page edits\nsince the software was upgraded (July 20, 2002).\nThat comes to <b>$5</b> average edits per page, and <b>$6</b> views per edit.\n\n {{MSGNW:sitestatstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitesubtitle&action=edit sitesubtitle]\n\n The Free Encyclopedia\n\n {{MSGNW:sitesubtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitesupport&action=edit sitesupport]\n\n Donations\n\n {{MSGNW:sitesupport}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitesupportpage&action=edit sitesupportpage]\n\n &lt;sitesupportpage&gt;\n\n {{MSGNW:sitesupportpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitetitle&action=edit sitetitle]\n\n Wikipedia\n\n {{MSGNW:sitetitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Skin&action=edit skin]\n\n Skin\n\n {{MSGNW:skin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Specialpages&action=edit specialpages]\n\n Special pages\n\n {{MSGNW:specialpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Spheading&action=edit spheading]\n\n Special pages for all users\n\n {{MSGNW:spheading}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sqlislogged&action=edit sqlislogged]\n\n Please note that all queries are logged.\n\n {{MSGNW:sqlislogged}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sqlquery&action=edit sqlquery]\n\n Enter query\n\n {{MSGNW:sqlquery}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Statistics&action=edit statistics]\n\n Statistics\n\n {{MSGNW:statistics}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Storedversion&action=edit storedversion]\n\n Stored version\n\n {{MSGNW:storedversion}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Stubthreshold&action=edit stubthreshold]\n\n Threshold for stub display\n\n {{MSGNW:stubthreshold}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subcategories&action=edit subcategories]\n\n Subcategories\n\n {{MSGNW:subcategories}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subject&action=edit subject]\n\n Subject/headline\n\n {{MSGNW:subject}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subjectpage&action=edit subjectpage]\n\n View subject\n\n {{MSGNW:subjectpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Successfulupload&action=edit successfulupload]\n\n Successful upload\n\n {{MSGNW:successfulupload}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Summary&action=edit summary]\n\n Summary\n\n {{MSGNW:summary}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysopspheading&action=edit sysopspheading]\n\n For sysop use only\n\n {{MSGNW:sysopspheading}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysoptext&action=edit sysoptext]\n\n The action you have requested can only be\nperformed by users with "sysop" status.\nSee $1.\n\n {{MSGNW:sysoptext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysoptitle&action=edit sysoptitle]\n\n Sysop access required\n\n {{MSGNW:sysoptitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tableform&action=edit tableform]\n\n table\n\n {{MSGNW:tableform}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkexists&action=edit talkexists]\n\n The page itself was moved successfully, but the\ntalk page could not be moved because one already exists at the new\ntitle. Please merge them manually.\n\n {{MSGNW:talkexists}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpage&action=edit talkpage]\n\n Discuss this page\n\n {{MSGNW:talkpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpagemoved&action=edit talkpagemoved]\n\n The corresponding talk page was also moved.\n\n {{MSGNW:talkpagemoved}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpagenotmoved&action=edit talkpagenotmoved]\n\n The corresponding talk page was <strong>not</strong> moved.\n\n {{MSGNW:talkpagenotmoved}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Textboxsize&action=edit textboxsize]\n\n Textbox dimensions\n\n {{MSGNW:textboxsize}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Textmatches&action=edit textmatches]\n\n Article text matches\n\n {{MSGNW:textmatches}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Thisisdeleted&action=edit thisisdeleted]\n\n View or restore $1?\n\n {{MSGNW:thisisdeleted}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Thumbnail-more&action=edit thumbnail-more]\n\n Enlarge\n\n {{MSGNW:thumbnail-more}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Timezoneoffset&action=edit timezoneoffset]\n\n Offset\n\n {{MSGNW:timezoneoffset}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Timezonetext&action=edit timezonetext]\n\n Enter number of hours your local time differs\nfrom server time (UTC).\n\n {{MSGNW:timezonetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Titlematches&action=edit titlematches]\n\n Article title matches\n\n {{MSGNW:titlematches}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Toc&action=edit toc]\n\n Table of contents\n\n {{MSGNW:toc}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uclinks&action=edit uclinks]\n\n View the last $1 changes; view the last $2 days.\n\n {{MSGNW:uclinks}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ucnote&action=edit ucnote]\n\n Below are this user's last <b>$1</b> changes in the last <b>$2</b> days.\n\n {{MSGNW:ucnote}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uctop&action=edit uctop]\n\n (top)\n\n {{MSGNW:uctop}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblockip&action=edit unblockip]\n\n Unblock user\n\n {{MSGNW:unblockip}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblockiptext&action=edit unblockiptext]\n\n Use the form below to restore write access\nto a previously blocked IP address or username.\n\n {{MSGNW:unblockiptext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblocklink&action=edit unblocklink]\n\n unblock\n\n {{MSGNW:unblocklink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblocklogentry&action=edit unblocklogentry]\n\n unblocked "$1"\n\n {{MSGNW:unblocklogentry}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undelete&action=edit undelete]\n\n Restore deleted page\n\n {{MSGNW:undelete}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletearticle&action=edit undeletearticle]\n\n Restore deleted article\n\n {{MSGNW:undeletearticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletebtn&action=edit undeletebtn]\n\n Restore!\n\n {{MSGNW:undeletebtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletedarticle&action=edit undeletedarticle]\n\n restored "$1"\n\n {{MSGNW:undeletedarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletedtext&action=edit undeletedtext]\n\n The article [[$1]] has been successfully restored.\nSee [[Wikipedia:Deletion_log]] for a record of recent deletions and restorations.\n\n {{MSGNW:undeletedtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletehistory&action=edit undeletehistory]\n\n If you restore the page, all revisions will be restored to the history.\nIf a new page with the same name has been created since the deletion, the restored\nrevisions will appear in the prior history, and the current revision of the live page\nwill not be automatically replaced.\n\n {{MSGNW:undeletehistory}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletepage&action=edit undeletepage]\n\n View and restore deleted pages\n\n {{MSGNW:undeletepage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletepagetext&action=edit undeletepagetext]\n\n The following pages have been deleted but are still in the archive and\ncan be restored. The archive may be periodically cleaned out.\n\n {{MSGNW:undeletepagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeleterevision&action=edit undeleterevision]\n\n Deleted revision as of $1\n\n {{MSGNW:undeleterevision}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeleterevisions&action=edit undeleterevisions]\n\n $1 revisions archived\n\n {{MSGNW:undeleterevisions}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unexpected&action=edit unexpected]\n\n Unexpected value: "$1"="$2".\n\n {{MSGNW:unexpected}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockbtn&action=edit unlockbtn]\n\n Unlock database\n\n {{MSGNW:unlockbtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockconfirm&action=edit unlockconfirm]\n\n Yes, I really want to unlock the database.\n\n {{MSGNW:unlockconfirm}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdb&action=edit unlockdb]\n\n Unlock database\n\n {{MSGNW:unlockdb}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbsuccesssub&action=edit unlockdbsuccesssub]\n\n Database lock removed\n\n {{MSGNW:unlockdbsuccesssub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbsuccesstext&action=edit unlockdbsuccesstext]\n\n The database has been unlocked.\n\n {{MSGNW:unlockdbsuccesstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbtext&action=edit unlockdbtext]\n\n Unlocking the database will restore the ability of all\nusers to edit pages, change their preferences, edit their watchlists, and\nother things requiring changes in the database.\nPlease confirm that this is what you intend to do.\n\n {{MSGNW:unlockdbtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectedarticle&action=edit unprotectedarticle]\n\n unprotected [[$1]]\n\n {{MSGNW:unprotectedarticle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectthispage&action=edit unprotectthispage]\n\n Unprotect this page\n\n {{MSGNW:unprotectthispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unusedimages&action=edit unusedimages]\n\n Unused images\n\n {{MSGNW:unusedimages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unusedimagestext&action=edit unusedimagestext]\n\n <p>Please note that other web sites\nsuch as the international Wikipedias may link to an image with\na direct URL, and so may still be listed here despite being\nin active use.\n\n {{MSGNW:unusedimagestext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unwatchthispage&action=edit unwatchthispage]\n\n Stop watching\n\n {{MSGNW:unwatchthispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Updated&action=edit updated]\n\n (Updated)\n\n {{MSGNW:updated}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Upload&action=edit upload]\n\n Upload file\n\n {{MSGNW:upload}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadbtn&action=edit uploadbtn]\n\n Upload file\n\n {{MSGNW:uploadbtn}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploaddisabled&action=edit uploaddisabled]\n\n Sorry, uploading is disabled.\n\n {{MSGNW:uploaddisabled}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadedfiles&action=edit uploadedfiles]\n\n Uploaded files\n\n {{MSGNW:uploadedfiles}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadedimage&action=edit uploadedimage]\n\n uploaded "$1"\n\n {{MSGNW:uploadedimage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploaderror&action=edit uploaderror]\n\n Upload error\n\n {{MSGNW:uploaderror}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadfile&action=edit uploadfile]\n\n Upload images, sounds, documents etc.\n\n {{MSGNW:uploadfile}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlink&action=edit uploadlink]\n\n Upload images\n\n {{MSGNW:uploadlink}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlog&action=edit uploadlog]\n\n upload log\n\n {{MSGNW:uploadlog}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlogpage&action=edit uploadlogpage]\n\n Upload_log\n\n {{MSGNW:uploadlogpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlogpagetext&action=edit uploadlogpagetext]\n\n Below is a list of the most recent file uploads.\nAll times shown are server time (UTC).\n<ul>\n</ul>\n\n\n {{MSGNW:uploadlogpagetext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadnologin&action=edit uploadnologin]\n\n Not logged in\n\n {{MSGNW:uploadnologin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadnologintext&action=edit uploadnologintext]\n\n You must be <a href="/wiki/Special:Userlogin">logged in</a>\nto upload files.\n\n {{MSGNW:uploadnologintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadtext&action=edit uploadtext]\n\n <strong>STOP!</strong> Before you upload here,\nmake sure to read and follow the <a href="/wiki/Wikipedia:Image_use_policy">image use policy</a>.\n<p>If a file with the name you are specifying already\nexists on the wiki, it'll be replaced without warning.\nSo unless you mean to update a file, it's a good idea\nto first check if such a file exists.\n<p>To view or search previously uploaded images,\ngo to the <a href="/wiki/Special:Imagelist">list of uploaded images</a>.\nUploads and deletions are logged on the <a href="/wiki/Wikipedia:Upload_log">upload log</a>.\n<p>Use the form below to upload new image files for use in\nillustrating your articles.\nOn most browsers, you will see a "Browse..." button, which will\nbring up your operating system's standard file open dialog.\nChoosing a file will fill the name of that file into the text\nfield next to the button.\nYou must also check the box affirming that you are not\nviolating any copyrights by uploading the file.\nPress the "Upload" button to finish the upload.\nThis may take some time if you have a slow internet connection.\n<p>The preferred formats are JPEG for photographic images, PNG\nfor drawings and other iconic images, and OGG for sounds.\nPlease name your files descriptively to avoid confusion.\nTo include the image in an article, use a link in the form\n<b>[[image:file.jpg]]</b> or <b>[[image:file.png|alt text]]</b>\nor <b>[[media:file.ogg]]</b> for sounds.\n<p>Please note that as with wiki pages, others may edit or\ndelete your uploads if they think it serves the encyclopedia, and\nyou may be blocked from uploading if you abuse the system.\n\n {{MSGNW:uploadtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadwarning&action=edit uploadwarning]\n\n Upload warning\n\n {{MSGNW:uploadwarning}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userexists&action=edit userexists]\n\n The user name you entered is already in use. Please choose a different name.\n\n {{MSGNW:userexists}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userlogin&action=edit userlogin]\n\n Log in\n\n {{MSGNW:userlogin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userlogout&action=edit userlogout]\n\n Log out\n\n {{MSGNW:userlogout}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userpage&action=edit userpage]\n\n View user page\n\n {{MSGNW:userpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userstats&action=edit userstats]\n\n User statistics\n\n {{MSGNW:userstats}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userstatstext&action=edit userstatstext]\n\n There are <b>$1</b> registered users.\n<b>$2</b> of these are administrators (see $3).\n\n {{MSGNW:userstatstext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Version&action=edit version]\n\n Version\n\n {{MSGNW:version}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewcount&action=edit viewcount]\n\n This page has been accessed $1 times.\n\n {{MSGNW:viewcount}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewprevnext&action=edit viewprevnext]\n\n View ($1) ($2) ($3).\n\n {{MSGNW:viewprevnext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewsource&action=edit viewsource]\n\n View source\n\n {{MSGNW:viewsource}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewtalkpage&action=edit viewtalkpage]\n\n View discussion\n\n {{MSGNW:viewtalkpage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wantedpages&action=edit wantedpages]\n\n Wanted pages\n\n {{MSGNW:wantedpages}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchdetails&action=edit watchdetails]\n\n ($1 pages watched not counting talk pages;\n$2 total pages edited since cutoff;\n$3...\n<a href='$4'>show and edit complete list</a>.)\n\n {{MSGNW:watchdetails}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watcheditlist&action=edit watcheditlist]\n\n Here's an alphabetical list of your\nwatched pages. Check the boxes of pages you want to remove\nfrom your watchlist and click the 'remove checked' button\nat the bottom of the screen.\n\n {{MSGNW:watcheditlist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlist&action=edit watchlist]\n\n My watchlist\n\n {{MSGNW:watchlist}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlistcontains&action=edit watchlistcontains]\n\n Your watchlist contains $1 pages.\n\n {{MSGNW:watchlistcontains}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlistsub&action=edit watchlistsub]\n\n (for user "$1")\n\n {{MSGNW:watchlistsub}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchmethod-list&action=edit watchmethod-list]\n\n checking watched pages for recent edits\n\n {{MSGNW:watchmethod-list}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchmethod-recent&action=edit watchmethod-recent]\n\n checking recent edits for watched pages\n\n {{MSGNW:watchmethod-recent}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnochange&action=edit watchnochange]\n\n None of your watched items were edited in the time period displayed.\n\n {{MSGNW:watchnochange}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnologin&action=edit watchnologin]\n\n Not logged in\n\n {{MSGNW:watchnologin}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnologintext&action=edit watchnologintext]\n\n You must be <a href="/wiki/Special:Userlogin">logged in</a>\nto modify your watchlist.\n\n {{MSGNW:watchnologintext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchthis&action=edit watchthis]\n\n Watch this article\n\n {{MSGNW:watchthis}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchthispage&action=edit watchthispage]\n\n Watch this page\n\n {{MSGNW:watchthispage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Welcomecreation&action=edit welcomecreation]\n\n <h2>Welcome, $1!</h2><p>Your account has been created.\nDon't forget to personalize your wikipedia preferences.\n\n {{MSGNW:welcomecreation}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whatlinkshere&action=edit whatlinkshere]\n\n What links here\n\n {{MSGNW:whatlinkshere}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistacctext&action=edit whitelistacctext]\n\n To be allowed to create accounts in this Wiki you have to [[Special:Userlogin|log]] in and have the appropriate permissions.\n\n {{MSGNW:whitelistacctext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistacctitle&action=edit whitelistacctitle]\n\n You are not allowed to create an account\n\n {{MSGNW:whitelistacctitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistedittext&action=edit whitelistedittext]\n\n You have to [[Special:Userlogin|login]] to edit articles.\n\n {{MSGNW:whitelistedittext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistedittitle&action=edit whitelistedittitle]\n\n Login required to edit\n\n {{MSGNW:whitelistedittitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistreadtext&action=edit whitelistreadtext]\n\n You have to [[Special:Userlogin|login]] to read articles.\n\n {{MSGNW:whitelistreadtext}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistreadtitle&action=edit whitelistreadtitle]\n\n Login required to read\n\n {{MSGNW:whitelistreadtitle}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wikipediapage&action=edit wikipediapage]\n\n View meta page\n\n {{MSGNW:wikipediapage}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wikititlesuffix&action=edit wikititlesuffix]\n\n Wikipedia\n\n {{MSGNW:wikititlesuffix}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wlnote&action=edit wlnote]\n\n Below are the last $1 changes in the last <b>$2</b> hours.\n\n {{MSGNW:wlnote}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wlsaved&action=edit wlsaved]\n\n This is a saved version of your watchlist.\n\n {{MSGNW:wlsaved}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wlshowlast&action=edit wlshowlast]\n\n Show last $1 hours $2 days $3\n\n {{MSGNW:wlshowlast}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wrong_wfQuery_params&action=edit wrong_wfQuery_params]\n\n Incorrect parameters to wfQuery()<br>\nFunction: $1<br>\nQuery: $2\n\n\n {{MSGNW:wrong_wfQuery_params}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wrongpassword&action=edit wrongpassword]\n\n The password you entered is incorrect. Please try again.\n\n {{MSGNW:wrongpassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yourdiff&action=edit yourdiff]\n\n Differences\n\n {{MSGNW:yourdiff}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Youremail&action=edit youremail]\n\n Your e-mail*\n\n {{MSGNW:youremail}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yourname&action=edit yourname]\n\n Your user name\n\n {{MSGNW:yourname}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yournick&action=edit yournick]\n\n Your nickname (for signatures)\n\n {{MSGNW:yournick}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yourpassword&action=edit yourpassword]\n\n Your password\n\n {{MSGNW:yourpassword}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yourpasswordagain&action=edit yourpasswordagain]\n\n Retype password\n\n {{MSGNW:yourpasswordagain}}\n
\n [http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Yourtext&action=edit yourtext]\n\n Your text\n\n {{MSGNW:yourtext}}\n
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  91. Wikipedia:How to use tables (2 links)
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','',0,'217.160.250.182','20040401165556','sysop',0,0,0,0,0.913210892969007,'20040401165556','79959598834443'); INSERT INTO cur VALUES (574,4,'!Orphaned_articles','
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Alkémi to Énsiklopédi
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\'\'\'Républik Indonésia\'\'\'
\n\n\n\n\n\n
[[Image:Bandera_indonesia.png|125px|Bandéra Indonesia]][[Image:Indonesiacoatofarms.jpg|Lambang Nagara Indonesia]]
([[Bandéra Indonésia|Detil]])(ukuran pinuh)
\'\'[[Motto]] nasional: [[Bhinneka Tunggal Ika]] ([[basa Sangsakerta]]): Nunggal dina karageman)\'\'
[[image:LocationIndonesia.png]]
[[Basa Nasional]] [[Basa Indonésia]]
[[Ibukota]] [[Jakarta]]
[[Daptar Présidén Indonésia|Présidén]] [[Megawati Soekarnoputri]]
[[Lega]]
 - Total:
 - % cai:
[[Daptar nagara dumasar lega|Urutan ka-15]]
[[1 E12 m²|1,919,440 km²]]
4.85%
[[Populasi]] \n
 - Total ([[2003]]): \n
 - [[Dénsitas]]:
[[Daptar nagara dumasar populasi|Urutan ka-4]]\n
234,893,453 \n
119/km²
[[Merdika]]\n
 - Déklarasi:\n
 - Diaku:
Ti [[Walanda]]\n
[[17 Agustus]] [[1945]]\n
[[27 Désémber]] [[1949]]
[[Mata uang]]: [[Rupiah]]
[[Wewengkon wanci]]: [[UTC]] +7 to [[UTC]] +9
[[Lagu kabangsaan]]: [[Indonesia Raya]]
[[Top-level domain|Internet TLD]]:.ID
[[Daptar nagara dumasar kode telepon|Kode Telepon]]62
\n\n== Sajarah ==\n\'\'Artikel Utama: [[Sajarah Indonésia]]\'\'\n\nDina pangaruh [[Buda]], aya sababaraha karajaan di pulo [[Sumatra]] jeung [[Pulo Jawa|Jawa]] ti [[abad ka-7]] nepi ka [[abad ka-14]]. Saterusna datang sodagar-sodagar ti [[Arab]] mawa [[Islam]], nu ka béh dieunakeun jadi agama mayoritas.\n\nNalika bangsa [[Éropa]] datang mangsa munggaran [[abad ka-16]], maranéhna manggihan rupa-rupa nagara leutik. Kabitaeun pisan bangsa Éropa, nu mémang keur karanjingan ngawasa dadagangan rempah-rempah. [[Abad ka-17]], bangsa [[Walanda]] nanjung jadi salasahiji nagara Éropa pangkuatna, ngawasa Nusantara kalawan ngalindih [[Inggris]] jeung [[Portugal]] (iwal [[Timor]]). \n\nSatutasna [[Maskapé Hindia Wétan|VOC]] dibubarkeun, kakawasaanana di Indonésia dicepeng ku Pamaréntah Walanda. Satutasna leupas tina pangjajah [[Jepang]] taun [[1945]], bangsa Indonésia ngabéwarakeun kamerdikaan dipingpin ku [[Sukarno]]. Walanda ahirna narima, najan elat, dina taun [[1949]]. Ti ngadegna Indonesia, Sukarno diangkat jadi présidén munggaran.\n\n[[Suharto]] jadi présidén ([[1968]]) satutasna ngagulingkeun Sukarno nu pamaréntahanana jadi otokratik. Alatan pamaréntahanana nu subur ku polah korup, Suharto dipaksa mundur taun [[1998]].\n\n== Pulitik ==\n\'\'Artikel utama: [[Pulitik Indonesia]]\'\'\n\nKakawasaan éksékutif dicepeng ku présidén jeung para mentrina. Parlemén Indonésia bentukna bi-kameral, mangrupa Majelis Permusyawaratan Rakyat (MPR) jeung Dewan Perwakilan Rakyat, duanana dipilih unggal 5 taun.\n\n== Propinsi ==\n\'\'Kaca Utama: [[Propinsi di Indonésia]]\'\'\n\nAyeuna, Indonésia ngabogaan 30 propinsi, 2 daérah istiméwa jeung 1 daérah husus ibukota. Propinsi-propinsi ieu dibagi deui jadi [[kabupatén]]-kabupatén, nu salajengna dibagi deui jadi [[kacamatan]] jeung kota administratif. Propinsi-propinsina nyaéta,\n\n[[Bali]],\n[[Bangka-Belitung]],\n[[Banten]],\n[[Bengkulu]],\n[[Jawa Tengah]],\n[[Kalimantan Tengah]],\n[[Sulawesi Tengah]], \n[[Jawa Wétan]],\n[[Kalimantan Wétan]],\n[[Nusa Tenggara Wétan]],\n[[Sumatra Kidul]],\n[[Gorontalo]],\n[[Jambi]], \n[[Lampung]], \n[[Maluku]], \n[[Maluku Kalér]], \n[[Sulawesi Kalér]],\n[[Sumatra Kalér]],\n[[Papua (Indonésia)|Papua]] (Irian Jaya),\n[[Riau]],\n[[Sulawesi Tenggara]],\n[[Kalimantan Kidul]],\n[[Sulawesi Kidul]],\n[[Irian Jaya Kulon]],\n[[Jawa Kulon]],\n[[Kalimantan Kulon]],\n[[Nusa Tenggara Kulon]],\n[[Sumatra Kulon]]\n\nDaérah-daérah hususna (\'\'daérah istiméwa\'\', DI) nyaéta [[Acéh]] jeung [[Jogjakarta]], sedengkeun daérah husus ibukotana [[Jakarta]].\n\n[[Kapuloan Riau]] bakal jadi propinsi sorangan, misah ti propinsi [[Riau]].\n\n==Géografi==\n\'\'Kaca Utama: [[Géografi Indonésia]]\'\'\n\n[[Image:Id-map.png|thumb|336px|right|Peta Indonésia]]\n\nTempo ogé: [[Asia#Peta|Peta Asia]]\n\n== Ekonomi ==\n\n\'\'Kaca Utama: [[Indonésia Ekonomi]]\'\'\n\n\n== Démografi ==\n\n\'\'Kaca utama: [[Démografi Indonesia]]\'\'\n\nPopulasi Indonésia sacara kasar bisa dibagi kana dua kelompok. Di beulah kulon, umumna dieusi ku urang [[urang Malayu|Malayu]], sedengkeun di wewengkon wétan nyaéta urang [[Papua]]. Sanajan kitu, struktur sélér sabenerna leuwih rupa-rupa, katambah ku sélér-sélér tradisional nu aya di Bornéo/Kalimantan jeung Papua. Urang [[Cina Indonésia|Cina]] ngabentuk hiji sélér minoritas (2 nepi ka 3 juta).\n\n[[Islam]] mangrupa agama nu utama di Indonesia, ampir 87% ngagem agama ieu. Sesana ngagem agama [[Kristen]] (9%), [[Buda]] (2%), jeung [[Hindu]] (1%), nu panungtungan lolobana aya di [[Bali]]. Koflik antaragama rada mindeng dina taun-taun ieu, utamana di [[Maluku]].\n\nBasa nasional, [[Bahasa Indonesia]] - hiji dialék [[basa Malayu]] - dipaké ku ampir sakabéh warga, sanajan dialék lokal biasana masih lumaku salaku basa poko.\n\n== Budaya ==\n\n\'\'Artikel utama: [[Budaya Indonesia]]\'\'\n\nWujud seni di Indonesia dipangaruhan ku sababaraha budaya. Misalna Ibing Jawa jeung ibing Bali nu geus kakoncara, dipangaruhan ku budaya jeung mitologi [[Hindu]].\n\nPintonan [[wayang kulit]] Jawa nu ogé geus kakoncara, nunjukkeun sababaraha kajadian mitologis.\n\nDina bukuna [[Max Havelaar]], pangarang [[Walanda]] [[Multatuli]] ngritik kalakuan pamarentahna (Pamarentah jajahan Walanda) ka Bangsa Indonesia, meunangkeun perhatian internasional.\n\n*[[Musik Indonesia]]\n\n==Bacaan salajengna==\n* \'\'\'Theodore Friend\'\'\', \'\'Indonesian Destinies\'\', [http://www.hup.harvard.edu/ Harvard University Press], 2003, jilid heuras, 544 kaca, ISBN 0674011376\n\n==Tumbu kaluar==\n\n* [http://www.indonesia.go.id/ www.indonesia.go.id - Jalaloka resmi Républik Indonésia] (basa Indonésia)\n* [http://www.info-ri.com/ Info-RI - Jalaloka Informasi Nasional] (basa Indonésia)\n* Antara - Kantor Iber Nasional (sadia boh dina [http://www.antara.co.id/english.asp basa Inggris] jeung [http://www.antara.co.id/indonesia.asp basa Indonésia])\n* [http://www.HavenWorks.com/world/indonesia Iber Indonesia] \n* [http://www.ngobrol.com Masarakat \'\'Online\'\' Indonésia]\n\n{{ASEAN}}\n{{OKI}}\n\n[[cy:Indonesia]]\n[[da:Indonesien]]\n[[de:Indonesien]]\n[[en:Indonesia]]\n[[eo:Indonezio]]\n[[es:Indonesia]]\n[[et:Indoneesia]]\n[[fr:Indonésie]]\n[[id:Indonesia]]\n[[ja:インドネシア]]\n[[jv:Indonesia]]\n[[ms:Indonesia]]\n[[nl:Indonesië]]\n[[no:Indonesia]]\n[[pl:Indonezja]]\n[[pt:Indonésia]]\n[[ru:Индонезия]]\n[[simple:Indonesia]]\n[[sl:Indonezija]]\n[[sr:Индонезија]]\n[[sv:Indonesien]]\n[[th:ประเทศอินโดนีเซีย]]\n[[tl:Indonesia]]\n[[zh-cn:印度尼西亚]]','/* Sajarah */',3,'Kandar','20050223153558','',0,0,1,0,0.490396511038,'20050315102836','79949776846441'); INSERT INTO cur VALUES (604,0,'Kimia','\'\'\'Kimia\'\'\' ngarupakeun [[élmu]] ngeunaan struktur, sipat, wangunan, jeung [[réaksi kimiawi|réaksi]] [[unsur kimiawi|unsur]] jeung [[sanyawa kimiawi]].\n\n==Cabang-cabang kimia==\nKimia sacara husus dibagi kana sababaraha cabang utama, sababaraha nu sipatna meuntas-disiplin, sarta cabang-cabang nu leuwih husus.\n\n; [[Kimia organik]] : \'\'Kimia organik\'\' ngarupakeun élmu struktur, sipat, wangunan, jeung réaksi sanyawa organik. \n\n; [[Kimia anorganik]] : \'\'Kimia anorganik\'\' ngarupakeun cabang kimia nu patali jeung sipat sarta réaksi sanyawa anorganik. Béda antara disiplin organik jeung anorganik sipatna teu mutlak, malah loba tumpang tindihna, utamana dina subdisiplin [[kimia organologam]].\n\n; [[Kimia fisik]] : \'\'Kimia fisik\'\' ngarupakeun ulikan ngeunaan dasar fisik sistem-sistem jeung prosés kimiawi. Kimia modern kalawan teges ngadeg dina dadasar [[fisika]] sarta kimia fisik salaku tumbu langsungna. Widang ulikan nu penting di antarana [[térmodinamik kimiawi]], [[kinetik]] kimiawi, [[kimia kuantum]], [[mékanik statistis]], jeung [[spéktroskopi]].\n\n; [[Biokimia]] : \'\'Biokimia\'\' ngarupakeun ulikan ngeunaan [[bahan kimiawi|bahan]], [[réaksi kimiawi|réaksi]], jeung [[interaksi]] kimiawi nu aya na [[organisme]] hirup. \n\n; [[Kimia analitis]] : \'\'Kimia analitis\'\' ngulik [[analisis]] sampel/conto bahan pikeun mikanyaho [[wangunan kimiawi|wangunan]] jeung [[struktur kimiawi]]na.\n\n; Cabang Minor : [[Élmu bahan]], [[Kimia polimér]], [[Kimia lingkungan]], [[Farmakologi]], [[Térmokimia]], [[Kimia inti]], [[Éléktrokimia]], [[Kimia komputasional]]\n\n==Konsép dasar==\n\n===Tata ngaran===\n\'\'Artikel utama: [[Tata ngaran zat kimia]].\'\' \n\nTata ngaran dimaksudkeun kana sistem pikeun méré ngaran [[sanyawa kimiawi]]. [[Sanyawa organik]] dingaranan nurutkeun sistem [[tata ngaran organik]]. [[Sanyawa anorganik]] dingaranan nurutkeun sistem [[tata ngaran anorganik]].\n\n===Atom===\n\'\'Artikel utama: [[Atom]].\'\'\n\n\'\'Atom\'\' ngarupakeun bagéan tina sistem kimiawi pangleutikna nu teu bisa dibeulah/dibagi-bagi deui.\n\n===Unsur===\n\'\'Artikel utama: [[Unsur kimiawi]].\'\'\n\n\'\'Unsur\'\' ngarupakeun bahan nu ngawengku [[atom|atom-atom]] nu boga wilangan/jumlah [[proton]] nu tinangtu dina [[inti atom|inti]]na. Wilangan ieu dipiwanoh salaku [[wilangan atom]] unsur. Conto, sakabéh atom nu boga 6 proton na intina disebut atom unsur [[karbon]], sedengkeun sakabéh atom nu boga 92 proton na intina disebut unsur [[uranium]].\n\nPintonan nu pangmerenahna pikeun unsur-unsur aya dina [[tabel periodik]], nu ngagolongkeun unsur-unsur dumasar kamiripan sipat kimiawina. Daptar unsur ogé bisa ditempo dina susunan [[Daptar unsur dumasar ngaran]], [[Daptar unsur dumasar lambang|dumasar lambang]], jeung [[Daptar unsur dumasar wilangan atom|dumasar wilangan atom]].\n\n===Sanyawa===\n\'\'Artikel utama: [[Sanyawa kimiawi]]\'\'\n\n\'\'Sanyawa\'\' ngarupakeun zat nu dibentuk tina dua atawa leuwih [[unsur]] dina babandingan nu tetep nu nangtukeun wangunanna. Misal, [[cai]] ngarupakeun sanyawa nu ngandung [[hidrogén]] jeung [[oksigén]] dina babandingan dua ka hiji. Sanyawa dibentuk jeung dibeulah ku [[réaksi kimiawi]].\n\n===Molekul===\n\'\'Artikel utama: [[Molekul]].\'\'\n\n\'\'Molekul\'\' ngarupakeun bagéan pangleutikna nu teu bisa dibeulah deui tina hiji [[sanyawa kimiawi]] nu mibanda sipat kimiawi jeung fisik unik nu tinangtu. Hiji molekul diwangun ku dua atawa leuwih [[atom]] nu [[Beungkeut kimiawi|kabeungkeut]].\n\n===Beungkeutan===\n\'\'Artikel utama: [[Beungkeut kimiawi]].\'\'\n\n\'\'Beungkeut kimiawi\'\' ngarupakeun gaya nu nahan ngabeungkeut atom-atom dina [[molekul]] atawa [[kristal]]. Dina loba sanyawa basajan, [[tiori beungkeut valénsi]] jeung konsép [[wilangan oksidasi]] bisa dipaké pikeun ngaduga-duga struktur jeung wangunan molekular. Nu sarupa, tiori-tiori tina [[fisika klasik]] bisa dipaké pikeun ngaduga-duga struktur-struktur ionik. Mun diterapkeun ka sanyawa nu leuwih pajeulit, samodél [[kompléks]] logam, tiori beungkeut valénsi gagal, jeung kudu aya pangaweruh nu leuwih jero nu dumasar kana [[mékanika kuantum]].\n\n===Wujud zat===\n\'\'Artikel utama: [[Fase (zat)]].\'\'\n\n\'\'Fase\'\' ngarupakeun hiji wujud sistem fisik makroskopis nu mibanda wangunan kimiawi jeung sipat fisik nu rélatif sarua/saragam (nyaéta [[dénsiti]], [[struktur kristal]], [[indéks réfraktif]], jsb.). Conto fase nu urang paling wawuh nyaéta [[padet]], [[cair]], jeung [[gas]]. Fase nu teu pati dipikawanoh di antarana [[plasma]], [[kondensat Bose-Einstein]], [[kondensat fermionik]], jeung fase bahan [[magnet]]ik [[paramagnetism|paramagnetik]] sarta [[ferromagnetism|ferromagnetik]].\n\n===Réaksi===\n\'\'Artikel utama: [[Réaksi kimiawi]].\'\'\n\n\'\'Réaksi kimiawi\'\' ngarupakeun transformasi/parobahan dina [[struktur]] [[molekul]]. Réaksi kieu bisa ngahasilkeun napelna hiji molekul ka nu séjénna pikeun ngawangun molekul nu leuwih gedé, beulahna molekul jadi dua atawa leuwih molekul nu leuwih leutik, atawa [[wangun-ulang]] [[atom]]-atom dina jero molekul. Réaksi kimiawi salawasna ngalibetkeun dibentuk atawa dipegatkeunana [[beungkeut kimiawi]].\n\n===Tiori kuantum===\n\'\'Artikel utama: [[Tiori kuantum]].\'\'\n\n\'\'Tiori kuantum\'\' ngagambarkeun paripolah [[zat]] dina skala nu heureut pisan. Ieu téh, prinsipna mah, ngamungkinkeun pikeun ngagambarkeun sakabéh sistem kimiawi ngagunakeun tiori ieu, tapi sacara matematis rumit sarta teu bisa diduga-duga. Praktékna, ukur sistem kimiawi nu pangbasajanna nu bisa réalistis ditalungtik dina kontéks mékanika kuantum murni, ieu gé lumangsung maké loba \'\'pendekatan/perkiraan\'\' (misalna \'\'[[Density functional theory]]\'\'). Ku sabab éta, pangaweruh mékanika kuantum nu leuwih jero tur mérélé teu pati perlu pikeun kalolobaan kimia, da penting aubna tiori ieu (hususna \'\'[[orbital atom|pendekatan orbital]])\'\' bisa dilenyepan sarta diterapkeun dina kontéks nu leuwih basajan.\n\n===Hukum===\n\'\'Hukum-hukum kimiawi\'\' sabenerna ngarupakeun [[hukum fisika]] hu diterapkeun na sistem kimiawi. \n\nKonsép paling \'\'fundaméntal\'\' dina kimia nyaéta \'\'[[Hukum konservasi massa]]\'\' nu ngunikeun yén teu aya parobahan kuantitas zat nu kaukur dina hiji [[réaksi kimiawi]] biasa. Fisika modern mintonkeun yén tétéla [[énergi]] nu \'\'conserved\'\', jeung yén énergi jeung massa raket [[Einstein#Kasatimbangan énergi|patalina]]. [[Konservasi énergi]] saterusna nungtun kana konsép penting ngeunaan [[kasatimbangan]], [[térmodinamik]], jeung [[kinetik]].\n\n==Sajarah kimia==\n*[[Alkémi]]\n*[[Papanggihan unsur-unsur kimiawi]]\n*[[Timeline of chemical element discovery]]\n*[[Hadiah Nobel widang kimia]]\n\n===Étimologi===\nPrancis Kuna: \'\'alkemie\'\'; Arab \'\'al-kimia\'\': \'\'seni transformasi\'\'.\n\n== Tempo ogé ==\n* [[Daptar jejer kimia]]\n* [[Kimiawan]] jeung [[Daptar kimiawan]]\n* [[American Chemical Society]]\n* [[International Union of Pure and Applied Chemistry]]\n* [[Téhnik kimiawi]]\n* [[Tabel periodik]]\n* [[Daptar sanyawa]]\n* [[Daptar publikasi kimia|Daptar publikasi penting widang kimia]]\n\n==Tumbu kaluar jeung sumber séjén==\n\n===Tumbu===\n* [[wikibooks:Chemistry|Buku téks kimia umum]] na [[wikibooks:Main_Page|Bukuwiki]]\n* [http://www.chem.qmw.ac.uk/iupac/ Rohangan Tata ngaran IUPAC], tempo hususna \"\'\'Gold Book\'\'\" nu ngandung pedaran ngeunaan istilah-istilah kimiawi baku\n* [http://physchem.ox.ac.uk/MSDS/ Lambaran bahan kasalametan pikeun rupa-rupa bahan kimiawi]\n\n===Bacaeun salajengna===\nChang, Raymond. Chemistry. 6th ed. Boston: James M. Smith, 1998. ISBN 0071152210.\n\n{{CabangKimia}}\n\n\n\n[[Category:Élmu alam]]\n[[Category:Kimia]]\n\n[[af:Skeikunde]]\n[[als:Chimie]]\n[[bg:Химия]]\n[[ca:Química]]\n[[co:Chimia]]\n[[cs:Chemie]]\n[[cy:Cemeg]]\n[[da:Kemi]]\n[[de:Chemie]]\n[[el:Χημεία]]\n[[en:Chemistry]]\n[[eo:Kemio]]\n[[es:Química]]\n[[et:Keemia]]\n[[eu:Kimika]]\n[[fa:شیمی]]\n[[fi:Kemia]]\n[[fr:Chimie]]\n[[gl:Química]]\n[[he:כימיה]]\n[[hr:Kemija]]\n[[hu:Kémia]]\n[[ia:Chimia]]\n[[id:Kimia]]\n[[is:Efnafræði]]\n[[it:Chimica]]\n[[ja:化学]]\n[[ko:화학]]\n[[la:Chemica]]\n[[lb:Chimie]]\n[[lt:Chemija]]\n[[lv:Ķīmija]]\n[[mi:Mātauranga matū]] \n[[ms:Kimia]]\n[[nds:Chemie]]\n[[nl:Scheikunde]]\n[[no:Kjemi]]\n[[oc:Quimia]]\n[[pl:Chemia]]\n[[pt:Química]]\n[[ro:Chimie]]\n[[ru:Химия]]\n[[simple:Chemistry]]\n[[sl:Kemija]]\n[[sr:Хемија]]\n[[sv:Kemi]]\n[[sw:Kemia]]\n[[th:เคมี]]\n[[tl:Kimika]]\n[[tr:Kimya]]\n[[tt:Ximiä]]\n[[uk:Хімія]]\n[[vi:Hoá học]]\n[[zh-cn:化学]]\n[[zh-tw:化学]]','',3,'Kandar','20050221032246','',0,0,1,0,0.288995395549,'20050221032246','79949778967753'); INSERT INTO cur VALUES (605,0,'Wikipédia:Wilujeng_sumping','{{msg:communitypage}}\n\n[http://en.wikipedia.org/wiki/Wikipedia Wikipédia] ngarupakeun [[Énsiklopédi|énsiklopédi]] nu ditulis babarengan ku nu maracana. Situs ieu ngarupakeun [http://en.wikipedia.org/wiki/WikiWiki WikiWiki], nu hartina sing saha waé, kaasup \'\'\'anjeun\'\'\', bisa ngédit artikel mana waé ku jalan nga-klik tumbu \'\'\'édit\'\'\' nu aya di kéncaeun/luhureun unggal kaca artikel Wikipédia.\n\n== Nyungsi Wikipédia ==\n\nWikipédia ngandung informasi nu kalintang lobana dina sagala widang/subjék. Kanggo ningalan, mangga sumping ka [[Tepas]], pilari subjek nu kira-kirana dipikaresep/narik, salajengna mah wilujeng ngalanglang baé. Tiasa ogé nganggo kotak \'\'pilari\'\' luhureun unggal kaca.\n\nMun anjeun manggih (maca maksud téh) artikel nu dipikaresep, dihaturan pisan kanggo masihan catetan atawa koméntar na [http://en.wikipedia.org/wiki/Wikipedia%3ATalk_page kaca omongan] artikel éta. Mimiti, pilih kaitan \'\'Sawalakeun kaca ieu\'\' (téang di beulah kéncaeun kaca) sangkan nepi ka kaca omong, teras pilih \'\'\'Édit kaca ieu\'\'\' na kaca omongan. Kacida bungahna mun kami meunang eupan pangrojong ti sadaya.\n\nIf there\'s something we don\'t cover, or you\'re having difficulty finding what you\'re after, just ask us at the [http://en.wikipedia.org/wiki/Wikipedia%3AReference_desk reference desk], or add the topic to our list of [[wikipedia:requested articles|requested articles]].\n\n== Ngédit ==\n\nSing saha baé bisa ngédit eusi kaca Wikipédia (kaasup kaca ieu!). Mun sakirana aya nu perlu diropéa, klik baé kaitan \'\'\'Édit kaca ieu\'\'\' di luhureun atawa handapeun kacana. Anjeun teu perlu jadi anggota; [http://en.wikipedia.org/wiki/Wikipedia:How_to_log_in asup] gé teu perlu malah mah.\n\nSalah sahiji cara nu gampang pikeun ngamimitian ngilu aub ngabantuan, nya ku ngamangpaatkeun Wikipédia sakumaha anjeun ngagunakeun énsiklopédi. Ngan, mun anjeun manggih masalah—salah tulis, sugan, atawa kalimah nu teu merenah—klik \"Edit kaca ieu\", sok benerkeun. [http://en.wikipedia.org/wiki/Wikipedia:Be_bold_in_updating_pages Sing wijak dina ngoréksi kaca téh]; mun anjeun boga kereteg pikeun ngalengkepan hiji kaca, sok pigawé. Ulah pati sieun nyieun kasalahan; mun anjeun geus nyieun kasalahan, saterusna anjeun, atawa sing saha baé nu séjén, salawasna bisa ngabenerkeun deui éta kasalahan. Paur ogé nya kadengena? Tempo \'\'[http://en.wikipedia.org/wiki/Wikipedia:Replies_to_common_objections replies to common objections]\'\' pikeun katerangan naha sistem ieu masih bisa jalan. Sanajan Wikipédia geus boga artikel cukup loba (nu Basa Inggris loba téh, da nu basa Sunda mah panungtungan ngitung téh ukur aya {{NUMBEROFARTICLES}}), Wikipédia mayeng nambahan artikel anyar nu ditulis ku jalma-jalma kawas anjeun. Anjeun bisa [http://en.wikipedia.org/wiki/Wikipedia:How_to_start_a_page muka artikel anyar], atawa neang artikel nu geus aya terus nambahkeun hiji bagean anyar di jerona. Mun anjeun ngarasa hariwang bisi \"ngaruksak\" hiji artikel, cobaan heula na [[Wikipédia:Kotrétan|Kotrétan]], di mana anjeun bisa nuliskeun naon nu hayang ditulis.\n\n==Kawijakan==\nDi dieu geus boga sababaraha [http://en.wikipedia.org/wiki/Wikipedia:Policies_and_guidelines kawijakan jeung tungtunan] nu meureun anjeun hayang nempoan. Garis badagna mah, kawijakan [[wikipedia:neutral point of view|neutral point of view]] dimaksudkeun sangkan artikel-artikel nu dijieun kudu nyingkahan bias, jeung kudu simpatik tur saimbang mun ditilik ti unggal sisi. Sagala kontribusi ka Wikipédia dikaluarkeun dina panangtayungan [http://en.wikipedia.org/wiki/GNU_Free_Documentation_License Lisénsi Dokumén Bébas GNU] (\'\'GNU Free Documentation License\'\', GFDL). GFDL ieu mastikeun yén Wikipédia bakal jeung bisa salawasna dibagikeun kalawan haratis (tempo [[Wikipédia:Hak cipta]] sangkan leuwih écés).\n\nWilujeng sukan-sukan!\n\n==Badé ngiringan?==\n\nSing saha waé bisa ngédit, tapi aya [[Wikipedia:Why create an account?|kauntungan]] mun anjeun nyieun \'\'account\'\' dina hayangna ilubiung kalawan mayeng. Mun rék miluan, mangga [[Special:Userlogin|damel account]] teras nepangkeun anjeun ka komunitas di [[Wikipedia:Pamaké anyar|log pamaké anyar]].\n\n== Tempo ogé ==\n\nDi handap ieu sababaraha \'\'link\'\' ka info-info panganteur:\n\n=== Informasi umum, tungtunan, jeung pitulung ===\n\n*[[Wikipedia:About|Ngeunaan ieu proyék]]\n*[[Pitulung: Eusi|Kaca pitulung]] - pitulung keur ngédit, ngamimitian artikel anyar, jeung jejer nu séjénna.\n*[[Wikipedia:FAQ|NLD Wikipédia]] - nu loba ditanyakeun ngeunaan situs ieu.\n*[[Wikipedia:Glossary|Glosarium]] - glosarium rupa-rupa istilah.\n*[[wikipedia:Policies and guidelines|Kawijakan jeung tungtunan keur kontributor]]\n*[[Wikipedia:Manual of Style|Manual of Style]]\n\n===For participants of similar sites ===\n\n*[[Wikipedia:Guide_for_h2g2_Researchers|Guide for h2g2 Researchers]]. For visitors from the [[h2g2]] community.\n*[[Wikipedia:Guide_for_Everything2 noders|Guide for Everything2 noders]]. For visitors from the [[Everything2]] community.\n*[[Wikipedia:Guide_for_Indymedia_authors|Guide for Indymedia authors]]. For visitors from the [[Indymedia]] community.\n\n\n=== Wikicivics ===\n====Tutorial Wing====\n*\'\'[[Wikipedia:Wikiquette|Wikiquette]]\'\'\n*\'\'[[Wikipedia:NPOV tutorial|Neutrality]]\'\'\n*\'\'[[Wikipedia:Writers rules of engagement|Writers rules of engagement]]\'\'\n*\'\'[[Wikipedia:Faux pas avoidance|Faux pas avoidance]]\'\'\n\n====Department of Deeper Inquiries====\n*\'\'[[Wikipedia:Civility|Civility]]\'\'\n*\'\'[[Wikipedia:Contributing to Wikipedia|Contributing]]\'\'\n*\'\'[[Wikipedia:Neutral point of view|NPOV Theory]]\'\'\n\n=== Komunitas Wikipédia ===\n*[[Wikipedia:Contact us|Contact us]]\n*[[Wikipedia:Wikipedians|Wikipedians]] - different listings of regular contributors; you may add yourself if you wish.\n\n[[ar:ويكيبيديا:ترحيب بالقادمين الجدد]]\n[[ca:Benvinguts A La Viquipиdia]]\n[[cs:Wikipedie:Vítejte ve Wikipedii]]\n[[da:Wikipedia:Velkommen nybegynder]]\n[[de:Wikipedia:Willkommen]]\n[[en:Welcome, newcomers]]\n[[eo:Vikipedio:Bonvenon al la Vikipedio]]\n[[es:Wikipedia:Bienvenidos]]\n[[fr:Wikipйdia:Bienvenue]]\n[[ga:Vicipéid:Fáilte, a núíosaigh]]\n[[hi:विकिपीडिया:स्वागत, नये आनेवालों]]\n[[ia:Wikipedia/Benvenite]] [[ja:Wikipedia:新規参加者の方、ようこそ]]\n[[ms:Wikipedia:Selamat_Datang]]\n[[nds:Infos Fцr Niege]] \n[[nl:Wikipedia:Welkom voor nieuwelingen]]\n[[pl:Wikipedia:Powitanie nowicjuszy]]\n[[pt:Boas vindas]]\n[[ro:Wikipedia:Bun venit]] \n[[sk:Wikip%C3%A9dia:Vitajte_vo_Wikip%C3%A9di%C3%AD]]\n[[sr:Википедија:Добродошли]] [[sv:Wikipedia:Vдlkommen]]\n[[tt:Sдlдm, Yaсa Kilgдnnдr]] \n[[ur:%D8%AE%D9%88%D8%B4_%D8%A2%D9%85%D8%AF%D9%8A%D8%AF]]\n[[zh:Wikipedia:欢迎,新来者]]','Reverted edit of 222.94.39.60, changed back to last version by Kandar',3,'Kandar','20050103032732','',0,0,1,0,0.526368116739,'20050103032732','79949896967267'); INSERT INTO cur VALUES (606,0,'Énsiklopédi','\'\'\'Énsiklopédi\'\'\' ngarupakeun [[kompendium]] tinulis [[pangaweruh]] manusa. \n\nIstilah éta asalna tina kecap [[Basa Yunani]] εγκύκλιος παιδεία, \'\'enkyklios paideia\'\' (\"in a circle of instruction\"). From εγκύκλιος, \'\'circuit shaped\'\' from κύκλος \'\'circuit\'\' and παιδεία, meaning \'\'instruction\'\'. See the \'\'Note on spelling\'\' below.\n\nÉnsiklopédi sipatna bisa umum, ngandung artikel-artikel dina jejer ti rupa-rupa widang (salah sahiji contona \'\'[[Encyclopædia Britannica]]\'\'), atawa bisa ogé husus hiji widang (saperti Énsiklopédi [[Sunda]] jeung énsiklopédi [[filosofi]]). Aya oge énsiklopédi nu ngawengku jejer-jejer nu lega tina jihat budaya atawa bangsa, kayaning \'\'[[Great Soviet Encyclopedia]]\'\' jeung Énsiklopédi [[Indonésia]].\n\nCatetan-catetan nu sarupa jeung énsiklopédi geus dijieun ti jaman sajarah manusa kénéh, ngan istilah \'\'énsiklopédi\'\' kakara dipaké dina [[abad ka-16]].\n\n== Karya énsiklopédis awal ==\n\nLoba elmuwan jaman baheula (contona [[Aristotle]] geus usaha nuliskeun kalawan gembleng sakabéh pangaweruh manusa. Sanajan [[John Harris]] dina karyana \'\'[[Lexicon technicum]]\'\'nu mindeng disebut/dipuji kana jasa maneuhkeun format énsiklopédi nu kawas ayeuna dina taun [[1704]], dokter Inggris [[Thomas Browne]] dina taun 1646 geus sacara husus maké kecap \'\'énsiklopédi\'\' pikeun ngagambarkeun kompendiumna...\n\nMany writers of antiquity (such as [[Aristotle]]) attempted to write comprehensively about all human knowledge. Although [[John Harris]] is often credited with establishing the now-familiar encyclopedia format in [[1704]] with his \'\'[[Lexicon technicum]]\'\' the English physician Sir [[Thomas Browne]] specifically employed the word \'\'encyclopaedia\'\' to describe his compendium of refuted \'\'Vulgar Errors\'\' also known as \'\'[[Pseudodoxia Epidemica]]\'\' as early as 1646 (6th edition 1676) . The venerable \'\'[[Encyclopædia Britannica]]\'\' had a modest beginning: from [[1768]] to [[1771]] three volumes were published. Perhaps the most famous early encyclopedia was the French \'\'[[L\'Encyclopédie|Encyclopédie]]\'\', edited by [[Jean le Rond d\'Alembert|Jean Baptiste le Rond d\'Alembert]] and [[Denis Diderot]] and completed in [[1772]] (28 volumes, 71,818 articles, 2,885 illustrations).\n\nThe encyclopedia\'s hierarchical structure and evolving nature is particularly adaptable to a disk-based or on-line computer format, and all major printed encyclopedias had moved to this method of delivery by the end of the [[abad ka-20|20th century]]. Disk-based (typically [[CD-ROM]] format) publications have the advantage of being cheaply produced and extremely portable. Additionally, they can include media which is impossible in the printed format, such as animations, audio, and video. [[hyperlink|Hyperlinking]] between conceptually related items is also a significant benefit. On-line encyclopedias offer the additional advantage of being (potentially) dynamic: new information can be presented almost immediately, rather than waiting for the next release of a static format (as with a disk or paper based publication).\n\nInformation in a printed encyclopedia necessarily needs some form of hierarchical structure, and traditionally the method employed is to present the information ordered alphabetically by the article title. However with the advent of dynamic electronic formats the need to impose a pre-determined structure is unnecessary. Nonetheless, most electronic encyclopedias still offer a range of organisational strategies for the articles, such as by subject area or alphabetically.\n\nArtikel ieu bagian ti [[Wikipédia]], nu mangrupa énsiklopédi.\n\n==Tumbu kaluar==\n*[http://stommel.tamu.edu/~baum/hyperref.html Daptar tumbu ka kamus jeung énsiklopédi (last updated Nov. 1999)]\n*[http://www.search.com/search?channel=19&cat=63 CNET\'s encyclopedia meta-search ] (kaasup Wikipédia)\n*[http://www.seeatown.com/search/ Encyclopedia Meta Search] (néang ampir di 20 énsiklopédi online sakaligus, kaasup Wikipédia)\n\n[[af:Ensiklopedie]] [[ar:موسوعة]] [[ca:Enciclopèdia]] [[cs:Encyklopedie]] [[da:Encyklopædi]] [[de:Enzyklopädie]] [[en:Encyclopaedia]] [[es:Enciclopedia]] [[eo:Enciklopedio]] [[fa:دایرةالمعارف]] [[fr:Encyclopédie]] [[it:Enciclopedia]] [[ia:Encyclopedia]] [[he:אנציקלופדיה]] [[la:Encyclopaedia]] [[nl:Encyclopedie]] [[ja:百科事典]] [[no:Encyklopedi]] [[oc:Oiquipedià]] [[nds:Nokieksel]] [[pl:Encyklopedia]] [[pt:Enciclopédia]] [[ro:Enciclopedie]] [[simple:Encyclopedia]] [[sv:Encyklopedi]] [[zh-cn:百科全书]] [[zh-tw:百科全書]] [[bg:Енциклопедия]]','',3,'Kandar','20050316104500','',0,0,1,0,0.194664117971,'20050316104500','79949683895499'); INSERT INTO cur VALUES (607,0,'Artikel','\'\'\'Artikel\'\'\' bisa nujul ka rupa-rupa hal:\n\n* dina [[tatabasa]]: [[artikel tatabasa]]\n* dina [[tatamba]]: [[sandi]] di antara dua [[tulang]]\n* dina [[jurnal]], [[majalah]], or [[koran]], artikél ngandung harti tulisan atawa [[éséy]] dina hiji jejer. \n\n\n{{disambig}}','',3,'Kandar','20040728094429','',0,0,0,0,0.524002544826,'20040728094429','79959271905570'); INSERT INTO cur VALUES (608,2,'Meursault2004','[[id:User:Meursault2004|Meursault2004]]\r\n\r\nHallo apa kabar? Saya biasa ada di Wikipedia Indonesia sebab saya kurang fasih berbahasa Sunda. Mungkin di sini saya bisa membantu-bantu sedikit.\r\n\r\nSalam Wikipedia','',5,'Meursault2004','20040318190145','',0,0,0,1,0.563952700032,'20040730042937','79959681809854'); INSERT INTO cur VALUES (609,1,'Tepas','[[Wikipédia: Ngeunaan]] - [[Wikipédia:Ngeunaan]]??\n
[[User:Robin Patterson|Robin Patterson]] 00:05, 15 Péb 2005 (UTC)\n\n--Hahah... Enya euy, bet nepi ka dobel kitu, padahal kuring sorangan nu nyieunna... [[Wikipédia: Ngeunaan]] bieu dihapus. Nuhun, Kang Robin! [[User:Kandar|kandar]] 05:54, 15 Péb 2005 (UTC)\n\n==Little modification==\n\n* It would be nice to unlock the home page once in a while to make edits. \n: If not, you guys could add this feature to your article count [[Special:Statistics|{{NUMBEROFARTICLES}}]][[User:24.201.116.26|24.201.116.26]] 05:16, 21 Péb 2005 (UTC)','unlock please',0,'24.201.116.26','20050221051653','',0,0,0,0,0.915749541445,'20050221051653','79949778948346'); INSERT INTO cur VALUES (610,0,'Wikipédia:NLD','Ieu ngarupakeun kumpulan \'\'\'Nu Loba Ditanyakeun\'\'\' (\'\'\'NLD\'\'\')-na Wikipédia.\n\nMun anjeun teu bisa manggihan jawaban nu ditéang, aya sababaraha pilihan séjén. Mun anjeun anyaran di Wikipédia ieu, bisa nyoba nempoan kaca [[Wikipédia:Wilujeng sumping|pangbagéa]], nu nyadiakeun émbaran jeung tumbu nu bisa ngabantu kumaha cara ngamimitianana.\n\nAnjeun oge bisa nyoba maca kaca [[Pitulung: Eusi|pitulung]]. Mun angger kénéh can manggih jawaban, dihaturan sumping ka \'\'\' rohangan [[Wikipédia:_Padungdengan|padungdengan]]\'\'\' pikeun ngadugikeun patarosan; [[Wikipédia:Wikipédiawan|Wikipédiawan]] nu sanesna mudah-mudahan tiasa maparin waleran nu nyugemakeun.\n\n== NLD umum ==\n\n*[[Wikipédia: NLD umum| NLD umum]] - Patarosan umum ngeunaan proyék ieu.\n*[[Wikipédia: NLD nu maca| NLD nu maca]] - Néangan, maca, jeung maké matéri ti Wikipédia.\n*[[Wikipédia: NLD sumbangsih| NLD sumbangsih]] - Alesan icikibung jeung kumaha carana.\n*[[Wikipedia: NLD ngédit| NLD ngédit]] - Cara jeung hal-hal nu kudu ditalingakeun nalika ngédit kaca-kaca Wikipédia.\n*[[Wikipedia: NLD tata usaha| NLD tata usaha]] - Naon hartina \'\'sysop\'\'/kuncén, status kuncén, jeung tata usaha \'\'server\'\'.\n*[[Wikipedia: NLD téhnis| NLD téhnis]] - Patarosan ngeunaan \'\'software\'\' jeung \'\'hardware\'\' Wikipédia jeung watesanana.\n*[[Wikipedia: NLD masalah| NLD masalah]] - Patarosan nu patali jeung masalah-masalah nu disanghareupan ku Wikipédia.\n*[[Wikipedia: NLD sakola| NLD sakola]] - Jawaban pikeun para murid jeung guru.\n*[[Wikipedia: NLD rupa-rupa| NLD rupa-rupa]] - Nu lianna.\n\n== NLD husus ==\n*[[Wikipédia: glosarium|Glosarium]] - Daptar istilah-istilah di Wikipédia.\n*[[Wikipédia: NLD naskah PHP| NLD naskah PHP]] - Ngawengku béda poko dina naskah PHP [[UseModWiki]].\n\n== Tempo ogé ==\n*[[Pitulung: Eusi|Kaca pitulung]] - Pitulung ngédit artikel, ngamimitian artikel anyar, jeung sajabana.\n*[[Wikipédia: ngoprék|Ngoprék]] - Pitulung pikeun rupa-rupa masalah téhnis nalika asup atawa ngédit kaca Wikipédia.\n*[[Wikipédia: jawaban pikeun kaabotan umum|Jawaban pikeun kaabotan umum]] - Jawaban pikeun kritik umum di Wikipédia.\n\n[[da:Wikipedia:OSS]] [[de:Wikipedia:FAQ]] [[el:Wikipedia:Συχνές Ερωτήσεις]] [[en:Wikipedia:FAQ]] [[eo:Vikipedio:Oftaj demandoj]] [[es:Wikipedia:FAQ]] [[fa:پرسش‌های رایج]] [[fr:Wikipédia:FAQ]] \n[[hi:विकिपीडिया:अक्सर पूछे जाने वाले सवाल]] [[hu:Wikip%C3%A9dia:GyIK]] [[ja:Wikipedia:FAQ]] [[nl:Wikipedia:Veel gestelde vragen]] [[pl:Wikipedia FAQ]] [[sv:Wikipedia:FAQ]] [[zh:Wikipedia:%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98%E8%A7%A3%E7%AD%94]]','',3,'Kandar','20050310091127','',0,0,1,0,0.964616135678,'20050310091127','79949689908872'); INSERT INTO cur VALUES (611,0,'Wikipédia:_Cara_ngédit_kaca','\'\'Salinan ti kaca [http://en.wikipedia.org/wiki/Wikipedia%3AHow_to_edit_a_page How to edit a page]\'\'\n\n:\'\'Tempo ogé [[Pitulung: Eusi]], [[m:Help:Editing]]\'\'\n[[Wikipédia]] téh mangrupa [[Wiki|WikiWiki]], nu hartina sing saha waé bisa kalawan gampil ngédit [[Wikipédia: artikel téh naon?|artikel]] mana waé nu \'\'\'[[Wikipédia: Kaca nu dijaga|teu dijaga]]\'\'\' sarta sacepetna ngamuat parobahanana. \n\nNgédit kaca Wiki mah gampang pisan, cukup ku ngaklik tab \"\'\'\'Édit kaca ieu\'\'\'\" di luhureun (atawa tumbu \'\'\'édit\'\'\' di katuhueun atawa handapeun) kaca Wiki, sahingga anjeun asup ka kaca kotak téks nu bisa dirobah. \'\'\'\'\'Mun anjeun rék ukur nyobaan, mangga pidamel na kaca [[Wikipédia:Kotrétan|kotrétan]], ulah di dieu.\'\'\'\'\'\n\nType away, write a short [[Wikipedia:Edit summary|edit summary]] on the small field below the edit-box. You may use shorthand to describe your changes, as described in the [[Wikipedia:Edit summary legend|legend]], and when you\'ve finished, press [[Wikipedia:Show preview|preview]] to see how your changes will look. Then press \"Save\". Depending on your system, pressing \"Enter\" while the edit box is not active (when there is no typing cursor in it) may have the same effect as pressing the \"Save\" button. Also, please do not vandalise the information on Wikipedia.\n\nAnjeun ogé bisa ngaklik tab \"\'\'\'Sawala\'\'\'\" (atawa tumbu \"\'\'\'Sawalakeun kaca ieu\'\'\'\") pikeun nempo [[Wikipédia: kaca omongan|kaca omongan]] nu patali, nu ngandung pamanggih ngeunaan kacana ti pamaké Wikipédia séjénna. Klik tab \"\'\'\'+\'\'\'\" (atawa \"\'\'\'Édit kaca ieu\'\'\'\") pikeun ngedalkeun pamanggih anjeun.\n\n==Kasalahan tatabasa ilahar==\nTempo [[Wikipédia: kasalahan tatabasa]].\n\n==Leuwih lengkep ngeunaan ngédit kaca Wiki==\n\nKaca ieu mangrupa acuan pikeun \'\'\'wiki markup\'\'\', salajengna anjeun bisa terus ngalenyepan ngeunaan\n\n* [[Pitulung: muka kaca anyar|Cara nyieun kaca anyar]] \n* Tips informal ngeunaan [[Wikipédia: Sumbangsih ka Wikipédia|nyumbangsih ka Wikipédia]]\n* Pancén-pancén ngédit sacara umum dina [[Wikipédia: NLD dina ngédit]]\n* Ngarobah ngaran kaca sangkan leuwih \'\'\'payus\'\'\', na [[Wikipédia: cara ngarobah ngaran (mindahkeun) hiji kaca]]\n* Témbongan pinilih artikel anjeun, na [[Wikipédia: tungtunan témbongan|tungtunan témbongan]] (tempo ogé [[Wikipedia:Boilerplate text]])\n* Kasapukan gaya na [[Wikipédia: tungtunan gaya]]\n* Kawijakan umum na [[Wikipédia: kawijakan jeung tungtunan]]\n* [[Wikipédia: kasapukan ngaran]] pikeun cara méré ngaran artikel\n* Mun anjeun nyien artikel ngeunaan hiji hal nu kagolongkeun kana sarupaning jejer (dayeuh, objék astronomis, aksara Cina, jsb.), pariksa sugan aya [http://en.wikipedia.org/wiki/Wikipédia:WikiProject Proyék Wiki] dina jejer éta.\n* Panungtung, pikeun daptar artikel ngeunaan ngédit na Wikipédia ngacu ka [http://en.wikipedia.org/wiki/Wikipedia:Style_and_How-to_Directory diréktori gaya jeung cara] atawa [http://en.wikipedia.org/wiki/Wikipedia:Utilities utiliti].\n\n==Tips ngédit artikel Wikipédia==\n\nPlease use a [[Neutral point of view|neutral point of view]], and please [[Wikipedia:Cite your sources|cite your sources]] so others can check and extend your work.\n\nIt is often more convenient to copy and paste the text first into your\nfavorite [[text editor]], edit and spell check there, and then paste back\ninto the browser to [[Wikipedia:Show preview|preview]]. This way, you can also keep a local backup copy of the pages you authored so that you can make changes offline. Some text editors can be specially adapted to edit Wikipedia articles: see [[Wikipedia:syntax highlighting]].\n\nIf during editing you want to see the current version again, open \"Cancel\" in a new window. This does not cancel your edit.\n\nAfter making a new page, it\'s a good idea to\n*With your page displayed, use \'\'What links here\'\' to check the articles that already link to it, and make sure that they are all expecting the same meaning that you have supplied;\n*Use the Search button to launch a Google search of Wikipedia for your topic title (and possibly variants), to find articles that mention it, and make links from them if appropriate;\n*Check for corresponding articles in the Wikipedias of other languages that you can read.\n\n== Éditan minor ==\n\'\'Tempo ogé [[Wikipédia: éditan minor]]\'\'\n\nNalika ngédit hiji kaca, pamaké nu geus [[Wikipédia: cara asup log|asup log]] bisa nandaan éditanana salaku \"minor\". Éditan minor hartina koréksi éjahan, format, sarta susunan ulang téks minor. Éditan minor bisa \'\'disumputkeun\'\' nalika muka [[Wikipedia:Recent Changes|parobahan anyar]]. Nandaan parobahan badag salaku éditan minor dianggap salaku watek goréng, komo mun ngawengku ngahapus sabagian eusi téks. Mun teu kahaja nandaan salaku éditan minor, jalmana kudu ngédit sumberna sakali deui, tandaan salaku mayor (nyaéta mastikeun yén kotak-contréng pikeun \"Ieu éditan minor\" teu dicontréng), jeung, na simpulan, sebutkeun yén parobahan saméméhna téh mayor.\n\n== \'\'Markup\'\' Wiki ==\nDina kolom kénca na tabel di handap ieu anjeun bisa nempo pangaruh naon nu bisa dijieun, sedengkeun na kolom katuhu anjeun bisa nempo cara nyieunna.\n\nMun can apal mah, anjeun bisa sakaligus tetep muka kaca ieu na panyungsi séjén pikeun acuan dina nulis artikel. Mun anjeun hayang nyoba-nyoba tanpa sieun ngaruksak, mangga \'\'\'pidamel na [[Wikipédia:Kotrétan|kotrétan]]\'\'\'.\n\n----\n\n=== Bagian, alinéa, daptar, jeung garis ===\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\"\n|-\n! What it looks like\n! What you type\n|- valign=\"top\"\n|\nStart your [[Wikipedia:Manual of Style (headings)|sections]] as follows:\n\n\n\n\n\'\'\'New section\'\'\'\n\n\'\'\'Subsection\'\'\'\n\n\'\'\'Sub-subsection\'\'\'\n\n* Start with a second-level heading (==); do not use first-level headings (=).\n* Do not skip levels (e.g., second-level followed by fourth-level).\n* A [[#Placement_of_the_Table_of_Contents_.28TOC.29|Table of Contents]] will automatically be added to an article that has four or more sections. \n|\n
\n==New section==\n\n===Subsection===\n\n====Sub-subsection====\n
\n|- valign=\"top\"\n|\nA single [[newline]]\ngenerally has no effect on the layout.\nThese can be used to separate\nsentences within a paragraph.\nSome editors find that this aids editing\nand improves the function \'\'diff\'\' \n(used internally to compare\ndifferent versions of a page).\n\nBut an empty line\nstarts a new paragraph.\n\n* When used in a list, a newline \'\'does\'\' affect the layout ([[#lists|see below]]).\n|\n
\nA single [[newline]]\ngenerally has no effect on the layout. \nThese can be used to separate\nsentences within a paragraph.\nSome editors find that this aids editing\nand improves the function \'\'diff\'\' \n(used internally to compare\ndifferent versions of a page).\n\nBut an empty line\nstarts a new paragraph.\n
\n|- valign=\"top\"\n|\nYou can break lines
\nwithout starting a new paragraph.\n\n* Please use this sparingly.\n* Close markup between lines, don\'t start a [[link]] or \'\'italics\'\' or \'\'\'bold\'\'\' on one line and close it on the next.\n|\n
\nYou can break lines
\nwithout starting a new paragraph.\n
\n|- id=\"lists\" valign=\"top\"\n|\n* Lists are easy to do:\n** Start every line with a star.\n*** More stars means deeper levels.\n**** A newline in a list\nmarks the end of a list item.\n\n* An empty line starts a new list.\n|\n
\n* Lists are easy to do:\n** Start every line with a star.\n*** More stars means deeper levels.\n**** A newline in a list\nmarks the end of a list item.\n\n* An empty line starts a new list.\n
\n|- valign=\"top\"\n|\n# Numbered lists are also good\n## very organized\n## easy to follow\n### easier still\n|\n
\n# Numbered lists are also good\n## very organized\n## easy to follow\n### easier still\n
\n|- valign=\"top\"\n|\n* You can even do mixed lists\n*# and nest them\n*#* like this\n|\n
\n* You can even do mixed lists\n*# and nest them\n*#* like this\n
\n|- valign=\"top\"\n|\n; Definition list : list of definitions\n; item : the item\'s definition\n; another item\n: the other item\'s definition\n\n* One item per line; a newline can appear before the colon, but using a space before the colon improves parsing.\n|\n
\n; Definition list : list of definitions\n; item : the item\'s definition\n; another item\n: the other item\'s definition\n
\n|- valign=\"top\"\n|\n: A colon indents a line or paragraph.\nA manual newline starts a new paragraph.\n\n* This is primarily for displayed material, but is also used for discussion on [[Wikipedia:Talk page|Talk page]]s.\n|\n
\n: A colon indents a line or paragraph.\nA manual newline starts a new paragraph.\n
\n|- valign=top\n|\n IF a line starts with a space THEN\n it will be formatted exactly\n as typed;\n in a fixed-width font;\n lines won\'t wrap;\n ENDIF\n\n*This is useful for:\n** pasting preformatted text;\n** algorithm descriptions;\n** program source code;\n** [[ASCII art]];\n** chemical structures;\n* \'\'\'WARNING\'\'\': If you make it wide, you [[page widening|force the whole page to be wide]] and hence less readable, especially for people who use lower resolutions. Never start ordinary lines with spaces.\n|\n
\n IF a line starts with a space THEN\n it will be formatted exactly\n as typed;\n in a fixed-width font;\n lines won\'t wrap;\n ENDIF\n
\n|- valign=\"top\"\n|\n
Centered text.
\n\n* Note the American spelling of \"center\" (not \"centre\").\n|\n
\n
Centered text.
\n
\n|- valign=\"top\"\n|\nA [[horizontal dividing line]]:\nthis is above it\n----\nand this is below it.\n\n* Mainly useful for separating threads on Talk pages.\n* Also used to [[Wikipedia:Disambiguation|disambiguate]] within an article without creating a separate page.\n|\n
\nA [[horizontal dividing line]]:\nthis is above it\n----\nand this is below it.\n
\n|}\n\n=== Links and URLs ===\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\"\n|-\n! What it looks like\n! What you type\n|- valign=\"top\"\n|\nLondon has [[public transport]].\n\n* A link to another Wikipedia article.\n* Internally, the first letter of the target page is automatically capitalized and spaces are represented as underscores (typing an underscore in the link has the same effect as typing a space, but is not recommended).\n* Thus the link above is to the [[URL]] http://www.wikipedia.org/wiki/Public_transport, which is the Wikipedia article with the name \"Public transport\". See also [[Wikipedia:Canonicalization]].\n|\n
\nLondon has [[public transport]].\n
\n|- valign=\"top\"\n|\nSan Francisco also has\n[[public transport|public transportation]].\n\n* Same target, different name.\n* This is a [[piped link]].\n|\n
\nSan Francisco also has\n[[public transport|public transportation]].\n
\n|- valign=\"top\"\n|\nSan Francisco also has\n[[public transport]]ation.\n\nExamples include [[bus]]es, [[taxi]]s\nand [[streetcar]]s.\n\n* Endings are blended into the link.\n* Preferred style is to use this instead of a piped link, if possible.\n|\n
\nSan Francisco also has\n[[public transport]]ation.\n\nExamples include [[bus]]es, [[taxi]]s\nand [[streetcar]]s.\n
\n|- valign=\"top\"\n|\nSee the [[Wikipedia:Manual of Style]].\n\n* A link to another [[Wikipedia:namespace|namespace]].\n|\n
\nSee the [[Wikipedia:Manual of Style]].\n
\n|- id=\"link-to-section\" valign=\"top\"\n|\n[[Economics#See also]] is a link\nto a section within another page.\n\n[[#Links and URLs]] is a link\nto a section on the current page.\n\n[[#example]] is a link to an\nanchor that was created using\n
an id attribute
\n\n* The part after the number sign (#) must match a section heading on the page, or an identifier created in some other way. Matches must be exact in terms of spelling, case and punctuation. Links to non-existent sections aren\'t broken; they are treated as links to the top of the page.\n* Identifiers may be created by attaching an id=\"...\"> attribute to almost any HTML element.\n|\n
\n[[Economics#See also]] is a link\nto a section within another page.\n\n[[#Links and URLs]] is a link\nto a section on the current page.\n\n[[#example]] is a link to an\nanchor that was created using\n
an id attribute
\n
\n|- valign=\"top\"\n|\nAutomatically hide stuff in parentheses:\n[[kingdom (biology)|kingdom]].\n\nAutomatically hide namespace:\n[[Wikipedia:Village Pump|Village Pump]]. \n\nOr both:\n[[Wikipedia:Manual of Style (headings)|Manual of Style]]\n\nBut not:\n[[Wikipedia:Manual of Style#Links|]]\n\n* The server fills in the part after the pipe character (|) when you save the page. The next time you open the edit box you will see the expanded piped link. When [[Wikipedia:Show preview|preview]]ing your edits, you will not see the expanded form until you press \'\'\'Save\'\'\' and \'\'\'Edit\'\'\' again. The same applies to links to sections within the same page ([[#link-to-section|see previous entry]]).\n|\n
\nAutomatically hide stuff in parentheses:\n[[kingdom (biology)|]].\n\nAutomatically hide namespace: \n[[Wikipedia:Village Pump|]].\n\nOr both:\n[[Wikipedia:Manual of Style (headings)|]]\n\nBut not:\n[[Wikipedia:Manual of Style#Links|]]\n
\n|- valign=\"top\"\n|\n[[The weather in London]] is a page\nthat doesn\'t exist yet.\n\n* You can create it by clicking on the link (but please don\'t do so with this particular link).\n* To create a new page: \n*# Create a link to it on some other (related) page.\n*# Save that page.\n*# Click on the link you just made. The new page will open for editing.\n* For more information, see [[Wikipedia:How to start a page|How to start a page]] and check out Wikipedia\'s [[Wikipedia:Naming conventions|naming conventions]].\n* Please do not create a new article without linking to it from at least one other article.\n|\n
\n[[The weather in London]] is a page \nthat doesn\'t exist yet.\n
\n|- valign=\"top\"\n|\n[[Wikipedia:How to edit a page]] is this page.\n\n* [[Self link]]s appear as bold text when the article is viewed.\n* Do not use this technique to make the article name bold in the first paragraph; see the [[Wikipedia:Manual of Style#Article names|Manual of Style]].\n|\n
\n[[Wikipedia:How to edit a page]] is this page.\n
\n|- valign=\"top\"\n|\nWhen adding a comment to a Talk page,\nyou should sign it by adding\nthree tildes to add your user name:\n: [[User:Brockert|Ben Brockert]]\nor four to add user name plus date/time:\n: [[User:Brockert|Ben Brockert]] 00:18, Nov 19, 2004 (UTC)\nFive tildes gives the date/time alone:\n: 00:18, Nov 19, 2004 (UTC)\n\n* The first two both provide a link to your [[Wikipedia:user page|user page]].\n|\n
\nWhen adding a comment to a Talk page,\nyou should sign it by adding\nthree tildes to add your user name:\n: ~~~\nor four for user name plus date/time:\n: ~~~~\nFive tildes gives the date/time alone:\n: ~~~~~\n
\n|- valign=\"top\"\n|\n* [[Wikipedia:Redirect|Redirect]] one article title to another by placing a directive like the one shown to the right on the \'\'first\'\' line of the article (such as at a page titled \"[[USA]]\").\n* Note that, while it is possible to link to a section, it is not possible to redirect to a section. For example, \"#REDIRECT [[United States#History]]\" will redirect to the [[United States]] page, but not to any particular section on it. This feature \'\'\'will not\'\'\' be implemented in the future, so such redirects should not be used.\n|\n
\n#REDIRECT [[United States]]\n
\n|- valign=\"top\"\n|\n* Link to a page on the same subject in another language by using a link of the form: [[language code:Title]].\n* It does not matter where you put these links while editing as they will always show up in the same place when you save the page, but placement at the end of the edit box is recommended.\n* Please see [[Wikipedia:Interlanguage links]] and the [[Wikipedia:Complete list of language wikis available|list of languages and codes]].\n|\n
\n[[fr:Wikipédia:Aide]]\n
\n|- valign=\"top\"\n|\n\'\'\'What links here\'\'\' and \'\'\'Related changes\'\'\'\npages can be linked as:\n[[Special:Whatlinkshere/Wikipedia:How to edit a page]]\nand\n[[Special:Recentchangeslinked/Wikipedia:How to edit a page]]\n\n|\n
\n\'\'\'What links here\'\'\' and \'\'\'Related changes\'\'\'\npages can be linked as:\n[[Special:Whatlinkshere/Wikipedia:How to edit a page]]\nand\n[[Special:Recentchangeslinked/Wikipedia:How to edit a page]]\n
\n|- valign=\"top\"\n|\nA user\'s \'\'\'Contributions\'\'\' page can be linked as:\n[[Special:Contributions/UserName]]\nor\n[[Special:Contributions/192.0.2.0]]\n|\n
\nA user\'s \'\'\'Contributions\'\'\' page can be linked as:\n[[Special:Contributions/UserName]]\nor\n[[Special:Contributions/192.0.2.0]]\n
\n|- valign=\"top\"\n|\n* To put an article in a [[Wikipedia:Category]], place a link like the one to the right anywhere in the article. As with interlanguage links, it does not matter where you put these links while editing as they will always show up in the same place when you save the page, but placement at the end of the edit box is recommended.\n|\n
\n[[Category:Character sets]]\n
\n|- valign=\"top\"\n|\n* To \'\'link\'\' to a [[Wikipedia:Category]] page without putting the article into the category, use an initial colon (:) in the link.\n|\n
\n[[:Category:Character sets]]\n
\n|- id=\"link-external\" valign=\"top\"\n|\nThree ways to link to external (non-wiki) sources:\n# Bare URL: http://www.nupedia.com/ (bad style)\n# Unnamed link: [http://www.nupedia.com/] (bad style)\n# Named link: [http://www.nupedia.com Nupedia]\n\n:See [[MetaWikiPedia:Interwiki_map]] for the list of shortcuts.\n\n* Square brackets indicate an external link. Note the use of a \'\'space\'\' (not a pipe) to separate the URL from the link text in the \"named\" version.\n* In the [[URL]], all symbols must be among:
\'\'\'A-Z a-z 0-9 . _ \\ / ~ % - + & # ? ! = ( ) @ \\x80-\\xFF\'\'\'\n* If a URL contains a character not in this list, it should be encoded by using a percent sign (%) followed by the [[hexadecimal|hex]] code of the character, which can be found in the table of [[ASCII#ASCII printable characters|ASCII printable characters]]. For example, the caret character (^) would be encoded in a URL as \'\'\'%5E\'\'\'.\n* See [[Wikipedia:External links]] for style issues.\n|\n
\nThree ways to link to external (non-wiki) sources:\n# Bare URL: http://www.nupedia.com/\n# Unnamed link: [http://www.nupedia.com/]\n# Named link: [http://www.nupedia.com Nupedia]\n
\n|- valign=\"top\"\n|\nLinking to other wikis:\n# [[Interwiki]] link: [[Wiktionary:Hello]]\n# Named interwiki link: [[Wiktionary:Hello|Hello]]\n# Interwiki link without prefix: [[Wiktionary:Hello|Hello]]\n\n* All of these forms lead to the URL http://en.wiktionary.org/wiki/Hello\n* Note that interwiki links use the \'\'internal\'\' link style.\n* See [[MetaWikiPedia:Interwiki_map]] for the list of shortcuts; if the site you want to link to isn\'t on the list, use an external link ([[#link-external|see above]]).\n* See also [[Wikipedia:How to link to Wikimedia projects]].\n\nLinking to another language\'s wiktionary:\n# [[Wiktionary:fr:Bonjour]]\n# [[Wiktionary:fr:Bonjour|Bonjour]]\n# [[Wiktionary:fr:Bonjour|fr:Bonjour]]\n\n* All of these forms lead to the URL http://fr.wiktionary.org/wiki/Bonjour\n|\n
\nLinking to other wikis:\n# [[Interwiki]] link: [[Wiktionary:Hello]]\n# Named interwiki link: [[Wiktionary:Hello|Hello]]\n# Interwiki link without prefix: [[Wiktionary:Hello|]]\n\nLinking to another language\'s wiktionary:\n# [[Wiktionary:fr:Bonjour]]\n# [[Wiktionary:fr:Bonjour|Bonjour]]\n# [[Wiktionary:fr:Bonjour|]]\n
\n|- valign=\"top\"\n|\nISBN 012345678X\n\nISBN 0-123-45678-X\n\n* Link to books using their [[Wikipedia:ISBN|ISBN]] numbers. This is preferred to linking to a specific online bookstore, because it gives the reader a choice of vendors.\n* ISBN links do not need any extra markup, provided you use one of the indicated formats.\n|\n
\nISBN 012345678X\n\nISBN 0-123-45678-X\n
\n|- valign=top\n|\nDate formats:\n# [[July 20]], [[1969]]\n# [[20 July]] [[1969]]\n# [[1969]]-[[07-20]]\n\n* Link dates in one of the above formats, so that everyone can set their own display order. If [[Special:Userlogin|logged in]], you can use [[Special:Preferences]] to change your own date display setting.\n* All of the above dates will appear as \"[[20 July|20 July]] [[1969|1969]]\" if you set your date display preference to \"15 January 2001\", but as \"[[20 July|July 20]], [[1969|1969]]\" if you set it to \"January 15, 2001\".\n|\n
\nDate formats:\n# [[July 20]], [[1969]]\n# [[20 July]] [[1969]]\n# [[1969]]-[[07-20]]\n
\n|- valign=\"top\"\n|\n[[media:Sg_mrob.ogg|Sound]]\n\n*To include links to non-image uploads such as sounds, use a \"media\" link. For images, [[#Images|see next section]].\n\nSome uploaded sounds are listed at [[Wikipedia:Sound]].\n|\n
\n[[media:Sg_mrob.ogg|Sound]]\n
\n|}\n\n=== Gambar ===\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\"\n|-\n! Némbonganana\n! Ngetikna\n|- valign=\"top\"\n| A picture: [[Image:Wiki.png]]\n\nor, with alternative text:\n[[Image:Wiki.png|jigsaw globe]]\n\nor, floating to the right side of the page and with a caption:\n[[Image:Wiki.png|frame|Wikipedia Encyclopedia]]
\n\nor, floating to the right side of the page \'\'without\'\' a caption:\n[[Image:Wiki.png|right|Wikipedia Encyclopedia]]
\n\n* Only images that have been uploaded to Wikipedia can be used. To upload images, use the [[Special:Upload|upload page]]. You can find the uploaded image on the [[Special:Imagelist|image list]].\n* See the [[Wikipedia:Image use policy|image use policy]], [[Wikipedia:Image markup|extended image markup/syntax]] (also possibly [[Wikipedia:Image markup with HTML|image HTML markup]]) for more hints.\n* Alternative text, used when the image isn\'t loaded, in a text-only browser, or when spoken aloud, is \'\'\'strongly\'\'\' encouraged. See [[Wikipedia:Alternate text for images|Alternate text for images]] for help on choosing it.\n* The frame tag automatically floats the image right.\n|
\nA picture: [[Image:Wiki.png]]\n\nor, with alternative text:\n[[Image:Wiki.png|jigsaw globe]]\n\nor, floating to the right side of the page and with a caption:\n[[Image:Wiki.png|frame|Wikipedia Encyclopedia]]\n\nor, floating to the right side of the page \'\'without\'\' a caption:\n[[Image:Wiki.png|right|Wikipedia Encyclopedia]]
\n|-\n|\nClicking on an uploaded image displays a description page, which you can also link directly to: [[:Image:Wiki.png]]\n|
\n\n[[:Image:Wiki.png]]\n
\n|-\n|\nTo include links to images shown as links instead of drawn on the page, use a \"media\" link.\n\n
[[media:Tornado.jpg|Image of a Tornado]]\n|\n
\n\n\n[[media:Tornado.jpg|Image of a Tornado]]\n\n
\n|}\n\n=== Format aksara ===\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\"\n|- valign=\"top\"\n! Témbonganana\n! Ngetikna\n|- id=\"emph\" valign=\"top\"\n|\n\'\'Emphasize\'\', \'\'\'strongly\'\'\', \'\'\'\'\'very strongly\'\'\'\'\'.\n* These are double and triple apostrophes (single-quote marks), not double-quote marks.\n|\n
\n\'\'Emphasize\'\', \'\'\'strongly\'\'\', \'\'\'\'\'very strongly\'\'\'\'\'.\n
\n|- valign=\"top\"\n|\n\\sin x + \\ln y
\nsin\'\'x\'\' + ln\'\'y\'\'\n\n\n\\mathbf{x} = 0
\n\'\'\'x\'\'\' = 0\n\nOrdinary text should use [[#emph|wiki markup for emphasis]], and should not use <i> or <b>. However, mathematical formulas often use italics, and sometimes use bold, for reasons unrelated to emphasis. Complex formulas should use [[m:Help:Formula|<math> markup]], and simple formulas may use <math>; or <i> and <b>; or \'\' and \'\'\'. According to [[Wikipedia:WikiProject Mathematics#Italicization and bolding|WikiProject Mathematics]], wiki markup is preferred over HTML markup like <i> and <b>.\n|\n
\n\\sin x + \\ln y\nsin\'\'x\'\' + ln\'\'y\'\'\n\n\\mathbf{x} = 0\n\'\'\'x\'\'\' = 0\n
\n|- valign=\"top\"\n|\nA typewriter font for monospace text\nor for computer code: int main()\n\n* For semantic reasons, using <code> where applicable is preferable to using <tt>.\n|\n
\nA typewriter font for monospace text\nor for computer code: int main()\n
\n|- valign=\"top\"\n|\nYou can use small text for captions.\n|\n
\nYou can use small text for captions.\n
\n|- valign=\"top\"\n|\nYou can strike out deleted material\nand underline new material.\n\nYou can also mark deleted material and\ninserted material using logical markup\nrather than visual markup.\n\n* When editing regular Wikipedia articles, just make your changes and don\'t mark them up in any special way.\n* When editing your own previous remarks in talk pages, it is sometimes appropriate to mark up deleted or inserted material.\n|\n
\nYou can strike out deleted material\nand underline new material.\n\nYou can also mark deleted material and\ninserted material using logical markup\nrather than visual markup.\n
\n|- valign=\"top\"\n|\n\'\'\'Diacritical marks:\'\'\'\n
\nè é ê ë ì í\n\nÀ Á Â Ã Ä Å
\nÆ Ç È É Ê Ë
\nÌ Í\nÎ Ï Ñ Ò
\nÓ Ô Õ\nÖ Ø Ù
\nÚ Û Ü ß\nà á
\nâ ã ä å æ\nç
\nè é ê ë ì í
\nî ï ñ ò ó ô
\nœ õ\nö ø ù ú
\nû ü ÿ\n\n* See [[meta:Help:Special characters|special characters]].\n|\n
\n
\nè é ê ë ì í\n\n&Agrave; &Aacute; &Acirc; &Atilde; &Auml; &Aring; \n&AElig; &Ccedil; &Egrave; &Eacute; &Ecirc; &Euml; \n&Igrave; &Iacute; &Icirc; &Iuml; &Ntilde; &Ograve; \n&Oacute; &Ocirc; &Otilde; &Ouml; &Oslash; &Ugrave; \n&Uacute; &Ucirc; &Uuml; &szlig; &agrave; &aacute; \n&acirc; &atilde; &auml; &aring; &aelig; &ccedil; \n&egrave; &eacute; &ecirc; &euml; &igrave; &iacute;\n&icirc; &iuml; &ntilde; &ograve; &oacute; &ocirc; \n&oelig; &otilde; &ouml; &oslash; &ugrave; &uacute; \n&ucirc; &uuml; &yuml;\n
\n|- valign=\"top\"\n|\n\'\'\'Punctuation:\'\'\'\n
\n¿ ¡ § ¶
\n† ‡ • – —
\n‹ › « »
\n‘ ’ “ ”\n|\n
\n
\n&iquest; &iexcl; &sect; &para;\n&dagger; &Dagger; &bull; &ndash; &mdash;\n&lsaquo; &rsaquo; &laquo; &raquo;\n&lsquo; &rsquo; &ldquo; &rdquo;\n
\n|- valign=\"top\"\n|\n\'\'\'Commercial symbols:\'\'\'\n
\n™ © ® ¢ € ¥
\n£ ¤\n|\n
\n
\n&trade; &copy; &reg; &cent; &euro; &yen; \n&pound; &curren;\n
\n|- valign=\"top\"\n|\n\'\'\'Subscripts:\'\'\'\n
\nx1 x2 x3\n\n\'\'\'Superscripts:\'\'\'\n
\nx1 x2 x3\nor x¹ x² x³\n*The latter method of superscripting can\'t be used in the most general context, but is preferred when possible (as with units of measurement) because most browsers have an easier time formatting lines with it.\n\nε0 =\n8.85 × 10−12\nC² / J m.\n\n1 [[hectare]] = [[1 E4 m²]]\n|\n
\n
\nx1 x2 x3\n
\n\n
\nx1 x2 x3\nor x&sup1; x&sup2; x&sup3;\n\n&epsilon;0 =\n8.85 &times; 10&minus;12\nC&sup2; / J m.\n\n1 [[hectare]] = [[1 E4 m&sup2;]]\n
\n|- valign=\"top\"\n|\n\'\'\'Greek characters:\'\'\'\n
\nα β γ δ ε ζ
\nη θ ι κ λ μ ν
\nξ ο π ρ σ ς
\nτ υ φ χ ψ ω
\nΓ Δ Θ Λ Ξ Π
\nΣ Φ Ψ Ω\n|\n
\n
\n&alpha; &beta; &gamma; &delta; &epsilon; &zeta; \n&eta; &theta; &iota; &kappa; &lambda; &mu; &nu; \n&xi; &omicron; &pi; &rho; &sigma; &sigmaf;\n&tau; &upsilon; &phi; &chi; &psi; &omega;\n&Gamma; &Delta; &Theta; &Lambda; &Xi; &Pi; \n&Sigma; &Phi; &Psi; &Omega;\n
\n|- valign=\"top\"\n|\n\'\'\'Math characters:\'\'\'\n
\n∫ ∑ ∏ √ − ± ∞
\n≈ ∝ ≡ ≠ ≤ ≥ →
\n× · ÷ ∂ ′ ″
\n∇ ‰ ° ∴ ℵ ø
\n∈ ∉ ∩ ∪ ⊂ ⊃ ⊆ ⊇
\n¬ ∧ ∨ ∃ ∀ ⇒ ⇔
\n→ ↔
\n* See also [[Wikipedia:WikiProject Mathematics|WikiProject Mathematics]].\n|\n
\n
\n&int; &sum; &prod; &radic; &minus; &plusmn; &infin;\n&asymp; &prop; &equiv; &ne; &le; &ge; &rarr;\n&times; &middot; &divide; &part; &prime; &Prime;\n&nabla; &permil; &deg; &there4; &alefsym; &oslash;\n&isin; &notin; &cap; &cup; &sub; &sup; &sube; &supe;\n&not; &and; &or; &exist; &forall; &rArr; &hArr;\n&rarr; &harr;\n
\n|- valign=\"top\"\n|\n\'\'\'Spacing in simple math formulas:\'\'\'\n
\nObviously, \'\'x\'\'² ≥ 0 is true.\n*To space things out without allowing line breaks to interrupt the formula, use non-breaking spaces: &nbsp;.\n|\n
\n
\nObviously, \'\'x\'\'&sup2;&nbsp;&ge;&nbsp;0 is true.\n
\n|- valign=\"top\"\n|\n\'\'\'Complicated formulas:\'\'\'\n
\n: \\sum_{n=0}^\\infty \\frac{x^n}{n!}\n* See [[m:Help:Formula]] for how to use <math>.\n* A formula displayed on a line by itself should probably be indented by using the colon (:) character.\n|\n
\n
\n: \\sum_{n=0}^\\infty \\frac{x^n}{n!}\n
\n|- valign=\"top\"\n|\n\'\'\'Suppressing interpretation of markup:\'\'\'\n
\nLink → (\'\'to\'\') the [[Wikipedia FAQ]]\n* Used to show literal data that would otherwise have special meaning.\n* Escape all wiki markup, including that which looks like HTML tags.\n* Does not escape HTML character references.\n* To escape HTML character references such as &rarr; use &amp;rarr;\n|\n
\n
\n<nowiki>Link &rarr; (\'\'to\'\') \nthe [[Wikipedia FAQ]]</nowiki>\n
\n|- valign=\"top\"\n|\n\'\'\'Commenting page source:\'\'\'\n
\n\'\'not shown when viewing page\'\'\n* Used to leave comments in a page for future editors.\n* Note that most comments should go on the appropriate [[Wikipedia:Talk page|Talk page]].\n|\n
\n
\n<!-- comment here -->\n
\n|}\n\'\'(Tempo ogé: [[Chess symbols in Unicode]])\'\'\n\n=== Tabel ===\n\n==== Nempatkeun Daptar Eusi [\'\'Table of Contents\'\' (TOC)] ====\nAt the current status of the wiki markup language, having at least four headers on a page triggers the TOC to appear in front of the first header (or after introductory sections). Putting __TOC__ anywhere forces the TOC to appear at that point (instead of just before the first header). Putting __NOTOC__ anywhere forces the TOC to disappear. See also [[Wikipedia:Section#Compact_TOC|compact TOC]] for alphabet and year headings.\n\n==== Keeping headings out of the Table of Contents ====\n\nIf you want some subheadings to not appear in the Table of Contents, then make the following replacements.\n\nReplace == Header 2 == with

Header 2

\n\nReplace === Header 3 === with

Header 3

\n\nAnd so forth.\n\nFor example, notice that the following header has the same font as the other subheaders to this \"Tables\" section, but the following header does not appear in the Table of Contents for this page.\n\n

This header has the h4 font, but is NOT in the Table of Contents

\n\nThis effect is obtained by the following line of code.\n\n

This header has the h4 font, but is NOT in the Table of Contents

\n\n\n==== Tabel ====\nAya dua cara nyieun tabel: \n*na markup-Wiki husus (tempo [[m:Help:Table]])\n*migunakeun unsur HTML nu ilahar: <table>, <tr>, <td> or <th>.\n\nPikeun nu ahir, sarta padungdengan ngeunaan perlu henteuna migunakeun tabel, tempo [[Wikipédia: cara migunakeun tabel]].\n\n===Variabel===\n\n\'\'(Tempo ogé [[m:Help:Variable]])\'\'\n{|\n|-\n! Code\n! Effect\n|-\n| {{CURRENTMONTH}} || {{CURRENTMONTH}}\n|-\n| {{CURRENTMONTHNAME}}\n| {{CURRENTMONTHNAME}}\n|-\n| {{CURRENTMONTHNAMEGEN}}\n| {{CURRENTMONTHNAMEGEN}}\n|-\n| {{CURRENTDAY}} || {{CURRENTDAY}}\n|-\n| {{CURRENTDAYNAME}} || {{CURRENTDAYNAME}}\n|-\n| {{CURRENTYEAR}} || {{CURRENTYEAR}}\n|-\n| {{CURRENTTIME}} || {{CURRENTTIME}}\n|-\n| {{NUMBEROFARTICLES}}\n| {{NUMBEROFARTICLES}}\n|-\n| {{PAGENAME}} || {{PAGENAME}}\n|-\n| {{NAMESPACE}} || {{NAMESPACE}}\n|-\n| {{localurl:pagename}}\n| {{localurl:pagename}}\n|-\n| {{localurl:\'\'Wikipedia:Sandbox\'\'|action=edit}}\n| {{localurl:Wikipedia:Sandbox|action=edit}}\n|-\n| {{SERVER}} || {{SERVER}}\n|-\n| {{ns:1}} || {{ns:1}}\n|-\n| {{ns:2}} || {{ns:2}}\n|-\n| {{ns:3}} || {{ns:3}}\n|-\n| {{ns:4}} || {{ns:4}}\n|-\n| {{ns:5}} || {{ns:5}}\n|-\n| {{ns:6}} || {{ns:6}}\n|-\n| {{ns:7}} || {{ns:7}}\n|-\n| {{ns:8}} || {{ns:8}}\n|-\n| {{ns:9}} || {{ns:9}}\n|-\n| {{ns:10}} || {{ns:10}}\n|-\n| {{ns:11}} || {{ns:11}}\n|-\n| {{ns:12}} || {{ns:12}}\n|-\n| {{ns:13}} || {{ns:13}}\n|-\n| {{ns:14}} || {{ns:14}}\n|-\n| {{ns:15}} || {{ns:15}}\n|-\n| {{SITENAME}} || {{SITENAME}}\n|}\n\n\'\'\'NUMBEROFARTICLES\'\'\' is the number of pages in the main namespace which contain a link and are not a redirect, i.e. number of articles, stubs containing a link, and disambiguation pages.\n\n===Templates===\n\nThe [[Wikipedia:MediaWiki|MediaWiki]] software used by Wikipedia has limited support for template inclusion. This means standardized text chunks (such as boilerplate text) can be inserted into articles. For example, typing {{stub}} will appear as \'\'This article is a [[Wikipedia:The perfect stub article|stub]]. You can help Wikipedia by [[Wikipedia:Find or fix a stub|expanding it]].\'\' when the page is saved. See [[Wikipedia:Template messages]] for the complete list. Other commonly used ones are: {{disambig}} for disambiguation pages, {{spoiler}} for spoiler warnings and {{sectstub}} like an article stub but for a section. The are many subject-specific stubs e.g.: {{Geo-stub}}, {{Hist-stub}} and {{Linux-stub}}. For a complete list of stubs see [[Wikipedia:Template messages#Stubs]].\n\n===Nyumputkeun tumbu édit===\n\nAsupkeun \'\'\'__NOEDITSECTION__\'\'\' kana dokuménna pikeun ngaleungitkeun tumbu édit nu némbongan dina unggal hulu bab.\n\n==Tempo ogé==\n*[[m:Help:Editing|Mediawiki user\'s guide to editing]]\n*[[Wikipedia:MediaWiki]].\n*[[HTML element]].\n*[[Wikipedia:Protection policy]]\n\n\n[[ar:ويكيبيديا:مساعدة التحرير]]\n[[be:Вікіпэдыя:Як рэдагаваць існуючы артыкул]][[bg:Уикипедия:Как се редактират страници]]\n[[ca:Viquipèdia:Com s\'edita una pàgina]]\n[[cs:Wikipedie:Jak editovat stránku]]\n[[da:Wikipedia:Hvordan redigerer jeg en side]]\n[[de:Wikipedia:Handbuch - Artikel bearbeiten]]\n[[el:Wikipedia:Πώς να επεξεργαστείτε μια σελίδα]]\n[[en:Wikipedia:How to edit a page]]\n[[eo:Vikipedio:Kiel redakti pagxon]]\n[[es:Wikipedia:Cómo se edita una página]]\n[[fi:Wikipedia:Kuinka_sivuja_muokataan]]\n[[fr:Wikipédia:Syntaxe wikipédia]]\n[[ga:Vicipéid:Conas a cuirtear leathanach in eagar]]\n[[he:ויקיפדיה:איך לערוך דף]]\n[[hi:लेख को कैसे बदलें]]\n[[hu:Wikipédia:Hogyan szerkessz egy lapot]]\n[[id:Wikipedia:Menyunting_sebuah_halaman]]\n[[it:Wikipedia:Guida_essenziale]]\n[[lt:Wikipedia:Kaip_Redaguoti_Puslap%C4%AF]]\n[[ja:Wikipedia:編集の仕方]]\n[[no:Wikipedia:Hvordan man redigerer en side]]\n[[nn:Hjelp:Redigering]]\n[[pt:Wikipedia:Como_editar_uma_p%C3%A1gina]]\n[[ro:Wikipedia:Cum să editezi o pagină]]\n[[ru:Как редактировать страницу]]\n[[simple:Wikipedia:How to edit]]\n[[sl:Wikipedija:Urejevanje slovenskih strani]]\n[[sr:%D0%92%D0%B8%D0%BA%D0%B8%D0%BF%D0%B5%D0%B4%D0%B8%D1%98%D0%B0:%D0%9A%D0%B0%D0%BA%D0%BE_%D1%81%D0%B5_%D0%BC%D0%B5%D1%9A%D0%B0_%D1%81%D1%82%D1%80%D0%B0%D0%BD%D0%B0]]\n[[sv:Wikipedia:Hur man redigerar en sida]]\n[[th:Wikipedia:การแก้ไขหน้า]]\n[[tr:Wikipedia:Sayfa_nas%C4%B1l_de%C4%9Fi%C5%9Ftirilir]]\n[[ur:%D8%B5%D9%81%D8%AD%DB%81_%DA%A9%D8%B3_%D8%B7%D8%B1%D8%AD_%D8%AA%D8%B1%D9%85%D9%8A%D9%85_%DA%A9%D8%B1%D9%8A%DA%BA]]\n[[vi:Wikipedia:C%C3%A1ch_ch%E1%BB%8Dn_l%E1%BB%8Dc_trang]]\n[[zh-cn:Wikipedia:%E5%A6%82%E4%BD%95%E7%BC%96%E8%BE%91%E9%A1%B5%E9%9D%A2]]\n[[zh-tw:Wikipedia:如何編輯頁面]]','/* Kasalahan tatabasa ilahar */',3,'Kandar','20050203201342','',0,0,0,0,0.675049407256,'20050203201342','79949796798657'); INSERT INTO cur VALUES (612,3,'Kandar','Hi Kandar, you are a [[Special:Listadmins|sysop]] now. Good work. -- [[m:User:Looxix|Looxix]]\n\n----\nSelamat! Sekarang kang Kandar bisa merubah-rubah dan melindungi beberapa halaman tertentu. Saya bisa sedikit bantu; bagaimana kalau Main_Page dirubah menjadi Kaca Utama saja? Ada beberapa cara untuk mencapai hal ini. Ngomong2 sudah baca artikel di Sinar Harapan belum? Tempo hari saya mencoba mengemail tapi tak sampai [[User:Meursault2004|Meursault2004]] 10:46, 8 Jul 2004 (UTC)\n----\nSaya coba mail beberapa kali kok \'nggak masuk ya? Katanya over quota! Begitu messagenya.\n\n==Berita mail==\nBagaimana kang kalau coba ini:\n\nhttp://su.wikipedia.org/wiki/Template:All_messages\n\nMemang lebih baik kalau bisa dan ada waktu\nmenterjemahkan language.php. Tapi ini lama sekali,\nsebab yang diterjemahkan banyak sekali. Kalau tidak\nsalah ada ~ 300 halaman!\n\nTidak semua bisa diterjemahkan sih dari all_messages.\nTetapi sebagian besar bisa. Beberapa istilah seperti\n\"Perbualan\" dan nama-nama hari serta bulan di Wiki\nIndonesia belum bisa saya rubah karena harus merubah\nlanguage file.\n\nBaik deh sukses ya ;-) nanti kalau ada pertanyaan lagi\nbisa kontak saya. Mudah-mudahan bisa bantu :)\n\nSalam wikipedia!\n\n[[User:Meursault2004|Meursault2004]] 08:53, 10 Jul 2004 (UTC)\n----\nTidak usah merasa malu tetapi justru harus berbangga karena anda bisa masuk Sinar Harapan! (Meskipun namanya \'nggak disebut ...) Sukses selanjutnya. Saya ada usul untuk membuat redirect ke Kaca Utama dari Main_Page. Selain itu di all_messages, main_page bisa dirubah pula [[User:Meursault2004|Meursault2004]] 08:34, 11 Jul 2004 (UTC)\n\n----\nKang Kandar, di halaman Template:all_messages, setiap pranala (\'\'link\'\') harus diklik dan disinilah yang diedit. Bukannya halamannya sendiri yang disunting. Sebab teks di halaman ini sebaiknya harus dibiarkan begitu saja, karena merupakan teks default dalam bahasa Inggris. Sehingga para developer yang tak kenal bahasa lokal masih bisa membetulkannya. Mudah-mudahan cukup ;-) Salam [[User:Meursault2004|Meursault2004]] 10:11, 28 Jul 2004 (UTC)\n\n----\nPesan-pesan dalam bahasa Indonesia sudah saya rubah ;-) Tempo hari saya balas mailnya kok nggak bisa ya? Memang mailnya kang Kandar jarang bisa dikirim ya. Salam Wiki! [[User:Meursault2004|Meursault2004]] 09:20, 17 Aug 2004 (UTC)\n\n==Administrator==\n\nHello Kandar, you are now an administrator on the Sundanese Wiktionary and Wikibooks. However, you do not have an account on Wikiquote, so I could not make you an admin there. Let me know on [[m:requests for permissions]] once you have a Wikiquote account and I can set it there as well. Good luck. [[User:Angela|Angela]] 12:55, 28 Sep 2004 (UTC)\n\n:Just to let you know, you\'re now an administrator on su.wikiquote too. [[User:Angela|Angela]] 12:30, 30 Sep 2004 (UTC)\n\n==Translation of the week==\nCurrently we have started a project on meta.wikipedia to get an article translated in as many wikipedias as possible every week. The article will be about a subject that usually gets rarely translated and has a lot of links to other subjects. Currently we have no-one to translate in your language. If someone is interested to participate please see: [[:meta:Translation of the week]] You can also submit articles from your own languages there that you think deserve translation, but have a small chance of it. The articles must not be to short and not to long and have lots of links to possible other articles! [[:en:user:Waerth]]\n\n==Greetings from a little further south==\nGreetings from the South Pacific. The recent use of \"202.27.88.100\" (here and on other Oceania and South-East Asia languages) has been by me, [[mi:User:Robin Patterson]]. I see this Wikipedia is a bit of a one-man band too! With much more English than \"mine\", which may account for the larger number of articles; I try to restrict my contributions there to Maori language, despite not being fluent in Maori.\n
I hope my \"[[2004]]\" page is helpful. If you translate the \"July\" line it will be all in your language, apart from the numbers, and you may find it is an easy page to encourage other people (even those who know little or nothing of your language) to add to. You can extend to earlier years and have your whole history set out where it all links quickly between years and to subject articles and to people articles. Different Wikipedias have different ways of organising links to other years and subjects, so have a look at the interwiki links and see which is a good combination of methods for you.\n
Anyway, be brave; I\'m sure your work here is enjoyable for itself and that it will all benefit someone else in the end. Robin. [[User:202.27.88.100|202.27.88.100]] 23:36, 16 Nov 2004 (UTC)\n----\n\nCan you please translate and post [[en:2005 Belize unrest]]. Thanks . [[en:User:Danny|Danny]]\n\n== Busy days for some of us ==\n\nHello again. You have had a fairly busy week. I have done a bit in the last 24 hours (since not much is happening on [[:mi:]]).\n\nPlease have a look at my work and translate or correct wherever you can. Some of those pages can then be used as models for similar pages. Tell me if you would like different styles anywhere.\n\nAlso have a look at [[Presiden Indonesia]]. Only [[Sukarno]] links to it. Wahid links to the non-existent version with more accents, [[Présidén Indonésia]]. Sukarnoputri links to [[President of Indonesia]] (the only page that does). If (as I presume) the one with accents is correct, one of us should move [[Presiden Indonesia]] accordingly; then someone can later fix the links that don\'t go to the correct name.\n\nFinally for today, please add the remaining \"months\" to my User page, so that I can use them as appropriate.\n\nKind regards\n\n[[User:Robin Patterson|Robin Patterson]] 05:08, 9 Péb 2005 (UTC)','Busy days for some of us',38,'Robin Patterson','20050209050822','',0,0,0,0,0.174051528878,'20050210184507','79949790949177'); INSERT INTO cur VALUES (614,0,'Hadiah_Nobel_widang_kimia','Nu meunangkeun [[Hadiah Nobel]] widang [[kimia]], disusun nurutkeun taun ti nu pangmimitina.\n\n{{msg:NobelPrizes}}\n\n[[1901]]
[[J. H. van\'t Hoff|Jacobus Henricus van \'t Hoff]]\n:\'\'for his discovery of the laws of chemical dynamics and [[osmotic pressure]] in [[solution]]s\'\'\n[[1902]]
[[Hermann Emil Fischer]]\n:\'\'kanggo damelna ngeunaan sintésis [[gula]] jeung [[purin]]\'\'\n[[1903]]
[[Svante Arrhenius|Svante August Arrhenius]]
\n:\'\'kanggo téori disosiasi elektrolitik\'\' (tempo [[ion]])\n[[1904]]
[[Sir William Ramsay]]\n:\'\'for his discovery of the [[inert gas]]eous elements in air\'\'\n[[1905]]
[[Johann Friedrich Wilhelm Adolf von Baeyer]]\n:\'\'kanggo damelna ngeunaan organic dyes jeung senyawa hidro[[aromatik]]\'\'\n[[1906]]
[[Henri Moissan]]\n:\'\'kanggo panalungtikan anjeunna dina isolasi [[unsur]] [[florin]], sarta kanggo electric furnace called after him\'\'\n[[1907]]
[[Eduard Buchner]]
\n:\'\'for his [[biochemistry|biochemical]] researches and his discovery of [[cell (biology)|cell]]-free [[fermentation]]\'\'\n[[1908]]
[[Ernest Rutherford]]
\n:\'\'for his investigations into the disintegration of the elements, and the chemistry of [[radioactivity|radioactive substances]]\'\'\n[[1909]]
[[Wilhelm Ostwald]]
\n:\'\'his work on [[catalysis]] and for his investigations into [[chemical equilibrium|chemical equilibria]] and rates of [[chemical reaction|reaction]]\'\'\n[[1910]]
[[Otto Wallach]]
\n:\'\'for his work in the field of alicyclic compounds\'\'\n[[1911]]
[[Marie Sklodowska-Curie]]
\n:\'\'for her discovery of [[radium]] and [[polonium]], and her study of radium\'\'\n[[1912]]
[[Victor Grignard]], [[Paul Sabatier]]
\n:\'\'for his the discovery of the [[Grignard reagent]]\'\' \'\'\'and\'\'\' \'\'for his method of [[hydrogenation|hydrogenating]] organic compounds\'\'\n[[1913]]
[[Alfred Werner]]
\n:\'\'for his work on the linkage of atoms in [[molecule]]s\'\'\n[[1914]]
[[Theodore William Richards]]
\n:\'\'for his determinations of the [[atomic weight]] of a large number of elements\'\'\n[[1915]]
[[Richard Martin Willstätter]]
\n:\'\'for his researches on plant pigments\'\'\n[[1918]]
[[Fritz Haber]]
\n:\'\'for his synthesis of ammonia\'\'\n[[1920]]
[[Walther Hermann Nernst]]
\n:\'\'for his work in [[thermodynamics|thermochemistry]]\'\'\n[[1921]]
[[Frederick Soddy]]
\n:\'\'for his work on the chemistry of radioactive substances and investigations into [[isotope]]s\'\'\n[[1922]]
[[Francis William Aston]]
\n:\'\'for his discovery of isotopes in a large number of non-radioactive elements, and for his whole-number rule\'\'\n[[1923]]
[[Fritz Pregl]]
\n:\'\'for his invention of the method of micro-analysis of organic substances\'\'\n[[1925]]
[[Richard Adolf Zsigmondy]]\n:\'\'for his demonstration of the heterogenous nature of [[colloid]] solutions and the methods used\'\'\n[[1926]] The (Theodor) Svedberg
\n:\'\'for his work on disperse systems\'\'\n[[1927]]
[[Heinrich Otto Wieland]]
\n:\'\'for his investigations of the [[bile acid]]s and related substances\'\'\n[[1928]]
[[Adolf Otto Reinhold Windaus]]
\n:\'\'for his research into [[sterol]]s and their connection with [[vitamin]]s\'\'\n[[1929]]
[[Arthur Harden]], [[Hans Karl August Simon von Euler-Chelpin]]
\n:\'\'for their investigations on the fermentation of sugar and fermentative [[enzyme]]s\'\'\n[[1930]]
[[Hans Fischer]]
\n:\'\'for his researches into [[haemin]] and [[chlorophyll]] \'\'\n[[1931]]
[[Carl Bosch]], [[Friedrich Bergius]]\n:\'\'for their contributions to chemical high pressure methods\'\'\n[[1932]]
[[Irving Langmuir]]\n:\'\'for his work in surface chemistry\'\'\n[[1934]]
[[Harold Clayton Urey]]\n:\'\'for his discovery of [[deuterium|heavy hydrogen]]\'\'\n[[1935]]
[[Frédéric Joliot]], [[Irene Joliot-Curie|Irene Joliot-Curie]]\n:\'\'for their synthesis of new radioactive elements\'\'\n[[1936]]
[[Peter Debye|Petrus (Peter) Josephus Wilhelmus Debye]]\n:\'\'for his work on molecular structure through investigations on [[dipole moment]]s and the [[diffraction]] of [[X-ray]]s and [[electron]]s in [[gas]]es\'\'\n[[1937]]
[[Walter Norman Haworth]], [[Paul Karrer]]\n:\'\'for his work on [[carbohydrate]]s and [[vitamin C]]\'\' \'\'\'and\'\'\' \'\'for his work on [[carotenoid]]s, [[flavin]]s and vitamins [[vitamin A|A]] and [[Vitamin B2|B2]]\'\'\n[[1938]]
[[Richard Kuhn]]\n:\'\'for his work on carotenoids and vitamins\'\'\n[[1939]]
[[Adolf Friedrich Johann Butenandt]], [[Leopold Ruzicka]]\n:\'\'for his work on [[sex hormone]]s\'\' \'\'\'and\'\'\' \'\'for his work on polymethylenes and higher [[terpene]]s\'\'\n[[1943]]
[[George de Hevesy]]\n:\'\'for his work on the use of isotopes as [[radioactive tracer|tracer]]s to study chemical processes\'\'\n[[1944]]
[[Otto Hahn]]\n:\'\'for his discovery of the [[nuclear fission|fission]] of heavy [[Atomic nucleus|nuclei]]\'\'\n[[1945]]
[[Artturi Ilmari Virtanen]]\n:\'\'for his research in agricultural and [[nutrition]] chemistry\'\'\n[[1946]]
[[James Batcheller Sumner]], [[John Howard Northrop]], [[Wendell Meredith Stanley]]\n:\'\'for his discovery that enzymes can be crystallized\'\' \'\'\'and\'\'\' \'\'for their preparation of enzymes and [[virus]] [[protein]]s in a pure form\'\'\n[[1947]]
[[Sir Robert Robinson]]\n:\'\'for his investigations on plant products, especially the [[alkaloid]]s\'\'\n[[1948]]
[[Arne Wilhelm Kaurin Tiselius]]\n:\'\'for his research on [[electrophoresis]] and adsorption analysis\'\'\n[[1949]]
[[William Francis Giauque]]\n:\'\'for his contributions in the field of chemical thermodynamics\'\'\n[[1950]]
[[Otto Paul Hermann Diels]], [[Kurt Alder]]\n:\'\'for their discovery and development of the diene synthesis\'\'. [[Diels-Alder reaction]].\n[[1951]]
[[Edwin Mattison McMillan]], [[Glenn T. Seaborg|Glenn Theodore Seaborg]]\n:\'\'for their discoveries in the chemistry of [[transuranium elements]]\'\'\n[[1952]]
[[Archer John Porter Martin]], [[Richard Laurence Millington Synge]]\n:\'\'for their invention of partition [[chromatography]]\'\'\n[[1953]]
[[Hermann Staudinger]]\n:\'\'for his discoveries in the field of [[macromolecule|macromolecular]] chemistry\'\'\n[[1954]]
[[Linus Pauling|Linus Carl Pauling]]\n:\'\'for his research into the nature of the [[chemical bond]]\'\'\n[[1955]]
[[Vincent du Vigneaud]]\n:\'\'for his work on [[sulphur]] compounds, especially the first synthesis of a [[polypeptide]] [[hormone]]\'\'\n[[1956]]
[[Sir Cyril Norman Hinshelwood]], [[Nikolay Nikolaevich Semenov]]\n:\'\'for their researches into the mechanism of chemical reactions\'\'\n[[1957]]
[[Lord Alexander R. Todd]]\n:\'\'for his work on [[nucleotide]]s and nucleotide [[co-enzyme]]s\'\'\n[[1958]]
[[Frederick Sanger]]\n:\'\'for his work on the [[primary structure|structure]] of proteins, especially [[insulin]]\'\'\n[[1959]]
[[Jaroslav Heyrovsky]]\n:\'\'for his discovery and development of the polarographic methods of analysis\'\'\n[[1960]]
[[Willard Libby|Willard Frank Libby]]\n:\'\'for his method to use carbon-14 for [[carbon dating|age determination]]\'\'\n[[1961]]
[[Melvin Calvin]]\n:\'\'for his research on [[carbon dioxide]] assimilation in [[plant]]s\'\'\n[[1962]]
[[Max Ferdinand Perutz]], [[John Cowdery Kendrew]]\n:\'\'for their studies of the structures of [[myoglobin|globular proteins]]\'\'\n[[1963]]
[[Karl Ziegler]], [[Giulio Natta]]\n:\'\'for their discoveries relating to high [[polymer]]s\'\'\n[[1964]]
[[Dorothy Crowfoot Hodgkin]]\n;\'\'for her determinations by [[crystallography|X-ray techniques]] of the structures of important biochemical substances\'\'\n[[1965]]
[[Robert Burns Woodward]]\n:\'\'for his achievements in organic synthesis\'\'\n[[1966]]
[[Robert S. Mulliken|Robert Sanderson Mulliken]]\n:\'\'for his work concerning chemical bonds and the electronic structure of molecules\'\'\n[[1967]]
[[Manfred Eigen]], [[Ronald George Wreyford Norrish]], [[George Porter]]\n:\'\'for their studies of extremely fast chemical reactions\'\'\n[[1968]]
[[Lars Onsager]]\n:\'\'for the discovery of the reciprocal relations bearing his name\'\'\n[[1969]]
[[Derek H. R. Barton]], [[Odd Hassel]]\n:\'\'for their contributions to the development of the concept of [[tertiary structure|conformation]]\'\'\n[[1970]]
[[Luis F. Leloir]]\n:\'\'for his discovery of sugar nucleotides and their role in the biosynthesis of carbohydrates\'\'\n[[1971]]
[[Gerhard Herzberg]]\n:\'\'for his contributions to electronic structure and the geometry of molecules, particularly free radicals\'\'\n[[1972]]
[[Christian B. Anfinsen]], [[Stanford Moore]], [[William H. Stein]]\n:\'\'for his work on [[ribonuclease]]\'\' \'\'\'and\'\'\' \'\'for their contribution to the understanding of the connection between chemical structure and catalytic activity of the ribonuclease molecule\'\'\n[[1973]]
[[Ernst Otto Fischer]], [[Geoffrey Wilkinson]]\n:\'\'for their work on the chemistry of [[organometallic compound]]s\'\'\n[[1974]]
[[Paul J. Flory]]\n:\'\'for his fundamental work, both theoretical and experimental, in the physical chemistry of macromolecules\'\'\n[[1975]]
[[John Warcup Cornforth]], [[Vladimir Prelog]]\n:\'\'for his work on the [[stereochemistry]] of enzyme-catalyzed reactions\'\' \'\'\'and\'\'\' \'\'for his research into the stereochemistry of organic molecules and reactions\'\'\n[[1976]]
[[William Lipscomb|William Nunn Lipscomb, Jr.]]\n:\'\'for his studies on the structure of [[borane]s\'\'\n[[1977]]
[[Ilya Prigogine]]\n:\'\'for his contributions to non-equilibrium thermodynamics\'\'\n[[1978]]
[[Peter D. Mitchell]]\n:\'\'for his formulation of the [[chemiosmotic theory]]\'\'\n[[1979]]
[[Herbert C. Brown]], [[Georg Wittig]]\n:\'\'for their development of the use of [[boron]]- and [[phosphorus]]-containing compounds, respectively, into reagents in organic synthesis\'\'\n[[1980]]
[[Paul Berg]], [[Walter Gilbert]], [[Frederick Sanger]]\n:\'\'for his studies of the biochemistry of nucleic acids\'\' \'\'\'and\'\'\' \'\'for their contributions concerning the determination of [[DNA sequence|base sequences]] in [[nucleic acid]]s\'\'\n[[1981]]
[[Kenichi Fukui]], [[Roald Hoffmann]]\n:\'\'for their theories concerning the course of chemical reactions\'\'\n[[1982]]
[[Aaron Klug]]\n:\'\'for his development of [[crystallography|crystallographic]] [[electron microscope|electron microscopy]] \'\'\n[[1983]]
[[Henry Taube]]\n:\'\'for his work on the mechanisms of electron transfer reactions\'\'\n[[1984]]
[[Robert Bruce Merrifield]]\n:\'\'for his development of methodology for chemical synthesis on a solid matrix\'\'\n[[1985]]
[[Herbert A. Hauptman]], [[Jerome Karle]]\n:\'\'for their achievements in developing [[crystallography|direct methods]] for the determination of crystal structures\'\'\n[[1986]]
[[Dudley R. Herschbach]], [[Yuan T. Lee]], [[John C. Polanyi]]\n:\'\'for their contributions concerning the dynamics of chemical elementary processes\'\'\n[[1987]]
[[Donald J. Cram]], [[Jean-Marie Lehn]], [[Charles J. Pedersen]]\n:\'\'for their development and use of molecules with structure-specific interactions of high selectivity\'\'\n[[1988]]
[[Johann Deisenhofer]], [[Robert Huber]], [[Hartmut Michel]]\n:\'\'for their determination of the three-dimensional structure of a [[photosynthetic reaction center|photosynthetic reaction centre]]\'\'\n[[1989]]
[[Sidney Altman]], [[Thomas R. Cech]]\n:\'\'for their discovery of catalytic properties of [[RNA]]\'\'\n[[1990]]
[[Elias James Corey]]\n:\'\'for his development of the theory and methodology of organic synthesis\'\'\n[[1991]]
[[Richard R. Ernst]]\n:\'\'for his contributions to the development of high resolution [[nuclear magnetic resonance]] (NMR) spectroscopy\'\'\n[[1992]]
[[Rudolph A. Marcus]]\n:\'\'for his contributions to the theory of electron transfer reactions in chemical systems\'\'\n[[1993]]
[[Kary Mullis|Kary B. Mullis]], [[Michael Smith]]\n:\'\'for contributions to the developments of [[polymerase chain reaction|methods within DNA-based chemistry]]\'\'\n[[1994]]
[[George A. Olah]]\n:\'\'for his contribution to [[carbocation]] chemistry\'\'\n[[1995]]
[[Paul J. Crutzen]], [[Mario J. Molina]], [[F. Sherwood Rowland]]\n:\'\'for their work in [[atmospheric chemistry]]\'\'\n[[1996]]
[[Robert Curl]], Sir [[Harold Kroto]], [[Richard Smalley]]\n:\'\'for their discovery of [[fullerene]]s\'\'\n[[1997]]
[[Paul D. Boyer]], [[John E. Walker]], [[Jens Christian Skou|Jens C. Skou]]\n:\'\'for their elucidation of the enzymatic mechanism underlying the synthesis of adenosine triphosphate\'\' \'\'\'and\'\'\' \'\'for his discovery of an [[Transmembrane ATPase|ion-transporting enzyme]], [[NaKATPase|Na+K+-ATPase]]\'\'\n[[1998]]
[[Walter Kohn]], [[John Pople|John A. Pople]]\n:\'\'for his development of the [[density functional theory]]\'\' \'\'\'and\'\'\' \'\'for his development of computational methods in [[quantum chemistry]]\'\'\n[[1999]]
[[Ahmed H. Zewail]]\n:\'\'for his studies of the transition states of chemical reactions using [[femtosecond]] [[spectroscopy]]\'\'\n[[2000]]
[[Alan J Heeger]], [[Alan G MacDiarmid]], [[Hideki Shirakawa]]\n:\'\'for their discovery and development of conductive polymers\'\'\n[[2001]]
[[William S. Knowles]], [[Ryoji Noyori]], [[K. Barry Sharpless]]\n:\'\'for their work on [[chiral]]ly catalysed [[hydrogenation]] reactions\'\' \'\'\'and\'\'\' \'\'for his work on chirally catalysed [[oxidation]] reactions\'\'\n[[2002]]
[[Kurt Wüthrich]], [[John Fenn|John B. Fenn]], [[Koichi Tanaka]]\n:\'\'for their development of methods for identification and structure analyses of biological macromolecules\'\'\n[[2003]]
[[Peter Agre]], [[Roderick MacKinnon]]\n:\'\'for discoveries concerning [[ion channel|channels]] in [[cell membrane]]s\'\'\n\n==External link==\n*http://www.nobel.se/chemistry/laureates/index.html\n* [http://www.nobel-winners.com/Chemistry/ Timeline of Nobel Prize Winners]\n\n[[cy:Gwobr Cemeg Nobel]]\n[[da:Nobelprisen i kemi]]\n[[de:Liste der Nobelpreisträger für Chemie]]\n[[en:Nobel Prize in Chemistry]]\n[[eo:Premio Nobel de Kemio]]\n[[es:Premio Nobel de Química]]\n[[eu:Kimikako Nobel saria]]\n[[fr:Prix Nobel de chimie]]\n[[fy:Nobelpriis foar de Skiekunde]]\n[[is:Nóbelsverðlaun í efnafræði]]\n[[ja:ノーベル化学賞]]\n[[nl:Nobelprijs voor de Scheikunde]]\n[[pl:Nagroda Nobla w dziedzinie chemii]]\n[[pt:Nobel de Química]]\n[[sl:Nobelova nagrada za kemijo]]','+:en,pt,fy,is,cy,sl -:it fix:pl',8,'Suisui','20040803024529','',0,0,1,0,0.466918182777,'20050208191941','79959196975470'); INSERT INTO cur VALUES (616,0,'Alkémi','[[ca:Alquímia]] [[de:Alchemie]] [[es:Alquimia]] [[fr:Alchimie]] [[ja:錬金術]] [[nl:alchemie]] [[pl:alchemia]] [[sv:Alkemi]] [[zh:%E7%82%BC%E9%87%91%E6%9C%AF]]\n\n\n\'\'\'Alkémi\'\'\' nujul kana prakték [[protoélmu|protoilmiah]] kuna nu ngagabungkeun unsur-unsur [[kimia]], [[fisika]], [[seni]], [[semiotik]], [[métalurgi]], [[tatamba]], [[astrologi]], [[tasaup]], jeung [[agama]]. Udagan umum nu utama para alkémis nyaéta pikeun manggihan cara pikeun [[transmutasi|ngarobah]] [[timah]] jadi [[emas]]. Alkémi bisa dianggap mangrupa bibit buit [[élmu]] modérn [[kimia]] nu ngagunakeun rumusan/aturan [[métode ilmiah]].\n\n\'\'Alkémi\'\' asalna tina kecap [[basa Arab]] \'\'al-kimiya\'\' atawa \'\'al-khimiya\'\' (الكيمياء atawa الخيمياء), nu jigana diwangun tina kecap \'\'al-\'\' jeung kecap [[basa Yunani]] \'\'chymeia\'\' (χυμεία) nu hartina \"cast together\", \"pour together\", \"weld\", \"alloy\" jsb. (tina \'\'chymatos\'\', \"that which is poured out, an ingot\").\n\n==Ihtisar==\n\nPersepsi umum ka alkémis dianggap [[pseudosains|élmuwan palsu]] nu hayang ngarobah [[timah]] jadi [[emas]], nu yakin yén sagala zat dijieunna tina [[unsur klasik|opat unsur]] bumi, hawa, seuneu, jeung cai and dabbled around the edges of [[mysticism]] and [[sihir (paranormal)|sihir]]. From today\'s perspective, these perceptions have some validity, but if we are to be objective we should judge them in the context of their times. They were attempting to explore and investigate nature before many of the most basic scientific tools and practices were available, relying instead on rules of thumb, traditions, basic observations, and mysticism to fill in the gaps. \n\nSangkan bisa ngarti alkémis, bisa dibantu ku ngabayangkeun kumaha kahébatan sihir dina ngarobah hiji barang jadi barang séjénna dina budaya nu teu miboga pangaweruh formal ngeunaan [[fisika]] jeung [[kimia]]. To the alchemist, there was no compelling reason to separate the chemical (material) dimension from the interpretive, symbolic or philosophical one. In those times, and even today, a physics devoid of metaphysical insight would have been as partial and incomplete as a metaphysics devoid of physical manifestation. So the alchemical symbols and processes often had both an inner meaning referring to the spiritual development of the practitioner as well as a material meaning connected to physical transformation of matter. Links between alchemy and the then commonly accepted [[astrology]] were also common. The [[transmutation]] of base [[metal]]s into gold symbolized an endeavour toward perfection or the highest heights of actual existence, and the division of the world into four basic elements was as much a [[geometry|geometric]] [[law (principle)|principle]] as a [[geology|geological]] one. The naive interpretations of some alchemists, or the fraudulent hopes fostered by others should not diminish the undertakings of the more sincere practitioners. \n\nFurther, the field of alchemy evolved greatly over time, beginning as a\nmetallurgical/medicinal arm of religion, maturing into a rich field of study in its own right, devolving into mysticism and outright charlatanism, and in the end providing some of the fundamental [[empirical knowledge]] of the fields of chemistry and modern [[medicine]]. \n\nNepi ka [[abad ka-18]], alkémi dianggap salaku élmu sacara daria di Éropa; misalna, [[Isaac Newton]] neuleuman seni ieu dina waktu nu cukup lila. Alkémis utama séjénna di Éropa nyéta [[Roger Bacon]], Saint [[Thomas Aquinas]], jeung [[Thomas Browne]]. Alkémi mimiti nyirorot pamorna dina abad ka-18 ku lahirna kimia modérn, nu nyadiakeun \'\'framework\'\' nu leuwih precise and reliable framework for matter transmutations and medicine, within a new grand design of the universe based on rational materialism. \n\nThe old matter transmutation ideal of alchemy enjoyed a moment in the sun in the [[20th Century]] when physicists were able to convert lead atoms into gold atoms via a nuclear reaction. However, the new gold atoms lasted for under five seconds before they broke apart. \n\nAlchemical symbolism has been occasionally used in the [[20th Century]] by [[psychologist]]s and philosophers. [[Carl Jung]] re-examined alchemical symbolism and theory and began to show the inner meaning of alchemical work as a [[spirit]]ual path. Alchemical philosophy, symbols and methods have enjoyed something of a renaissance in [[post-modern]] contexts, such as the [[New Age]] movement. Even some physicists have played with alchemical ideas in books such as \'\'[[The Tao of Physics]]\'\' and \'\'[[The Dancing Wu Li Masters]]\'\'.\n\nThe \'\'history\'\' of alchemy, on the other hand, is a \"respectable\" and vigorous academic field. As the obscure — \'\'hermetic\'\', of course — language of the alchemists is gradually being \"deciphered\", historians are becoming more aware of the intellectual connections between that discipline and other facets of Western cultural history, such as the [[Rosicrucianism|Rosicrucian society]] and other mystic societies, [[witchcraft]], and of course the evolution of [[science]] and [[philosophy]].\n\n==Sajarah Alkémi==\n\nNgaran \'\'alkémi\'\' sabenerna ngawengku sababaraha tradisi filosofis nu ngampar ti opat milenia lan tilu benua, jeung deuih kacenderungan basana nu ngarusiah lan simbolik ngahesekeun cukcrukan hubungan sarta silih pangaruhanana.\n\nUrang bisa ngabédakeun sahenteuna aya dua leunjeuran, nu katémbong umumna mandiri, sahanteuna dina tahap awalna: [[alkémi Cina]], nu museur di [[Cina]] jeung wewengkon nu kapangaruhan ku budayana; sarta [[alkémi Kulon]], nu puseurna géséh liwat rébuan taun antara [[Mesir]], [[Yunani]], jeung [[Roma]], dunya [[Islam]], nu ahirna balik deui ka [[Éropah]]. [[Alkémi Cina]] raket pisan patalina jeung [[Taoisme]], sedengkeun [[alkémi Kulon]] ngembangkeun sistim filosofis nu mandiri, with only superficial connections to the major Western religions. It is still an open question whether these two strands share a common origin, or to what extent they influenced each other.\n\n===Alkémi Cina===\nWhereas Western alchemy eventually centered on the transmutation of base metals into noble ones, Chinese alchemy had a more obvious connection to medicine. The [[Philosopher\'s Stone]] of European alchemists can be compared to the [[Grand Elixir of Immortality]] sought by Chinese alchemists. However, in the hermetic view, these two goals were not unconnected; therefore, the two traditions may have had more in common than it initially appears.\n\n[[Black powder]] may have been the most important invention of Chinese alchemists. Described in [[9th century]] texts and used in [[fireworks]] by the [[10th Century]], it was used in [[cannon]]s by [[1290]]. From China, the use of gunpowder spread to Japan, the Mongols, the Arab world and Europe. Gunpowder was used by the Mongols against the Hungarians in [[1241]], and in Europe starting with the 14th century.\n\nChinese alchemy was closely connected to [[Taoist]] forms of [[traditional Chinese medicine|medicine]], such as [[Acupuncture]] and [[Moxibustion]], and to [[martial arts]] such as [[Tai Chi Chuan]] and [[Kung Fu]] (although some Tai Chi schools believe that their art derives from the Hygienic or [[Philosophical]] branches of Taoism, not the Alchemical).\n\n===Alkémi Hindu===\nLittle is known in the West about the character and history of [[India|Hindu]] alchemy. An [[11th century|eleventh century]] Iranian alchemist named [[al-Biruni]] reported that they \"have a science similar to alchemy which is quite peculiar to them. They call it [[Rasayana]]. It means the art which is restricted to certain operations, drugs, compounds, and medicines, most of which are taken from plants. Its principles restored the health of those who were ill beyond hope and gave back youth to fading old age.\"\n\n===Alkémi di Mesir kuna===\nAlkémis Kulon sacara umum nyukcruk sasakala senina ka [[Mesir Kuna]]. [[Metallurgy]] and [[mysticism]] were inexorably tied together in the ancient world, as the transformation of drab ore into shining [[metal]] must have seemed to be an act of magic governed by mysterious rules. It is claimed therefore that Alchemy in Ancient Egypt was the domain of the priestly class. \n\nKota [[Iskandariah]] di Mesir ngarupakeun puseur élmu alkémi, and retained its preminence even after the decline of ancient Egyptian culture, through most of the Greek and Roman periods. Hanjakalna, praktis teu hiji-hiji acan catetan alkémi Mesir nu salamet. Catetan-catetan eta teh, mun memang pernah aya, jigana musna nalika [[Kaisar Romawi|kaisar]] [[Diocletian]] marentah dimusnahkeunana (diduruk) buku-buku alkémi sanggeus hasil numpes baruntakna Iskandariah ([[296]]), nu geus jadi puseur alkémi Mesir. Alkémi Mesir utamana dipikawanoh ngaliwatan tulisan filosof (Hellenis) [[Yunani]] kuna, nu saterusna kasalametkeun satutasna ditarjamahkeun di jaman Islam.\n\nLegend has it that the founder of Egyptian alchemy was the god [[Thoth]], called Hermes-Thoth or Thrice-Great Hermes (\'\'[[Hermes Trismegistus]]\'\') by the Greek. According to legend, he wrote what were called the forty-two Books of Knowledge, covering all fields of knowledge — including alchemy. Hermes\'s symbol was the [[caduceus]] or serpent-staff, which became one of many of alchemy\'s principal symbols. The \"Emerald Tablet\" or \'\'[[Hermetica]]\'\' of Thrice-Greatest Hermes, which is known only through Greek and [[Arabic language|Arabic]] translations, is generally understood to form the basis for Western alchemical philosophy and practice, called the [[hermeticism|hermetic philosophy]] by its early practitioners.\n\nThe first point of the \"Emerald Tablet\" tells the purpose of hermetical science: \"in truth certainly and without doubt, whatever is below is like that which is above, and whatever is above is like that which is below, to accomplish the miracles of one thing.\" ([[Johann Ludwig Burkhardt|Burckhardt]], p. 196-7). This is the [[macrocosm]]-[[microcosm]] belief central to the [[hermetic]] philosophy. In other words, the human body (the microcosm) is affected by the exterior world (the macrocosm), which includes the heavens through [[astrology]], and the earth through the [[element]]s. (Burckhardt,p. 34-42)\n\n===Alkémi di alam Yunani===\nThe Greeks appropriated the hermetical beliefs of the Egyptians and melded with them the philosophies of [[Pythagoras|Pythagoreanism]], [[ionianism]], and [[gnosticism]]. Pythagorean philosophy is, essentially, the belief that numbers rule the universe, originating from the observations of sound, stars, and geometric shapes like triangles, or anything from which a [[ratio]] could be derived. [[Ionia|Ionian]] thought was based on the belief that the universe could be explained through concentration on [[phenomenon|natural phenomena]]; this philosophy is believed to have originated with [[Thales]] and his pupil [[Anaximander]], and later developed by [[Plato]] and [[Aristotle]], whose works came to be an integral part of alchemy. According to this belief, the universe can be described by a few unified [[law (principle)|natural laws]] that can be determined only through careful, thorough, and exacting philosophical explorations. The third component introduced to hermetical philosophy by the Greeks was [[gnosticism]], a belief prevalent in the pre-Christian and early post-Christian [[Roman empire]], that the world is imperfect because it was created in a flawed manner, and that learning about the nature of spiritual matter would lead to salvation. They further believed that [[God]] did not \"create\" the universe in the classic sense, but that the universe was created \"from\" him, but was corrupted in the process (rather than becoming corrupted by the transgressions of Adam and Eve, i.e. [[original sin]]). According to Gnostic belief, by worshipping the cosmos, nature, or the creatures of the world, one worships the True God. Gnostics do not seek salvation from sin, but instead seek to escape ignorance, believing that sin is merely a consequence of ignorance. Platonic and neo-Platonic theories about universals and the omnipotence of God were also absorbed.\n\nOne very important concept introduced at this time, originated by [[Empedocles]] and developed by [[Aristotle]], was that all things in the universe were formed from only four elements: \'\'earth\'\', \'\'air\'\', \'\'water\'\', and \'\'fire\'\'. According to Aristotle, each element had a sphere to which it belonged and to which it would return if left undisturbed. (Lindsay, p. 16) \n\nThe four elements of the Greek were mostly qualitative aspects of matter, not quantitative, as our modern elements are. \"...True alchemy never regarded earth, air, water, and fire as corporeal or chemical substances in the present-day sense of the word. The four elements are simply the primary, and most general, qualities by means of which the amorphous and purely quantitative substance of all bodies first reveals itself in differentiated form.\" (Hitchcock, p. 66) Later alchemists extensively developed the mystical aspects of this concept.\n\n===Alkémi di Kamaharajaan Romawi===\nUrang [[Romawi Kuna|Romawi]] ngadopsi alkémi jeung métafisik ti Yunani, sakumaha maranéhna ngadopsi kalolobaan pangaweruh jeung filosofi Yunani. Dina panungtungan [[kamaharajaan Romawi], filosofi alkémis Yunani ngagabung jeung filosofi hermetik urang Mesir. (Lindsay)\n\nDina mangsa tumuwuhna pangaruh [[Kristen]]... \n\nHowever, the development of [[Christianity]] in the Empire brought a contrary line of thinking, stemming from [[Augustine of Hippo|Augustine]] (354-430 CE), an early Christian philosopher who wrote of his beliefs shortly before the fall of the Roman Empire. In essence, he felt that [[reason]] and [[faith]] could be used to understand God, but [[experimental philosophy]] was evil: \"There is also present in the soul, by means of these same bodily sense, a kind of empty longing and curiosity which aims not at taking pleasure in the flesh but at acquiring experience through the flesh, and this empty curiosity is dignified by the names of learning and science.\" (Augustine, p. 245) \n\nAugustinian ideas were decidedly anti-experimental, yet when Aristotelian experimental techniques were made available to the West they were not shunned. Still, Augustinian thought was well ingrained in [[medieval society]] and was used to show alchemy as being un-Godly. Ultimately, by the high middle ages, this line of thought created a permanent rift separating alchemy from the very religion that had fostered its birth.\n\nMuch of the Roman knowledge of Alchemy, like that of the Greeks and Egyptians, is now lost. In Alexandria, the centre of alchemical studies in the Roman Empire, the art was mainly oral and in the interests of secrecy little was committed to paper. (Whence the use of \"hermetic\" to mean \"secretive\".) (Lindsay, p. 155) It is possible that some writing was done in Alexandria, and that it was subsequently lost or destroyed in fires and the turbulent periods that followed.\n\n===Alkémi Dunya Islam===\nSAnggeus runtagna Kakaisaran Romawi, fokus kamajuan alkémi pindah ka Tatar Arab. Alkémi [[Islam]] leuwih loba dipikanyaho sabab dokuméntasina leuwih hadé: malahan mah, tulisan-tulisan nu leuwih heubeul nepi ka mangsa harita disalametkeun dina mangrupa tarjamah Islam (Arab). (Burckhardt p. 46)\n\nThe Islamic world was a melting pot for alchemy. [[Plato|Platonic]] and [[Aristotle|Aristotelian]] thought, which had already been somewhat appropriated into hermetical science, continued to be assimilated. Islamic alchemists such as [[Abu Bakr Mohammad Ibn Zakariya al-Razi|al-Razi]] (Latin Rasis or Rhazes) contributed key chemical discoveries of their own, such as the technique of distillation (the words \'\'[[alembic]]\'\' and \'\'[[alcohol]]\'\' are of [[Arabic language|Arabic]] origin), the [[muriatic acid|muriatic]], [[sulfuric acid|sulfuric]], and [[nitric acid|nitric]] acids, soda and potash (\'\'[[alkali]]\'\'), and more. The discovery that [[aqua regia]], a mixture of nitric and muriatic acids, could dissolve the noblest metal — gold — was to fuel the imagination of alchemists for the next millennium.\n\nIslamic philosophers also made great contributions to alchemical hermeticism. \nThe most influential author in this regard was arguably [[Jabir ibn-Hayyn]] (Arabic جابر إبن حيان, Latin Geberus; usually rendered in English as Geber). He analyzed each Aristotelian element in terms of four basic qualities of \'\'hotness\'\', \'\'coldness\'\', \'\'dryness\'\', and \'\'moistness\'\'. (Burkhardt, p. 29) Thus, fire was both hot and dry, earth cold and dry, water cold and moist, and air hot and moist. According to Geber, in each metal two of these qualities were interior and two were exterior. For example, lead was externally cold and dry, while gold was hot and moist. Thus, Jabir theorized, by rearranging the qualities of one metal, a different metal would result. (Burckhardt, p. 29) By this reasoning, the search for the [[philosopher\'s stone]] was introduced to Western alchemy. \n\nIt is now commonly accepted that Chinese alchemy influenced Arabic alchemists (Edwards pp. 33-59; Burckhardt, p. 10-22), although the extent of that influence is still a matter of debate. Likewise, [[Hindu]] learning was assimilated into Islamic alchemy, but again the extent and effects of this are not well known.\n\n===Alkémi Éropah Jaman Pertengahan===\nKusabab kuatna patali kana budaya Yunani jeung Romawi, alkémi kalawan gampang bisa ditarima dina filosofi Kristen, ongkoh para alkémis Éropah Pertengahan ogé sacara éksténsif nyerep pangaweruh alkémi Islam. [[Gerbert of Aurillac]], nu engkéna jadi [[Pope Silvester II]], ngarupakeun di antarana nu munggaran mawa sains Islam ka Éropah ti [[Spanyol]]. Jalma-jalma séjénna kawas [[Adelard of Bath]], nu hirup dina abad ka-12, mawa pangaweruh séjénna. Ngan, nepi ka abad ka-13 .... (wah... lieur euy!)\n\nBecause of its strong connections to the Greek and Roman cultures, alchemy was easily accepted into Christian philosophy, and Medieval European alchemists extensively absorbed Islamic alchemical knowledge. [[Gerbert of Aurillac]], who was later to become [[Pope Silvester II]], (d. 1003) was among the first to bring Islamic science to Europe from [[Spain]]. Later men such as [[Adelard of Bath]], who lived in the [[12th century]], brought additional learning. But until the [[13th century|thirteenth century]] the moves were mainly assimilative. (Hollister p. 124, 294)\n\nIn this period there appeared some deviations from the [[Augustinian]] principles of earlier Christian thinkers. [[Saint Anselm]] ([[1033]]-[[1109]]) was an Augustinian who believed faith must precede rationalism, as Augustine and most theologians prior to Anselm had believed, but Anselm put forth the opinion that faith and rationalism were compatible and encouraged rationalism in a Christian context. His views set the stage for the philosophical explosion to occur. [[Saint Abelard]] followed Anselm\'s work, laying the foundation for acceptance of Aristotelian thought before the first works of Aristotle reached the West. His major influence on alchemy was his belief that Platonic universals did not have a separate existence outside of man\'s [[consciousness]]. Abelard also systematized the analysis of philosophical contradictions. (Hollister, p. 287-8)\n\n[[Robert Grosseteste]] ([[1170]]-[[1253]]) was a pioneer of the scientific theory that would later be used and refined by the alchemists. he took\nAbelard\'s methods of analysis and added the use of observations, experimentation, and conclusions in making scientific evaluations. Grosseteste also did much work to bridge Platonic and Aristotelian thinking. (Hollister pp. 294-5)\n\n[[Albertus Magnus]] ([[1193]]-[[1280]]) and [[Thomas Aquinas]] ([[1225]]-[[1274]]) were both [[Dominican]]s who studied Aristotle and worked at reconciling the differences between philosophy and Christianity. Aquinas also did a great deal of work in developing the [[scientific method]]. He even went as far as claiming that universals could be discovered only through [[logical reasoning]]: this ran contrary to the commonly held Platonic belief that universals were found through [[divine illumination]] alone. Magnus and Aquinas were among the first to take up the examination of alchemical theory, and could be considered to be alchemists themselves, except that these two did little in the way of [[experimentation]]. One major contribution of Aquinas was the belief that since [[reason]] could not run in opposition to God, reason must be compatible with [[theology]]. (Hollister p. 290-4, 355)\n\nThe first true alchemist in Medieval Europe was [[Roger Bacon]]. His work did as much for alchemy as [[Robert Boyle]]\'s was to do for [[chemistry]] and [[Galileo]]\'s for [[astronomy]] and [[physics]]. Bacon ([[1214]]-[[1294]]) was an Oxford [[Franciscan]] who explored [[optics]] and [[linguistics|languages]] in addition to alchemy. The Franciscan ideals of taking on the world rather than rejecting the world led to his conviction that experimentation was more important than reasoning: \"Of the three ways in which men think that they acquire [[knowledge]] of things - authority, [[reason|reasoning]], and [[experience]] - only the last is effective and able to bring peace to the intellect.\" (Bacon p. 367) \"[[Experimental Science]] controls the conclusions of all other sciences. It reveals truths which reasoning from [[law (principle)|general principles]] would never have discovered.\" (Hollister p. 294-5) Roger Bacon has also been attributed with originating the search for the philosopher\'s stone and the elixir of life: \"That medicine which will remove all impurities and corruptibilities from the lesser metals will also, in the opinion of the wise, take off so much of the corruptibility of the body that human life may be prolonged for many centuries.\" The idea of [[immortality]] was replaced with the notion of [[longevity|long life]]; after all, man\'s time on Earth was simply to wait and prepare for immortality in the world of God. Immortality on Earth did not mesh with Christian theology. (Edwards p. 37-8)\n\nBacon was not the only alchemist of the high middle ages, but he was the most significant. His works were used by countless alchemists of the fifteenth through nineteenth centuries. Other alchemists of Bacon\'s time shared several traits. First, and most obviously, nearly all were members of the clergy. This was simply because few people outside the parochial schools had the education to examine the Arabic-derived works. Also, alchemy at this time was sanctioned by the church as a good method of exploring and developing theology. Alchemy was interesting to the wide variety of churchmen because it offered a rationalistic view of the universe when men were just beginning to learn about rationalism. (Edwards p. 24-7)\n\nSo by the end of the thirteenth century, alchemy had developed into a fairly structured system of belief. Most importantly, the alchemists were all true \nChristians. They believed in the macrocosm-microcosm theories of Hermes, that is to say, they believed that processes that affect minerals and other substances could have an effect on the human body (e.g., if one could learn\nthe secret of purifying gold, one could use the technique to purify the [[soul|human soul]].) These men believed the philosophers\' stone was a substance that was capable of purifying base metals (and thereby [[transmutation|transmuting]] them to gold) as well as purifying the soul. They believed in the four elements and the four qualities as described above,\nand they had a strong tradition of cloaking their written ideas in a labyrinth of coded [[jargon]] set with traps to mislead the uninitiated. Finally, the alchemists practiced their art: they actively experimented with chemicals and made [[observation]]s and [[theory|theories]] about how the universe operated. Their entire philosophy revolved around their belief that man\'s soul was divided within himself after the fall of Adam. By purifying the two parts of man\'s soul, man could be reunited with God. (Burckhardt p. 149)\n\nIn the fourteenth century, these views underwent a major change. [[William of Ockham]], an [[Oxford]] Franciscan who died in [[1349]], attacked the [[Thomist]] view of compatibility between faith and reason. His view, widely accepted today, was that God must be accepted on faith alone; He could not be limited by human reason. Of course this view was not incorrect if one accepted the postulate of a limitless God versus limited human reasoning capability, but it virtually erased alchemy from practice in the fourteenth and fifteenth centuries. (Hollister p. 335) [[Pope John XXII]] in the early [[1300s]] issued an edict against alchemy, which effectively removed all church personnel from the practice of the Art. (Edwards, p.49) The climate changes, [[Black death|Black plague]], and increase in [[war|warfare]] and [[famine]] that characterized this century no doubt also served to hamper philosophical pursuits in general.\n\nAlchemy was kept alive by men such as [[Nicolas Flamel]], who was noteworthy only because he was one of the few alchemists writing in those troubled times. Flamel lived from [[1330]] to [[1417]] and would serve as the archetype for the next phase of alchemy. He was not a religious scholar as were many of his \npredecessors, and his entire interest in the subject revolved around the pursuit of the philosopher\'s stone, which he is reputed to have found; his work spends a great deal of time describing the processes and reactions, but never actually gives the formula for carrying out the transmutations. Most of his work was aimed at gathering alchemical knowledge that had existed before him, especially as regarded the philosophers\' stone. (Burckhardt pp.170-181)\n\nThrough the [[high middle ages]] (1300-1500) alchemists were much like [[Nicolas Flamel]]: they concentrated on looking for the philosophers\' stone and the elixir of youth (now believed to be separate things.) This had only one possible consequence; the cryptic allusions and [[symbolism]] led to wide variations in interpretation of the art and, while many \"true\", that is, inducted, alchemists existed, many new alchemists interpreted the purification of the soul to mean the [[transmutation]] of lead into gold and pursued this track. These men came to be viewed as [[magic (paranormal)|magicians and\nsorcerers]] by the common people, and were often persecuted for their practices. (Edwards pp. 50-75; Norton pp lxiii-lxvii)\n\n[[Tycho Brahe]], better known for his [[astronomical]] investigations, was also an alchemist. He had a laboratory built for that purpose at his [[Uraniborg]] observatory/research institute.\n\nOne of these men who emerged at the beginning of the sixteenth century was named [[Heinrich Cornelius Agrippa]]. This alchemist believed himself to be a wizard and actually thought himself capable of summoning [[spirit]]s. His influence was negligible, but like Flamel, he produced writings which were referred to by alchemists of later years. Again like Flamel, he did much to change alchemy from a mystical philosophy to an occultist magic. He did keep alive the philosophies of the earlier alchemists, including experimental science, numerology, etc., but he added magic theory, which reinforced the idea of alchemy as an occultist belief. In spite of all this, Agrippa was still a Christian, though his views often came into conflict with the church. Edwardes p56-9; Wilson p.23-9)\n\n===Alkémi di Jaman Modérn jeung Renaissance===\nAlkémi Éropah tetep lumangsung dina cara kieu nepi ka mangsa medalna [[Renaissance]]. \n\nEuropean alchemy continued in this way through the dawning of the [[Renaissance]]. The era also saw a flourishing of [[con artist]]s who would would use chemical tricks and sleight of hand to \"demonstrate\" the transmutation of common metals into gold, or claim to possess secret knowledge that — with a \"small\" initial investment — would surely lead to to that goal. \n\nThe most important name in this period is Philippus Aureolus [[Paracelsus]], (Theocrastus Bombastus von Hohenheim, [[1493]]–[[1541]]) who cast alchemy into a new form, rejecting some of the occultism that had accumulated over the years and promoting the use of observations and experiments to learn about the human body. He rejected Gnostic traditions, but kept much of the Hermetical, neo-Platonic, and Pythagorean philosophies; however, Hermetical science had so much Aristotelian theory that his rejection of Gnosticism was practically meaningless. In particular, Paracelsus rejected the magic theories of Agrippa and Flamel. He did not think of himself as a magician, and scorned those who did. (Williams p.239-45) \n\nParacelsus pioneered the use of chemicals and minerals in medicine, and wrote \"Many have said of Alchemy, that it is for the making of gold and silver. For me such is not the aim, but to consider only what virtue and power may lie in medicines.\" (Edwardes, p.47) His hermetical views were that sickness and health in the body relied on the harmony of man the microcosm and Nature the macrocosm. He took an approach different from those before him, using this analogy not in the manner of soul-purification but in the manner that humans must have certain balances of minerals in their bodies, and that certain illnesses of the body had chemical remedies that could cure them. (Debus & Multhauf, p.6-12)\n\nIn [[England]], the topic of alchemy in that time frame is often associated with Doctor [[John Dee]] ([[13 July]] [[1527]] - [[December]], [[1608]]), better known for his role as astrologer, cryptographer, and general \"scientific consultant\" to [[Queen Elizabeth I]]. Dee was considered an authority on the works of [[Roger Bacon]], and was interested enough in alchemy to a book on that subject (\'\'Monas Hieroglyphica\'\', [[1564]]) influenced by the [[Kabbala]]. In the life and writings of John Dee it is possible to see a parallel development to that of Paracelsus, insofar as Dee was also redefining the alchemical and magical traditions by the application of more modern methodology. Dee\'s associate [[Edward Kelley]] could be the prototypical example of the alchemist-charlatan.\n\n===Nyirorotna alkémi Kulon===\nThe demise of Western alchemy was brought about by the rise of modern science with its emphasis on rigorous quantitative experimentation and its disdain for \"ancient wisdom\". Although the seeds of these events were planted as early as the [[17th century]], alchemy still flourished for some two hundred years, and in fact may have reached its apogee in the [[18th century]].\n\n[[Robert Boyle]] ([[1627]]-[[1691]]), better known for his studies of gases (cf. [[Boyles law]]) pioneered the scientific method in chemical investigations. He assumed nothing in his experiments and compiled every piece of relevant data; in a typical experiment, Boyle would note the place in which the experiment was carried out, the wind characteristics, the position of the sun and moon, and the barometer reading, all just in case they proved to be relevant. (Pilkington p.11) This approach eventually led to the the founding of modern chemistry in the [[18th century|18th]] and [[19th century|19th]] centuries, based on revolutionary discoveries of [[Antoine Lavoisier|Lavoisier]] and [[John Dalton]] — which finally provided a logical, quantitative and reliable framework for understanding matter transmutations, and revealed the futility of longstanding alchemical goals such as the philospher\'s stone. \n\nMeanwhile, Paracelsian alchemy led to the development of modern medicine. Experimentalists gradually uncovered the workings of the human body, such as blood circulation ([[William Harvey|Harvey]], [[1616]]), and eventually traced many diseases to infections with germs ([[Robert Koch|Koch]] and [[Louis Pasteur|Pasteur]], [[19th century]]) or lack of \'\'natural\'\' nutrients and vitamins ([[James Lind|Lind]], [[Christiaan Eijkman|Eijkman]], [[Casimir Funk|Funk]], et al.). Supported by parallel developments in organic chemistry, the new science easily displaced alchemy from its medical roles, interpretive and prescritive, while deflating its hopes of miraculous elixirs and exposing the inefectiveness or even toxicity of its remedies.\n\nThus, as science steadily continued to uncover and rationalize the clockwork of the universe, founded on its own materialistic metaphysics, Alchemy was left deprived of its chemical and medical connections — but still incurably burdened by them. Reduced to an arcane philosophical system, poorly connected to the material world, it suffered the common fate of other esoteric disciplines such as Astrology and Kabalism: excluded from university curricula, shunned by its former patrons, [[damned knowledge|ostracized]] by scientists, and commonly viewed as the epitome of charlatanism and superstition.\n\nThese develpoments could be interpreted as part of a broader reaction in European intellectualism against the [[Romantic]] movement of the preceding century. Be as it may, it is sobering to observe how a discipline that held so much intellectual and material prestige, for more than two thousand years, could disappear so easily from the universe of Western thought. \n\n\'\'\'Also see:\'\'\' [[The four humours]], [[Necromancy]], [[Jungian]] [[Psychology]], [[Historicism]], [[Physics]] and [[Chemistry]]\n\n==Tumbu kaluar==\n* [http://www.levity.com/alchemy/texts.html Naskah sumber primér alkémi online]','',3,'Kandar','20040806041329','',0,0,0,0,0.408707971875,'20041225124916','79959193958670'); INSERT INTO cur VALUES (617,0,'Unsur_kimia','\'\'\'Unsir kimia\'\'\' (kadang ukur disebut \'\'\'unsur\'\'\') téh ngarupakeun matéri nu disusun ku atom-[[atom]] nu jumlah [[proton]] jero [[inti atom|intina]] sarua. Tah jumlah proton ieu nu katelah [[wilangan atom]] unsur. Pikeun conto, sakabéh atom nu jumlah proton na intina aya 6 disebutna atom unsur [[karbon]], jeung sakabéh atom nu boga 92 proton na intina disebut atom unsur [[uranium]].\n\nDi dieu disadiakeun daptar unsur [[Daptar unsur nurutkeun ngaran|nurutkeun ngaran]], [[Daptar unsur nurutkeun lambang|nurutkeun lambang]], jeung [[Daptar unsur nurutkeun wilangan atom|nurutkeun wilangan atom]]. Paling merenah mun dipintonkeun dina bentuk [[tabel periodik]], nu ngumpulkeun/nyusun unsur-unsur dumasar kana kamiripan sipat-sipatna.\n\nAtom-atom unsur nu sarua nu intina ngandung jumlah [[neutron]] nu béda disebut [[isotop]] unsur. Unsur murni bisa aya dina kaayaan unit monoatomik, diatomik, atawa poliatomik nu disusun ku atom-atom nu sarupa. Nu kieu disebutna [[alotrop]]. \n\nNgaran resmi unsur-unsur kimiawi ditangtukeun ku International Union of Pure and Applied Chemistry, [[IUPAC]], nu sacara umum nyokot ngaran nu dipilih ku nu manggihanana. Unsur kimiawi oge dibéré lambang kimiawi nu unik, dumasar kana ngaran unsurna (teu kudu basa Inggris). (Pikeun conto, karbon lambangna \'C\', ari sodium (vérsi Inggris) lambangna \'Na\', tina kecap Latin \"natrium\"). Lambang kimiawi dipaké sacara internasional, sedengkeun ngaran unsurna bisa waé ditarjamahkeun kana basa séwang-séwangan. Lambang kimiawi ditulisna kapital (aksara kahiji), sedengkeun ngaran lengkepna mah henteu, samodél dina conto tadi, iwal mun aya di awal kalimah.\n\nUnsur-unsur bisa ngagabung (réaksi) jadi sanyawa murni (samodél [[cai]], [[uyah]], [[oksida]], jeung [[sanyawa organik]]). Umumna sanyawa-sanyawa ieu mibanda hiji wangunan [[stoikiométri]] jeung struktur sarta sipat nu mandiri.\n\nSababaraha unsur, utamana unsur logam, ngagabung jadi struktur anyar nu wangunanana bisa rupa-rupa (samodél \'\'[[alloy]]\'\' logam). Dina kasus modél kieu, leuwih merenah nyebut fase batan sanyawa.\n\nSacara umum, bahan kimia bisa waé diwangun ku campuran rupa-rupa nu di luhur.\n\n== Tempo ogé ==\n* [[Kimia]]\n* [[Papanggihan unsur kimia]]\n* [[Ayana unsur kimia di alam]]\n* [[Ngaran unsur sistimatis]]\n* [[Elements song]]\n* [[Fictional element]]\n* [[Unsur kimia nu dingaranan saluyu jeung nu manggihna]]\n* [[Unsur kimia nu dingaranan saluyu jeung tempat manggihna]]\n* [[Sanyawa kimia]]\n* [[Talk:Unsur_kimia|Citakan pikeun eusi kaca unsur-unsur kimia]]\n\n== Tumbu kaluar ==\n* [http://www.vanderkrogt.net/elements/ Ngaran unsur multibasa]\n\n[[Category:Kimia]]\n[[Category:unsur kimia]]\n\n[[ca:Element Químic]] [[da:Grundstof]] [[de:Chemisches Element]] [[en:Chemical element]] [[eo:Kemia elemento]] [[es:Elemento químico]] [[et:Keemiline element]] [[fr:Élément chimique]] [[gl:Elemento quimico]] [[it:Elemento (chimico)]] [[ja:元素]] [[nds:Chemisch Element]] [[nl:Scheikundig element]] [[pl:Pierwiastek chemiczny]] [[sv:Grundämne]] [[zh:元素]]','/* Tempo ogé */',3,'Kandar','20050302110408','',0,0,1,0,0.949953701324,'20050302110408','79949697889591'); INSERT INTO cur VALUES (618,0,'Atom','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n\'\'\'\'\'Définisi Séjén\'\'\'\'\'\n* Dina [[Prolog]], atom nunjukkeun hiji niléy husus (sabalikna ti \'\'[[unbound variable]]\'\'), nu nunjukkeun sakabéh niléy nu mungkin.\n* Atom mangrupa ngaran tokoh kartun Jepang nu populér ogé disebut [[Astroboy]].\n* [[Atom (standard)|Atom]] mangrupa standar [[sindikasi wéb]]\n----\n\n\'\'\'Atom\'\'\' ngarupakeun komponén sistem kimiawi pangleutikna nu teu bisa dibeulah/dibagi deui. Kecap ieu diturunkeun tina kecap [[basa Yunani|Yunani]] \'\'atomos\'\', teu bisa dibagi, tina \'\'a-\'\', teu, jeung \'\'tomos\'\', beulah. Biasana ngandung harti atom kimiawi, komponén dasar [[molekul]] jeung [[zat]] biasa. Atom teu bisa dibeulah deui ku [[réaksi kimiawi]], tapi ayeuna geus kapanggih yén atom ogé disusun ku [[partikel subatomik]] nu leuwih leutik. Diaméter atom umumna antara [[1_E-11_m|10pm]] nepi ka [[1_E-10_m|100pm]].\n\nRupa-rupa zat dina kahirupan sapopoé ngarupakeun atom-atom nu mibanda ciri mandiri. Kaayaan partikel kitu rupa mimiti diajengkeun ku filsuf Yunani sapertos [[Democritus]], [[Leucippus]], jeung ku para \'\'[[Epicureanism|Epicureans]]\'\', tapi kusabab teu bari dipaluruh kumaha benerna, konsep éta tilem nepi ka diangkat deui ku [[Rudjer Boscovich]] dina abad ka-18, nu saterusna ku [[John Dalton]] diterapkeun dina [[kimia]].\n\n[[Rudjer Boscovich]] ngedalkeun téorina dumasar ka [[mékanika Newtonian]] taun [[1758]] dina \'\'Theoria philosophiae naturalis redacta ad unicam legem virium in natura existentium\'\'. Numutkeun Boscovich, atom téh mangrupa titik nu teu mibanda struktur, nu némbongkeun gaya silih tolak jeung silih betot, saluyu jeung jarakna. [[John Dalton]] maké téori atom pikeun nerangkeun naha [[gas]] salawasna pacampur dina babandingan nu basajan. Ku ayana hasil gawé [[Amedeo Avogadro]], dina abad ka-19, para ilmuwan mimiti bisa ngabédakeun atom jeung [[molekul]]. DIna mangsa modern, atom geus bisa ditengetan sacara ékspériméntal.\n\nSakumaha nu kabukti ayeuna, tétéla atom sorangan disusun ku [[partikel]] nu leuwih leutik. Nyatana, ampir sakabéh atom ngarupakeun rohangan kosong. Di [[tengah]]na mangrupa [[inti atom|inti]] positip nu leutik nu diwangun ku [[nukleon]] [[proton]] jeung [[neutron]], sedengkeun sésana dieusi ku cangkang-cangkang [[éléktron]] nu saimbang. Atom salawasna boga [[muatan listrik|muatan nétral]] ku ayana [[éléktron]] jeung [[proton]] nu jumlahna sarua. \nAtom umumna digolongkeun dumasar wilangan atomna, saluyu jeung jumlah proton na jero atom. Misalna, atom [[karbon]] nyaéta atom nu boga 6 proton. Sakabéh atom nu boga wilangan atom nu sarua mibanda rupa-rupa sipat fisik tur némbongkeun paripolah kimiawi nu sarua. Rupa-rupa atom dibéréndélkeun na [[Tabel periodik]]. Atom nu mibanda wilangan atom nu sarua tapi beurat atom nu béda (sabab béda jumlah neutronna), disebut [[isotop]]. \n\nAtom nu pangbasajanna, nyéta atom [[hidrogén]] nu mibanda nomer atom 1 jeung ngandung ukur hiji proton jeung hiji éléktron. Atom H ieu jaman kiwari ngarupakeun salah sahiji fokus subjék dina panalungtikan ilmiah, utamana dina munggaran mekarna [[tiori kuantum]].\n\nPolah kimiawi atom loba pisan disababkeun ayana interaksi antaréléktron. Utamana éléktron nu aya dina cangkang pangluarna, disebut éléktron valénsi, boga pangaruh nu panggedéna kana paripolah kimiawi. Éléktron nu di jero (nu lain di cangkang pangluarna) ogé méré pangaruh, ngan biasana dina hal mangaruhan muatan positif na inti atom.\n\nAya kacenderungan nu kuat pikeun atom-atom pikeun sakabéhna ngeusi (atawa ngosongkeun) cangkang éléktron luarna, nu na hidrogén jeung hélium boga rohangan pikeun dua éléktron, sedengkeun di sakabéh atom séjén boga rohangan pikeun dalapan. Ieu kahontal ku maké éléktron babarengan jeung atom tatangga atawa ku cara nyokot éléktron sagemblengna ti atom séjén. Nalika éléktron dipaké bareng, [[beungkeut kovalén]] ngawujud antara dua atom. Beungkeut kovalén ngarupakeun beungkeut atomik nu pangkuatna.\n\nNalika hiji atawa leuwih éléktron sagemblengna dipiceun ti hiji aton ka atom séjénna, mangka kabentuk [[ion]]. Ion ngarupakeun atom nu mibanda [[muatan]] alatan teu saimbangna jumlah proton jeung éléktron. Ion nu narima éléktron disebut \'\'anion\'\', muatanna négatip. Atom nu kaleungitan (ngaleupaskeun) éléktron disebut \'\'kation\'\', muatanna positip. Kation jeung anion silih katarik alatan gaya coulomb antara muatan positip jeung négatip. Tarikan ieu disebutna [[beungkeut ionik|beungkeutan ionik]] nu kakuatanana leuwih lemah batan beungkeutan kovalén.\n\nSakumaha nu geus dipedar di luhur, beungkeutan kovalén nunjukkeun kaayaan nalika éléktron dibagi saimbang antara atom-atom, sedengkeun beungkeutan ionik nunjukkeun yén éléktron sagemblengna dipasrahkeun ka anion. Iwal ti sababaraha kasus ékstrim, teu hiji ogé ti ieu gambaran sagemblengna bener. Dina kalolobaan beungkeutan kovalén, éléktron teu kabagi sarwa saimbang, leuwih loba ngumpul di atom [[éléktronégatip]], nu matak beungkeutan kovalén mibanda sababaraha ciri ionik. Sarua ti éta, dina beungkeutan ionik éléktron kadang sakeudeung ngumpul di atom nu leuwih éléktropositip, nimbulkeun sababaraha ciri kovalén na beungkeut ionik.\n\n==Modél atom==\n*Modél atom bentuk [[Democritus]] (for want of a better name)\n*[[Atom/plum pudding|The plum pudding model]]\n*[[Cubical atom]]\n*[[Modél Bohr]]\n*[[Atom/Modél gelombang|Modél mékanis kuantum]]\n\n==Tempo ogé==\n* [[Atomisme]]\n* [[Atom éksotik]]\n* [[Isotop radioaktif]]\n* [[Daptar partikel]]\n* [[Individual]] (same literal meaning)\n\n==Tumbu kaluar==\n* [http://www.bartleby.com/61/19/A0501900.html The American Heritage Dictionary] (\'\'contains popups\'\')\n\n[[bg:Атом]] [[bs:Atom]] [[ca:Àtom]] [[cs:Atom]] [[da:Atom]] [[de:Atom]] [[en:Atom]] [[eo:Atomo]] [[es:Átomo]] [[et:Aatom]] [[fa:اتم]] [[fi:Atomi]] [[fr:Atome]] [[he:אטום]] [[hr:Atom]] [hu:Atom]] [[ia:Atomo]] [[it:Atomo]] [[ja:原子]] [[la:Atomus]] [[nds:Atom]] [[nl:Atoom]] [[pl:Atom]] [ru:Атом]] [[simple:Atom]] [[sl:Atom]] [[sv:Atom]] [[uk:Атом]] [[zh:原子]]','',3,'Kandar','20040805052200','',0,0,0,0,0.174914200406,'20050126082014','79959194947799'); INSERT INTO cur VALUES (619,1,'Kotak_keusik','tong lieur-liuer ah. :P\r\nUrang muali wae, misalna nyieun list kategorih, terus eusian jang conto, da kudu dimuali atuh heu euh?','',0,'202.153.129.110','20040422105346','',0,0,0,1,0.138798132138,'20040422105346','79959577894653'); INSERT INTO cur VALUES (620,0,'Perang_Bubat','\'\'\'Perang Bubat\'\'\' dimaksudkeun ka hiji kajadian perang Raja Karajaan [[Sunda]] sarta pangiringna ngalawan pasukan Karajaan [[Majapait]]. Dina \'\'[[Pararaton]]\'\' kajadian perang ieu disebut \'\'\'pabubat\'\'\' atawa \'\'\'pasundabubat\'\'\'. Kajadian ieu lumangsung di Bubat, wewengkon kalér Majapait taun 1357 M. Rombongan ti Karajaan Sunda harita ngarupakeun aleutan Raja Sunda jeung pangagung karajaan, kaasup calon prameswari, nyéta [[Dyah Pitaloka]] atawa Citraresmi putri Raja Sunda nu dilamar pikeun nyanding jeung [[Hayam Wuruk]], Raja Majapait. Nalika nepi ka wewengkon Bubat, aleutan calon pangantén dipegat ku utusan Patih [[Gajahmada]] nu ménta sangkan Diah Pitaloka dipasrahkeun ka Hayam Wuruk mangrupa séba taluk Karajaan Sunda ka Karajaan Majapait. Ngarasa dihina jeung dihianat ku ieu paménta, Raja Sunda teu sadia masrahkeun putrina ka Majapait. Dina pamustunganana sakabéh aleutan pangantén bitotama bégalan pati dihuruk ku pasukan Majapait nu jauh leuwih loba. Dina ieu kajadian, sakabéh rombongan Karajaan Sunda gugur, kaasup Dyah Pitaloka nu \'\'labuh tumangan\'\' maéhan manéh.\n\nNumutkeun \'\'[[Carita Parahyangan]]\'\', Raja Sunda nu ngalaman ieu kajadian téh nyéta Prabu Maharaja nu mingpin Karajaan Sunda salila 7 taun (1350-1357), sedeng nurutkeun \'\'[[Pustaka Pararatwan i Bhumi Jawadwipa]]\'\' nu disusun ku Pangéran [[Wangsakerta]] saparakanca (1677-1698), ngaran ieu raja téh [[Linggabuana]]. Kajadian ieu kaunggel ogé dina \'\'[[Kidung Sunda]]\'\'.\n\n\n{{Pondok}}\n\n[[Category:Sajarah Sunda]] [[Category:Sunda]]','',3,'Kandar','20041112011812','',0,0,0,0,0.410553704207,'20050303211247','79958887988187'); INSERT INTO cur VALUES (621,0,'Karajaan_Sunda','Karajaan Sunda ngarupakeun karajaan nu ngadeg ngaganti [[Karajaan Tarumanagara]] nu kabagi dua jadi Karajaan Sunda jeung [[Karajaan Galuh]]. Karajaan Sunda diadegkeun ku [[Tarusbawa]] dina [[Radite]] [[Pon]], 9 [[Suklapaksa]], bulan [[Yista]], taun 591 [[Caka Sunda]].\n\n\n{{Pondok}}\n\n[[Category:Sunda]] [[Category:Sajarah Sunda]]','',3,'Kandar','20050120040527','',0,0,0,0,0.574365985382,'20050303211247','79949879959472'); INSERT INTO cur VALUES (622,0,'Karajaan_Tarumanagara','\'\'\'Karajaan Tarumanagara\'\'\' (atawa Taruma) ngarupakeun salah sahiji karajaan munggaran di Nusantara, diadegkeun ku Rajadirajaguru Jayasingawarman dina taun [[358]] M di wewengkon Bekasi ayeuna. Raja nu kadua satutasna Jayasingawarman pupus nyeta Dharmayawarman ([[382]] - [[395]] M) nu salajengna diteraskeun ku Purnawarman (395 - [[434]] M). Dina taun [[397]] Purnawarman ngalihkeun puseur pamarentahan ka [[Sundapura]] nu leuwih deukeut ka basisir.\n\n\n{{Pondok}}\n\n[[Category:Sajarah Sunda]] [[Category:Sunda]]','',3,'Kandar','20041203062028','',0,0,0,0,0.144651542485,'20050303211247','79958796937971'); INSERT INTO cur VALUES (623,0,'Fermentasi','\'\'\'Fermentation\'\'\' is the [[digestion]] of some matter by [[bacterium|bacteria]] or other small organism (such as [[yeast]]), especially the [[anaerobic]] breakdown of [[sugar]] into [[alcohol]] and [[biogas]].\r\n\r\nFermentation is popularly taken to refer to the fermentation of [[sugar]] in solution to [[alcohol]] using yeast, but other fermentation processes include the making of [[yogurt]]. The science of fermentation is known as [[zymology]].\r\n\r\nIn the process, the organism metabolises one or more substances to produce the energy and chemicals it needs to live and re-produce. This process of chemical reactions will produce some form of by-product. In the case of yeast used for [[brewing]], these by-products are [[carbon dioxide]], and [[ethanol]].\r\n\r\nThe 1811 \'\'Household Cyclopedia\'\' adds:\r\n\r\n\'\'\'\'Alcoholic Beverages\'\'\'\'\r\n\r\nMay be divided into fermented drinks including beer and [[wine]]s, and distilled drinks or spirits which are obtained from the former by distillation. Spirits usually contain about fifty per cent. of alcohol, beer and wines from one to twenty per cent. The alcohol in all cases results from the breaking up of the sugar in the fermenting liquid. \r\n\r\n\'\'\'\'Sugars\'\'\'\' \r\n\r\nOrdinary sugar, or cane sugar, uncrystallizable, or fruit sugar; and grape sugar, or glucose, are the three most important varieties. Fruit sugar exists in all the sub-acid fruits as grapes, currants, apples, peaches, etc. When these are dried, it changes to grape sugar forming the whitish grains which are seen on the outside of prunes, raisins, etc. Grape sugar is found to a limited extent in fruits associated with fruit sugar. Cane sugar is readily changed by the action of acids or ferments into fruit sugar, and the latter into grape sugar, but the process cannot be reversed. Grape sugar is the only fermentable variety, the others becoming changed into it before fermentation. \r\n\r\n\'\'\'\'Transformation of Starch, etc.\'\'\'\' \r\n\r\nUnder the influence of acids, or diastare, a principle existing in germinating grains, starch is changed first into gum (dextrine) and afterwards into grape sugar. Hence one of our most important sources of alcohol is to be found in the starch of barley, corn, wheat, potatoes, etc. Wood may be converted into grape sugar by the action of strong sulphuric acid which is afterwards neutralized. An attempt to produce alcohol in this way on a commercial scale was made in France, but was not successful. \r\n\r\n\'\'\'\'Ferment\'\'\'\' \r\n\r\nA solution of pure sugar will remain unchanged for an indefinite period of time. To induce fermentation, a portion of some nitrogenous body, itself undergoing decomposition, must be added. Such ferments are albumen (white of egg), fibrin (fibre of flesh), casein (basis of cheese), gluten (the pasty matter of flour). Yeast consists of vegetable egg-shaped cells, which is increased during its action as a ferment. \r\n\r\n\'\'\'\'Circumstances influencing Fermentation\'\'\'\' \r\n\r\nIn order that fermentation shall begin we require, besides the contact of the ferment, the presence of air. The most easily decomposed articles of food may be preserved for an indefinite period by hermetically sealing them in jars, after drawing out the air. When once begun, however, fermentation will go on, if the air be excluded. Temperature is important. The most favorable temperature is between 68¡ and 77¡ Fahr. At a low temperature fermentation is exceedingly slow. Bavarian or lager beer is brewed between 32¡ and 46 1/2¡ Fahr. A boiling heat instantly stops fermentation, by killing the ferment. \r\n\r\nTo check fermentation we may remove the yeast by filtration. Hops, oil of mustard, sulphurous acid (from burning sulphur), the sulphites, sulphuric acid, check the process by killing the ferment. \r\n\r\nToo much sugar is unfavorable to fermentation, the best strength for the syrup is ten parts of water to one of sugar. \r\n\r\n\'\'\'\'Changes during Fermentation, etc.\'\'\'\'\r\n\r\nThe grape-sugar breaks up into carbonic acid which escapes as gas, alcohol and water which remain. In malting the grain is allowed to germinate, during which process the starch of the grain is changed into gum and sugar: the rootlets make their appearance at one end and the stalk or [[acrospire]] at the other. The germination is then checked by heating in a kiln; if allowed to proceed a certain portion of the sugar would be converted into woody matter, and lost. \r\n\r\nIn brewing the sacharine matter is extracted from the malt during the mashing. Yeast is added to cause fermentation; an infusion of hops afterwards, to add to the flavor and to check fermentation. In [[wine making]] there is sufficient albuminous matter in the grape to cause fermentation without the use of yeast. \r\n\r\nDistillation separates the alcohol in great part from the water. Alcohol boils at 179¡ Fahr., and water at 212¡. It is not possible, however, to separate entirely alcohol and water by distillation. \r\n\r\n\'\'\'\'Acetic Fermentation\'\'\'\' \r\n\r\nWeak fermented liquors will become sour on exposure to the air. This is owing to the conversion of their alcohol into acetic acid (see [[Vinegar]]). This change is due to the absorption of the oxygen of the air and is much promoted by the presence of a peculiar plant, the mother of vinegar. It is sometimes called the acetous fermentation. \r\n\r\n\'\'\'\'Viscous Fermentation\'\'\'\' \r\n\r\nBy the action of yeast on beet-sugar a peculiar fermentation is set up; but little alcohol is formed. The same gives ropiness to wines and beer. It is checked by vegetable astringents.\r\n\r\n:\'\'See also\'\': [[alcoholic beverages]]\r\n\r\n[[da:Fermentering]] [[de:Fermentation]] [[ja:醗酵]] [[nl:Alcoholische gisting]]','',3,'Kandar','20040428092807','',0,0,0,1,0.124454944452,'20040428092807','79959571907192'); INSERT INTO cur VALUES (624,0,'Wikipédia:Kotrétan','[[en:sandbox]] [[id:kotak pasir]] [[jv:kothak wedhi]] [[ms:kotak pasir]]\n----\n----\n
Kotak keusik
\n----\n----\n\nKumaha ieu? Mani lieur pisan aing mah\n\n-> sumuhun, lier kacida.\naing hayang ulubiung kumaha carana?
auoooooooooooooooooooooooooooo\n\n[[Image:Wikipedia.png|frame|Wikipédia maké aksara Sunda]]\n\n\n\n\n\n
\'\'\'Hal Semasa\'\'\'
\n\n
\'\'\'[[Wikipedia:Hal Semasa|Hal Semasa]]\'\'\' ~ \n\n*\'\'\'[[Special:Newpages|Rencana Baru]], [[Special:Recentchanges|Suntingan Baru]]\'\'\' [[Awan Oort]] - [[Lafal buatan]] - [[Israel dan senjata pemusnahan meluas]] - [[Gnutella]] - [[Justin Frankel]] - [[Napster]] - [[Pengakap]] - [[Boudicca]] - [[Kaca]] - [[Mata]]\n\n*Bakal Medal: \'\'\'Mana-mana yang ada masa\'\'\'.\n\n
\n
\n','',0,'202.150.80.58','20050306113319','',0,0,0,0,0.285510759468,'20050306113319','79949693886680'); INSERT INTO cur VALUES (625,8,'Accesskey-addsection','+','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.649331307643402,'20040602102451','79959397897548'); INSERT INTO cur VALUES (626,8,'Accesskey-anontalk','n','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.779584010857701,'20040602102451','79959397897548'); INSERT INTO cur VALUES (627,8,'Accesskey-anonuserpage','.','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.949926162091946,'20040602102451','79959397897548'); INSERT INTO cur VALUES (628,8,'Accesskey-article','a','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.410878808620273,'20040602102451','79959397897548'); INSERT INTO cur VALUES (629,8,'Accesskey-compareselectedversions','v','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.204615587559171,'20041223055405','79958776944594'); INSERT INTO cur VALUES (630,8,'Accesskey-contributions','<accesskey-contributions>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.790441542668679,'20040602102451','79959397897548'); INSERT INTO cur VALUES (631,8,'Accesskey-currentevents','<accesskey-currentevents>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.33836098139953,'20040602102451','79959397897548'); INSERT INTO cur VALUES (632,8,'Accesskey-delete','d','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.320480309725255,'20040602102451','79959397897548'); INSERT INTO cur VALUES (633,8,'Accesskey-edit','e','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.587318635161332,'20040602102451','79959397897548'); INSERT INTO cur VALUES (634,8,'Accesskey-emailuser','<accesskey-emailuser>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.975152277364537,'20040602102451','79959397897548'); INSERT INTO cur VALUES (635,8,'Accesskey-help','<accesskey-help>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.113805512072337,'20040602102451','79959397897548'); INSERT INTO cur VALUES (636,8,'Accesskey-history','h','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.64357075900172,'20040602102451','79959397897548'); INSERT INTO cur VALUES (637,8,'Accesskey-login','o','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.876437289525231,'20040602102451','79959397897548'); INSERT INTO cur VALUES (638,8,'Accesskey-logout','o','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.45147420135464,'20040602102451','79959397897548'); INSERT INTO cur VALUES (639,8,'Accesskey-mainpage','z','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.628059168931152,'20040602102451','79959397897548'); INSERT INTO cur VALUES (640,8,'Accesskey-minoredit','i','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.785873271325485,'20041223055405','79958776944594'); INSERT INTO cur VALUES (641,8,'Accesskey-move','m','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.0451888805676148,'20040602102451','79959397897548'); INSERT INTO cur VALUES (642,8,'Accesskey-mycontris','y','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.868324619595264,'20040602102451','79959397897548'); INSERT INTO cur VALUES (643,8,'Accesskey-mytalk','n','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.206056487007119,'20040602102451','79959397897548'); INSERT INTO cur VALUES (644,8,'Accesskey-portal','<accesskey-portal>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.42530860698345,'20040602102451','79959397897548'); INSERT INTO cur VALUES (645,8,'Accesskey-preferences','<accesskey-preferences>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.508373604629537,'20040602102451','79959397897548'); INSERT INTO cur VALUES (646,8,'Accesskey-preview','p','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.265942232930979,'20041223055405','79958776944594'); INSERT INTO cur VALUES (647,8,'Accesskey-protect','=','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.80459038149993,'20040602102451','79959397897548'); INSERT INTO cur VALUES (648,8,'Accesskey-randompage','x','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.225125239440357,'20040602102451','79959397897548'); INSERT INTO cur VALUES (649,8,'Accesskey-recentchanges','r','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.711855083435639,'20040602102451','79959397897548'); INSERT INTO cur VALUES (650,8,'Accesskey-recentchangeslinked','c','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.88389972959077,'20040602102451','79959397897548'); INSERT INTO cur VALUES (651,8,'Accesskey-save','s','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.283933428380576,'20041223055405','79958776944594'); INSERT INTO cur VALUES (652,8,'Accesskey-search','f','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.767967983864218,'20041223055405','79958776944594'); INSERT INTO cur VALUES (653,8,'Accesskey-sitesupport','<accesskey-sitesupport>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.988039664913006,'20040602102451','79959397897548'); INSERT INTO cur VALUES (654,8,'Accesskey-specialpage','<accesskey-specialpage>','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.63629440370602,'20040602102451','79959397897548'); INSERT INTO cur VALUES (655,8,'Accesskey-specialpages','q','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.217353054524728,'20040602102451','79959397897548'); INSERT INTO cur VALUES (656,8,'Accesskey-talk','t','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.177882092239225,'20040602102451','79959397897548'); INSERT INTO cur VALUES (657,8,'Accesskey-undelete','d','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.237351328355587,'20040602102451','79959397897548'); INSERT INTO cur VALUES (658,8,'Accesskey-unwatch','w','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.653110395793906,'20040602102451','79959397897548'); INSERT INTO cur VALUES (659,8,'Accesskey-upload','u','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.553498024636412,'20040602102451','79959397897548'); INSERT INTO cur VALUES (660,8,'Accesskey-userpage','.','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.808158966533988,'20040602102451','79959397897548'); INSERT INTO cur VALUES (661,8,'Accesskey-viewsource','e','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.380300789494348,'20040602102451','79959397897548'); INSERT INTO cur VALUES (662,8,'Accesskey-watch','w','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.47702707860342,'20040602102451','79959397897548'); INSERT INTO cur VALUES (663,8,'Accesskey-watchlist','l','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.2442330552677,'20040602102451','79959397897548'); INSERT INTO cur VALUES (664,8,'Accesskey-whatlinkshere','b','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.790084071261887,'20040602102451','79959397897548'); INSERT INTO cur VALUES (665,8,'Addsection','+','',0,'MediaWiki default','20041223055405','sysop',0,0,0,0,0.217721221239978,'20041223055405','79958776944594'); INSERT INTO cur VALUES (666,8,'And','jeung','',3,'Kandar','20040729081653','sysop',0,0,0,0,0.718353923147874,'20040729081653','79959270918346'); INSERT INTO cur VALUES (667,8,'Anontalk','Omongan pikeun IP ieu','',3,'Kandar','20040729081707','sysop',0,0,0,0,0.938605982753081,'20040729081707','79959270918292'); INSERT INTO cur VALUES (668,8,'Anonymous','Pamaké anonim Wikipédia','',3,'Kandar','20040810060011','sysop',0,0,0,0,0.537968175055429,'20040810060011','79959189939988'); INSERT INTO cur VALUES (669,8,'Article','Kaca eusi','',3,'Kandar','20040904050104','sysop',0,0,0,0,0.874022957751549,'20040904050104','79959095949895'); INSERT INTO cur VALUES (670,8,'Compareselectedversions','Bandingkeun vérsi nu dipilih','',3,'Kandar','20040827080106','sysop',0,0,0,0,0.756210294325101,'20040827080106','79959172919893'); INSERT INTO cur VALUES (671,8,'Confirmprotect','Konfirmasi ngonci','',3,'Kandar','20050221110526','sysop',0,0,1,0,0.158982629104501,'20050221110526','79949778889473'); INSERT INTO cur VALUES (672,8,'Confirmprotecttext','Naha anjeun leres hoyong ngonci kaca ieu?','',3,'Kandar','20050221110625','sysop',0,0,1,0,0.52628229328085,'20050221110625','79949778889374'); INSERT INTO cur VALUES (673,8,'Confirmunprotect','Konfirmasi muka konci','',3,'Kandar','20050221110536','sysop',0,0,1,0,0.154463609824389,'20050221110536','79949778889463'); INSERT INTO cur VALUES (674,8,'Confirmunprotecttext','Naha anjeun leres hoyong muka konci kaca ieu?','',3,'Kandar','20050221110612','sysop',0,0,1,0,0.193471200013041,'20050221110612','79949778889387'); INSERT INTO cur VALUES (675,8,'Copyright','Eusi aya dina panangtayungan $1.','',3,'Kandar','20040827080434','sysop',0,0,0,0,0.503965201325682,'20040827080434','79959172919565'); INSERT INTO cur VALUES (676,8,'Delete','Hapus','',3,'Kandar','20040729083842','sysop',0,0,0,0,0.939412437322934,'20040729083842','79959270916157'); INSERT INTO cur VALUES (677,8,'Edit','Édit','',3,'Kandar','20040802085616','sysop',0,0,0,0,0.185166613371267,'20040802085616','79959197914383'); INSERT INTO cur VALUES (678,8,'Feedlinks','Asupan:','',3,'Kandar','20040802094016','sysop',0,0,0,0,0.107595785621177,'20040802094016','79959197905983'); INSERT INTO cur VALUES (679,8,'History_short','Jujutan','',3,'Kandar','20040802094853','sysop',0,0,0,0,0.982479118725731,'20040802094853','79959197905146'); INSERT INTO cur VALUES (680,8,'Import','Impor kaca','',3,'Kandar','20040802095528','sysop',0,0,0,0,0.589608267498769,'20040802095528','79959197904471'); INSERT INTO cur VALUES (681,8,'Importfailed','Ngimpor gagal: $1','',3,'Kandar','20040802095551','sysop',0,0,0,0,0.000604012050297122,'20040802095551','79959197904448'); INSERT INTO cur VALUES (682,8,'Importhistoryconflict','Aya révisi jujutan nu béntrok (may have imported this page before)','',3,'Kandar','20041229063733','sysop',0,0,0,0,0.234195288488823,'20041229063733','79958770936266'); INSERT INTO cur VALUES (683,8,'Importnotext','Kosong atawa teu aya téks','',3,'Kandar','20040802095556','sysop',0,0,0,0,0.16916443702687,'20040802095556','79959197904443'); INSERT INTO cur VALUES (684,8,'Importsuccess','Ngimpor geus hasil!','',3,'Kandar','20040802095615','sysop',0,0,0,0,0.143236350401525,'20040802095615','79959197904384'); INSERT INTO cur VALUES (685,8,'Importtext','Mangga ékspor koropakna ti sumber nu dipaké ku wiki migunakeun fungsi Special:Export, simpen na piringan anjeun, teras muatkeun di dieu.','',3,'Kandar','20040904053055','sysop',0,0,0,0,0.208688471660659,'20040904053055','79959095946944'); INSERT INTO cur VALUES (686,8,'Infobox_alert','Asupkeun téks nu hayang diformat.\\n It will be shown in the infobox for copy and pasting.\\nExample:\\n$1\\nwill become:\\n$2','',3,'Kandar','20040802100310','sysop',0,0,0,0,0.613733337832366,'20040802100310','79959197899689'); INSERT INTO cur VALUES (687,8,'Isbn','ISBN','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.4426013049135,'20041223055408','79958776944591'); INSERT INTO cur VALUES (688,8,'Lastmodifiedby','Kaca ieu panungtungan dirobah $1 ku $2.','',3,'Kandar','20040802100532','sysop',0,0,0,0,0.371806541804044,'20040802100532','79959197899467'); INSERT INTO cur VALUES (689,8,'Loginreqtext','Anjeun kudu \'\'[[special:Userlogin|login]]\'\' pikeun némbongkeun kaca séjén.','',3,'Kandar','20040802101401','sysop',0,0,0,0,0.531228825013366,'20040802101401','79959197898598'); INSERT INTO cur VALUES (690,8,'Loginreqtitle','Kudu asup log','',3,'Kandar','20050221093847','sysop',0,0,1,0,0.540724530388345,'20050221093847','79949778906152'); INSERT INTO cur VALUES (691,8,'Mailerror','Kasalahan ngirim surat: $1','',3,'Kandar','20040924064018','sysop',0,0,0,0,0.109936207635269,'20040924064018','79959075935981'); INSERT INTO cur VALUES (692,8,'Mainpagedocfooter','Mangga tingal \'\'[http://meta.wikipedia.org/wiki/MediaWiki_i18n documentation on customizing the interface]\'\' jeung [http://meta.wikipedia.org/wiki/MediaWiki_User%27s_Guide Tungtunan Pamaké] pikeun pitulung maké jeung konfigurasi.','',3,'Kandar','20040810064221','sysop',0,0,0,0,0.927507477744955,'20040810064221','79959189935778'); INSERT INTO cur VALUES (693,8,'Makesysop','Ngangkat pamaké jadi kuncén','',3,'Kandar','20050208084150','sysop',0,0,0,0,0.307728796552614,'20050208084150','79949791915849'); INSERT INTO cur VALUES (694,8,'Math_bad_output','Can\'t write to or create math output directory','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.75612158026185,'20041223055408','79958776944591'); INSERT INTO cur VALUES (695,8,'Math_bad_tmpdir','Can\'t write to or create math temp directory','',0,'MediaWiki default','20041223055408','sysop',0,0,0,0,0.857421542385054,'20041223055408','79958776944591'); INSERT INTO cur VALUES (696,8,'Math_notexvc','Missing texvc executable; please see math/README to configure.','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.0187430018733656,'20041223055409','79958776944590'); INSERT INTO cur VALUES (697,8,'Missingimage','Gambar leungit
$1','',3,'Kandar','20040827082533','sysop',0,0,0,0,0.52145041294531,'20040827082533','79959172917466'); INSERT INTO cur VALUES (698,8,'Move','Pindahkeun','',3,'Kandar','20040803050729','sysop',0,0,0,0,0.551023089840098,'20040803050729','79959196949270'); INSERT INTO cur VALUES (699,8,'Navigation','Pituduh','',3,'Kandar','20041021050408','sysop',0,0,0,0,0.190764241098207,'20041021050408','79958978949591'); INSERT INTO cur VALUES (700,8,'Nocreativecommons','Creative Commons RDF metadata disabled for this server.','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.300751966704383,'20041223055409','79958776944590'); INSERT INTO cur VALUES (701,8,'Nodublincore','Dublin Core RDF metadata disabled for this server.','',0,'MediaWiki default','20041223055409','sysop',0,0,0,0,0.931467140960942,'20041223055409','79958776944590'); INSERT INTO cur VALUES (702,8,'Notacceptable','\'\'Server\'\' wiki teu bisa nyadiakeun data dina format nu bisa dibaca ku klien anjeun.','',3,'Kandar','20050224110506','sysop',0,0,0,0,0.755079835425205,'20050224110506','79949775889493'); INSERT INTO cur VALUES (703,8,'Nstab-category','Kategori','',3,'Kandar','20040827073655','sysop',0,0,0,0,0.980997784976845,'20040827073655','79959172926344'); INSERT INTO cur VALUES (704,8,'Nstab-help','Pitulung','',3,'Kandar','20040827073638','sysop',0,0,0,0,0.639749449342256,'20040827073638','79959172926361'); INSERT INTO cur VALUES (705,8,'Nstab-image','Gambar','',3,'Kandar','20040827073549','sysop',0,0,0,0,0.255753922514388,'20040827073549','79959172926450'); INSERT INTO cur VALUES (706,8,'Nstab-main','Artikel','',3,'Kandar','20040804064512','sysop',0,0,0,0,0.359521295278819,'20040804064512','79959195935487'); INSERT INTO cur VALUES (707,8,'Nstab-media','Média','',3,'Kandar','20040831062529','sysop',0,0,0,0,0.0303447395845733,'20040831062529','79959168937470'); INSERT INTO cur VALUES (708,8,'Nstab-mediawiki','Pesen','',3,'Kandar','20040804064707','sysop',0,0,0,0,0.0731598428200556,'20040804064707','79959195935292'); INSERT INTO cur VALUES (709,8,'Nstab-special','Husus','',3,'Kandar','20040827073542','sysop',0,0,0,0,0.274765026080203,'20040827073542','79959172926457'); INSERT INTO cur VALUES (710,8,'Nstab-template','Citakan','',3,'Kandar','20040827084907','sysop',0,0,0,0,0.154345632674494,'20040827084907','79959172915092'); INSERT INTO cur VALUES (711,8,'Nstab-user','Kaca pamaké','',3,'Kandar','20040810062419','sysop',0,0,0,0,0.947433115865507,'20040810062419','79959189937580'); INSERT INTO cur VALUES (712,8,'Nstab-wp','Ngeunaan','',3,'Kandar','20040827073502','sysop',0,0,0,0,0.274128712037698,'20040827073502','79959172926497'); INSERT INTO cur VALUES (713,8,'Othercontribs','Dumasar karya $1.','',3,'Kandar','20040831062544','sysop',0,0,0,0,0.528344243325614,'20040831062544','79959168937455'); INSERT INTO cur VALUES (714,8,'Pagetitle','$1 - Wikipédia','',3,'Kandar','20040803050929','sysop',0,0,0,0,0.819335111248619,'20040803050929','79959196949070'); INSERT INTO cur VALUES (715,8,'Perfcached','Data di handap ieu di-\'\'cache\'\' sarta meureun teu mutahir:','',3,'Kandar','20050221095220','sysop',0,0,1,0,0.511642856999899,'20050221095220','79949778904779'); INSERT INTO cur VALUES (716,8,'Personaltools','Parabot pribadi','',3,'Kandar','20040827073235','sysop',0,0,0,0,0.100208981987284,'20040827073235','79959172926764'); INSERT INTO cur VALUES (717,8,'Portal','Panglawungan','',3,'Kandar','20050204041857','sysop',0,0,0,0,0.966116369670365,'20050204041857','79949795958142'); INSERT INTO cur VALUES (718,8,'Portal-url','Wikipédia: Panglawungan','',3,'Kandar','20050204041847','sysop',0,0,0,0,0.529954933123621,'20050204041847','79949795958152'); INSERT INTO cur VALUES (719,8,'Poweredby','Wikipédia dipatéakeun ku [http://www.mediawiki.org/ MédiaWiki], mesin wiki nembrak.','',3,'Kandar','20040827085248','sysop',0,0,0,0,0.751425587340654,'20040827085248','79959172914751'); INSERT INTO cur VALUES (720,8,'Prefs-help-userdata','* Ngaran asli (teu wajib): Mun anjeun milih nyadiakeun, ngaran ieu bakal dipaké pikeun atribusi karya anjeun.
\n* Surélék (teu wajib): Batur bisa nepungan anjeun ti situs wéb tanpa anjeun kudu mikeun alamat surélék anjeun ka batur, sarta bisa dipaké pikeun ngirim sandi anyar mun anjeun poho.','',3,'Kandar','20040827072630','sysop',0,0,0,0,0.167263168066054,'20040827072630','79959172927369'); INSERT INTO cur VALUES (721,8,'Prefs-misc','Pangaturan rupa-rupa','',3,'Kandar','20050224110606','sysop',0,0,0,0,0.582039109041951,'20050224110606','79949775889393'); INSERT INTO cur VALUES (722,8,'Prefs-personal','Data pamaké','',3,'Kandar','20040810062508','sysop',0,0,0,0,0.408406071745237,'20040810062508','79959189937491'); INSERT INTO cur VALUES (723,8,'Prefs-rc','Panémbong robahan anyar jeung tukung','',3,'Kandar','20040827085414','sysop',0,0,0,0,0.29591306233398,'20040827085414','79959172914585'); INSERT INTO cur VALUES (724,8,'Protect','Konci','',3,'Kandar','20050221110619','sysop',0,0,1,0,0.254347127167831,'20050221110619','79949778889380'); INSERT INTO cur VALUES (725,8,'Protectcomment','Alesan ngonci','',3,'Kandar','20050221110710','sysop',0,0,1,0,0.383996479570862,'20050221110710','79949778889289'); INSERT INTO cur VALUES (726,8,'Protectreason','(béré alesan)','',3,'Kandar','20040803061050','sysop',0,0,0,0,0.156941047084463,'20040803061050','79959196938949'); INSERT INTO cur VALUES (727,8,'Protectsub','(Ngonci \"$1\")','',3,'Kandar','20050221110800','sysop',0,0,1,0,0.632715827443372,'20050221110800','79949778889199'); INSERT INTO cur VALUES (728,8,'Proxyblocker','Pameungpeuk proxy','',3,'Kandar','20040827090033','sysop',0,0,0,0,0.692756026697118,'20040827090033','79959172909966'); INSERT INTO cur VALUES (729,8,'Proxyblockreason','Alamat IP anjeun dipeungpeuk sabab mangrupa proxy muka. Mangga tepungan \'\'Internet service provider\'\' atanapi \'\'tech support\'\' anjeun, béjakeun masalah serius ieu.','',3,'Kandar','20040827090227','sysop',0,0,0,0,0.565632681889117,'20040827090227','79959172909772'); INSERT INTO cur VALUES (730,8,'Proxyblocksuccess','Réngsé.','',3,'Kandar','20040803061057','sysop',0,0,0,0,0.749895360087878,'20040803061057','79959196938942'); INSERT INTO cur VALUES (731,8,'Rfcurl','http://www.faqs.org/rfcs/rfc$1.html','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.0525787855056848,'20041223055411','79958776944588'); INSERT INTO cur VALUES (732,8,'Rights','Hak:','',3,'Kandar','20050224111335','sysop',0,0,1,0,0.0132078779984339,'20050224111335','79949775888664'); INSERT INTO cur VALUES (733,8,'Rollback_short','Rollback','',0,'MediaWiki default','20041223055411','sysop',0,0,0,0,0.90830306420876,'20041223055411','79958776944588'); INSERT INTO cur VALUES (734,8,'Selectnewerversionfordiff','Pilih vérsi nu leuwih anyar pikeun babandingan','',3,'Kandar','20040924072128','sysop',0,0,0,0,0.501891717782143,'20040924072128','79959075927871'); INSERT INTO cur VALUES (735,8,'Selectolderversionfordiff','Pilih vérsi nu leuwih heubeul pikeun babandingan','',3,'Kandar','20040924072152','sysop',0,0,0,0,0.784549427018081,'20040924072152','79959075927847'); INSERT INTO cur VALUES (736,8,'Seriousxhtmlerrors','There were serious xhtml markup errors detected by tidy.','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.417072012477621,'20041223055412','79958776944587'); INSERT INTO cur VALUES (737,8,'Set_rights_fail','HAk pamaké pikeun \"$1\" teu bisa diatur. (Ngaran nu diasupkeun geus bener can?)','',3,'Kandar','20040810064332','sysop',0,0,0,0,0.731711812067509,'20040810064332','79959189935667'); INSERT INTO cur VALUES (738,8,'Set_user_rights','Atur hak pamaké','',3,'Kandar','20040810064344','sysop',0,0,0,0,0.407343053638323,'20040810064344','79959189935655'); INSERT INTO cur VALUES (739,8,'Siteuser','Pamaké $1 Wikipédia','',3,'Kandar','20040810063013','sysop',0,0,0,0,0.841579862722736,'20040810063013','79959189936986'); INSERT INTO cur VALUES (740,8,'Siteusers','Pamaké $1 Wikipédia','',3,'Kandar','20040810063035','sysop',0,0,0,0,0.985870183432354,'20040810063035','79959189936964'); INSERT INTO cur VALUES (741,8,'Specialpage','Kaca Husus','',3,'Kandar','20040803083729','sysop',0,0,0,0,0.404611359727207,'20040803083729','79959196916270'); INSERT INTO cur VALUES (742,8,'Talk','Sawala','',3,'Kandar','20040803022742','sysop',0,0,0,0,0.0654462790726184,'20040803022742','79959196977257'); INSERT INTO cur VALUES (743,8,'Talkpagetext','','',0,'MediaWiki default','20041223055412','sysop',0,0,0,0,0.113397346915116,'20041223055412','79958776944587'); INSERT INTO cur VALUES (744,8,'Toolbox','Kotak parabot','',3,'Kandar','20040803023337','sysop',0,0,0,0,0.370647928091369,'20040803023337','79959196976662'); INSERT INTO cur VALUES (745,8,'Tooltip-addsection','Add a comment to this page. [alt-+]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.513047630445145,'20040602102451','79959397897548'); INSERT INTO cur VALUES (746,8,'Tooltip-anontalk','Discussion about edits from this ip address [alt-n]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.45329439868526,'20040602102451','79959397897548'); INSERT INTO cur VALUES (747,8,'Tooltip-anonuserpage','The user page for the ip you\'re editing as [alt-.]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.727329132824511,'20040602102451','79959397897548'); INSERT INTO cur VALUES (748,8,'Tooltip-article','View the content page [alt-a]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.276762498800422,'20040602102451','79959397897548'); INSERT INTO cur VALUES (749,8,'Tooltip-atom','Atom feed for this page','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.201825126262219,'20040602102451','79959397897548'); INSERT INTO cur VALUES (750,8,'Tooltip-compareselectedversions','Tempo béda antara dua vérsi kaca ieu nu dipilih [alt-v].','',3,'Kandar','20040803023436','sysop',0,0,0,0,0.178838165643474,'20040803023436','79959196976563'); INSERT INTO cur VALUES (751,8,'Tooltip-contributions','View the list of contributions of this user','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.28871548016436,'20040602102451','79959397897548'); INSERT INTO cur VALUES (752,8,'Tooltip-currentevents','Find background information on current events','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.907062934625021,'20040602102451','79959397897548'); INSERT INTO cur VALUES (753,8,'Tooltip-delete','Delete this page [alt-d]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.669168263365671,'20040602102451','79959397897548'); INSERT INTO cur VALUES (754,8,'Tooltip-edit','You can edit this page. Please use the preview button before saving. [alt-e]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.624652543686938,'20040602102451','79959397897548'); INSERT INTO cur VALUES (755,8,'Tooltip-emailuser','Send a mail to this user','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.115757959071321,'20040602102451','79959397897548'); INSERT INTO cur VALUES (756,8,'Tooltip-help','The place to find out.','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.704832195029438,'20040602102451','79959397897548'); INSERT INTO cur VALUES (757,8,'Tooltip-history','Past versions of this page, [alt-h]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.176887128666869,'20040602102451','79959397897548'); INSERT INTO cur VALUES (758,8,'Tooltip-login','You are encouraged to log in, it is not mandatory however. [alt-o]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.769939088979679,'20040602102451','79959397897548'); INSERT INTO cur VALUES (759,8,'Tooltip-logout','Log out [alt-o]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.319034089631433,'20040602102451','79959397897548'); INSERT INTO cur VALUES (760,8,'Tooltip-mainpage','Visit the Main Page [alt-z]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.285353211951771,'20040602102451','79959397897548'); INSERT INTO cur VALUES (761,8,'Tooltip-minoredit','Tandaan ieu salaku éditan minor [alt-i]','',3,'Kandar','20040924072315','sysop',0,0,0,0,0.469663821598202,'20040924072315','79959075927684'); INSERT INTO cur VALUES (762,8,'Tooltip-move','Move this page [alt-m]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.492259502869341,'20040602102451','79959397897548'); INSERT INTO cur VALUES (763,8,'Tooltip-mycontris','List of my contributions [alt-y]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.0523060802857448,'20040602102451','79959397897548'); INSERT INTO cur VALUES (764,8,'Tooltip-mytalk','My talk page [alt-n]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.784751923554346,'20040602102451','79959397897548'); INSERT INTO cur VALUES (765,8,'Tooltip-nomove','You don\'t have the permissions to move this page','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.76684140764814,'20040602102451','79959397897548'); INSERT INTO cur VALUES (766,8,'Tooltip-portal','About the project, what you can do, where to find things','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.479951298311307,'20040602102451','79959397897548'); INSERT INTO cur VALUES (767,8,'Tooltip-preferences','My preferences','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.0992322993457618,'20040602102451','79959397897548'); INSERT INTO cur VALUES (768,8,'Tooltip-preview','Sawang heula robahan anjeun, pami tos leres mangga simpen! [alt-p]','',3,'Kandar','20040906071257','sysop',0,0,0,0,0.056307632528532,'20040906071257','79959093928742'); INSERT INTO cur VALUES (769,8,'Tooltip-protect','Protect this page [alt-=]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.983841295339019,'20040602102451','79959397897548'); INSERT INTO cur VALUES (770,8,'Tooltip-randompage','Load a random page [alt-x]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.750283609843146,'20040602102451','79959397897548'); INSERT INTO cur VALUES (771,8,'Tooltip-recentchanges','The list of recent changes in the wiki. [alt-r]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.799894193932316,'20040602102451','79959397897548'); INSERT INTO cur VALUES (772,8,'Tooltip-recentchangeslinked','Recent changes in pages linking to this page [alt-c]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.748620170865785,'20040602102451','79959397897548'); INSERT INTO cur VALUES (773,8,'Tooltip-rss','RSS feed for this page','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.343418303265626,'20040602102451','79959397897548'); INSERT INTO cur VALUES (774,8,'Tooltip-save','Simpen parobahan anjeun [alt-s]','',3,'Kandar','20041231060252','sysop',0,0,0,0,0.471231034464418,'20041231060252','79958768939747'); INSERT INTO cur VALUES (775,8,'Tooltip-search','Téang wiki ieu [alt-f]','',3,'Kandar','20040906064620','sysop',0,0,0,0,0.325900293258857,'20040906064620','79959093935379'); INSERT INTO cur VALUES (776,8,'Tooltip-sitesupport','Support Wikipedia','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.215808393634677,'20040602102451','79959397897548'); INSERT INTO cur VALUES (777,8,'Tooltip-specialpage','This is a special page, you can\'t edit the page itself.','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.10134111913046,'20040602102451','79959397897548'); INSERT INTO cur VALUES (778,8,'Tooltip-specialpages','List of all special pages [alt-q]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.859280445481912,'20040602102451','79959397897548'); INSERT INTO cur VALUES (779,8,'Tooltip-talk','Discussion about the content page [alt-t]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.992378900751824,'20040602102451','79959397897548'); INSERT INTO cur VALUES (780,8,'Tooltip-undelete','Restore $1 deleted edits to this page [alt-d]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.384053198047032,'20040602102451','79959397897548'); INSERT INTO cur VALUES (781,8,'Tooltip-unwatch','Remove this page from your watchlist [alt-w]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.943129318713331,'20040602102451','79959397897548'); INSERT INTO cur VALUES (782,8,'Tooltip-upload','Upload images or media files [alt-u]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.563487030159204,'20040602102451','79959397897548'); INSERT INTO cur VALUES (783,8,'Tooltip-userpage','My user page [alt-.]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.988047225389674,'20040602102451','79959397897548'); INSERT INTO cur VALUES (784,8,'Tooltip-viewsource','This page is protected. You can view it\'s source. [alt-e]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.2497750672044,'20040602102451','79959397897548'); INSERT INTO cur VALUES (785,8,'Tooltip-watch','Tambahkeun kaca ieu kana awaskeuneun kuring [alt-w]','',3,'Kandar','20050224111801','sysop',0,0,1,0,0.284733690586624,'20050224111801','79949775888198'); INSERT INTO cur VALUES (786,8,'Tooltip-watchlist','The list of pages you\'re monitoring for changes. [alt-l]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.674343282053567,'20040602102451','79959397897548'); INSERT INTO cur VALUES (787,8,'Tooltip-whatlinkshere','List of all wiki pages that link here [alt-b]','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.517515369241606,'20040602102451','79959397897548'); INSERT INTO cur VALUES (788,8,'Undelete_short','Tong dihapus','',3,'Kandar','20040906071339','sysop',0,0,0,0,0.564547030780974,'20040906071339','79959093928660'); INSERT INTO cur VALUES (789,8,'Unprotect','Buka konci','',3,'Kandar','20050221110818','sysop',0,0,1,0,0.270189076913697,'20050221110818','79949778889181'); INSERT INTO cur VALUES (790,8,'Unprotectcomment','Alesan muka konci','',3,'Kandar','20050221110748','sysop',0,0,1,0,0.657304322959207,'20050221110748','79949778889251'); INSERT INTO cur VALUES (791,8,'Unprotectsub','(Muka konci \"$1\")','',3,'Kandar','20050221110553','sysop',0,0,1,0,0.475954414788591,'20050221110553','79949778889446'); INSERT INTO cur VALUES (792,8,'Unwatch','Eureun ngawaskeun','',3,'Kandar','20050224111937','sysop',0,0,1,0,0.407859135798979,'20050224111937','79949775888062'); INSERT INTO cur VALUES (793,8,'User_rights_set','Hak pamaké pikeun \"$1\" geus dirobah','',3,'Kandar','20040810064931','sysop',0,0,0,0,0.611432465362765,'20040810064931','79959189935068'); INSERT INTO cur VALUES (794,8,'Usercssjs','\'\'\'Note:\'\'\' After saving, you have to tell your bowser to get the new version: \'\'\'Mozilla:\'\'\' click \'\'reload\'\'(or \'\'ctrl-r\'\'), \'\'\'IE / Opera:\'\'\' \'\'ctrl-f5\'\', \'\'\'Safari:\'\'\' \'\'cmd-r\'\', \'\'\'Konqueror\'\'\' \'\'ctrl-r\'\'.','',0,'MediaWiki default','20040602102451','sysop',0,0,0,0,0.833584950150535,'20040602102451','79959397897548'); INSERT INTO cur VALUES (795,8,'Usercssjsyoucanpreview','Tip: Pigunakeun tombol \'Témbongkeun sawangan\' pikeun nyoba css/js anyar anjeun méméh nyimpen.','',3,'Kandar','20040906072710','sysop',0,0,0,0,0.333627385398026,'20040906072710','79959093927289'); INSERT INTO cur VALUES (796,8,'Usercsspreview','\'\'\'Inget yén anjeun ukur nyawang css pamaké anjeun, can disimpen!\'\'\'','',3,'Kandar','20040810065012','sysop',0,0,0,0,0.167382107272169,'20040810065012','79959189934987'); INSERT INTO cur VALUES (797,8,'Userjspreview','\'\'\'Inget yén anjeun ukur nguji/nyawang \'\'javascript\'\' pamaké anjeun, can disimpen!\'\'\'','',3,'Kandar','20040810065112','sysop',0,0,0,0,0.836028410900411,'20040810065112','79959189934887'); INSERT INTO cur VALUES (798,8,'Usermailererror','Mail object returned error: ','',0,'MediaWiki default','20041223055413','sysop',0,0,0,0,0.677995763419192,'20041223055413','79958776944586'); INSERT INTO cur VALUES (799,8,'Watch','Awaskeun','',3,'Kandar','20040803102846','sysop',0,0,0,0,0.881893615128373,'20040803102846','79959196897153'); INSERT INTO cur VALUES (800,8,'Yourrealname','Ngaran anjeun*','',3,'Kandar','20040906073319','sysop',0,0,0,0,0.375480816117936,'20040906073319','79959093926680'); INSERT INTO cur VALUES (801,10,'All_system_messages','{{int:allmessagestext}}\n\n
\n\'\'\'Name\'\'\'\n\n\'\'\'Default text\'\'\'\n\n\'\'\'Current text\'\'\'\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:1movedto2&action=edit 1movedto2]
\n[[MediaWiki_talk:1movedto2|Talk]]\n
\n$1 moved to $2\n\n{{int:1movedto2}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:About&action=edit about]
\n[[MediaWiki_talk:About|Talk]]\n
\nAbout\n\n{{int:About}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Aboutpage&action=edit aboutpage]
\n[[MediaWiki_talk:Aboutpage|Talk]]\n
\nWikipedia:About\n\n{{int:Aboutpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Aboutwikipedia&action=edit aboutwikipedia]
\n[[MediaWiki_talk:Aboutwikipedia|Talk]]\n
\nAbout Wikipedia\n\n{{int:Aboutwikipedia}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-addsection&action=edit accesskey-addsection]
\n[[MediaWiki_talk:Accesskey-addsection|Talk]]\n
\n+\n\n{{int:Accesskey-addsection}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-anontalk&action=edit accesskey-anontalk]
\n[[MediaWiki_talk:Accesskey-anontalk|Talk]]\n
\nn\n\n{{int:Accesskey-anontalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-anonuserpage&action=edit accesskey-anonuserpage]
\n[[MediaWiki_talk:Accesskey-anonuserpage|Talk]]\n
\n.\n\n{{int:Accesskey-anonuserpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-article&action=edit accesskey-article]
\n[[MediaWiki_talk:Accesskey-article|Talk]]\n
\na\n\n{{int:Accesskey-article}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-compareselectedversions&action=edit accesskey-compareselectedversions]
\n[[MediaWiki_talk:Accesskey-compareselectedversions|Talk]]\n
\nv\n\n{{int:Accesskey-compareselectedversions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-contributions&action=edit accesskey-contributions]
\n[[MediaWiki_talk:Accesskey-contributions|Talk]]\n
\n&lt;accesskey-contributions&gt;\n\n{{int:Accesskey-contributions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-currentevents&action=edit accesskey-currentevents]
\n[[MediaWiki_talk:Accesskey-currentevents|Talk]]\n
\n&lt;accesskey-currentevents&gt;\n\n{{int:Accesskey-currentevents}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-delete&action=edit accesskey-delete]
\n[[MediaWiki_talk:Accesskey-delete|Talk]]\n
\nd\n\n{{int:Accesskey-delete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-edit&action=edit accesskey-edit]
\n[[MediaWiki_talk:Accesskey-edit|Talk]]\n
\ne\n\n{{int:Accesskey-edit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-emailuser&action=edit accesskey-emailuser]
\n[[MediaWiki_talk:Accesskey-emailuser|Talk]]\n
\n&lt;accesskey-emailuser&gt;\n\n{{int:Accesskey-emailuser}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-help&action=edit accesskey-help]
\n[[MediaWiki_talk:Accesskey-help|Talk]]\n
\n&lt;accesskey-help&gt;\n\n{{int:Accesskey-help}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-history&action=edit accesskey-history]
\n[[MediaWiki_talk:Accesskey-history|Talk]]\n
\nh\n\n{{int:Accesskey-history}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-login&action=edit accesskey-login]
\n[[MediaWiki_talk:Accesskey-login|Talk]]\n
\no\n\n{{int:Accesskey-login}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-logout&action=edit accesskey-logout]
\n[[MediaWiki_talk:Accesskey-logout|Talk]]\n
\no\n\n{{int:Accesskey-logout}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-mainpage&action=edit accesskey-mainpage]
\n[[MediaWiki_talk:Accesskey-mainpage|Talk]]\n
\nz\n\n{{int:Accesskey-mainpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-minoredit&action=edit accesskey-minoredit]
\n[[MediaWiki_talk:Accesskey-minoredit|Talk]]\n
\ni\n\n{{int:Accesskey-minoredit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-move&action=edit accesskey-move]
\n[[MediaWiki_talk:Accesskey-move|Talk]]\n
\nm\n\n{{int:Accesskey-move}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-mycontris&action=edit accesskey-mycontris]
\n[[MediaWiki_talk:Accesskey-mycontris|Talk]]\n
\ny\n\n{{int:Accesskey-mycontris}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-mytalk&action=edit accesskey-mytalk]
\n[[MediaWiki_talk:Accesskey-mytalk|Talk]]\n
\nn\n\n{{int:Accesskey-mytalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-portal&action=edit accesskey-portal]
\n[[MediaWiki_talk:Accesskey-portal|Talk]]\n
\n&lt;accesskey-portal&gt;\n\n{{int:Accesskey-portal}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-preferences&action=edit accesskey-preferences]
\n[[MediaWiki_talk:Accesskey-preferences|Talk]]\n
\n&lt;accesskey-preferences&gt;\n\n{{int:Accesskey-preferences}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-preview&action=edit accesskey-preview]
\n[[MediaWiki_talk:Accesskey-preview|Talk]]\n
\np\n\n{{int:Accesskey-preview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-protect&action=edit accesskey-protect]
\n[[MediaWiki_talk:Accesskey-protect|Talk]]\n
\n=\n\n{{int:Accesskey-protect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-randompage&action=edit accesskey-randompage]
\n[[MediaWiki_talk:Accesskey-randompage|Talk]]\n
\nx\n\n{{int:Accesskey-randompage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-recentchanges&action=edit accesskey-recentchanges]
\n[[MediaWiki_talk:Accesskey-recentchanges|Talk]]\n
\nr\n\n{{int:Accesskey-recentchanges}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-recentchangeslinked&action=edit accesskey-recentchangeslinked]
\n[[MediaWiki_talk:Accesskey-recentchangeslinked|Talk]]\n
\nc\n\n{{int:Accesskey-recentchangeslinked}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-save&action=edit accesskey-save]
\n[[MediaWiki_talk:Accesskey-save|Talk]]\n
\ns\n\n{{int:Accesskey-save}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-search&action=edit accesskey-search]
\n[[MediaWiki_talk:Accesskey-search|Talk]]\n
\nf\n\n{{int:Accesskey-search}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-sitesupport&action=edit accesskey-sitesupport]
\n[[MediaWiki_talk:Accesskey-sitesupport|Talk]]\n
\n&lt;accesskey-sitesupport&gt;\n\n{{int:Accesskey-sitesupport}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-specialpage&action=edit accesskey-specialpage]
\n[[MediaWiki_talk:Accesskey-specialpage|Talk]]\n
\n&lt;accesskey-specialpage&gt;\n\n{{int:Accesskey-specialpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-specialpages&action=edit accesskey-specialpages]
\n[[MediaWiki_talk:Accesskey-specialpages|Talk]]\n
\nq\n\n{{int:Accesskey-specialpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-talk&action=edit accesskey-talk]
\n[[MediaWiki_talk:Accesskey-talk|Talk]]\n
\nt\n\n{{int:Accesskey-talk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-undelete&action=edit accesskey-undelete]
\n[[MediaWiki_talk:Accesskey-undelete|Talk]]\n
\nd\n\n{{int:Accesskey-undelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-unwatch&action=edit accesskey-unwatch]
\n[[MediaWiki_talk:Accesskey-unwatch|Talk]]\n
\nw\n\n{{int:Accesskey-unwatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-upload&action=edit accesskey-upload]
\n[[MediaWiki_talk:Accesskey-upload|Talk]]\n
\nu\n\n{{int:Accesskey-upload}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-userpage&action=edit accesskey-userpage]
\n[[MediaWiki_talk:Accesskey-userpage|Talk]]\n
\n.\n\n{{int:Accesskey-userpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-viewsource&action=edit accesskey-viewsource]
\n[[MediaWiki_talk:Accesskey-viewsource|Talk]]\n
\ne\n\n{{int:Accesskey-viewsource}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-watch&action=edit accesskey-watch]
\n[[MediaWiki_talk:Accesskey-watch|Talk]]\n
\nw\n\n{{int:Accesskey-watch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-watchlist&action=edit accesskey-watchlist]
\n[[MediaWiki_talk:Accesskey-watchlist|Talk]]\n
\nl\n\n{{int:Accesskey-watchlist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accesskey-whatlinkshere&action=edit accesskey-whatlinkshere]
\n[[MediaWiki_talk:Accesskey-whatlinkshere|Talk]]\n
\nb\n\n{{int:Accesskey-whatlinkshere}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accmailtext&action=edit accmailtext]
\n[[MediaWiki_talk:Accmailtext|Talk]]\n
\nThe Password for '$1' has been sent to $2.\n\n{{int:Accmailtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Accmailtitle&action=edit accmailtitle]
\n[[MediaWiki_talk:Accmailtitle|Talk]]\n
\nPassword sent.\n\n{{int:Accmailtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Actioncomplete&action=edit actioncomplete]
\n[[MediaWiki_talk:Actioncomplete|Talk]]\n
\nAction complete\n\n{{int:Actioncomplete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Addedwatch&action=edit addedwatch]
\n[[MediaWiki_talk:Addedwatch|Talk]]\n
\nAdded to watchlist\n\n{{int:Addedwatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Addedwatchtext&action=edit addedwatchtext]
\n[[MediaWiki_talk:Addedwatchtext|Talk]]\n
\nThe page "$1" has been added to your [[Special:Watchlist|watchlist]].\nFuture changes to this page and its associated Talk page will be listed there,\nand the page will appear '''bolded''' in the [[Special:Recentchanges|list of recent changes]] to\nmake it easier to pick out.\n\n<p>If you want to remove the page from your watchlist later, click "Stop watching" in the sidebar.\n\n{{int:Addedwatchtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Addsection&action=edit addsection]
\n[[MediaWiki_talk:Addsection|Talk]]\n
\n+\n\n{{int:Addsection}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Administrators&action=edit administrators]
\n[[MediaWiki_talk:Administrators|Talk]]\n
\nWikipedia:Administrators\n\n{{int:Administrators}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Affirmation&action=edit affirmation]
\n[[MediaWiki_talk:Affirmation|Talk]]\n
\nI affirm that the copyright holder of this file\nagrees to license it under the terms of the $1.\n\n{{int:Affirmation}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:All&action=edit all]
\n[[MediaWiki_talk:All|Talk]]\n
\nall\n\n{{int:All}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allmessages&action=edit allmessages]
\n[[MediaWiki_talk:Allmessages|Talk]]\n
\nAll system messages\n\n{{int:Allmessages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allmessagestext&action=edit allmessagestext]
\n[[MediaWiki_talk:Allmessagestext|Talk]]\n
\nThis is a list of all system messages available in the MediaWiki: namespace.\n\n{{int:Allmessagestext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Allpages&action=edit allpages]
\n[[MediaWiki_talk:Allpages|Talk]]\n
\nAll pages\n\n{{int:Allpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alphaindexline&action=edit alphaindexline]
\n[[MediaWiki_talk:Alphaindexline|Talk]]\n
\n$1 to $2\n\n{{int:Alphaindexline}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alreadyloggedin&action=edit alreadyloggedin]
\n[[MediaWiki_talk:Alreadyloggedin|Talk]]\n
\n<font color=red><b>User $1, you are already logged in!</b></font><br />\n\n\n{{int:Alreadyloggedin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Alreadyrolled&action=edit alreadyrolled]
\n[[MediaWiki_talk:Alreadyrolled|Talk]]\n
\nCannot rollback last edit of [[$1]]\nby [[User:$2|$2]] ([[User talk:$2|Talk]]); someone else has edited or rolled back the page already. \n\nLast edit was by [[User:$3|$3]] ([[User talk:$3|Talk]]). \n\n{{int:Alreadyrolled}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ancientpages&action=edit ancientpages]
\n[[MediaWiki_talk:Ancientpages|Talk]]\n
\nOldest pages\n\n{{int:Ancientpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:And&action=edit and]
\n[[MediaWiki_talk:And|Talk]]\n
\nand\n\n{{int:And}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Anontalk&action=edit anontalk]
\n[[MediaWiki_talk:Anontalk|Talk]]\n
\nTalk for this IP\n\n{{int:Anontalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Anontalkpagetext&action=edit anontalkpagetext]
\n[[MediaWiki_talk:Anontalkpagetext|Talk]]\n
\n----''This is the discussion page for an anonymous user who has not created an account yet or who does not use it. We therefore have to use the numerical [[IP address]] to identify him/her. Such an IP address can be shared by several users. If you are an anonymous user and feel that irrelevant comments have been directed at you, please [[Special:Userlogin|create an account or log in]] to avoid future confusion with other anonymous users.'' \n\n{{int:Anontalkpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Anonymous&action=edit anonymous]
\n[[MediaWiki_talk:Anonymous|Talk]]\n
\nAnonymous user(s) of Wikipedia\n\n{{int:Anonymous}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Article&action=edit article]
\n[[MediaWiki_talk:Article|Talk]]\n
\nContent page\n\n{{int:Article}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Articleexists&action=edit articleexists]
\n[[MediaWiki_talk:Articleexists|Talk]]\n
\nA page of that name already exists, or the\nname you have chosen is not valid.\nPlease choose another name.\n\n{{int:Articleexists}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Articlepage&action=edit articlepage]
\n[[MediaWiki_talk:Articlepage|Talk]]\n
\nView content page\n\n{{int:Articlepage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Asksql&action=edit asksql]
\n[[MediaWiki_talk:Asksql|Talk]]\n
\nSQL query\n\n{{int:Asksql}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Asksqltext&action=edit asksqltext]
\n[[MediaWiki_talk:Asksqltext|Talk]]\n
\nUse the form below to make a direct query of the\ndatabase.\nUse single quotes ('like this') to delimit string literals.\nThis can often add considerable load to the server, so please use\nthis function sparingly.\n\n{{int:Asksqltext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Autoblocker&action=edit autoblocker]
\n[[MediaWiki_talk:Autoblocker|Talk]]\n
\nAutoblocked because you share an IP address with "$1". Reason "$2".\n\n{{int:Autoblocker}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badarticleerror&action=edit badarticleerror]
\n[[MediaWiki_talk:Badarticleerror|Talk]]\n
\nThis action cannot be performed on this page.\n\n{{int:Badarticleerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badfilename&action=edit badfilename]
\n[[MediaWiki_talk:Badfilename|Talk]]\n
\nImage name has been changed to "$1".\n\n{{int:Badfilename}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badfiletype&action=edit badfiletype]
\n[[MediaWiki_talk:Badfiletype|Talk]]\n
\n".$1" is not a recommended image file format.\n\n{{int:Badfiletype}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badipaddress&action=edit badipaddress]
\n[[MediaWiki_talk:Badipaddress|Talk]]\n
\nInvalid IP address\n\n{{int:Badipaddress}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badquery&action=edit badquery]
\n[[MediaWiki_talk:Badquery|Talk]]\n
\nBadly formed search query\n\n{{int:Badquery}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badquerytext&action=edit badquerytext]
\n[[MediaWiki_talk:Badquerytext|Talk]]\n
\nWe could not process your query.\nThis is probably because you have attempted to search for a\nword fewer than three letters long, which is not yet supported.\nIt could also be that you have mistyped the expression, for\nexample "fish and and scales".\nPlease try another query.\n\n{{int:Badquerytext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badretype&action=edit badretype]
\n[[MediaWiki_talk:Badretype|Talk]]\n
\nThe passwords you entered do not match.\n\n{{int:Badretype}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badtitle&action=edit badtitle]
\n[[MediaWiki_talk:Badtitle|Talk]]\n
\nBad title\n\n{{int:Badtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Badtitletext&action=edit badtitletext]
\n[[MediaWiki_talk:Badtitletext|Talk]]\n
\nThe requested page title was invalid, empty, or\nan incorrectly linked inter-language or inter-wiki title.\n\n{{int:Badtitletext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blanknamespace&action=edit blanknamespace]
\n[[MediaWiki_talk:Blanknamespace|Talk]]\n
\n(Main)\n\n{{int:Blanknamespace}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockedtext&action=edit blockedtext]
\n[[MediaWiki_talk:Blockedtext|Talk]]\n
\nYour user name or IP address has been blocked by $1.\nThe reason given is this:<br />''$2''<p>You may contact $1 or one of the other\n[[Wikipedia:Administrators|administrators]] to discuss the block.\n\nNote that you may not use the "email this user" feature unless you have a valid email address registered in your [[Special:Preferences|user preferences]].\n\nYour IP address is $3. Please include this address in any queries you make.\n\n\n{{int:Blockedtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockedtitle&action=edit blockedtitle]
\n[[MediaWiki_talk:Blockedtitle|Talk]]\n
\nUser is blocked\n\n{{int:Blockedtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockip&action=edit blockip]
\n[[MediaWiki_talk:Blockip|Talk]]\n
\nBlock user\n\n{{int:Blockip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockipsuccesssub&action=edit blockipsuccesssub]
\n[[MediaWiki_talk:Blockipsuccesssub|Talk]]\n
\nBlock succeeded\n\n{{int:Blockipsuccesssub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockipsuccesstext&action=edit blockipsuccesstext]
\n[[MediaWiki_talk:Blockipsuccesstext|Talk]]\n
\n"$1" has been blocked.\n<br />See [[Special:Ipblocklist|IP block list]] to review blocks.\n\n{{int:Blockipsuccesstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blockiptext&action=edit blockiptext]
\n[[MediaWiki_talk:Blockiptext|Talk]]\n
\nUse the form below to block write access\nfrom a specific IP address or username.\nThis should be done only only to prevent vandalism, and in\naccordance with [[Wikipedia:Policy|policy]].\nFill in a specific reason below (for example, citing particular\npages that were vandalized).\n\n{{int:Blockiptext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklink&action=edit blocklink]
\n[[MediaWiki_talk:Blocklink|Talk]]\n
\nblock\n\n{{int:Blocklink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklistline&action=edit blocklistline]
\n[[MediaWiki_talk:Blocklistline|Talk]]\n
\n$1, $2 blocked $3 (expires $4)\n\n{{int:Blocklistline}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogentry&action=edit blocklogentry]
\n[[MediaWiki_talk:Blocklogentry|Talk]]\n
\nblocked "$1" with an expiry time of $2\n\n{{int:Blocklogentry}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogpage&action=edit blocklogpage]
\n[[MediaWiki_talk:Blocklogpage|Talk]]\n
\nBlock_log\n\n{{int:Blocklogpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Blocklogtext&action=edit blocklogtext]
\n[[MediaWiki_talk:Blocklogtext|Talk]]\n
\nThis is a log of user blocking and unblocking actions. Automatically \nblocked IP addresses are not be listed. See the [[Special:Ipblocklist|IP block list]] for\nthe list of currently operational bans and blocks.\n\n{{int:Blocklogtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bold_sample&action=edit bold_sample]
\n[[MediaWiki_talk:Bold_sample|Talk]]\n
\nBold text\n\n{{int:Bold_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bold_tip&action=edit bold_tip]
\n[[MediaWiki_talk:Bold_tip|Talk]]\n
\nBold text\n\n{{int:Bold_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Booksources&action=edit booksources]
\n[[MediaWiki_talk:Booksources|Talk]]\n
\nBook sources\n\n{{int:Booksources}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Booksourcetext&action=edit booksourcetext]
\n[[MediaWiki_talk:Booksourcetext|Talk]]\n
\nBelow is a list of links to other sites that\nsell new and used books, and may also have further information\nabout books you are looking for.Wikipedia is not affiliated with any of these businesses, and\nthis list should not be construed as an endorsement.\n\n{{int:Booksourcetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Brokenredirects&action=edit brokenredirects]
\n[[MediaWiki_talk:Brokenredirects|Talk]]\n
\nBroken Redirects\n\n{{int:Brokenredirects}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Brokenredirectstext&action=edit brokenredirectstext]
\n[[MediaWiki_talk:Brokenredirectstext|Talk]]\n
\nThe following redirects link to a non-existing pages.\n\n{{int:Brokenredirectstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bugreports&action=edit bugreports]
\n[[MediaWiki_talk:Bugreports|Talk]]\n
\nBug reports\n\n{{int:Bugreports}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bugreportspage&action=edit bugreportspage]
\n[[MediaWiki_talk:Bugreportspage|Talk]]\n
\nWikipedia:Bug_reports\n\n{{int:Bugreportspage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucratlog&action=edit bureaucratlog]
\n[[MediaWiki_talk:Bureaucratlog|Talk]]\n
\nBureaucrat_log\n\n{{int:Bureaucratlog}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucratlogentry&action=edit bureaucratlogentry]
\n[[MediaWiki_talk:Bureaucratlogentry|Talk]]\n
\nRights for user "$1" set "$2"\n\n{{int:Bureaucratlogentry}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucrattext&action=edit bureaucrattext]
\n[[MediaWiki_talk:Bureaucrattext|Talk]]\n
\nThe action you have requested can only be\nperformed by sysops with "bureaucrat" status.\n\n{{int:Bureaucrattext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bureaucrattitle&action=edit bureaucrattitle]
\n[[MediaWiki_talk:Bureaucrattitle|Talk]]\n
\nBureaucrat access required\n\n{{int:Bureaucrattitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bydate&action=edit bydate]
\n[[MediaWiki_talk:Bydate|Talk]]\n
\nby date\n\n{{int:Bydate}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Byname&action=edit byname]
\n[[MediaWiki_talk:Byname|Talk]]\n
\nby name\n\n{{int:Byname}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Bysize&action=edit bysize]
\n[[MediaWiki_talk:Bysize|Talk]]\n
\nby size\n\n{{int:Bysize}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cachederror&action=edit cachederror]
\n[[MediaWiki_talk:Cachederror|Talk]]\n
\nThe following is a cached copy of the requested page, and may not be up to date.\n\n{{int:Cachederror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cancel&action=edit cancel]
\n[[MediaWiki_talk:Cancel|Talk]]\n
\nCancel\n\n{{int:Cancel}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cannotdelete&action=edit cannotdelete]
\n[[MediaWiki_talk:Cannotdelete|Talk]]\n
\nCould not delete the page or image specified. (It may have already been deleted by someone else.)\n\n{{int:Cannotdelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cantrollback&action=edit cantrollback]
\n[[MediaWiki_talk:Cantrollback|Talk]]\n
\nCannot revert edit; last contributor is only author of this page.\n\n{{int:Cantrollback}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Categories&action=edit categories]
\n[[MediaWiki_talk:Categories|Talk]]\n
\nCategories\n\n{{int:Categories}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Category&action=edit category]
\n[[MediaWiki_talk:Category|Talk]]\n
\ncategory\n\n{{int:Category}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Category_header&action=edit category_header]
\n[[MediaWiki_talk:Category_header|Talk]]\n
\nArticles in category "$1"\n\n{{int:Category_header}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Changepassword&action=edit changepassword]
\n[[MediaWiki_talk:Changepassword|Talk]]\n
\nChange password\n\n{{int:Changepassword}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Changes&action=edit changes]
\n[[MediaWiki_talk:Changes|Talk]]\n
\nchanges\n\n{{int:Changes}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Columns&action=edit columns]
\n[[MediaWiki_talk:Columns|Talk]]\n
\nColumns\n\n{{int:Columns}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Commentedit&action=edit commentedit]
\n[[MediaWiki_talk:Commentedit|Talk]]\n
\n (comment)\n\n{{int:Commentedit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Compareselectedversions&action=edit compareselectedversions]
\n[[MediaWiki_talk:Compareselectedversions|Talk]]\n
\nCompare selected versions\n\n{{int:Compareselectedversions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirm&action=edit confirm]
\n[[MediaWiki_talk:Confirm|Talk]]\n
\nConfirm\n\n{{int:Confirm}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmcheck&action=edit confirmcheck]
\n[[MediaWiki_talk:Confirmcheck|Talk]]\n
\nYes, I really want to delete this.\n\n{{int:Confirmcheck}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmdelete&action=edit confirmdelete]
\n[[MediaWiki_talk:Confirmdelete|Talk]]\n
\nConfirm delete\n\n{{int:Confirmdelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmdeletetext&action=edit confirmdeletetext]
\n[[MediaWiki_talk:Confirmdeletetext|Talk]]\n
\nYou are about to permanently delete a page\nor image along with all of its history from the database.\nPlease confirm that you intend to do this, that you understand the\nconsequences, and that you are doing this in accordance with\n[[Wikipedia:Policy]].\n\n{{int:Confirmdeletetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmprotect&action=edit confirmprotect]
\n[[MediaWiki_talk:Confirmprotect|Talk]]\n
\nConfirm protection\n\n{{int:Confirmprotect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmprotecttext&action=edit confirmprotecttext]
\n[[MediaWiki_talk:Confirmprotecttext|Talk]]\n
\nDo you really want to protect this page?\n\n{{int:Confirmprotecttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmunprotect&action=edit confirmunprotect]
\n[[MediaWiki_talk:Confirmunprotect|Talk]]\n
\nConfirm unprotection\n\n{{int:Confirmunprotect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Confirmunprotecttext&action=edit confirmunprotecttext]
\n[[MediaWiki_talk:Confirmunprotecttext|Talk]]\n
\nDo you really want to unprotect this page?\n\n{{int:Confirmunprotecttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contextchars&action=edit contextchars]
\n[[MediaWiki_talk:Contextchars|Talk]]\n
\nCharacters of context per line\n\n{{int:Contextchars}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contextlines&action=edit contextlines]
\n[[MediaWiki_talk:Contextlines|Talk]]\n
\nLines to show per hit\n\n{{int:Contextlines}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contribslink&action=edit contribslink]
\n[[MediaWiki_talk:Contribslink|Talk]]\n
\ncontribs\n\n{{int:Contribslink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contribsub&action=edit contribsub]
\n[[MediaWiki_talk:Contribsub|Talk]]\n
\nFor $1\n\n{{int:Contribsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Contributions&action=edit contributions]
\n[[MediaWiki_talk:Contributions|Talk]]\n
\nUser contributions\n\n{{int:Contributions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyright&action=edit copyright]
\n[[MediaWiki_talk:Copyright|Talk]]\n
\nContent is available under $1.\n\n{{int:Copyright}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightpage&action=edit copyrightpage]
\n[[MediaWiki_talk:Copyrightpage|Talk]]\n
\nWikipedia:Copyrights\n\n{{int:Copyrightpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightpagename&action=edit copyrightpagename]
\n[[MediaWiki_talk:Copyrightpagename|Talk]]\n
\nWikipedia copyright\n\n{{int:Copyrightpagename}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Copyrightwarning&action=edit copyrightwarning]
\n[[MediaWiki_talk:Copyrightwarning|Talk]]\n
\nPlease note that all contributions to Wikipedia are\nconsidered to be released under the GNU Free Documentation License\n(see $1 for details).\nIf you don't want your writing to be edited mercilessly and redistributed\nat will, then don't submit it here.<br />\nYou are also promising us that you wrote this yourself, or copied it from a\npublic domain or similar free resource.\n<strong>DO NOT SUBMIT COPYRIGHTED WORK WITHOUT PERMISSION!</strong>\n\n{{int:Copyrightwarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Couldntremove&action=edit couldntremove]
\n[[MediaWiki_talk:Couldntremove|Talk]]\n
\nCouldn't remove item '$1'...\n\n{{int:Couldntremove}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Createaccount&action=edit createaccount]
\n[[MediaWiki_talk:Createaccount|Talk]]\n
\nCreate new account\n\n{{int:Createaccount}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Createaccountmail&action=edit createaccountmail]
\n[[MediaWiki_talk:Createaccountmail|Talk]]\n
\nby email\n\n{{int:Createaccountmail}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Cur&action=edit cur]
\n[[MediaWiki_talk:Cur|Talk]]\n
\ncur\n\n{{int:Cur}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Currentevents&action=edit currentevents]
\n[[MediaWiki_talk:Currentevents|Talk]]\n
\nCurrent events\n\n{{int:Currentevents}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Currentrev&action=edit currentrev]
\n[[MediaWiki_talk:Currentrev|Talk]]\n
\nCurrent revision\n\n{{int:Currentrev}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Databaseerror&action=edit databaseerror]
\n[[MediaWiki_talk:Databaseerror|Talk]]\n
\nDatabase error\n\n{{int:Databaseerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dateformat&action=edit dateformat]
\n[[MediaWiki_talk:Dateformat|Talk]]\n
\nDate format\n\n{{int:Dateformat}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dberrortext&action=edit dberrortext]
\n[[MediaWiki_talk:Dberrortext|Talk]]\n
\nA database query syntax error has occurred.\nThis could be because of an illegal search query (see $5),\nor it may indicate a bug in the software.\nThe last attempted database query was:\n<blockquote><tt>$1</tt></blockquote>\nfrom within function "<tt>$2</tt>".\nMySQL returned error "<tt>$3: $4</tt>".\n\n{{int:Dberrortext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dberrortextcl&action=edit dberrortextcl]
\n[[MediaWiki_talk:Dberrortextcl|Talk]]\n
\nA database query syntax error has occurred.\nThe last attempted database query was:\n"$1"\nfrom within function "$2".\nMySQL returned error "$3: $4".\n\n\n{{int:Dberrortextcl}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deadendpages&action=edit deadendpages]
\n[[MediaWiki_talk:Deadendpages|Talk]]\n
\nDead-end pages\n\n{{int:Deadendpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Debug&action=edit debug]
\n[[MediaWiki_talk:Debug|Talk]]\n
\nDebug\n\n{{int:Debug}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Defaultns&action=edit defaultns]
\n[[MediaWiki_talk:Defaultns|Talk]]\n
\nSearch in these namespaces by default:\n\n{{int:Defaultns}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Defemailsubject&action=edit defemailsubject]
\n[[MediaWiki_talk:Defemailsubject|Talk]]\n
\nWikipedia e-mail\n\n{{int:Defemailsubject}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Delete&action=edit delete]
\n[[MediaWiki_talk:Delete|Talk]]\n
\nDelete\n\n{{int:Delete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletecomment&action=edit deletecomment]
\n[[MediaWiki_talk:Deletecomment|Talk]]\n
\nReason for deletion\n\n{{int:Deletecomment}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletedarticle&action=edit deletedarticle]
\n[[MediaWiki_talk:Deletedarticle|Talk]]\n
\ndeleted "$1"\n\n{{int:Deletedarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletedtext&action=edit deletedtext]
\n[[MediaWiki_talk:Deletedtext|Talk]]\n
\n"$1" has been deleted.\nSee $2 for a record of recent deletions.\n\n{{int:Deletedtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deleteimg&action=edit deleteimg]
\n[[MediaWiki_talk:Deleteimg|Talk]]\n
\ndel\n\n{{int:Deleteimg}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletepage&action=edit deletepage]
\n[[MediaWiki_talk:Deletepage|Talk]]\n
\nDelete page\n\n{{int:Deletepage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletesub&action=edit deletesub]
\n[[MediaWiki_talk:Deletesub|Talk]]\n
\n(Deleting "$1")\n\n{{int:Deletesub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletethispage&action=edit deletethispage]
\n[[MediaWiki_talk:Deletethispage|Talk]]\n
\nDelete this page\n\n{{int:Deletethispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Deletionlog&action=edit deletionlog]
\n[[MediaWiki_talk:Deletionlog|Talk]]\n
\ndeletion log\n\n{{int:Deletionlog}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dellogpage&action=edit dellogpage]
\n[[MediaWiki_talk:Dellogpage|Talk]]\n
\nDeletion_log\n\n{{int:Dellogpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Dellogpagetext&action=edit dellogpagetext]
\n[[MediaWiki_talk:Dellogpagetext|Talk]]\n
\nBelow is a list of the most recent deletions.\nAll times shown are server time (UTC).\n<ul>\n</ul>\n\n\n{{int:Dellogpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developerspheading&action=edit developerspheading]
\n[[MediaWiki_talk:Developerspheading|Talk]]\n
\nFor developer use only\n\n{{int:Developerspheading}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developertext&action=edit developertext]
\n[[MediaWiki_talk:Developertext|Talk]]\n
\nThe action you have requested can only be\nperformed by users with "developer" status.\nSee $1.\n\n{{int:Developertext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Developertitle&action=edit developertitle]
\n[[MediaWiki_talk:Developertitle|Talk]]\n
\nDeveloper access required\n\n{{int:Developertitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Diff&action=edit diff]
\n[[MediaWiki_talk:Diff|Talk]]\n
\ndiff\n\n{{int:Diff}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Difference&action=edit difference]
\n[[MediaWiki_talk:Difference|Talk]]\n
\n(Difference between revisions)\n\n{{int:Difference}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguations&action=edit disambiguations]
\n[[MediaWiki_talk:Disambiguations|Talk]]\n
\nDisambiguation pages\n\n{{int:Disambiguations}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguationspage&action=edit disambiguationspage]
\n[[MediaWiki_talk:Disambiguationspage|Talk]]\n
\nWikipedia:Links_to_disambiguating_pages\n\n{{int:Disambiguationspage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disambiguationstext&action=edit disambiguationstext]
\n[[MediaWiki_talk:Disambiguationstext|Talk]]\n
\nThe following pages link to a <i>disambiguation page</i>. They should link to the appropriate topic instead.<br />A page is treated as dismbiguation if it is linked from $1.<br />Links from other namespaces are <i>not</i> listed here.\n\n{{int:Disambiguationstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disclaimerpage&action=edit disclaimerpage]
\n[[MediaWiki_talk:Disclaimerpage|Talk]]\n
\nWikipedia:General_disclaimer\n\n{{int:Disclaimerpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Disclaimers&action=edit disclaimers]
\n[[MediaWiki_talk:Disclaimers|Talk]]\n
\nDisclaimers\n\n{{int:Disclaimers}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Doubleredirects&action=edit doubleredirects]
\n[[MediaWiki_talk:Doubleredirects|Talk]]\n
\nDouble Redirects\n\n{{int:Doubleredirects}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Doubleredirectstext&action=edit doubleredirectstext]
\n[[MediaWiki_talk:Doubleredirectstext|Talk]]\n
\n<b>Attention:</b> This list may contain false positives. That usually means there is additional text with links below the first #REDIRECT.<br />\nEach row contains links to the first and second redirect, as well as the first line of the second redirect text, usually giving the "real" target page, which the first redirect should point to.\n\n{{int:Doubleredirectstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Edit&action=edit edit]
\n[[MediaWiki_talk:Edit|Talk]]\n
\nEdit\n\n{{int:Edit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editcomment&action=edit editcomment]
\n[[MediaWiki_talk:Editcomment|Talk]]\n
\nThe edit comment was: "<i>$1</i>".\n\n{{int:Editcomment}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editconflict&action=edit editconflict]
\n[[MediaWiki_talk:Editconflict|Talk]]\n
\nEdit conflict: $1\n\n{{int:Editconflict}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editcurrent&action=edit editcurrent]
\n[[MediaWiki_talk:Editcurrent|Talk]]\n
\nEdit the current version of this page\n\n{{int:Editcurrent}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Edithelp&action=edit edithelp]
\n[[MediaWiki_talk:Edithelp|Talk]]\n
\nEditing help\n\n{{int:Edithelp}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Edithelppage&action=edit edithelppage]
\n[[MediaWiki_talk:Edithelppage|Talk]]\n
\nHelp:Editing\n\n{{int:Edithelppage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editing&action=edit editing]
\n[[MediaWiki_talk:Editing|Talk]]\n
\nEditing $1\n\n{{int:Editing}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editingold&action=edit editingold]
\n[[MediaWiki_talk:Editingold|Talk]]\n
\n<strong>WARNING: You are editing an out-of-date\nrevision of this page.\nIf you save it, any changes made since this revision will be lost.</strong>\n\n\n{{int:Editingold}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editsection&action=edit editsection]
\n[[MediaWiki_talk:Editsection|Talk]]\n
\nedit\n\n{{int:Editsection}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Editthispage&action=edit editthispage]
\n[[MediaWiki_talk:Editthispage|Talk]]\n
\nEdit this page\n\n{{int:Editthispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailflag&action=edit emailflag]
\n[[MediaWiki_talk:Emailflag|Talk]]\n
\nDisable e-mail from other users\n\n{{int:Emailflag}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailforlost&action=edit emailforlost]
\n[[MediaWiki_talk:Emailforlost|Talk]]\n
\nFields marked with a star (*) are optional. Storing an email address enables people to contact you through the website without you having to reveal your \nemail address to them, and it can be used to send you a new password if you forget it.<br /><br />Your real name, if you choose to provide it, will be used for giving you attribution for your work.\n\n{{int:Emailforlost}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailfrom&action=edit emailfrom]
\n[[MediaWiki_talk:Emailfrom|Talk]]\n
\nFrom\n\n{{int:Emailfrom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailmessage&action=edit emailmessage]
\n[[MediaWiki_talk:Emailmessage|Talk]]\n
\nMessage\n\n{{int:Emailmessage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailpage&action=edit emailpage]
\n[[MediaWiki_talk:Emailpage|Talk]]\n
\nE-mail user\n\n{{int:Emailpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailpagetext&action=edit emailpagetext]
\n[[MediaWiki_talk:Emailpagetext|Talk]]\n
\nIf this user has entered a valid e-mail address in\nhis or her user preferences, the form below will send a single message.\nThe e-mail address you entered in your user preferences will appear\nas the "From" address of the mail, so the recipient will be able\nto reply.\n\n{{int:Emailpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsend&action=edit emailsend]
\n[[MediaWiki_talk:Emailsend|Talk]]\n
\nSend\n\n{{int:Emailsend}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsent&action=edit emailsent]
\n[[MediaWiki_talk:Emailsent|Talk]]\n
\nE-mail sent\n\n{{int:Emailsent}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsenttext&action=edit emailsenttext]
\n[[MediaWiki_talk:Emailsenttext|Talk]]\n
\nYour e-mail message has been sent.\n\n{{int:Emailsenttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailsubject&action=edit emailsubject]
\n[[MediaWiki_talk:Emailsubject|Talk]]\n
\nSubject\n\n{{int:Emailsubject}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailto&action=edit emailto]
\n[[MediaWiki_talk:Emailto|Talk]]\n
\nTo\n\n{{int:Emailto}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Emailuser&action=edit emailuser]
\n[[MediaWiki_talk:Emailuser|Talk]]\n
\nE-mail this user\n\n{{int:Emailuser}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Enterlockreason&action=edit enterlockreason]
\n[[MediaWiki_talk:Enterlockreason|Talk]]\n
\nEnter a reason for the lock, including an estimate\nof when the lock will be released\n\n{{int:Enterlockreason}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Error&action=edit error]
\n[[MediaWiki_talk:Error|Talk]]\n
\nError\n\n{{int:Error}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Errorpagetitle&action=edit errorpagetitle]
\n[[MediaWiki_talk:Errorpagetitle|Talk]]\n
\nError\n\n{{int:Errorpagetitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exbeforeblank&action=edit exbeforeblank]
\n[[MediaWiki_talk:Exbeforeblank|Talk]]\n
\ncontent before blanking was:\n\n{{int:Exbeforeblank}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exblank&action=edit exblank]
\n[[MediaWiki_talk:Exblank|Talk]]\n
\npage was empty\n\n{{int:Exblank}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Excontent&action=edit excontent]
\n[[MediaWiki_talk:Excontent|Talk]]\n
\ncontent was:\n\n{{int:Excontent}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Explainconflict&action=edit explainconflict]
\n[[MediaWiki_talk:Explainconflict|Talk]]\n
\nSomeone else has changed this page since you\nstarted editing it.\nThe upper text area contains the page text as it currently exists.\nYour changes are shown in the lower text area.\nYou will have to merge your changes into the existing text.\n<b>Only</b> the text in the upper text area will be saved when you\npress "Save page".\n<p>\n\n{{int:Explainconflict}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Export&action=edit export]
\n[[MediaWiki_talk:Export|Talk]]\n
\nExport pages\n\n{{int:Export}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exportcuronly&action=edit exportcuronly]
\n[[MediaWiki_talk:Exportcuronly|Talk]]\n
\nInclude only the current revision, not the full history\n\n{{int:Exportcuronly}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Exporttext&action=edit exporttext]
\n[[MediaWiki_talk:Exporttext|Talk]]\n
\nYou can export the text and editing history of a particular\npage or set of pages wrapped in some XML; this can then be imported into another\nwiki running MediaWiki software, transformed, or just kept for your private\namusement.\n\n{{int:Exporttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Extlink_sample&action=edit extlink_sample]
\n[[MediaWiki_talk:Extlink_sample|Talk]]\n
\nhttp://www.example.com link title\n\n{{int:Extlink_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Extlink_tip&action=edit extlink_tip]
\n[[MediaWiki_talk:Extlink_tip|Talk]]\n
\nExternal link (remember http:// prefix)\n\n{{int:Extlink_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Faq&action=edit faq]
\n[[MediaWiki_talk:Faq|Talk]]\n
\nFAQ\n\n{{int:Faq}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Faqpage&action=edit faqpage]
\n[[MediaWiki_talk:Faqpage|Talk]]\n
\nWikipedia:FAQ\n\n{{int:Faqpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Feedlinks&action=edit feedlinks]
\n[[MediaWiki_talk:Feedlinks|Talk]]\n
\nFeed:\n\n{{int:Feedlinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filecopyerror&action=edit filecopyerror]
\n[[MediaWiki_talk:Filecopyerror|Talk]]\n
\nCould not copy file "$1" to "$2".\n\n{{int:Filecopyerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filedeleteerror&action=edit filedeleteerror]
\n[[MediaWiki_talk:Filedeleteerror|Talk]]\n
\nCould not delete file "$1".\n\n{{int:Filedeleteerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filedesc&action=edit filedesc]
\n[[MediaWiki_talk:Filedesc|Talk]]\n
\nSummary\n\n{{int:Filedesc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filename&action=edit filename]
\n[[MediaWiki_talk:Filename|Talk]]\n
\nFilename\n\n{{int:Filename}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filenotfound&action=edit filenotfound]
\n[[MediaWiki_talk:Filenotfound|Talk]]\n
\nCould not find file "$1".\n\n{{int:Filenotfound}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filerenameerror&action=edit filerenameerror]
\n[[MediaWiki_talk:Filerenameerror|Talk]]\n
\nCould not rename file "$1" to "$2".\n\n{{int:Filerenameerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filesource&action=edit filesource]
\n[[MediaWiki_talk:Filesource|Talk]]\n
\nSource\n\n{{int:Filesource}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Filestatus&action=edit filestatus]
\n[[MediaWiki_talk:Filestatus|Talk]]\n
\nCopyright status\n\n{{int:Filestatus}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Fileuploaded&action=edit fileuploaded]
\n[[MediaWiki_talk:Fileuploaded|Talk]]\n
\nFile "$1" uploaded successfully.\nPlease follow this link: $2 to the description page and fill\nin information about the file, such as where it came from, when it was\ncreated and by whom, and anything else you may know about it.\n\n{{int:Fileuploaded}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Formerror&action=edit formerror]
\n[[MediaWiki_talk:Formerror|Talk]]\n
\nError: could not submit form\n\n{{int:Formerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Fromwikipedia&action=edit fromwikipedia]
\n[[MediaWiki_talk:Fromwikipedia|Talk]]\n
\nFrom Wikipedia\n\n{{int:Fromwikipedia}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Getimagelist&action=edit getimagelist]
\n[[MediaWiki_talk:Getimagelist|Talk]]\n
\nfetching image list\n\n{{int:Getimagelist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Go&action=edit go]
\n[[MediaWiki_talk:Go|Talk]]\n
\nGo\n\n{{int:Go}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Googlesearch&action=edit googlesearch]
\n[[MediaWiki_talk:Googlesearch|Talk]]\n
\n\n<!-- SiteSearch Google -->\n<FORM method=GET action="http://www.google.com/search">\n<TABLE bgcolor="#FFFFFF"><tr><td>\n<A HREF="http://www.google.com/">\n<IMG SRC="http://www.google.com/logos/Logo_40wht.gif"\nborder="0" ALT="Google"></A>\n</td>\n<td>\n<INPUT TYPE=text name=q size=31 maxlength=255 value="$1">\n<INPUT type=submit name=btnG VALUE="Google Search">\n<font size=-1>\n<input type=hidden name=domains value="{{SERVER}}"><br /><input type=radio name=sitesearch value=""> WWW <input type=radio name=sitesearch value="{{SERVER}}" checked> {{SERVER}} <br />\n<input type='hidden' name='ie' value='$2'>\n<input type='hidden' name='oe' value='$2'>\n</font>\n</td></tr></TABLE>\n</FORM>\n<!-- SiteSearch Google -->\n\n{{int:Googlesearch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Guesstimezone&action=edit guesstimezone]
\n[[MediaWiki_talk:Guesstimezone|Talk]]\n
\nFill in from browser\n\n{{int:Guesstimezone}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Headline_sample&action=edit headline_sample]
\n[[MediaWiki_talk:Headline_sample|Talk]]\n
\nHeadline text\n\n{{int:Headline_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Headline_tip&action=edit headline_tip]
\n[[MediaWiki_talk:Headline_tip|Talk]]\n
\nLevel 2 headline\n\n{{int:Headline_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Help&action=edit help]
\n[[MediaWiki_talk:Help|Talk]]\n
\nHelp\n\n{{int:Help}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Helppage&action=edit helppage]
\n[[MediaWiki_talk:Helppage|Talk]]\n
\nHelp:Contents\n\n{{int:Helppage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hide&action=edit hide]
\n[[MediaWiki_talk:Hide|Talk]]\n
\nhide\n\n{{int:Hide}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hidetoc&action=edit hidetoc]
\n[[MediaWiki_talk:Hidetoc|Talk]]\n
\nhide\n\n{{int:Hidetoc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hist&action=edit hist]
\n[[MediaWiki_talk:Hist|Talk]]\n
\nhist\n\n{{int:Hist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Histlegend&action=edit histlegend]
\n[[MediaWiki_talk:Histlegend|Talk]]\n
\nDiff selection: mark the radio boxes of the versions to compare and hit enter or the button at the bottom.<br/>\nLegend: (cur) = difference with current version,\n(last) = difference with preceding version, M = minor edit.\n\n{{int:Histlegend}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:History&action=edit history]
\n[[MediaWiki_talk:History|Talk]]\n
\nPage history\n\n{{int:History}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:History_short&action=edit history_short]
\n[[MediaWiki_talk:History_short|Talk]]\n
\nHistory\n\n{{int:History_short}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Historywarning&action=edit historywarning]
\n[[MediaWiki_talk:Historywarning|Talk]]\n
\nWarning: The page you are about to delete has a history: \n\n{{int:Historywarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Hr_tip&action=edit hr_tip]
\n[[MediaWiki_talk:Hr_tip|Talk]]\n
\nHorizontal line (use sparingly)\n\n{{int:Hr_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ignorewarning&action=edit ignorewarning]
\n[[MediaWiki_talk:Ignorewarning|Talk]]\n
\nIgnore warning and save file anyway.\n\n{{int:Ignorewarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ilshowmatch&action=edit ilshowmatch]
\n[[MediaWiki_talk:Ilshowmatch|Talk]]\n
\nShow all images with names matching\n\n{{int:Ilshowmatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ilsubmit&action=edit ilsubmit]
\n[[MediaWiki_talk:Ilsubmit|Talk]]\n
\nSearch\n\n{{int:Ilsubmit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Image_sample&action=edit image_sample]
\n[[MediaWiki_talk:Image_sample|Talk]]\n
\nExample.jpg\n\n{{int:Image_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Image_tip&action=edit image_tip]
\n[[MediaWiki_talk:Image_tip|Talk]]\n
\nEmbedded image\n\n{{int:Image_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelinks&action=edit imagelinks]
\n[[MediaWiki_talk:Imagelinks|Talk]]\n
\nImage links\n\n{{int:Imagelinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelist&action=edit imagelist]
\n[[MediaWiki_talk:Imagelist|Talk]]\n
\nImage list\n\n{{int:Imagelist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagelisttext&action=edit imagelisttext]
\n[[MediaWiki_talk:Imagelisttext|Talk]]\n
\nBelow is a list of $1 images sorted $2.\n\n{{int:Imagelisttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagepage&action=edit imagepage]
\n[[MediaWiki_talk:Imagepage|Talk]]\n
\nView image page\n\n{{int:Imagepage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imagereverted&action=edit imagereverted]
\n[[MediaWiki_talk:Imagereverted|Talk]]\n
\nRevert to earlier version was successful.\n\n{{int:Imagereverted}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imgdelete&action=edit imgdelete]
\n[[MediaWiki_talk:Imgdelete|Talk]]\n
\ndel\n\n{{int:Imgdelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imgdesc&action=edit imgdesc]
\n[[MediaWiki_talk:Imgdesc|Talk]]\n
\ndesc\n\n{{int:Imgdesc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imghistlegend&action=edit imghistlegend]
\n[[MediaWiki_talk:Imghistlegend|Talk]]\n
\nLegend: (cur) = this is the current image, (del) = delete\nthis old version, (rev) = revert to this old version.\n<br /><i>Click on date to see image uploaded on that date</i>.\n\n{{int:Imghistlegend}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imghistory&action=edit imghistory]
\n[[MediaWiki_talk:Imghistory|Talk]]\n
\nImage history\n\n{{int:Imghistory}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Imglegend&action=edit imglegend]
\n[[MediaWiki_talk:Imglegend|Talk]]\n
\nLegend: (desc) = show/edit image description.\n\n{{int:Imglegend}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Import&action=edit import]
\n[[MediaWiki_talk:Import|Talk]]\n
\nImport pages\n\n{{int:Import}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Importfailed&action=edit importfailed]
\n[[MediaWiki_talk:Importfailed|Talk]]\n
\nImport failed: $1\n\n{{int:Importfailed}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Importhistoryconflict&action=edit importhistoryconflict]
\n[[MediaWiki_talk:Importhistoryconflict|Talk]]\n
\nConflicting history revision exists (may have imported this page before)\n\n{{int:Importhistoryconflict}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Importnotext&action=edit importnotext]
\n[[MediaWiki_talk:Importnotext|Talk]]\n
\nEmpty or no text\n\n{{int:Importnotext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Importsuccess&action=edit importsuccess]
\n[[MediaWiki_talk:Importsuccess|Talk]]\n
\nImport succeeded!\n\n{{int:Importsuccess}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Importtext&action=edit importtext]
\n[[MediaWiki_talk:Importtext|Talk]]\n
\nPlease export the file from the source wiki using the Special:Export utility, save it to your disk and upload it here.\n\n{{int:Importtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Infobox&action=edit infobox]
\n[[MediaWiki_talk:Infobox|Talk]]\n
\nClick a button to get an example text\n\n{{int:Infobox}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Infobox_alert&action=edit infobox_alert]
\n[[MediaWiki_talk:Infobox_alert|Talk]]\n
\nPlease enter the text you want to be formatted.\\n It will be shown in the infobox for copy and pasting.\\nExample:\\n$1\\nwill become:\\n$2\n\n{{int:Infobox_alert}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Internalerror&action=edit internalerror]
\n[[MediaWiki_talk:Internalerror|Talk]]\n
\nInternal error\n\n{{int:Internalerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Intl&action=edit intl]
\n[[MediaWiki_talk:Intl|Talk]]\n
\nInterlanguage links\n\n{{int:Intl}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ip_range_invalid&action=edit ip_range_invalid]
\n[[MediaWiki_talk:Ip_range_invalid|Talk]]\n
\nInvalid IP range.\n\n\n{{int:Ip_range_invalid}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipaddress&action=edit ipaddress]
\n[[MediaWiki_talk:Ipaddress|Talk]]\n
\nIP Address/username\n\n{{int:Ipaddress}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipb_expiry_invalid&action=edit ipb_expiry_invalid]
\n[[MediaWiki_talk:Ipb_expiry_invalid|Talk]]\n
\nExpiry time invalid.\n\n{{int:Ipb_expiry_invalid}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbexpiry&action=edit ipbexpiry]
\n[[MediaWiki_talk:Ipbexpiry|Talk]]\n
\nExpiry\n\n{{int:Ipbexpiry}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipblocklist&action=edit ipblocklist]
\n[[MediaWiki_talk:Ipblocklist|Talk]]\n
\nList of blocked IP addresses and usernames\n\n{{int:Ipblocklist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbreason&action=edit ipbreason]
\n[[MediaWiki_talk:Ipbreason|Talk]]\n
\nReason\n\n{{int:Ipbreason}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipbsubmit&action=edit ipbsubmit]
\n[[MediaWiki_talk:Ipbsubmit|Talk]]\n
\nBlock this user\n\n{{int:Ipbsubmit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipusubmit&action=edit ipusubmit]
\n[[MediaWiki_talk:Ipusubmit|Talk]]\n
\nUnblock this address\n\n{{int:Ipusubmit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ipusuccess&action=edit ipusuccess]
\n[[MediaWiki_talk:Ipusuccess|Talk]]\n
\n"$1" unblocked\n\n{{int:Ipusuccess}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Isbn&action=edit isbn]
\n[[MediaWiki_talk:Isbn|Talk]]\n
\nISBN\n\n{{int:Isbn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Isredirect&action=edit isredirect]
\n[[MediaWiki_talk:Isredirect|Talk]]\n
\nredirect page\n\n{{int:Isredirect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Italic_sample&action=edit italic_sample]
\n[[MediaWiki_talk:Italic_sample|Talk]]\n
\nItalic text\n\n{{int:Italic_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Italic_tip&action=edit italic_tip]
\n[[MediaWiki_talk:Italic_tip|Talk]]\n
\nItalic text\n\n{{int:Italic_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Iteminvalidname&action=edit iteminvalidname]
\n[[MediaWiki_talk:Iteminvalidname|Talk]]\n
\nProblem with item '$1', invalid name...\n\n{{int:Iteminvalidname}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Largefile&action=edit largefile]
\n[[MediaWiki_talk:Largefile|Talk]]\n
\nIt is recommended that images not exceed 100k in size.\n\n{{int:Largefile}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Last&action=edit last]
\n[[MediaWiki_talk:Last|Talk]]\n
\nlast\n\n{{int:Last}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lastmodified&action=edit lastmodified]
\n[[MediaWiki_talk:Lastmodified|Talk]]\n
\nThis page was last modified $1.\n\n{{int:Lastmodified}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lastmodifiedby&action=edit lastmodifiedby]
\n[[MediaWiki_talk:Lastmodifiedby|Talk]]\n
\nThis page was last modified $1 by $2.\n\n{{int:Lastmodifiedby}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lineno&action=edit lineno]
\n[[MediaWiki_talk:Lineno|Talk]]\n
\nLine $1:\n\n{{int:Lineno}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Link_sample&action=edit link_sample]
\n[[MediaWiki_talk:Link_sample|Talk]]\n
\nLink title\n\n{{int:Link_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Link_tip&action=edit link_tip]
\n[[MediaWiki_talk:Link_tip|Talk]]\n
\nInternal link\n\n{{int:Link_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linklistsub&action=edit linklistsub]
\n[[MediaWiki_talk:Linklistsub|Talk]]\n
\n(List of links)\n\n{{int:Linklistsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linkshere&action=edit linkshere]
\n[[MediaWiki_talk:Linkshere|Talk]]\n
\nThe following pages link to here:\n\n{{int:Linkshere}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linkstoimage&action=edit linkstoimage]
\n[[MediaWiki_talk:Linkstoimage|Talk]]\n
\nThe following pages link to this image:\n\n{{int:Linkstoimage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Linktrail&action=edit linktrail]
\n[[MediaWiki_talk:Linktrail|Talk]]\n
\n/^([a-z]+)(.*)$/sD\n\n{{int:Linktrail}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Listform&action=edit listform]
\n[[MediaWiki_talk:Listform|Talk]]\n
\nlist\n\n{{int:Listform}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Listusers&action=edit listusers]
\n[[MediaWiki_talk:Listusers|Talk]]\n
\nUser list\n\n{{int:Listusers}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loadhist&action=edit loadhist]
\n[[MediaWiki_talk:Loadhist|Talk]]\n
\nLoading page history\n\n{{int:Loadhist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loadingrev&action=edit loadingrev]
\n[[MediaWiki_talk:Loadingrev|Talk]]\n
\nloading revision for diff\n\n{{int:Loadingrev}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Localtime&action=edit localtime]
\n[[MediaWiki_talk:Localtime|Talk]]\n
\nLocal time display\n\n{{int:Localtime}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockbtn&action=edit lockbtn]
\n[[MediaWiki_talk:Lockbtn|Talk]]\n
\nLock database\n\n{{int:Lockbtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockconfirm&action=edit lockconfirm]
\n[[MediaWiki_talk:Lockconfirm|Talk]]\n
\nYes, I really want to lock the database.\n\n{{int:Lockconfirm}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdb&action=edit lockdb]
\n[[MediaWiki_talk:Lockdb|Talk]]\n
\nLock database\n\n{{int:Lockdb}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbsuccesssub&action=edit lockdbsuccesssub]
\n[[MediaWiki_talk:Lockdbsuccesssub|Talk]]\n
\nDatabase lock succeeded\n\n{{int:Lockdbsuccesssub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbsuccesstext&action=edit lockdbsuccesstext]
\n[[MediaWiki_talk:Lockdbsuccesstext|Talk]]\n
\nThe database has been locked.\n<br />Remember to remove the lock after your maintenance is complete.\n\n{{int:Lockdbsuccesstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lockdbtext&action=edit lockdbtext]
\n[[MediaWiki_talk:Lockdbtext|Talk]]\n
\nLocking the database will suspend the ability of all\nusers to edit pages, change their preferences, edit their watchlists, and\nother things requiring changes in the database.\nPlease confirm that this is what you intend to do, and that you will\nunlock the database when your maintenance is done.\n\n{{int:Lockdbtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Locknoconfirm&action=edit locknoconfirm]
\n[[MediaWiki_talk:Locknoconfirm|Talk]]\n
\nYou did not check the confirmation box.\n\n{{int:Locknoconfirm}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Login&action=edit login]
\n[[MediaWiki_talk:Login|Talk]]\n
\nLog in\n\n{{int:Login}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginend&action=edit loginend]
\n[[MediaWiki_talk:Loginend|Talk]]\n
\n&nbsp;\n\n{{int:Loginend}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginerror&action=edit loginerror]
\n[[MediaWiki_talk:Loginerror|Talk]]\n
\nLogin error\n\n{{int:Loginerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginpagetitle&action=edit loginpagetitle]
\n[[MediaWiki_talk:Loginpagetitle|Talk]]\n
\nUser login\n\n{{int:Loginpagetitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginproblem&action=edit loginproblem]
\n[[MediaWiki_talk:Loginproblem|Talk]]\n
\n<b>There has been a problem with your login.</b><br />Try again!\n\n{{int:Loginproblem}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginprompt&action=edit loginprompt]
\n[[MediaWiki_talk:Loginprompt|Talk]]\n
\nYou must have cookies enabled to log in to Wikipedia.\n\n{{int:Loginprompt}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginreqtext&action=edit loginreqtext]
\n[[MediaWiki_talk:Loginreqtext|Talk]]\n
\nYou must [[special:Userlogin|login]] to view other pages.\n\n{{int:Loginreqtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginreqtitle&action=edit loginreqtitle]
\n[[MediaWiki_talk:Loginreqtitle|Talk]]\n
\nLogin Required\n\n{{int:Loginreqtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginsuccess&action=edit loginsuccess]
\n[[MediaWiki_talk:Loginsuccess|Talk]]\n
\nYou are now logged in to Wikipedia as "$1".\n\n{{int:Loginsuccess}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Loginsuccesstitle&action=edit loginsuccesstitle]
\n[[MediaWiki_talk:Loginsuccesstitle|Talk]]\n
\nLogin successful\n\n{{int:Loginsuccesstitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logout&action=edit logout]
\n[[MediaWiki_talk:Logout|Talk]]\n
\nLog out\n\n{{int:Logout}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logouttext&action=edit logouttext]
\n[[MediaWiki_talk:Logouttext|Talk]]\n
\nYou are now logged out.\nYou can continue to use Wikipedia anonymously, or you can log in\nagain as the same or as a different user. Note that some pages may\ncontinue to be displayed as if you were still logged in, until you clear\nyour browser cache\n\n\n{{int:Logouttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Logouttitle&action=edit logouttitle]
\n[[MediaWiki_talk:Logouttitle|Talk]]\n
\nUser logout\n\n{{int:Logouttitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Lonelypages&action=edit lonelypages]
\n[[MediaWiki_talk:Lonelypages|Talk]]\n
\nOrphaned pages\n\n{{int:Lonelypages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Longpages&action=edit longpages]
\n[[MediaWiki_talk:Longpages|Talk]]\n
\nLong pages\n\n{{int:Longpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Longpagewarning&action=edit longpagewarning]
\n[[MediaWiki_talk:Longpagewarning|Talk]]\n
\nWARNING: This page is $1 kilobytes long; some\nbrowsers may have problems editing pages approaching or longer than 32kb.\nPlease consider breaking the page into smaller sections.\n\n{{int:Longpagewarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailerror&action=edit mailerror]
\n[[MediaWiki_talk:Mailerror|Talk]]\n
\nError sending mail: $1\n\n{{int:Mailerror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailmypassword&action=edit mailmypassword]
\n[[MediaWiki_talk:Mailmypassword|Talk]]\n
\nMail me a new password\n\n{{int:Mailmypassword}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailnologin&action=edit mailnologin]
\n[[MediaWiki_talk:Mailnologin|Talk]]\n
\nNo send address\n\n{{int:Mailnologin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mailnologintext&action=edit mailnologintext]
\n[[MediaWiki_talk:Mailnologintext|Talk]]\n
\nYou must be <a href="{{localurl:Special:Userlogin">logged in</a>\nand have a valid e-mail address in your <a href="/wiki/Special:Preferences">preferences</a>\nto send e-mail to other users.\n\n{{int:Mailnologintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mainpage&action=edit mainpage]
\n[[MediaWiki_talk:Mainpage|Talk]]\n
\nMain Page\n\n{{int:Mainpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mainpagedocfooter&action=edit mainpagedocfooter]
\n[[MediaWiki_talk:Mainpagedocfooter|Talk]]\n
\nPlease see [http://meta.wikipedia.org/wiki/MediaWiki_i18n documentation on customizing the interface]\nand the [http://meta.wikipedia.org/wiki/MediaWiki_User%27s_Guide User's Guide] for usage and configuration help.\n\n{{int:Mainpagedocfooter}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mainpagetext&action=edit mainpagetext]
\n[[MediaWiki_talk:Mainpagetext|Talk]]\n
\nWiki software successfully installed.\n\n{{int:Mainpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintenance&action=edit maintenance]
\n[[MediaWiki_talk:Maintenance|Talk]]\n
\nMaintenance page\n\n{{int:Maintenance}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintenancebacklink&action=edit maintenancebacklink]
\n[[MediaWiki_talk:Maintenancebacklink|Talk]]\n
\nBack to Maintenance Page\n\n{{int:Maintenancebacklink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Maintnancepagetext&action=edit maintnancepagetext]
\n[[MediaWiki_talk:Maintnancepagetext|Talk]]\n
\nThis page includes several handy tools for everyday maintenance. Some of these functions tend to stress the database, so please do not hit reload after every item you fixed ;-)\n\n{{int:Maintnancepagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysop&action=edit makesysop]
\n[[MediaWiki_talk:Makesysop|Talk]]\n
\nMake a user into a sysop\n\n{{int:Makesysop}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopfail&action=edit makesysopfail]
\n[[MediaWiki_talk:Makesysopfail|Talk]]\n
\n<b>User "$1" could not be made into a sysop. (Did you enter the name correctly?)</b>\n\n{{int:Makesysopfail}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopname&action=edit makesysopname]
\n[[MediaWiki_talk:Makesysopname|Talk]]\n
\nName of the user:\n\n{{int:Makesysopname}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopok&action=edit makesysopok]
\n[[MediaWiki_talk:Makesysopok|Talk]]\n
\n<b>User "$1" is now a sysop</b>\n\n{{int:Makesysopok}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysopsubmit&action=edit makesysopsubmit]
\n[[MediaWiki_talk:Makesysopsubmit|Talk]]\n
\nMake this user into a sysop\n\n{{int:Makesysopsubmit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysoptext&action=edit makesysoptext]
\n[[MediaWiki_talk:Makesysoptext|Talk]]\n
\nThis form is used by bureaucrats to turn ordinary users into administrators. \nType the name of the user in the box and press the button to make the user an administrator\n\n{{int:Makesysoptext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Makesysoptitle&action=edit makesysoptitle]
\n[[MediaWiki_talk:Makesysoptitle|Talk]]\n
\nMake a user into a sysop\n\n{{int:Makesysoptitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Matchtotals&action=edit matchtotals]
\n[[MediaWiki_talk:Matchtotals|Talk]]\n
\nThe query "$1" matched $2 page titles\nand the text of $3 pages.\n\n{{int:Matchtotals}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math&action=edit math]
\n[[MediaWiki_talk:Math|Talk]]\n
\nRendering math\n\n{{int:Math}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_bad_output&action=edit math_bad_output]
\n[[MediaWiki_talk:Math_bad_output|Talk]]\n
\nCan't write to or create math output directory\n\n{{int:Math_bad_output}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_bad_tmpdir&action=edit math_bad_tmpdir]
\n[[MediaWiki_talk:Math_bad_tmpdir|Talk]]\n
\nCan't write to or create math temp directory\n\n{{int:Math_bad_tmpdir}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_failure&action=edit math_failure]
\n[[MediaWiki_talk:Math_failure|Talk]]\n
\nFailed to parse\n\n{{int:Math_failure}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_image_error&action=edit math_image_error]
\n[[MediaWiki_talk:Math_image_error|Talk]]\n
\nPNG conversion failed; check for correct installation of latex, dvips, gs, and convert\n\n{{int:Math_image_error}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_lexing_error&action=edit math_lexing_error]
\n[[MediaWiki_talk:Math_lexing_error|Talk]]\n
\nlexing error\n\n{{int:Math_lexing_error}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_notexvc&action=edit math_notexvc]
\n[[MediaWiki_talk:Math_notexvc|Talk]]\n
\nMissing texvc executable; please see math/README to configure.\n\n{{int:Math_notexvc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_sample&action=edit math_sample]
\n[[MediaWiki_talk:Math_sample|Talk]]\n
\nInsert formula here\n\n{{int:Math_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_syntax_error&action=edit math_syntax_error]
\n[[MediaWiki_talk:Math_syntax_error|Talk]]\n
\nsyntax error\n\n{{int:Math_syntax_error}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_tip&action=edit math_tip]
\n[[MediaWiki_talk:Math_tip|Talk]]\n
\nMathematical formula (LaTeX)\n\n{{int:Math_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_unknown_error&action=edit math_unknown_error]
\n[[MediaWiki_talk:Math_unknown_error|Talk]]\n
\nunknown error\n\n{{int:Math_unknown_error}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Math_unknown_function&action=edit math_unknown_function]
\n[[MediaWiki_talk:Math_unknown_function|Talk]]\n
\nunknown function \n\n{{int:Math_unknown_function}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Media_sample&action=edit media_sample]
\n[[MediaWiki_talk:Media_sample|Talk]]\n
\nExample.mp3\n\n{{int:Media_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Media_tip&action=edit media_tip]
\n[[MediaWiki_talk:Media_tip|Talk]]\n
\nMedia file link\n\n{{int:Media_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minlength&action=edit minlength]
\n[[MediaWiki_talk:Minlength|Talk]]\n
\nImage names must be at least three letters.\n\n{{int:Minlength}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minoredit&action=edit minoredit]
\n[[MediaWiki_talk:Minoredit|Talk]]\n
\nThis is a minor edit\n\n{{int:Minoredit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Minoreditletter&action=edit minoreditletter]
\n[[MediaWiki_talk:Minoreditletter|Talk]]\n
\nM\n\n{{int:Minoreditletter}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelings&action=edit mispeelings]
\n[[MediaWiki_talk:Mispeelings|Talk]]\n
\nPages with misspellings\n\n{{int:Mispeelings}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelingspage&action=edit mispeelingspage]
\n[[MediaWiki_talk:Mispeelingspage|Talk]]\n
\nList of common misspellings\n\n{{int:Mispeelingspage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mispeelingstext&action=edit mispeelingstext]
\n[[MediaWiki_talk:Mispeelingstext|Talk]]\n
\nThe following pages contain a common misspelling, which are listed on $1. The correct spelling might be given (like this).\n\n{{int:Mispeelingstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missingarticle&action=edit missingarticle]
\n[[MediaWiki_talk:Missingarticle|Talk]]\n
\nThe database did not find the text of a page\nthat it should have found, named "$1".\n\n<p>This is usually caused by following an outdated diff or history link to a\npage that has been deleted.\n\n<p>If this is not the case, you may have found a bug in the software.\nPlease report this to an administrator, making note of the URL.\n\n{{int:Missingarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missingimage&action=edit missingimage]
\n[[MediaWiki_talk:Missingimage|Talk]]\n
\n<b>Missing image</b><br /><i>$1</i>\n\n\n{{int:Missingimage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinks&action=edit missinglanguagelinks]
\n[[MediaWiki_talk:Missinglanguagelinks|Talk]]\n
\nMissing Language Links\n\n{{int:Missinglanguagelinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinksbutton&action=edit missinglanguagelinksbutton]
\n[[MediaWiki_talk:Missinglanguagelinksbutton|Talk]]\n
\nFind missing language links for\n\n{{int:Missinglanguagelinksbutton}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Missinglanguagelinkstext&action=edit missinglanguagelinkstext]
\n[[MediaWiki_talk:Missinglanguagelinkstext|Talk]]\n
\nThese pages do <i>not</i> link to their counterpart in $1. Redirects and subpages are <i>not</i> shown.\n\n{{int:Missinglanguagelinkstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Moredotdotdot&action=edit moredotdotdot]
\n[[MediaWiki_talk:Moredotdotdot|Talk]]\n
\nMore...\n\n{{int:Moredotdotdot}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Move&action=edit move]
\n[[MediaWiki_talk:Move|Talk]]\n
\nMove\n\n{{int:Move}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movearticle&action=edit movearticle]
\n[[MediaWiki_talk:Movearticle|Talk]]\n
\nMove page\n\n{{int:Movearticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movedto&action=edit movedto]
\n[[MediaWiki_talk:Movedto|Talk]]\n
\nmoved to\n\n{{int:Movedto}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movenologin&action=edit movenologin]
\n[[MediaWiki_talk:Movenologin|Talk]]\n
\nNot logged in\n\n{{int:Movenologin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movenologintext&action=edit movenologintext]
\n[[MediaWiki_talk:Movenologintext|Talk]]\n
\nYou must be a registered user and <a href="/wiki/Special:Userlogin">logged in</a>\nto move a page.\n\n{{int:Movenologintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepage&action=edit movepage]
\n[[MediaWiki_talk:Movepage|Talk]]\n
\nMove page\n\n{{int:Movepage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagebtn&action=edit movepagebtn]
\n[[MediaWiki_talk:Movepagebtn|Talk]]\n
\nMove page\n\n{{int:Movepagebtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagetalktext&action=edit movepagetalktext]
\n[[MediaWiki_talk:Movepagetalktext|Talk]]\n
\nThe associated talk page, if any, will be automatically moved along with it '''unless:'''\n*You are moving the page across namespaces,\n*A non-empty talk page already exists under the new name, or\n*You uncheck the box below.\n\nIn those cases, you will have to move or merge the page manually if desired.\n\n{{int:Movepagetalktext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movepagetext&action=edit movepagetext]
\n[[MediaWiki_talk:Movepagetext|Talk]]\n
\nUsing the form below will rename a page, moving all\nof its history to the new name.\nThe old title will become a redirect page to the new title.\nLinks to the old page title will not be changed; be sure to\n[[Special:Maintenance|check]] for double or broken redirects.\nYou are responsible for making sure that links continue to\npoint where they are supposed to go.\n\nNote that the page will '''not''' be moved if there is already\na page at the new title, unless it is empty or a redirect and has no\npast edit history. This means that you can rename a page back to where\nit was just renamed from if you make a mistake, and you cannot overwrite\nan existing page.\n\n<b>WARNING!</b>\nThis can be a drastic and unexpected change for a popular page;\nplease be sure you understand the consequences of this before\nproceeding.\n\n{{int:Movepagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movetalk&action=edit movetalk]
\n[[MediaWiki_talk:Movetalk|Talk]]\n
\nMove "talk" page as well, if applicable.\n\n{{int:Movetalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Movethispage&action=edit movethispage]
\n[[MediaWiki_talk:Movethispage|Talk]]\n
\nMove this page\n\n{{int:Movethispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mycontris&action=edit mycontris]
\n[[MediaWiki_talk:Mycontris|Talk]]\n
\nMy contributions\n\n{{int:Mycontris}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mypage&action=edit mypage]
\n[[MediaWiki_talk:Mypage|Talk]]\n
\nMy page\n\n{{int:Mypage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Mytalk&action=edit mytalk]
\n[[MediaWiki_talk:Mytalk|Talk]]\n
\nMy talk\n\n{{int:Mytalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Navigation&action=edit navigation]
\n[[MediaWiki_talk:Navigation|Talk]]\n
\nNavigation\n\n{{int:Navigation}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nbytes&action=edit nbytes]
\n[[MediaWiki_talk:Nbytes|Talk]]\n
\n$1 bytes\n\n{{int:Nbytes}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nchanges&action=edit nchanges]
\n[[MediaWiki_talk:Nchanges|Talk]]\n
\n$1 changes\n\n{{int:Nchanges}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newarticle&action=edit newarticle]
\n[[MediaWiki_talk:Newarticle|Talk]]\n
\n(New)\n\n{{int:Newarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newarticletext&action=edit newarticletext]
\n[[MediaWiki_talk:Newarticletext|Talk]]\n
\nYou've followed a link to a page that doesn't exist yet.\nTo create the page, start typing in the box below \n(see the [[Wikipedia:Help|help page]] for more info).\nIf you are here by mistake, just click your browser's '''back''' button.\n\n{{int:Newarticletext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newmessages&action=edit newmessages]
\n[[MediaWiki_talk:Newmessages|Talk]]\n
\nYou have $1.\n\n{{int:Newmessages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newmessageslink&action=edit newmessageslink]
\n[[MediaWiki_talk:Newmessageslink|Talk]]\n
\nnew messages\n\n{{int:Newmessageslink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpage&action=edit newpage]
\n[[MediaWiki_talk:Newpage|Talk]]\n
\nNew page\n\n{{int:Newpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpageletter&action=edit newpageletter]
\n[[MediaWiki_talk:Newpageletter|Talk]]\n
\nN\n\n{{int:Newpageletter}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpages&action=edit newpages]
\n[[MediaWiki_talk:Newpages|Talk]]\n
\nNew pages\n\n{{int:Newpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newpassword&action=edit newpassword]
\n[[MediaWiki_talk:Newpassword|Talk]]\n
\nNew password\n\n{{int:Newpassword}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newtitle&action=edit newtitle]
\n[[MediaWiki_talk:Newtitle|Talk]]\n
\nTo new title\n\n{{int:Newtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Newusersonly&action=edit newusersonly]
\n[[MediaWiki_talk:Newusersonly|Talk]]\n
\n (new users only)\n\n{{int:Newusersonly}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Next&action=edit next]
\n[[MediaWiki_talk:Next|Talk]]\n
\nnext\n\n{{int:Next}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nextn&action=edit nextn]
\n[[MediaWiki_talk:Nextn|Talk]]\n
\nnext $1\n\n{{int:Nextn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nlinks&action=edit nlinks]
\n[[MediaWiki_talk:Nlinks|Talk]]\n
\n$1 links\n\n{{int:Nlinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noaffirmation&action=edit noaffirmation]
\n[[MediaWiki_talk:Noaffirmation|Talk]]\n
\nYou must affirm that your upload does not violate\nany copyrights.\n\n{{int:Noaffirmation}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noarticletext&action=edit noarticletext]
\n[[MediaWiki_talk:Noarticletext|Talk]]\n
\n(There is currently no text in this page)\n\n{{int:Noarticletext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noblockreason&action=edit noblockreason]
\n[[MediaWiki_talk:Noblockreason|Talk]]\n
\nYou must supply a reason for the block.\n\n{{int:Noblockreason}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noconnect&action=edit noconnect]
\n[[MediaWiki_talk:Noconnect|Talk]]\n
\nSorry! The wiki is experiencing some technical difficulties, and cannot contact the database server.\n\n{{int:Noconnect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocontribs&action=edit nocontribs]
\n[[MediaWiki_talk:Nocontribs|Talk]]\n
\nNo changes were found matching these criteria.\n\n{{int:Nocontribs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocookieslogin&action=edit nocookieslogin]
\n[[MediaWiki_talk:Nocookieslogin|Talk]]\n
\nWikipedia uses cookies to log in users. You have cookies disabled. Please enable them and try again.\n\n{{int:Nocookieslogin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocookiesnew&action=edit nocookiesnew]
\n[[MediaWiki_talk:Nocookiesnew|Talk]]\n
\nThe user account was created, but you are not logged in. Wikipedia uses cookies to log in users. You have cookies disabled. Please enable them, then log in with your new username and password.\n\n{{int:Nocookiesnew}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nocreativecommons&action=edit nocreativecommons]
\n[[MediaWiki_talk:Nocreativecommons|Talk]]\n
\nCreative Commons RDF metadata disabled for this server.\n\n{{int:Nocreativecommons}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nodb&action=edit nodb]
\n[[MediaWiki_talk:Nodb|Talk]]\n
\nCould not select database $1\n\n{{int:Nodb}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nodublincore&action=edit nodublincore]
\n[[MediaWiki_talk:Nodublincore|Talk]]\n
\nDublin Core RDF metadata disabled for this server.\n\n{{int:Nodublincore}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemail&action=edit noemail]
\n[[MediaWiki_talk:Noemail|Talk]]\n
\nThere is no e-mail address recorded for user "$1".\n\n{{int:Noemail}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemailtext&action=edit noemailtext]
\n[[MediaWiki_talk:Noemailtext|Talk]]\n
\nThis user has not specified a valid e-mail address,\nor has chosen not to receive e-mail from other users.\n\n{{int:Noemailtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noemailtitle&action=edit noemailtitle]
\n[[MediaWiki_talk:Noemailtitle|Talk]]\n
\nNo e-mail address\n\n{{int:Noemailtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nogomatch&action=edit nogomatch]
\n[[MediaWiki_talk:Nogomatch|Talk]]\n
\nNo page with this exact title exists, trying full text search.\n\n{{int:Nogomatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nohistory&action=edit nohistory]
\n[[MediaWiki_talk:Nohistory|Talk]]\n
\nThere is no edit history for this page.\n\n{{int:Nohistory}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nolinkshere&action=edit nolinkshere]
\n[[MediaWiki_talk:Nolinkshere|Talk]]\n
\nNo pages link to here.\n\n{{int:Nolinkshere}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nolinkstoimage&action=edit nolinkstoimage]
\n[[MediaWiki_talk:Nolinkstoimage|Talk]]\n
\nThere are no pages that link to this image.\n\n{{int:Nolinkstoimage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Noname&action=edit noname]
\n[[MediaWiki_talk:Noname|Talk]]\n
\nYou have not specified a valid user name.\n\n{{int:Noname}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nonefound&action=edit nonefound]
\n[[MediaWiki_talk:Nonefound|Talk]]\n
\n<strong>Note</strong>: unsuccessful searches are\noften caused by searching for common words like "have" and "from",\nwhich are not indexed, or by specifying more than one search term (only pages\ncontaining all of the search terms will appear in the result).\n\n{{int:Nonefound}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nospecialpagetext&action=edit nospecialpagetext]
\n[[MediaWiki_talk:Nospecialpagetext|Talk]]\n
\nYou have requested a special page that is not\nrecognized by the wiki.\n\n{{int:Nospecialpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchaction&action=edit nosuchaction]
\n[[MediaWiki_talk:Nosuchaction|Talk]]\n
\nNo such action\n\n{{int:Nosuchaction}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchactiontext&action=edit nosuchactiontext]
\n[[MediaWiki_talk:Nosuchactiontext|Talk]]\n
\nThe action specified by the URL is not\nrecognized by the wiki\n\n{{int:Nosuchactiontext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchspecialpage&action=edit nosuchspecialpage]
\n[[MediaWiki_talk:Nosuchspecialpage|Talk]]\n
\nNo such special page\n\n{{int:Nosuchspecialpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nosuchuser&action=edit nosuchuser]
\n[[MediaWiki_talk:Nosuchuser|Talk]]\n
\nThere is no user by the name "$1".\nCheck your spelling, or use the form below to create a new user account.\n\n{{int:Nosuchuser}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notacceptable&action=edit notacceptable]
\n[[MediaWiki_talk:Notacceptable|Talk]]\n
\nThe wiki server can't provide data in a format your client can read.\n\n{{int:Notacceptable}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notanarticle&action=edit notanarticle]
\n[[MediaWiki_talk:Notanarticle|Talk]]\n
\nNot a content page\n\n{{int:Notanarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notargettext&action=edit notargettext]
\n[[MediaWiki_talk:Notargettext|Talk]]\n
\nYou have not specified a target page or user\nto perform this function on.\n\n{{int:Notargettext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notargettitle&action=edit notargettitle]
\n[[MediaWiki_talk:Notargettitle|Talk]]\n
\nNo target\n\n{{int:Notargettitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Note&action=edit note]
\n[[MediaWiki_talk:Note|Talk]]\n
\n<strong>Note:</strong> \n\n{{int:Note}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notextmatches&action=edit notextmatches]
\n[[MediaWiki_talk:Notextmatches|Talk]]\n
\nNo page text matches\n\n{{int:Notextmatches}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notitlematches&action=edit notitlematches]
\n[[MediaWiki_talk:Notitlematches|Talk]]\n
\nNo page title matches\n\n{{int:Notitlematches}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Notloggedin&action=edit notloggedin]
\n[[MediaWiki_talk:Notloggedin|Talk]]\n
\nNot logged in\n\n{{int:Notloggedin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowatchlist&action=edit nowatchlist]
\n[[MediaWiki_talk:Nowatchlist|Talk]]\n
\nYou have no items on your watchlist.\n\n{{int:Nowatchlist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowiki_sample&action=edit nowiki_sample]
\n[[MediaWiki_talk:Nowiki_sample|Talk]]\n
\nInsert non-formatted text here\n\n{{int:Nowiki_sample}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nowiki_tip&action=edit nowiki_tip]
\n[[MediaWiki_talk:Nowiki_tip|Talk]]\n
\nIgnore wiki formatting\n\n{{int:Nowiki_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-category&action=edit nstab-category]
\n[[MediaWiki_talk:Nstab-category|Talk]]\n
\nCategory\n\n{{int:Nstab-category}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-help&action=edit nstab-help]
\n[[MediaWiki_talk:Nstab-help|Talk]]\n
\nHelp\n\n{{int:Nstab-help}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-image&action=edit nstab-image]
\n[[MediaWiki_talk:Nstab-image|Talk]]\n
\nImage\n\n{{int:Nstab-image}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-main&action=edit nstab-main]
\n[[MediaWiki_talk:Nstab-main|Talk]]\n
\nArticle\n\n{{int:Nstab-main}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-media&action=edit nstab-media]
\n[[MediaWiki_talk:Nstab-media|Talk]]\n
\nMedia\n\n{{int:Nstab-media}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-mediawiki&action=edit nstab-mediawiki]
\n[[MediaWiki_talk:Nstab-mediawiki|Talk]]\n
\nMessage\n\n{{int:Nstab-mediawiki}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-special&action=edit nstab-special]
\n[[MediaWiki_talk:Nstab-special|Talk]]\n
\nSpecial\n\n{{int:Nstab-special}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-template&action=edit nstab-template]
\n[[MediaWiki_talk:Nstab-template|Talk]]\n
\nTemplate\n\n{{int:Nstab-template}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-user&action=edit nstab-user]
\n[[MediaWiki_talk:Nstab-user|Talk]]\n
\nUser page\n\n{{int:Nstab-user}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nstab-wp&action=edit nstab-wp]
\n[[MediaWiki_talk:Nstab-wp|Talk]]\n
\nAbout\n\n{{int:Nstab-wp}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Nviews&action=edit nviews]
\n[[MediaWiki_talk:Nviews|Talk]]\n
\n$1 views\n\n{{int:Nviews}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ok&action=edit ok]
\n[[MediaWiki_talk:Ok|Talk]]\n
\nOK\n\n{{int:Ok}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Oldpassword&action=edit oldpassword]
\n[[MediaWiki_talk:Oldpassword|Talk]]\n
\nOld password\n\n{{int:Oldpassword}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Orig&action=edit orig]
\n[[MediaWiki_talk:Orig|Talk]]\n
\norig\n\n{{int:Orig}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Orphans&action=edit orphans]
\n[[MediaWiki_talk:Orphans|Talk]]\n
\nOrphaned pages\n\n{{int:Orphans}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Othercontribs&action=edit othercontribs]
\n[[MediaWiki_talk:Othercontribs|Talk]]\n
\nBased on work by $1.\n\n{{int:Othercontribs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Otherlanguages&action=edit otherlanguages]
\n[[MediaWiki_talk:Otherlanguages|Talk]]\n
\nOther languages\n\n{{int:Otherlanguages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Pagemovedsub&action=edit pagemovedsub]
\n[[MediaWiki_talk:Pagemovedsub|Talk]]\n
\nMove succeeded\n\n{{int:Pagemovedsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Pagemovedtext&action=edit pagemovedtext]
\n[[MediaWiki_talk:Pagemovedtext|Talk]]\n
\nPage "[[$1]]" moved to "[[$2]]".\n\n{{int:Pagemovedtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Pagetitle&action=edit pagetitle]
\n[[MediaWiki_talk:Pagetitle|Talk]]\n
\n$1 - Wikipedia\n\n{{int:Pagetitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordremindertext&action=edit passwordremindertext]
\n[[MediaWiki_talk:Passwordremindertext|Talk]]\n
\nSomeone (probably you, from IP address $1)\nrequested that we send you a new Wikipedia login password.\nThe password for user "$2" is now "$3".\nYou should log in and change your password now.\n\n{{int:Passwordremindertext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordremindertitle&action=edit passwordremindertitle]
\n[[MediaWiki_talk:Passwordremindertitle|Talk]]\n
\nPassword reminder from Wikipedia\n\n{{int:Passwordremindertitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Passwordsent&action=edit passwordsent]
\n[[MediaWiki_talk:Passwordsent|Talk]]\n
\nA new password has been sent to the e-mail address\nregistered for "$1".\nPlease log in again after you receive it.\n\n{{int:Passwordsent}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Perfcached&action=edit perfcached]
\n[[MediaWiki_talk:Perfcached|Talk]]\n
\nThe following data is cached and may not be completely up to date:\n\n{{int:Perfcached}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Perfdisabled&action=edit perfdisabled]
\n[[MediaWiki_talk:Perfdisabled|Talk]]\n
\nSorry! This feature has been temporarily disabled\nbecause it slows the database down to the point that no one can use\nthe wiki.\n\n{{int:Perfdisabled}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Perfdisabledsub&action=edit perfdisabledsub]
\n[[MediaWiki_talk:Perfdisabledsub|Talk]]\n
\nHere's a saved copy from $1:\n\n{{int:Perfdisabledsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Personaltools&action=edit personaltools]
\n[[MediaWiki_talk:Personaltools|Talk]]\n
\nPersonal tools\n\n{{int:Personaltools}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Popularpages&action=edit popularpages]
\n[[MediaWiki_talk:Popularpages|Talk]]\n
\nPopular pages\n\n{{int:Popularpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Portal&action=edit portal]
\n[[MediaWiki_talk:Portal|Talk]]\n
\nCommunity portal\n\n{{int:Portal}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Portal-url&action=edit portal-url]
\n[[MediaWiki_talk:Portal-url|Talk]]\n
\nWikipedia:Community Portal\n\n{{int:Portal-url}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Postcomment&action=edit postcomment]
\n[[MediaWiki_talk:Postcomment|Talk]]\n
\nPost a comment\n\n{{int:Postcomment}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Poweredby&action=edit poweredby]
\n[[MediaWiki_talk:Poweredby|Talk]]\n
\nWikipedia is powered by [http://www.mediawiki.org/ MediaWiki], an open source wiki engine.\n\n{{int:Poweredby}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Powersearch&action=edit powersearch]
\n[[MediaWiki_talk:Powersearch|Talk]]\n
\nSearch\n\n{{int:Powersearch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Powersearchtext&action=edit powersearchtext]
\n[[MediaWiki_talk:Powersearchtext|Talk]]\n
\n\nSearch in namespaces :<br />\n$1<br />\n$2 List redirects &nbsp; Search for $3 $9\n\n{{int:Powersearchtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Preferences&action=edit preferences]
\n[[MediaWiki_talk:Preferences|Talk]]\n
\nPreferences\n\n{{int:Preferences}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefs-help-userdata&action=edit prefs-help-userdata]
\n[[MediaWiki_talk:Prefs-help-userdata|Talk]]\n
\n* <strong>Real name</strong> (optional): if you choose to provide it this will be used for giving you attribution for your work.<br/>\n* <strong>Email</strong> (optional): Enables people to contact you through the website without you having to reveal your \nemail address to them, and it can be used to send you a new password if you forget it.\n\n{{int:Prefs-help-userdata}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefs-misc&action=edit prefs-misc]
\n[[MediaWiki_talk:Prefs-misc|Talk]]\n
\nMisc settings\n\n{{int:Prefs-misc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefs-personal&action=edit prefs-personal]
\n[[MediaWiki_talk:Prefs-personal|Talk]]\n
\nUser data\n\n{{int:Prefs-personal}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefs-rc&action=edit prefs-rc]
\n[[MediaWiki_talk:Prefs-rc|Talk]]\n
\nRecent changes and stub display\n\n{{int:Prefs-rc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefslogintext&action=edit prefslogintext]
\n[[MediaWiki_talk:Prefslogintext|Talk]]\n
\nYou are logged in as "$1".\nYour internal ID number is $2.\n\nSee [[Wikipedia:User preferences help]] for help deciphering the options.\n\n{{int:Prefslogintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsnologin&action=edit prefsnologin]
\n[[MediaWiki_talk:Prefsnologin|Talk]]\n
\nNot logged in\n\n{{int:Prefsnologin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsnologintext&action=edit prefsnologintext]
\n[[MediaWiki_talk:Prefsnologintext|Talk]]\n
\nYou must be <a href="/wiki/Special:Userlogin">logged in</a>\nto set user preferences.\n\n{{int:Prefsnologintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prefsreset&action=edit prefsreset]
\n[[MediaWiki_talk:Prefsreset|Talk]]\n
\nPreferences have been reset from storage.\n\n{{int:Prefsreset}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Preview&action=edit preview]
\n[[MediaWiki_talk:Preview|Talk]]\n
\nPreview\n\n{{int:Preview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Previewconflict&action=edit previewconflict]
\n[[MediaWiki_talk:Previewconflict|Talk]]\n
\nThis preview reflects the text in the upper\ntext editing area as it will appear if you choose to save.\n\n{{int:Previewconflict}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Previewnote&action=edit previewnote]
\n[[MediaWiki_talk:Previewnote|Talk]]\n
\nRemember that this is only a preview, and has not yet been saved!\n\n{{int:Previewnote}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Prevn&action=edit prevn]
\n[[MediaWiki_talk:Prevn|Talk]]\n
\nprevious $1\n\n{{int:Prevn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Printableversion&action=edit printableversion]
\n[[MediaWiki_talk:Printableversion|Talk]]\n
\nPrintable version\n\n{{int:Printableversion}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Printsubtitle&action=edit printsubtitle]
\n[[MediaWiki_talk:Printsubtitle|Talk]]\n
\n(From http://su.wikipedia.org)\n\n{{int:Printsubtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protect&action=edit protect]
\n[[MediaWiki_talk:Protect|Talk]]\n
\nProtect\n\n{{int:Protect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectcomment&action=edit protectcomment]
\n[[MediaWiki_talk:Protectcomment|Talk]]\n
\nReason for protecting\n\n{{int:Protectcomment}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedarticle&action=edit protectedarticle]
\n[[MediaWiki_talk:Protectedarticle|Talk]]\n
\nprotected [[$1]]\n\n{{int:Protectedarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedpage&action=edit protectedpage]
\n[[MediaWiki_talk:Protectedpage|Talk]]\n
\nProtected page\n\n{{int:Protectedpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedpagewarning&action=edit protectedpagewarning]
\n[[MediaWiki_talk:Protectedpagewarning|Talk]]\n
\nWARNING: This page has been locked so that only\nusers with sysop privileges can edit it. Be sure you are following the\n<a href='/w/wiki.phtml/Wikipedia:Protected_page_guidelines'>protected page\nguidelines</a>.\n\n{{int:Protectedpagewarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectedtext&action=edit protectedtext]
\n[[MediaWiki_talk:Protectedtext|Talk]]\n
\nThis page has been locked to prevent editing; there are\na number of reasons why this may be so, please see\n[[Wikipedia:Protected page]].\n\nYou can view and copy the source of this page:\n\n{{int:Protectedtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectlogpage&action=edit protectlogpage]
\n[[MediaWiki_talk:Protectlogpage|Talk]]\n
\nProtection_log\n\n{{int:Protectlogpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectlogtext&action=edit protectlogtext]
\n[[MediaWiki_talk:Protectlogtext|Talk]]\n
\nBelow is a list of page locks/unlocks.\nSee [[Wikipedia:Protected page]] for more information.\n\n{{int:Protectlogtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectpage&action=edit protectpage]
\n[[MediaWiki_talk:Protectpage|Talk]]\n
\nProtect page\n\n{{int:Protectpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectreason&action=edit protectreason]
\n[[MediaWiki_talk:Protectreason|Talk]]\n
\n(give a reason)\n\n{{int:Protectreason}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectsub&action=edit protectsub]
\n[[MediaWiki_talk:Protectsub|Talk]]\n
\n(Protecting "$1")\n\n{{int:Protectsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Protectthispage&action=edit protectthispage]
\n[[MediaWiki_talk:Protectthispage|Talk]]\n
\nProtect this page\n\n{{int:Protectthispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Proxyblocker&action=edit proxyblocker]
\n[[MediaWiki_talk:Proxyblocker|Talk]]\n
\nProxy blocker\n\n{{int:Proxyblocker}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Proxyblockreason&action=edit proxyblockreason]
\n[[MediaWiki_talk:Proxyblockreason|Talk]]\n
\nYour IP address has been blocked because it is an open proxy. Please contact your Internet service provider or tech support and inform them of this serious security problem.\n\n{{int:Proxyblockreason}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Proxyblocksuccess&action=edit proxyblocksuccess]
\n[[MediaWiki_talk:Proxyblocksuccess|Talk]]\n
\nDone.\n\n\n{{int:Proxyblocksuccess}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbbrowse&action=edit qbbrowse]
\n[[MediaWiki_talk:Qbbrowse|Talk]]\n
\nBrowse\n\n{{int:Qbbrowse}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbedit&action=edit qbedit]
\n[[MediaWiki_talk:Qbedit|Talk]]\n
\nEdit\n\n{{int:Qbedit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbfind&action=edit qbfind]
\n[[MediaWiki_talk:Qbfind|Talk]]\n
\nFind\n\n{{int:Qbfind}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbmyoptions&action=edit qbmyoptions]
\n[[MediaWiki_talk:Qbmyoptions|Talk]]\n
\nMy pages\n\n{{int:Qbmyoptions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbpageinfo&action=edit qbpageinfo]
\n[[MediaWiki_talk:Qbpageinfo|Talk]]\n
\nContext\n\n{{int:Qbpageinfo}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbpageoptions&action=edit qbpageoptions]
\n[[MediaWiki_talk:Qbpageoptions|Talk]]\n
\nThis page\n\n{{int:Qbpageoptions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbsettings&action=edit qbsettings]
\n[[MediaWiki_talk:Qbsettings|Talk]]\n
\nQuickbar settings\n\n{{int:Qbsettings}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Qbspecialpages&action=edit qbspecialpages]
\n[[MediaWiki_talk:Qbspecialpages|Talk]]\n
\nSpecial pages\n\n{{int:Qbspecialpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Querybtn&action=edit querybtn]
\n[[MediaWiki_talk:Querybtn|Talk]]\n
\nSubmit query\n\n{{int:Querybtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Querysuccessful&action=edit querysuccessful]
\n[[MediaWiki_talk:Querysuccessful|Talk]]\n
\nQuery successful\n\n{{int:Querysuccessful}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Randompage&action=edit randompage]
\n[[MediaWiki_talk:Randompage|Talk]]\n
\nRandom page\n\n{{int:Randompage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Range_block_disabled&action=edit range_block_disabled]
\n[[MediaWiki_talk:Range_block_disabled|Talk]]\n
\nThe sysop ability to create range blocks is disabled.\n\n{{int:Range_block_disabled}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rchide&action=edit rchide]
\n[[MediaWiki_talk:Rchide|Talk]]\n
\nin $4 form; $1 minor edits; $2 secondary namespaces; $3 multiple edits.\n\n{{int:Rchide}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclinks&action=edit rclinks]
\n[[MediaWiki_talk:Rclinks|Talk]]\n
\nShow last $1 changes in last $2 days<br />$3\n\n{{int:Rclinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclistfrom&action=edit rclistfrom]
\n[[MediaWiki_talk:Rclistfrom|Talk]]\n
\nShow new changes starting from $1\n\n{{int:Rclistfrom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcliu&action=edit rcliu]
\n[[MediaWiki_talk:Rcliu|Talk]]\n
\n; $1 edits from logged in users\n\n{{int:Rcliu}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcloaderr&action=edit rcloaderr]
\n[[MediaWiki_talk:Rcloaderr|Talk]]\n
\nLoading recent changes\n\n{{int:Rcloaderr}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rclsub&action=edit rclsub]
\n[[MediaWiki_talk:Rclsub|Talk]]\n
\n(to pages linked from "$1")\n\n{{int:Rclsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcnote&action=edit rcnote]
\n[[MediaWiki_talk:Rcnote|Talk]]\n
\nBelow are the last <strong>$1</strong> changes in last <strong>$2</strong> days.\n\n{{int:Rcnote}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rcnotefrom&action=edit rcnotefrom]
\n[[MediaWiki_talk:Rcnotefrom|Talk]]\n
\nBelow are the changes since <b>$2</b> (up to <b>$1</b> shown).\n\n{{int:Rcnotefrom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonly&action=edit readonly]
\n[[MediaWiki_talk:Readonly|Talk]]\n
\nDatabase locked\n\n{{int:Readonly}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonlytext&action=edit readonlytext]
\n[[MediaWiki_talk:Readonlytext|Talk]]\n
\nThe database is currently locked to new\nentries and other modifications, probably for routine database maintenance,\nafter which it will be back to normal.\nThe administrator who locked it offered this explanation:\n<p>$1\n\n{{int:Readonlytext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Readonlywarning&action=edit readonlywarning]
\n[[MediaWiki_talk:Readonlywarning|Talk]]\n
\nWARNING: The database has been locked for maintenance,\nso you will not be able to save your edits right now. You may wish to cut-n-paste\nthe text into a text file and save it for later.\n\n{{int:Readonlywarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchanges&action=edit recentchanges]
\n[[MediaWiki_talk:Recentchanges|Talk]]\n
\nRecent changes\n\n{{int:Recentchanges}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangescount&action=edit recentchangescount]
\n[[MediaWiki_talk:Recentchangescount|Talk]]\n
\nNumber of titles in recent changes\n\n{{int:Recentchangescount}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangeslinked&action=edit recentchangeslinked]
\n[[MediaWiki_talk:Recentchangeslinked|Talk]]\n
\nRelated changes\n\n{{int:Recentchangeslinked}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Recentchangestext&action=edit recentchangestext]
\n[[MediaWiki_talk:Recentchangestext|Talk]]\n
\nTrack the most recent changes to the wiki on this page.\n\n{{int:Recentchangestext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Redirectedfrom&action=edit redirectedfrom]
\n[[MediaWiki_talk:Redirectedfrom|Talk]]\n
\n(Redirected from $1)\n\n{{int:Redirectedfrom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Remembermypassword&action=edit remembermypassword]
\n[[MediaWiki_talk:Remembermypassword|Talk]]\n
\nRemember my password across sessions.\n\n{{int:Remembermypassword}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removechecked&action=edit removechecked]
\n[[MediaWiki_talk:Removechecked|Talk]]\n
\nRemove checked items from watchlist\n\n{{int:Removechecked}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removedwatch&action=edit removedwatch]
\n[[MediaWiki_talk:Removedwatch|Talk]]\n
\nRemoved from watchlist\n\n{{int:Removedwatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removedwatchtext&action=edit removedwatchtext]
\n[[MediaWiki_talk:Removedwatchtext|Talk]]\n
\nThe page "$1" has been removed from your watchlist.\n\n{{int:Removedwatchtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Removingchecked&action=edit removingchecked]
\n[[MediaWiki_talk:Removingchecked|Talk]]\n
\nRemoving requested items from watchlist...\n\n{{int:Removingchecked}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Resetprefs&action=edit resetprefs]
\n[[MediaWiki_talk:Resetprefs|Talk]]\n
\nReset preferences\n\n{{int:Resetprefs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Restorelink&action=edit restorelink]
\n[[MediaWiki_talk:Restorelink|Talk]]\n
\n$1 deleted edits\n\n{{int:Restorelink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Resultsperpage&action=edit resultsperpage]
\n[[MediaWiki_talk:Resultsperpage|Talk]]\n
\nHits to show per page\n\n{{int:Resultsperpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Retrievedfrom&action=edit retrievedfrom]
\n[[MediaWiki_talk:Retrievedfrom|Talk]]\n
\nRetrieved from "$1"\n\n{{int:Retrievedfrom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Returnto&action=edit returnto]
\n[[MediaWiki_talk:Returnto|Talk]]\n
\nReturn to $1.\n\n{{int:Returnto}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Retypenew&action=edit retypenew]
\n[[MediaWiki_talk:Retypenew|Talk]]\n
\nRetype new password\n\n{{int:Retypenew}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reupload&action=edit reupload]
\n[[MediaWiki_talk:Reupload|Talk]]\n
\nRe-upload\n\n{{int:Reupload}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reuploaddesc&action=edit reuploaddesc]
\n[[MediaWiki_talk:Reuploaddesc|Talk]]\n
\nReturn to the upload form.\n\n{{int:Reuploaddesc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Reverted&action=edit reverted]
\n[[MediaWiki_talk:Reverted|Talk]]\n
\nReverted to earlier revision\n\n{{int:Reverted}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revertimg&action=edit revertimg]
\n[[MediaWiki_talk:Revertimg|Talk]]\n
\nrev\n\n{{int:Revertimg}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revertpage&action=edit revertpage]
\n[[MediaWiki_talk:Revertpage|Talk]]\n
\nReverted edit of $2, changed back to last version by $1\n\n{{int:Revertpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revhistory&action=edit revhistory]
\n[[MediaWiki_talk:Revhistory|Talk]]\n
\nRevision history\n\n{{int:Revhistory}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revisionasof&action=edit revisionasof]
\n[[MediaWiki_talk:Revisionasof|Talk]]\n
\nRevision as of $1\n\n{{int:Revisionasof}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revnotfound&action=edit revnotfound]
\n[[MediaWiki_talk:Revnotfound|Talk]]\n
\nRevision not found\n\n{{int:Revnotfound}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Revnotfoundtext&action=edit revnotfoundtext]
\n[[MediaWiki_talk:Revnotfoundtext|Talk]]\n
\nThe old revision of the page you asked for could not be found.\nPlease check the URL you used to access this page.\n\n\n{{int:Revnotfoundtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rfcurl&action=edit rfcurl]
\n[[MediaWiki_talk:Rfcurl|Talk]]\n
\nhttp://www.faqs.org/rfcs/rfc$1.html\n\n{{int:Rfcurl}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rights&action=edit rights]
\n[[MediaWiki_talk:Rights|Talk]]\n
\nRights:\n\n{{int:Rights}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollback&action=edit rollback]
\n[[MediaWiki_talk:Rollback|Talk]]\n
\nRoll back edits\n\n{{int:Rollback}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollback_short&action=edit rollback_short]
\n[[MediaWiki_talk:Rollback_short|Talk]]\n
\nRollback\n\n{{int:Rollback_short}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollbackfailed&action=edit rollbackfailed]
\n[[MediaWiki_talk:Rollbackfailed|Talk]]\n
\nRollback failed\n\n{{int:Rollbackfailed}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rollbacklink&action=edit rollbacklink]
\n[[MediaWiki_talk:Rollbacklink|Talk]]\n
\nrollback\n\n{{int:Rollbacklink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Rows&action=edit rows]
\n[[MediaWiki_talk:Rows|Talk]]\n
\nRows\n\n{{int:Rows}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savearticle&action=edit savearticle]
\n[[MediaWiki_talk:Savearticle|Talk]]\n
\nSave page\n\n{{int:Savearticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savedprefs&action=edit savedprefs]
\n[[MediaWiki_talk:Savedprefs|Talk]]\n
\nYour preferences have been saved.\n\n{{int:Savedprefs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Savefile&action=edit savefile]
\n[[MediaWiki_talk:Savefile|Talk]]\n
\nSave file\n\n{{int:Savefile}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Saveprefs&action=edit saveprefs]
\n[[MediaWiki_talk:Saveprefs|Talk]]\n
\nSave preferences\n\n{{int:Saveprefs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Search&action=edit search]
\n[[MediaWiki_talk:Search|Talk]]\n
\nSearch\n\n{{int:Search}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchdisabled&action=edit searchdisabled]
\n[[MediaWiki_talk:Searchdisabled|Talk]]\n
\n<p>Sorry! Full text search has been disabled temporarily, for performance reasons. In the meantime, you can use the Google search below, which may be out of date.</p>\n\n{{int:Searchdisabled}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchhelppage&action=edit searchhelppage]
\n[[MediaWiki_talk:Searchhelppage|Talk]]\n
\nWikipedia:Searching\n\n{{int:Searchhelppage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchingwikipedia&action=edit searchingwikipedia]
\n[[MediaWiki_talk:Searchingwikipedia|Talk]]\n
\nSearching Wikipedia\n\n{{int:Searchingwikipedia}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchquery&action=edit searchquery]
\n[[MediaWiki_talk:Searchquery|Talk]]\n
\nFor query "$1"\n\n{{int:Searchquery}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresults&action=edit searchresults]
\n[[MediaWiki_talk:Searchresults|Talk]]\n
\nSearch results\n\n{{int:Searchresults}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresultshead&action=edit searchresultshead]
\n[[MediaWiki_talk:Searchresultshead|Talk]]\n
\nSearch result settings\n\n{{int:Searchresultshead}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Searchresulttext&action=edit searchresulttext]
\n[[MediaWiki_talk:Searchresulttext|Talk]]\n
\nFor more information about searching Wikipedia, see $1.\n\n{{int:Searchresulttext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sectionedit&action=edit sectionedit]
\n[[MediaWiki_talk:Sectionedit|Talk]]\n
\n (section)\n\n{{int:Sectionedit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selectnewerversionfordiff&action=edit selectnewerversionfordiff]
\n[[MediaWiki_talk:Selectnewerversionfordiff|Talk]]\n
\nSelect a newer version for comparison\n\n{{int:Selectnewerversionfordiff}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selectolderversionfordiff&action=edit selectolderversionfordiff]
\n[[MediaWiki_talk:Selectolderversionfordiff|Talk]]\n
\nSelect an older version for comparison\n\n{{int:Selectolderversionfordiff}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selectonly&action=edit selectonly]
\n[[MediaWiki_talk:Selectonly|Talk]]\n
\nOnly read-only queries are allowed.\n\n{{int:Selectonly}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selflinks&action=edit selflinks]
\n[[MediaWiki_talk:Selflinks|Talk]]\n
\nPages with Self Links\n\n{{int:Selflinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Selflinkstext&action=edit selflinkstext]
\n[[MediaWiki_talk:Selflinkstext|Talk]]\n
\nThe following pages contain a link to themselves, which they should not.\n\n{{int:Selflinkstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Seriousxhtmlerrors&action=edit seriousxhtmlerrors]
\n[[MediaWiki_talk:Seriousxhtmlerrors|Talk]]\n
\nThere were serious xhtml markup errors detected by tidy.\n\n{{int:Seriousxhtmlerrors}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Servertime&action=edit servertime]
\n[[MediaWiki_talk:Servertime|Talk]]\n
\nServer time is now\n\n{{int:Servertime}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Set_rights_fail&action=edit set_rights_fail]
\n[[MediaWiki_talk:Set_rights_fail|Talk]]\n
\n<b>User rights for "$1" could not be set. (Did you enter the name correctly?)</b>\n\n{{int:Set_rights_fail}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Set_user_rights&action=edit set_user_rights]
\n[[MediaWiki_talk:Set_user_rights|Talk]]\n
\nSet user rights\n\n{{int:Set_user_rights}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Setbureaucratflag&action=edit setbureaucratflag]
\n[[MediaWiki_talk:Setbureaucratflag|Talk]]\n
\nSet bureaucrat flag\n\n{{int:Setbureaucratflag}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Shortpages&action=edit shortpages]
\n[[MediaWiki_talk:Shortpages|Talk]]\n
\nShort pages\n\n{{int:Shortpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Show&action=edit show]
\n[[MediaWiki_talk:Show|Talk]]\n
\nshow\n\n{{int:Show}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showhideminor&action=edit showhideminor]
\n[[MediaWiki_talk:Showhideminor|Talk]]\n
\n$1 minor edits | $2 bots | $3 logged in users \n\n{{int:Showhideminor}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showingresults&action=edit showingresults]
\n[[MediaWiki_talk:Showingresults|Talk]]\n
\nShowing below <b>$1</b> results starting with #<b>$2</b>.\n\n{{int:Showingresults}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showingresultsnum&action=edit showingresultsnum]
\n[[MediaWiki_talk:Showingresultsnum|Talk]]\n
\nShowing below <b>$3</b> results starting with #<b>$2</b>.\n\n{{int:Showingresultsnum}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showlast&action=edit showlast]
\n[[MediaWiki_talk:Showlast|Talk]]\n
\nShow last $1 images sorted $2.\n\n{{int:Showlast}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showpreview&action=edit showpreview]
\n[[MediaWiki_talk:Showpreview|Talk]]\n
\nShow preview\n\n{{int:Showpreview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Showtoc&action=edit showtoc]
\n[[MediaWiki_talk:Showtoc|Talk]]\n
\nshow\n\n{{int:Showtoc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sig_tip&action=edit sig_tip]
\n[[MediaWiki_talk:Sig_tip|Talk]]\n
\nYour signature with timestamp\n\n{{int:Sig_tip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitestats&action=edit sitestats]
\n[[MediaWiki_talk:Sitestats|Talk]]\n
\nSite statistics\n\n{{int:Sitestats}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitestatstext&action=edit sitestatstext]
\n[[MediaWiki_talk:Sitestatstext|Talk]]\n
\nThere are '''$1''' total pages in the database.\nThis includes "talk" pages, pages about Wikipedia, minimal "stub"\npages, redirects, and others that probably don't qualify as content pages.\nExcluding those, there are '''$2''' pages that are probably legitimate\ncontent pages.\n\nThere have been a total of '''$3''' page views, and '''$4''' page edits\nsince the wiki was setup.\nThat comes to '''$5''' average edits per page, and '''$6''' views per edit.\n\n{{int:Sitestatstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitesubtitle&action=edit sitesubtitle]
\n[[MediaWiki_talk:Sitesubtitle|Talk]]\n
\nThe Free Encyclopedia\n\n{{int:Sitesubtitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitesupport&action=edit sitesupport]
\n[[MediaWiki_talk:Sitesupport|Talk]]\n
\nDonations\n\n{{int:Sitesupport}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sitetitle&action=edit sitetitle]
\n[[MediaWiki_talk:Sitetitle|Talk]]\n
\nWikipedia\n\n{{int:Sitetitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Siteuser&action=edit siteuser]
\n[[MediaWiki_talk:Siteuser|Talk]]\n
\nWikipedia user $1\n\n{{int:Siteuser}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Siteusers&action=edit siteusers]
\n[[MediaWiki_talk:Siteusers|Talk]]\n
\nWikipedia user(s) $1\n\n{{int:Siteusers}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Skin&action=edit skin]
\n[[MediaWiki_talk:Skin|Talk]]\n
\nSkin\n\n{{int:Skin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Spamprotectiontext&action=edit spamprotectiontext]
\n[[MediaWiki_talk:Spamprotectiontext|Talk]]\n
\nThe page you wanted to save was blocked by the spam filter. This is probably caused by a link to an external site. \n\nYou might want to check the following regular expression for patterns that are currently blocked:\n\n{{int:Spamprotectiontext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Spamprotectiontitle&action=edit spamprotectiontitle]
\n[[MediaWiki_talk:Spamprotectiontitle|Talk]]\n
\nSpam protection filter\n\n{{int:Spamprotectiontitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Specialpage&action=edit specialpage]
\n[[MediaWiki_talk:Specialpage|Talk]]\n
\nSpecial Page\n\n{{int:Specialpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Specialpages&action=edit specialpages]
\n[[MediaWiki_talk:Specialpages|Talk]]\n
\nSpecial pages\n\n{{int:Specialpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Spheading&action=edit spheading]
\n[[MediaWiki_talk:Spheading|Talk]]\n
\nSpecial pages for all users\n\n{{int:Spheading}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sqlislogged&action=edit sqlislogged]
\n[[MediaWiki_talk:Sqlislogged|Talk]]\n
\nPlease note that all queries are logged.\n\n{{int:Sqlislogged}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sqlquery&action=edit sqlquery]
\n[[MediaWiki_talk:Sqlquery|Talk]]\n
\nEnter query\n\n{{int:Sqlquery}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Statistics&action=edit statistics]
\n[[MediaWiki_talk:Statistics|Talk]]\n
\nStatistics\n\n{{int:Statistics}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Storedversion&action=edit storedversion]
\n[[MediaWiki_talk:Storedversion|Talk]]\n
\nStored version\n\n{{int:Storedversion}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Stubthreshold&action=edit stubthreshold]
\n[[MediaWiki_talk:Stubthreshold|Talk]]\n
\nThreshold for stub display\n\n{{int:Stubthreshold}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subcategories&action=edit subcategories]
\n[[MediaWiki_talk:Subcategories|Talk]]\n
\nSubcategories\n\n{{int:Subcategories}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subject&action=edit subject]
\n[[MediaWiki_talk:Subject|Talk]]\n
\nSubject/headline\n\n{{int:Subject}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Subjectpage&action=edit subjectpage]
\n[[MediaWiki_talk:Subjectpage|Talk]]\n
\nView subject\n\n{{int:Subjectpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Successfulupload&action=edit successfulupload]
\n[[MediaWiki_talk:Successfulupload|Talk]]\n
\nSuccessful upload\n\n{{int:Successfulupload}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Summary&action=edit summary]
\n[[MediaWiki_talk:Summary|Talk]]\n
\nSummary\n\n{{int:Summary}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysopspheading&action=edit sysopspheading]
\n[[MediaWiki_talk:Sysopspheading|Talk]]\n
\nFor sysop use only\n\n{{int:Sysopspheading}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysoptext&action=edit sysoptext]
\n[[MediaWiki_talk:Sysoptext|Talk]]\n
\nThe action you have requested can only be\nperformed by users with "sysop" status.\nSee $1.\n\n{{int:Sysoptext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Sysoptitle&action=edit sysoptitle]
\n[[MediaWiki_talk:Sysoptitle|Talk]]\n
\nSysop access required\n\n{{int:Sysoptitle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tableform&action=edit tableform]
\n[[MediaWiki_talk:Tableform|Talk]]\n
\ntable\n\n{{int:Tableform}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talk&action=edit talk]
\n[[MediaWiki_talk:Talk|Talk]]\n
\nDiscussion\n\n{{int:Talk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkexists&action=edit talkexists]
\n[[MediaWiki_talk:Talkexists|Talk]]\n
\nThe page itself was moved successfully, but the\ntalk page could not be moved because one already exists at the new\ntitle. Please merge them manually.\n\n{{int:Talkexists}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpage&action=edit talkpage]
\n[[MediaWiki_talk:Talkpage|Talk]]\n
\nDiscuss this page\n\n{{int:Talkpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpagemoved&action=edit talkpagemoved]
\n[[MediaWiki_talk:Talkpagemoved|Talk]]\n
\nThe corresponding talk page was also moved.\n\n{{int:Talkpagemoved}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpagenotmoved&action=edit talkpagenotmoved]
\n[[MediaWiki_talk:Talkpagenotmoved|Talk]]\n
\nThe corresponding talk page was <strong>not</strong> moved.\n\n{{int:Talkpagenotmoved}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Talkpagetext&action=edit talkpagetext]
\n[[MediaWiki_talk:Talkpagetext|Talk]]\n
\n<!-- MediaWiki:talkpagetext -->\n\n{{int:Talkpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Textboxsize&action=edit textboxsize]
\n[[MediaWiki_talk:Textboxsize|Talk]]\n
\nTextbox dimensions\n\n{{int:Textboxsize}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Textmatches&action=edit textmatches]
\n[[MediaWiki_talk:Textmatches|Talk]]\n
\nPage text matches\n\n{{int:Textmatches}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Thisisdeleted&action=edit thisisdeleted]
\n[[MediaWiki_talk:Thisisdeleted|Talk]]\n
\nView or restore $1?\n\n{{int:Thisisdeleted}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Thumbnail-more&action=edit thumbnail-more]
\n[[MediaWiki_talk:Thumbnail-more|Talk]]\n
\nEnlarge\n\n{{int:Thumbnail-more}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Timezoneoffset&action=edit timezoneoffset]
\n[[MediaWiki_talk:Timezoneoffset|Talk]]\n
\nOffset\n\n{{int:Timezoneoffset}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Timezonetext&action=edit timezonetext]
\n[[MediaWiki_talk:Timezonetext|Talk]]\n
\nEnter number of hours your local time differs\nfrom server time (UTC).\n\n{{int:Timezonetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Titlematches&action=edit titlematches]
\n[[MediaWiki_talk:Titlematches|Talk]]\n
\nArticle title matches\n\n{{int:Titlematches}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Toc&action=edit toc]
\n[[MediaWiki_talk:Toc|Talk]]\n
\nTable of contents\n\n{{int:Toc}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Toolbox&action=edit toolbox]
\n[[MediaWiki_talk:Toolbox|Talk]]\n
\nToolbox\n\n{{int:Toolbox}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-addsection&action=edit tooltip-addsection]
\n[[MediaWiki_talk:Tooltip-addsection|Talk]]\n
\nAdd a comment to this page. [alt-+]\n\n{{int:Tooltip-addsection}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-anontalk&action=edit tooltip-anontalk]
\n[[MediaWiki_talk:Tooltip-anontalk|Talk]]\n
\nDiscussion about edits from this ip address [alt-n]\n\n{{int:Tooltip-anontalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-anonuserpage&action=edit tooltip-anonuserpage]
\n[[MediaWiki_talk:Tooltip-anonuserpage|Talk]]\n
\nThe user page for the ip you're editing as [alt-.]\n\n{{int:Tooltip-anonuserpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-article&action=edit tooltip-article]
\n[[MediaWiki_talk:Tooltip-article|Talk]]\n
\nView the content page [alt-a]\n\n{{int:Tooltip-article}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-atom&action=edit tooltip-atom]
\n[[MediaWiki_talk:Tooltip-atom|Talk]]\n
\nAtom feed for this page\n\n{{int:Tooltip-atom}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-compareselectedversions&action=edit tooltip-compareselectedversions]
\n[[MediaWiki_talk:Tooltip-compareselectedversions|Talk]]\n
\nSee the differences between the two selected versions of this page. [alt-v]\n\n{{int:Tooltip-compareselectedversions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-contributions&action=edit tooltip-contributions]
\n[[MediaWiki_talk:Tooltip-contributions|Talk]]\n
\nView the list of contributions of this user\n\n{{int:Tooltip-contributions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-currentevents&action=edit tooltip-currentevents]
\n[[MediaWiki_talk:Tooltip-currentevents|Talk]]\n
\nFind background information on current events\n\n{{int:Tooltip-currentevents}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-delete&action=edit tooltip-delete]
\n[[MediaWiki_talk:Tooltip-delete|Talk]]\n
\nDelete this page [alt-d]\n\n{{int:Tooltip-delete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-edit&action=edit tooltip-edit]
\n[[MediaWiki_talk:Tooltip-edit|Talk]]\n
\nYou can edit this page. Please use the preview button before saving. [alt-e]\n\n{{int:Tooltip-edit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-emailuser&action=edit tooltip-emailuser]
\n[[MediaWiki_talk:Tooltip-emailuser|Talk]]\n
\nSend a mail to this user\n\n{{int:Tooltip-emailuser}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-help&action=edit tooltip-help]
\n[[MediaWiki_talk:Tooltip-help|Talk]]\n
\nThe place to find out.\n\n{{int:Tooltip-help}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-history&action=edit tooltip-history]
\n[[MediaWiki_talk:Tooltip-history|Talk]]\n
\nPast versions of this page, [alt-h]\n\n{{int:Tooltip-history}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-login&action=edit tooltip-login]
\n[[MediaWiki_talk:Tooltip-login|Talk]]\n
\nYou are encouraged to log in, it is not mandatory however. [alt-o]\n\n{{int:Tooltip-login}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-logout&action=edit tooltip-logout]
\n[[MediaWiki_talk:Tooltip-logout|Talk]]\n
\nLog out [alt-o]\n\n{{int:Tooltip-logout}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-mainpage&action=edit tooltip-mainpage]
\n[[MediaWiki_talk:Tooltip-mainpage|Talk]]\n
\nVisit the Main Page [alt-z]\n\n{{int:Tooltip-mainpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-minoredit&action=edit tooltip-minoredit]
\n[[MediaWiki_talk:Tooltip-minoredit|Talk]]\n
\nMark this as a minor edit [alt-i]\n\n{{int:Tooltip-minoredit}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-move&action=edit tooltip-move]
\n[[MediaWiki_talk:Tooltip-move|Talk]]\n
\nMove this page [alt-m]\n\n{{int:Tooltip-move}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-mycontris&action=edit tooltip-mycontris]
\n[[MediaWiki_talk:Tooltip-mycontris|Talk]]\n
\nList of my contributions [alt-y]\n\n{{int:Tooltip-mycontris}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-mytalk&action=edit tooltip-mytalk]
\n[[MediaWiki_talk:Tooltip-mytalk|Talk]]\n
\nMy talk page [alt-n]\n\n{{int:Tooltip-mytalk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-nomove&action=edit tooltip-nomove]
\n[[MediaWiki_talk:Tooltip-nomove|Talk]]\n
\nYou don't have the permissions to move this page\n\n{{int:Tooltip-nomove}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-portal&action=edit tooltip-portal]
\n[[MediaWiki_talk:Tooltip-portal|Talk]]\n
\nAbout the project, what you can do, where to find things\n\n{{int:Tooltip-portal}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-preferences&action=edit tooltip-preferences]
\n[[MediaWiki_talk:Tooltip-preferences|Talk]]\n
\nMy preferences\n\n{{int:Tooltip-preferences}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-preview&action=edit tooltip-preview]
\n[[MediaWiki_talk:Tooltip-preview|Talk]]\n
\nPreview your changes, please use this before saving! [alt-p]\n\n{{int:Tooltip-preview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-protect&action=edit tooltip-protect]
\n[[MediaWiki_talk:Tooltip-protect|Talk]]\n
\nProtect this page [alt-=]\n\n{{int:Tooltip-protect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-randompage&action=edit tooltip-randompage]
\n[[MediaWiki_talk:Tooltip-randompage|Talk]]\n
\nLoad a random page [alt-x]\n\n{{int:Tooltip-randompage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-recentchanges&action=edit tooltip-recentchanges]
\n[[MediaWiki_talk:Tooltip-recentchanges|Talk]]\n
\nThe list of recent changes in the wiki. [alt-r]\n\n{{int:Tooltip-recentchanges}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-recentchangeslinked&action=edit tooltip-recentchangeslinked]
\n[[MediaWiki_talk:Tooltip-recentchangeslinked|Talk]]\n
\nRecent changes in pages linking to this page [alt-c]\n\n{{int:Tooltip-recentchangeslinked}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-rss&action=edit tooltip-rss]
\n[[MediaWiki_talk:Tooltip-rss|Talk]]\n
\nRSS feed for this page\n\n{{int:Tooltip-rss}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-save&action=edit tooltip-save]
\n[[MediaWiki_talk:Tooltip-save|Talk]]\n
\nSave you changes [alt-s]\n\n{{int:Tooltip-save}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-search&action=edit tooltip-search]
\n[[MediaWiki_talk:Tooltip-search|Talk]]\n
\nSearch this wiki [alt-f]\n\n{{int:Tooltip-search}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-sitesupport&action=edit tooltip-sitesupport]
\n[[MediaWiki_talk:Tooltip-sitesupport|Talk]]\n
\nSupport Wikipedia\n\n{{int:Tooltip-sitesupport}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-specialpage&action=edit tooltip-specialpage]
\n[[MediaWiki_talk:Tooltip-specialpage|Talk]]\n
\nThis is a special page, you can't edit the page itself.\n\n{{int:Tooltip-specialpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-specialpages&action=edit tooltip-specialpages]
\n[[MediaWiki_talk:Tooltip-specialpages|Talk]]\n
\nList of all special pages [alt-q]\n\n{{int:Tooltip-specialpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-talk&action=edit tooltip-talk]
\n[[MediaWiki_talk:Tooltip-talk|Talk]]\n
\nDiscussion about the content page [alt-t]\n\n{{int:Tooltip-talk}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-undelete&action=edit tooltip-undelete]
\n[[MediaWiki_talk:Tooltip-undelete|Talk]]\n
\nRestore $1 deleted edits to this page [alt-d]\n\n{{int:Tooltip-undelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-unwatch&action=edit tooltip-unwatch]
\n[[MediaWiki_talk:Tooltip-unwatch|Talk]]\n
\nRemove this page from your watchlist [alt-w]\n\n{{int:Tooltip-unwatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-upload&action=edit tooltip-upload]
\n[[MediaWiki_talk:Tooltip-upload|Talk]]\n
\nUpload images or media files [alt-u]\n\n{{int:Tooltip-upload}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-userpage&action=edit tooltip-userpage]
\n[[MediaWiki_talk:Tooltip-userpage|Talk]]\n
\nMy user page [alt-.]\n\n{{int:Tooltip-userpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-viewsource&action=edit tooltip-viewsource]
\n[[MediaWiki_talk:Tooltip-viewsource|Talk]]\n
\nThis page is protected. You can view it's source. [alt-e]\n\n{{int:Tooltip-viewsource}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-watch&action=edit tooltip-watch]
\n[[MediaWiki_talk:Tooltip-watch|Talk]]\n
\nAdd this page to your watchlist [alt-w]\n\n{{int:Tooltip-watch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-watchlist&action=edit tooltip-watchlist]
\n[[MediaWiki_talk:Tooltip-watchlist|Talk]]\n
\nThe list of pages you're monitoring for changes. [alt-l]\n\n{{int:Tooltip-watchlist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Tooltip-whatlinkshere&action=edit tooltip-whatlinkshere]
\n[[MediaWiki_talk:Tooltip-whatlinkshere|Talk]]\n
\nList of all wiki pages that link here [alt-b]\n\n{{int:Tooltip-whatlinkshere}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uclinks&action=edit uclinks]
\n[[MediaWiki_talk:Uclinks|Talk]]\n
\nView the last $1 changes; view the last $2 days.\n\n{{int:Uclinks}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Ucnote&action=edit ucnote]
\n[[MediaWiki_talk:Ucnote|Talk]]\n
\nBelow are this user's last <b>$1</b> changes in the last <b>$2</b> days.\n\n{{int:Ucnote}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uctop&action=edit uctop]
\n[[MediaWiki_talk:Uctop|Talk]]\n
\n (top)\n\n{{int:Uctop}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblockip&action=edit unblockip]
\n[[MediaWiki_talk:Unblockip|Talk]]\n
\nUnblock user\n\n{{int:Unblockip}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblockiptext&action=edit unblockiptext]
\n[[MediaWiki_talk:Unblockiptext|Talk]]\n
\nUse the form below to restore write access\nto a previously blocked IP address or username.\n\n{{int:Unblockiptext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblocklink&action=edit unblocklink]
\n[[MediaWiki_talk:Unblocklink|Talk]]\n
\nunblock\n\n{{int:Unblocklink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unblocklogentry&action=edit unblocklogentry]
\n[[MediaWiki_talk:Unblocklogentry|Talk]]\n
\nunblocked "$1"\n\n{{int:Unblocklogentry}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undelete&action=edit undelete]
\n[[MediaWiki_talk:Undelete|Talk]]\n
\nRestore deleted page\n\n{{int:Undelete}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undelete_short&action=edit undelete_short]
\n[[MediaWiki_talk:Undelete_short|Talk]]\n
\nUndelete\n\n{{int:Undelete_short}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletearticle&action=edit undeletearticle]
\n[[MediaWiki_talk:Undeletearticle|Talk]]\n
\nRestore deleted page\n\n{{int:Undeletearticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletebtn&action=edit undeletebtn]
\n[[MediaWiki_talk:Undeletebtn|Talk]]\n
\nRestore!\n\n{{int:Undeletebtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletedarticle&action=edit undeletedarticle]
\n[[MediaWiki_talk:Undeletedarticle|Talk]]\n
\nrestored "$1"\n\n{{int:Undeletedarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletedtext&action=edit undeletedtext]
\n[[MediaWiki_talk:Undeletedtext|Talk]]\n
\n[[$1]] has been successfully restored.\nSee [[Wikipedia:Deletion_log]] for a record of recent deletions and restorations.\n\n{{int:Undeletedtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletehistory&action=edit undeletehistory]
\n[[MediaWiki_talk:Undeletehistory|Talk]]\n
\nIf you restore the page, all revisions will be restored to the history.\nIf a new page with the same name has been created since the deletion, the restored\nrevisions will appear in the prior history, and the current revision of the live page\nwill not be automatically replaced.\n\n{{int:Undeletehistory}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletepage&action=edit undeletepage]
\n[[MediaWiki_talk:Undeletepage|Talk]]\n
\nView and restore deleted pages\n\n{{int:Undeletepage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeletepagetext&action=edit undeletepagetext]
\n[[MediaWiki_talk:Undeletepagetext|Talk]]\n
\nThe following pages have been deleted but are still in the archive and\ncan be restored. The archive may be periodically cleaned out.\n\n{{int:Undeletepagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeleterevision&action=edit undeleterevision]
\n[[MediaWiki_talk:Undeleterevision|Talk]]\n
\nDeleted revision as of $1\n\n{{int:Undeleterevision}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Undeleterevisions&action=edit undeleterevisions]
\n[[MediaWiki_talk:Undeleterevisions|Talk]]\n
\n$1 revisions archived\n\n{{int:Undeleterevisions}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unexpected&action=edit unexpected]
\n[[MediaWiki_talk:Unexpected|Talk]]\n
\nUnexpected value: "$1"="$2".\n\n{{int:Unexpected}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockbtn&action=edit unlockbtn]
\n[[MediaWiki_talk:Unlockbtn|Talk]]\n
\nUnlock database\n\n{{int:Unlockbtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockconfirm&action=edit unlockconfirm]
\n[[MediaWiki_talk:Unlockconfirm|Talk]]\n
\nYes, I really want to unlock the database.\n\n{{int:Unlockconfirm}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdb&action=edit unlockdb]
\n[[MediaWiki_talk:Unlockdb|Talk]]\n
\nUnlock database\n\n{{int:Unlockdb}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbsuccesssub&action=edit unlockdbsuccesssub]
\n[[MediaWiki_talk:Unlockdbsuccesssub|Talk]]\n
\nDatabase lock removed\n\n{{int:Unlockdbsuccesssub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbsuccesstext&action=edit unlockdbsuccesstext]
\n[[MediaWiki_talk:Unlockdbsuccesstext|Talk]]\n
\nThe database has been unlocked.\n\n{{int:Unlockdbsuccesstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unlockdbtext&action=edit unlockdbtext]
\n[[MediaWiki_talk:Unlockdbtext|Talk]]\n
\nUnlocking the database will restore the ability of all\nusers to edit pages, change their preferences, edit their watchlists, and\nother things requiring changes in the database.\nPlease confirm that this is what you intend to do.\n\n{{int:Unlockdbtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotect&action=edit unprotect]
\n[[MediaWiki_talk:Unprotect|Talk]]\n
\nUnprotect\n\n{{int:Unprotect}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectcomment&action=edit unprotectcomment]
\n[[MediaWiki_talk:Unprotectcomment|Talk]]\n
\nReason for unprotecting\n\n{{int:Unprotectcomment}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectedarticle&action=edit unprotectedarticle]
\n[[MediaWiki_talk:Unprotectedarticle|Talk]]\n
\nunprotected [[$1]]\n\n{{int:Unprotectedarticle}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectsub&action=edit unprotectsub]
\n[[MediaWiki_talk:Unprotectsub|Talk]]\n
\n(Unprotecting "$1")\n\n{{int:Unprotectsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unprotectthispage&action=edit unprotectthispage]
\n[[MediaWiki_talk:Unprotectthispage|Talk]]\n
\nUnprotect this page\n\n{{int:Unprotectthispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unusedimages&action=edit unusedimages]
\n[[MediaWiki_talk:Unusedimages|Talk]]\n
\nUnused images\n\n{{int:Unusedimages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unusedimagestext&action=edit unusedimagestext]
\n[[MediaWiki_talk:Unusedimagestext|Talk]]\n
\n<p>Please note that other web sites may link to an image with\na direct URL, and so may still be listed here despite being\nin active use.\n\n{{int:Unusedimagestext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unwatch&action=edit unwatch]
\n[[MediaWiki_talk:Unwatch|Talk]]\n
\nUnwatch\n\n{{int:Unwatch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Unwatchthispage&action=edit unwatchthispage]
\n[[MediaWiki_talk:Unwatchthispage|Talk]]\n
\nStop watching\n\n{{int:Unwatchthispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Updated&action=edit updated]
\n[[MediaWiki_talk:Updated|Talk]]\n
\n(Updated)\n\n{{int:Updated}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Upload&action=edit upload]
\n[[MediaWiki_talk:Upload|Talk]]\n
\nUpload file\n\n{{int:Upload}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadbtn&action=edit uploadbtn]
\n[[MediaWiki_talk:Uploadbtn|Talk]]\n
\nUpload file\n\n{{int:Uploadbtn}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploaddisabled&action=edit uploaddisabled]
\n[[MediaWiki_talk:Uploaddisabled|Talk]]\n
\nSorry, uploading is disabled.\n\n{{int:Uploaddisabled}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadedfiles&action=edit uploadedfiles]
\n[[MediaWiki_talk:Uploadedfiles|Talk]]\n
\nUploaded files\n\n{{int:Uploadedfiles}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadedimage&action=edit uploadedimage]
\n[[MediaWiki_talk:Uploadedimage|Talk]]\n
\nuploaded "$1"\n\n{{int:Uploadedimage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploaderror&action=edit uploaderror]
\n[[MediaWiki_talk:Uploaderror|Talk]]\n
\nUpload error\n\n{{int:Uploaderror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadfile&action=edit uploadfile]
\n[[MediaWiki_talk:Uploadfile|Talk]]\n
\nUpload images, sounds, documents etc.\n\n{{int:Uploadfile}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlink&action=edit uploadlink]
\n[[MediaWiki_talk:Uploadlink|Talk]]\n
\nUpload images\n\n{{int:Uploadlink}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlog&action=edit uploadlog]
\n[[MediaWiki_talk:Uploadlog|Talk]]\n
\nupload log\n\n{{int:Uploadlog}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlogpage&action=edit uploadlogpage]
\n[[MediaWiki_talk:Uploadlogpage|Talk]]\n
\nUpload_log\n\n{{int:Uploadlogpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadlogpagetext&action=edit uploadlogpagetext]
\n[[MediaWiki_talk:Uploadlogpagetext|Talk]]\n
\nBelow is a list of the most recent file uploads.\nAll times shown are server time (UTC).\n<ul>\n</ul>\n\n\n{{int:Uploadlogpagetext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadnologin&action=edit uploadnologin]
\n[[MediaWiki_talk:Uploadnologin|Talk]]\n
\nNot logged in\n\n{{int:Uploadnologin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadnologintext&action=edit uploadnologintext]
\n[[MediaWiki_talk:Uploadnologintext|Talk]]\n
\nYou must be <a href="/wiki/Special:Userlogin">logged in</a>\nto upload files.\n\n{{int:Uploadnologintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadtext&action=edit uploadtext]
\n[[MediaWiki_talk:Uploadtext|Talk]]\n
\n<strong>STOP!</strong> Before you upload here,\nmake sure to read and follow the <a href="/wiki/Special:Image_use_policy">image use policy</a>.\n<p>If a file with the name you are specifying already\nexists on the wiki, it'll be replaced without warning.\nSo unless you mean to update a file, it's a good idea\nto first check if such a file exists.\n<p>To view or search previously uploaded images,\ngo to the <a href="/wiki/Special:Imagelist">list of uploaded images</a>.\nUploads and deletions are logged on the <a href="/wiki/Wikipedia:Upload_log">upload log</a>.\n</p><p>Use the form below to upload new image files for use in\nillustrating your pages.\nOn most browsers, you will see a "Browse..." button, which will\nbring up your operating system's standard file open dialog.\nChoosing a file will fill the name of that file into the text\nfield next to the button.\nYou must also check the box affirming that you are not\nviolating any copyrights by uploading the file.\nPress the "Upload" button to finish the upload.\nThis may take some time if you have a slow internet connection.\n<p>The preferred formats are JPEG for photographic images, PNG\nfor drawings and other iconic images, and OGG for sounds.\nPlease name your files descriptively to avoid confusion.\nTo include the image in a page, use a link in the form\n<b>[[Image:file.jpg]]</b> or <b>[[Image:file.ogg]]</b> for sounds.\n<p>Please note that as with wiki pages, others may edit or\ndelete your uploads if they think it serves the project, and\nyou may be blocked from uploading if you abuse the system.\n\n{{int:Uploadtext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Uploadwarning&action=edit uploadwarning]
\n[[MediaWiki_talk:Uploadwarning|Talk]]\n
\nUpload warning\n\n{{int:Uploadwarning}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:User_rights_set&action=edit user_rights_set]
\n[[MediaWiki_talk:User_rights_set|Talk]]\n
\n<b>User rights for "$1" updated</b>\n\n{{int:User_rights_set}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Usercssjs&action=edit usercssjs]
\n[[MediaWiki_talk:Usercssjs|Talk]]\n
\n'''Note:''' After saving, you have to tell your bowser to get the new version: '''Mozilla:''' click ''reload''(or ''ctrl-r''), '''IE / Opera:''' ''ctrl-f5'', '''Safari:''' ''cmd-r'', '''Konqueror''' ''ctrl-r''.\n\n{{int:Usercssjs}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Usercssjsyoucanpreview&action=edit usercssjsyoucanpreview]
\n[[MediaWiki_talk:Usercssjsyoucanpreview|Talk]]\n
\n<strong>Tip:</strong> Use the 'Show preview' button to test your new css/js before saving.\n\n{{int:Usercssjsyoucanpreview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Usercsspreview&action=edit usercsspreview]
\n[[MediaWiki_talk:Usercsspreview|Talk]]\n
\n'''Remember that you are only previewing your user css, it has not yet been saved!'''\n\n{{int:Usercsspreview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userexists&action=edit userexists]
\n[[MediaWiki_talk:Userexists|Talk]]\n
\nThe user name you entered is already in use. Please choose a different name.\n\n{{int:Userexists}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userjspreview&action=edit userjspreview]
\n[[MediaWiki_talk:Userjspreview|Talk]]\n
\n'''Remember that you are only testing/previewing your user javascript, it has not yet been saved!'''\n\n{{int:Userjspreview}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userlogin&action=edit userlogin]
\n[[MediaWiki_talk:Userlogin|Talk]]\n
\nLog in\n\n{{int:Userlogin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userlogout&action=edit userlogout]
\n[[MediaWiki_talk:Userlogout|Talk]]\n
\nLog out\n\n{{int:Userlogout}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Usermailererror&action=edit usermailererror]
\n[[MediaWiki_talk:Usermailererror|Talk]]\n
\nMail object returned error: \n\n{{int:Usermailererror}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userpage&action=edit userpage]
\n[[MediaWiki_talk:Userpage|Talk]]\n
\nView user page\n\n{{int:Userpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userstats&action=edit userstats]
\n[[MediaWiki_talk:Userstats|Talk]]\n
\nUser statistics\n\n{{int:Userstats}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Userstatstext&action=edit userstatstext]
\n[[MediaWiki_talk:Userstatstext|Talk]]\n
\nThere are '''$1''' registered users.\n'''$2''' of these are administrators (see $3).\n\n{{int:Userstatstext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Version&action=edit version]
\n[[MediaWiki_talk:Version|Talk]]\n
\nVersion\n\n{{int:Version}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewcount&action=edit viewcount]
\n[[MediaWiki_talk:Viewcount|Talk]]\n
\nThis page has been accessed $1 times.\n\n{{int:Viewcount}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewprevnext&action=edit viewprevnext]
\n[[MediaWiki_talk:Viewprevnext|Talk]]\n
\nView ($1) ($2) ($3).\n\n{{int:Viewprevnext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewsource&action=edit viewsource]
\n[[MediaWiki_talk:Viewsource|Talk]]\n
\nView source\n\n{{int:Viewsource}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Viewtalkpage&action=edit viewtalkpage]
\n[[MediaWiki_talk:Viewtalkpage|Talk]]\n
\nView discussion\n\n{{int:Viewtalkpage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Wantedpages&action=edit wantedpages]
\n[[MediaWiki_talk:Wantedpages|Talk]]\n
\nWanted pages\n\n{{int:Wantedpages}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watch&action=edit watch]
\n[[MediaWiki_talk:Watch|Talk]]\n
\nWatch\n\n{{int:Watch}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchdetails&action=edit watchdetails]
\n[[MediaWiki_talk:Watchdetails|Talk]]\n
\n($1 pages watched not counting talk pages;\n$2 total pages edited since cutoff;\n$3...\n<a href='$4'>show and edit complete list</a>.)\n\n{{int:Watchdetails}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watcheditlist&action=edit watcheditlist]
\n[[MediaWiki_talk:Watcheditlist|Talk]]\n
\nHere's an alphabetical list of your\nwatched pages. Check the boxes of pages you want to remove\nfrom your watchlist and click the 'remove checked' button\nat the bottom of the screen.\n\n{{int:Watcheditlist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlist&action=edit watchlist]
\n[[MediaWiki_talk:Watchlist|Talk]]\n
\nMy watchlist\n\n{{int:Watchlist}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlistcontains&action=edit watchlistcontains]
\n[[MediaWiki_talk:Watchlistcontains|Talk]]\n
\nYour watchlist contains $1 pages.\n\n{{int:Watchlistcontains}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchlistsub&action=edit watchlistsub]
\n[[MediaWiki_talk:Watchlistsub|Talk]]\n
\n(for user "$1")\n\n{{int:Watchlistsub}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchmethod-list&action=edit watchmethod-list]
\n[[MediaWiki_talk:Watchmethod-list|Talk]]\n
\nchecking watched pages for recent edits\n\n{{int:Watchmethod-list}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchmethod-recent&action=edit watchmethod-recent]
\n[[MediaWiki_talk:Watchmethod-recent|Talk]]\n
\nchecking recent edits for watched pages\n\n{{int:Watchmethod-recent}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnochange&action=edit watchnochange]
\n[[MediaWiki_talk:Watchnochange|Talk]]\n
\nNone of your watched items were edited in the time period displayed.\n\n{{int:Watchnochange}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnologin&action=edit watchnologin]
\n[[MediaWiki_talk:Watchnologin|Talk]]\n
\nNot logged in\n\n{{int:Watchnologin}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchnologintext&action=edit watchnologintext]
\n[[MediaWiki_talk:Watchnologintext|Talk]]\n
\nYou must be <a href="/wiki/Special:Userlogin">logged in</a>\nto modify your watchlist.\n\n{{int:Watchnologintext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchthis&action=edit watchthis]
\n[[MediaWiki_talk:Watchthis|Talk]]\n
\nWatch this page\n\n{{int:Watchthis}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Watchthispage&action=edit watchthispage]
\n[[MediaWiki_talk:Watchthispage|Talk]]\n
\nWatch this page\n\n{{int:Watchthispage}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Welcomecreation&action=edit welcomecreation]
\n[[MediaWiki_talk:Welcomecreation|Talk]]\n
\n<h2>Welcome, $1!</h2><p>Your account has been created.\nDon't forget to change your Wikipedia preferences.\n\n{{int:Welcomecreation}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whatlinkshere&action=edit whatlinkshere]
\n[[MediaWiki_talk:Whatlinkshere|Talk]]\n
\nWhat links here\n\n{{int:Whatlinkshere}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistacctext&action=edit whitelistacctext]
\n[[MediaWiki_talk:Whitelistacctext|Talk]]\n
\nTo be allowed to create accounts in this Wiki you have to [[Special:Userlogin|log]] in and have the appropriate permissions.\n\n{{int:Whitelistacctext}}\n
\n[http://su.wikipedia.org/w/wiki.phtml?title=MediaWiki:Whitelistacctitle&action=edit whitelistacctitle]
\n[[MediaWiki_talk:Whitelistacctitle|Talk]]\n
\nYou are not allowed to create an account\n\n{{int:Whitelistacctitle}}\n
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','',0,'MediaWiki default','20040602102605','',0,0,0,0,0.805737755171,'20040603084250','79959397897394'); INSERT INTO cur VALUES (802,8,'All_messages','#redirect [[Template:All messages]]\n','MediaWiki:All messages moved to Template:All messages',0,'Template namespace initialisation script','20040603084248','',0,1,0,1,0.231723265938203,'20040728102518','79959396915751'); INSERT INTO cur VALUES (803,8,'All_system_messages','#redirect [[Template:All system messages]]\n','MediaWiki:All system messages moved to Template:All system messages',0,'Template namespace initialisation script','20040603084250','',0,1,0,1,0.0321739120708536,'20040603084250','79959396915749'); INSERT INTO cur VALUES (804,8,'Gnunote','#redirect [[Template:Gnunote]]\n','MediaWiki:Gnunote moved to Template:Gnunote',0,'Template namespace initialisation script','20040603084251','',0,1,0,1,0.465699793273303,'20040603084251','79959396915748'); INSERT INTO cur VALUES (805,8,'Sitesupportpage','#redirect [[Template:Sitesupportpage]]\n','MediaWiki:Sitesupportpage moved to Template:Sitesupportpage',0,'Template namespace initialisation script','20040603084252','',0,1,0,1,0.231977260887602,'20040603084252','79959396915747'); INSERT INTO cur VALUES (806,4,'','\n\n
20th century ka Énzim
\n','',0,'24.29.135.164','20040813125544','sysop',0,0,0,0,0.762786955351743,'20040813125544','79959186874455'); INSERT INTO cur VALUES (807,0,'Ékologi','[[Category:Biologi]]\n[[Category:Ékologi]]\n\'\'\'Ékologi\'\'\' ngarupakeun cabang [[élmu]] nu ngulik sebaran jeung ayana [[mahluk hirup]], [[habitat]], jeung interaksi antara maranéhna sarta [[biologi lingkungan|lingkungan]]ana — nu ngawengku boh unsur-unsur [[abiotik]] (teu hirup) saperti [[cuaca]] jeung [[géologi]], jeung unsur [[biotik]] saperti [[spésiés]]. Istilah ieu diwanohkeun dina taun [[1866]] ku biolog Jérman [[Ernst Haeckel]], nyokot tina [[basa Yunani]] \'\'oikos\'\' nu hartina \"imah\" jeung \'\'logos\'\' nu hartina \"élmu\".\n\n\'\'\'[[Ékologi manusa]]\'\'\' ngarupakeun disiplin akademik nu patali tapi béda, ngulik [[kamanusaan]], kagiatan spésiésna nu teratur, jeung lingkunganana; raket pisan hubunganana jeung ékologi biologis, [[sosiologi]], ogé disiplin séjénna.\n\nDi saluareun kontéks ilmiah, kecap \'\'\'ékologi\'\'\' mindeng dipaké salaku sinonim pikeun \"[[lingkungan alami|lingkungan\'\'ana\'\']]\", nyaéta reureujeunganana sakur organisme liar nu kalolobaanana hirup dina tata sarta lingkungan aslina, kalawan saeutik pangaruh manusa; utamana nu patali jeung naon baé kapentingan [[umat manusa|manusa]] — [[ékonomi|ékonomis]], [[kaséhatan|médis]], [[éstétik|éstétis]], [[hédonisme|hédonistik]], séntiméntal, jsb... Harti ieu biasana dilarapkeun nalika urang nyebutkeun yén hiji barang/kagiatan mibanda ajén hadé atawa goréng pikeun \"ékologi\", jeung na [[ékologi politis]].\n\nNu séjén bisa ngalarapkeun kecap \'\'\'ékologi\'\'\' lain dina maksud élmu, tapi salaku sistem [[filosofi|filosofis]] atawa malah [[agamis]], nu nunjukkeun hiji sawangan ngeunaan mayapada jeung ajén-inajén husus sarta ajén moral — misalna yén totalitas hirup ngarupakeun hiji sistem kohérén, nu meureun aya tujuanana; yén punahna spésiés luhur téh \"goréng\"; yén jalma sakuduna hirup harmonis jeung mahluk hirup séjénna; jeung yén alam kudu leupas tina pangaruh jalma. \'\'Ékologi\'\' dina jihat ieu sok ogé disebut [[énvirontalisme]].\n\n\n== Cakupan ==\n\nÉkologi biasana dianggap salaku salasahiji cabang [[biologi]], élmu umum nu ngulik [[mahluk hirup]]. Hal ieu bisa diulik dina sababaraha tingkatan, ti [[protéin]] jeung [[asam nukléat]] (dina [[biokimia]] jeung [[biologi molekular]]), [[sél]] (dina [[biologi sél]]), organisme (dina [[botani]], [[zoologi]], jeung disiplin séjén nu sarupa), jeung pamungkas dina tingkatan populasi, komunitas, jeung [[ékosistem]] — nu ngarupakeun subjék ékologi.\n\nKusabab fokusna nu panglegana dina kahirupan jeung dina hubunganana antara mahluk hirup jeung [[(biologi) lingkungan|lingkungan]]na, ékologi ngamalir ka cabang élmu séjénna, kayaning [[géologi]] jeung [[géografi]], [[météorologi]], [[pedologi]], [[kimia]], jeung [[fisika]]. kusabab kitu, sakapeung ékologi sok disebut salaku élmu [[holistik]].\n\nÉkologi mindeng digambarkeun sabagé ulikan [[hubungan]] segitiga:\n\n* hubungan antara individu hiji [[spésiés]] — pikeun conto, ulikan ngeunaan [[nyiruan ratu]] jeung kumaha hubungan manéhna jeung [[nyiruan]] pagawé sarta [[nyiruan jalu]]. Nyiruan ratu sagemblengna dirawatan ku nyiruan pagawé; teu boga kakawasaan dina sayangna, tapi ngalaksanakeun réproduksi sakabéh populasina jeung ngaluarkeun féromon nu diperlukeun pikeun hirup kumbuhna koloni.\n\n* aktivitas nu diatur dina hiji spésiés — misalna, aktivitas nyiruan jadi jaminan [[pembuahan]] [[tangkal kembang|tatangkalan karembangan]]. Sayang nyiruan ogé ngahasilkeun [[madu]] keur spésiés séjén kayaning [[biruang]] jeung [[manusa]].\n\n* sarta lingkungan aktivitas ieu — pikeun conto, konsékuansi tina parobahan lingkungan kana aktivitas nyiruan. Nyiruan bisa paraéh alatan parobahan lingkungan (tempo \'\'[[pollinator decline]]\'\'). Lingkungan sakaligus kapangaruhan sarta jadi hiji konsékuénsi ayana kagiatan ieu sahingga ngait jeung kasalametan spésiésna.\n\n===Disiplin dina ékologi===\nÉkologi ngarupakeun hiji élmu nu ambahanana ngahontal cabang-cabang husus nu loba, di antarana\n\n* [[ékofisiologi]] (atawa autoékologi), ngulik hubungan antara hiji tipeu [[organismeu]] jeung faktor-faktor lingkunganana;\n* [[ékologi populasi]], ngulik hubungan antara hiji populasi jeung lingkunganana;\n* [[sinékologi]], ngulik hubungan antara hiji [[komunitas]], individu-individu rupa-rupa spésiés jeung lingkunganana;\n* Ulikan ngeunaan [[ékosistem]] spésifik.\n* [[ékologi global]], ngulik ékologi dina skala [[ékosfir]] atawa biosfir (sakabéh rohangan nu dieusi ku mahluk hirup).\n* [[ékologi kimiawi]], [[ékologi molekular]], jeung [[ékotoksikologi]].\n* [[ékologi terapan]], kaasup [[agroékologi]]\n* [[ékologi konservasi]], [[ékologi réstorasi]], jeung [[ékologi landscape]].\n* [[ékologi sato]], [[ékologi tutuwuhan]], jeung [[ékologi akuatik]]\n* [[ékologi taneuh]] jeung [[ékologi mikrobial]].\n* [[ékologi tropis]], [[ékologi kutub]], jeung [[ékologi kota]].\n* [[ékologi paripolah]]\n* [[ékoévolusi]] jeung [[paléoékologi]]\n* [[makroékologi]] jeung [[ékologi tioritis]]\n\nÉkologi ogé boga ketak nu penting dina loba lapang interdisiplin:\n\n* [[ékologi manusa]] jeung [[antropologi ékologis]].\n* [[ékologi komunitas]], [[ékologi sosial]], jeung [[kaséhatan ékologis]].\n* [[ékonomi ékologis]].\n* [[rancang ékologis|rancang]] jeung [[rékayasa ékologis]].\n\nPamungkas, ékologi ogé dipangaruhan (jeung nginjeumkeun ngaranna ka) disiplin non-biologis séjénna kayaning\n\n* [[ékologi software]] jeung [[ ékologi informasi]].\n* [[ékologi industri]].\n\n== Prinsip dasar ékologi ==\n\n===Biosfir jeung biodiversiti===\n\n\'\'Artikel utama:\'\' [[Biosfir]], [[Biodiversiti]], \'\'[[Unified neutral theory of biodiversity]]\'\'\n\nPikeun ahli ékologi modern, ékologi bisa diulik dina sababaraha tingkatan: tingkat [[populasi]] (individu nu saspésiés), tingkat \'\'[[biocenose]]\'\' (atawa kumpulan spésiés), tingkat [[ékosistem]], jeung tingkat [[biosfir]].\n\nBumi, tina jihat ékologis, diwangun ku sababaraha rohangan: [[hidrosfir]] (atawa lapisan cai), [[litosfir]] (atawa lapisan taneuh lan batu), jeung [[atmosfir bumi|atmosfir]] (atawa lapisan hawa). [[Biosfir]], sakapeung digambarkeun mangrupa lapisan kaopat, ngarupakeun bagian planét tempat hirup kumbuh. Ngarupakeun lapisan nu kacida ipisna, biosfir aya di antara 11000 méter ka jero jeung 15000 méter ka langit, najan kalolobaan kahirupan ayana di wewengkon antara -100 jeung +100 méter.\n\nKahirupan munggaran tumuwuh di hidrosfir, dina [[zona fotik]]. Organisme multisélular saterusna mucunghul turta ngeusi [[béntos|zona béntik]]. Kahirupan terestrial tumuwuh kadieunakeun, sanggeus ngawujudna [[lapisan ozon]] nu mayungan mahluk hirup tina cahya [[UV]]. Tumuwuhna rupa-rupa spésiés terestrial diduga ngaronjat alatan \'\'[[beulahna buana|beulahna]]\'\' atawa ngahijina buana. Biosfir jeung biodiversiti ngarupakeun ciri nu teu bisa dipisahkeun ti Bumi. Biosfir digambarkeun salaku lapisan kahirupan, sedengkeun [[biodiversiti]] salaku kabinékaanana. Lapisan salaku wadahna, sedengkeun kabinékaan salaku eusina. Kabinékaan ieu diéksprésikeun kalawan babarengan dina tingkat ékologis (ékosistem), tingkat populasi (kabinékaan intraspésifik), jeung tingkat spésiés (kabinékaan spésifik).\n\nBiosfir ngandung unsur nu jumlahna kalintang loba, kayaning [[karbon]], [[nitrogén]], jeung [[oksigén]]. Unsur séjénna, kayaning [[fosfor]], [[kalsium]], jeung [[kalium]], ogé penting pikeun [[kahirupan]]. Dina tingkat ékosistem jeung biosfir, aya prosés daur ulang sakabéh unsur-unsur ieu nu permanén, nu robah-robah antara wujud mineral jeung wujud organik.\n\nWhile there is a slight input of geothermal energy, the bulk of the functioning of the ecosystem is primarily based on the input of [[solar energy]]. Plants convert [[light]] into into chemical energy by the process of [[photosynthesis]], which creates [[glucose]] (a simple sugar) and releases free [[oxygen]]. Glucose thus becomes the secondary energy source which drives the ecosystem. Some of this glucose is used directly by other organisms for energy. Other sugar molecules can be converted to other molecules such as [[amino acid]]s. Plants use some of this sugar, concentrated in [[nectar]] to entice pollinators to aid them in reproduction. \'\'(Honeybees concentrate the sugar still further as honey, which can be said to be \"stored summer sunshine\"\'\').\n\n[[Cellular respiration]] is the process by which organisms (like [[mammal]]s) breakdown the glucose back to its constituents, [[cai]] jeung [[karbon dioksida]], gaining back the stored energy the sun originally gave to the plants. The proportion of photosynthetic activity of plants to the respiration of other organisms determines the specific composition of the Earth\'s atmosphere, particularly its oxygen level. [[airstream|Global air currents]] mix the atmosphere and maintain nearly the same balance in areas of intense biological activity and areas of slight biological activity.\n\nCai ogé disilihtukeurkeun antara hidrosfir, litosfir, atmosfir, jeung biosfir dina [[daur]] nu teratur. Sagara mangrupa téngki raksasa, nu ngawadahan cai, mastikeun stabilitas panas jeung cuaca, ogé pindahna unsur-unsur kimia ku ayana [[arus sagara]].\n\nFor better understanding of how the biosphere works, and the dysfunctions related to human activity, American scientists carried out, under [[greenhouse]]s, a small-scale model of the biosphere, called [[Biosphere II]].\n\n=== Konsép ngeunaan ékosistem ===\n\n\'\'Artikel utama:\'\' [[Ékosistem]]\n\nPrinsip utama ékologi nyéta unggal mahluk hirup mibanda hubungan nu lumangsung tur sinambung jeung unggal unsur séjén nu nyusun lingkunganna. Hiji [[ékosistem]] bisa didefinisikeun salaku kaayaan naon baé nu mibanda karakter interaksi antara organisme jeung lingkunganana.\n\nÉkosistem disusun ku dua éntitas: ayana kahirupan (disebut [[biocenose]]) jeung lahan/média pikeun hirup kumbuhna ([[biotope]]). Jeroeun ékosistem, spésiés-spésiés silih hubungkeun jeung silih gumantung hiji jeung nu séjénna dina [[ranté dahareun]], parobahan [[énérgi]], sarta parobahan [[matter]] antara maranéhna jeung lingkunganana.\n\nKonsép ngeunaan hiji ékosistem bisa dilarapkeun ka unit-unit nu ukuranana baréda, hiji [[balong]], hiji lapang, atawa sapotong tunggul kai. Unit nu ukuranana leutik disebut hiji \'\'[[mikroékosistem]]\'\'. Pikeun conto, hiji ékosistem basa mangrupa hiji batu jeung sagala kahirupan dihandapeunana. Hiji \'\'[[mésoékosistem]]\'\' bisa mangrupa hiji [[leuweung]], jeung hiji \'\'makroékosistem\'\' sakuliah \'\'[[ecoregion]]\'\', kaasup [[gawir]]na.\n\nPatalékan utama nalika ngulik hiji ékosistem di antarana,\n* how could be carried out the colonization of an arid area? \n* Kumaha dinamika jeung parobahan ékosistem?\n* Kumaha cara interaksi hiji ékosistem dina skala lokal, régional, jeung global?\n* Naha kaayaan kiwari téh stabil?\n* Naon ajén hiji ékosistem? Kumaha carana sangkan interaksi sistem ékologis bisa méré kauntungan pikeun manusa, utamana dina sasadiaan cai nu beresih/séhat?\n\nÉkosistem mindeng digolongkeun dumasar biotop nu patali. Ékosistem di handap ieu bisa dihartikeun: \n* salaku [[ékosistem kontinéntal]] (atawa terestrial), kayaning [[ékosistem leuweung]], [[ékosistem jukut]] (lapangan jukut, stépa, sabana), atawa [[agro-ékosistem]] (sistem agrikultural). \n* salaku ékosistem cai darat, kayaning \'\'[[lentic ecosystem]]\'\' (situ, balong) atawa \'\'[[lotic ecosystem]]\'\' (walungan) \n* salaku \'\'[[oceanic ecosystem]]\'\' (sagara, samudra).\n\nGolongan-golongan séjénna bisa dijieun dumasar komunitasna (misalna [[ékosistem manusa]]).\n\n===Dinamika jeung stabilitas===\n\n\'\'Artikel utama:\'\' [[faktor ékologis]], [[siklus géobiokimia]], [[homeostasis]], [[dinamika populasi]]\n\nBiotop ngarupakeun wewengkon nu lingkunganana saragam, ditunjukkeun ku sakabéh ukuran géologis, géografis, jeung klimatologis nu disebut [[abiotik|faktor ékologis abiotik]]:\n\n* [[cai]], ngarupakeun unsur nu ésénsial, boh pikeun kahirupan ogé lingkungan sabudeureunana ([[milieu]])\n* [[hawa]], nu nyadiakeun oksigén jeung karbon dioksida ka spésiés hirup, tur méré kasempetan pikeun sumebarna [[tipung sari]] jeung [[spora]]\n* [[taneuh]], nu sakaligus jadi sumber hara jeung ngarojong tumuwuhna\n* [[suhu]], nu samistina teu ngaleuwihan titik-titik ékstrim, najan pikeun sababaraha spésiés bisa nahan\n* [[cahya]], méré kasempetan ayana prosés [[fotosintésis]].\n\nBiosénosa, atawa komunitas, ngarupakeun kumpulan populasi tatangkalan, sato, jeung mikro-organisme. Tiap [[populasi]] ngarupakeun jumlah hasil kawin- baranahan individu-individu nu [[spésiés|saspésiés]] di hiji wewengkon dina hiji waktu. Nalika hiji populasi jumlah anggotana teu nyukupan, spésiésna kaancam punah, boh alatan \'\'underpopulation\'\' atawa alatan [[inbreeding|kawin saturunan]]. Hiji populasi bisa ngurangan ku sababaraha sabab, misalna, alatan leungit habitatna (karuksakan leuweung) atawa alatan loba teuing prédator (saperti diboro).\n\nBiosenosa dicirikeun ku dua tipe [[biotik|faktor ékologis biotik]]: hubungan intra- jeung inter-spésifik.\n\n[[Hubungan intraspésifik]] ngarupakeun hubungan nu dingawujud antarindividu nu saspésiés nu ngabentuk hiji populasi: mangrupa hubungan [[ko-operasi]] atawa [[kompetisi]], kalawan ayana babagi wewengkon kakawasaan, jeung kadang organisasi dina susunan hirarkis.\n\n[[Hubungan interspésifik]], nyéta hubungan nu aya antara spésis nu hiji jeung nu séjénna, loba pisan, jeung biasana digambarkeun nurutkeun pangaruh kauntungan, karugian, atawa nétral (misalna [[simbiosis]](hubungan ++) atawa [[kompetisi]] (hubungan --)). Hubungan nu pangsignifikanana mah nyéta hubungan [[prédator|prédasi]] (ngahakan atawa dihakan), nu ngajurung kana konsép dasar dina ékologi [[ranté dahareun]] (misalna, jukut dihakan ku hérbivora, nu dihakan ku karnivora, nu ogé dihakan ku karnivora nu leuwih badag). \'\'[[Ecological niche]]\'\' ngarupakeun wewengkon nu dipaké babarengan ku dua spésiés nu nempatan wewengkon sarta rupa [[diet (nutrisi)|diet]] nu sarua.\n\nThe existing interactions between the various living beings go along with a permanent mixing of mineral and organic substances, absorbed by organisms for their growth, their maintenance and their reproduction, to be finally rejected as waste. These permanent recyclings of the elements (in particular [[carbon]], [[oxygen]] and [[nitrogen]]) as well as the [[water]] are called [[biogeochemical cycle]]s. They guarantee a durable stability of the biosphere (at least when human influence and [[extreme weather]] phenomena are left aside). This self-regulation, supported by negative [[feedback]] controls, ensures the perenniality of the ecosystems. It is showed by the very stable concentrations of most elements of each compartment. This is referred to as [[homeostasis]]. The ecosystem also tends to evolve to a state of ideal balance, reached after a [[ecological succession|succession]] of events, the [[climax (biology)|climax]] (for example a pond can become a [[peat bog]]).\n\n===Spatial relationships and subdivisions of land===\n\n\'\'Main articles:\'\' [[Biome]], [[ecozone]]\n\nEcosystems are not isolated from each other, but are interrelated. For example, [[water]] may circulate between ecosystems by the means of a [[river]] or [[ocean current]]. Water itself, as a liquid medium, even defines ecosystems. Some species, such as [[salmon]] or freshwater [[eel]]s move between marine systems and fresh-water systems. These relationships between the ecosystems lead to the concept of a \'\'biome\'\'.\n\nA [[biome]] is a homogeneous ecological formation that exists over a vast region, such as [[tundra]] or [[steppe]]s. The [[biosphere]] comprises all of the Earth\'s biomes -- the entirety of places where life is possible -- from the highest mountains to the depths of the oceans.\n\nBiomes correspond rather well to subdivisions distributed along the latitudes, from the [[equator]] towards the [[pole]]s, with differences based on to the physical environment (for example, oceans or mountain ranges) and to the [[climate]]. Their variation is generally related to the distribution of species according to their ability to tolerate temperature and/or dryness. For example, one may find [[photosynthesis|photosynthetic]] [[algae]] only in the \'\'photic\'\' part of the ocean (where light penetrates), while [[conifer]]s are mostly found in mountains.\n\nThough this is a simplification of more complicated scheme, [[latitude]] and [[altitude]] approximate a good representation of the distribution of [[biodiversity]] within the biosphere. Very generally, the richness of biodiversity (as well for animal than plant species) is decreasing most rapidly near the [[equator]] (as in [[Brazil]]) and less rapidly as one approaches the [[pole]]s.\n\nThe biosphere may also be divided into [[ecozone]], which are very well defined today and primarily follow the continental borders. The ecozones are themselves divided into [[ecoregions]], though there is not agreement on their limits.\n\n===Produktivitas ékosistem===\n\nDina hiji ékosistem, patali antarspésiés sacara umum dihubungkeun kana [[dahareun]] jeung peranna dina [[ranté dahareun]]. Aya tilu kategori organisme: \n\n* \'\'produsén\'\' -- tutuwuhan nu bisa [[fotosintésis]]\n* \'\'konsumén\'\' -- sato, nu bisa mangrupa konsumén primér ([[herbivora]]), atawa sékundér atawa térsiér ([[karnivora]]). \n* \'\'pengurai\'\' -- [[bakteri]], [[suung]] nu nguraikeun zat-zat organik ti sakabéh kategori sarta mulangkeun mineral ka lingkungan.\n\nHubungan-hubungan ieu ngawujud urutan, dimana unggal individu ngahakan nu saméméhna sarta dihakan ku nu saanggeusna, dina nu disebut [[ranté dahareun]] atawa [[jaringan dahareun. In a food network, there will be fewer organisms at each level as one follows the links of the network up the chain.\n\nThese concepts lead to the idea of [[biomass]] (the total living matter in a given place), of [[primary productivity]] (the increase in the mass of plants during a given time) and of [[secondary productivity]] (the living matter produced by consumers and the decomposers in a given time).\n\nThese two last ideas are key, since they make it possible to evaluate the [[load capacity]] -- the number of organisms which can be supported by a given ecosystem. In any food network, the energy contained in the level of the producers is not completely transferred to the consumers. Thus, from an energy point of view, it is more efficient for humans to be primary consumers (to get nourishment from grains and vegetables) than as secondary consumers (from herbivores such as beef and veal), and more still than as a tertiary consumer (from eating carnivores).\n\nThe productivity of ecosystems is sometimes estimated by comparing three types of land-based ecosystems and the total of aquatic ecosystems: \n* the forests (1/3 of the Earth\'s land area) contain dense biomasses and are very productive. The total production of the world\'s forests corresponds to half of the primary production. \n* savannas, meadows, and marshes (1/3 of the Earth\'s land area) contain less dense biomasses, but are productive. These ecosystems represent the major part of what humans depend on for food. \n* extreme ecosystems in the areas with more extreme climates -- deserts and semi-deserts, tundra, alpine meadows, and steppes -- (1/3 of the Earth\'s surface) have very sparse biomasses and low productivity \n* finally, the marine and fresh water ecosystems (3/4 of Earth\'s surface) contain very sparse biomasses (apart from the coastal zones).\n\nHumanity\'s actions over the last few centuries have seriously reduced the amount of the Earth covered by forests ([[deforestation]]), and have increased agro-ecosystems ([[agriculture]]). In recent decades, an increase in the areas occupied by extreme ecosystems has occurred ([[desertification]]).\n\n===Krisis ékologis===\n\nSacara umum, [[krisis ékologis]] nyéta naon rupa kajadian nu ngarobah [[lingkungan]] hirup hiji spésiés atawa populasi sahingga ngabahyakeun kasalametanana.\n\nIeu bisa mangrupa kualitas lingkungan nu nurun dibandingkeun jeung pangabutuh spésiés alatan parobahan [[faktor ékologis]] abiotik (pikeun conto, naékna suhu, hujan nu beuki jarang).
\nIt may be that the environment becomes unfavourable for the survival of a species (or a population) due to an increase pressure of [[predation]] (for example overfishing).
\nLastly, it may be that the situation becomes unfavourable to the quality of life of the species (or the population) due to raise in the number of individuals ([[overpopulation]]).\n\nEcological crises may be more or less brutal (occurring between a few months to a few million years). They can also be of natural or anthropic origin. They may relate to one unique species or on the contrary, to a high number of species (see the article on [[Extinction event]]).\n\nLastly, an ecological crisis may be local (as an [[oil spill]]) or global (a rise in the sea level related to [[global warming]]).\n\nAccording to its degree of endemism, a local crisis will have more or less significant consequences, from the death of many individuals to the total extinction of a species. Whatever its origin, disappearance of one or several species often will involve a rupture in the [[food chain]], further impacting the survival of other species.\n\nIn the case of a global crisis, the consequences can be much more significant; some extinction events showed the disappearance of more than 90% of existing species at that time. However, it should be noted that the disappearance of certain species, such as the dinosaurs, by freeing an ecological niche, allowed the development and the diversification of the mammals. An ecological crisis thus paradoxically favored biodiversity.\n\nSometimes, an ecological crisis can be a specific and reversible phenomenon at the ecosystem scale. But more generally, the crises impact will last. Indeed, it rather is a connected series of events, that occur till a final point. From this stage, no return to the previous stable state is possible, and a new stable state will be set up gradually (see [[homeorhesy]]).\n\nLastly, if an ecological crisis can cause extinction, it can also more simply reduce the quality of life of the remaining individuals. Thus, even if the diversity of the human population is sometimes considered threatened (see in particular [[indigenous people]]), few people envision human disappearance at short span. However, [[epidemic disease]]s, [[famine]]s, impact on health of reduction of [[air quality]], [[food crise]]s, reduction of living space, accumulation of toxic or non degradable wastes, threats on [[keystone species]] (great apes, panda, whales) are also factors influencing the [[well-being]] of people.\n\nDuring the past decades, it was observed an increasing responsibility of human in some ecological crises. Due to his technological acquisitions and to a strong increase in population, man is the only species whose activity has a major influence on his environment of life.\n\nSome usually quoted examples as ecological crises are\n*[[Permian-Triassic extinction event]] 250 million of years ago \n*[[Cretaceous-Tertiary extinction event]] 65 million years ago \n*[[global warming]] related to the [[greenhouse effect]]. Warming could involve flooding of the Asian deltas (see also [[ecorefugee]]s), multiplication of [[extreme weather]] phenomena and changes in the nature and quantity of the food resources (see [[Global warming and agriculture]])\n*[[Ozone layer]] hole issue\n*[[Deforestation]] and [[desertification]], with disappearance of many species.\n* The [[nuclear reactor|nuclear]] meltdown at [[Chernobyl]] in [[1986]] caused the death of many people and animals from [[cancer]], and caused mutations in a large number of animals and people. The area around the plant is now abandoned because of the large amount of radiation generated by the meltdown.\n\n== Sajarah ékologi ==\n\nSalasahiji [[ahli ékologi]] munggaran jigana mah [[Aristotle]] nu boga pangaresep kana rupa-rupa spésiés sato. Anjeunna dituturkeun ku loba naturalis kayaning [[Buffon]] jeung [[Carolus Linnaeus]], nu damelanana sok dianggap salaku asal-usul ékologi modern.\n\n===Géografi botanis jeung Alexander von Humboldt===\nSalila abad ka-18 nepi ka munggaran abad ka-19, kakuatan maritim raya kayaning Prancis jeung Jérman, medalkeun loba ékspédisi éksplorasi dunya pikeun ngembangkeun [[hubungan dagang maritim]] jeung nagara-nagara séjén, sarta pikeun manggihan sumberdaya alam anyar, as well as to catalog them. At the beginning of the [[18th century]], about twenty thousand plant species were known, versus forty thousand at the beginning of the [[19th century]], and almost 400,000 today.\n\nThese expeditions were joined by many scientists, including [[botany|botanists]], such as the German explorer [[Alexander von Humboldt]]. Humboldt is often considered the true father of ecology. He was the first to take on the study of the relationship between organisms and their [[environment]]. He exposed the existing relationships between observed plant species and [[climate]], and described vegetation zones using [[latitude]] and [[altitude]], a discipline now known as [[geobotany]].\n\nIn [[1804]], for example, he reported an impressive number of species, particularly plants, for which he sought to explain their geographic distribution with respect to [[geological]] data. One of Humboldt\'s famous works was \"Idea for a Plant Geography\" ([[1805]]).\n\nOther important botanists include [[Aimé Bonpland]] and [[Eugenius Warming]].\n\n=== Pamanggih ngeunaan \'\'biocenose\'\': Charles Darwin jeung Alfred Wallace ===\nDeukeut ka taun [[1850]] aya nu narabas dina widang ieu ku medalna karya [[Charles Darwin]] \'\'[[The Origin of Species]]\'\': Ecology passed from a repetitive, mechanical model to a biological, organic, and hence [[evolution|evolutionary]] model.\n\n[[Alfred Russel Wallace]], nu leuwih heubeul sarta saingan Darwin, munggaran ngajukeun \"géografi\" spésiés sasatoan. Sababaraha ahli harita wanoh yén spésiés teu mandiri ti nu séjén, sarta digolongkeun kana spésiés tangkal, sato, sarta komunitas mahluk hirup atawa [[biocenose]]. Istilah ieu munggaran dikedalkeun taun [[1877]] ku [[Karl Möbius]].\n\n=== Biosfir - Eduard Suess jeung Vladimir Vernadsky ===\nDina abad ka-19, ékologi ngembang ku ayana papanggihan widang [[kimia]] ku [[Lavoisier]] jeung [[de Saussure]], utamana ngeunaan [[daur nitrogén]]. Sanggeus nengetan bukti yén kahirupan tumuwuhna ukur dina wates-wates rohangan nu ngawujud [[atmosfir Bumi|atmosfir]], [[hidrosfir]], jeung [[litosfir]], Ahli géologi Austria [[Eduard Suess]] ngajukeun istilah [[biosfir]] taun [[1875]]. Suess ngajukeun ngaran biosfir pikeun kaayaan nu ngadukung kahirupan, kayaning nu kapanggih di [[Bumi]], nyaéta [[flora]], [[fauna]], [[mineral]], [[daur zat]], jeung sajabana.\n\nDina taun [[1920]]an [[Vladimir I. Vernadsky]], ahli géologi Rusia nu pindah ka Prancis, ngajéntrékeun pamanggih ngeunaan biosfir dina karyana \"The biosphere\" ([[1926]]), sarta ngagambarkeun prinsip-prinsip pondamén [[daur biogéokimiawi]]. Mangka anjeunna ngartikeun ulang biosfir salaku jumlah sakabéh [[ékosistem]].\n\nKaruksakan ékologis munggaran kabéjakeun dina [[abad ka-18]], ku baranahanana koloni-koloni nu ngakibatkeun [[déforestasi]]. Mimiti [[abad ka-19]], ku ayana [[révolusi industri]], kamelang kana karuksakan [[lingkungan]] alatan kagiatan manusa beuki ningkat. Istilah \'\'[[ahli géologi|ecologist]]\'\' geus dipaké ti panungtungan [[abad ka-19]].\n\n===Ékosistem: Arthur Tansley===\nSapanjang [[abad ka-19]], géografi botanis jeung zoogéografi ngagabung jadi basis [[biogéografi]]. Élmu ieu, nu ngurus habitat spésiés, nyiar jawaban pikeun ayana spésiés tinangtu di wewengkon nu tinangtu ogé.\n\nDina taun [[1935]], [[Arthur Tansley]], [[ahli ékologi]] Inggris, nyiptakeun istilah [[ékosistem]], nyaéta sistem interaktif nu ngawujud antara \'\'[[biocenose]]\'\' (kumpulan mahluk hirup) jeung [[biotop]]na, lingkungan tempat maranéhna hirup. Mangka ékologi jadi élmu ngeunaan ékosistem.\n\n===Ékoogi manusa===\n[[Ékologi manusa]] dimimitian dina taun [[1920an]], ku ayana ulikan ngeunaan parobahan [[suksési vegetasi]] di kota [[Chicago]]. Saterusna jadi widang ulikan nu béda dina taun [[1970an]]. Ieu nyirikeun munggaran diakuna manusa, nu geus ngeusi satungtung [[buana]] dunya, salaku hiji [[faktor ékologis]] penting. Manusa kalawan gedé-gedéan ngarobah lingkungan ku ngawangun habitat (utamana [[tata kota]]) ku kagiatan éksploitasi nu leket saperti \'\'[[logging]]\'\' jeung \'\'[[fishing]]\'\', sarta pangaruh séjén [[agrikultur]], [[pertambangan]], jeung [[industri]]. Di sagigireun ékologi jeung biologi, disiplin ieu ngawengku ogé élmu alam jeung sosial séjénna, kayaning [[antropologi]] jeung [[étnologi]], [[ékonomi]], [[démografi]], [[arsitéktur]] jeung [[tata kota]], [[tatamba]] jeung [[psikologi]], sarta nu séjénna. Ngembangna ékologi manusa ngajurung kana ngaronjatna peran élmu ékologis dina rarancang jeung ngokolaan [[dayeuh]].\n\n===James Lovelock jeung hipotésis Gaia===\n[[Téori Gaia (élmu)|Téori Gaia]], nu diajukeun ku [[James Lovelock]] dina karyana \'\'The Earth is Alive\'\', geus ngalegaan sawangan yén Bumi kudu dihargaan salaku hiji makroorganisme tunggal nu hirup. Hususna dina pamadegan yén \'\'ensemble\'\' sadaya organisme hirup geus ngalaman évolusi sahingga mampuh ngatur lingkungan global — ku jalan mangaruhan paraméter fisik penting kayaning wangunan atmosfir, laju penguapan, kimia taneuh jeung sagara — nepi ka bisa mertahankeun kaayaan nu dipiharep pikeun mahluk hirup.\n\nSawangan ieu geus jadi totondén jaman harita, hususna persépsi nu beuki kuat satutasna [[Perang Dunya kadua]] yén kagiatan manusa kayaning [[énergi nuklir]], [[industrialisasi]], [[polusi]], jeung éksplorasi [[sumberdaya alami]] nu kaleuleuwihi, katambah ku [[pertumbuhan populasi éksponénsial]], geus ngancam kaciptakeunana [[katastrop]] dina skala planet. Ku ayana kitu, majan kontoversial di kalangan élmuwan, hipotésis Gaia Lovelock geus dirontok ku loba [[pergerakan lingkungan]] salaku hiji sawangan nu ngagagas: \'\'indung-Bumi\'\'na, [[Gaia]], \"jadi gering alatan manusa jeung kagiatanana\".\n\n===Konservasi jeung pergerakan lingkungan===\nBener, ti abad ka-19 ékologi geus kalawan nyata relevan pikeun [[pergerakan lingkungan|pergerakan sosial jeung filosofis]] nu patali jeung perlindungan [[lingkungan alami]], kayaning [[konservasionism]] jeung [[environmentalism]]. Ékologi kiwari geus jadi salasahiji [[ékologi politis|jejer politis]] penting sarta sumber [[ideologi]] pikeun organisasi-organisasi politis penting samodél [[Partéy Héjo]] jeung [[Greenpeace]].\n\n===Ékologi jeung kawijakan global===\nÉkologi geus jadi bagéan puseur dina politik Dunya ti taun [[1971]], [[UNESCO]] medalkeun program panalungtikan nu disebut \'\'[[Man and Biosphere]]\'\', nu tujuanana pikeun ngaronjatkeun pangaweruh ngeunaan hubungan nu silih untungkeun antara manusa jeung alam. Sababaraha taun ti harita geus kaluar katangtuan ngeunaan konsép \'\'[[Biosphere Reserve]]\'\'.\n\nTaun [[1972]] [[United Nations]] (Perserikatan Bangsa-bangsa, PBB) ngayakeun konferensi internasional lingjkungan manusa nu munggaran di [[Stockholm]], diluluguan ku [[René Dubos]] jeung sababaraha ahli séjénna. Konferensi ieu pisan nu marajian frase \"Mikir Global, Ketak Lokal\" (\'\'Think Globally, Act Locally)\'\'. The next major events in ecology were the development of the concept of biosphere and the appearance of terms \"biological diversity\" -- or now more commonly [[biodiversity]] -- in the [[1980s]]. These terms were developed during the [[Earth Summit]] in [[Rio de Janeiro]] in [[1992]], where the concept of the biosphere was recognized by the major international organizations, and risks associated with reductions in biodiversity were publicly acknowledged.\n\nThen, in [[1997]], the dangers the biosphere was facing were recognized from an international point of view at the [[Kyoto conference]]. In particular, this conference highlighted the increasing dangers of the [[greenhouse effect]] -- related to the increasing concentration of [[greenhouse gases]] in the atmosphere, leading to [[Climate change|global changes in climate]]. In [[Kyoto]], most of the world\'s nations recognized the importance of looking at ecology from a global point of view, on a worldwide scale, and to take into account the impact of humans on the Earth\'s environment.\n\n==Tempo ogé==\n*[[ELDIS]], \'\'database\'\' aspék ékologis pengembangan ékonomis. \n*[[Daptar jejer ékologi]]\n*[[Daptar jejer lingkungan]]\n*[[Daptar jejer biologi]]\n*[[List of planned cities]]\n\n{{msg:Biology-footer}}\n\n[[ms:Ekologi]] [[ca:Ecologia]] [[cy:Ecoleg]] [[da:Økologi]] [[de:Ökologie]] [[en:Ecology]] [[es:Ecología]] [[eo:Ekologio]] [[fr:Écologie]] [[ia:Ecologia]] [[lt:Ekologija]] [[hu:Ökológia]] [[nl:Ecologie]] [[ja:生態学]] [[pl:Ekologia]] [[ro:Ecologie]] [[simple:Ecology]] [[tr:Ekoloji]] [[bg:Екология]]','kategori ekologi',20,'DiN','20050303195055','',0,0,0,0,0.037638939003,'20050303195055','79949696804944'); INSERT INTO cur VALUES (808,0,'Biologi','\'\'\'Biologi\'\'\' ngarupakeun [[élmu]] [[mahluk hirup]]. Ulikanana museur dina ciri jeung [[paripolah]] [[organisme]], cara tumuwuhna [[spésiés]] jeung individu, sarta interaksi hiji jeung nu séjénna tur [[lingkungan]]ana.\n\n==Ihtisar ngeunaan biologi==\nBiologi boga ambahan nu lega na lapang akademik nu mindeng diteuteup salaku hiji disiplin nu mandiri. Kalawan babarengan, aranjeunna ngulik kahirupan nu aya dina [[Orders of magnitude (length)|skala]] nu lega:\n\n* na skala atomik jeung molekular, [[biologi molekular]], [[biokimia]], jeung [[genetics]]\n* na skala sélular, [[biologi sél]] \n* na skala multisélular, [[fisiologi]], [[anatomi]], jeung [[histologi]]\n* na tingkat tumuwuhna atawa [[ontogeni]] organisme individual, [[developmental biology]]\n* na tingkat tumurunna kolot ka anak, [[genetik]]\n* na tingkat paripolah kumpulan, [[ethology]]\n* na tingkat sakabéh [[populasi]], [[genetik populasi]] \n* na skala multi-spésiés [[lineage]], [[sistematik]] \n* na tingkat silih gumantung antara populasi jeung habitatna dina [[ékologi]] sarta [[évolusi|biologi évolusionér]]\n* sarta, sacara spékulatif, \'\'[[xenobiology]]\'\' dina tingkat kahirupan saluareun Bumi. \n\n\n\n
\n\n===Widang ulikan na biologi=== \n[[Aérobiologi]] -- [[Anatomi]] -- [[Arachnology]]-- [[Astrobiologi]] -- [[Biokimia]] -- [[Bionik]] -- [[Biogéografi]] -- [[Bioinformatik]] -- [[Biomékanik]] -- [[Biofisik]]-- [[Biotéknologi]] -- [[Botani]] -- [[Biologi sél]] -- [[Chorology]] -- [[Kladistik]] -- [[Crustaceology]] -- [[Cryptozoology]] -- [[Siklus]] -- [[Sitologi]] -- [[Developmental biology]] -- [[Panyakit]] ([[Panyakit genetik]], [[Panyakit inféksi]]) -- [[Ékologi]] ([[Ékologi téoritis]], [[simbiosis|Simbiologi]], [[Autecology]], [[Synecology]]) -- [[Ethology]] -- [[Entomologi]] -- [[Biologi évolusi]] ([[Évolusi]]) -- [[Evolutionary developmental biology]] -- [[Freshwater biology]] -- [[Genetik]] ([[Genetik populasi]], [[Genetik kuantitatif]], [[Genomik]], [[Protéomik]]) -- [[Hérpetologi]] -- [[Histologi]] -- [[Biologi manusa]] ([[Antropologi]]) -- [[Ichthyology]] -- [[Imunologi]] -- [[Patologi]] -- [[Épidemiologi]] -- [[Limnologi]] -- [[Malacologi]] -- [[Mammalogi]] -- [[Biologi laut]] -- [[Mikrobiologi]] ([[Bakteriologi]]) -- [[Biologi molekular]] -- [[Morfologi]] -- [[Mikologi]] / [[Lichenology]] --- [[Myrmecology]] --- [[Élmu saraf]] ([[Neuroanatomi]], [[Neurofisiologi]], [[Élmu saraf sistem]], [[Psikologi biologis]], [[Psikiatri]], [[Psikofarmakologi]], [[Behavioral science]], [[Neuroethology]], [[Psikofisik]], [[Élmu saraf komputasional]], [[Élmu saraf kognitif]], [[Élmu kognitif]])-- [[Onkologi]] (ulikan ngeunaan kangker) -- [[Ontogeni]] -- [[Asal-usul manusa]] -- [[Ornitologi]] -- [[Paléontologi]] ([[Paléobotani]], [[Paléozoologi]])-- [[Parasitologi]] -- [[Fikologi]] (Algologi) -- [[Filogeni]] ([[Filogenetik]], [[Filogéografi]]) -- [[Fisiologi]] -- [[Fitopatologi]] -- [[Biologi struktural]] -- [[Taksonomi]] -- [[Toksikologi]] (ulikan ngeunaan racun jeung [[polusi]]) -- [[Virologi]] -- [[Xénobiologi]] -- [[Zoologi]]\n\n===Disiplin nu pakait===\n[[Tatamba]] -- [[Antropologi fisik]]\n\n===Jalma jeung sajarah===\n[[Daptar biolog|Inohong widang biologi]] -- [[Sajarah biologi]] -- [[Hadiah Nobel/Fisiologi atawa tatamba|Hadiah Nobel widang fisiologi atawa tatamba]] -- [[Timeline of biology and organic chemistry]]\n\n===Daptar jejer===\nTempo: [[Daptar jejer biologi]]\n\n\'\'Naon prioritas urang nulis di dieu? Pikeun mantuan ngembangkeun daptar jejer-jejer nu pangdasarna dina widang biolodi, mangga tempo [[Wikipedia:biology basic topics]].\'\'\n
\n\n== Évolusi jeung biologi ==\nSalasahiji konsép puseur jeung pangatur dina biologi nandeskeun yén sadaya nu hirup diturunkeun ti hiji \'\'[[common origin]]\'\' ngaliwatan prosés [[évolusi]]. [[Charles Darwin]] nerangkeun konsép téoritis évolusi nu masih kénéh jadi puseur nepi ka kiwari, ku jalan ngajukeun [[seléksi alam]] pikeun mékanismena. Salajengna \'\'[[genetic drift]]\'\' dirangkul salaku mékanisme tambahan dina nu disebut [[sintésis modern]]. Sajarah évolusionér hiji [[spésies]]— nu ngécéskeun karakteristik rupa-rupa spésiés asal-usulna—sarta kakaitan genéalogis jeung spésiés séjénna disebut [[filogeni]]. Rupa-rupa \'\'pendekatan\'\' dina biologi ngahasilkeun informasi ngeunaan filogeni. Salasahijina nyéta ku ngabandingkeun [[urutan DNA]] nu diulik dina [[biologi molekular]] atawa [[genomik]] jeung ngabandingkeun [[fosil]] atawa rekaman séjénna ngeunaan organisme kuna dina [[paléontologi]]. Para ahli biologi ngatur jeung nganalisis hubungan évolusionér ngaliwatan rupa-rupa métode, di antarana [[filogenetik]], [[fenetik]], sarta [[kladistik]]. Kajadian-kajadian utama dina évolusi mahluk hirup, sakumaha nu ayeuna diagem ku maranéhna, diringkeskeun dina \'\'[[evolutionary timeline]]\'\'.\n\n== Klasifikasi mahluk hirup ==\nKlasifikasi mahluk hirup disebutna [[sistematika]] atawa [[taksonomi]], nu kudu ngeunteung kana tangkal évolusi ([[tangkal filogenetik]]) organisme-organisme nu baréda. Taksonomi ngumpulkeun organisme-organisme dina kumpulan nu disebut [[taksa]], sedengkeun sistematika nyiar patali-patalina. Sistem nu dominan disebut [[taksonomi Linnaean]], nu ngawengku urutan jeung [[tatangaran binomial]]. Kumaha hiji organisme dibéré ngaran diatur ku kasapukan internasional saperti [[International Code of Botanical Nomenclature]] (ICBN), [[International Code of Zoological Nomenclature]] (ICZN), jeung [[International Code of Nomenclature of Bacteria]] (ICNB). Draf kaopat BioCode geus medal taun 1997 dina usaha ngabakukeun tatangaran na tangkalna, ngan rupana can sacara formal diadopsi. [[International Code of Virus Classification and Nomenclature]] (ICVCN) tetep aya di luareun BioCode.\n\nSacara tradisional, mahluk hirup dibagi kana lima karajaan:\n\n:[[Monéra]] -- [[Protista]] -- [[Fungi]] -- [[Plantae]] -- [[Animalia]]\n\nNgan, sistem lima-karajaan ieu kiwari geus loba dianggap tinggaleun jaman. Pilihan séjén nu leuwih modern sacara umum dimimitian ku [[sistem tilu-wewengkon]]:\n\n:[[Archaea]] (tadina Archaebacteria) -- [[Bacteria]] (tadina Eubacteria) -- [[Eukaryota]]\n\nWewengkon ieu ngagambarkeun aya henteuna inti tur béda ékstérior sélna.\n\nAya ogé saréngréngan [[parasit]] intrasélular nu \"teu hirup\" dina harti aktivitas [[métabolisme|métabolismena]]:\n\n:[[virus (biologi)|Virus]] -- [[Viroid]] -- [[Prion]]\n\n== Sajarah kecap \"biologi\" ==\nDiwangun ku ngagabungkeun kecap Yunani βίος \'\'(bios)\'\', nu hartina \'hirup\', jeung λόγος \'\'(logos)\'\', nu hartina \'kecap\', kecap \"biologi\" dina harti modern jigana mimiti diwanohkeun sacara séwang-séwangan ku [[Gottfried Reinhold Treviranus]] (\'\'Biologie oder Philosophie der lebenden Natur\'\', [[1802]]) jeung ku [[Jean-Baptiste Lamarck]] (\'\'Hydrogéologie\'\', 1802). Kecap ieu kadang kasebutkeun cenah diciptakeun taun [[1800]] ku [[Karl Friedrich Burdach]], tapi ogé kapanggih na judul [[Michael Christoph Hanov]] Volume 3 \'\'Philosophiae naturalis sive physicae dogmaticae\'\': \'\'Geologia, biologia, phytologia generalis et dendrologia\'\', nu medal taun [[1766]].\n\n==Tempo ogé== \n* [[Eukariot]]\n* [[Asal-usul hirup]]\n* [[Morfologi]]\n* [[Lingkungan]]\n* [[Ékosistem]]\n* [[Ahli biologi]]\n* [[Dokter]]\n* [[NASA Ames Research Center]]\n* [[Bachelor of Science]]\n* [[Daptar téknologi]]\n* [[Masalah nu teu kaungkab dina biologi]]\n* [[Daptar jejer ngeunaan konservasi]]\n\n==Tumbu kaluar jeung sumber séjén==\n===Tumbu===\n*\'\'[[wikibooks:General Biology|Bukutéks Biologi Umum Wiki]]\'\', [[wikibooks:Biology|buku biologi]], jeung situs [[wikibooks:Main Page|Bukuwiki]].\n* \'\'Kaca Biologi Kimball\'\', http://users.rcn.com/jkimball.ma.ultranet/BiologyPages : Buku téks online.\n* \'\'Tangkal Kahirupan\'\', http://tolweb.org/tree/phylogeny.html : A multi-authored, distributed Internet project containing information about phylogeny and biodiversity.\n* \'\'The Journal of Biology\'\', http://www.jbiol.com : Jurnal panalungtikan, leutik tapi gratis.\n* \'\'The Public Library of Science: Biology\'\', http://www.plosbiology.org : Jurnal panalungtikan nu leuwih anyar, tapi ogé leuwih ambisius.\n* \'\'BioCode\'\', http://www.rom.on.ca/biodiversity/biocode/biocode1997.html : Proposal pikeun tata ngaran organisme.\n* [http://www.ohiou.edu/phylocode/index.html PhyloCode]\n\n===Bacaeun===\n* Lynn Margulis, \'\'Five Kingdoms: An Illustrated Guide to the Phyla of Life on Earth,\'\' 3rd ed., St. Martin\'s Press, [[1997]], paperback, ISBN 0805072527 (many other editions)\n* Neil Campbell, \'\'Biology: Concepts & Connections (4th edition)\'\', Benjamin-Cummings Publishing Company, [[2002]], hardcover, ISBN 080536627X (college-level text)\n\n[[Category:Biologi]]\n\n[[af:Biologie]]\n[[als:Biologie]]\n[[ast:Bioloxía]]\n[[bg:Биология]]\n[[bs:Biologija]]\n[[ca:Biologia]]\n[[co:Biulugia]]\n[[cs:Biologie]]\n[[cy:Bioleg]]\n[[da:Biologi]]\n[[de:Biologie]]\n[[el:Βιολογία]]\n[[en:Biology]]\n[[eo:Biologio]]\n[[es:Biología]]\n[[et:Bioloogia]]\n[[fa:زیست‌شناسی]]\n[[fi:Biologia]]\n[[fo:Lívfrøði]]\n[[fr:Biologie]]\n[[fy:Biology]]\n[[gd:Bith-Eòlas]]\n[[gl:Bioloxía]]\n[[he:ביולוגיה]]\n[[hr:Biologija]]\n[[hu:Biológia]]\n[[ia:Biologia]]\n[[id:Biologi]]\n[[ie:Biologie]]\n[[io:Biologio]]\n[[it:Biologia]]\n[[ja:生物学]]\n[[jbo:Mivyske]]\n[[ko:생물학]]\n[[la:Biologica]]\n[[lb:Biologie]]\n[[lt:Biologija]]\n[[ms:Biologi]]\n[[nah:Yolizmatiliztli]]\n[[nds:Biologie]]\n[[nl:Biologie]]\n[[no:Biologi]]\n[[oc:Biologia]]\n[[pl:Biologia]]\n[[pt:Biologia]]\n[[ro:Biologie]]\n[[ru:Биология]]\n[[scn:Bioluggia]]\n[[simple:Biology]]\n[[sl:Biologija]]\n[[sr:Биологија]]\n[[sv:Biologi]]\n[[sw:Biolojia]]\n[[th:ชีววิทยา]]\n[[tl:Biyolohiya]]\n[[tr:Biyoloji]]\n[[tt:Biologí]]\n[[uk:Біологія]]\n[[vi:Sinh vật học]]\n[[vo:Lifav]]\n[[zh:生物学]]','HasharBot - warnfile Adding:zh,th,lt,lb,tt,co,vi,jbo,ast,ie,bg,als,fa,scn Modifying:zh-cn,simple,zh-tw,nah',0,'81.220.107.14','20041110061401','',0,0,0,0,0.803566710932,'20050117082707','79958889938598'); INSERT INTO cur VALUES (809,0,'Alam','[[Image:Nature1.png|right|Nature]]\n\n\'\'\'Alam\'\'\' ngarupakeun [[dunya material|dunya alami]], utamana dina wujud asli/dasarna, leupas tina pangaruh manusa.\n\n== Dunya alami ==\n\nNurutkeun [[skala]] mah, \'alam\' téh ngawengku sagala rupa, ti ukuran [[mayapada]] nepi ka ukuran [[partikel subatomik|subatomik]], kaasup sagala rupa [[sato]], tangkal, jeung [[mineral]]; sagala [[pakaya alam]] jeung kajadian-kajadianana ([[hurricane]], [[tornado]], sarta [[lini]]). Ogé kaasup [[paripolah]] sasatoan hirup, jeung prosés-prosés nu patali jeung [[objék]]-objék nu teu nyawaan.\nAya jihat pangbéda nu fundaméntal antara nu ngajeujeut manusa (boh kasadaran jeung kagiatanana) jeung nu henteu.\n\n== Métafisik ==\n\nDina [[filosofi]], sawangan yén dunya materil sarupaning atom, sasatoan, graviti, béntang, angin, mikroba, jsb. sabenerna aya sacara mandiri, leupas tina pangaruh urang, disebutna [[réalisme]]; sabalikna ti [[idéalisme]].\n\n== Nu alami jeung nu artifisial ==\n\n\"Alami\" jeung \"artifisial\" (=\"jieunan manusa\") mindengna mah dibédakeun. Bisa teu éta pangbéda dibuktikeun? Salasahiji \'\'pendekatan\'\' nyaéta ku ngiwalkeun [[pikiran]] tina widang alami; cara séjén nyaéta ku ngiwalkeun lain ukur pikiran, tapi ogé [[manusa]] jeung pangaruhna. Dina dua kasus éta, wates antara alami jeung [[artifisial]] hésé pisan diguratkeunana (tempo [[mind-body problem]]). Sababaraha urang percaya yén masalah ieu paling hadé disingkahan ku nyebutkeun yén sagalana alami, tapi éta teu bisa loba ngécéskeun konsép \"artifisial\". In any event, [[ambiguity|ambiguities]] about the [[distinct]]ion between the natural and the artificial animate much of [[art]], [[literature]] and [[philosophy]].\n\n== Konsép nu pakait ==\n\nIstilah [[élmu alam]] dipaké dina rupa-rupa jalan, utamana\n* pikeun nandakeun ulikan ngeunaan prosés-prosés alami nu bébas tina pangaruh kagiatan manusa, béda jeung [[élmu sosial]]; jeung\n* pikeun nandakeun [[élmu]]-élmu nu maké [[métode ilmiah]], béda jeung, misalna, [[matematik]] jeung [[élmu komputer]].\n\nIstilah [[filosofi alami]] asalna dipaké pikeun disiplin ilmiah nu ayeuna disebut [[fisika]].\n\n[[Téologi alami]] ngajégang antara disiplin [[téologi]] jeung [[filosofi ageman]]. \n\nDina widang [[atikan]] jeung nu patalina, kontras \"alami/artifisial\" bisa katémbong salaku \"[[nature versus nurture|nature/nurture]]\".\n\nTempo ogé: [[praeternatural]], [[unnatural]], jeung [[supernatural]].\n\n==Tempo ogé==\n\n*[[biofili]]\n*[[Sobat alam]]\n*[[Wilangan alami]] (wilangan Planck)\n\n[[Category:Alam]]\n\n[[da:Natur]] [[de:Natur]] [[en:Nature]] [[eo:Naturo]] [[fi:Luonto]] [[fr:Nature]] [[nl:Natuur]] [[simple:Nature]] [[ru:Природа]] [[zh:自然]]','',3,'Kandar','20041222041348','',0,0,0,0,0.14099594771,'20041225124916','79958777958651'); INSERT INTO cur VALUES (810,0,'Géografi','\'\'\'Géografi\'\'\' ngarupakeun ulikan ngeunaan lokasi jeung variasi spatial boh dina fénoména fisik atawa manusana di [[Bumi]]. Kecap ieu diturunkeun tina kecap [[Basa Yunani]] \'\'gê\'\' (\"Bumi\") jeung \'\'graphein\'\' (\"nulis\" atawa \"ngagambakeun\").\n\n\'\'Géografi\'\' ogé mangrupa judul rupa-rupa buku sajarah dina subjék ieu, di antarana \'\'Geographia\'\' kénging [[Ptolemy|Klaudios Ptolemaios]] ([[abad ka-2]]).\n\nGéografi leuwih lega batan [[kartografi]], ulikan ngeunaan [[atlas]]. Teu ukur nalungtik naon baé nu aya di lebah mana di Bumi, tapi ogé naha bet aya di dinya jeung henteu di tempat séjén, sometimes referred to as \"location in space\". Ngulik naha alatan manusa atawa alami, sarta akibat bébédaan éta.\n\n== Sajarah Géografi ==\n\nUrang [[Yunani kuna|Yunani]] nu geus kanyahoan boga adat nu sacara aktif ngalanglang géografi salaku [[élmu]] jeung [[filsafat]]. Inohongna di antarana [[Thales]] ti Miletus, [[Herodotus]], [[Eratosthenes]], [[Hipparchus]], [[Aristotle]], [[Dicaearchus]] ti Messana, [[Strabo]], jeung [[Ptolemy]]. Mapping by the [[Roman Empire|Roman]]s as they explored new lands added new techniques. One technique was the [[periplus]], a description of the ports and landfalls a coastwise sailor would find along a coastline; two early examples that have survived are the periplus of the Carthaginian [[Hanno the Navigator]] and a Periplus of the Erythraean sea, which describes the coastlines of the Red Sea and the Persian gulf.. \n\nDuring the [[Middle Ages]], [[Arab]]s such as [[Idrisi]], [[Ibn Battuta]], and [[Ibn Khaldun]] built on and maintained the Greek and Roman learnings. Following the journeys of [[Marco Polo]], interest in geography spread throughout [[Europe]]. During the [[Renaissance]] and into the [[abad ka-16|16th]] and [[abad ka-17|17th centuries]] the great voyages of exploration revived a desire for solid theoretical foundations and accurate detail. The [[Geographia Generalis]] by [[Bernhardus Varenius]] and [[Gerardus Mercator]]\'s world map are prime examples. \n\nBy the [[18th century]], geography had become recognized as a discrete discipline and became part of a typical [[university]] curriculum. Over the past two centuries the quantity of knowledge and the number of tools has exploded. There are strong links between geography and the sciences of [[géologi]] and [[botany]].\n\nIn the West during the [[abad ka-20|20th century]], the discipline of geography went through four major phases: [[environmental determinism]], [[regional geography]], the [[quantitative revolution]], and [[critical geography]].\n\nEnvironmental determinism is the theory that characteristics of people and cultures are due to the influence of the natural environment. Prominent environmental determinists included [[Carl Ritter]], [[Ellen Churchill Semple]], and [[Ellsworth Huntington]]. Popular hypotheses included \"heat makes inhabitants of the tropics lazy\" and \"frequent changes in barometric pressure make inhabitants of temperate latitudes more intellectually agile.\" Environmental determinist geographers attempted to make the study of such influences scientific. Around the 1930s, this school of thought was widely repudiated as lacking any basis and being prone to (often bigoted) generalizations. Environmental determinism remains an embarrassment to many contemporary geographers, and leads to skepticism among many of them of claims of environmental influence on culture (such as the theories of [[Jared Diamond]]).\n\nRegional geography represented a reaffirmation that the proper topic of geography was space and place. Regional geographers focused on the collection of descriptive information about places, as well as the proper methods for dividing the earth up into regions. The philosophical basis of this field was laid out by [[Richard Hartshorne]].\n\nThe quantitative revolution was geography\'s attempt to redefine itself as a science, in the wake of the revival of interest in science following the launch of Sputnik. Quantitative revolutionaries, often referred to as \"space cadets,\" declared that the purpose of geography was to test general laws about the spatial arrangement of phenomena. They adopted the philosophy of [[positivism]] from the natural sciences and turned to [[mathematics]] -- especially [[statistik]] -- as a way of proving hypotheses. The quantitative revolution laid the groundwork for the development of [[geographic information systems]].\n\nThough positivist and post-positivist approaches remain important in geography, critical geography arose as a critique of positivism. The first strain of critical geography to emerge was [[humanist geography]]. Drawing on the philosophies of [[existentialism]] and [[phenomenology]], humanist geographers (such as [[Yi-Fu Tuan]]) focused on people\'s sense of, and relationship with, places. More influential was [[Marxist geography]], which applied the social theories of [[Karl Marx]] and his followers to geographic phenomena. [[David Harvey]] and [[Richard Peet]] are well-known Marxist geographers. [[Feminist geography]] is, as the name suggests, the use of ideas from [[feminism]] in geographic contexts. The most recent strain of critical geography is [[postmodernist geography]], which employs the ideas of [[postmodernism|postmodernist]] and [[poststructuralism|poststructuralist]] theorists to explore the social construction of spatial relations.\n\n== Métode ==\n\nSpatial interrelationships are key to this [[synoptic science]], and it uses [[map|maps]] as a key tool. Classical [[cartography]] has been joined by the more modern approach to geographical analysis, computer-based [[geographic information systems]] (GIS).\n\nGeographers use four interrelated approaches: \n* Systematic - Groups geographical knowledge into categories that can be explored globally\n* Regional - Examines systematic relationships between categories for a specific region or location on the [[planet]].\n\n* Descriptive - Simply specifies the locations of features and populations.\n* Analytical - Asks \'\'why\'\' we find features and populations in a specific geographic area.\n\n== Cabang-cabang ==\n=== Géografi fisik ===\n\nCabang ieu museur kana géografi salaku [[élmu Bumi]], ngamangpaatkeun biologi pikeun neuleuman pola global [[flora]] jeung [[fauna]], sarta [[matematik]] jeung [[fisika]] pikeun pergerakan Bumi jeung hubunganana jeung matéri séjénna di [[tatasurya]]. Ogé ngawengku [[ékologi landscape]] jeung [[géografi lingkungan]].\n\nJejer nu patali: [[Atmosfir Bumi|atmosfir]] -- [[kapuloan]] -- [[benua]] -- [[padang pasir]] -- [[pulo]] -- [[landform]] -- [[sagara]] -- [[laut]] -- [[walungan]] -- [[situ]] -- [[ékologi]] -- [[iklim]] -- [[taneuh]] -- [[géomorfologi]] -- [[biogéografi]] - [[Timeline of geography, paléontologi]], [[paléogéografi]]\n\n=== Géografi manusa ===\n\n[[Manusa]], atawa [[pulitik]]/[[budaya]], cabang ti géografi - ogé disebut [[antropogéografi]] museur kana [[élmu sosial]], aspék non-fisik kumaha tataan dunya. Nguji cara manusa nyaluyukeun anjeun ka lemah jeung jalma séjén, sarta dina transformasi makroskopik cara peranna di dunya. Ieu bisa diwilah-wilah kana kategori lega: [[géografi ékonomis]], [[géografi politis]] (kaasup [[géopolitik]]), [[géografi sosial]] (kaasup [[géografi urban]]), [[géografi féminis]], jeung [[géografi militér]].\n\nJejer nu patali: [[Nagara-nagara sadunya]] -- [[nagara]] -- [[bangsa]] -- \'\'[[state]]\'\' -- [[personal union]] -- [[propinsi]] -- [[kota]] -- [[pamaréntahan kota]]\n\n=== Géografi manusa-lingkungan ===\n\nDuring the time of environmental determinism, geography was defined not as the study of spatial relationships, but as the study of how humans and the natural environment interact. Though environmental determinism has died out, there remains a strong tradition of geographers addressing the relationships between people and nature. There are two main subfields of human-environment geography: cultural and political ecology (CAPE), and risk-hazards research.\n\n==== Ékologi budaya jeung politik ====\n\nCultural ecology grew out of the work of [[Carl O. Sauer|Carl Sauer]] in geography and a similar school of thought in [[anthropology]]. It examined how human societies adapt themselves to the natural environment. [[Sustainability]] science has been one important outgrowth of this tradition. Political ecology arose when some geographers used aspects of [[critical geography]] to look at relations of power and how they affect people\'s use of the environment. For example, an influential study by [[Michael Watts]] argued that famines in the [[Sahel]] are caused by the changes in the region\'s political and economic system as a result of [[colonialism]] and the spread of [[capitalism]]. \n\n==== Risk-hazards research ====\n\nResearch on hazards began with the work of geographer [[Gilbert F. White]], who sought to understand why people live in disaster-prone floodplains. Since then, the hazards field has expanded to become a multidisciplinary field examining both natural hazards (such as [[earthquake]]s) and technological hazards (such as [[nuclear reactor]] meltdowns). Geographers studying hazards are interested in both the dynamics of the hazard event and how people and societies deal with it.\n\n=== Géografi sajarah ===\n\nThis branch seeks to determine how cultural features of the multifarious societies across the planet evolved and came into being. Study of the [[landscape]] is one of many key foci in this field - much can be deduced about earlier societies from their impact on their local environment and surroundings.\n\n==== What\'s in a name? Historical Geography and the Berkeley School ====\n\n\"Historical Geography\" can indeed refer to the reciprocal effects of geography and history on each other. But in the United States, it has a more specialized meaning: This is the name given by [[Carl O. Sauer|Carl Ortwin Sauer]] of the [[University of California, Berkeley]] to his program of reorganizing cultural geography (some say all geography) along regional lines, beginning in the first decades of the 20th Century.\n\nTo Sauer, a landscape and the cultures in it could only be understood if all of its influences through history were taken into account: Physical, cultural, economic, political, environmental. Sauer stressed [[regional specialization]] as the only means of gaining expertise on regions of the world.\n\nSauer\'s philosophy was the principal shaper of American geographic thought in the mid-20th century. Regional specialists remain in academic geography departments to this day. But many geographers feel that it harmed the discipline in the long run: Too much effort was spent on data collection and classification, and too little on analysis and explanation. Studies became more and more area specific as later geographers struggled to find places to make names for themselves. This probably led in turn to the [[1950\'s crisis in Geography]] which nearly destroyed it as an academic discipline.\n\n== Téhnik Géografis ==\n\n* \'\'[[Kartografi]]\'\' studies the representation of the Earth\'s surface with abstract symbols. It can be said, without much controversy, that cartography is the seed from which the larger field of Geography grew. Most geographers will cite a childhood fascination with maps as an early sign they would end up in the field. Although other subdisciplines of geography rely on maps for presenting their analyses, the actual making of maps is abstract enough to be regarded separately.
Cartography has grown from a collection of drafting techniques into an actual science. Cartographers must learn [[cognitive psychology]] and ergonomics to understand which symbols convey information about the Earth most effectively, and [behavioral psychology] to induce the readers of their maps to act on the information. They must learn [[geodesy]] and fairly advanced [[mathematics]] to understand how the shape of the Earth affects the distortion of map symbols projected onto a flat surface for viewing.\n\n\n\n* \'\'[[Geographic Information System]]s\'\' deals with the storage of information about the Earth for automatic retrieval by a computer, in an accurate manner appropriate to the information\'s purpose. In addition to all of the other subdisciplines of geography, GIS specialists must understand [[computer science]] and [[database]] systems. GIS has so revolutionized the field of cartography that nearly all mapmaking is now done with the assistance of some form of GIS software. \n\n* \'\'Geographic quantitative methods\'\' deal with numerical methods peculiar to (or at least most commonly found in) geography. In addition to [[spatial analyses]], you are likely to find things like [[cluster analysis]], [[discriminant analysis]], and [[non-parametric statistical tests]] in geographic studies.\n\n== Widang-widang nu patali ==\n=== Rarancang Kota jeung Régional ===\n\n[[Rarancang kota]] jeung [[Rarancang régional]] ngamangpaatkeun géografi pikeun ngabantu nangtukeun cara ngembangkeun (atawa teu ngembangkeun) tanah pikeun nedunan kriteria husus, samodél kasalametan, kaéndahan, lolongkrang ékonomi, the preservation of the built or natural heritage, jeung sajabana. Rarancang wewengkon kota jeung pilemburan bisa ditempo salaku géografi terapan sanajan loba ogé aspék/faktor seni, élmu, jeung atikan sajarah. Some of the issues facing planning are considered briefly under the headings of [[rural exodus]], [[urban exodus]] and [[Smart Growth]].\n\n=== Élmu Régional ===\n\nTaun [[1950-an]] pergerakan [[élmu régional]] tumuwuh, dipingpin ku [[Walter Isard]] pikeun nyadiakeun dasar nu leuwih kuantitatif jeung analitis pikeun pananya-pananya géografis, kontras jeung kacondongan program géografi tradisional nu leuwih kualitatif. Élmu régional comprises the body of knowledge in which the spatial dimension plays a fundamental role, such as [[ékonomi régional]], [[manajemén sumberdaya]], [[téori lokasi]], [[tata kota]] jeung [[tata régional]], [[angkutan]] jeung [[komunikasi]], [[géografi manusa]], [[sebaran populasi]], [[ékologi landscape]], jeung kualitas lingkungan.\n\n==Tumbu kaluar==\n* [http://www.populationdata.net PopulationData.net]\n* [http://www.ericdigests.org/1996-4/high.htm Ngamangpaatkeun Literatur pikeun Ngajar Géografi di Sakola. ERIC Digest.]\n* [http://ericdigests.org/1992-5/geography.htm Ngajar Géografi di Sakola jeung Imah. ERIC Digest.]\n* [http://ericdigests.org/1996-1/geography.htm Baku Eusi Géografi Nasional. ERIC Digest.]\n\n== Tempo ogé ==\n\n*[[Daptar jejer géografi]]\n*[[Daptar nagara]]\n*[[Daptar_tabel_rujukan#Géografi_jeung_tempat]]\n\n\n\n[[Category:Géografi]]\n[[af:Geografie]] [[ar:إستونيا]] [[az:Coğrafiya]] [[bg:География]] [[bs:Geografija]] [[ca:Geografia]] [[co:Geografia]] [[cs:Zeměpis]] [[cy:Daearyddiaeth]] [[da:Geografi]] [[de:Geographie]] [[als:Geographie]] [[et:Geograafia]] [[el:Γεωγραφία]] [[en:Geography]] [[es:Geografía]] [[eo:Geografio]] [[fr:Géographie]] [[fy:Geografy]] [[gl:Xeografía]] [[ko:지리학]] [[hi:भूगोल]] [[hr:Zemljopis]] [[id:Geografi]] [[ia:Geographia]] [[it:Geografia]] [[he:גיאוגרפיה]] [[csb:Ge%C3%B2grafij%C3%B4]] [[ks:Geografia]] [[sw:Jiografia]] [[la:Geographia]] [[lv:Geografija]] [[lt:Geografija]] [[hu:Földrajztudomány]] [[ms:Geografi]] [[nl:Geografie]] [[ja:地理学]] [[no:Geografi]] [[oc:Geografia]] [[nds:Geographie]] [[pl:Geografia]] [[pt:Geografia]] [[ro:Geografie]] [[ru:География]] [[sl:Geografija]] [[sr:Географија]] [[sv:Geografi]] [[th:ภูมิศาสตร์]] [[ur:%D8%AC%D8%BA%D8%B1%D8%A7%D9%81%D9%8A%DB%81]] [[tr:Coğrafya]] [[uk:Географя]] [[vo:Taledav]] [[zh:地理学]] [[simple:Geography]]','/* Sajarah Géografi */',3,'Kandar','20050316082133','',0,0,1,0,0.540324417195,'20050316082133','79949683917866'); INSERT INTO cur VALUES (811,0,'Fisika','\'\'\'Fisika\'\'\' (tina [[Basa Yunani]] φυσικός (\'\'physikos\'\'): \'\'natural\'\', tina φύσις (\'\'physis\'\'): [[Alam]]) ngarupakeun [[élmu]] Alam tina jihat nu panglegana. [[Fisikawan]] ngulik paripolah jeung interaksi [[zat]] jeung [[gaya (fisika)|gaya]]. [[Hukum fisika]] umumna diwujudkeun dina rupa hubungan [[matematik|matematis]].\n\nFisika raket pisan hubunganana jeung [[élmu alam]] séjén, utamana [[kimia]], élmu [[molekul]] jeung senyawa kimia nu dibentukna. Kimia mirip pisan jeung fisika, utamana dina [[mékanika kuantum]], [[térmodinamika]] jeung [[éléktromagnétisme]]. Ngan, kusabab fénoména kimiawi nu kompléks jeung kacida lobana ngajadikeun kimia salawasna dianggap salaku disiplin nu misah. \n\nDi handap ieu hiji ihtisar sub-widang jeung konsép utama dina fisika, disusul tepus ku ringkesan sajarah fisika jeung sub-widangna. [[Béréndélan jejer]] nu leuwih lengkep ogé aya.\n\n==Ihtisar fisika==\n\n
\n===Téori===\n\'\'Artikel utama\'\': [[Fisika Téoritis|Téori Fisika]]\n
\n\n====Téori puseur====\n[[Mékanika klasik]] -- [[Térmodinamika]] -- [[Mékanika statistik]] -- [[Éléctromagnétisme]] -- [[Rélativitas husus]] -- [[Rélativitas umum]] -- [[Mékanika kuantum]] -- [[Téori médan kuantum]] -- [[Modél baku]] -- [[Dinamika cairan]]\n\n====Téori nu diajukeun====\n[[Téori Sagalana]] -- [[Gabungan Sagala Téori]] -- [[Téori-M]] -- [[Loop quantum gravity]] -- [[Emergence]]\n\n====Téori Fringe====\n[[Fusi tiis]] -- [[Téori dinamis graviti]] -- [[Luminiferous aether]] -- [[Orgone energy]] -- [[Reciprocal System of Theory]] -- [[Steady state theory]] -- [[Torowongan waktu]] -- [[Variable Laju jeung Cahaya]] \n\n
\n\n=== Konsép ===\n\n[[Zat]] -- [[Antizat]] -- [[Partikel éléméntér]] -- [[Boson]] -- [[Fermion]]\n\n[[Simétri]] -- [[Gerakan]] -- [[Hukum konservasi]] -- [[Massa]] -- [[Énergi]] -- [[Moméntum]] -- [[Angular momentum]] -- [[Spin (physics)|Spin]]\n\n[[Waktu]] -- [[Ruang]] -- [[Diménsi]] -- [[Ruangwaktu]] -- [[Panjang]] -- [[Velocity]] -- [[Gaya (Fisika)|Gaya]] -- [[Torque]]\n\n[[Gelombang]] -- [[Fungsigelombang]] -- [[Quantum entanglement]] -- [[Harmonic oscillator]] -- [[Magnetism]] -- [[Electricity]] -- [[Electromagnetic radiasi]] -- [[Temperatur]] -- [[Entropy]] -- [[Physical information]] --\n[[Tanaga Vacuum]] -- [[Tanaga Titik-nol ]]\n\n[[Phase transitions]] -- [[Critical phenomena]] -- [[Self-organization]] -- [[Spontaneous symmetry breaking]] -- [[Superconductivity]] -- [[Superfluidity]] -- [[Quantum phase transitions]]\n\n=== [[Gaya fundaméntal]] ===\n[[Graviti|Gravitasi]] -- [[Éléktromagnétisme|Éléktromagnétik]] -- [[Weak interaction|Weak]] -- [[Strong interaction|Strong]]\n\n=== Partikel ===\n\'\'Main article\'\': [[Fisika partikel|Partikel]]\n\n[[Atom]] -- [[Éléktron]] -- [[Gluon]] -- [[Graviton]] -- [[Neutrino]] -- [[Neutron]] -- [[Quark]] -- [[Photino]] -- [[Photon]] -- [[Proton]] -- [[Boson W jeung Z]] -- [[Radiasi partikel]] -- [[Phonon]] -- [[Roton]]\n\n[[Boson]] -- [[Fermion]] -- [[Supersimétri]]\n\n=== Sub-widang fisika ===\n[[Accelerator physics]] -- [[Akustik]] -- [[Astrofisika]] -- [[Fisika Atomik, Molekular, jeung Optik]] -- [[Fisika komputasional]] -- [[Condensed matter physics]] -- [[Kosmologi]] -- [[Cryogenics]] -- [[Dinamika fluida]] -- [[Fisika polimer]] -- [[Optik]] -- [[Fisika material]] -- [[Fisika inti]] -- [[Fisika plasma]] -- [[Fisika partikel]] (or High Energy Physics) -- [[Vehicle dynamics]]\n\n=== Métode ===\n[[Métode ilmiah]] -- [[Kuantitas fisik]] -- [[Ukuran]] -- [[Alat ukur]] -- [[Analisis dimensional]] -- [[Statistik]]--[[Skala]]\n\n=== Tabel ===\n[[Daptar hukum ilmiah|Daptar hukum fisika]] -- [[Konstanta fisika]] -- [[Unit dasar SI]] -- [[unit turunan SI]] -- [[préfix SI]] -- [[Konversi unit|Konversi unit]]\n\n=== Sajarah ===\n[[Sajarah Fisika]] -- [[Inohong Fisikawan]] -- [[Hadiah Nobel widang fisika]]\n\n=== Widang nu patali ===\n[[Astronomi]] -- [[Biofisik]] -- [[Siklus]] -- [[Éléktronik]] -- [[Rékayasa]] -- [[Géofisik]] -- [[Élmu material]] -- [[Fisika Matematis]] -- [[Fisika médis]] -- [[Kimia Fisik]]\n
\n\n== Sajarah ringkes fisika ==\n\n\'\'Catetan: di handap ieu ngarupakeun ihtisar ringkes tumuwuhna fisika. Pikeun leuwih jéntré, baca artikel utama subjék ieu, [[Sajarah fisika]].\'\'\n\nGeus ti jaman baheula manusa nyoba neuleuman paripolah zat: naha apel bet ragrag kana taneuh, naha barang nu béda boga sipat nu béda, jeung saterusna. Ogé ngeunaan karakter [[mayapada]], samodél bentuk Bumi jeung paripolah \'\'celestial object\'\' samodél [[panonpoé]] jeung [[bulan]]. Sababaraha téori geus diajukeun, tétéla lolobana salah. Téori-téori ieu umumna kedal dina istilah [[filosofi|filosofis]], teu kungsi dibuktikeun maké uji éksperimén nu sistematis. There were exceptions and there are [[anachronism]]s: for example, the [[Hellenic civilization|Greek]] thinker [[Archimedes]] derived many correct quantitative descriptions of mechanics and hydrostatics.\n\nMunggaran [[abad ka-17]], [[Galileo Galilei|Galiléo]] naratas dipakéna ékspérimén pikeun ngabuktikeun téori-téori fisik, nu jadi ide konci dina [[métode ilmiah]]. Galiléo geus sacara suksés ngarumuskeun jeung nguji sababaraha hasil panalungtikan ngeunaan [[dinamika (mekanik)|dinamika]], utamana Hukum [[Inersia]]. Dina taun [[1687]], [[Isaac Newton|Newton]] published the [[Principia Mathematica]], detailing two comprehensive and successful physical theories: [[Newton\'s laws of motion]], from which arise [[classical mechanics]]; and [[gravity|Newton\'s Law of Gravitation]], which describes the [[fundamental force]] of [[gravity]]. Both theories agreed well with experiment. Classical mechanics would be exhaustively extended by [[Joseph-Louis de Lagrange|Lagrange]], [[William Rowan Hamilton|Hamilton]], and others, who produced new formulations, principles, and results. The Law of Gravitation initiated the field of [[astrophysics]], which describes [[astronomy|astronomical]] phenomena using physical theories.\n\nFrom the [[18th century]] onwards, [[thermodynamics]] was developed by [[Robert Boyle|Boyle]], [[Thomas Young|Young]], and many others. In [[1733]], [[Daniel Bernoulli|Bernoulli]] used statistical arguments with classical mechanics to derive thermodynamic results, initiating the field of [[statistical mechanics]]. In [[1798]], [[Benjamin Thompson|Thompson]] demonstrated the conversion of mechanical work into heat, and in [[1847]] [[James Joule|Joule]] stated the law of conservation of [[energy]], in the form of heat as well as mechanical energy.\n\nThe behavior of [[electricity]] and [[magnetism]] was studied by [[Michael Faraday|Faraday]], [[Georg Ohm|Ohm]], and others. In [[1855]], [[James Clerk Maxwell|Maxwell]] unified the two phenomena into a single theory of [[electromagnetism]], described by [[Maxwells equations|Maxwell\'s equations]]. A prediction of this theory was that [[light]] is an [[electromagnetic radiation|electromagnetic wave]].\n\nIn [[1895]], [[Wilhelm Röntgen|Roentgen]] discovered [[X-ray]]s, which turned out to be high-frequency electromagnetic radiation. [[Radioactivity]] was discovered in [[1896]] by [[Henri Becquerel]], and further studied by [[Pierre Curie]] and [[Marie Curie]] and others. This initiated the field of [[nuclear physics]].\n\nIn [[1897]], [[J.J. Thomson|Thomson]] discovered the [[electron]], the elementary particle which carries electrical current in circuits. In [[1904]], he proposed the first model of the [[atom]], known as the [[atom/plum pudding|plum pudding model]]. (The existence of the atom had been proposed in [[1808]] by [[John Dalton|Dalton]].)\n\nIn [[1905]], Einstein formulated the theory of [[special relativity]], unifying space and time into a single entity, [[spacetime]]. Relativity prescribes a different transformation between [[inertial frame of reference|reference frames]] than classical mechanics; this necessitated the development of relativistic mechanics as a replacement for classical mechanics. In the regime of low (relative) velocities, the two theories agree. In [[1915]], Einstein extended special relativity to explain gravity with the [[general relativity|general theory of relativity]], which replaces Newton\'s law of gravitation. In the regime of low masses and energies, the two theories agree.\n\nIn [[1911]], [[Ernest Rutherford|Rutherford]] deduced from [[rutherford scattering|scattering experiments]] the existence of a compact atomic nucleus, with positively charged constituents dubbed [[proton]]s. [[neutron|Neutrons]], the neutral nuclear constituents, were discovered in [[1932]] by [[James Chadwick|Chadwick]].\n\nBeginning in [[1900]], [[Max Planck|Planck]], [[Albert Einstein|Einstein]], [[Niels Bohr|Bohr]], and others developed [[quantum]] theories to explain various anomalous experimental results by introducing discrete energy levels. In [[1925]], [[Werner Heisenberg|Heisenberg]] and [[1926]], [[Erwin Schrödinger|Schrödinger]] and [[P.A.M. Dirac|Dirac]] formulated [[quantum mechanics]], which explained the preceding quantum theories. In quantum mechanics, the outcomes of physical measurements are inherently [[probability|probabilistic]]; the theory describes the calculation of these probabilities. It successfully describes the behavior of matter at small distance scales.\n\nQuantum mechanics also provided the theoretical tools for [[condensed matter physics]], which studies the physical behavior of solids and liquids, including phenomena such as [[crystal structure]]s, [[semiconductor|semiconductivity]], and [[superconductor|superconductivity]]. The pioneers of condensed matter physics include [[Felix Bloch|Bloch]], who created a quantum mechanical description of the behavior of electrons in crystal structures in [[1928]].\n\nDuring [[World War II]], research was conducted by each side into [[nuclear physics]], for the purpose of creating a [[nuclear weapon|nuclear bomb]]. The German effort, led by Heisenberg, did not succeed, but the Allied [[Manhattan Project]] reached its goal. In America, a team led by [[Enrico Fermi|Fermi]] achieved the first man-made [[nuclear chain reaction]] in [[1942]], and in [[1945]] the world\'s first [[nuclear weapon|nuclear explosive]] was detonated at [[Trinity site]], near [[Alamogordo]], [[New Mexico]].\n\n[[Quantum field theory]] was formulated in order to extend quantum mechanics to be consistent with special relativity. It achieved its modern form in the late [[1940s]] with work by [[Richard Feynman|Feynman]], [[Julian Schwinger|Schwinger]], [[Tomonaga]], and [[Freeman Dyson|Dyson]]. They formulated the theory of [[quantum electrodynamics]], which describes the electromagnetic interaction.\n\nQuantum field theory provided the framework for modern [[particle physics]], which studies [[fundamental force]]s and elementary particles. In [[1954]], [[Yang Chen Ning|Yang]] and [[Robert Mills|Mills]] developed a class of [[gauge theory|gauge theories]], which provided the framework for the [[Standard Model]]. The Standard Model, which was completed in the [[1970s]], successfully describes almost all elementary particles observed to date.\n\n== Future directions ==\n\nAs of [[As of 2003|2003]], research is progressing on a large number of fields of physics.\n\nIn [[condensed matter physics]], the biggest unsolved theoretical problem is the explanation for [[high-temperature superconductivity]]. Strong efforts, largely experimental, are being put into making workable [[spintronics]] and [[quantum computer]]s.\n\nIn particle physics, the first pieces of experimental evidence for physics beyond the [[Standard Model]] have begun to appear. Foremost amongst this are indications that [[neutrino]]s have non-zero [[mass]]. These experimental results appear to have solved the long-standing [[solar neutrino problem]] in solar physics. The physics of massive neutrinos is currently an area of active theoretical and experimental research. In the next several years, [[particle accelerator]]s will begin probing energy scales in the [[TeV]] range, in which experimentalists are hoping to find evidence for the [[higgs boson]] and [[supersymmetry|supersymmetric particles]].\n\nTheoretical attempts to unify [[quantum mechanics]] and [[general relativity]] into a single theory of [[quantum gravity]], a program ongoing for over half a century, has yet to bear fruit. The current leading candidates are [[M-theory]] and [[loop quantum gravity]].\n\nMany [[astronomy|astronomical]] phenomena have yet to be explained, including the existence of [[GZK paradox|ultra-high energy cosmic rays]] and the [[galaxy rotation problem|anomalous rotation rates of galaxies]]. Theories that have been proposed to resolve these problems include [[doubly-special relativity]], [[modified Newtonian dynamics]], and the existence of [[dark matter]]. In addition, the cosmological predictions of the last several decades have been contradicted by recent evidence that the [[Accelerating universe|expansion of the universe is accelerating]].\n\nTingali [[Masalah nu teu bisa dipeupeuskeun]] jang \"fuller treatment\" tina subjek ieu.\n\nSee the definition of [[physical]].\n\n==Bacaan nu dianjurkeun sarta tumbu kaluar==\n\n*\'\'[http://textbook.wikipedia.org/wiki/Physics A Study Guide to the Science of Physics]\'\' ~ at \'\'Wikibooks\'\'\n* [[Richard Feynman|Feynman]], \'\'The Character of Physical Law\'\', Random House (Modern Library), 1994, hardcover, 192 pages, ISBN 0679601279\n* [[Richard Feynman|Feynman]], Leighton, Sands, \'\'The Feynman Lectures on Physics\'\', Addison-Wesley 1970, 3 volumes, paperback, ISBN 0201021153, hardcover Commemorative edition, 1989, ISBN 0201500647\n* [[Brian Greene]], \'\'The Elegant Universe: Superstrings, Hidden Dimensions, and the Quest for the Ultimate Theory\'\', 464 pages, paperback, Vintage Books, 2000, ISBN 0375708111, hardcover, W.W. Norton & Company, 2003, ISBN 0393058581\n* Eric Weisstein, Weisstein and Wolfram Research, Inc., and et al, \'\'[http://scienceworld.wolfram.com/physics/ World of Physics]\'\'. Online Physics encyclopedic dictionary.\n* Optics.net, \'\'[http://www.optics.net/ Optics on the Net]\'\'. Online Optics, optoelectronics technical, forums and buyer\'s guide.\n* Electronics-ee, \'\'[http://www.electronicsee.com/ Electronics for engineers]\'\'. Online Electronics, electrical resources and forums.\n* Optics2001, \'\'[http://www.optics2001.com/ The Optics Odyssey]\'\'. Optics community and library.\n* Carl R. Nave, \'\'[http://hyperphysics.phy-astr.gsu.edu/hbase/hph.html HyperPhysics]\'\', . Online crosslinked physics concept maps.\n* [http://www.physics.org/ Physics.org]. Website of the Institute of Physics.\n* Karlsson, Erik B., \"\'\'[http://www.nobel.se/physics/articles/karlsson/index.html#2 The Nobel Prize in Physics 1901-2000]\'\'\". The [[Nobel Prize|Nobel Foundation]].\n\n{{Physics-footer}}\n\n[[af:Fisika]]\n[[ar:فيزياء]]\n[[bg:Физика]]\n[[bs:Fizika]]\n[[ca:Física]]\n[[cs:Fyzika]]\n[[cy:Ffiseg]]\n[[da:Fysik]]\n[[de:Physik]]\n[[et:Füüsika]]\n[[el:Φυσική]]\n[[es:Física]]\n[[eo:Fiziko]]\n[[fr:Physique]]\n[[gl:Física]]\n[[ko:물리학]]\n[[lt:Fizika]]\n[[hr:Fizika]]\n[[id:Fisika]]\n[[is:Eðlisfræði]]\n[[it:Fisica]]\n[[ia:Physica]]\n[[he:פיסיקה]]\n[[la:Physica]]\n[[hu:Fizika]]\n[[lv:Fizika]]\n[[nl:Natuurkunde]]\n[[ja:物理学]]\n[[no:Fysikk]]\n[[nds:Physik]]\n[[pl:Fizyka]]\n[[pt:Física]]\n[[ro:Fizică]]\n[[ru:Физика]]\n[[simple:Physics]]\n[[sk:Fyzika]]\n[[sl:Fizika]]\n[[sr:Физика]]\n[[fi:Fysiikka]]\n[[sv:Fysik]]\n[[tr:Fizik]]\n[[uk:Фізика]]\n[[vo:Füsüd]]\n[[zh-cn:物理学]]\n[[zh-tw:物理學]]\n\n[[Category:Élmu alam]]','',3,'Kandar','20041029074856','',0,0,0,0,0.956810892074,'20050208191941','79958970925143'); INSERT INTO cur VALUES (812,0,'Astronomi','\'\'\'Astronomi\'\'\', nu sacara [[étimologi|étimologis]] hartina \"\'\'[[elmu]] [[béntang]]\'\'\" (tina [[Basa Yunani]]: αστρονομία = άστρον + [[nomos|νόμος]]) ngarupakeun [[élmu]] nu ngawengku [[panalungtikan]] jeung katerangan [[kajadian|kajadian-kajadian]] nu tumiba di luareun [[Marcapada]] jeung [[atmosfir marcapada|atmosfirna]]. Astronomi ngulik sasakala, évolusi, sipat-sipat kimia jeung fisika objék-objék nu bisa kapanggih di langit (luareun Bumi), sarta prosés-prosés nu patali.\n\n[[image:moon.crater.arp.750pix.jpg|thumb|right|250px|Astronomi]] bulan: kawah nu badag nyéta [[Kawah Daedalus|Daedalus]], fotograf beunang awak [[Apollo 11]] nalika maranéhna ngurilingan [[Bulan]] taun 1969. Located near the center of the far side of Earth\'s Moon, its diameter is about 93 kilometers (58 miles).]]\n\nAstronomi ngarupakeun salasahiji ti saeutik élmu di mana para [[astronomi amatir|amatir]] bisa boga peran nu aktif, utamana dina manggihan jeung ngawaskeun [[fénoména]] transién. Astronomi teu aya patalina jeung [[astrologi]], [[pseudoscience]] nu nyoba-nyoba ngaramalkeun takdir jalma ku jalan nyukcruk jalur objék astronomis. Sanajan dua widang éta babagi sumber nu méh sarua, ari sabenerna mah béda pisan; astronomer maké [[métode ilmiah]], sedengkeun astrologer mah henteu.\n\n==Bagbagan astronomi==\nDina mangsa munggaranana, balik deui ka jaman [[Yunani kuna]] jeung nu séjénna, astronomi utamana ngulik [[astrométri]], ngalelebah planét jeung bintang di langit. Kadieunakeun, pagawéan [[Johannes Kepler|Kepler]] jeung [[Isaac Newton|Newton]] geus naratas jalan pikeun [[celestial mechanics]], nu sacara matematis ngaramal ketak/pola interaksi \'\'celestial bodies\'\' nu kapangaruhan ku graviti, jeung objék-objék [[tatasurya]] umumna. Pagawéan-pagawéan nu dikeureuyeuh dina dua widang ieu, nu baheula lolobana dipigawé ku leungeun, ayeuna mah geus maké alat-alat otomatis, nepi ka geus dianggap lain disiplin mandiri deui. Gerakan jeung posisi objék geus gampang pisan ditéang, astronomi modern leuwih merhatikeun jeung ngusahakeun nengetan jeung neuleuman sipat fisik sabenerna objék-objék langit—what makes them \"tick\".\n\nTi mimiti abad ka-20 widang astronomi profésional beulah jadi \'\'[[observational astronomy]]\'\' jeung [[astrofisik tioritis]]. Najan \'\'astronomer\'\' lolobana ngagabungkeun unsur-unsur ti éta dua widang dina panalungtikanana, kusabab bédana kaahlian nu dipaké, kalolobaan astronomer profésional leuwih condong ka salasahijina. \'\'Observational astronomy\'\' leuwih condong utamana ka ngumpulkeun data, kaasup ngawangun jeung ngaropéa instrumén sarta ngolah data nu kakumpulkeun; cabang ieu ayeuna disebut salaku \"astrométri\" atawa \"astronomy\". Theoretical astrophysics is concerned mainly with figuring out the observational implications of different models, and involves working with computer or analytic models. \n\nWidang ulikan astronomi ogé digolongkeun dumasar dua jalan nu béda: dumasar \"subjék\", biasana nurutkeun wewengkon langit (misalna \'\'Galactic astronomy\'\') atawa \"masalah nu ditujul\" (saperti dibentukna béntang atawa kosmologi); atawa dumasar cara nu dipaké pikeun meunangkeun data.\n\n===Dumasar subjék atawa masalah nu ditujul===\n[[image:dust.devil.mars.arp.750pix.jpg|thumb|right|250px|Planetary astronomy, or Planetary Sciences: a [[dust devil]] on [[Mars (planet)|Mars]]. Photographed by [[Mars Global Surveyor]], the long dark streak is formed by a moving swirling column of Martian atmosphere (with similarities to a terrestrial tornado). The dust devil itself (the black spot) is climbing the crater wall. The streaks on the right are sand dunes on the crater floor.]]\n\n*[[Astrobiologi]]: the study of the advent and evolution of biological systems in the universe.\n*[[Astrométri]]: the study of the position of objects in the sky and their changes of position. Defines the system of coordinates used and the [[kinematics]] of objects in our galaxy.\n*[[Kosmologi]]: the study of the universe as a whole and its evolution.\n*[[Galactic astronomy]]: the study of the structure and components of our galaxy and of other galaxies.\n*[[Extragalactic astronomy]]: the study of objects (mainly galaxies) outside our galaxy.\n*[[Galaxy formation and evolution]]: the study of the formation of the galaxies, and their evolution.\n*[[Planetary Sciences]]: the study of the [[planet|planets]] of the [[solar system]]. \n*[[Stellar astronomy]]: the study of the stars.\n*[[Stellar evolution]]: the study of the evolution of stars from their formation to their end as a stellar remnant.\n*[[Star formation]]: the study of the condition and processes that led to the formation of stars in the interior of gas clouds, and the process of formation itself.\n\nAlso, there are other disciplines that may be considered part of astronomy:\n\n*[[Archaeoastronomy]]\n*[[Astrokimia]]\n*[[Planetary sciences]]\n*[[Kosmologi]]\n\nSee [[list of astronomical topics]] for a more exhaustive list of astronomy-related pages.\n\n===Ways of obtaining information===\nIn astronomy, information is mainly received from the detection and analysis of [[electromagnetic radiation]],\n[[photon|photons]], but information is also carried by [[cosmic ray]]s, [[neutrino|neutrinos]], [[meteor|meteors]], and, in the near future, [[gravitational wave|gravitational waves]] (see [[LIGO]] and [[LISA (astronomy)|LISA]]).\n\nA traditional division of astronomy is given by the region of the [[electromagnetic spectrum]] observed:\n\n*[[Optical astronomy]] describes the techniques used to detect and analyze [[light]] in and slightly around the [[wavelength]]s that can be detected with the [[eye]]s (about 400 - 800 nm). The most common tool is the [[telescope]], with [[electronic imager]]s and [[spectrograph]]s.\n*[[Infrared astronomy]] deals with the detection of infrared radiation (wavelengths longer than red light). The most common tool is the [[telescope]] but with the instrument optimized for infrared. [[Space telescope]]s are also used to eliminate noise (electromagnetic interference) from the atmosphere.\n*[[Radio astronomy]] uses completely different instruments to detect [[radiation]] of wavelengths of mm to cm. The receivers are similar to those used in [[radio]] broadcast transmission (which uses those wavelengths of radiation). See also [[Radio telescope]]s.\n*[[High-energy astronomy]]\n\n[[image:grav.lens1.arp.750pix.jpg|thumb|right|250px|Extragalactic astronomy: [[gravitational lensing]]. This image shows several blue, loop-shaped objects that are multiple images of the same galaxy. They have been duplicated by the gravitational lens effect of the cluster of yellow galaxies near the photograph\'s center. The lens is produced by the cluster\'s gravitational field that bends light to magnify and distort the image of a more distant object.]]\n\nOptical and radio astronomy can be performed with ground-based [[observatory|observatories]], because the [[Earth\'s atmosphere|atmosphere]] is transparent at those wavelengths. Infrared light is heavily absorbed by\n[[water vapor]], so infrared observatories have to be located in high, dry places or in space.\n\nThe atmosphere is opaque at the wavelengths used by [[X-ray astronomy]], [[gamma-ray astronomy]], [[UV astronomy]] and, except for a few wavelength \"windows\", [[Far infrared astronomy]] , so observations\ncan be carried out only from [[balloon]]s or [[space observatory|space observatories]].\n\n==Sajarah ringkes==\nDina bagian awal sajarahna, astronomi ngan wungkul ngawengku observasi jeung prédiksi ketak/gerak objék-objék langit nu bisa ditempo langsung ku panon.[[Rigveda]] didumasarkeun kana 27 [[konstélasi]] nu aya patalina jeung gerakan panonpoé jeung 12 babagian [[zodiak]] langit. [[Peradaban Hellenik|Yunani Kuna]] méré sumbangan nu kalintang lobana pikeun astronomi, di antarana definisi sistim [[apparent magnitude|magnitude]]. The [[Bible]] contains a number of statements on the position of the earth in the universe and the nature of the stars and planets, most of which are poetic rather than literal; see [[Biblical cosmology]]. In [[500|500 AD]], [[Aryabhata]] presented a mathematical system that took the earth to spin on its axis and considered the motions of the planets with respect to the sun.\n\nAstronomy was mostly stagnant in [[Middle Ages|medieval]] [[Europe]], but flourished meanwhile in the [[Arab]] world. The late [[9th century]] Islamic astronomer [[al-Farghani]] (Abu\'l-Abbas Ahmad ibn Muhammad ibn Kathir al-Farghani) wrote extensively on the motion of celestial bodies. His work was translated into Latin in the [[12th century]]. In the late [[10th century]], a huge [[observatory]] was built near [[Tehran]], [[Iran]], by the astronomer al-Khujandi who observed a series of meridian transits of the Sun, which allowed him to calculate the obliquity of the ecliptic. In Persia, [[Omar Khayyam]] (Ghiyath al-Din Abu\'l-Fath Umar ibn Ibrahim al-Nisaburi al-Khayyami) compiled many tables and performed a reformation of the [[calendar]] that was more accurate than the [[Julian Calendar|Julian]] and came close to the [[Gregorian calendar|Gregorian]].\n\nDuring the [[Renaissance]] [[Copernicus]] proposed a [[heliocentric model]] of the [[Solar System]]. His work was defended, expanded upon, and corrected by [[Galileo Galilei]] and [[Johannes Kepler]]. Kepler was the first to devise a system that described correctly the details of the motion of the planets with the Sun at the center. However, Kepler did not succeed in formulating a theory behind the laws he wrote down. It was left to [[Sir Isaac Newton|Newton\'s]] invention of [[celestial dynamics]] and his [[law of gravitation]] to finally explain the motions of the [[planet]]s.\n\nStars were found to be faraway objects. With the advent of [[spectroscopy]] it was proved that they were similar to our own sun, but with a wide range of [[temperature]]s, [[mass]]es and sizes. The existence of our [[galaxy]], the [[Milky Way]], as a separate group of stars was only proven in the 20th century, along with the existence of \"external\" galaxies, and soon after, the expansion of the [[universe]] seen in the recession of most galaxies from us. [[Cosmology]] made huge advances during the 20th century, with the model of the [[big bang]] heavily supported by the evidence provided by astronomy and physics, such as the [[cosmic microwave background radiation]], [[Hubble\'s Law]] and [[big bang nucleosynthesis|cosmological abundances of elements]].\n\n\'\'\'Pikeun dadaran nu leuwih lengkep ngeunaan sajarah astronomi, tempo [[sajarah astronomi]].\'\'\'\n\n[[image:ant.nebula.arp.600pix.jpg|thumb|right|250px|Stellar astronomy, Stellar Evolution: The [[Mz3|Ant planetary nebula]]. The ejection of gas, from the dying star at the center, has symmetrical patterns unlike the chaotic patterns expected from an ordinary explosion.]]\n\n== Tempo ogé ==\n* [[Ahli Astronomi|Ahli Astronomi jeung Astrofisik]]\n* [[Astronomical naming conventions]]\n* [[Daur]]\n* [[space science]]...\n* [[Timeline of black hole physics]]\n* [[Timeline of cosmology]]\n* [[Timeline of cosmic microwave background astronomy]]\n* [[Timeline of other background radiation fields]]\n* [[Timeline of galaxies, clusters of galaxies, and large scale structure]]\n* [[Timeline of the interstellar medium and intergalactic medium]]\n* [[Timeline of white dwarfs, neutron stars, and supernovae]]\n* [[Timeline of stellar astronomy]]\n* [[Timeline of solar astronomy]]\n* [[Timeline of solar system astronomy]]\n\n* [[Timeline of astronomical maps, catalogs, and surveys]]\n* [[Timeline of telescopes, observatories, and observing technology]]\n* [[Timeline of artificial satellites and space probes]]\n*[[International Astronomical Union]]\n*[[American Astronomical Society]]\n*[[Royal Astronomical Society]]\n*[[European Southern Observatory]]\n* [[Lambang astronomis]]\n\n==Pakakas astronomi==\n* [[Teleskop]]\n* [[Komputer]]\n* [[Kalkulator]]\n* [[Observatorium]]\n* [[Observatorium langit]]\n\n==Tumbu kaluar==\n===Organisasi===\n*[http://www.aavso.org/ American Association of Variable Star Observers]\n*[http://www.aas.org/ American Astronomical Society]\n*[http://www.astrosociety.org/ Astronomical Society of the Pacific]\n*[http://ciclops.lpl.arizona.edu/ Cassini Imaging Laboratory] - Stunning images of the planets taken by the Cassini exploratory spacecraft\n*[http://www.astro.cz/ Czech Astronomical Society]\n*[http://www.drastronomy.com/ Durham Region Astronomical Association]\n*[http://www.hawastsoc.org/ Hawaiian Astronomical Society]\n*[http://www.hia-iha.nrc-cnrc.gc.ca/ Herzberg Institute of Astrophysics]\n*[http://www.noao.edu/ National Optical Astronomy Observatories]\n*[http://www.nyaa-starfest.com/ North York Astronomical Association]\n*[http://open-site.org/Science/Astronomy/ Open Encyclopedia Project] - Astronomy Section.\n*[http://www.rasc.ca/ Royal Astronomical Society of Canada]\n*[http://www.ras.org.uk/ Royal Astronomical Society (UK)]\n*[http://www.rasnz.org.nz/ Royal Astronomical Society of New Zealand]\n*[http://www.slasonline.org/ Saint Louis Astronomical Society]\n*[http://www.popastro.com/ Society for Popular Astronomy (UK)]\n\n===Rujukan: Rumus jeung konstanta===\n* [http://www.jqjacobs.net/astro/astrofor.html Astronomy Formulas] \n* [http://www.jqjacobs.net/astro/astro.html Astronomical Constants Index]\n* [http://ads.harvard.edu/books/hsaa/ Zombeck\'s \'\'Handbook of Space Astronomy and Astrophysics\'\']\n\n===Tumbu kaluar===\n* [http://www.facts-and-figures.org/html/astronomy.php Situs astronomi pikeun guru] \n* [http://xxx.lanl.gov/ Los Alamos Astrophysics e-Print Database]\n* [http://antwrp.gsfc.nasa.gov/apod/ Gambar Astronomi Poé Ieu]\n* [http://www.phys-astro.sonoma.edu/BruceMedalists/ Bruce Medalists (annual astronomical award since 1898)]\n*[http://physics.unr.edu/grad/welser/astro/arab.html Astronomi Islam jeung Arab]\n\n[[af:Sterrekunde en Astrofisika]] [[ar:فلك]] [[bg:Астрономия]] [[bs:Astronomija i Astrofizika]] [[ca:Astronomia]] [[cs:Astronomie]] [[cy:Seryddiaeth]] [[da:Astronomi]] [[de:Astronomie]] [[el:Αστρονομία]] [[en:Astronomy]] [[eo:Astroscienco]] [[es:Astronomía y astrofísica]] [[et:Astronoomia]] [[eu:Astronomia]] [[fa:ستاره‌شناسی]] [[fi:Tähtitiede]] [[fr:Astronomie]] [[gl:Astronomía]] [[hi:खगोल शास्त्र]] [[hr:Astronomija i Astrofizika]] [[hu:Asztronómia és asztrofizika]] [[ia:Astronomia]] [[it:Astronomia]] [[ja:天文学]] [[ko:천문학]] [[la:Astronomia]] [[lt:Astronomija]] [[ms:Astronomi]] [[nds:Astronomie]] [[nl:Astronomie]] [[no:Astronomi]] [[pl:Astronomia]] [[pt:Astronomia]] [[ro:Astronomie şi astrofizică]] [[ru:Астрономия]] [[simple:Astronomy]] [[sl:Astronomija in astrofizika]] [[sq:Astronomia]] [[sr:Астрономија и астрофизика]] [[sv:Astronomi]]\n[[sw:Unajimu]] [[ta:வானியல்]] [[th:ดาราศาสตร์]] [[tl:Astronomiya]]\n[[tr:Astronomi]] [[vo:Stelav]] [[zh-cn:天文学]] [[zh-tw:天文學]]\n\n[[Category:Élmu alam]]\n[[Category:Astronomi]]','',41,'Djoko','20050303093949','',0,0,1,0,0.406852615255,'20050303093949','79949696906050'); INSERT INTO cur VALUES (813,0,'Matematik','\'\'\'Matematik\'\'\' sacara umum dihartikeun salaku ulikan [[pola]] struktur, [[parobahan]], jeung [[ruang]]; jéntréna, urang bisa nyebut ulikan ngeunaan \'gambar jeung angka\'. Tina jihat [[formal]], disebut salaku panalungtikan ngeunaan [[struktur teu nyata]] nu ditangtukeun sacara [[aksioma]]tis migunakeun [[logika simbolik|logika]] jeung [[lambang matematis]]; sawangan séjén dijéntrékeun dina [[Filosofi matematik]]. Matematik meunang ditingali salaku basa simpel tina basa tulisan jeun ucapan, kalawan aturan jeun tatabahasa anu jelas katut pasti, for the purpose of describing and exploring physical and conceptual relationships.\n\nStruktur nu spésifik nu ditalungtik ku para matematikawan mun dicukcruk sasakalana sok kapanggih na [[élmu alam]], pangmindengna [[fisika]], tapi [[matematikawan]] ogé nangtukeun jeung nalungtik struktur pikeun alesan-alesan nu murni pikeun dunya matematik, sabab struktur éta nyadiakeun, misalna, generalisasi panghiji pikeun sababaraha subwidang, atawa pakakas pikeun itung-itungan biasa. Pamungkas, loba matematikawan ngulik wewengkon ukur pikeun alesan éstétik, némbongkeun matematik salaku hiji wujud [[seni]] batan salaku hiji élmu terapan atawa praktis. Sababaraha matematikawan mikaresep gelar \"\'\'the Queen of Sciences\'\'\" pikeun widangna.\n\nMatematik kadang diringkes jadi \'\'\'math\'\'\' (na \'\'[[American English]]\'\') atawa \'\'\'maths\'\'\' (na \'\'[[British English]]\'\'). Mun ceuk barudak sakola urang, matematik téh sok disebut ogé \'\'\'maté\'\'\'.\n\n== Ihtisar jeung sajarah matematik ==\n\'\'Pikeun leuwih lengkep, tempo artikel [[sajarah matematik]].\'\'\n\nKecap \"matematik\" datangna tina [[Basa Yunani]] μάθημα (\'\'máthema\'\') nu hartina \"élmu, pangaweruh, atawa diajar\"; μαθηματικός (\'\'mathematikós\'\') nu hartina \"\'\'fond of learning\'\'\".\n\nDisiplin utama dina matematik nyelengceng tina kabutuh nyieun rupa-rupa itungan dina widang bilintik/usaha, pikeun ngukur taneuh jeung pikeun ngira-ngira kajadian-kajadian astronomis. Tilu pangabutuh ieu sacara kasar bisa dipatalikeun ka rupa-rupa bagbagan matematik nu lega kana ulikan struktur, spasi (rohangan), jeung parobahan.\n\nUlikan ngeunaan struktur dimimitian ku [[wilangan]], mimiti nu geus pada mikawanoh [[wilangan natural]] jeung [[wilangan buleud]] sarta operasi [[aritmatik]]na, nu dicatetkeun dina [[aljabar]] dasar. Sipat wilangan nu leuwih jero diulik dina [[tiori wilangan]]. Panalungtikan ngeunaan métode-métode pikeun ngudar/meupeuskeun \'\'persamaan\'\' ngawujud jadi widang [[aljabar abstrak]], nu, di antara nu séjén, ngulik [[ring (mathematics)|rings]] jeung [[field (mathematics)|field]]s, struktur nu ngajabarkeun sifat-sifat nu dipibanda ku angka-anka anu geus umum. The physically important concept of [[vector (spatial)|vector]]s, generalized to [[vector space]]s and studied in [[linear algebra]], belongs to the two branches of structure and space.\n\nUlikan ngeunaan rohangan dimimitian ku [[géometri]], kahiji [[géométri Euclid]] jeung [[trigonométri]] dina rohangan tilu diménsi, tapi kadieunakeun dijieun leuwih umum ku ulikan [[Non-euclidean geometry|non-Euclidean geometries]] nu ngabogaan pangaruh nu utama dina [[general relativity]]. Sababaraha masalah klasik ngeunaan [[ruler and compass constructions]] ahirna bisa dijawab ku [[Galois theory]]. Widang modern ngeunaan [[differential geometry]] jeung [[algebraic geometry]] ngalegakeun geometri ka arah anu rada beda: geometri differensial nekenkeun konsep fungsi, [[fiber bundle]]s, [[derivative]]s, [[smooth function|smoothness]] jeung arah, sedengkeun aljabar geometri naliti wangun geometri anu dijieun tina jawaban sasaruaan (persamaan) sakumpulan [[polynomial]]. [[group (mathematics)|Group theory]] naliti konsep simetri sacara abstrak jeung mere kaitan antra ulikan rohangan jeung ulikan struktur. [[Topology]] ngaitkeun ulikan rohangan jeung ulikan parobahan ku alatan nekenkeun kana konsep [[continuous|continuity]]. \n\nBisa ngarti jeung ngajelaskeun parobahan dina kuantitas nu ka ukur mangrupakeun salah sahiji tema elmu alam. [[Kalkulus]] mangrupakeun salah sahiji alat nu utama pikeun ngajelaskeun eta perkara. Konsep nu utama pikeun nerangkeun parobahan variabel nyaeta ku konsep [[Fungsi (matematik)|fungsi]]. Loba masalah anu bisa diterangkeun sacara alami ku kaitan antara kuantitas jeung laju parobahannana, metoda pikeun ngajawab hal ieu di ulik dina widang [[differential equations]]. Wilangan anu dipake pikeun nerangkeun kasinambungan kuantitas nyeta wilangan [[real numbers]], ulikan nu taliti ngeunaan sifat wilangan real jeung fungsi nu ngabogaan niley real disebut [[real analysis]]. Ku sababaraha alesan, wilangan real perlu dilegakeun ka [[complex number]]nu di ulik dina widang [[complex analysis]]. [[Functional analysis]] nekenkeun ulikanna kana(typically infinite-dimensional) rohangan fungsi, nu mere dadasar pikeun [[quantum mechanics]] diantaran nu sejenna. Loba kajadian di alam nu bisa dijelaskeun ku [[dynamical system]]s jeung [[chaos theory]] ngurus sistim anu kalakuanna mengpar tina kalakuan nu galib.\n\nKu perluna ngajentrekeun jeung naliti dadasar matematik, widang [[tiori set]], [[logika matematik]] jeung [[tiori model]] dikembangkeun. \n\nNalika[[komputer]] mimiti katimu, sababaraha konsep tioritis anu utama diwangun ku matematikawan, nu ngalahirkeun widang [[tiori itungan]], [[tiori itungan komplek]], [[tiori informasi]] jeung [[tiori informasi algoritma]]. Loba pamasalahan ieu nu ayeuna di taliti dina widang [[sain komputer]] tioritis. \n[[Matematik Diskrit]] nyaeta ngaran anu galib pikeun widang matematika anu kapake dina elmu komputer.\nSalah sahiji widang anu penting dina [[matematika terapan]] nyaeta [[statistik]], nu ngagunakeun [[tiori kamungkinan]] pikeun jadi alat nu mampuh nerangkeun, nganalisis jeung nyawang kajadian-kajadian nu bakal tumiba. Elmu ieu dipake ampir ku sakabeh elmu alam. [[analisis angka]] naliti metode anu efisien mecahkeun(meupeuskeun???) rupa-rupa masalah matematika sacara numerik ngagunakeun komputer dimana kasalahan ngitung oge dipertimabangkeun.\n\n== Jejer-jejer na matematik ==\n\nDi handap ieu béréndélan subwidang jeung jejer-jejer nu ngagambarkeun salasahiji sawangan organisasional matematik.\n\n=== Kuantitas ===\nSacara umum, jejer jeung pamendak némbongkeun ukuran-ukuran éksplisit ukuran wilangan atawa sét, atawa cara-cara pikeun manggihan pangukuran-pangukuran nu sarupa.\n\n:[[Wilangan]] -- [[Wilangan natural]] -- [[Pi]] -- [[Integer]]s -- [[Wilangan rasional]] -- [[Wilangan real]] -- [[Wilangan kompléks]] -- [[Wilangan hiperkompléks]] -- [[Quaternion]]s -- [[Octonion]]s -- [[Sedenion]]s -- [[Hyperreal number]]s -- [[Surreal number]]s -- [[Ordinal number]]s -- [[Cardinal number]]s -- [[P-adic number|p-adic number]]s -- [[Integer sequence]]s -- [[Konstanta matematik]]s -- [[Number names]] -- [[Infinity]] -- [[Base (math)|Base]]\n\n=== Parobahan ===\nJejer-jejer di handap méré jalan pikeun ngukur parobahan dina rumus matematis jeung parobahan antarwilangan.\n\n:[[Aritatik]] -- [[Kalkulus]] -- [[Kalkulus Véktor|Kalkulus véktor]] -- [[Analisis matematis|Analisis]] -- [[Differential equation]]s -- [[Sistem dinamis jeung chaos theory]] -- [[Béréndélan rumus]]\n\n=== Struktur ===\nRangkadak dahan matematik nu aya di handap nangtukeun ukuran jeung simétri wilangan, sarta rupa-rupa wangun.\n\n:[[Aljabar abstrak]] -- [[Téori wilangan]] -- [[Géométri aljabar]] -- [[group (mathematics)|Group theory]] -- [[Monoid]]s -- [[Analisis matematis|Analisis]] -- [[Topologi]] -- [[Aljabar liniér]] -- [[Téori grafik]] -- [[Aljabar universal]] -- [[Téori kategori]] -- [[Order theory]]\n\n=== Space ===\nThese topics tend to quantify a more visual approach to mathematics than others.\n\n:[[Topology]] -- [[Geometry]] -- [[Trigonometry]] -- [[Algebraic geometry]] -- [[Differential geometry]] -- [[Differential topology]] -- [[Algebraic topology]] -- [[Linear algebra]] -- [[Fractal geometry]]\n\n=== [[Matematik Diskrit]] ===\nSuch topics deal with branches of mathematics with objects that can only take on specific, separated values.\n\n:[[Combinatorics]] -- [[Naive set theory]] -- [[Probability]] -- [[Computation|Theory of computation]] -- [[Finite mathematics]] -- [[Cryptography]] -- [[Graph theory]] -- [[Game theory]]\n\n=== [[Matematik terapan]] ===\nWidang-widang di handap nerapkeun pangaweruh matematik dina masalah-masalah kahirupan nyata.\n\n:[[Mékanik]] -- [[Analisis numeris]] -- [[Optimization (mathematics)|Optimization]] -- [[Probability]] -- [[Statistik]] -- [[Financial mathematics]]\n\n=== Famous theorems and conjectures ===\nThese theorems have interested mathematicians and non-mathematicians alike.\n\n:[[Fermat\'s last theorem]] -- [[Goldbach\'s conjecture]] -- [[Twin Prime Conjecture]] -- [[Gödel\'s incompleteness theorem]]s -- [[Poincaré conjecture]] -- [[Cantor\'s diagonal argument]] -- -- [[Four color theorem]] -- [[Zorn\'s lemma]] -- [[Euler\'s identity]] -- [[Scholz Conjecture]] -- [[Church-Turing thesis]]\n\n=== Important theorems ===\nThese are theorems that have changed the face of mathematics throughout history.\n\n:[[Riemann hypothesis]] -- [[Continuum hypothesis]] -- [[Complexity classes P and NP|P=NP]] -- [[Pythagorean theorem]] -- [[Central limit theorem]] -- [[Fundamental theorem of calculus]] -- [[Fundamental theorem of algebra]] -- [[Fundamental theorem of arithmetic]] --[[Fundamental theorem of projective geometry]] -- [[classification theorems of surfaces]] -- [[Gauss-Bonnet theorem]]\n\n=== Foundations and methods ===\nSuch topics are approaches to mathematics, and influence the way mathematicians study their subject.\n\n:[[Philosophy of mathematics]] -- [[Mathematical intuitionism]] -- [[Mathematical constructivism]] -- [[Foundations of mathematics]] -- [[Set theory]] -- [[Symbolic logic]] -- [[Model theory]] -- [[Category theory]] -- [[Theorem-proving]] -- [[Logic]] -- [[Reverse Mathematics]] -- [[Table of mathematical symbols]]\n\n=== Sajarah jeung jagat matematikawan ===\n:[[Sajarah matematik]] -- [[Timeline of mathematics]] -- [[Matematikawan]] -- [[Fields Medal|Fields medal]] -- [[Abel Prize]] -- [[Millennium Prize Problems|Millennium Prize Problems (Clay Math Prize)]] -- [[International Mathematical Union]] -- [[Mathematics Competitions|Mathematics competitions]] -- [[Lateral thinking]]\n\n=== Matematik jeung widang séjénna ===\n:[[Matematik jeung arsitéktur]] -- [[Matematik jeung atikan]] -- [[Mathematics of musical scales]]\n\n=== Mathematical coincidences ===\n\n\n\n:[[List of mathematical coincidences]]\n\n== Pakakas matematis ==\n\nHeubeul:\n* [[Abacus]]\n* [[Napier\'s bones]], [[Slide Rule]]\n* [[Jidar]] jeung [[Kompas]]\n* [[Mental calculation]]\n\nAnyar:\n* [[Kalkulator]] jeung [[komputer]]\n* [[Programming language]]s\n* [[Computer algebra system]]s ([[List of abstract algebra topics#computer algebra|listing]])\n* [[Internet shorthand notation]]\n* [[software]] [[analisis statistis]]\n** [[SPSS]]\n** [[SAS]]\n\n== Quotes ==\n\nReferring to the axiomatic method, where certain properties of an (otherwise unknown) structure are assumed and consequences thereof are then logically derived, [[Bertrand Russell]] said:\n:\'\'Mathematics may be defined as the subject in which we never know what we are talking about, nor whether what we are saying is true.\'\'\n\nThis may explain why [[John Von Neumann]] once said:\n:\'\'In mathematics you don\'t understand things. You just get used to them.\'\'\n\nAbout the beauty of Mathematics, [[Bertrand Russell]] said in \'\'Study of Mathematics\'\':\n:\'\'Mathematics, rightly viewed, possesses not only truth, but supreme beauty -- a beauty cold and austere, like that of sculpture, without appeal to any part of our weaker nature, without the gorgeous trappings of painting or music, yet sublimely pure, and capable of a stern perfection such as only the greatest art can show. The true spirit of delight, the exaltation, the sense of being more than Man, which is the touchstone of the highest excellence, is to be found in mathematics as surely as poetry.\'\'\n\nElucidating the symmetry between the creative and logical aspects of mathematics, W.S. Anglin observed, in \'\'Mathematics and History\'\':\n:\'\'Mathematics is not a careful march down a well-cleared highway, but a journey into a strange wilderness, where the explorers often get lost. Rigour should be a signal to the historian that the maps have been made, and the real explorers have gone elsewhere.\'\'\n\n== Mathematics is not... ==\n* [[Numerology]]\n\n== Bibliografi ==\n\n*\'\'\'Courant, R. and H. Robbins\'\'\', \'\'What Is Mathematics?\'\' ([[1941]]); \n*\'\'\'Davis, Philip J. and Hersh, Reuben\'\'\', \'\'The Mathematical Experience\'\'. Birkhäuser, Boston, Mass., [[1980]]. A gentle introduction to the world of mathematics.\n*\'\'\'Gullberg, Jan\'\'\', \'\'Mathematics--From the Birth of Numbers\'\'. W.W. Norton, [[1996]]. Ihtisar matematik énsiklopédis nu dipedar maké basa nu jéntré tur basajan.\n*\'\'\'Hazewinkel, Michiel (ed.)\'\'\', \'\'Encyclopaedia of Mathematics\'\'. Kluwer Academic Publishers [[2000]]. Vérsi tarjamah énsiklopédi Matematik Soviet nu dilegaan dina sapuluh jilid, karya nu panglengkepna tur pangmundelna. Ogé aya dina rupa CD-ROM.\n*\'\'\'Kline, M.\'\'\', \'\'Mathematical Thought from Ancient to Modern Times\'\' ([[1973]]);\n\n== Tumbu kaluar ==\n* Rusin, Dave: [http://www.math-atlas.org/ \'\'The Mathematical Atlas\'\']. A guided tour through the various branches of modern mathematics.\n* [http://planetmath.org/ \'\'Planet Math\'\']. An online math encyclopedia under construction, focusing on modern mathematics. Uses the [[GFDL]] license, allowing article exchange with Wikipedia. Uses [[TeX]] markup.\n* Weisstein, Eric et al.: [http://www.mathworld.com/ \'\'World of Mathematics\'\']. An online encyclopedia of mathematics, focusing on classical mathematics.\n* Stefanov, Alexandre: [http://us.geocities.com/alex_stef/mylist.html \'\'Textbooks in Mathematics\'\']. A list of free online textbooks and lecture notes in mathematics.\n* A mathematical [[thesaurus]] maintained by the [http://nrich.maths.org/ NRICH] project at the [[University of Cambridge]] (UK), [http://thesaurus.maths.org/ \'\'Connecting Mathematics\'\']\n* Bogomolny, Alexander: [http://www.cut-the-knot.org/ \'\'Interactive Mathematics Miscellany and Puzzles\'\']. A huge collection of articles on various math topics with more than 400 illustrated with Java applets.\n* [http://www.mathforge.net/ \'\'Mathforge\'\']. A news-blog with topics ranging from popular mathematics to popular physics to computer science and education.\n* [http://metamath.org/ \'\'Metamath\'\']. A site and a language, that formalize math from its foundations.\n\n[[Category:Matematik]]\n[[Category:Tepas]]\n\n[[af:Wiskunde]] [[als:Mathématiques]] [[ar:رياضيات]] [[bg:Математика]] [[bs:Matematika]] [[ca:Matemàtiques]] [[co:Matematica]] [[cs:Matematika]] [[da:Matematik]] [[de:Mathematik]] [[et:Matemaatika]] [[el:Μαθηματικά]] [[en:Mathematics]] [[es:Matemáticas]] [[eo:Matematiko]] [[fi:Matematiikka]] [[fr:Mathématiques]] [[fy:Wiskunde]] [[ga:Matamaitic]] [[gd:Matamataig]] [[gl:Matemática]] [[he:מתמטיקה]] [[hr:Matematika]] [[hu:Matematika]] [[ia:Mathematica]] [[it:Matematica]] [[ja:数学]] [[ko:수학]] [[la:Mathematica]] [[lt:Matematika]] [[nl:Wiskunde]] [[no:Matematikk]] [[pl:Matematyka]] [[pt:Matemática]] [[ro:Matematic%C4%83]] [[ru:%D0%9C%D0%B0%D1%82%D0%B5%D0%BC%D0%B0%D1%82%D0%B8%D0%BA%D0%B0]] [[simple:Mathematics]] [[sk:Matematika]] [[sl:Matematika]] [[sr:Математика]] [[sv:Matematik]]\n[[sw:Hisabati]] [[ta:கணிதம்]] [[th:คณิตศาสตร์]] [[tr:Matematik]] [[uk:Математика]] [[zh-cn:%E6%95%B0%E5%AD%A6]] [[zh-tw:數學]]','',3,'Kandar','20050203101936','',0,0,0,0,0.683604206277,'20050221030719','79949796898063'); INSERT INTO cur VALUES (814,0,'Élmu_bumi','\'\'\'Elmu bumi\'\'\' (biasa oge disebut \'\'\'geoscience\'\'\' atawa \'\'\'the geosciences\'\'\'), mangrupakeun salah sahiji widang élmu anu nalungtik [[Mayapada]]. It is arguably a special case in [[planetary science]], being the only known [[life]]-bearing planet. There are both [[reductionist]] and [[holistic]] approaches to Earth science. The major historic disciplines use physics, mathematics, chemistry, and biology to build a quantitative understanding of the principal areas or \'\'[[Earth\'s spheres|spheres]]\'\' of the Earth system: \n\n*\'\'\'[[Géologi]]\'\'\' covers the [[Rock (geology)|rocky]] parts of the Earth (or [[lithosphere]]) including the planet\'s core, mantle and crust. Subdisiplin pentingna di antarana [[géofisik]], [[géokimia]], [[paléontologi]], [[mineralogi]], jeung [[sédiméntologi]].\n\n*\'\'\'[[Oceanography]]\'\'\' and \'\'\'[[Limnology]]\'\'\' describe respectively the marine and freshwater domains of the [[cai|watery]] parts of the Earth (or [[hydrosphere]]). Major subdisciplines are [[Physical oceanography|physical]], [[Chemical oceanography|chemical]], and [[Biological oceanography|biological]] oceanography.\n\n*\'\'\'[[Atmospheric sciences]]\'\'\' cover the [[gas|gaseous]] parts of the Earth (or [[Earth\'s atmosphere|atmosphere]]).\n\n*\'\'\'[[Glaciology]]\'\'\' covers the [[ice|icy]] parts of the Earth (or [[cryosphere]])\n\nHowever, given the numerous interactions between the [[Earth\'s spheres|spheres]] many modern fields take an interdisciplinary approach and thus do not sit comfortably in this scheme:\n\n*\'\'\'[[Biogéokimia]]\'\'\' follows the cycling of elements through the [[Earth\'s spheres|spheres]] mediated by biological and geological processes, and especially their distribution and fluxes between \'\'reservoirs\'\'.\n\n*\'\'\'[[Paleoceanography]]\'\'\' and \'\'\'[[Paleoclimatology]]\'\'\' use the properties of [[sediment]]s, [[ice core]]s, or biological material to infer past states of the ocean, atmosphere or climate.\n\n\nFurthermore, other modern disciplines known collectively as \'\'\'[[Earth system science]]\'\'\' approach the entire Earth as a [[Systems thinking|system]] in its own right, which evolves as a result of \'\'[[positive feedback|positive]]\'\' and \'\'[[negative feedback]]s\'\' between constituent systems: \n\n*\'\'\'[[Meteorology]]\'\'\' describes, explains and predicts the [[weather]] based on the interaction of principally the ocean and atmosphere.\n\n*\'\'\'[[Climatology]]\'\'\' describes and explains the [[climate]] in terms of the interaction of the litho-, hydro-, atmo-, cryo-, and bio- spheres.\n\n*\'\'\'[[Gaia theory (science)|Gaia theories]]\'\'\' explain the behaviour of the Earth system in terms of the influence of the biosphere. \n\nSakumaha élmuwan séjénna, élmuwan nu ngulik marcapada nerapkeun [[métode ilmiah]]: formulate hypotheses after observation of and gathering data about natural phenomena and then test those hypotheses. In earth science, data usually plays a critical role in testing and formulating hypotheses. The [[Systems thinking|systems approach]], enabled by the combined use of computer models as hypotheses tested by global [[Earth observation satellite|satellite]] and ship-board data, is increasingly giving scientists the ability to explain the past and possible future behaviour of the Earth system.\n\n== Partial list of the major Earth Science topics ==\n\n=== Géologi ===\n\n* [[Cataclysmic Geology]]\n* [[Economic geology]]\n* [[Engineering geology]]\n* [[Environmental geology]]\n* [[Gemology]]\n* [[Géokimia]]\n* [[Geochronology]]\n* [[Geomagnetic]]s\n* [[Géomorfologi]]\n* [[Geophysics]]\n* [[Géostatistik]]\n* [[Géotéhnik]]\n* [[Historical geology]]\n* [[Mantle plumes]]\n* [[Medical geology]]\n* [[Mineralogi]] \n* [[Mining]]\n* [[Paleontology]]\n* [[Palynology]]\n* [[Pedology]]\n* [[Petrology]]\n* [[Planetary geology]]\n* [[Physical geodesy]]\n* [[Physical geology]]\n* [[Petroleum geology]]\n* [[Quaternary geology]]\n* [[Sedimentology]]\n* [[Seismology]]\n* [[Stratigraphy]]\n* [[Structural geology]]\n* [[Vulkanologi]]\n\n=== Oséanografi ===\n\n* [[Physical oceanography]]\n* [[Chemical oceanography]]\n* [[Biological oceanography]]\n* [[Paleoceanography]]\n* [[Marine Geology]]\n* [[Marine Geophysics]]\n\n=== Géografi ===\n* [[Human geography]]\n* [[Physical geography]]\n* [[Paleogeography]]\n\n=== Limnology ===\n* \'\'\'[[Limnology]]\'\'\'\n\n=== Glaciology ===\n* \'\'\'[[Glaciology]]\'\'\'\n\n=== Élmu Atmosfir ===\n* \'\'\'[[Élmu Atmosfir]]\'\'\'\n\n=== Systems/multidisciplinary ===\n\n* [[Earth system science]]\n* [[Meteorology]]\n* [[Climatology]]\n* [[Paleoclimatology]]\n* [[Gaia theory (science)|Gaia theories]]\n\n[[Category:Élmu bumi]]\n[[Category:Élmu alam]]\n[[Category:daptar jejer]]\n\n[[ar:عِلْمُ تربة]] [[bg:Науки за Земята]] [[bs:Geologija]] [[ca:Ciències De La Terra]] [[de:Geowissenschaften]] [[en:Earth science]] [[es:Ciencias de la tierra]] [[eo:Tersciencoj]] [[fr:Sciences de la Terre]] [[fy:Ierdwittenskip]] [[ko:지구과학]] [[hr:Geologija]]\n[[it:Scienze della Terra]] [[he:מדעי כדור הארץ]] [[ms:Sains bumi]] [[nl:Aardwetenschappen]] [[ja:地球科学]] [[pl:Nauki o Ziemi]] [[pt:Ciências da Terra]] [[ro:Ştiinţele Pământului]] [[sl:Znanosti o Zemlji]] [[vi:Khoa học về đất]] [[zh-cn:地球科学]] [[simple:Éarth science]]','',3,'Kandar','20040818081837','',0,0,0,0,0.73214835568,'20040818081837','79959181918162'); INSERT INTO cur VALUES (815,0,'Internét','Dina harti umum, \'\'\'internét\'\'\' (maké aksara leutik \"i\", singgetan tina \'\'\'inter-network\'\'\') ngarupakeun [[jaringan komputer]] nu nyambungkeun sababaraha jaringan. Salaku hiji istilah nu mandiri, \'\'\'Internét\'\'\' ngarupakeun sistim [[komputer]] (kaasup [[informasi]] jeung layanan nu disadiakeun pikeun nu marakéna) umum nu kasambungkeun sacara internasional migunakeun the [[TCP/IP]] suite of [[packet switching]] [[communications protocol]]s. Thus, the largest internet is called simply \"the\" Internet. Seni nyambungkeun jaringan-jaringan ku cara ieu disebutna \'\'[[internetworking]]\'\'.\n\nDina basa sapopoé, \'\'Internét\'\' kadang nujul ka layanan \'\'[[WWW|World Wide Web]]\'\', [[surélék|surat éléktronik]], jeung \'\'[[ngobrol online]]\'\' nu aya na Internét.\n\n== Lahirna Internét ==\n\'\'Artikel utama: [[Sajarah Internét]]\'\'\n\nNgacambahna bibit Internét dimimitian dina taun [[1969]] ku ayana [[ARPANET]] nu diwangun ku \'\'Advanced Research Projects Agency\'\' (ARPA), Departemén Pertahanan [[Amérika Sarikat]]. \n\nSababaraha panalungtikan munggaran nu nyumbang ka ARPANET nyéta gawé dina desentralisasi jaringan, [[queueing theory]], jeung \'\'packet switching\'\'.\n\nTanggal [[1 January]], [[1983]], ARPANET ngarobah inti protokol jaringanana tina [[Network Control Program|NCP]] ka TCP/IP, nandakeun awal Internét sakumaha nu ayeuna urang apal.\n\nLéngkah penting séjén dina ngembangna Internét nyaéta ku ayana [[National Science Foundation|National Science Foundation\'s]] (NSF), [[NSFNet]], taun [[1986]]. Important disparate networks that have successfully been accommodated within the Internet include [[Usenet]], [[Fidonet]], and [[Bitnet]].\n\nDuring the [[1990s]], the Internet successfully accommodated the majority of previously existing computer networks. This growth is often attributed to the lack of central administration, which allows organic growth of the network, as well as the non-proprietary nature of the internet protocols, which encourages vendor interoperability and prevents one company from exerting control over the network.\n\n== Internét kiwari ==\n\nInternét diadegkeun babarengan ku kontrak komérsil bi- atawa multilateral (for example [[peering agreement]]s) and by technical specifications or [[Communications protocol|protocol]]s that describe how to exchange [[data]] over the network. These protocols are formed by discussion within the Internet Engineering Task Force ([[IETF]]) and its working groups, which are open to public participation and review. These committees produce documents that are known as [[Request for Comments]] documents (RFCs). Some RFCs are raised to the status of [[Internet Standard]] by the Internet Architecture Board ([[Internet Architecture Board|IAB]]).\n\nSome of the most used protocols in the [[Internet protocol suite]] are [[Internet Protocol|IP]], [[Transmission Control Protocol|TCP]], [[User Datagram Protocol|UDP]], [[Domain Name System|DNS]], [[Point-to-Point Protocol|PPP]], [[Serial line IP|SLIP]], [[ICMP]], [[POP3]], [[IMAP]], [[Simple Mail Transfer Protocol|SMTP]], [[HTTP]], [[HTTPS]], [[Secure shell|SSH]], [[Telnet]], [[File transfer protocol|FTP]], [[LDAP]], and [[Secure Sockets Layer|SSL]].\n\nSome of the popular services on the Internet that make use of these protocols are [[e-mail]], [[Usenet]] newsgroups, [[file sharing]], the [[World Wide Web]], [[Gopher protocol|Gopher]], [[session|session access]], [[WAIS]], [[finger protocol|finger]], [[Internet relay chat|IRC]], [[MUD]]s, and [[MUSH]]s. Of these, e-mail and the World Wide Web are clearly the most used, and many other services are built upon them, such as [[mailing list]]s and [[web log]]s. The internet makes it possible to provide real-time services such as [[web radio]] and [[webcast]]s that can be accessed from anywhere in the world.\n\nSome other popular services of the Internet were not created this way, but were originally based on proprietary systems.\nThese include [[Internet relay chat|IRC]], [[ICQ]], [[AOL Instant Messenger|AIM]], [[CDDB]], and [[Gnutella]].\n\nThere have been many analyses of the Internet and its structure.\nFor example, it has been determined that the Internet IP routing structure\nand hypertext links of the World Wide Web are examples of [[scale-free network]]s.\n\nSimilar to how the commercial Internet providers connect via [[peering|Internet exchange points]], research networks tend to interconnect into large subnetworks such as:\n*[[GEANT]]\n*[[Internet2]]\n*[[Little Global Ring Network for Advanced Application Development|Little GLORIAD]]\n\nThese in turn are built around relatively smaller networks such as:\n*[[JANET]]\n*[[HEAnet]]\n*[[CARNet]]\n*[[ARNES]]\n\n== Budaya Internet ==\n\nInternét ogé mibanda pangaruh nu nyosok jero ka na [[pangaweruh]] jeung sawangan dunya. Through [[keyword]]-driven [[Internet research]], using [[search engines]], like [[Google]], millions worldwide have easy, instant access to a vast amount and diversity of online information. Dibandingkeun jeung [[énsiklopédi]] sarta [[pabukon]] tradisional, Internét mintonkeun hiji desentralisasi informasi jeung data nu dadakan sakaligus ékstrim.\n\nBasa nu utama dipaké dina komunikasi di Internét umumna [[Basa Inggris|Inggris]], dumasar ka bibit buitna, kailaharan basa program software, jeung sabab kalemahan komputer heubeul dina narima karakter-karakter lian ti [[alfabét]] kulon.\n\nThe net has grown enough in recent years, though, that sufficient native-language content for a worthwhile experience is available in most developed countries. However, some glitches such as [[mojibake]] still remain.\n\nInternét geus nulungan loba kumpulan jalma pikeun ngahiji jeung silih panggihan.\n\nTempo ogé: [[Internet dynamics]], [[Nétikét]], [[Internet friendship]], [[Internet troll|Trolls and trolling]], [[Flaming]], [[Cybersex]], [[Hacktivism]] atawa [[Hacker culture]], [[Internet humor]], [[Internet slang]], jeung [[Internet art]].\n\n== Isu Hukum jeung moral ==\n\nThere is public concern about the [[Internet]] stemming from some of the controversial material it contains. [[Copyright infringement]], [[internet pornography|pornography]] and [[pedophilia]], [[identity theft]], and [[hate speech]] are available and difficult to regulate (see [[cyber law]]). \"Sex\" remains one of the most frequently searched terms on many Internet [[search engine]]s. Some of the concerns, which many argue are not rationally based, have approached a level of [[moral panic]] similar to the British one over [[Video nasty|video nasties]] in the [[1980s]].\n\nThe Internet has been cited as a factor in a number of deaths. [[Brandon Vedas]] died after overdosing on a mixture of legal and illegal drugs while other [[Internet Relay Chat|IRC]] chatters egged him on. [[Shawn Woolley]] shot himself after his life was ruined by an addiction to [[Everquest]], according to his mother. Bernd-Jurgen Brandes was stabbed to death and eaten by [[Armin Meiwes]] after responding to an Internet advertisement requesting a \"well-built male prepared to be slaughtered and then consumed.\"\n\n== Asup ka Internét ==\nCara akses Internét nu umum digunakeun di imah-imah nyaeta [[Dial-up access|dial-up]] jeung [[Broadband Internet access|broadband]].\n\n[[Public place]]s nu ngagunakeun internet kaasup [[libraries]] jeung [[Internet cafe]]s, where computers with Internet connections are available. There are also Internet access points in public places like airport halls, sometimes just for brief use while standing. Various terms are used, such as \"public Internet kiosk\", \"public access terminal\", \"web [[payphone]]\".\n\n[[Wi-Fi]] provides wireless access to the Internet. [[Hotspot]]s providing such access include [[Wi-Fi#Commercial Wi-Fi|Wifi-cafes]], where one needs to bring one\'s own wireless-enabled devices such as a [[notebook]] or [[Personal Digital Assistant|PDA]]. These services may be free to all, free to customers only, or fee-based. A hotspot need not be limited to a confined location. Whole campuses and parks have been enabled, even an entire downtown area. Grassroots efforts have led to [[wireless community network]]s.\n\nAdvantages of using one\'s own computer include more upload and download possibilities, using one\'s favorite browser and browser settings (customization may be disabled on a public computer), and integrating activities on the Internet and on one\'s own computer, using one\'s own programs and data. (Using public computers one can use one\'s email box as a storage area for data. For programs one may do the same, but the size of the mailbox and restrictions on the public computer limit the possibilities of running one\'s own programs. Another option is remotely hosted files that can be accessed from any Internet-connected machine. Companies such as Apple offer services that allow users to upload files, as a sort of \"virtual drive\".)\n\nCountries with particularly good Internet access include [[South Korea]], where 50% of the population has broadband access, [[Sweden]], [[Canada]] (where 61,6% of households use the Internet [http://www.statcan.ca/english/Pgdb/arts56a.htm]) and [[Internet access in the United States|the United States]]. [http://cyberatlas.internet.com/big_picture/geographics/article/0,,5911_2174111,00.html]\n\n==Tumbu jeung réferénsi==\n\n===Réferénsi===\n*[http://www.tjm.org/rebuildnyc/articles/2001-09-29_Jon-Ipplito_Dont-Blame-the-Internet.htm Don\'t Blame the Internet] - from the [[Washington Post]]\n*[http://www.jsonline.com/news/state/mar02/31536.asp Death of a Game Addict]\n*[http://www.guardian.co.uk/germany/article/0,2763,1098905,00.html German internet cannibal begins murder trial]\n\n=== Tempo ogé ===\n*[[List of Internet topics]]\n*[[bogon filtering]]\n*[[Catenet]]\n*[[extranet]]\n*[[Internet Archive]]\n*[[intranet]]\n*[[NANOG]]\n*[[Minitel]], a [[France|French]] predecessor to the Internet\n*[[Network Mapping]]\n*[[Open Directory Project]]\n*[[WebQuest]]\n*[[Webstacle]]\n*[[Web browser]]\n*[[Web hosting]]\n\n=== Tumbu kaluar ===\n*[http://www.worldofends.com/ \'\'World of Ends, What the Internet Is and How to Stop Mistaking It for Something Else\'\' by Doc Searls and David Weinberger]\n*[http://www.isoc.org/ The Internet Society (ISOC)] \n*[http://research.lumeta.com/ches/map/ Internet Mapping Project]\n*[http://www1.ietf.org/mail-archive/ietf/Current/msg18554.html TCP/IP switchover anniversary]\n*RFC 801, planning the TCP/IP switchover\n*[http://www.peepo.co.uk peepo a graphic portal for people with low literacy]\n*[http://www.netz-tipp.de/languages.html Web content by language]\n* Access and usage statistics: [http://cyberatlas.internet.com/big_picture/geographics/article/0,,5911_151151,00.html], [http://cyberatlas.internet.com/big_picture/traffic_patterns/article/0,,5931_3099471,00.html], [http://news.earthweb.com/stats/print.php/3096031], [http://banners.noticiasdot.com/termometro/boletines/docs/consultoras/idate/2003/idate_244.pdf] (pdf)\n*[http://www.glreach.com/globstats/index.php3 Access at home, by native language]\n*[http://www.dmoz.org/Computers/Internet/ Internet Directory @ dmoz]\n*[http://www.fourmilab.ch/documents/digital-imprimatur/ John Walker: The Digital Imprimatur]\n*[http://www.addressingtheworld.info addressingtheworld.info] - website accompanying a book (ISBN 0742528103) on the history of DNS\n*[http://en.wikipedia.org/wiki/Telegraph Hobbes\' Internet Timeline v7.0]\n*[http://www.internetworldstats.com Internet World Usage Statistics]\n\n[[Category:Internét]]\n[[Category:Komunikasi]]\n[[Category:Jaringan komputer]]\n\n[[af:Internet]]\n[[ar:إنترنت]]\n[[be:Інтэрнэт]]\n[[bg:Интернет]]\n[[bs:Internet]]\n[[ca:Internet]]\n[[cs:Internet]]\n[[da:Internet]]\n[[de:Internet]]\n[[el:Διαδίκτυο]]\n[[en:Internet]]\n[[eo:Interreto]]\n[[es:Internet]]\n[[et:Internet]]\n[[fa:اینترنت]]\n[[fi:Internet]]\n[[fr:Internet]]\n[[fy:Ynternet]]\n[[ga:Idirlíon]]\n[[gl:Internet]]\n[[he:אינטרנט]]\n[[hr:Internet]]\n[[hu:Internet]]\n[[ia:Internet]]\n[[id:Internet]]\n[[it:Internet]]\n[[ja:インターネット]]\n[[ko:인터넷]]\n[[ku:Înternet]]\n[[lt:Internetas]]\n[[ms:Internet]]\n[[nds:Internet]]\n[[nl:Internet]]\n[[no:Internett]]\n[[pl:Internet]]\n[[pt:Internet]]\n[[ro:Internet]]\n[[ru:Интернет]]\n[[sa:आन्तरजालम्]]\n[[simple:Internet]]\n[[sk:Internet]]\n[[sl:Internet]]\n[[sv:Internet]]\n[[tr:İnternet]]\n[[tt:Päräwez]]\n[[uk:Інтернет]]\n[[vi:Internet]]\n[[vo:Vüresod]]\n[[zh-cn:因特网]]\n[[zh-tw:網際網路]]','/* Tumbu kaluar */',3,'Kandar','20041111024627','',0,0,0,0,0.662079668446,'20050128065809','79958888975372'); INSERT INTO cur VALUES (816,0,'Surélék','\'\'\'E-mail\'\'\', atawa \'\'\'email\'\'\', disundakeun jadi \'\'\'surélék\'\'\', ngarupakeun landihan pikeun \"[[surat]] [[éléktronik]]\" (as opposed to conventional mail, in this context also called [[snail mail]]) nu dimaksudkeun kana nyusun/nulis, ngirim, jeung narima pesen/surat ngaliwatan sistem komunikasi éléktronik. Sistem surélék ayeuna lolobana maké [[Internet]], malah surélék nu ngarupakeun pungsi Internét nu paling ilahar/popular.\n\n== Asal-usul surélék ==\n\nBéda jeung asumsi umum, surélék sabenerna geus aya méméh Internét; malah, ayana sistem surélék ngarupakeun alat nu penting pisan dina nyiptakeun Internét.\n\nE-mail started in [[1965]] as a way for multiple users of a [[time-sharing]] [[mainframe computer]] to communicate; although the exact history is murky, among the first systems to have such a facility were [[SDC]]\'s [[Q32]] and [[Massachusetts Institute of Technology|MIT]]\'s [[CTSS]].\n\nE-mail was quickly extended to become \'\'network e-mail\'\', allowing users to pass messages between different computers. The early history of network e-mail is also murky; the [[AUTODIN]] system may have been the first allowing electronic text messages to be transferred between users on different computers, in [[1966]], but it is possible the [[SAGE]] system had something similar some time before.\n\nThe [[ARPANET]] [[computer network]] made a major contribution to the evolution of e-mail. There is one report [http://www.multicians.org/thvv/mail-history.html] which indicates experimental inter-system e-mail transfers on it shortly after its creation, in [[1969]]. [[Ray Tomlinson]] initiated the use of the [[Commercial at|@ sign]] to separate the names of the user and their machine in [[1972]]. The common report that he \"invented\" e-mail is an exaggeration, although his early e-mail programs [[SNDMSG]] and [[READMAIL]] were very important. The ARPANet significantly increased the popularity of e-mail, and it became the \"killer app\" of the ARPANET.\n\n== Growing popularity ==\n\nAs the utility and advantages of e-mail on the ARPANET became more widely known, the popularity of e-mail increased, leading to demand from people who were not allowed access to the ARPANET. A number of protocols were developed to deliver e-mail among groups of time-sharing computers over alternative transmission systems, such as [[UUCP]] and [[IBM]]\'s [[VNET]] e-mail system.\n\nSince not all [[computer]]s or [[network]]s were directly inter-networked, e-mail addresses had to include the \"route\" of the message, that is, a path between the computer of the sender and the computer of the receivers. E-mail could be passed this way between a number of networks, including the [[ARPANET]], [[Bitnet|BITNET]] and [[NSFNET]], as well as to hosts connected directly to other sites via UUCP.\n\nThe route was specified using so-call \"bang path\" addresses, specifying hops to get from some assumed-reachable location to the addressee, so called because each hop is signified by a \"bang sign\", i.e. [[Exclamation mark|\"!\"]]. Thus, for example, the path ...!bigsite!foovax!barbox!me directs people to route their mail to machine bigsite (presumably a well-known location accessible to everybody) and from there through the machine foovax to the account of user me on barbox.\n\nBefore auto-routing mailers became commonplace, people often published compound bang addresses using the { } convention (see [[glob]]) to give paths from several big machines, in the hopes that one\'s correspondent might be able to get mail to one of them reliably (example: ...!{seismo, ut-sally, ihnp4}!rice!beta!gamma!me). Bang paths of 8 to 10 hops were not uncommon in [[1981]]. Late-night dial-up UUCP links would cause week-long transmission times. Bang paths were often selected by both transmission time and reliability, as messages would often get lost. See the network and sitename.\n\n== Surélék Internét Modern ==\nAlmost all e-mail is delivered directly to an Internet-connected host accepting mail for the recipient, using [[Simple Mail Transfer Protocol]]. Very few modern servers will perform routing for messages sent by third parties due to the potential for abuse by people sending [[unsolicited bulk e-mail]]. Those that do allow it are called [[Open mail relay|open relay]]s.\n\nA modern Internet \'\'\'e-mail address\'\'\' is a string of the form \'\'jsmith@domain.example\'\'. It should be read as \"jsmith \'\'\'at\'\'\' domain dot example\". The part before the @ sign is the \'\'\'local part\'\'\' of the address, often the [[username]] of the recipient, and the part after the @ sign is a [[domain name]] which can be looked up in the [[Domain Name System]] to find the [[mail exchange server]]s accepting e-mail for that address.\n\nThe format of Internet e-mail messages is defined in [[RFC 2822]]. Prior to the introduction of RFC 2822 the format was described by [[RFC 822]].\n\nInternet e-mail messages consist of two major components:\n*Headers - Message summary, sender, receiver, and other information about the e-mail\n*Body - The message itself, usually containing a [[signature block]] at the end\n\nThe headers usually have at least four fields:\n\n#From - The e-mail address of the sender of the message\n#To - The e-mail address of the receiver of the message\n#Subject - A brief summary of the contents of the message\n#Date - The local time and date when the message was originally sent\n\nNote however that the \"To\" field does not necessarily have the e-mail address of the recipient. The information supplied in the headers on the recipients computer is similar to that found on top of a conventional letter. The actual information such as who the message was addressed to is removed by the mail server after it assigns it to the correct user\'s mailbox. \nAlso note that the from field does not have to be the real sender of the e-mail. It is very easy to fake the from line and let an e-mail seem to be from any mail address. It is possible to digitally sign an e-mail. This is a lot harder to fake.\n\nOther common header fields include:\n\n#Cc - [[Carbon copy]] (because [[typewriter]]s used [[carbon film]] to copy what was written on them)\n#Bcc - Blind carbon copy (the recipient of this copy will know who was in the To: field, but the recipients cannot see who is on the Bcc: list)\n#Received - Tracking information generated by mail servers that have previously handled a message\n#Content-Type - Information about how the message has to be displayed, usually a [[MIME]] type\n\n== Messages and mailboxes ==\n\nMessages are exchanged between hosts using the [[SMTP|Simple Mail Transfer Protocol]] with software like [[Sendmail]]. Users download their messages from servers usually with either the [[Post Office Protocol|POP]] or [[IMAP]] protocols, yet in a large [[corporate]] environment users are likely to use some [[proprietary]] protocol such as [[Lotus Notes]] or [[Microsoft Exchange Server]]\'s.\n\nMails can be stored either on the [[client]] or on the [[server]] side. Standard formats for mailboxes include [[Maildir]] and [[mbox]]. Several prominent e-mail clients use their own, proprietary format, and require conversion software to transfer e-mail between them.\n\n== E-mail content encoding ==\n\nE-mail is only defined to carry 7-bit [[ASCII]] messages. Although many e-mail transports are in fact \"8-bit clean\", this cannot be guaranteed. For this reason, e-mail has been extended by the [[MIME]] standard to allow the encoding of binary [[attachment]]s including images, sounds and [[HTML]] attachments.\n\n== Spamming and e-mail worms ==\n\nThe usefulness of e-mail is being threatened by two phenomena, [[spamming]] and [[e-mail worm]]s. \n\nSpamming is unsolicited commercial e-mail. Because of the very low cost of sending e-mail, spammers can send hundreds of millions of e-mail messages each day over an inexpensive Internet connection. Hundreds of active spammers sending this volume of mail results in many computer users receiving tens or even hundreds of junk e-mails each day.\n\nE-mail worms use e-mail as a way of replicating themselves into vulnerable computers. Although the first e-mail worm (the [[Morris worm]]) affected early UNIX computers, this problem is today almost entirely confined to the [[Microsoft Windows]] operating system.\n\nThe combination of spam and worm programs results in users receiving a constant drizzle of junk e-mail, which reduces the usefulness of E-mail as a practical tool.\n\nA number of [[stopping E-mail abuse|technology-based initiatives]] mitigate the impact of spam. [[United States Congress|Congress]] has also passed a law, the [[Can Spam Act of 2003]], to regulate such e-mail.\n\n==Further reading==\n* Katie Hafner, Matthew Lyon, \'\'Where Wizards Stay Up Late: The Origins of the Internet\'\' (Simon and Schuster, 1996) also covers the early history of e-mail\n\n==See also==\n* [[E-mail art]]\n* E-mail social issues: \n**[[netiquette]]\n** [[Internet humor]]\n** [[Internet slang]]\n** [[spamming|spam]]\n** [[stopping e-mail abuse]]\n**[[virus (computing)|virus]].\n*Clients and servers:\n** [[e-mail client]]\n** [[mail transfer agent]]\n** [[webmail]] / [[HTMLmail]]\n** [[branded e-mail]]\n*Mailing list: \n**[[electronic mailing list]]\n** [[mailing list archive]]\n* [[e-mail address]]\n* [[Internet mail standard]]s\n* Free e-mail services/[[webmail]]:\n** [[Hotmail]]\n** [[Yahoo! Mail]]\n** [[Gmail]]\n\n==Further Reading==\n\nAbdullah, M. H. (1998). \"Electronic discourse: Evolving conventions in online academic environments\". Bloomington, IN: ERIC Clearinghouse on Reading, English, and Communication. [ED 422 593]\n\nAbras, C. (2002) The principle of relevance and metamessages in online discourse: Electronic exchanges in a graduate course. Language, \"Literacy and Culture Review\" 1(2), 39-53.\n\nBiesenbach-Lucas, S. & Wiesenforth, D. (2001). E-mail and word processing in the ESL classroom: How the medium affects the message. \"Language Learning and Technology\", 5 (1), 135-165. [EJ 621 506]\n\nDanet, B. (2001). Cyberplay: Communicating online. Oxford: Berg Publishing. \n\n==External links==\n* [http://www.multicians.org/thvv/mail-history.html The History of Electronic Mail] is a personal memoir by the implementer of one of the first e-mail systems\n* Michael A. Padlipsky, \'\'[http://www.mids.org/mn/1002/mike.html And They Argued All Night...]\'\' is an alternative personal recollection of the origins of network e-mail\n* [http://www.pretext.com/mar98/features/story2.htm The First E-Mail Message] is an article about the history of network e-mail; contains some errors\n* [http://www.ericdigests.org/2002-3/e-mail.htm E-Mail Counseling: Skills for Maximum Impact]\n* [http://www.ericdigests.org/2004-1/impact.htm The Impact of Electronic Communication on Writing]\n\n----\n\'\'This article, or an earlier version, contains content derived from [[FOLDOC]], used by permission.\'\'\n\n[[da:E-mail]]\n[[de:E-Mail]]\n[[en:Electronic mail]]\n[[es:Correo electrónico]]\n[[fr:Courrier électronique]]\n[[he:דואר אלקטרוני]]\n[[ko:이메일]]\n[[hu:E-mail]]\n[[nl:E-mail]]\n[[ja:電子メール]]\n[[no:E-post]]\n[[pl:Poczta elektroniczna]]\n[[pt:E-mail]]\n[[ro:E-mail]]\n[[ru:Электронная почта]]\n[[simple:Email]]\n[[sv:E-post]]\n[[tr:Elektronik posta]]\n[[uk:Електронна пошта]]\n[[zh-cn:电子邮件]]\n[[zh-tw:電子郵件]]\n\n[[Category:Email]]','/* Asal-usul surélék */',3,'Kandar','20040701085454','',0,0,0,0,0.391870350294,'20041231124514','79959298914545'); INSERT INTO cur VALUES (817,0,'Élmu_alam','Cara medar rupa-rupa widang ulikan loba ditangtukeun ku kasapukan historis (\'\'historical convention\'\') nepi ka jadi harti kecap nu lumaku kiwari. \n\nGambaran tradisional pikeun \'\'\'élmu alam\'\'\' nyéta ulikan ngeunaan aspék fisik dunya \'\'nonhuman\'\'. Salaku kumpulan, di hiji sisi élmu alam dibédakeun ti [[téologi]] jeung \'\'[[élmu sosial]]\'\', di sisi séjén dibédakeun ti [[seni]] jeung [[kamanusaan]]. [[Matematik]] lain ngarupakeun élmu alam, tapi nyadiakeun loba bahan jeung métode dasar pikeun élmu alam. Élmu alam umumna usaha nerangkeun gawéna alam dunya leuwih ngaliwatan prosés alami batan prosés \'\'[[divine]]\'\'. Istilah \'\'\'élmu alam\'\'\' ogé dipaké pikeun mikawanoh \"élmu\" salaku hiji disiplin nu nuturkeun [[métode ilmiah]].\n\nDi sagigireun pamakéan tradisional ieu, kiwari kecap \"élmu alam\" mindeng dipaké dina harti nu leuwih deukeut kana harti sapopoé. Dina jihat ieu, \"élmu alam\" bisa jadi frase pilihan pikeun [[élmu biologis]] (kajeujeut na prosés biologis), sarta dibédakeun ti [[élmu fisik]] (kajeujeut na hukum kimia jeung fisika nu ngadadasaran mayapada).\n\n==Élmu-élmu alam==\n*[[Astronomi]]\n*[[Biologi]]\n*[[Kimia]]\n*[[Élmu bumi]]\n*[[Ékologi]]\n*[[Fisika]]\n\n==Élmu-élmu terapan jeung rékayasa==\n*[[Élmu tatanén]]\n*[[Rékayasa listrik]]\n*[[Élmu taneuh]]\n\n==Tempo ogé==\n* [[Daptar disiplin akademis]]\n\n==Tumbu kaluar==\n* [http://hrst.mit.edu/ Sajarah Élmu jeung Téhnologi Mutahir]\n* [http://www.scibooks.org/ Ulasan Buku-buku Ngeunaan Élmu Alam] Situs ieu ngandung leuwih ti 50 ulasan buku-buku élmu alam, ditambah sababaraha éséy. \n\n[[Category:Tepas]]\n[[Category:Élmu alam]]\n\n[[ast:Ciencies naturales]]\n[[ca:Ciències naturals]]\n[[da:Naturvidenskab]]\n[[de:Naturwissenschaft]]\n[[el:Φυσικές επιστήμες]]\n[[en:Natural science]]\n[[eo:Naturscienco]]\n[[es:Ciencias naturales]]\n[[fi:Luonnontiede]]\n[[fr:Sciences naturelles]]\n[[fy:Eksakte wittenskip]]\n[[he:מדעי הטבע]]\n[[ia:Scientia natural]]\n[[ie:Scienties natural]]\n[[ja:自然科学]]\n[[nds:Naturwetenschap]]\n[[nl:Exacte wetenschappen]]\n[[sl:Naravoslovje]]\n[[sr:Природне науке]]\n[[sv:Naturvetenskap]]\n[[vi:Khoa học tự nhiên]]\n[[zh:自然科学]]','',3,'Kandar','20041229074334','',0,0,0,0,0.167583234686,'20041229074334','79958770925665'); INSERT INTO cur VALUES (818,0,'Logika','[[Category:Logika]]\n\nDina basa sapopoé, \'\'\'logika\'\'\' ngarupakeun tinimbangan nu dipaké pikeun ngahontal hiji kasimpulan/kacindekan tina sakumpulan sangkaan. Nu leuwih formal, logika ngarupakeun ulikan ngeunaan \'\'valid inference\'\', nyaéta [[prosés]] ngahontal hiji kasimpulan/kacindekan tina sakumpulan sangkaan kalawan maké cara/jalan nu sistematis tur sohéh. Ceuk kasarna, kasohéhan ngandung harti nalika sakumpulan sangkaan boga ajén bener, mangka kasimpulanana ogé bener. \n\nDi sagigireun éta, logika nyadiakeun rumus/resép pikeun tinimbangan, nyéta kumaha jalma—ogé mahluk pinter séjénna, mesin, jeung sistem—sakuduna méré alesan. Ngan, rumus modél kitu lain mataholang pikeun logika sorangan, tapi leuwih mangrupa larapan. Kumaha jalma sabenerna méré alesan biasana diulik dina widang séjén, kaasup [[psikologi kognitif]].\n\nSacara tradisional, logika diulik salaku cabang tina [[filosofi]]. Mimiti panengah taun [[1800]]-an logika geus umum diulik na [[matematik]], jeung, nu leuwih mutahir, dina [[élmu komputer]]. Salaku [[élmu]], logika nalungtik jeung ngagolongkeun struktur pernyataan jeung argumén sarta ngarancang skéma pikeun nyandikeunana. Ku sabab éta cakupan logika bisa lega pisan, kaasup tinimbangan ngeunaan [[kamungkinan|probabiliti]] jeung [[kausaliti]]. Nu ogé diulik na logika nyéta struktur argumén salah jeung [[paradoks]].\n\n==Cakupan logika==\nNuturkeun tumuwuhna, loba bébédaan geus diwanohkeun kana logika. Bébédaan ieu disadiakeun pikeun nulungan ngaresmikeun rupa-rupa bentuk logika salaku élmu. Di handap ieu sababaraha bébédaan nu penting.\n\n===Tinimbangan deduktif jeung induktif===\n\nSasakalana, logika ngan ngawengku [[tinimbangan deduktif]] which concerns what follows from given premises. Ngan, perlu dicatet yén [[tinimbangan induktif]]—ulikan nurunkeun kacindekan umum nu bisa dipercaya tina observasi—kadang diasupkeun dina ulikan logika. Patali jeung éta, urang kudu ngabédakeun antara kasahéhan deduktif jeung induktif. An inference is deductively valid if and only if there is no possible situation in which all the premises are true and the conclusion false. The notion of deductive validity can be rigorously stated for systems of [[formal logic]] in terms well-understood notions of [[semantics]]. Inductive validity on the other hand requires us to define \'\'reliable generalization\'\' of some set of observations. The task of providing this definition may be approached in various ways, some less formal than others; some of these definitions may use mathematical models of probability. For the most part our discussion of logic deals only with deductive logic.\n\n===Logika formal jeung informal===\nSomewhat arbitrarily, study of logic is divided into formal and [[informal logic]]. \n\nFormal logic (sometimes called symbolic logic) approaches logic and in particular logical argument as a set of rules for manipulating symbols. There are two kinds of rules in any system of formal logic: [[Syntax]] rules and [[rules of inference]]. Syntax says how to build meaningful expressions; rules of inference say how to obtain true formulas from other true formulas. Logic also needs [[semantics]], which says how to assign meaning to expressions. Formal logic encompasses a wide variety of logical systems. For instance, [[propositional logic]] and [[predicate logic]] are a kind of formal logic, as well as [[temporal logic]], [[modal logic]], [[Hoare logic]], the [[calculus of constructions]] etc. [[Higher order logic]]s refer to logical systems based on a hierarchy of [[type theory|types]]. \n\n[[Informal logic]] is the study of logic as used in natural language arguments. Informal logic is complicated by the fact that it may be very hard to tease out the formal logical structure imbedded in an argument. Informal logic is also more difficult because the semantics of natural language assertions is much more complicated than the semantics of formal logical systems. \n\nFollowing are more specific discussions of some systems of logic. See also: [[list of topics in logic]].\n\n==Logika Aristotelian==\n\'\'Main article:[[Aristotelian logic]]\'\'\n\nThe [[Prior Analytics]] was [[Aristotle]]\'s pioneering work establishing a system of logic and inference based on the forms of the premises and the conclusion. These rules were codified into various forms of syllogisms which, until recently at least, were part of the standard high school curriculum in the West, much like euclidean plane geometry. [[Aristotelian logic]] is sometimes referred to as formal logic because it specifically deals with forms of reasoning, but is not formal in the sense we use it here or as is common in current usage. It can be considered as a precursor to formal logic. \n\nIn the tradition of aristotelian logic is also [[term logic]].\n\n==Logika matematis==\n\'\'Main article:[[Mathematical logic]]\'\'\n\nMathematical logic refers to two distinct areas of research: The first, primarily of historical interest, is the use of formal\nlogic to study mathematical reasoning, and the second, in the other direction, the\napplication of mathematics to the study of formal logic. At the\nbeginning of the twentieth century, philosophical logicians including\n([[Gottlob Frege|Frege]], [[Bertrand Russell|Russell]]) attempted to\nprove that mathematics could be entirely reduced to logic. The\nreduction had limited success (for reasons which are well beyond the\nscope of this article) but in the process, logic took on much of the\nnotation and methodology of mathematics. In the other direction, in the early 1930s, [[Kurt Gödel]] embarked on an ambitious program of considering logic and proof as an object of mathematical study, leading him to state far\nreaching results on provability and model theory such as the\n[[incompleteness theorem]]s of first order arithmetic. This line of research has continued to the present time, leading to various stunning results such as for example, [[Paul Cohen]]\'s proof of the independence of the continuum hypothesis from the axioms of Zermelo-Fraenkel set theory.\n\n==Logika filosofis==\n\'\'Main article [[philosophical logic]]\'\'\n\n[[Philosophical logic]] deals with formal descriptions of\nnatural language. Most philosophers assume that the bulk of \"normal\"\nproper reasoning can be captured by logic, if one can find the right\nmethod for translating ordinary language into that logic.\nPhilosophical logic is essentially a continuation of the traditional\ndiscipline that was called \"Logic\" before it was supplanted by the\ninvention of Mathematical logic. Philosophical logic has a much\ngreater concern with the connection between natural language and\nlogic. As a result, philosophical logicians have contributed a great\ndeal to the development of non-standard logics (e.g., free logics,\ntense logics) as well as various extensions of classical logic (e.g.,\nmodal logics), and non-standard semantics for such logics (e.g.,\nsupervaluation semantics).\n\n==Multi-valued logic==\n\nThe logics discussed above are all \"[[bivalent]]\" or \"two-valued\"; that is, the semantics for each of these languages will assign to every sentence either the value \"True\" or the value \"False.\" Systems which do not always make this distinction are known as [[non-Aristotelian logic]]s, or [[Multi-valued logic|multi-valued logics]].\n\nIn the early [[abad ka-20|20th century]] [[Jan Lukasiewicz|Jan Łukasiewicz]] investigated the extension of the traditional true/false values to include a third value, \"possible\".\n\nLogics such as [[Fuzzy logic|fuzzy logic]] have since been devised with an infinite number of \"degrees of truth\", e.g., represented by a [[real number]] between 0 and 1. [[Bayesian probability]] can be interpreted as a system of logic where probability is the subjective truth value.\n\n== Logic and computation ==\n\nLogic is extensively used in the fields of [[artificial intelligence]], and [[computer science]]. \n\nIn the 1950s and 1960s, researchers predicted that when human knowledge could be expressed using logic with mathematical notation, it would be possible to create a machine that reasons, or artificial intelligence. This turned out to be more difficult than expected because of the complexity of human reasoning. [[Logic programming]] is an attempt to make computers do logical reasoning and [[Prolog programming language]] is commonly used for it.\n\nIn symbolic logic and mathematical logic, proofs by humans can be computer-assisted. Using [[automated theorem proving]] the machines can find and check proofs, as well as work with proofs too lengthy to be written out by hand.\n\nIn computer science, [[Boolean algebra]] is the basis of hardware design, as well as much software design. \n\nThere are also various systems for reasoning about computer programs. [[Hoare logic]] is one the earliest of such systems. Other systems are [[CSP]], [[CCS]], [[pi-calculus]] for reasoning about concurrent processes or mobile proceses. See also [[computability logic]]; this is a formal theory of computability in the same sense as classical logic is a formal theory\nof truth. \n\n==Tempo ogé==\n\n\'\'\'Konsép logika\'\'\'\n*[[proposisi analitik]]\n*[[argument form]]\n*[[cogency]]\n*[[college logic]]\n*[[computability logic]]\n*[[hybrid logic]]\n*[[interpretability logic]]\n*[[provability logic]]\n*[[soundness]]\n*[[validity]]\n*[[ternary logic]]\n\'\'\'Techniques and rules\'\'\'\n*[[affirming the consequent]]\n*[[deduction and induction]]\n*[[disjunctive syllogism]]\n*[[modus ponens]]\n*[[modus tollens]]\n\'\'\'Related Topics\'\'\'\n*[[faith]]\n*[[fuzzy logic]]\n*[[game semantics]]\n*[[history of logic]]\n*[[lambda calculus]]\n*[[set theory]]\n* [[List of important publications in mathematics#Logic| Important publications in logic]]\n\n\n\n[[af:Formele logika]]\n[[bg:Логика]]\n[[ca:Lògica]]\n[[da:Logik]]\n[[de:Logik]]\n[[en:Logic]]\n[[eo:Logiko]]\n[[es:Lógica]]\n[[et:Loogika]]\n[[fi:Logiikka]] \n[[fr:Logique]]\n[[hu:Logika]]\n[[id:Logika]]\n[[it:Logica]]\n[[ja:論理学]]\n[[la:Logica]]\n[[lv:Logika]]\n[[nl:Logica]]\n[[pl:Logika]]\n[[pt:Lógica]]\n[[simple:Logic]]\n[[sv:Logik]]\n[[zh:逻辑学]]','/* Multi-valued logic */',3,'Kandar','20050316082215','',0,0,1,0,0.091039978941,'20050316082215','79949683917784'); INSERT INTO cur VALUES (819,0,'Budaya','== Gelar Budaya dan Wisata Kontemplatif \'\'NYIAR LUMAR 4\'\'\nSitus Astana Gede Kawali 28 Agustus 2004 ==\n\n[[NYIAR LUMAR 4]]\n\nnihan tapak wa\nlar nu siya mulia tapa(k) I\nna parbu raja wastu\nmanadeg di kuta kawa\nli nu mahayu na kadatuan\nsurawisesa nu marigi sa\nkulilin dayoh nu najur sakala\ndesa aya ma nu pa(n) dori pakena\ngawe rahayu pakon hobol ja\nya di buana\n\n(Prasasti Kawali 1)\n\n\n\n1. Dasar Pemikiran\n\nAda secercah harapan yang tetap hidup di hati kami. Bahwa seni warisan nenek moyang dan seni Sunda terkini berhak hidup dan berkembang, dihargai semestinya oleh masyarakat luas, di tengah zaman yang serba seperti ini. Sekian lama kami tergoda, memikirkan bagaimana cara setepat-tepatnya untuk menggapai hal itu.\n\nJawabannya adalah: semua mesti dikembalikan kepada alam, demikian gagasan yang terlintas dalam pikiran kami. Seni tradisi yang alamiah akan bernapas dan berdenyut ditengah-tengah alamnya. Apabila dicabut dari alam lingkungannya, seni tradisi selalu cenderung kehilangan nuansa dan makna. Seni Sunda terkini mesti berpijak pada tradisi dan alam, agar keberadaannya memiliki pondasi yang lebih kokoh untuk kelangsungan perkembangannya. Demikian pula manusianya, pencipta dan penikmatnya, yang kadung terkurung di zaman yang serba jauh dari alam, akan merasa nyaman berada di lingkungan yang mungkin telah lama terlupakan \n\nUntuk gagasan itulah maka kami tela mencoba menggelar tradisi dan seni Sunda terkini dengan berlatarkan alam. Pada suatu malam, 20 Mei 2000, di situs Surawisesa (Astana Gede) Kawali, hadirin kami ajak bertualang ke dunia bihari yang masih ngancik di kiwari, dengan hidangan berbagai jenis seni Sunda di tengah-tengah alamnya. Kala itu, hadirin yang terdiri dari berbagai kalangan, baik seniman maupun masyarakat kebanyakan, yang datang dari penjuru Pasundan, ternyata menyambutnya dengan sangat antusias. Sungguh lebih dari perkiraan kami semula. Hal yang sama kembali kami lakukan pada 24 Agustus 2002, tidak kalah dengan pergelaran yang pertama sampai dengan kedua, yang kali ini pun masyarakat tetap menyambutnya dengan sangat antusias. \n\nDemikianlah, atas dorongan dari berbagai pihak, kami bermaksud menyelenggarakan acara serupa dengan upaya peningkatannya. Perasaan kami menyatakan bentuk acara seperti ini akan baik pula bagi pengembangan potensi wisata. Wisata yang bersifat kontemplatif terbilang jarang diselenggarakan. Padahal wisata seperti ini sangat baik bagi kesehatan jiwa raga wisatawan. \n\n2. Nama Pergelaran\n\nNyiar Lumar, demikianlah acara ini bertajuk. Nyiar adalah mencari. Lumar itulah jamur cahaya. Perjalanan mencari jamur cahaya, demikianlah arti tersuratnya. Arti tersiratnya tiada lain adalah perjalanan kontemplatif, kembali mendekatkan diri dengan alam, merenungi akar-akar kehidupan, mencari jatining diri agar yakin melangkah kemasa depan.\n\nTepatnya, acara kali ini bertajuk: Nyiar Lumar 4.\n\n3. Tempat Pergelaran\n\nKegiatan berpusat di situs Surawisesa (Astana Gede) Kawali. Tempat ini kami anggap yang paling mengusung tema, karena disana banyak peninggalan berupa batu tulis, berisi wangsit karuhun, yang masih tetap bermakna untuk bekal mengarungi kehidupan. \n\nSelain itu, tempat ini kami anggap masih cukup alamiah, dengan sawah dan ladangnya, hutan dan sungai-sungainya, yang nantinya akan kami jadikan lahan untuk menggelar berbagai mata acara dalam rangkaian yang padu.\n\n4. Waktu Pergelaran\n\nNyiar Lumar 4 dijadwalkan terselenggara pada tanggal 28Agustus 2004. semalam suntuk. Dari senja sambil menikmati lembayung, bersama melewatkan malam berbulan (ngabungbang), hingga kalbu bersatu menyambut fajar. \n\n5. Materi Kegiatan\n\n Pergelaran tari Sunda klasik\n Komposisi tari oleh Studio Titikdua, Ciamis\n Pergelaran teater (teater wastu dan jagat)\n Pergelaran Dramatisasi Puisi Sunda \n Tarawangsa Cibalong Sumedang\n Seni Pencak Silat Cianjuran\n Tembang Sunda oleh Dadak Sakala Kawali\n Monolog\n Pembacaan Puisi Sunda: Hadi AKS, Darpan Ariawinangun, Godi Suwarna, Nazaruddin Azhar, Chyie Reti Isnendes, Etti RS, Soni Farid Maulana, Acep Zamzam Noor, Deden Abdul Aziz, dll.\n Pergelaran Pantun Sunda\n Pergelaran Ronggeng Gunung\n Genjring Ronyok Kawali\n Memancing/Marak di Sungai Cibulan\n\n6. Rangkaian Pergelaran\n\nNgawalan: \n\n Selepas Asar para tamu diharap telah hadir di lingkungan Pendopo Kecamatan Kawali yang bentuk bangunannya masih menyiratkan keanggunan masa bihari, dari sana, sambil menikmati hidangan (lalawuh), akan terhidang suasana yang serba khas sebuah kota mungil, Kawali. \n\n Selepas sembahyang Isya di Mesjid Agung Kawali, para tamu diharap telah berganti pakaian. Mengenakan pakaian yang bukan pakaian keseharian. Para tamu mengikuti acara pelepasan oleh panitia. \n\nLalampahan:\n\n Para tamu berjalan kaki dari Pendopo Kecamatan menuju situs Surawisesa (Astana Gede) Kawali, bersama Gulang-Gulang pembawa obor. Sepanjang perjalanan, para tamu akan disuguhi pemandangan alam dimalam bulan purnama, suasana perkampungan, bentangan sawah dengan bunyi-bunyi seraganya, aliran sungai dengan germercik airnya.\n\nMagelaran:\n\n Dipintu gerbang situs Astana Gede, para tamu akan disambut musik khas genjring ronyok selanjutnya para tamu dipersilahkan istirahat. Menyaksikan rajah dari Ki Juru Pantun. Tari-tari Sunda klasik, komposisi tari dan pergelaran Dramatisasi Puisi. Para tamu dipersilahkan masuk ke situs Astana Gede. Berjiarah. Menyaksikan pergelaran tembang Sunda. \n\n Para tamu bergerak ke alun-alun Surawisesa, antara situs Astana Gede dan Mata Air Keramat Cikawali. Dilapangan tersebut para tamu disuguhi pencak silat Cianjuran dan Ronggeng Kaler. Selepas itu para tamu melanjutkan perjalanan ke Mata Air Cikawali. \n\n Puncak acara di gelar di Cikawali, pembacaan puisi Sunda dilaksanakan di Sungai Cibulan, pergelaran teater Wastu Kawali, pergelaran seni tarawangsa Cibalong Sumedang dan Ronggeng Gunung di gelar diladang pesawahan Pasanggrahan Cikawali. Diakhiri dengan menari bersama. Selanjutnya, para tamu dipersilahkan memancing di lubuk Sungai Cibulan. Untuk tamu yang ingin beristirahat panitia menyediakan tenda-tenda di sekitar Cikawali\n\n7. Pembiayaan\n\nKami sungguh sangat mengharapkan bantuan semua pihak, baik moril dan terutama materil, untuk tergelarnya acara tersebut di atas. Insya Allah, acara ini menjanjikan tempat terhormat bagi mereka yang sudi mengulurkan tangan dengan segenap harapan, kami lampirkan rincian pembiayaan, dan susunan panitia.\n\n8. Penutup\n\nDemikianlah seluruh gagasan kami, yang tentunya tiada mungkin terlaksana tanpa bantuan segenap pihak. Semoga ada penerus yang melaksanakan berbuat kebajikan agar lama jaya dibuana, begitulah wangsit Sang Wastukencana yang terpahat pada Prasasti Kawali I. Insya Allah, kita sedang melangkah kearah sana.\n\n\nNYIAR LUMAR 4\nSEKRETARIAT :\nPendopo Kecamatan Kawali\nJl. Veteran No. 47 Kawali – Ciamis 46253\ne-mail: nyiarlumar@yahoo.com\nWeb : http://www.nyiarlumar.tk\nContact Person : Nurdani, D-Jay 628172304514\nnurdani@msn.com\ndjaynurdani@yahoo.com','',0,'202.159.126.34','20040816013608','',0,0,0,0,0.456502345603,'20040816013608','79959183986391'); INSERT INTO cur VALUES (820,0,'Rékayasa','\'\'\'Rékayasa\'\'\' ngarupakeun [[aplikasi]] [[élmu]] pikeun nedunan pangabutuh manusa. Ieu kacumponan ku ayana [[pangaweruh]], [[matematik]], jeung [[pangalaman]] praktis nu diterapkeun kana [[rancang]] [[barang (filosofi|barang]] atawa [[prosés]] nu mangpaat. Praktisi rékayasa nu profésional disebut [[daptar insinyur|insinyur]].\n\n==Dibandingkeun jeung pagawéan séjén==\n\nRékayasa patali jeung implementasi jawaban pikeun hiji masalah praktis. Saurang élmuwan bisa nanya \"naha?\" nu diteruskeun ku nalungtik pijawabeun pananyana. Sabalikna ti éta, insinyur hayang nyaho \"kumaha carana\" ngaréngsékeun hiji masalah jeung kumaha cara ngajalankeun éta solusi.\n\nDina kalimah sejen, ilmuwan nalungtik kajadian, sedengkeun ahli rekayasa neangan cara keur meupeuskeun masalah atawa nyieun cara anyar tina cara anu geus aya samemehna. \n\nWatesan \"ahli rekayasa\" jeung \"ahli teknologi\" teu bisa silih gantikeun; duanana ngabogaan tipe pagawéan jeung profési anu béda. Pikeun gambaran: nalika insinyur geus manggihan solusi pikeun masalah nu disanghareupan, pagawéanana eureun, nu diteruskeun ku [[ahli téhnologi]] pikeun nyampurnakeun solusina. This process is dependent on various factors that vary with time. A solution that could be a practical application of a scientific fact does not satisfy a technologist. A technologist endeavours to bring it within the economic constraints so that the common person not only understands and marvels at science but also is able to enjoy it and loses fear of it by constant interaction.\n\nPikeun gambaran contona, tanggal 21 Novémber 1877, [[Thomas A. Edison]] ngawangun [[fonograf]] -- hiji préstasi punjul tina rékayasa. Salajengna, anjeunna ngarahkeun asisténna (si ahli téhnologi) piekun ngaronjatkeun parabotna ku jalan ngaleungitkeun harmonik tina kaluaran sorana.\n\n==Pancén insinyur==\n\nThe engineer must identify and understand the relevant constraints in order to produce a successful design. Constraints include available resources, physical or technical limitations, flexibility for future modifications and additions, and other factors such as requirements for cost, manufacturability, serviceability, and marketing and aesthetic, social, or ethic considerations. By understanding the constraints, engineers deduce specifications for the limits within which an object or system may be produced and operated. Engineering is therefore influenced by many considerations.\n\n===Problem solving===\n\nEngineers use their knowledge of [[science]] and [[mathematics]], and [[empirical knowledge|appropriate experience]], to find suitable solutions to a problem. Creating an appropriate [[mathematical model]] of a problem allows them to analyze it (perhaps, but exceptionally, definitively), and to test potential solutions. If multiple reasonable solutions exist, engineers evaluate the different [[design choice]]s on their merits and choose the solution that best meets the requirements.\n\nEngineers typically attempt to predict how well their designs will perform to their specifications prior to full-scale production. They use, among other things: [[prototype]]s, [[scale model]]s, [[simulation]]s, [[destructive testing | destructive test]]s, [[nondestructive testing]], and [[ stress test]]s. Testing ensures that products will perform as expected. Engineers as professionals take seriously their responsibility to produce designs that will perform as expected and will not cause unintended harm to the public at large. Engineers typically include a [[factor of safety]] in their designs to reduce the risk of unexpected failure.\n\n===Mangpaat komputer===\n\nComputers, and design software, play an increasingly important role. Using [[computer aided design]] (CAD) software, engineers are able to capture more information about their designs. The computer can automatically translate some models to instructions suitable for automatic machinery (e.g., [[CNC]]) to fabricate (part of) a design. The computer also allows increased reuse of previously developed designs by presenting an engineer with a library of predefined parts ready to be used in designs.\n\nAdditionally, engineers make use of a variety of circuit [[schematic]]s software to aid in the creation of circuit designs that perform an electronic task when used for a [[printed circuit board]] (PCB) or a computer chip.\n\n==[[Étimologi]]==\n\nYén kecap \'\'engineer\'\' (insinyur) asalna tina gambaran pikeun jalma nu nyieun/ngawangun \'\'engine\'\' (mesin), sabenerna ngan ukur mitos. Nyatana, kecap \'\'engine\'\' jeung \'\'engineer\'\' (ogé kecap \'\'ingenious\'\') sarua asalna tina kecap Latin \'\'ingeniosus\'\' nu hartina \"\'\'skilled\'\'\", \"ahli\". Mangka saurang insinyur kudu pinter, boga pangalaman, mecahkeun masalah. Pangucapan \'\'engineer\'\' saméméhna dipangaruhan ku asal kecap tina \'\'engine\'\'. Istilah ieu salajengna robah jadi ngawengku sagala widang di mana kaahlian terapan [[métode ilmiah]] digunakeun. Dina sababaraha basa séjén, saperti basa Arab, kecap \"engineering\" ogé ngandung harti \"géométri\". Ogé na basa Indonésia jeung Sunda, kecap \"engineering\" geus ilahar ditarjamahkeun jadi \"teknik/téhnik\" jeung \"rékayasa\".\n\n==Patalina jeung disiplin séjén==\n\n[[Science]] attempts to explain newly observed and unexplained phenomena, often creating [[mathematical model]]s of observed phenomena. [[Technology]] and engineering are attempts at practical application of knowledge (often from science). Scientists work on science; engineers work on technology. However, there is often an overlap between science and engineering. It is not uncommon for scientists to become involved in the practical application of their discoveries; thereby becoming, for the moment, engineers. Conversely, in the process of developing technology engineers sometimes find themselves exploring new phenomena, thus becoming, for the moment, scientists.\n\nThere are significant parallels between the practice of [[medicine]] and [[engineering]]. Both professions are well known for their pragmatism -- the solution to real world problems often requires moving forward before phenomenea are completely understood in a more rigorous [[scientific]] sense.\n\nThere are also close connections between the workings of engineers and artists; they are direct in some fields, for example, [[architecture]] and [[industrial design]], and indirect in others. Artistic and engineering creativity may be fundamentally connected.\n\n==Insinyur jeung budaya==\n\nSacara historis, rékayasa diteuteup salaku widang nu garing sarta teu dipikaresep dina [[budaya popular]], sarta ogé dianggap salaku ladangna jalma \'\'[[nerd]]\'\'.\n\n==Tempo ogé==\n\n===Pakakas===\n* [[Komputer]]\n* [[Kalkulator]] \n\n===Métode===\n* [[Matematik]], hususna [[Aljabar]], [[Géométri]], jeung [[Kalkulus]]\n* [[Fisika]]\n* [[Kimia]]\n\n===Cabang utama===\n*[[Rékayasa aerospace]]\n*[[Rékayasa agrikultural]]\n*[[Rékayasa biomedis]]\n*[[Rékayasa komputer]]\n*[[Rékayasa sipil]]\n*[[Rékayasa kimiawi]]\n*[[Rékayasa listrik]] \n*[[Rékayasa Industrial jeung manufaktur]]\n*[[Rékayasa mékanis]]\n*Rékayasa [[Mékatronik]]\n*[[Rékayasa bahan]]\n*[[Rékayasa pertambangan]]\n*[[Rékayasa inti]]\n*[[Rékayasa pétroleum]]\n*[[Rékayasa software]]\n*[[Rékayasa struktural]]\n\nTempo [[widang-widang rékayasa]] pikeun béréndélan nu lengkep.\n\n===Rupa-rupa===\n*[[Daptar jejer rékayasa]]\n*[[Widang-widang rékayasa]]\n*[[Masarakat rékayasa]]\n\n[[af:Ingenieurswese]]\n[[ca:Enginyeria]]\n[[da:Ingeniørfag]]\n[[de:Technik]]\n[[en:Engineering]]\n[[es:Ingeniería]]\n[[eo:Ingxenierarto]]\n[[fr:Ingénierie]]\n[[fy:Technyk]]\n[[it:Tecnologia]]\n[[ja:工学]]\n[[ko:공학]]\n[[nl:Techniek]]\n[[pl:Inżynieria]]\n[[pt:Engenharia]]\n[[ro:Inginerie]]\n[[simple:Engineering]]\n[[sl:Tehnika]]\n[[ta:பொறியியல்]]\n[[zh:工程学]]\n[[Category:Rékayasa]]\n[[Category:Tepas]]','',3,'Kandar','20040812040618','',0,0,0,0,0.475050871482,'20050128065809','79959187959381'); INSERT INTO cur VALUES (821,3,'202.122.173.10','Saha tea ieu teh?','',3,'Kandar','20040707074512','',0,0,0,1,0.870367249879,'20040707074512','79959292925487'); INSERT INTO cur VALUES (822,0,'Statistik','\'\'\'Statistik\'\'\' ngarupakeun élmu jeung prakték ngeunaan ngembangkeun [[pangaweruh]] [[manusa]] ku jalan ngagunakeun [[data]] émpiris, dumasar kana [[tiori statistik]] nu ngarupakeun cabang ti [[matematik]] terapan. Di antara téori statistik, \'\'randomness\'\' jeung \'\'uncertainty\'\' dimodélan ku [[téori kamungkinan]]. [[Prakték statistis]] ngawengku ngararancang, nyimpulkeun, jeung napsirkeun panenget nu can tangtu. Ku sabab statistik ditujukeun pikeun ngahasilkeun béja nu \"panghadéna\" tina data nu aya, sababaraha panalungtik ngajadikeun ststistik salaku hiji cabang [[téori kaputusan]].\n\n==Asal-usul==\nKecap \'\'\'statistik\'\'\' datang ti frase [[Latin]] modern \'\'statisticum collegium\'\' (kuliah/ceramah ngeunaan urusan nagara), nu tina istilah éta kaluar kecap [[basa Itali|basa Itali]] \'\'statista\'\', nu hartina \"[[nagarawan]]\" (\'\'statesman\'\') atawa \"[[politisi]]\" (bandingkeun jeung [[status]]) jeung kecap [[basa Jérman]] \'\'statistik\'\', nu asalna dimaksudkeun kana analisis data-data ngeunaan nagara. Ieu ngawengku ngumpulkeun jeung ngagolongkeun data sacara umum dina mangsa awal abad ka-19. Pangumpulan data ngeunaan nagara jeung daérah terus mayeng, utamana ku [[List of national and international statistical services|layanan statistis nasional jeung internasional]]; sacara husus [[sénsus]] nyadiakeun béja teratur ngeunaan [[populasi]].\n\n==Métode statistis==\nUrang ngagambarkeun pangaweruh (jeung kabodoan) urang sacara matematis jeung salawasna diajar ti naon baé nu bisa katengetkeun. Hartina urang kudu\n# [[Planning statistical research|ngararancang observasi]] pikeun ngontrol variabilitina (\'\'rancangan percobaan\'\'),\n# [[kasimpulan statistik|kasimpulan tina kumpulan observasi]] keur nembongkeun komunalna ku kaayaan nu leuwih jentre dina ([[statistik deskriptif]]), sarta \n# reach consensus about what [[statistical inference|the observations tell us]] about the world we observe ([[statistical inference]]).\n\nDina sababaraha wujud statistik déskriptif, utamana \'\'[[data mining]]\'\', léngkah nu kadua sarta nu katilu kalintang pentingna sahingga léngkah kahiji katémbong teu pati penting. Dina disiplin ieu, data mindeng dikumpulkeun di luar kontrol jalma nu migawé analisis, sahingga hasil analisis leuwih mangrupa modél operasional batan laporan konsénsus.\n\n==Kamungkinan==\n[[Kamungkinan]] (probabilitas) hiji kajadian kadang digambarkeun salaku angka/wilangan antara hiji jeung enol. Ngan dina kanyataanana hakékatna teu aya nu boga kamungkinan 1 atawa 0. Anjeun bisa nyebutkeun yén [[panonpoé]] pasti bakal medal isuk-isuk, tapi kumaha mun aya kajadian nu ngancurkeun panonpoé méméh isuk? Kumaha mun aya perang nuklir sahingga langit katutupan ku silalatu jeung haseup?\n\nUrang mindeng nganggap kamungkinan samodél kitu pasti atawa teu mungkin kajadian, sahingga leuwih gampang nampa kajadian kitu salaku kamungkinan hiji atawa enol. \n\nNajan kitu, hal ieu bisa ngakibatkeun salah harti jeung kabiasaan nu bahaya, sabab jalma teu bisa ngabédakeun ngabédakeun antara, misalna, kamungkinan 10-4 jeung kamungkinan 10-9, padahal sacara praktis béda pisan. Misalna anjeun dina saumur hirup bakal kungsi meuntas jalan 105 atawa 106 kali, saterusna anjeun ngurangan resioko salila meuntas jadi 10-9 bakal ngajadikeun anjeun aman salila hirup, sabalikna lamun resiko meuntas 10-4 bakal ngajadikeun anjeun salawasna ngalaman kacilakaan, sabalikna dumasar kana rarasaan yen 0.01% teh ngabogaan resiko nu kacida leutikna.\n\nKu cara ngagunakeun distribusi mimiti (prior probabilities) bisa 0 (atawa 1) biasa dipake dina perkara [[Bayesian statistics]], akhirna [[posterior distribution]] bakal sarua hadeana jeung leuwih yakin bisa 0 (atawa 1). Dina basa lain, data teu kudu dicokol keur ngitung sakabehna! Siga Lindley make teori eta, lamun coherent Bayesian ditambahkeun ka nol kamungkinan mimiti kana hipotesa yen Bulan (Moon) dijieun tina keju hejo, saterusna kajadian astronot balik ka bumi mawa keju hejo teu ngayakinkeun manehna. Lindley ngabela yen teu pernah make kamungkinan mimiti 0 atawa 1. Manehna nyebut eta [[Cromwell\'s Rule]], tina tulisan Oliver Cromwell nu nulis muktamar ti Gareja Scotland dina 5 Agustus 1650, manehna ngomong yen \"I beseech you, in the bowels of Christ, consider it possible that you are mistaken.\"\n\n==Disiplin nu dihususkeun==\nSababaraha élmu maké [[statistik terapan]] sacara éksténsif nepi ka migunakeun \'\'[[specialized terminology]]\'\'. Disiplin ieu di antarana:\n* [[Biostatistik]]\n* [[Statistik bisnis]]\n* [[Statistik ékonomi]]\n* [[Statistik téhnik]]\n* [[Fisika statistis]]\n* [[Démografi]]\n* [[Statistik psikologis]]\n* [[Statistik sosial]] (pikeun sadaya élmu \'\'sosial\'\')\n* [[Analisis prosés]] jeung [[Kémometrik]] (pikeun analisis data [[kimia analitis]] jeung [[téhnik kimiawi]])\n* Reliability engineering\n\nStatistik ngawujud jadi salasahiji konci dasar dina dunya bisnis jeung manufaktur. It is used to understand measurement systems variability, control processes (as in [[statistical process control]] or SPC), for summarizing data, and to make data-driven decisions. In these roles it is a key tool, and perhaps the only reliable tool.\n\n== Tempo ogé ==\n*\'\'[[Analisa varian]]\'\' (ANOVA)\n*\'\'[[Extreme value theory]]\'\'\n*[[Régrési liniér]]\n*[[Daptar asosiasi statistis akademik]]\n*[[Daptar layanan statistis international]]\n*[[Daptar jejer statistis]]\n*[[Daptar Statistikawan]]\n*\'\'[[Machine learning]]\'\'\n*\'\'[[Multivariate statistics]]\'\'\n*[[Fénoména statistis]]\n*[[daptar publikasi widang statistik]]\n\n==Tumbu kaluar==\n* [http://www.r-project.org/ Proyék R pikeun Itungan Statistis]\n* [http://www.statsoft.com/textbook/stathome.html Statistics resources]\n* [http://www.mathcs.carleton.edu/probweb/probweb.html The Probability Web]\n* [http://www.math.uah.edu/stat/index.html Laboratorium Maya Kamungkinan jeung Statistik]\n* [http://www.xycoon.com/ Statistics resources and calculators]\n* [http://lib.stat.cmu.edu/ Data, Software jeung Béja ti Masarakat Statistik]\n* [http://www.ericdigests.org/2000-2/resources.htm Resources for Teaching and Learning about Probability and Statistics. ERIC Digest.]\n* [http://www.ericdigests.org/1993/marriage.htm Resampling: A Marriage of Computers and Statistics. ERIC/TM Digest.]\n* [http://www.cbs.nl/isi/ Lembaga Statistis Internasional]\n* [http://members.aol.com/johnp71/javasta2.html Software Statistis Gratis]\n* [http://gsociology.icaap.org/methods/statontheweb.html Free Statistical Tools on the WEB ]\n* [http://www.thenakedscientists.com/HTML/Columnists/robstanforthcolumn2.htm The Probability of Co-incidence]\n\n\n\n\n\n[[ar:إحصائياتُ]] \n[[bg:Статистика]]\n[[ca:Estadística]] \n[[da:Statistik]] \n[[de:Statistik]]\n[[el:Στατιστική]]\n[[en:Statistics]]\n[[es:Estadística]]\n[[et:Statistika]]\n[[fa:آمار]] \n[[fr:Statistiques]] \n[[gl:Estadística]]\n[[he:סטטיסטיקה]] \n[[ia:Statistica]]\n[[it:statistica]] \n[[ja:統計学]] \n[[lv:Statistika]] \n[[ms:Statistik]]\n[[nl:Statistiek]] \n[[pl:Statystyka]] \n[[ro:Statistică]]\n[[ru:Статистика]]\n[[simple:Statistics]] \n[[sl:statistika]]\n[[sv:Statistik]] \n[[zh:统计学]]','/* Sasakala */',3,'Kandar','20050310030417','',0,0,1,0,0.326117524098,'20050310030417','79949689969582'); INSERT INTO cur VALUES (823,0,'Élmu_komputer','Dina basa nu umum, \'\'\'élmu komputer\'\'\' nyaéta élmu ngeunaan [[komputasi]] jeung [[information processing]], boh dina hal [[computer hardware|hardware]] atawa [[software]].\n\n==Pangwanoh==\n\nPikeun kaperluan praktis, élmu komputer kaasup ogé topik-topik anu aya hubunganana jeung [[komputer]], tina hal saperti analisa [[algoritma]] abstrak, [[formal grammar]]s, jeung salian ti eta, nepi ka subyék anu kongkrit saperti [[programming language]], software, jeung hardware komputer. Sabagé disiplin élmu, loba bédana jeung [[matematik]], [[programming]], [[rékayasa software]], sarta [[rékayasa komputer]], sanajan kadang-kadang ngabingungkeun. [[Edsger Dijkstra]] nyebutkeun yén:\n:\'\'\"Computer science is no more about computers than [[astronomy]] is about [[telescope]]s.\"\'\'\nDilengkepan ku [[physicist]] [[Richard Feynman]] nyebutkeun:\n:\'\'\"Computer science is not as old as physics; it lags by a couple of hundred years. However, this does not mean that there is significantly less on the computer scientist\'s plate than on the physicist\'s: younger it may be, but it has had a far more intense upbringing!\"\'\'\n\nTesis [[Church-Turing thesis]] nyebutkeun yen sakabeh tipe paradigma kanyaho anu [[reasonable]] tina komputasi ngarupakeun hal anu sarua pentingnya salila bisa ngagawekeun sanajan aya variasi efisien dina waktu jeung ruang. Tesis ieu lain teorema matematika anu bisa dibuktikeun, tapi a statement based on empirical observation that two distinct computational schemes do in fact have the same computational power. This thesis is a fundamental principle of computer science.\n\nMost research in computer science has been related to [[von Neumann machine|von Neumann computer]]s or [[Turing machine]]s (computers that do one small, deterministic task at a time). These models resemble most real computers in use today. Computer scientists also study other kinds of machines, some practical (like [[Parallel computers|parallel]] machines) and some theoretical (like [[Random computer|random]], [[Oracle (computer science)|oracle]], and [[Quantum computers|quantum]] machines). \n\nComputer scientists study what programs can and cannot do (see [[computability]] and [[artificial intelligence]]), how programs should efficiently perform specific tasks (see [[algoritma]]), how programs should store and retrieve specific kinds of [[information]] (see [[data structures]] and [[data base]]s), and how programs and people should communicate with each other (see [[human-computer interaction]] and [[user interface]]s).\n\nComputer science has roots in [[electrical engineering]], [[mathematics]] and [[linguistics]]. In the last third of the [[abad ka-20|20th century]] computer science has become recognized as a distinct discipline and has developed its own methods and terminology.\n\nThe first computer science department in the [[United States]] was founded at [[Purdue University]] in [[1962]]. The [[University of Cambridge]] in [[England]], among others, taught CS prior to this, however at the time, CS was seen as a branch of [[mathematics]], and not a separate department. Cambridge claims to have the world\'s oldest taught qualification in computing. Most universities today have specific departments devoted to computer science.\n\nThe highest honor in computer science is the [[Turing Award]].\n\n== Related fields ==\n\nComputer science is closely related to a number of fields. These fields overlap considerably, though important differences exist\n\n* [[Information science]] is the study of data and information, including how to interpret, analyze, store, and retrieve it. Information science started as the foundation of scientific analysis of [[communication]] and [[database]]s.\n* [[Computer programming]] or [[software development]] is the act of writing program code.\n* [[Lexicography]] and [[specialized lexicography]] focus on the study of lexicographic reference works and include the study of electronic and Internet-based dictionaries.\n* [[Linguistics]] is the study of [[language]]s, converging with computer science in such areas as [[programming language]] design and [[natural language processing]].\n* [[Software engineering]] emphasizes analysis, design, construction, and testing of useful software. Software engineering includes development methodologies (such as the [[waterfall model]] and [[extreme programming]]) and [[project management]].\n* [[Information systems]] (IS) is the application of computing to support the operations of an organization: operating, installing, and maintaining the computers, software, and data.\n** [[Management information systems]] (MIS) is a subfield of information systems, that emphasizes financial and personnel management.\n* [[Mathematics]] shares many techniques and topics with computer science, but is more general. In some sense, CS is the mathematics of computing.\n* [[Logic]] is a formal system of reasoning, and studies principles that lay at the very basis of computing/reasoning machines, whether it be the hardware (digital logic) or software (verification, AI etc.) levels. The subfield of logic called [[computability logic]] provides a systematic answer to the fundamental questions about what can be computed and how. \n* [[Computer engineering]] is the analysis, design, and construction of computer hardware.\n* [[Information security]] is the analysis and implementation of [[information system]] security, including [[cryptography]].\n\n== Major fields of importance for computer science ==\n\n=== Mathematical foundations ===\n* [[Boolean algebra]]\n* [[Discrete mathematics]]\n* [[Graph theory]]\n* [[Information theory]]\n* [[Symbolic logic]]\n* [[Probability]] and [[Statistics]]\n\n=== Tiori élmu komputer ===\n* [[Algorithmic information theory]]\n* [[Computability theory]]\n* [[Cryptography]]\n* [[Formal semantics]]\n* [[Computation|Theory of computation]] (or \'\'theoretical computer science\'\')\n** analysis of [[algorithm]]s and problem [[Computational complexity theory|complexity]] \n** logics and meanings of programs\n** [[Mathematical logic]] and [[Formal language]]s\n* [[Type theory]]\n\n=== Hardware ===\n(see also [[electrical engineering]])\n* [[Control structures]] and [[Microprogram]]ming\n* [[Arithmetic]] and [[data structures|Logic structures]]\n* [[Computer storage|Memory]] structures\n* [[input/output]] and [[Communications|Data communications]]\n* [[Logic]] Design\n* [[Integrated circuits]]\n** [[Very-large-scale integration|VLSI design]]\n* [[Performance tuning|Performance]] and reliability\n\n=== Computer systems organization ===\n(see also [[electrical engineering]])\n* [[Computer architecture]]\n* [[Computer network]]s\n** [[Distributed computing]]\n* [[Performance tuning|Performance of systems]]\n* [[Computer system]] implementation\n\n=== Software ===\n* [[Computer program]] and [[Computer programming]]\n** [[Parallel Programming]]\n** [[Program specification]]\n** [[Program verification]]\n* [[Computer programming|Programming techniques]] \n* [[Software engineering]]\n** [[Software optimization|Optimization]]\n** [[Software metric]]s\n** [[Configuration management]] and Software Configuration Management ([[SCM]])\n** [[Structured programming]]\n** [[Object-oriented programming|Object orientation]]\n** [[Design pattern (computer science)|Design patterns]]\n** [[Software Documentation|Documentation]]\n* [[Programming language]]s\n* [[Operating Systems]]\n* [[Compiler]]s\n** [[Lexical analysis]]\n** [[Parsing]]\n\n=== Data and information systems ===\n* [[Data structure]]s\n* Data storage representations\n* Data [[encryption]]\n* [[Data compression]]\n* [[Data recovery]]\n* [[Computer programming|Coding]] and [[Information theory]] \n* [[Computer file|Files]] \n** [[File format]]s\n* [[Information systems]] \n** [[Database]]s\n** [[Memory|Information Storage]] and [[Information retrieval|retrieval]]\n** Information Interfaces and Presentation\n\n=== Computing methodologies ===\n* [[Algebra|Symbolic and Algebraic manipulation]]\n* [[Artificial intelligence]]\n* [[Computer graphics]]\n* [[Image processing]] and [[computer vision]]\n* [[Pattern recognition]]\n** [[Speech recognition]]\n* [[Simulation]] and [[Modeling]] \n* [[Document]] and [[Word processing|text processing]] \n* [[Digital signal processing]]\n\n=== Computer applications ===\n* Administrative data processing\n** [[Enterprise resource planning]]\n** [[Customer relationship management]]\n* Mathematical software\n** [[Numerical analysis]]\n** [[Automated theorem proving]]\n** [[Computer algebra system]]s\n* [[Physical science]] and [[Engineering]]\n** [[Computational chemistry]]\n** [[Computational physics]]\n* [[Biology|Life]] and [[Medicine|medical sciences]]\n** [[Bioinformatics]]\n** [[Computational Biology]]\n** [[Medical informatics]]\n* [[Social sciences|Social]] and [[Behavioral science|behavioral sciences]]\n* [[Arts]] and [[Humanities]]\n* [[Computer-aided engineering]]\n* [[Robotics]]\n* [[Human-computer interaction]]\n** [[Speech synthesis]]\n** [[Usability engineering]]\n\n=== [[Computing]] milieux ===\n* [[Computer industry]]\n* [[History of computing hardware]]\n* [[Computers and education]]\n* [[Computers and society]]\n** [[Computer supported cooperative work]]\n* [[Legal aspects of computing]]\n** [[Free software]] and [[Open Source]]\n* Management of computing and [[Information systems]]\n* [[Personal computing]]\n* [[Computer security|Computer]] and [[information security]]\n\n== History ==\n* [[History of computing]]\n* [[List of computer term etymologies|Origins of computer terms]]\n* [[Early programming projects]]\n* [[Computer science departments]]\n* [[Timeline of algorithms]]\n\n== Prominent pioneers in computer science ==\n* [[Charles Babbage]], Designed and built a prototype for a [[difference engine|mechanical calculator]]; designed, but never built, the more powerful [[analytical engine|Analytical Engine]].\n* [[John Backus]] Invention of [[FORTRAN]] (\'\'\'For\'\'\'mula \'\'\'Tran\'\'\'slation), the first practical high-level programming language and the [[Backus-Naur form]] for describing formal language [[syntax]].\n* [[James W. Cooley]] and [[John W. Tukey]] The [[Cooley-Tukey FFT algorithm|Fast Fourier Transform]] and its impact on scientific research. \n* [[Ole-Johan Dahl]] and [[Kristen Nygaard]], inventors of the proto-object oriented language [[SIMULA]].\n* [[Edsger Dijkstra]] for algorithms, [[Goto|Goto considered harmful]], [[rigor]], and pedagogy.\n* [[Tony Hoare|C.A.R Hoare]] for the development of the formal language [[Communicating Sequential Processes]] (CSP) and [[Quicksort]].\n* Admiral [[Grace Hopper|Grace Murray Hopper]], for doing pioneer work in the 1940s, one of the first to recognize the necessity for higher level programming languages, or what she termed \'\'automatic programming\'\'. She wrote the A-O [[compiler]]. Her ideas heavily influenced the [[COBOL]] language.\n* [[Kenneth Iverson]] Inventor of [[APL programming language|APL]], for his contribution to interactive computing. \n* [[William Kahan]] for the IEEE [[floating-point]] standard. (Perhaps this reference should be moved to hardware engineering.)\n* [[Donald Knuth]] for \'\'[[The Art of Computer Programming]]\'\' series.\n* [[Ada Lovelace]], contemporary of Charles Babbage, famous for her \'\'Sketch of the Analytical Engine\'\', an analysis of Babbage\'s work; the namesake for the modern computer language, [[Ada programming language|Ada]].\n* [[John von Neumann]] for devising the [[von Neumann architecture]] upon which most modern computers are based.\n* [[Claude E. Shannon]] for [[information theory]].\n* [[Alan Turing]] for [[computability theory]], pioneering work in the field of [[Artificial Intelligence]], and for the design of the Pilot ACE.\n* [[Maurice Wilkes]] for building the first practical [[stored program]] computer to be completed, and credited with the ideas of several high-level programming language constructs.\n* [[James H. Wilkinson]] The technique of \"backward error analysis\" and advances in the field of [[matrix computations]]. Wilkinson was also a principal mover in the development of the [[Pilot ACE]], the first British computer, in the late [[1940s]]. (See more on Wilkinson in the MacTutor Biographies.)\n* [[Konrad Zuse]] Builder of a binary computer in the [[1930s]], for which he allegedly devised a theoretical high level programming language, [[Plankalkül]]. \n\nSee [[list of computer scientists]] for many more notables.\n\n== Tempo ogé ==\n\n* [[Jejer dasar élmu komputer]]\n* [[Jejer élmu komputer]], daptar nu leuwih lengkep\n* [[Computing]]\n* [[List of computing topics]]\n* [[History of computing]]\n* [[History of computing hardware]]\n* [[Turing Award]] ([[Association for Computing Machinery|ACM]])\n* [[IEEE John von Neumann Medal]]\n* [[Computer jargon]]\n* [[Jargon file|Computer slang]]\n* [[Computing analogies]]\n* [[Internét]]\n* [[Multimédia]]\n* [[Data acquisition]]\n* [[Benchmark]]\n* [[Sensor network]]\n* [[Online computations and algorithms]]\n* [[Computer numbering formats]]\n* [[List of important publications in computer science]]\n\n== Tumbu kaluar ==\n*[http://www.mills.edu/ACAD_INFO/MCS/SPERTUS/Gender/gender.html \'\'Women and Computer Science\'\' by Ellen Spertus]\n*[http://www.dmoz.org/Computers/Computer_Science/ Open Directory Project: Computer Science]\n\n[[Category:Komputasi]]\n[[Category:Élmu komputer]]\n[[Category:Téhnologi]]\n[[Category:Matematik]]\n\n[[af:Rekenaarwetenskap]]\n[[ar:علم الحاسبات]]\n[[bg:Информатика]]\n[[ca:Informàtica]]\n[[cs:Počítačová věda]]\n[[da:Datalogi]]\n[[de:Informatik]]\n[[el:Πληροφορική]]\n[[es:Informática/Computación]]\n[[eo:Komputiko]]\n[[et:Informaatika]]\n[[fr:Informatique]]\n[[fy:Ynformatika]]\n[[ko:컴퓨터 과학]]\n[[hr:Računarstvo]]\n[[id:Ilmu Komputer]]\n[[it:Informatica]]\n[[ia:Informatica]]\n[[hu:Számítástechnika]]\n[[ml:കംപ്യുട്ടര്‍ ശാസ്ത്രം]]\n[[nl:Informatica]]\n[[ja:情報工学]]\n[[no:Datavitenskap]]\n[[pl:Informatyka (technika)]]\n[[pt:Ciência da Computação]]\n[[ro:Informatică]]\n[[ru:Информатика]]\n[[simple:Computer Science]]\n[[sl:Računalništvo]]\n[[sr:Рачунарство]]\n[[fi:Tietojenkäsittelytiede]]\n[[sv:Datavetenskap]]\n[[th:วิทยาการคอมพิวเตอร์]]\n[[tr:Bilgisayar Mühendisliği]]\n[[uk:Інформатика]]\n[[zh-cn:计算机科学]]\n[[zh-tw:計算機科學]]','/* Pangwanoh */',3,'Kandar','20050316082257','',0,0,1,0,0.81840835317,'20050316082257','79949683917742'); INSERT INTO cur VALUES (824,0,'Anatomi','\'\'\'Anatomi\'\'\' (tina [[basa Yunani]] \'\'anatome\'\', tina \'\'ana-temnein\'\', nyiksik), ngarupakeun cabang [[biologi]] nu ngurus struktur jeung organisasi mahluk hirup; sahingga aya anatomi sato([[zootomi]]) jeung anatomi tangkal ([[fitonomi]]).\nCabang utama anatomi nyaéta [[anatomi komparatif]] jeung [[anatomi manusa]].\n\nAnatomi sato bisa ngawengku ulikan struktur sato-sato nu béda mun disebut [[anatomi komparatif]] atawa [[morfologi sato]]. Mun diwates ukur hiji sato, disebutna anatomi husus.\n\nTina jihat mangpaat, ulikan ngeunaan manusa ngarupakeun bagéan nu pangpentingna dina anatomi husus, sarta anatomi manusa ieu bisa ditilik tina jihat nu béda-béda ogé. Tina jihat médis, ieu ngawengku pangaweruh ngeunaan wujud sabenerna, posisi, ukuran, jeung hubungan antara rupa-rupa struktur awak manusa dina kasehatan. Sarta pikeun ulikan ieu kaluar istilah anatomi deskriptif atawa topografis, najan mindeng oge disebut salaku antropotomi. \n\nSangkan meunangkeun pangaweruh nu tepat sacara rinci awak manusa, butuh waktu panenget mangtaun-taun nu pinuh kasabaran nu ngan bisa dipigawé ku saeutik jalma. So intricate is man\'s body that only a small number of professional human anatomists are complete masters of all its details, and most of them specialize on certain parts, such as the brain, viscera, &c.; contenting themselves with a good working knowledge of the rest. \nTopographical anatomy must be learned by each person for himself by the repeated dissection and inspection of the dead human body. It is no more a science than a pilot\'s knowledge is, and, like that knowledge, must be exact and available in moments of emergency. \n\nTina jihat morfologis, anatomi manusa ngarupakeun ulikan nu ilmiah tur matak pogot, sabab tujuanna nu hayang nyingkabkeun [[morfogenesis|sasakala]] struktur tangtungan jelema, and needing a knowledge of the allied sciences of [[émbriologi]] or [[developmental biology]], [[filogeni]], and [[histologi]]. \n\n[[Image:Anatomi otot.jpg|thumb|250px|Gambar anatomis otot manusa na \'\' [[Encyclopédie]]\'\'.]]\n\n[[Anatomical_pathology|Anatomi patologis]] (atawa anatomi morbid) nyéta ulikan ngeunaan organ gering, while sections of normal anatomy, applied to various purposes, receive special names such as medical, surgical, gynaecological, artistic and superficial anatomy. \nThe comparison of the anatomy of different races of mankind is part of the science of physical anthropology or anthropological anatomy. \nIn the present edition of this work the subject of anatomy is treated systematically rather than topographically. \nEach anatomical article contains first a description of the structures of an organ or system (such as nerves, arteries, heart, &c.), as itis found in Man; and this is followed by an account of the development or embryology and comparative anatomy or morphology, as far as vertebrate animals are concerned; but only those parts of the lower animals which are of interest in explaining Man\'s structure are here dealt with. \nThe articles have a twofold purpose; first, to give enough details of man\'s structure to make the articles on physiology, surgery, medicine and pathology intelligible; and, secondly, to give the non-expert inquirer, or the worker in some other branch of science, the chief theories on which the modern scientific groundwork of anatomy is built. \n\n*Sistim-sistim na awak (manusa):\n**[[integumentary system]]\n**[[sistim otot]]\n**[[sistim saraf]]\n**[[sistim réproduktif]]\n**[[sistim napas]]\n**[[sistim ékskresi]]\n**[[sistim sirkulasi]]\n**[[sistim rorongkong]] ([[Rorongkong manusa]])\n**[[sistim éndokrin]]\n**[[digestive system]]\n\n*[[organ (anatomi)|Organ]] na awak (manusa):\n**[[kérod salawé]]\n**[[Vermiform appendix|appendix]]\n**[[otak]]\n**[[pinareup]]\n**[[colon (organ)|colon]] or large intestine\n**[[diaphragm (anatomy)|diaphragm]]\n**[[ceuli]]\n**[[panon]]\n**[[jantung]]\n**[[ginjal]]\n**[[palawangan]]\n**[[larynx]]\n**[[haté]]\n**[[burih]]\n**[[irung]]\n**[[ovary]]\n**[[pharynx]]\n**[[pankréas]]\n**[[sirit]]\n**[[plasénta]]\n**[[rectum]]\n**[[kulit]]\n**[[usus leutik]]\n**[[limpa]]\n**[[stomach]]\n**[[létah]]\n**[[uterus]]\n\n*[[Tulang]] na [[rorongkong manusa]]:\n**[[tulang beuheung]] (clavicle)\n**[[thigh bone]] (femur)\n**[[humerus]]\n**[[rahang]]\n**[[patella]]\n**[[radius (bone)|radius]]\n**[[skull]]\n**[[tibia]]\n**[[ulna]]\n**[[rib]]\n**[[vertebrae]]\n\n*[[Kalenjar]] na awak (manusa):\n**[[ductless gland]]\n**[[kalenjar susu]]\n**[[kalenjar ciduh]]\n**[[thyroid gland]]\n**[[parathyroid gland]]\n**[[adrenal gland]]\n**[[pituitary gland]]\n**[[pineal gland]]\n\n*[[Tissue]]s in the (human) body:\n**[[connective tissue]]\n**[[endothelial tissue]]\n**[[epithelial tissue]]\n**[[glandular tissue]]\n\n*Bagéan luar awak (manusa) nu katempo:\n**[[beuteung]]\n**[[leungeun]]\n**[[tonggong]]\n**[[imbit]]\n**[[dada]]\n**[[ceuli]]\n**[[panon]]\n**[[beungeut]]\n**[[genitals]]\n**[[sirah]]\n**[[sandi (anatomi)|sandi]]\n**[[suku]]\n**[[baham]]\n**[[beuheung]]\n**\'\'[[scalp]]\'\'\n**[[kulit]]\n**[[huntu]]\n**[[létah]]\n\n*Istilah anatomik séjén (teu digolongkeun):\n**[[artery]]\n**[[coelom]]\n**[[diafragma (anatomi)|diafragma]]\n**[[gastrointestinal tract]]\n**[[rambut]]\n**[[exoskeleton]]\n**[[baham]]\n**[[saraf]]\n**[[peritoneum]]\n**[[serous membrane]]\n**[[rorongkong]]\n**[[tangkorak]]\n**[[spinal cord]]\n**[[vein]]\n\n==Artikel nu patali==\n*[[Sajarah anatomi]]\n*[[Organ (anatomi)]]\n*[[Superficial anatomy]]\n*[[List of human anatomical features]]\n*[[zootomical terms for location]].\n*[[Daptar jejer anatomis]]\n\n==Tumbu kaluar==\n*[http://www.innerbody.com/htm/body.html Atlas anatomi \'\'online\'\' bébas]\n*[http://www.npac.syr.edu/projects/vishuman/VisibleHuman.html The NPAC Visible Human Viewer]\n*[http://cancerweb.ncl.ac.uk/omd/index.html Kamus Médis \'\'online\'\']\n*[http://www.bartleby.com/107/ Anatomi Awak Manusa beunang Henry Gray]\n*[http://www.rtstudents.com/ Online Radiologic Anatomy Resources]\n\n{{Biology-footer}}\n\n-----\n\nAya tipe historis sajak Inggris nu disebut \'\'\'anatomy\'\'\', lengkepna mah \'\'\'[[amatory anatomy]]\'\'\'. Ieu ngarupakeun [[sonéta]] cinta nu dibaktikeun pikeun ngagambarkeun babagéan anatomi \'\'[[lover]]\'\', biasana [[awéwé]].\n\n[[Category:Anatomi]]\n[[cy:Anatomeg]] [[da:Anatomi]] [[de:Anatomie]] [[et:Anatoomia]] [[en:Anatomy]] [[es:Anatomía]] [[eo:Anatomio]] [[fr:Anatomie]] [[fy:Anatomy]] [[it:Anatomia]] [[ia:Anatomia]] [[nl:Anatomie]] [[ja:解剖学]] [[pl:Anatomia]] [[pt:Anatomia]] [[simple:Anatomy]] [[sv:Anatomi]]','',3,'Kandar','20041029095009','',0,0,0,0,0.20529359868,'20041203125804','79958970904990'); INSERT INTO cur VALUES (825,0,'Antropologi','\'\'\'Antropologi\'\'\' ngarupakeun ulikan ngeunaan [[manusa]] (tempo genus [[Hominoid|Homo]]) nu nagdung nagdung dua harti [[holistik]]: patali jeung sakabéh manusa di sakabéh jaman, ogé sakabéh diménsi kamanusaan. Nu jadi puseur na antropologi nyaéta konsép [[budaya]], jeung gagasan yén bawaan manusa téh budaya; yén spésiés urang geus ngalaman évolusi kamampuhan universal pikeun ngabayangkeun alam dunya sacara [[simbol]]is, pikeun ngajarkeun jeung diajar simbol-simbol éta sacara sosial, jeung pikeun ngatransformasikeun dunya (kaasup urangna) dumasar kana simbol-simbol éta.\n\nDi [[Amérika Serikat]], \'\'\'antropologi\'\'\' biasana dibagi kana opat widang: \n* [[antropologi fisik]], nu ngulik [[primatology|paripolah primata]], [[évolusi manusa]], jeung [[genetik populasi]]; kadang widang ieu disebut ogé [[antropologi biologis]].\n* [[antropologi budaya]], (ogé disebut antropologi sosial atawa antropologi sosiokultural). Widang-widang nu diulik dina antropologi budaya di antarana \'\'social networks\'\', \'\'paripolah sosial\'\', \'\'pola [[duduluran]]\'\', politik, kapercayaan, pola produksi, exchange, konsumsi, sarta éksprési budaya séjénna; \n* [[antropologi basa linguistik]], nu ngulik variasi [[basa]] meuntasan wanci jeung rohangan, mangpaat sosial basa, sarta hubungan antara basa jeung budaya; jeung\n* [[arkéologi]], nu ngulik titinggal [[masarakat]] (di [[Inggris]] mindeng dipisahkeun).\n\nNu anyaran ieu, sababaraha program \'\'\'antropologi\'\'\' di AS mimiti meulah widang ieu jadi dua, nu hiji nekenkeun [[kamanusaan]] jeung [[téori kritis]], nu séjénna nekenkeun [[élmu alam]] jeung [[positivisme]].\n\n\n==Kontéks historis jeung institusional==\n\nAntropolog [[Eric Wolf]] kungsi nyirikeun antropologi salaku kamanusaan nu pang ilmiahna jeung élmu sosial nu pang manusawina. Ngarti kumaha tumuwuhna antropologi bakal ngabantu urang neuleuman kumaha ieu élmu bisa luyu jeung disiplin akademis lainna.\n\nAntropolog kontémporér ngaku yén sababaraha ahli pikir heubeul salaku \"karuhun\"-na jeung yén disiplin ieu boga sumber nu loba. Ngan, antropologi leuwih bisa dihartikeun salaku hasil tina \'\'[[Jaman Pencerahan]]\'\'. Nalika jaman ieu pisan urang Éropah ngulik paripolah manusa sacara sistematis. Tradisi [[yurisprudénsi]], [[sajarah]], [[filologi]], jeung [[sosiologi]] tumuwuh dina mangsa ieu, kaasup [[élmu sosial]] nu ngawengku antropologi. Dina waktu nu sarua, réaksi \'\'[[romantisisme|romantic]]\'\' tina ayana \'\'Pencerahan\'\' ieu ngahasilkeun ahli pikir kawas [[Herder]] nu dituturkeun ku [[Wilhelm Dilthey]] nu ngawujudkeun dasar pikeun konsép budaya nu ngarupakeun puseur disiplin ieu.\n\nSacara kalembagaan, antropologi mucunghul ti [[sajarah alam]] (dibéjérbéaskeun ku \'\'penulis\'\' kawas [[Buffon]]) nu ngulik ngeunaan umat manusa - utamana nu hirup di [[kolonialisme|koloni]] Éropah]]. Jadi, ngulik basa, budaya, fisiologi, jeung titinggal koloni Éropah leuwih kurang sarua jeung ngulik flora jeung fauna tempat éta. Ku alesan éta, misalna, [[Lewis Henry Morgan]] bisa nyieun monograf \'\'The League of the Iroquois\'\' jeung \'\'The American Beaver and His Works\'\' sakaligus. Ieu ogé nu jadi alesan pangna barang-barang budaya bangsa \"beradab\" kawas Cina dipintonkeun di muséum-muséum seni di sapanjang Éropah, sedengkeun titinggal budaya ti Afrika atawa Pribumi Amerika Kalér dipintonkeunna di Muséum Natural History babarengan jeung tulang-taléng dinosaurus sarta diorama alam. Kabéjakeun, prakték modél kieu geus robah sacara dramatis dina sababaraha taun ieu, sarta salah mun nganggap antropologi samata-mata hasil peran kolonial jeung chauvinisme urang Éropah, sabab patalina jeung [[imperialisme]] téh rumit.\n\nAntropologi tumuwuh misah ti sajarah alam, dina panungtungan abad ka dalapan welas disiplin ieu geus mimiti ngawujud kana bentuk nu modern - taun 1935, misalna, T.K. Penniman geus bisa nulis buku sajarah ngeunaan disiplin ieu dina judul \'\'A Hundred Years of Anthropology\'\'. Mangsa harita, widang ieu didominasi ku \'métode komparatif\'. Sakabéh maasrakat dianggap geus ngaliwatan hiji prosés évolusionér tunggal ti nu paling primitif nepi ka paling maju. Masarakat Non-Éropah kungsi ditilik salaku \'fosil hirup\' évolusionér nu bisa diulik pikeun nalungtik bangsa Éropah jaman baheula. Para sarjana narulis sajarah ngeunaan migrasi prasajarah nu kadang aya mangpaatna, tapi mindeng ogé pikahéraneun. DIna mangsa ieu pisan bangsa Éropah munggaran bisa sacara akurat nyukcruk migrasi [[urang Polinésia]] meuntasan [[Sagara Pasifik]] misalna - najan sawaréh ti antarana yakin yén asalna ti [[Mesir]]. Pamungkas, konsép ngeunaan [[ras]] geus sacara aktif disawalakeun salaku hiji cara pikeun ngagolongkeun - jeung ngurutkeun - umat manusa dumasar kana béda sipat/ciri biologisna.\n\n==Antropologi di A.S.==\nAntropologi di A.S. dialpukahan ku [[Franz Boas]], nu ngamangpaatkeun posisina di [[Columbia University]] jeung [[American Museum of Natural History]] pikeun ngalatih tur ngembangkeun sababaraha angkatan murid. Boasian anthropology was politically active and suspicious of generalizations. Boas studied immigrant children in order to demonstrate that biological race was not immutable and that humans conduct and behavior was the result of nature rather than nurture. Drawing on his German roots, he argued that the world was full of distinct \'cultures\' rather than societies whose evolution could be measured by how much or how little \'civilization\' they had. Boas felt that each culture has to be studied in its particularity, and argued that cross-cultural generalizations like those made in the [[natural science]]s were not possible. In doing so Boas fought discrimination against immigrants, African Americans, and Native North Americans.\n\nBoas\'s first generation of students included [[Alfred Kroeber]], [[Robert Lowie]], and [[Edward Sapir]]. All of these scholars produced richly detailed studies which were to first to describe Native North America. In doing so they provided a wealth of details used to attack evolutionary theory. Their focus on Native American languages also helped establish linguistics as a truly general science and free it from its historical focus on Indo-European languages.\n\nThe publication of [[Alfred Kroeber]]\'s textbook \'\'Anthropology\'\' marked a turning point in American anthropology. After three decades of amassing material the urge to generalize grew. This was most obvious in the \'Culture and Personality\' studies carried out by younger Boasians such as [[Margaret Mead]] and [[Ruth Benedict]]. Influenced by psychologists such as [[Sigmund Freud]] and [[Carl Jung]], these authors sought to understand that way that individual personalities were shaped by the wider cultural and social forces in which they grew up. While Culture and Personality works such as \'\'Coming of Age in Samoa\'\' and \'\'The Chrysanthemum and the Sword\'\' remain popular with the American public, Mead and Benedict never had the impact on the discipline of anthropology that some expected. While Boas had planned that Ruth Benedict succeed him as chair of Columbia\'s anthropology department, she was sidelined by [[Ralph Linton]], and Mead was limited to her offices at the [[American Museum of Natural History| ANHM]].\n\n==Antropologi di Inggris==\nWhereas Boas picked his opponents to pieces through attention to detail, in Britain modern anthropology was formed by rejecting historical reconstruction in the name of a science of society that focused on analyzing how societies held together in the present.\n\nThe two most important names in this tradition were [[Alfred Reginald Radcliffe-Brown]] and [[Bronislaw Malinowski]], both of\nwhom released seminal works in 1922. Radcliffe-Brown\'s initial fieldwork in the [[Andaman Islands]] was carried out in the old style, but after reading [[Emile Durkheim]] he published an account of his research (entitled simply \'\'The Andaman Islanders\'\') which drew heavily on the French sociologist. Over time he developed an approach known as structure-functionalism, which focused on how institutions in societies worked to balance out or create an equilibirum in the social system to keep it functioning harmoniously. [[Bronislaw Malinowski| Malinowski]], on the other hand, advocated an unhyphenated \'functionalism\' which examined how society functioned to meet individual needs. Malinowski is best known not for his theory, however, but for his detailed ethnography and advances in methodology. His classic \'\'Argonauts of the Western Pacific\'\' advocated getting \'the native\'s point of view\' and an approach to field work that became standard in the field.\n\nMalinowksi and Radcliffe-Brown\'s success stem from the fact that they, like Boas, actively trained students and aggresively built up institutions which furthered their programmatic ambitions. This was particularly the case with Radcliffe-Brown, who spread his agenda for \'Social Anthropology\' by teaching at universities across the [[Commonwealth of Nations|Commonwealth]]. From the late 1930s until the post-war period a string of monographs and edited volumes appeared which cemented the paradigm of British Social Anthropology. Famous ethnographies include \'\'The Nuer\'\' by [[Edward Evan Evans-Pritchard]] and \'\'The Dynamics of Clanship Among the Tallensi\'\' by [[Meyer Fortes]], while well known edited volumes include \'\'African Systems of Kinship and Marriage\'\' and \'\'African Political Systems\'\'.\n\n==Antropologi di Prancis==\nAnthropology in France has a less clear genealogy than the British and American traditions. Most commentators consider [[Marcel Mauss]] to be the founder of the French anthropological tradition. Mauss was a member of [[Emile Durkheim| Durkheim\'s]] [[Annee Sociologique]] group, and while Durkheim and other examined the state of modern societies, Mauss and his collaborators (such as [[Henri Hubert]] and [[Robert Hertz]]) drew on ethnography and philology to analyze societies which were not as \'differentiated\' as European nation states. In particular, Mauss\'s \'\'Essay on the Gift\'\' was to prove of enduring relevance in anthropological studies of [[exchange]] and [[reciprocity]].\n\nThroughout the interwar years, French interest in anthropology often dovetailed with wider cultural movements such as [[surrealism]] and [[primitivism(art movement)| primitivism]] which drew on ethnography for inspiration. [[Marcel Griaule]] and [[Michel Leiris]] are examples of people who combined anthropology with the French avant-garde.\n\nAbove all, however, it was [[Claude Levi-Strauss]] who helped institutionalize anthropology in France. In addition to the enormous influence his [[structuralism]] exerted across multiple disciplines, Levi-Strauss established ties with American and British anthropologists. At the same time he established centers and labratories within France to provide an institutional context within anthropology while training influential students such as [[Maurice Godelier]] and [[Francoise Heritier]] who would prove influential in the world of French anthropology.\n\n==Antropologi sanggeus Perang Dunya Kadua==\nMéméh [[PD II]] \'antropologi sosial\' Inggris jeung \'antropologi budaya\' Amérika masih mangrupa dua tradisi nu béda. Sanggeus perang nu dua ieu bisa ngahiji ngawujud antropologi \'sosiobudaya\'.\n\nTaun [[1950]]-an jeung panengah [[1960]]-an antropologi tumuwuhna condong kawas [[élmu alam]]. Kayaning [[Llyd Fallers]] jeung [[Clifford Geertz]] museurkeun manéh kana prosés modernisasi by which newly independent states could develop. Others, such as [[Julian Steward]] and [[Leslie White]] focused on how societies evolve and fit their ecological niche - an approach popularized by [[Marvin Harris]]. [[Economic Anthropology]] as influenced by [[Karl Polanyi]] and practiced by [[Marshall Sahlins]] and [[Greg Dalton]] focused on how traditional [[economics]] ignored cultural and social factors. In England, British Social Anthropology\'s paradigm began to fragment as [[Max Gluckman]] and [[Peter Worsley]] experimented with Marxism and authors such as [[Rodney Needham]] and [[Edmund Leach]] incorporated Levi-Strauss\'s structuralism into their work.\n\nStructuralism also influenced a number of development in 1960s and 1970s, including [[cognitive anthropology]] and componential analysis. Authors such as [[David Schneider]], [[Clifford Geertz]], and [[Marshall Sahlins]] developed a more fleshed out concept of culture as a web or meaning or signification which proved very popular. In keeping with the times, much of anthropology became politicized through its opposition to the [[Vietnam War]] and the [[Algerian War of Independence]] and the authors of volumes such as \'\'Reinventing Anthropology\'\' worried about its relevance and [[Marxism]] became more and more popular in the discipline.\n\nIn the 1980s issues of power, such as those examined in [[Eric Wolf]]\'s \'\'Europe and the People Without History\'\' - were central to the discipline. Books like \'\'Anthropology and the Colonial Equality\'\' pondered anthropology\'s ties to colonial inequality, while the immense popularity of authors such as [[Antonio Gramsci]] and [[Michel Foucault]] moved issues of power and hegemony into the spotlight. Gender and sexuality became a popular topic, as did the relationship between history and anthropology, influenced by [[Marshall Sahlins]] (again) who drew on [[Levi-Strauss]] and [[Fernand Braudel]] to examine the relationship between cultural structure and individual agency. \n\nIn the late 1980s and 1990s authors such as [[George Marcus]] and [[James Clifford]] pondered ethnographic authority and how and why anthropological knowledge was possible and authoritative. This was part of a more general trend of [[postmodernism]] that was popular. Currently anthropology focuses on globalization, medicine and biotechnology, indigenous rights, and the anthropology of Europe.\n\n==Konsép-konsép antropologis==\n*[[Behavioral modernity]]\n*[[Kolonialisme]]\n*[[Budaya]]\n*[[Bangsa]]\n*[[Exchange]] and [[Reciprocity]]\n*[[Kulawarga]]\n*[[Gender role]]\n*[[Kinship and descent]]\n*[[Nikah]]\n*[[Sistim politik]]\n*[[Ras]]\n*[[Agama]]\n*[[Subsistence]]\n*[[Transkulturasi]]\n\n==Widang jeung subwidang antropologis==\n*[[Antropologi biologis]] (ogé [[Antropologi fisik]])\n**[[Antropologi forénsik]]\n**[[Paléoétnobotani]]\n*[[Antropologi budaya]] (ogé [[Antropologi sosial]])\n**[[Antropologi terapan]]\n**\'\'[[Studi lintas-budaya]]\'\' \n**\'\'[[Cyber anthropology]]\'\'\n**[[Development anthropology]]\n**[[Antropologi lingkungan]]\n**[[Antropologi ékonomi]]\n**[[Étnografi]]\n**[[Étnomusikologi]]\n**[[Antropologi médis]]\n**[[Antropologi prikologis]]\n**[[Antropologi politis]]\n**[[Antropologi agama]]\n**[[Antropologi publik]]\n**\'\'[[Antropologi visual]]\'\'\n\n*[[Antropologi linguistik]]\n**[[Linguistik singkronik]] (atawa [[Linguistik deskriptif]])\n**[[Linguistik diakronik]] (atawa [[Linguistik historis]])\n**[[Étnolinguistik]]\n**[[Sosiolinguistik]]\n\n*[[Arkéologi]]\n\n==Tempo ogé== \n* [[Daptar antropolog]]\n\n\n\n[[Category:Antropologi]]\n[[af:Antropologie]] [[bg:Антропология]] [[ca:Antropologia]] [[da:Antropologi]] [[de:Anthropologie]] [[en:Anthropology]] [[es:Antropología]] [[eo:Antropologio]] [[et:Antropoloogia]] [[fr:Anthropologie]]\n[[gl:Antropoloxía]] [[fy:Antropology]] [[ko:인류학]] [[ku:Antropolojî]]\n[[ms:Antropologi]] [[nl:Antropologie]] [[ja:人類学]] [[no:Antropologi]]\n[[pl:Antropologia]] [[pt:Antropologia]] [[ro:Antropologie]] [[ru:Антропология]] [[sa:मानवविज्ञानं]] [[simple:Anthropology]] [[sl:antropologija]] [[fi:Antropologia]] [[sv:Antropologi]]\n[[zh:人类学]]','/* Antropologi sanggeus Perang Dunya Kadua */',3,'Kandar','20050113074806','',0,0,0,0,0.3428891652,'20050113074806','79949886925193'); INSERT INTO cur VALUES (826,0,'Téhnologi','\'\'\'Téhnologi\'\'\' mibanda leuwih ti hiji harti. Nu hiji ngarupakeun tumuwuh jeung tumerapna [[parabot]], [[mesin]], [[bahan]], jeung [[prosés]] nu nulungan manusa méréskeun masalah sarta nedunan pangabutuh. Salaku kagiatan manusa, téhnologi ngamangsa boh [[élmu]] boh [[rékayasa]]. Istilah \'\'téhnologi\'\' ku sabab kitu mindeng dicirikeun ku papanggihan-papanggihan jeung \'\'[[gadget]]\'\' maké prinsip jeung prosés ilmiah nu anyaran kapanggih. Tapi, [[papanggihan]] nu geus heubeul pisan saperti [[gilinding]] gé ngarupakeun conto téhnologi.\n\nHarti séjén -- dipaké na widang [[ékonomi]] -- nilik téhnologi salaku wujud \'\'mutahir\'\' pangaweruh urang dina cara ngagabungkeun rupa-rupa sumberdaya pikeun ngahasilkeun produk nu dipikahayang (jeung pangaweruh urang kana naon wae nu bisa dihasilkeun). Ku kituna, urang bisa nempo \'\'\'parobahan téhnologis\'\'\' nalika pangaweruh téhnis urang ningkat/nambahan. \n\n== Téhnologi jeung idéologi ==\n\nMindeng pisan, \"anyar\" dianggap boga harti \"leuwih hadé\" dina puseuran téhnologi jeung rékayasa. Pamanggih ngeunaan [[téhnologi tepat guna]] nu tumuwuh dina abad ka-20 pikeun ngagambarkeun kaayaan di tempat nu teu pati miharep ayana téhnologi mutahir atawa téhnologi nu merlukeun ayana [[infrastruktur]] atawa suku cadang atawa kaahlian nu diimpor. \'\'Pergerakan [[eco-village]]\'\' ogé milu ketak dina masalah ieu. [[Téhnologi panengah]], nu loba patalina jeung [[daptar artikel ékonomi|masalah ékonomi]], nu dimaksudkeun salaku jalan tengah antara téhnologi puseur nu mahal di [[nagara maju]] jeung [[nagara tumuwuh]] nu ngarasakeun cukup éféktif pikeun nyerep pagawé nu sakitu lobana dina kaayaan monétér nu seuseut seuat. Sacara umum, téhnologi nu \"tepat guna\" sakaligus bakal \"panengah\". \n\nDina [[ékonomi]], harti atawa anggapan ngeunaan [[kamajuan]] atawa \'\'[[pertumbuhan ekonomi|pertumbuhan]]\'\' mindeng dipatalikeun jeung hiji atawa leuwih anggapan di luhur. Challenging prevailing assumptions about technology and its usefulness has led to ideas like [[uneconomic growth]] or [[measuring well-being]]. These, and economics itself, can often be described as technologies, specifically, as [[persuasion technology]] - a concern covered in its own separate article.\n\n==Konsép-konsép na téknologi==\n* \'\'[[Technological singularity]]\'\'\n* [[Prinsip pencegahan]]\n* [[Strategi téhnologi]] (ngamangpaatkeun kamajuan téhnologi sacara strategis)\n* [[Téhnokapitalisme]] \n* \'\'[[Emergent philosophy]]\'\'\n* [[Transhumanisme]]\n* [[Poshumanisme]]\n* [[Téhnologi panengah]]\n* [[Téhnologi tepat guna]]\n* [[Alih téhnologi]]\n* [[Daur hirup téhnologi]]\n* \'\'[[Technology acceptance model]]\'\'\n* [[Internét]]\n\n== Tempo ogé ==\n* \'\'[[Golden hammer]]\'\'\n* [[Sajarah élmu jeung téhnologi]]\n* [[Téhnik]]\n* \'\'[[Technology assessment]]\'\' \n* \'\'[[Timeline of inventions]]\'\'\n* \'\'[[Technological convergence]]\'\'\n* [[Daptar téhnologi]]\n* [[-ologi|Daptar -ologi]]\n\n\n{{Téhnologi}}\n\n[[Category:Daptar jejer]] [[Category:Téhnologi]]\n\n[[af:Tegnologie]] [[ms:Teknologi]] [[ca:Tecnologia]] [[da:Teknologi]] [[de:Technologie]] [[en:Technology]] [[eo:Teknologio]] [[es:Tecnología]] [[fr:Technologie]] [[hr:Tehnologija]] [[it:Tecnologia]] [[ja:工業]]\n[[la:Technologia]] [[nl:Technologie]] [[sw:Teknolojia]] [[th:เทคโนโลยี]]\n[[zh:技术]]','/* Tempo ogé */',3,'Kandar','20041111061153','',0,0,0,0,0.873849955794,'20041111061153','79958888938846'); INSERT INTO cur VALUES (827,0,'Élmu',':\'\'Pikeun jurnal nu ngaranna \'\'Science\'\', tempo [[Science (jurnal)]].\'\'\n\n\'\'\'Élmu\'\'\' sakaligus ngarupakeun prosés ngumpulkeun pangaweruh jeung wangunan pangaweruh nu kakumpulkeun ku prosés ieu. \'\'Prosés ilmiah\'\' ngarupakeun \'\'akuisisi sistematik\'\' [[pangaweruh]] anyar ngeunaan hiji [[sistem]]. Akuisisi sistematik ieu sacara umum mah [[métode ilmiah]], sedengkeun sistemna umumna [[alam]]. Élmu ogé ngarupakeun \'\'pangaweruh ilmiah\'\' nu sacara sistematik kaala ku \'\'prosés ilmiah\'\' ieu. \n\nSabaraha papanggihan élmu bisa \'\'[[counter-intuitive]]\'\' pisan. [[Téori atom]], misalna, nunjukkeun yén guruntulan granit nu katémbong beurat, teuas, padet, abu-abu, jsb. sabenerna ngarupakeun campuran [[fisika partikel|partikel]] subatomik nu saeutik gé teu mibanda sipat-sipat éta, nu gerak cepet pisan dina hiji rohangan nu lolobana kosong. Many of humanity\'s preconceived notions about the workings of the universe have been challenged by new scientific discoveries.\n\n== Modél, téori, jeung hukum ilmiah ==\n\n\'\'Artikel utama:\'\' [[métode ilmiah]]\n\nIstilah \"[[hipotésis]]\", \"[[modél]]\", \"[[téori]]\", jeung \"[[hukum fisika|hukum]]\" dina élmu mibanda larapan nu béda jeung istilah umum. Élmuwan migunakeun istilah \'\'modél\'\' nujul ka dadaran hiji hal, hususna nu ditujukeun pikeun nyieun pangira nu bisa diuji ku dicoba atawa panenget/observasi. \'\'Hipotésis\'\' nyaéta a contention that has not (yet) been well supported nor ruled out by experiment. \'\'Hukum fisika\'\' atawa \'\'hukum alam\'\' nyaéta a scientific generalization based on empirical observations. \n\nMost non-scientists are unaware that what scientists call \"theories\" are what most people call \"facts\". The general public uses the word \'\'theory\'\' to refer to ideas that have no firm proof or support; in contrast, scientists usually use this word to refer only to ideas that have repeatedly withstood test. Thus, when scientists refer to the theories of [[evolution|biological evolution]], [[electromagnetism]], and [[relativity]], they are referring to ideas that have survived considerable experimental testing. But there are exceptions, such as [[string theory]], which seems to be a promising model but as yet has no empirical evidence to give it precedence over competing models. \n\nEspecially fruitful theories that have withstood the test of time are considered to be \"proven\" in the scientific sense-- that it is true and factual but of course can still be falsified. This includes many theories, such as universally accepted ones such as [[heliocentric theory]] and controversial ones such as [[evolution]], which are backed by many observations and experimental data. Theories are always open to revision if new evidence is provided or directly contradicts predictions or other evidence. As scientists do not claim absolute knowledge, even the most basic and fundamental theories may turn out to be incorrect if new data and observations contradict older ones.\n\n[[Isaac Newton|Newton]]\'s [[Newtonian mechanics|law of gravitation]] is a famous example of a law falsified by experiments regarding motions at high speeds and in close proximity to strong gravitational fields. Outside of those conditions, Newton\'s Laws remain excellent accounts of motion and gravity. Because [[general relativity]] accounts for all of the phenomena that Newton\'s Laws do, and more, general relativity is currently regarded as our best account of gravitation.\n\n== Matematik jeung métode ilmiah ==\n\n[[Matematik]] \'\'esensial\'\' pikeun élmu, mangpaat pangpentingna nyaéta dina éksprési/ngawujudkeun \'\'modél\'\' ilmiah. Nengetan tur ngumpulkeun ukuran-ukuran, ogé nyieun hipotésis jeung pangduga, biasana merlukeun modél matematis sarta maké matematik kalawan éksténsif. Cabang matematik nu pangmindengna dipaké dina élmu di antarana [[kalkulus]] jeung [[statistik]], najan sabenerna sakabéh cabang matematik boga larapanana, kaasup wewengkon \"murni\" saperti [[téori wilangan]] jeung [[topologi]].\n\nSome thinkers see mathematicians as scientists, regarding physical experiments as inessential or mathematical proofs as equivalent to experiments. Others do not see mathematics as a science, since it does not require experimental test of its theories and hypotheses. In either case, the fact that mathematics is such a useful tool in describing the universe is a central issue in the [[philosophy of mathematics]].\n\nTempo: [[Eugene Wigner]] [[The Unreasonable Effectiveness of Mathematics in the Natural Sciences|The Unreasonable Effectiveness of Mathematics]]. \n\n[[R.P. Feynman]] nyarita \"Matematik mah teu nyata, tapi \'\'\'asa\'\'\' nyata. Di mana nya perenahna?\".\n\n==Tujuan élmu==\n\nDespite popular impressions of science, it is not the goal of science to answer all questions, only those that pertain to physical reality (measurable empirical experience). Also, science cannot possibly address all possible questions, so the choice of which questions to answer becomes important. Science does not and can not produce absolute and unquestionable truth. Rather, science consistently tests the currently best hypothesis about some aspect of the physical world, and when necessary revises or replaces it in light of new observations or data.\n\nScience does not make any statements about how nature actually \"is\"; science can only make conclusions about our \'\'observations\'\' of nature. The developments of quantum mechanics in the early 20th century showed that observations are not independent of interactions, and the implications of wave-particle duality have challenged the traditional notion of \"objectivity\" in science.\n\nScience is not a source of subjective value judgements, though it can certainly speak to matters of ethics and public policy by pointing to the likely consequences of actions. However, science can\'t tell us which of those consequences to desire or which is \'best\'. What one projects from the currently most reasonable scientific hypothesis onto other realms of interest is not a scientific issue, and the scientific method offers no assistance for those who wish to do so. Scientific justification (or refutation) for many things is, nevertheless, often claimed.\n\n==Perenahna élmu==\n\nÉlmu dipraktékkeun di [[universitas]] jeung lembaga ilmiah séjénna; najan ngarupakeun cocooan para [[akademia]], ogé dipraktékkeun ku [[amatir]], hususna dina [[observation]]al part of science.\n\nSome workers in corporate research laboratories also practice the methods of science and eventually become renowned enough in their fields to also work in academia. Conversely, some academics become well-known enough to consult to industry by applying their findings in some [[technology]].\n\n==Widang élmu==\n\n=== Élmu fisik jeung hirup ===\n\n* [[Arkéologi]]\n\n* [[Biologi]]\n** [[Élmu tatanén]]\n** [[Anatomi]]\n** [[Antropologi]]\n** [[Astrobiologi]]\n** [[Biokimia]]\n** [[Bioinformatik]] \n** [[Biofisik]]\n** [[Botani]]\n** [[Biologi sél]]\n** [[Kladistik]]\n** [[Sitologi]]\n** [[Developmental biology]] \n** [[Ékologi]]\n** [[Éntomologi]]\n** [[Épidemiologi]]\n** [[Évolusi]] (Biologi évolusioner) \n** [[Biologi pertumbuhan évolusionér]] (\"\'\'Evo-devo\'\'\" atawa évolusi pertumbuhan)\n** [[Biologi cai seger]]\n** [[Genetik]] ([[Genetik populasi]], [[Genomik]], [[Protéomik]])\n** [[Élmu Kaséhatan]]\n*** [[Dentistry]]\n*** [[Tatamba]]\n*** [[Farmakologi]]\n*** [[Toksikologi]]\n*** [[Tatamba ingon]]\n** [[Histologi]]\n** [[Imunologi]] \n** [[Biologi laut]]\n** [[Mikrobiologi]]\n** [[Biologi Molekular]]\n** [[Morfologi]]\n** [[Élmu saraf]]\n** [[Onkologi]] (ulikan ngeunaan kanker)\n** [[Ontogeni]]\n** [[Paléontologi]]\n** [[Patologi]]\n** [[Fikologi]] (Algologi) \n** [[Filogeni]]\n** [[Fisiologi]]\n** [[Biologi struktural]]\n** [[Taksonomi]]\n** [[Toksikologi]]\n** [[Virologi]]\n** [[Zoologi]]\n\n* [[Élmu Bumi]]\n** [[Géologi]]\n** [[Météorologi]]\n** [[Oséanografi]]\n** [[Séismologi]]\n\n* [[Fisika]]\n** [[Akustik]]\n** [[Astronomi]]\n** [[Astrofisik]]\n** [[Fisika Atomik, Molekular, jeung Optis]]\n** [[Biofisik]]\n** [[Fisika komputasi]]\n** [[Fisika zat padet]]\n** [[Kriogenik]]\n** [[Éléktronik]]\n** [[Rékayasa]]\n** [[Dinamika cairan]]\n** [[Fisika polimér]]\n** [[Optik]] \n** [[Fisika bahan]]\n** [[Fisika matematis]]\n** [[Fisika inti]]\n** [[Fisika plasma]]\n** [[Fisika partikel]] (atawa Fisika énergi luhur) \n** [[Dinamika kendaraan]] \n\n* [[Kimia]] \n** [[Kimia analitik]]\n** [[Biokimia]]\n** [[Kimia komputasi]]\n** [[Éléktrokimia]]\n** [[Kimia anorganik]]\n** [[Élmu bahan]]\n** [[Kimia organik]]\n** [[Kimia fisik]]\n** [[Kimia kuantum]]\n** [[Spéktroskopi]]\n** [[Stéréokimia]]\n** [[Térmokimia]]\n\n=== Komputer jeung élmu informasi ===\n\n* [[Élmu komputer]]\n* [[Élmu kognitif]]\n* [[Sistem kognitf]]\n* \'\'[[Cybernetics]]\'\'\n* [[Téori sistem]]\n* [[Téknologi Informasi]]\n\n=== [[Élmu sosial]] ===\n\n* [[Ékonomi]]\n* [[Linguistik]]\n* [[Étimologi]]\n* [[Psikologi]]\n* Psikopatologi\n* [[Sosiologi]]\n* [[Atikan]]\n* [[Gawé Sosial]]\n\n==Filosofi==\n\nScience’s effectiveness has made it a subject of much [[philosophy|philosophical]] speculation. The [[philosophy of science]] seeks to understand the nature and justification of scientific knowledge, and its ethical implications. It has proved remarkably difficult to provide an [[Scientific_method#Philosophical_Issues |account of the scientific method]] that can serve to distinguish science from non-science.\n\n\n\n==Jejer nu patali==\n\n*Organisasi jeung prakték élmu: [[International Council of Science]] (ICSU)\n*Pikeun dadaran kumaha tumuwuhna ieu widang, tempo [[Sajarah Élmu jeung Téhnologi]]. \n*Tempo ogé [[élmuwan]] pikeun katalog jalma-jalma nu giat dina widang-widangna.\n\n==Tempo ogé==\n[[Tiori dasar élmu]] -\n[[Élmu runtah]] - \n[[Patafisik]] - \n[[Élmu patologis]] - \n[[Filosofi élmu]] -\n[[Protosains]] - \n[[Pseudosains]] - \n[[Atikan élmu]] - \n[[Scientific enterprise]] -\n[[Scientific misconduct]] -\n[[Scientific materialism]] -\n[[Métode ilmiah]] -\n[[Révolusi ilmiah]] -\n[[Hubungan antara agama jeung élmu]] - \n[[Patarosan sadidinten]] - \n[[Daptar publikasi ilmiah]]-\n[[List of scientific howlers in literature]]-\n\n==Tumbu kaluar==\n\n*[http://unisci.com/science2.shtml UniSci: Naha Bet Élmu?]\n*[http://www.mit.edu/~bkrupa/whyscience.html Boris Krupa: Naha Bet Élmu?]\n*[http://www.people.virginia.edu/~rjh9u/studysci.html Keur Naon Ngulik Élmu?]\n*[http://www.scienceandyou.org/articles/ess_01.shtml Naha Bet Élmu & Anjeun]\n*[http://www.epinions.com/content_2841616516 Naha élmu teu bisa démokratis]\n*[http://physicsweb.org/article/world/13/5/2 Why science thrives on criticism]\n*[http://www.edge.org/documents/archive/edge53.html Is Science Killing the soul? A discussion between Steven Pinker and Richard Dawkins]\n*[http://www.thehumanist.org/humanist/articles/dawkins.html Richard Dawkins essay: Is Science a Religion?]\n*[http://textbook.wikipedia.org/wiki/General_Science Wikibooks - GSCE science textbook]\n*[http://science.shumans.com Daily Science News]\n* Alphabetized and ordered list of sciences adapted from the Internet-Encyclopedia article, \"Science\" [http://www.internet-encyclopedia.info/wiki.phtml?title=Science Internet-Encyclopedia March 14, 2003]\n\n\n[[Category:Tepas]]\n[[Category:Élmu]]\n\n\n\n[[ast:Ciencia]]\n[[ca:Ciència]]\n[[cs:Věda]]\n[[da:Videnskab]]\n[[de:Wissenschaft]]\n[[en:Science]]\n[[eo:Scienco]]\n[[es:Ciencia]]\n[[et:Teadus]]\n[[fi:Tiede]]\n[[fr:Science]]\n[[gd:Saidheans]]\n[[he:מדע]]\n[[hi:विज्ञान]]\n[[id:Sains]]\n[[is:Vísindi]]\n[[it:Scienza]]\n[[ja:科学]]\n[[ku:Zanist]]\n[[la:Scientia]]\n[[nah:Tlapohualmatiliztli]]\n[[nds:Wetenschap]]\n[[nl:Wetenschap]]\n[[no:Vitenskap]]\n[[pl:Nauka]]\n[[pt:Ciência]]\n[[ru:Наука]]\n[[simple:Science]]\n[[sl:Znanost]]\n[[sv:Vetenskap]]\n[[sw:Sayansi]]\n[[tl:Agham]]\n[[tr:Bilim]]\n[[uk:Наука]]\n[[zh:科学]]','/* Étimologi */',3,'Kandar','20050307102802','',0,0,0,0,0.149039867403,'20050307102802','79949692897197'); INSERT INTO cur VALUES (828,0,'Wilangan','[[Category:Group theory]][[Category:Number]]\nWilangan atawa angka nyaeta hiji entitas abstrak pikeun ngagambarkeun [[quantity]]. Aya sababaraha jenis wilangan. Nu pada mikawanoh nyaeta [[angka natural]]s {0, 1, 2, ...} digunakeun pikeun [[ngawilang]] jeung dilambangkeun ku \'\'\'N\'\'\'. Upama [[angka negatip|negative]] oge diasupkeun, mangka urang meunang [[wilangan buleud]] \'\'\'Z\'\'\'. Rasio wilangan buleud disebut [[rational angka]] atawa [[fractions]]; kumpulan sakabeh wilangan rasional dilambangkeun ku \'\'\'Q\'\'\'. Wilangan rasional bisa dituliskeun ku wilangan desimal nu ngabogaan digit nu kawates atawa periodik. Umpamana sakabeh wilangan desimal nu teu kawates jeun nu teu periodik diasupkeun, mangka dihasilkeun wilangan [[nyata(real) ]]s \'\'\'R\'\'\'. Wilangan nyata anu henteu rasional disebut wilangan [[wilangan irrasional ]]. Wilangan real bisa dilegakeun ka [[wilangan kompleks]] \'\'\'C\'\'\' pikeun mecahkeun sakabeh sasaruaan aljabar. Lambang di luhur biasana ditulis ku huruf [[kandel]], nyaeta:\n:\\mathbb{N}\\sub\\mathbb{Z}\\sub\\mathbb{Q}\\sub\\mathbb{R}\\sub\\mathbb{C}\n\nWilangan komplek kahareupna bisa leuwih dilegakeun [[quaternion]]s, but multiplication of quaternions is not [[commutative]]. [[Octonion]]s, in turn, extend the quaternions, but this time, [[associativity]] is lost. In fact, the only finite-dimensional associative [[division algebra]]s over \'\'\'R\'\'\' are the reals, the complex numbers, and the quaternions.\n\nNumbers should be distinguished from \'\'[[numeral]]s\'\', which are (combinations of) [[symbol]]s used to represent numbers. The notation of numbers as a series of digits is discussed in [[numeral system]]s. \n\nPeople like to assign numbers to objects in order to have unique names. There are various [[numbering scheme]]s for doing so.\n\nMany [[language]]s have the concept of [[grammatical number]], an attribute of certain words and phrases that affects their syntactic usage and meaning.\n\n== Extensions ==\n\nHasil nu paling anyar diana panalungtikan wilangan nyaeta [[hyperreal numbers]] jeung [[surreal numbers]], numangrupakeun perluasan tina wilangan nyata by adding infinitesimal and infinitely large numbers. While (most) real numbers have infinitely long expansions to the right of the decimal point, one can also try to allow for infinitely long expansions to the left, leading to the [[p-adic numbers]]. For dealing with infinite collections, the natural numbers have been generalized to the [[ordinal number|ordinal numbers]] and to the [[cardinal number|cardinal numbers]]. The former give the ordering of the collection, the latter its size. (For the finite case, the ordinal and cardinal numbers are equivalent; they diverge in the infinite case.) \n\nThe arithmetical operations of numbers, such as [[addition]], [[subtraction]], [[multiplication]] and [[division]], are generalized in the branch of [[mathematics]] called [[abstract algebra]]; one obtains the [[group (mathematics)|group]]s, [[ring (algebra)|ring]]s and [[field (mathematics)|field]]s.\n\n== Biological basis of culture-free similarities ==\n\nIn many cultures, the notation for the numbers \'\'one\'\', \'\'two\'\', and \'\'three\'\' is very similar. In Roman numerals, the corresponding numerals are I, II, and III, and in Chinese, the same notation is used but with the tally marks written horizontally. \n\nHowever, neither the Roman nor the Chinese systems use simple tally marks for \'\'four\'\'. The Roman numeral for \'\'four\'\' is IV, meaning one less than V, which stands for \'\'five\'\'. Evidently, five has significance because of the number of digits on each human hand. However, there is more here than mere human anatomy. Psychologists explain that the reason for the shift from a simple tally notation to one involving more symbols is the difficulty humans have in visually separating similar patterns with more than three identical elements. For example, it\'s hard to tell at a glance which is greater: IIIIIIII, or IIIIIII, but it is easy to tell X from XI.\n\nThe Arabic numeral system uses modified tally marks for 1, 2, and 3: \'\'1\'\' has undergone only very minor modification, and \'\'2\'\' and \'\'3\'\' are evidently based on horizontal lines written without lifting the pen. And again, the simple tally is abandoned with the numeral for \'\'4\'\'.\n\n== Particular numbers ==\n\nSee: [[List of numbers]], [[mathematical constant]]s, [[even and odd numbers]], [[negative and non-negative numbers]], [[small number]]s, [[large number]]s, [[orders of magnitude (numbers)]], [[prime number]]s; [[umpteen]]\n\n== Tempo ogé ==\n\n* [[Grammatical number]]\n* [[Numbers in various languages]]\n* [[Subitizing and counting]]\n\n== Tumbu kaluar ==\n\n* [http://wiktionary.org/wiki/Number Wiktionary article on \'\'number\'\']\n* [http://www.stetson.edu/~efriedma/numbers.html What\'s special about this number?]\n\n[[bg:Число]] [[ca:nombre]] [[da:Tal]] [[de:Zahl]] [[en:Number]] [[eo:Nombro]] [[es:Número]] [[et:Arv]] [[fr:nombre]] [[it:Numero]] [[ja:数]] [[nl:Getal]] [[no:Tall]] [[pl:Liczba]] [[ro:număr]] [[sl:število]] [[simple:Number]] [[sv:Tal]] [[tr:Sayı]]\n\n{{msg:quantity}}','/* External links */',3,'Kandar','20040928075218','',0,0,0,0,0.734230762224,'20040928075218','79959071924781'); INSERT INTO cur VALUES (829,0,'Arsitéktur','\'\'Artikel ieu ngeunaan arsitéktur nu patali jeung wangunan jeung\'\' landscape; \'\'pikeun harti séjén tempo [[arsitéktur komputer]], [[arsitéktur software]], jeung [[arsitéktur informasi]]\'\'\n\n------------------\n\n[[Image:ac.acropolis.jpg|thumbnail|250px|Parthenon na punclut Kota Akropolis, Aténa, Yunani]] \n\n\'\'\'Arsitéktur\'\'\' ngarupakeun [[seni]] jeung [[élmu]] [[rarancang|ngarancang]] [[wangunan]]. Harti nu leuwih lega bisa ngawengku rarancang wangun lingkungan sagemblengna, tina tingkat makro [[town planning]], [[urban design]], jeung [[landscape architecture]] nepi ka tingkat mikro [[furniture]] jeung [[product design]]. Architecture, equally importantly, also refers to the product of such a design. \n\nDumasar kana tulisan munggaran nu aya kénéh ngeunaan ieu, \'\'De Architectura\'\'-na [[Vitruvius]], wangunan nu hadé kudu mibanda Kaéndahan (Venustas), Weweg (Firmitas), tur Mangpaat (Utilitas); arsitéktur bisa disebutkeun salaku kasaimbangan jeung kasarasian tina tilu unsur ieu, bari teu silih éléhkeun. Harti modern nilik arsitéktur pikeun nyaluyukeun itung-itungan pungsi, kaéndahan (éstétik), jeung psikologis. Najan kitu, mun ditilik ti sisi séjén, pungsi sorangan geus dianggap ngawengku sakabéh patokan, kaasup kaéndahan jeung psikologis.\n\nArsitéktur ngarupakeun widang multidisiplin, kaasup [[matematik]], [[élmu]], [[seni]], [[téhnologi]], [[élmu sosial]], [[pulitik]], [[sajarah]], [[filosofi]], jsb. Ceuk Vitruvius mah, \"Arsitéktur téh mangrupa hiji élmu nu ngacambah tina rupa-rupa élmu turta dipapaés ku loba jeung rupa-rupa kaweruh: by the help of which a judgement is formed of those works which are the result of other arts\". He adds that an architect should be well versed in fields such as [[musik]], [[astronomi]], jsb. [[Filosofi]] is a particular favourite; in fact one frequently refers to the philosophy of each [[arsiték]] when one means the approach. [[Rasionalisme]], [[émpirisisme]], [[strukturalisme]], [[poststrukturalisme]], and [[fénoménologi]] are some directions from philosophy influencing architecture.\n\n[[Image:Colosseum-2003-07-09.jpg|thumb|left|250px|Colosseum, Roma, Itali]]\n\nThe importance of [[theory]] in informing [[practice]] cannot be overemphasised, though many architects shun theory. Vitruvius continues: \"Practice and theory are its parents. Practice is the frequent and continued contemplation of the mode of executing any given work, or of the mere operation of the hands, for the conversion of the material in the best and readiest way. Theory is the result of that reasoning which demonstrates and explains that the material wrought has been so converted as to answer the end proposed. Wherefore the mere practical architect is not able to assign sufficient reasons for the forms he adopts; and the theoretic architect also fails, grasping the shadow instead of the substance. He who is theoretic as well as practical, is therefore doubly armed; able not only to prove the propriety of his design, but equally so to carry it into execution\". \n\nThe difference between architecture and building is a subject matter that has engaged the attention of many. According to [[Nikolaus Pevsner]], [[Europe]]an historian of the early 20th century, \"A bicycle shed is a building, [[Lincoln Cathedral]] is a piece of architecture\". In current thinking, the division is not too clear. [[Bernard Rudofsky]]\'s famous \'\'[[Architecture Without Architects]]\'\' consolidated a whole range of structures designed by ordinary people into the realm of architecture. The further back in history one goes, the greater is the consensus on what architecture is or is not, possibly because time is an efficient filter. If like Vitruvius we consider architecture as good building, then does it mean that bad architecture does not exist? To resolve this dilemma, especially with the increasing number of buildings in the world today, architecture can also be defined as what an architect does. This would then place the emphasis on the evolution of architecture and the architect. \n\nArchitecture first evolved out of the dynamics between needs (conducive environmental conditions, security, etc.) and means (available [[building material]]s and [[construction technology]]). Prehistoric and primitive architecture constitute this early stage. As humans progressed and knowledge began to be formalised through oral traditions and practices, architecture evolved into a [[craft]]. Here there is first a process of trial and error, and later improvisation or replication of a successful trial. The architect is not the sole important figure; he is merely part of a continuing tradition. What is termed as [[Vernacular architecture]] today falls under this mode and still continues to be produced in many parts of the world. \n\n[[Image:Hampi1.JPG|thumb|Virupaksha Temple, Hampi, India]]\n\nEarly human settlements were essentially [[rural]]. As surplus of production began to occur, rural societies transformed into [[urban]] ones. The complexity of buildings and their types increased. General civil construction such as roads and bridges began to be built. Many new building types such as schools, hospitals, and recreational facilities emerged. Religious architecture retained its primacy in most societies. Architectural styles developed and texts on architecture began to be written. These became [[canons]] to be followed in important works, especially religious architecture. Some examples of canons are the works of Vitruvius and [[Vaastu Shastra]] in ancient [[India]]. In [[Europe]] in the [[Classical]] and [[Medieval]] periods, buildings were not attributed to specific individual architects who remained anonymous. [[Guild]]s were formed by craftsmen to organise their trade.\n\nWith the [[Renaissance]] and its emphasis on the individual and humanity rather than religion, and with all its attendant progress and achievements, a new chapter began. Buildings were ascribed to specific architects - [[Michaelangelo]], [[Brunelleschi]], [[Leonardo da Vinci]] - and the cult of the individual had begun. But there was no dividing line between [[artist]], [[architect]] and [[engineer]], or any of the related vocations. At this stage, it was still possible for an artist to design a bridge as the level of structural calculations involved were within the scope of the generalist.\n\nWith the consolidation of knowledge in scientific fields such as [[engineering]] and the rise of new materials and technology, the architect began to lose ground on the technical aspects of building. He therefore cornered for himself another playing field - that of [[aesthetics]]. There was the rise of the \"gentleman architect\" who usually dealt with wealthy clients and concentrated predominantly on visual qualities derived usually from historical prototypes. In the 19th century [[Ecole des Beaux Arts]] in [[France]], the training was toward producing quick sketch schemes involving beautiful drawings without much emphasis on context.\n\nMeanwhile, the [[Industrial Revolution]] laid open the door for mass consumption and aesthetics started becoming a criterion even for the middle class as ornamented products, once within the province of expensive craftmanship, became cheaper under machine production. Such products lacked the beauty and honesty associated with the expression of the process in the product. \n\n[[Image:taj_mahal.jpg|thumbnail|left|Taj Mahal, Agra, India]]\n\nThe dissatisfaction with such a general situation at the turn of the twentieth century gave rise to many new lines of thought that in architecture served as precursors to [[Modern Architecture]]. Notable among these is the [[Deutscher Werkbund]], formed in 1907 to produce better quality machine made objects. The rise of the profession of [[industrial design]] is usually placed here. Following this lead, the [[Bauhaus]] school, founded in [[Germany]] in 1919, consciously rejected [[history]] and looked at architecture as a synthesis of art, craft, and technology. \n\nWhen Modern architecture first began to be practiced, it was an [[avant garde]] movement with moral, philosophical, and aesthetic underpinnings. Truth was sought by rejecting history and turning to function as the generator of form. Architects became prominent figures and were termed masters. Later modern architecture moved into the realm of mass production due to its simplicity and economy.\n\nHowever, a reductive quality began to be perceived in modern architecture by the general public from the [[1960s]]. Some reasons cited for this are its perceived lack of meaning, sterility, ugliness, uniformity, and psychological effects.\n\n[[Image:Chryslerbldg.jpg|thumbnail|100px|Chrysler building, New York City, USA]]\n\nThe architectural profession responded to this partly by attempting a more populist architecture at the visual level, even if at the expense of sacrificing depth for shallowness, a direction called [[Postmodernism]]. [[Robert Venturi]]\'s contention that a \"decorated shed\" (an ordinary building which is functionally designed inside and embellished on the outside) was better than a \"duck\" (a building in which the whole form and its function are considered together) gives an idea of this approach.\n\nAnother part of the profession, and also some non-architects, responded by going to what they considered the root of the problem. They felt that architecture was not a personal philosophical or aesthetic pursuit by individualists; rather it had to consider everyday needs of people and use technology to give a livable environment. The [[Design Methodology Movement]] involving people such as [[Chris Jones(design)|Chris Jones]], [[Christopher Alexander]] started searching for a more inclusive process of design in order to lead to a better product. Extensive studies on areas such as behavioural, environmental, and social sciences were done and started informing the design process. \n\nAs many other concerns began to be recognised and complexity of buildings began to increase in terms of aspects such as services, architecture started becoming more multi-disciplinary than ever. Architecture now required a team of professionals in its making, an architect being one among the many, sometimes the leader, sometimes not. This is the state of the profession today. However, individuality is still cherished and sought for in the design of buildings seen as cultural symbols - the museum or fine arts centre has become a showcase for new experiments in style: today [[Deconstructivism]], tomorrow maybe something else. \n\nBuildings are the most visible productions of man ever. However, most of them are still designed by people themselves or masons as in developing countries, or through standardised production as in developed countries. The architect remains at the fringes of building production. The skills of the architect are sought only in complex building types or those seen as cultural and political symbols. And this is what the public perceives as architecture. The role of the architect, though changing, has not been central and never autonomous. There is always a dialogue between society and the architect. And what results from this dialogue can be termed architecture - as a product and as a discipline.\n\n== Arsitéktur Wangunan Sunda ==\nTipologi (rupa wangunan), utamana ditoong di rupa suhunanana. Ieu kabéh dina modél aslina, panggung.\n\n*\'\'\'Suhunan jolopong\'\'\': suhunan nu lempeng. Mun basa indonesia mah, atap pelana. Siga pelana kuda. Kaci ogé disebut regol.\n\n*\'\'\'Jogo anjing\'\'\': upami hoyong terang rupana siga kumaha, pilari heula anjing, terus sina jogo. mun teu daékeun, olo. Tah, mun geus jogo, siga modél imah nu ieu, atawa tibalik, modél imah kieu, siga anjing keur jogo diténjo ti gigir. Suhunan hareup (nu siga bangus anjing) ngiuhan émpér imah.\n\n*\'\'\'Badak heuay\'\'\': nu hoyong apal kumaha wanda imah nu siga badak heuay, walah hésé ieu mah, kudu nganjang ka Ujung Kulon heula. Ari dedegna mah rada deukeut ka jogo anjing, ngan luhureun sirahnya aya ceulian-susuhunan tambahan, kahareup.\n\n*\'\'\'Parahu kumureb\'\'\': nya siga tangkuban parahu pisan, trapesium tibalik di Tomo Sumedang, disebutna jubleg nangkub.\n\n*\'\'\'Julang ngapak\'\'\': julang teh ngaran manuk. dipaké ku Maclain Point jang nyieun aula kulon-aula wétan ITB. Nya manéhna nu nyebut ieu model téh ciri suhunan Sunda Besar. Julang ngapak mun diténjo ti hareup, suhunan kénca katuhuna siga jangjang manuk julang-suhunanana opat nyambung nu di sisi nyorondoy. Sambunganana di tengah, maké tambahan siga gunting muka di punclutna.\n\n*\'\'\'Buka palayu\'\'\': suhunan sigan imah Betawi aya émpér panjang dihareup.\n\n*\'\'\'Buka pongpok\'\'\': rada mirip buka palayu, ngan pantona dirobah ka arah jalan.\n\n== Tempo ogé ==\n* [[Arsiték]]\n* [[Landscape Architecture]]\n* [[Destination/Coastal Architects]]\n* [[Sajarah arsitektural]]\n* [[Gaya arsitéktural]] \n* [[Architecture timeline]]\n* [[Daptar wangunan]]\n* [[Forms in Architecture]] \n* [[Daptar arsiték penting]]\n* [[Skyscraper]]\n* [[Arsitéktur katedral]]\n* [[Rékayasa struktur]] (\'\'structural Engineering\'\')\n* [[Akustik]]\n* [[Building code]]\n* [[Space Syntax]]\n* [[Sustainable Design]]\n* [[Environmental Design]]\n* [[Building Materials]]\n* [[Pattern language]]\n* [[Matematik jeung arsitéktur]]\n* [[Vastu]]\n* [[World Heritage Sites]]\n\n== Tumbu kaluar ==\n*[http://www.0lll.com/lud/pages/architecture/archgallery/ 0lll.com] - Fotograf Arsitéktur Kontémporér\n*[http://www.ukans.edu/history/index/europe/ancient_rome/E/Roman/Texts/Vitruvius/home.html \"Sapuluh Buku Arsitéktur\" Vitruvius \'\'online\'\']\n*[http://www.idad.org Institute of Destination Architects and Designers]\n*[http://www.skyscrapers.com Skyscrapers.com database on skyscrapers and tall structures]\n*[http://www.architecture.com/go/Architecture/Home.html Royal Institute of British Architects]\n*[http://www2.aia.org/myaia/communities/community.asp?UserID=2&CommunityID=200 American Institute of Architects]\n*[http://www.riai.ie Royal Institute of Architects of Ireland]\n*[http://www.aia.org American Institute of Architects]\n*[http://www.gta.arch.ethz.ch/moravanszky Institute for Architectural Theory, Swiss Federal Institute of Technology, Zurich]\n*[http://www.cnu.org/about/index.cfm What is New Urbanism? - Congress for the New Urbanism]\n*[http://www.asla.org/nonmembers/publicrelations/What_is_ASLA.cfm What is Landscape Architecture? - American Society of Landscape Architects]\n*[http://www.arch.kth.se/a-url Architecture and Urban Research Laboratory]\n*[http://cca.qc.ca Canadian Centre for Architecture] - International Research Centre and Museum devoted to Architecture\n*http://www.architexturez.net\n*http://www.pritzkerprize.com/ \n*http://theArchitectureRoom.com\n*http://www.vitruvio.ch/\n*[http://www.cupola.com/ Cupola]\n*[http://www.archnewsnow.com/ Archnewsnow.com]\n*[http://www.archiseek.com Archiseek.com]\nRelated [[adjective]]s are \'\'\'architectural\'\'\' and \'\'\'architectonic\'\'\'\n\n\n----\n\nKecap arsitéktur ogé dipaké pikeun [[rarancang]] atawa \'\'[[act]]\'\' ngarancang sistem kompléks séjénna. Pikeun conto, [[arsitéktur komputer]], [[arsitéktur software]], jeung [[arsitéktur informasi]]. Dina kasus ieu, nujulna ka sakujur [[struktur]] [[sistim]]na.\n\n[[Category:Tepas]]\n\n[[af:Argitektuur]]\n[[ast:Arquiteutura]]\n[[bg:Архитектура]]\n[[bs:Arhitektura]]\n[[ca:Arquitectura]]\n[[cy:Pensaernïaeth]]\n[[da:Arkitektur]]\n[[de:Architektur]]\n[[el:Αρχιτεκτονική]]\n[[en:Architecture]]\n[[eo:Arkitekturo]]\n[[es:Arquitectura]]\n[[fi:Arkkitehtuuri]]\n[[fr:Architecture]]\n[[fy:Boukeunst]]\n[[he:אדריכלות]]\n[[hi:वास्तुशास्त्र]]\n[[hr:Arhitektura]]\n[[ia:Architectura]]\n[[it:Architettura]]\n[[ja:建築学]]\n[[la:Architectura]]\n[[lt:Architektūra]]\n[[lv:Arhitektūra]]\n[[nah:Arquitectura]]\n[[nl:Architectuur]]\n[[no:Arkitektur]]\n[[pl:Architektura]]\n[[pt:Arquitectura]]\n[[ro:Arhitectură]]\n[[ru:Архитектура]]\n[[simple:Architecture]]\n[[sl:Arhitektura]]\n[[sr:Архитектура]]\n[[sv:Arkitektur]]\n[[sw:Majenzi]]\n[[ta:கட்டிடக்கலை]]\n[[zh:建筑学]]','',3,'Kandar','20041125033824','',0,0,0,0,0.09413688448,'20041125033824','79958874966175'); INSERT INTO cur VALUES (830,1,'Kimia','Istilah \'\'\'kimia analisis\'\'\' dipulangkeun deui jadi \'\'\'kimia analitis\'\'\' sabab kecap \'\'\'analisis\'\'\' ngarupakeun kecap gawé, teu loyog mun dilarapkeun kana istilah di luhur. Nu loyog nya make kecap sipat \'\'\'analitis\'\'\'. [[User:Kandar|Kandar]] 03:29, 15 Jul 2004 (UTC)','',3,'Kandar','20040715032930','',0,0,0,1,0.912887771108,'20040728053711','79959284967069'); INSERT INTO cur VALUES (831,0,'Réaksi_kimia','\'\'\'Réaksi kimia\'\'\' ogé dipiwanoh salaku [[parobahan]] [[zat kimia|kimiawi]], nu maksudna nyaéta parobahan dina [[struktur]] [[molekul]]. Réaksi ieu bisa mangrupa napelna hiji molekul kanu séjén ngahasilkeun molekul nu leuwih gedé, molekul beulah jadi dua atawa leuwih molekul nu leuwih leutik, atawa [[wangun ulang]] [[atom]]-atom jeroeun molekul. Réaksi kimia salawasna ngajeujeutkeun dibentuk atawa dipegatkeunana [[beungkeut kimia]].\n\n==Rupa-rupa==\nAya sababaraha rupa réaksi kimia dasar:\n*\'\'Sintésis\'\' nu diwangun ku dua atawa leuwih atom, ion, atawa molekul mandiri nu ngahiji jadi hiji zat anyar.
\n
A + B → AB
\n*\'\'Dékomposisi\'\' nu sabalikna ti sintésis, nalika hiji sanyawa beulah jadi dua atawa leuwih atom, ion, atawa molekul mandiri.
\n
AB → A + B
\n*Dina réaksi nukeuran tunggal, salasahiji atom diganti ku atom séjén.
\n
A + BC → B + AC
\n*Dina réaksi nukeuran ganda (ogé katelah [[métatésis]]), atom-atom nu kabeungkeut na sakabéh réaktan silih tukeurkeun.
\n
AB + CD → AD + CB
\n*Dina réaksi oksidasi-réduksi (ogé katelah [[réaksi rédoks]]), hiji réaktan ngaleupaskeun éléktron (molekulna dioksidasi), sedengkeun réaktan nu séjénna narima éléktron (molekulna diréduksi). Réaktan nu dioksidasi ngarupakeun [[agén pangréduksi]], sedengkeun réaktan nu diréduksi salaku [[agén pangoksidasi]].
\n
A + B → A+ + B-
\n\nRéaksi kimia teu ngarobah [[inti atom]], nu robah ukur interaksi awan [[éléktron]] na atom-atom nu kajeujeut (parobahan wangunan inti atom disebutna [[réaksi inti]], jeung teu dianggap salaku réaksi kimia, sanajan réaksi kimia bisa nuturkeun transformasi inti).\n\nRéaksi kimia ampir salawasna ngalibetkeun parobahan [[énergi]], nu pangmerenahna/panggampangna diukur dina parobahan [[panas]]. Béda énergi antara kaayaan \"méméh\" jeung \"sanggeus\" réaksi kimia bisa diitung sacara téoritis maké tabel data (atawa komputer). Pikeun conto, misalkeun réaksi CH4 + 2 O2 → CO2 + 2 H2O (ngadurukan [[métan]] dina [[oksigén]]). Ku jalan ngitung jumlah énergi nu diperlukeun pikeun megatkeun sakabéh beungkeut nu beulah kénca (\"méméh\") jeung katuhu (\"sanggeus\") \'\'persamaan\'\', urang bisa ngitung béda énergi antara réaktan jeung produkna. Ieu disebutna ΔH, di mana Δ (Délta) ngandung harti béda, sedengkeun H salaku [[éntalpi]], ukuran énergi nu sarua jeung panas nu dipindahkeun dina kaayaan \'\'tekanan\'\' angger (konstan). ΔH biasana ditunjukkeun dina unit kJ (rebuan [[joule]]) atawa dina kkal ([[Kalori|kilokalori]]). Mun réaksi ΔH-na négatip, mangka énergi dileupaskeun. Réaksi rupa kieu disebutna [[éksotérmik]] (hartina panas luar atawa miceun panas). Réaksi éksotérmik leuwih dipikaresep sahingga leuwih gampang lumangsung. Conto réaksi nu tadi éksotérmik, nu geus biasa urang manggihan sapopoé, sabab ngaduruk gas dina hawa ngaluarkeun panas.\n\nRéaksi bisa boga ΔH positip, hartina, sangkan bisa lumangsung, réaksi butuh asupan énergi ti luar. Réaksi kieu disebut [[éndotérmik]] (hartina panas jero atawa nyerep panas).\n\n==[[Laju réaksi]]==\nLaju réaksi kimia gumantung ka:\n*[[Konséntrasi]] [[réaktan]]\n*[[Énergi aktivasi]]\n*[[Temperatur]]\n*Aya henteuna [[katalis]].\n\n==Kabisamalikan==\nUnggal réaksi kimia sacara tioritis bisa malik (Ing. \'\'reversible\'\').\nDina hiji \'\'réaksi maju\'\' [[réaktan]] dirobah jadi [[produk]], kitu ogé sabalikna. [[Kasatimbangan kimia]] ngarupakeun kaayaan nalika laju réaksi maju jeung sabalikna sarua, sahingga nahan jumlah réaktan jeung produkna.\n\nSanajan sakabéh réaksi bisa malik, sababaraha réaksi bisa kagolongkeun teu bisa malik (Ing. \'\'irreversible\'\'). \'\'Réaksi teu bisa malik\'\' bisa lumaku mun dina kasatimbangan ampir sakabéh molekul réaktan geus robah jadi produk.\n\n==[[Hukum polah massa]]==\nKonséntrasi réaktan jeung produk nangtukeun laju boh réaksi maju jeung malik.\n\n==[[Katalis]]==\nKatalis teu ruksak dina réaksi kimia, tapi nulung pikeun nurunkeun énergi nu dipikabutuh pikeun aktivasi sahingga ningkatkeun laju réaksi.\n\n==Tempo ogé==\n[[Sintésis kimia]], \'\'[[Persamaan kimia]]\'\'\n\n[[ca:Reacció química]] [[de:Chemische Reaktion]] [[en:Chemical reaction]] [[es:Reacción química]] [[fr:Réaction chimique]] [[ja:化学反応]] [[nds:Chemisch Reaktschonen]] [[nl:Chemische reactie]] [[pl:Reakcja chemiczna]]','',3,'Kandar','20041125070741','',0,0,0,0,0.839429302998,'20041125070741','79958874929258'); INSERT INTO cur VALUES (833,4,'Deletion_log','','dihapus \"Algorithms\": Parantos dialihkeun ka [[algoritma]]',3,'Kandar','20040825103209','sysop',0,0,0,0,0.118003024829554,'20040825103209','79959174896790'); INSERT INTO cur VALUES (834,0,'Sanyawa_kimia','Dina widang [[kimia]], \'\'\'sanyawa\'\'\' ngarupakeun zat nu ngawujud tina dua atawa leuwih [[unsur kimia|unsur]] dina \'\'nisbah tetep\'\' nu nangtukeun wangunanna. Pikeun conto, [[cai]] ngarupakeun sanyawa nu disusun ku [[hidrogén]] jeung [[oksigén]] dina nisbah dua ka hiji.\n\nSacara umum, nisbah tetep ieu kudu ditangtukeun dumasar sababaraha ciri sipat fisik, leuwih ti ukur beunang sagawayah jijieunan jelema. Ieu nu jadi sabab pangna [[kuningan]], [[superkonduktor]], [[YBCO]], [[semikonduktor]] [[Aluminium gallium arsénida]], atawa [[coklat]] dianggap [[campuran]] atawa \'\'[[alloy]]\'\', lain sanyawa.\n\nCiri nu nangtukeun hiji sanyawa nyéta ayana [[rumus kimia]]. Rumus ngagambarkeun nisbah jumlah atom na hiji zat. Pikeun conto, dina [[hidrogén|H]]2[[oksigén|O]] (cai) aya dua atom hidrogén pikeun tiap hiji atom oksigén. Rumus ieu \'\'teu\'\' nétélakeun yén cai dijieun ku [[molekul]].\n\nSanyawa bisa mibanda sababaraha [[fase zat|fase]]. Pikeun sanyawa, sangkan [[cair]] atawa [[gas]]na tetep disebut sanyawa, atom-atomna nu ti rupa-rupa unsur kudu kabeungkeut dina wujud [[molekul]]. Wangunan molekul nu jadi sabab pangna aya sanyawa modél [[étana|C2H4]] (batan ukur CH2) - rumus nétélakeun teu wungkul nisbah, tapi ogé sabaraha atom nu aya na unggal molekul.\n\nSakabéh sanyawa bakal beulah jadi sanyawa nu leuwih leutik atawa [[atom]] mandiri mun dipanaskeun nepi ka [[temperatur]] nu cukup. Temperatur ieu disebutna [[temperatur dékomposisi]].\n\nUnggal sanyawa kimia nu geus dijéntrékeun na literatur dibéré pananda wilangan unik, [[wilangan CAS]]. Tempo ogé [[ngaran sistematik]].\n\n==Rupa-rupa sanyawa==\n* [[asam]], \n* [[basa (kimia)|basa]], \n* [[uyah]], \n* [[oksida]], \n* [[sanyawa organik]]\n\n==Tempo ogé==\n[[Daptar sanyawa]] na Wikipédia.\n\n[[ca:Compost Químic]] [[de:Chemische Verbindung]] [[en:Chemical compound]] [[eo:Kemiaj kombinajxoj]] [[et:Keemiline aine]] [[es:Compuesto químico]] [[fr:Composé chimique]] [[he:תרכובת]] [[ja:化合物]]\n[[nds:Chemisch Verbinnung]] [[pl:Związek chemiczny]] [[pt:Composto químico]] [[sl:spojina]]\n\n[[Category:Zat kimia]]','',3,'Kandar','20041125070910','',0,0,0,0,0.975997590449,'20041125070910','79958874929089'); INSERT INTO cur VALUES (835,0,'Kimia_organik','\'\'\'Kimia organik\'\'\' ngarupakeun ulikan [[élmu|ilmiah]] ngeunaan struktur, sipat, wangunan, jeung [[réaksi kimia|réaksi]] [[sanyawa organik]]. \n\n==Tata ngaran organik==\n[[tata ngaran organik]] ngarupakeun sistem nu dimaneuhkeun pikeun ngaranan jeung ngagolongkeun [[sanyawa organik]]. \n\n==Sanyawa alifatik==\n[[Hidrokarbon]] - [[Alkana]] - [[Alkéna]] - [[diéna|Diéna atawa Alkadiéna]] - [[Alkuna]] - [[Halogénoalkana]] - [[Alkohol]] - [[Mérkaptan]] - [[Éter]] - [[Aldehid]] - [[Keton]] - [[Asam karboksilat]] - [[Éster]] - [[Karbohidrat]] - [[Sanyawa alisiklik]] - [[Amida]] - [[Amina]] - [[Lipid]] - [[Nitril]]\n\n==Sanyawa aromatik==\n[[Bénzén]] - [[Toluén]] - [[Xilén]] - [[Anilin]] - [[Fénol]] - [[Asétofénon]] - [[Bénzonitril]] - [[Halogénoaren]] - [[Naftalén]] - [[Antrasén]] - [[Fénantrén]] - [[Bénzopirén]] - [[Koronén]] - [[Azulén]] - [[Bifénil]]\n\n==Sanyawa hétérosiklik==\n[[Piridin]] - [[Pirol]] - [[Tiofén]] - [[Furan]] - [[Imidazol]]\n\n==Polimér==\nPolimér ngarupakeun hiji wujud molekul nu husus. Umum dianggap molekul \"gedé\", polimér meunang gelar éta dumasar kana ukuranana sabab disusun ku loba bagéan nu leuwih leutik. Bagéan nu leutikna bisa kembar kimiawi nu ngawujud jadi molekul homopolimér, atawa bisa ogé tina béda-béda struktur kimiawi nu ngawujud jadi molekul hétéropolimér. Polimér ngarupakeun sawaréh ti \"makromolekul\" nu ukur digolongkeun dumasar ukuranana nu dianggap gedé.\n\nPolimér bisa organik atawa anorganik, umum kapanggih mah organik (misal poliétilén, polipropilén, Pléxiglas, jsb), tapi nu anorganik ge mindeng kapanggih na kahirupan sapopoé (misal \'\'silly putty\'\', silikon, jsb).\n\n==Konsép==\n[[Tata ngaran organik]] - [[Rumus kimia]] - [[Rumus struktur]] - [[Rumus rangka]] - [[Réaksi organik]]\n\n==Ciri-ciri zat organik==\nNu jadi alesan pangna aya loba pisan sanyawa karbon nyéta sabab karbon mibanda kamampuhan pikeun ngawangun ranté karbon nu panjangna rupa-rupa, sarta cingcin nu ukuranana béda ([[katénasi]]). Lolobana sanyawaan karbon peka pisan ku [[panas]] jeung umumna \'\'terurai\'\' méméh 300\'C. Cenderung kurang [[leyur]] na [[cai]] dibanding kalolobaan uyah anorganik. Béda ti uyah, sanyawa organik leuwih leyur na [[pangleyur]] organik saperti [[éter]] atawa [[alkohol]]. Sanyawa organik [[beungkeut kovalén|kabeungkeut sacara kovalén]].\n\n==Sajarah==\nKimia organik salakuélmu umumna kaaku dimimitian ku [[sintésis]] organik [[uréa]] ku [[Friedrich Woehler]] tina bahan anorganik taun 1828.\n\n==Tempo ogé==\n*[http://wikibooks.org/wiki/Organic_chemistry Buku téks kimia organik]\n\n\n{{CabangKimia}}\n\n[[ca:Qu%EDmica Org%E0nica]] [[de:Organische Chemie]] [[en:Organic chemistry]] [[eo:Organika Kemio]] [[es:Química orgánica]] [[fr:Chimie organique]] [[it:Chimica organica]] [[ja:%E6%9C%89%E6%A9%9F%E5%8C%96%E5%AD%A6]] [[nl:organische scheikunde]] [[pl:Chemia organiczna]] [[sl:organska kemija]] [[zh-tw:有機化學]]\n\n[[Category:Kimia]]','',3,'Kandar','20041211024134','',0,0,0,0,0.908019885378,'20050303210134','79958788975865'); INSERT INTO cur VALUES (836,0,'Kimia_anorganik','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n\'\'\'Kimia anorganik\'\'\' ngarupakeun cabang [[kimia]] ngeunaan sipat jeung réaksi sanyawaan anorganik. Ieu ngawengku sadaya sanyawaan kimiawi iwal nu mibanda ranté atawa cingcin atom [[karbon]], nu diistilahan sanyawaan organik nu diulik dina jejer [[kimia organik]] nu misah. Bébédaan antara dua disiplin ieu teu mutlak, malah loba patumpangtindihna, utamana dina subdisiplin [[kimia organologam]].\n\nCabang-cabang utama kimia anorganik di antarana,\n* [[Mineral]], kayaning [[uyah]], [[asbéstos]], [[silikat]], ...\n* [[Logam]] jeung \'\'alloy\'\'na, kayaning [[beusi]], [[tambaga]], [[aluminium]], [[kuningan]], \'\'[[perunggu]]\'\', ...\n* Sanyawaan nu ngajeujeutkeun unsur nonlogam kayaning [[silikon]], [[fosfor]], [[klorin]], [[oksigén]], misalna [[cai]]\n* [[Kompléks]] logam\n\nZat anorganik nu penting sacara komersil di antarana [[Semikonduktor|chip silikon]], [[transistor]], layar [[LCD]], [[serat optik|kabel serat optik]], sarta rupa-rupa [[katalisis|katalis]].\n\nKimia anorganik dumasar kana [[kimia fisik]] sarta ngawujud jadi dadasar pikeun [[mineralogi]] jeung [[kimia bahan]]. Kimia anorganik kadang tumpang tindih jeung [[géokimia]], [[kimia analitis]], [[kimia lingkungan]], jeung [[kimia organologam]]. \n\n[[Kimia organologam]] ngagabungkeun aspék-aspék [[kimia organik]] jeung kimia anorganik, nu sacara formal didefinisikeun salaku ulikan sanyawaan nu ngandung beungkeut logam-karbon, najan loba \"[[sanyawa organologam]]\" teu mibanda éta beungkeut. Di antara sanyawa organologam nu pangbasajanna nyéta karbonil logam, nalika [[karbon monoksida]] kabeungkeut kana logam ngaliwatan karbonna. [[Vitamin B12]], nu sisi aktifna sarua jeung na [[hémoglobin]], ngarupakeun [[sanyawa organologam]] alami nu sacara métabolis penting nu ngandung bagéan organik nu gedé ([[korin]] jeung [[protéin]]) sarta logam [[kobalt]] nu kabeungkeut na karbon.\n\nAmbahan kimia anorganik ngawengku boh sanyawaan molekular, nu aya salaku [[molekul]] diskrét, jeung [[kristal]], nu strukturna digambarkeun salaku kisi tanpa wates of regularly-ordered atoms sarta nu diulik dina [[kristalografi]] jeung [[kimia bahan padet]].\n\n\n{{CabangKimia}}\n\n[[ca:Química Inorgànica]] [[da:Uorganisk kemi]] [[en:Inorganic chemistry]][[es:Química inorgánica]] [[fr:Chimie Inorganique]] [[it:Chimica inorganica]] [[nl:Anorganische chemie]] [[ja:無機化学]] [[nds:Anorganisch Chemie]] [[pl:Chemia nieorganiczna]] [[sv:oorganisk kemi]]\n\n[[Category:Kimia]]','',3,'Kandar','20041125074110','',0,0,0,0,0.569154372238,'20041125074110','79958874925889'); INSERT INTO cur VALUES (837,1,'Rékayasa','Rada mangmang saleresna mah, naha kecap \'\'engineering\'\' teh pasna ditarjamahkeun janten naon? Dina basa Indonesia, aya dua harti: rekayasa jeung teknik. Tah ari \'\'engineering\'\' ieu nu mana nya? Asana mah langkung caket kana \'\'teknik\'\', basa Sundana \'\'tehnik\'\' meureun nya? Pami pada nyatujuan mah, artikel ieu badé dialihkeun ka artikel \'\'tehnik\'\'. [[User:Kandar|Kandar]] 03:43, 19 Jul 2004 (UTC)','',3,'Kandar','20040719034300','',0,0,0,1,0.551687773574,'20040728053711','79959280965699'); INSERT INTO cur VALUES (838,0,'Kimia_fisik','[[pl:Chemia fizyczna]] [[ca:Química Física]] [[de:Physikalische Chemie]] [[en:Physical chemistry]] [[fr:Chimie physique]] [[nl:Fysische chemie]] [[eo:Fizika Kemio]]\n\n\'\'\'Kimia fisik\'\'\' ngarupakeun ulikan ngeunaan dasar fisik sistem jeung prosés [[kimia|kimiawi]]. Kimia fisik modern kalawan teges ngadeg dia dadasar [[fisika]]. Widang ulikan nu penting di antarana [[térmodinamik kimiawi]], [[kinetik]] kimiawi, [[kimia kuantum]], [[mékanik ststistis]], [[éléktrokimia]], \'\'[[kimia permukaan|surface]]\'\' jeung [[kimia bahan padet]], sarta [[spéktroskopi]].\n\nKimia fisik ogé mangrupa pondamén pikeun [[élmu bahan]].\n\n==Kimiawan fisik nu penting==\n\n* [[Svante Arrhenius]]\n* [[Peter Debye]]\n* [[Erich Hückel]]\n* [[J.W. Gibbs]]\n* [[J.H. van \'t Hoff]]\n* [[Lars Onsager]]\n* [[Wilhelm Ostwald]]\n* [[Linus Pauling]]\n\n==Pustaka==\n\n* Physical Chemistry, P.W. Atkins, 1978, Oxford University Press ISBN 0-7167-3539-3\n* Introduction to Modern Colloid Science, R.J. Hunter, 1993, Oxford University Press ISBN 0198553862\n* Principles of Colloid and Surface Chemistry, P.C. Hiemenz, R. Rajagopalan, 1997, Marcel Dekker Inc., New York ISBN 0824793978\n\n{{CabangKimia}}\n\n[[Category:Kimia]]','fix eo',8,'Suisui','20040909032839','',0,0,1,0,0.789795659385,'20040909032839','79959090967160'); INSERT INTO cur VALUES (839,0,'Biokimia','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n\'\'\'Biokimia\'\'\' ngarupakeun [[kimia]] [[hirup|kahirupan]]. Biokimiawan ngulik [[unsur kimia|unsur]]-unsur, [[sanyawa kimia|sanyawa]]an, jeung [[réaksi kimia]] nu dikontrol ku [[énzim]]-énzim na jero awak sakabéh [[organisme]]. \n\nBiokimia museur kana struktur jeung pungsi [[sél (biologi)|komponén sélular]] kayaning [[protéin]], [[lipid]], [[karbohidrat]], [[asam nukléat]], jeung [[biomolekul]] séjénna. Kaayeunakeun biokimia leuwih museur kana kimia réaksi nu dimédiasi [[énzim]] jeung sipat-sipat protéin.\n\nBiokimia [[métabolisme sél]] geus digambarkeun sacara éksténsif. Widang biokimia séjénna di antarana [[sandi genetik]] ([[DNA]], [[RNA]]), [[sintésis protéin]], transpor [[mémbran sél]], [[transduksi sinyal]], jeung [[siklus dékomposisi énergi]].\n\n== Perkembangan biokimia ==\nMucunghulna biokimia meureun dimimitian ku ayana papanggihan [[énzim]] munggaran, [[diastase]], taun [[1833]] ku [[Anselme Payen]]. taun [[1828]], [[Friedrich Wöhler]] medalkeun tulisan ngeunaan sistésis [[uréa]], nu ngabuktikeun yén sanyawa [[kimia organik|organik]] bisa dijieun sacara artifisial, kontras jeung pamadegan harita yén sanyawa organik ngan bisa dijieun ku organisme. Saprak harita, biokimia maju ninggalkeun nu séjén, utamana mimiti panengah [[abad ka-20]], ku kapanggihna téhnik anyar kayaning [[kromatografi]], [[difraksi sinar-X]], [[NMR]], [[panyiri radioisotop]], [[mikroskop éléktron]], jeung simulasi [[dinamik molekular]]. Téhnik ieu jadi ngagampangkeun papanggihan jeung analisis nu detil rupa-rupa molekul jeung [[jalur métabolik]] [[sél (biologi)|sél]], kayaning [[glikolisis]] jeung [[siklus asam sitrat|siklus Krébs]].\n\nAyeuna, papanggihan-papanggihan na widang kimia dipaké dina loba widang, ti [[genetik]] nepi ka [[biologi molekular]] jeung ti [[agrikultur|tatanén]] nepi ka [[tatamba]]. Biokimia bisa jadi munggaran diterapkeun dina nyieun [[roti]] migunakeun [[kapang]], kira-kira 5000 taun katukang.\n\n== Kategori ==\nBiokimia sacara prinsip patali jeung kimia zat-zat nu bisa digolongkeun kana sababaraha kategori utama:\n\n*[[Karbohidrat]]\n*[[Lipid]]\n*[[Protéin]] jeung [[Asam amino]]\n*[[Asam nukléat]]\n\n==Tempo ogé==\n{{Bukuwiki}}\n*[[Ékologi kimia]]\n*[[Jejer konci biokimia]]\n*[[Daptar jejer biokimia]]\n*[[Daptar biomolekul]]\n*[[Daptar biokimiawan]]\n\n{{Biologi}}\n\n{{CabangKimia}}\n\n\n\n[[af:Biochemie]] [[bg:Биохимия]] [[ms:Biokimia]] [[ca:Bioquímica]] [[da:Biokemi]] [[de:Biochemie]] [[en:Biochemistry]] [[es:Bioquímica]] [[eo:Biokemio]] [[fr:Biochimie]]\n[[fy:Biogemy]] [[ko:생화학]] [[lv:Biokimija]] [[hu:Biokémia]]\n[[nl:Biochemie]] [[ja:生化学]] [[pl:Biochemia]] [[sv:Biokemi]] [[fi:Biokemia]] [[zh:生物化学]]\n\n\n[[Category:Biokimia]]','/* Tempo ogé */',3,'Kandar','20041125094111','',0,0,0,0,0.394092029144,'20050302051215','79958874905888'); INSERT INTO cur VALUES (840,0,'Kimia_analitis','\'\'\'Kimia analitis\'\'\' ngulik analisis sampel/conto bahan pikeun mikanyaho wangunan jeung struktur kimiawina.\n\n==Tipe==\nKimia analitis bisa dibagi jadi dua tipe utama:\n#[[Analisis kualitatif]] pikeun nangtukeun [[éksisténsi|aya/henteuna]] [[unsur kimia|unsur]] atawa [[sanyawa kimia]] nu ditéang.\n#[[Analisis kuantitatif]] pikeun nangtukeun [[kadar]] unsur atawa sanyawa kimia nu ditéang.\n\nKimia analitis lolobana kuantitatif, nu bisa dibagi deui kana widang ulikan nu béda. Bahanna bisa dianalisis pikeun nangtukeun kadar unsur atawa kadar unsur dina spésiés kimia tinangtu. Nu panungtung ngarupakeun interés husus na sistem biologis; molekul-molekul mahluk hirup ngandung karbon, hidrogén, oksigén, nitrogén, jeung sajabana dina struktur-struktur nu kompléks/pajeulit.\n\n==Téhnik==\nAya rupa-rupa téhnik nu bisa dipaké pikeun misahkeun, ngadeteksi, jeung ngukur sanyawaan kimiawi. \n\n*[[Pamisahan zat kimia]] pikeun ngukur beurat atawa volum produk ahir. Ieu ngarupakeun prosés nu geus heubeul nu kudu pisan taliti. \n*Analisis zat migunakeun alat [[spéktroskopi]]. Ngukur serapan sinar ku hiji larutan atawa gas, nu saterusna bisa diitung eusi sababaraha spésiés, nu kadang teu merlukeun pamisahan. Métode nu leuwih anyar kayaning [[spéktroskopi serapan atom]] (\'\'atomic absorbance spectroscopy\'\', AAS), [[résonansi magnetik inti]] (\'\'nuclear magnetic resonance\'\', NMR), jeung [[analisis aktivasi neutron]] (\'\'neutron activation analysis\'\', NAA).\n*Loba téhnik nu ngagabungkeun dua atawa leuwih métode analitis. Contona kayaning [[ICP-MS]] (\'\'Inductively-Coupled Plasma - Mass Spectrometry\'\'), dimana dina tahap kahiji sampel di[[volatilisasi]], sedengkeun pangukuran kadarna ditangtukeun dina tahap kadua. Tahap kahiji bisa ogé ngalibetkeun téhnik pamisahan kayaning [[kromatografi]], sedengkeun nu kadua parabot pikeun ngukur atawa deteksi.\n*Téhnik-téhnik nu ngawengku volatilisasi nu tujuanana pikeun ngahasilkeun atom-atom bébas unsur-unsur nu nyusun sampelna, nu salajengna bisa diukur dina kadar dumasar darajat serapan atawa émisina dina frékuénsi spéktrum nu husus. Rugina métode ieu, sampelna béak diancurkeun, kaasup naon baé nu aya dikandungna. Nu kaasup téhnik ieu di antarana [[spéktroskopi serapan atom]] (Ing. \'\'atomic absorption spectroscopy\'\') jeung \'\'[[ICP-MS/ICP-AES]]. Téhnik-téhnik ieu bisa tetep dipaké pikeun ngulik spésiasi, nyaéta saméméh volatilisasi.\n\n== Métode ==\nMétode analitis gumantung kana katalitian, kabersihan, préparasi sampel, [[akurasi jeung présisi|akurasi, sarta présisi]]. \n\nBiasana praktisi nu neundeun parabot gelasna dina asam sangkan nyegah kontaminasi, sampelna diuji sababaraha kali, sedengkeun parabotna dikumbah ku pangleyur murni nu husus.\n\nMétode standar pikeun analisis kadar ngaewngku dijieunna [[kurva kalibrasi]]. \n\nMun kadar unsur atawa sanyawa na sampelna luhur teuing ti rentang detéksi téhnikna, sampelna bisa diéncérkeun kitu baé maké pangleyur murni. Mun kadarna handapeun rentang ukuran alat, métode adisi bisa dipaké. Na métode ieu, kana sampel ditambahkeun sanyawa/unsur nu diulik nu kadarna geus dipikanyaho, lajeng béda antara kadar nu ditambahkeun jeung kadar nu kaukur ngarupakeun jumlah sabenerna dina sampel.\n\n[[bg:аналитична химия]] [[ca:Química Analítica]] [[de:Analytische Chemie]] [[en:Analytical chemistry]] [[es:Química analítica]] [[fr:Chimie analytique]] [[nl:Analytische scheikunde]]\n\n\n{{CabangKimia}}\n\n[[Category:Kimia]]','',3,'Kandar','20041224072710','',0,0,0,0,0.435028663573,'20041224072710','79958775927289'); INSERT INTO cur VALUES (843,0,'Analisis_régrési','\'\'\'Analisis régrési\'\'\' nyaéta [[métode statistik]] where the [[mean]] of one or more [[variabel acak]] is [[prediction|predicted]] conditioned on other (measured) random variables. Sacara husus, aya [[régrési liniér]], [[régrési logistik]], jeung \'\'[[supervised learning]]\'\'.\n\n\n{{pondok}}\n\n[[de:Regressionsanalyse]]\n[[en:Regression analysis]]','',3,'Kandar','20041229084611','',0,0,0,0,0.470004225369,'20050303211247','79958770915388'); INSERT INTO cur VALUES (844,1,'Analisis_régrési','Langkung merenah pami ieu artikel dialihkeun ka \'\'\'régrési liniér\'\'\'. [[User:Kandar|Kandar]] 03:24, 20 Jul 2004 (UTC)','',3,'Kandar','20040720032457','',0,0,0,1,0.1053266875,'20041229082021','79959279967542'); INSERT INTO cur VALUES (845,3,'Budhi','Kang Bud, terang istilah Sunda nu sarupi/sawanda sareng istilah \'\'\'timeline\'\'\' teu? [[User:Kandar|Kandar]] 07:09, 24 Jul 2004 (UTC)\n----\nWilujeng sumping, Kang Budhi. Hayu urang sasarengan ngeureuyeuh Wikipedia Basa Sunda! [[User:Kandar|Kandar]] 03:27, 20 Jul 2004 (UTC)\n\n== tarjamah ==\n\nKang Bud, mangga atuh geura tarjamahkeun artikel-artikelna. Yu ah! [[User:Kandar|kandar]] 07:13, 13 Aug 2004 (UTC)\n----\n\n== nyobaan ==\n\ncing ah ... ieu teh keur naon kitu nya ?\n\n== talk page ==\n\nKang Bud, ieu teh fungsina pikeun rohangan komunikasi antarkontributor Wikipedia. Misalna abdi, aya nu hoyong dicarioskeun perkawis Wikipedia nu patali sareng kang Budhi (conto: nyawalakeun istilah nu cocog pikeun hiji istilah asing), nya di dieu kuring ninggalkeun pesen. Kitu pangiten. [[User:Kandar|kandar]] 07:33, 18 Aug 2004 (UTC)\n----\n\n== tarjamah ==\n\nnaon basa sunda-na MAKA ? contona, lamun nilai A ...., lamun nilai B ..., MAKA ....\n----\nMANGKA kitu? [[User:Kandar|kandar]] 02:40, 20 Aug 2004 (UTC)\n\n----\nlamun persamaan naon basa sunda-na ?\n\n== robah ngaran ==\n\nkang .. kumaha lamun memeh ngarobah istilah basa inggris ka basa sunda di link-keun heula nu basa inggris, janten heunteu pareumeun obor. sabab kadang istilah nu sami kapendak dina widang sejen. sakadar usul, nuhun\n\n== chi-square ==\n\nKang Bud, perkawis artikel chi-square distribution, ku akang ditarjamahkeun [[sebaran Chi-kuadrat]]. Naha \'\'Chi\'\' di dieu kedah ngangga kapital atanapi henteu? Sareng \'\'chi-square\'\' nu leres janten \'\'chi-kuadrat\'\' atanapi \'\'kuadrat-chi\'\'? Rumaos abdi mah sok pabaluit, heuheu... [[User:Kandar|kandar]] 04:38, 27 Aug 2004 (UTC)\n----\nasana mah basa baheula keur diajar statistik make basa indonesia kitu ... sebaran chi-kuadrat ... henteu oge kedah hurup kapital, da teu aya beda hartosna ieuh .. maklum rada heubeul teu maca teksbook basa indonesia, ayeuna basa jepun terus bari jeung lieur ... kitu manawi ... heu heu oge ah ...\n\n== colenak ==\n\nsaha colenak teh ?\n\n== perilaku ==\n\nnaon tah tarjamah kana basa sundana ? teras persamaan naon tah ?','perilaku',13,'Budhi','20040908063800','',0,0,0,0,0.59061086345,'20040908063800','79959091936199'); INSERT INTO cur VALUES (847,1,'Linear_regression','#REDIRECT [[Talk:Régrési liniér]]\n','Talk:Linear regression moved to Talk:Régrési liniér',3,'Kandar','20040720032939','',0,1,0,1,0.301654288826188,'20040817100853','79959279967060'); INSERT INTO cur VALUES (850,0,'Angkutan','[[Category:Téhnologi]]\n[[Category:Hirup-hurip]]\n{{transport}}\n\n\'\'\'Transport\'\'\', atawa \'\'\'transportation\'\'\' (umum digunakeun di [[Amerika Serikat]]), nyaeta [[pindahna]] jalma jeung barang ti hiji tempat ka tempat sejenna. Istilah ieu asalna tina basa [[Latin]] \'\'trans\'\', hartina \'\'meuntas\'\', jeung \'\'portare\'\', hartina \'\'mawa\'\'. Di Indonésia umumna, ilahar ogé digunakeun kecap \'\'\'angkutan\'\'\'.\n\n==Aspék angkutan==\n\nWidang angkutan ngabogaan sababaraha aspék nu gampangna bisa dibagi jadi 3 bagian: [[infrastruktur]], [[tutumpakan]], jeung [[operasi]]. Infrastruktur kaasup jaringan angkutan ([[jalan]], [[karéta rél]], [[penerbangan]], [[kanal]], [[pipeline transport|pipelines]], jsb.) nu digunakeun, oge kaasup tempat ngumpulna atawa terminal (kayaning [[bandara]], [[stasion karéta]], [[terminal beus]], jeung [[labuan]]). Tutumpakan umumna anu bolak-balik dina jaringan, saperti [[mobil]], [[karéta]], [[pesawat terbang]]. Nu kaasup kana operasi nyaéta saperti [[rambu lalu lintas]] jeung [[ramp meter]], [[railroad switch]], [[kontrol lalu lintas awang-awang]], jsb, ogé pulisi, nu lianna saperti kumaha sistim [[béaya angkutan|béaya]] (saperti make [[jalan tol|tol]] atawa [[pajeg béngsin]] dina kasus angkutan jalan tol). \n\nSacara luas bisa disebutkeun, disain jaringan ngarupakeun widang dina [[rékayasa sipil|téhnik sipil]] jeung [[tata kota]], disain tutumpakan di widang [[rékayasa mékanis]] jeung bagian husus saperti \'\'[[nautical engineering]]\'\' jeung \'\'[[aerospace engineering]]\'\', sarta operasi biasa husus, bisa ngagunakeun \"pendekatan\" \'\'[[operations research]]\'\' atawa [[rékayasa sistim]].\n\n== Moda Transportasi ==\n\nModa nyaéta kombinasi jaringan, alat, jeung operasi, kaasup [[leumpang]], sistim [[angkutan jalan]], [[angkutan rél]], [[angkutan kapal laut]], jeung [[penerbangan]] modern.\n\n== Kategori Transpotasi ==\n* [[Angkutan tanaga sato]]\n* [[Angkutan awang-awang]] \n* [[Cable transport]]\n* [[Conveyor transport]]\n* [[Angkutan tanaga manusa]]\n* [[Angkutan hibrid]]\n* [[Angkutan jalan]] motoran\n* [[Pipeline transport]]\n* [[Angkutan karéta]]\n* [[Angkutan kapal laut]]\n* [[Angkutan luar angkasa]]\n* [[Transport on other planets]]\n* [[Proposed future transport]]\n\n== Angkutan jeung komunikasi ==\n\nAngkutan jeung [[komunikasi]] duanana silih gantikeun jeung silih lengkepan (\'\'substitutes and complements\'\'). Malah kamajuan dina widang komunikasi bisa ngagantikeun angkutan, kayaning ngaliwatan telegraf, telefon, faks, atawa [[surélék]], batan didatangan jelemana hiji-hiji, nyata yén cara komunikasi kitu ngalahirkeun interaksi nu leuwih gembleng, kaasup interaksi antarpribadi. Pertumbuhan angkutan teu mungkin mun teu aya komunikasi, nu penting pisan pikeun sistim angkutan nu maju. Ti rél karéta nu rék diliwatan ku karéta ti dua arah dina jalur tunggal, nepi ka lalu lintas awang-awang nu merlukeun nyaho lokasi pesawat di awang-awang. Jadi, geus kapangih yén kamajuan nu hiji bakal ngarojong kana kamajuan nu séjénna.\n\n== Angkutan, [[sistim kagiatan|kagiatan]], sarta [[guna lahan]] ==\n\nThere is a well-known relationship between the density of development, and types of transportation. Density is defined as area of floorspace per area of land. As a rule of thumb, densities of 1.5 or less are well suited to automobiles. Densities of six and above are well suited to trains. The range of densities from about two up to about four is not well served by conventional [[public_transport|public]] or [[private_transport|private]] transport. Many cities have grown into these densities, and are suffering traffic problems. [[Personal rapid transit]] might fill this gap.\n\nLand uses support activities. Those activities are spatially separated. People need transport to go from one to the other (from home to work to shop back to home for instance). Transport is a \"derived demand,\" in that transport is unnecessary but for the activities pursued at the ends of trips. \nGood land use keeps common activities close (e.g. housing and food shopping), and places higher-density development closer to transportation lines and hubs. Poor land use concentrates activities (such as jobs) far from other destinations (such as housing and shopping). \n\nThere are [[economies of agglomeration]]. Beyond transportation some land uses are more efficient when clustered.\nTransportation facilities consume land, and in cities, pavement (devoted to streets and parking) can easily exceed 20% of the total land use. An efficient transport system can reduce land waste.\n\n== Angkutan, énergi, jeung lingkungan ==\n\nAngkutan ngarupakeun konsumén [[énergi]] nu utama, lolobana maké [[hidrokarbon]]. Mun ngadurukna teu sampurna, balukarna jadi [[polusi]]. Sanajan tutumpakan di [[Amérika Serikat]] geus beuki bersih ku ayana [[aturan lingkungan]]. Low-pollution fuels can reduce pollution. The most popular low-pollution fuel at this time is liquified natural gas. [[Hydrogen]] is an even lower-pollution fuel.\n\nAnother tack is to make vehicles more efficient, which reduces pollution and waste by reducing the energy use. If electricity can be gotten to the vehicle, electric motors are the most efficient of all. Another method is to generate energy using [[fuel cell]]s, which are two to five times as efficient as the [[heat engine]]s traditionally used in vehicles. A trivial, but very effective method is to streamline ground vehicles, which spend up to 75% of their energy on air-resistance. Another method is to recycle the energy normally lost to braking, but this leads to a [[hybrid electric vehicle|more complex]] vehicle.\n\n== Tempo ogé ==\n* [[Daptar jejer angkutan]]\n* [[List_of_reference_tables#Transportation|Transportation reference tables]]\n\n==Tumbu kaluar==\n\n*[http://www.its.usyd.edu.au/conferences/thredbo/thredbo_about.asp Thredbo Series - International Conference on Competition and Ownership in Land Passenger Transport]\n**[http://www.publicpurpose.com/t-series.htm Contributions of Wendell Cox Consultancy]\n*[http://www.travelwalk.net/tokyo.htm Travel Walk] - Shortcut to Japan\'s Trains\n\n{{LapangTéhnologi}}\n\n[[Category:Commercial item transport and distribution]]\n\n[[af:Vervoer]] [[ca:Transport]] [[da:Transport]] [[de:Transport]] [[el:Μεταφορά]] [[en:Transportation]] [[et:Transport]] [[es:Transporte]] [[eo:Transporto]] [[fr:Transport]] [[fy:Transport]] [[gl:Transporte]] [[id:Transportasi]] [[it:Trasporti]] [[ia:Transporto]] [[he:תחבורה]] [[nl:Transport]] [[ja:交通]]\n[[no:Transport]] [[pl:Transport]] [[pt:Transporte]] [[ru:Транспорт]] [[simple:Transport]] [[fi:Liikenne]] [[ta:போக்குவரத்து]] [[uk:Транспорт]] [[zh:交通运输]]','kategori',20,'DiN','20050303200116','',0,0,0,0,0.016419313856,'20050303200116','79949696799883'); INSERT INTO cur VALUES (851,0,'Analisa_varian','Dina [[statistik]], \'\'\'analisa varian\'\'\' (\'\'\'ANOVA\'\'\') nyaeta kumpulan [[model statistik]] sarta prosedur nu pakait nu ngabandingan mean ku nukerkeun sakabeh varian observasi kana sababaraha bagian. Teknik analisa varian mimiti diwanohkeun ku [[statistician|statistikawan]] jeung [[geneticist|ahli genetik]] [[Ronald Fisher]] dina taun [[1920]]-an sarta [[1930]]-an. Aya tilu kelas konsep model nyaeta:\n\n*Model efek-fixed nu nganggap yen data asalna tina [[sebaran normal|populasi normal]] nu mibanda nilai mean beda.\n\n*Model efek-random nu nganggap yen data dijelaskeun sacara hirarki ku bedana populasi nu beda dina konstrain hirarki.\n\n*Model campuran nu ngajelaskeun kaayan boh efek fixed atawa random aya.\n\nTeknik dasarna nyaeta ngabagi total jumlah kuadrat kana sababaraha komopen pakait kana efek dina model. Contona, rek nembongkeun ANOVA sederhana ku make hiji \'\'perlakuan\'\' dina tingkat nu beda. (Lamun tingkat perlakuan bisa diitung sarta efekna linier, analisa [[régrési liniér]] bisa dipake).\n\n: SS_{\\hbox{Total}} = SS_{\\hbox{Error}} + SS_{\\hbox{Treatments}}\n\nJumlah tingkat kabebasan (disingkat \'\'df\'\') bisa dibagi-bagi ku cara nu sarua sarta hususna dina [[sebaran chi-kuadrat]] nu ngajelaskeun hubungan jumlah kuadrat.\n\n: df_{\\hbox{Total}} = df_{\\hbox{Error}} + df_{\\hbox{Treatments}}\n\n== Model fixed-efek ==\n\nModel fixed-efek analisa varian dipake keur kaayaan dimana nu ngagawekeun percobaan ngabogaan sababaraha perlakuan dina percobaanna, unggal percobaan ngan mangaruhan kana mean sebaran normal tina \'\'variabel nu mangaruhan\'\' tadi.\n\n== Model efek-random ==\n\nModel efek-random dipake keur ngajelaskeun kaayaan beda nu teu bisa dibandingkeun dina percobaan. Conto sederhana nyaeta estimasi mean teu dipikanyaho numana individu kabehanna beda. Dina kasus ieu, variasi antara individu \'\'ngabingungkeun\'\' kana alat observasi.\n\n== Tingkat kabebasan ==\n\nTingkat kabebasan nunjukeun wilangan observasi efektip nu mere pangaruh kana jumlah kuadrat dina ANOVA, jumlah total observasi dikurangan ku jumlah konstrain linier dina data.\n\n== Tes kapercayaan ==\n\nAnalisa varian nuju kana tes [[statistical significance|kapercayaan statistik]] make [[sebaran-F]] [[Ronald Fisher|Fisher]]. \n\nTempo oge: [[ANCOVA]] [[MANOVA]]\n\n[[en:Analysis of variance]]\n[[it:Analisi della varianza]]','',3,'Kandar','20050221052650','',0,0,1,0,0.322462470421,'20050221052650','79949778947349'); INSERT INTO cur VALUES (852,0,'Biostatistik','[[sv:Biostatistik]]\n\n\'\'\'Biostatistics\'\'\' (kadangkala disebut oge \'\'\'biometrics\'\'\'), leuwih umum, nyaeta \"aplikasi\"[[statistik]] keur [[biology]] jeung, biasa oge dipake, keur [[medicine]]. Because research questions in [[biology]] and [[medicine]] are various, biostatistics has expanded its domain to include any quantitative, not just statistical, models that may be used to answer these questions.\n\nPrograms in biostatistics are almost exclusively post-baccalaureate (i.e., found in graduate schools). They are most often found in schools of public health, affiliated with schools of medicine, agricultural universities or as a focus of application in departments of statistics.\n\nHowever, many universities that deal with ecological research have a biostatistics course that introduces concepts such as hypothesis testing for univariate and sometimes multivariate data sets with one, two, or more samples. Often this is combined or followed with some kind of experimental design course.\n\nAs a discipline designed to yield information, biostatistics may be considered as one (highly-developed) branch of [[medical informatics]], which, in turn, may be encompassed by the newer field of [[bioinformatics]].\n\nAkibatna, biostatistik mangrupakeun metoda kuantitatif saperti widang:\n*[[statistik]],\n*[[operations research]],\n*[[economics]], and, generally,\n*[[matematik]]\n\nand it is applied to research questions in fields such as:\n*[[public health]], which includes [[epidemiology]], [[nutrition]], [[environmental health]], and [[health services research]],\n*[[genomics]] and [[population genetics]],\n*[[medicine]],\n*[[ecology]],\n*[[bioassay]], and\n*[[agriculture]].\n\nFinally, the terms, biostatistics and [[biometry]], appear to be interchangeable, although [[biometry]] tends to connote a biological (or even agricultural), rather than medical, application.','',13,'Budhi','20040723020659','',0,0,0,0,0.480648508519,'20040723020659','79959276979340'); INSERT INTO cur VALUES (853,0,'Daptar_nagara','{{Lists by country}}\n\nIeu daptar mangrupi \'\'\'daptar nagara merdika\'\'\' sadunya, disusun numutkeun abjad. Nu kaasup di dieu teu ngan wungkul nu merdika \'\'de jure\'\', tapi ogé kaasup nu \'\'de facto\'\'nagara merdika, [[state]] for some explanation of the difference between these. To be listed here as a de facto independent country, article 1 of the [[Montevideo Convention]] from [[1933]] is followed, which means that entity should possess the following qualifications: (a) a permanent population; (b) a defined territory; (c) government; and (d) capacity to enter into relations with the other states. Furthermore, the entity doesn\'t accept that it de jure belongs to another country.\nIn the case a de facto independent country is included in this list, a note explains why this country is included. There are also a [[list of dependent territories]] and a [[list of disputed or occupied areas]]. \n\nOther articles focus on [[Imaginary country|imaginary countries]], [[micronation]]s and former countries (see [[List of extinct countries, empires, etc.]]).\nOne can also browse countries [[List of national capitals|by capital city]], [[List of countries by continent|by continent]], [[List of countries by population|by population]], [[List of countries by area|by area]], [[List of countries by population density|by population density]], [[List of countries by gross domestic product|by gross domestic product]], [[List of countries by date of nationhood|by date of nationhood]] and by [[time zone]]. Also, you can see a [[list of island countries]].\n\nThe [[Wikipedia:WikiProject Countries|WikiProject Countries]] is an attempt to formulate a template for the country articles and expands articles with public domain sources (\'\'see\'\' [[Wikipedia:Status of the porting of the CIA World Factbook|Status of the porting of the CIA World Factbook]], [[Wikipedia:Status of the porting of U.S. Dept of State info|Status of the porting of U.S. Dept of State info]]).\n\nFor more sources, see [[Geographic references]].\n\n:{{msg:compactTOC2}}__NOTOC__\n\n==A==\n[[Abkhazia]][[#Notes|7]] - [[Afghanistan]] - [[Albania]] - [[Algeria]] - [[Andorra]] - [[Angola]] - [[Antigua and Barbuda]] - [[Argentina]] - [[Armenia]] - [[Australia]] - [[Austria]] - [[Azerbaijan]]\n\n==B==\n[[The Bahamas]] - [[Bahrain]] - [[Bangladesh]] - [[Barbados]] - [[Belarus]] - [[Belgium]] - [[Belize]] - [[Benin]] - [[Bhutan]] - [[Bolivia]] - [[Bosnia and Herzegovina]] - [[Botswana]] - [[Brazil]] - [[Brunei]] - [[Bulgaria]] - [[Burkina Faso]] - Burma (now [[Myanmar]]) - [[Burundi]]\n\n==C==\n[[Cambodia]] - [[Cameroon]] - [[Canada]] - [[Cape Verde]] - [[Central African Republic]] - [[Chad]] - [[Chile]] - [[People\'s Republic of China]] - [[Republic of China]][[#Notes|1]] (\'\'Taiwan\'\') - [[Colombia]] - [[Comoros]] - [[Democratic Republic of the Congo]] (formerly \'\'Zaire\'\') - [[Republic of the Congo]] - [[Costa Rica]] - [[Côte d\'Ivoire]] - [[Croatia]] - [[Cuba]] - [[Cyprus]][[#Notes|8]] - [[Czech Republic]]\n\n==D==\n[[Denmark]] - [[Djibouti]] - [[Dominica]] - [[Dominican Republic]]\n\n==E==\n[[East Timor]] - [[Ecuador]] - [[Egypt]] - [[El Salvador]] - [[Equatorial Guinea]] - [[Eritrea]] - [[Estonia]] - [[Ethiopia]]\n\n==F==\n[[Fiji]] - [[Finland]] - [[France]]\n\n==G==\n[[Gabon]] - [[The Gambia]] - [[Georgia (country)|Georgia]] - [[Germany]] - [[Ghana]] - [[Greece]] - [[Grenada]] - [[Guatemala]] - [[Guinea]] - [[Guinea-Bissau]] - [[Guyana]]\n\n==H==\n[[Haiti]] - Holy See (see [[Vatican City]][[#Notes|4]]) - [[Honduras]] - [[Hungary]]\n\n==I==\n[[Iceland]] - [[India]] - [[Indonésia]] - [[Iran]] - [[Iraq]] - [[Republic of Ireland|Ireland]] - [[Israel]] - [[Italy]] - Ivory Coast (see [[Côte d\'Ivoire]])\n\n==J==\n[[Jamaica]] - [[Jepang]] - [[Jordania]]\n\n==K==\n[[Kazakhstan]] - [[Kenya]] - [[Kiribati]] - [[North Korea|Korea, North]] - [[South Korea|Korea, South]] - [[Kuwait]] - [[Kyrgyzstan]]\n\n==L==\n\n[[Laos]] - [[Latvia]] - [[Lebanon]] - [[Lesotho]] - [[Liberia]] - [[Libya]] - [[Liechtenstein]] - [[Lithuania]] - [[Luxembourg]]\n\n==M==\n[[Republic of Macedonia]][[#Notes|6]]- [[Madagascar]] - [[Malawi]] - [[Malaysia]] - [[Maldives]] - [[Mali]] - [[Malta]] - [[Marshall Islands]] - [[Mauritania]] - [[Mauritius]] - [[Mexico]] - [[Federated States of Micronesia]] - [[Moldova]] - [[Monaco]] - [[Mongolia]] - [[Morocco]] - [[Mozambique]] - [[Myanmar]]\n\n==N==\n[[Namibia]] - [[Nauru]] - [[Nepal]] - [[Netherlands]] - [[New Zealand]][[#Notes|2]] - [[Nicaragua]] - [[Niger]] - [[Nigeria]] - [[Turkish Republic of Northern Cyprus|Northern Cyprus]][[#Notes|8]] - [[North Korea]] - [[Norway]]\n\n==O==\n[[Oman]]\n\n==P==\n[[Pakistan]] - [[Palau]] - [[Palestine]] (see [[West Bank]], [[Gaza Strip]])[[#Notes|3]] - [[Panama]] - [[Papua New Guinea]] - [[Paraguay]] - [[Peru]] - [[Philippines]] - [[Poland]] - [[Portugal]]\n\n==Q==\n[[Qatar]]\n\n==R==\n[[Romania]] - [[Russia]] - [[Rwanda]]\n\n==S==\n[[Saint Kitts and Nevis]] - [[Saint Lucia]] - [[Saint Vincent and the Grenadines]] - [[Samoa]] - [[San Marino]] - [[São Tomé and Príncipe]] - [[Saudi Arabia]] - [[Senegal]] - [[Serbia and Montenegro]] - [[Seychelles]] - [[Sierra Leone]] - [[Singapore]] - [[Slovakia]] - [[Slovenia]] - [[Solomon Islands]] - [[Somalia]] - [[Somaliland]][[#Notes|7]] - [[South Africa]] - [[South Korea]] - [[South Ossetia]][[#Notes|7]] - [[Spain]] - [[Sri Lanka]] - [[Sudan]] - [[Suriname]] - [[Swaziland]] - [[Sweden]] - [[Switzerland]] - [[Syria]]\n\n==T==\nTaiwan (see [[Republic of China]][[#Notes|1]]) - [[Tajikistan]] - [[Tanzania]] - [[Thailand]] - Timor Leste (see [[East Timor]]) - [[Togo]] - [[Tonga]] - [[Trinidad and Tobago]] - [[Tunisia]] - [[Turkey]] - [[Turkmenistan]] - [[Tuvalu]]\n\n==U==\n[[Uganda]] - [[Ukraine]] - [[United Arab Emirates]] - [[United Kingdom]] - [[United States|United States of America]] - [[Uruguay]] - [[Uzbekistan]]\n\n==V==\n[[Vanuatu]] - [[Vatican City]][[#Notes|4]] (\'\'Holy See\'\') - [[Venezuela]] - [[Vietnam]]\n\n==W==\n[[Western Sahara]][[#Notes|5]] \n\n==Y==\n[[Yemen]]\n\n==Z==\n\n[[Zambia]] - [[Zimbabwe]]\n\n\n----\n\n\n==Notes==\nAbout the status/sovereignty of countries listed\n*1 [[Republic of China]] (Taiwan): see [[Political status of Taiwan]]\n*2 [[Cook Islands]] and [[Niue]] are in free association with New Zealand (see also [[Niue Constitution Act 1974 (NZ)]]) and can be found at the [[list of dependent territories]]\n*3 Palestine: \"[[State of Palestine]]\" was declared 1988 and recognized by a series of Arab and Muslim countries, see also: [[proposals for a Palestinian state]] and [[Palestinian territories]]. [[Gaza Strip]], [[West Bank]], [[Israel]] include country articles about areas in the [[Palestine]] region.\n*4 Vatican: see [[Holy See]]\n*5 Western Sahara: see [[Politics of Western Sahara]]\n*6 [[Republic of Macedonia]]: known internationally as \"The Former Yugoslav Republic of Macedonia\" (see there).\n*7 Abkhazia, Somaliland, and South Ossetia are self-declared independent states with no international recognition from any other nation: see [[List of unrecognized countries]].\n*8 The [[Turkish Republic of Northern Cyprus]] seceded from [[Cyprus]], but is only recognized by [[Turkey]].\n\n==Jejer nu patali==\n*[[List of reference tables#List of countries and other entities]]\n*[[Géografi]]\n*[[Bumi]]\n*[[Buana]]\n*[[Thirty most populous cities in the world]]\n\n[[ar:قائمة الدول المستقلة]]\n[[bg:Списък на страните]]\n[[bs:Spisak država]]\n[[ca:Estat]]\n[[cs:Seznam států světa (abecedně)]]\n[[cy:Gwledydd y byd]]\n[[da:Verdens lande]]\n[[de:Liste unabhängiger Staaten]]\n[[el:Κατάλογος χωρών]] [[en:List of countries]]\n[[es:Lista de paises]]\n[[et:Maailma maad]]\n[[fr:Liste des pays du monde]]\n[[hr:Popis država]]\n[[hu:Országok listája]]\n[[ia:Paises del mundo]]\n[[id:Daftar Negara-Negara di Dunia]]\n[[it:Paesi del mondo]]\n[[ja:国の一覧]]\n[[ko:세계의 나라]]\n[[la:Nationes mundi]]\n[[lt:%C5%A0ali%C5%B3_s%C4%85ra%C5%A1as]]\n[[ms:Daftar negara]]\n[[nl:Landen van de wereld]]\n[[no:Liste over stater]]\n[[pl:Pa%F1stwa %B6wiata]]\n[[pt:Lista de paises]]\n[[ro:Ţări ale lumii]]\n[[ru:Алфавитный список стран]]\n[[sl:Države sveta]]\n[[sr:Списак држава]]\n[[sv:Alfabetisk lista över världens länder]]\n[[ta:உலக நாடுகளின் பட்டியல்]]\n[[th:รายชื่อประเทศ]]\n[[tt:Däwlätlär isemlege]]\n[[tr:Ülkeler]]\n[[uk:Список країн]]\n[[ur:%D9%85%D9%85%D8%A7%D9%84%DA%A9]]\n[[zh:世界地理索引]]\n[[simple:List of countries]]\n[[Category:Lists of countries]]','',0,'61.94.47.36','20041224134836','',0,0,0,0,0.150109297666,'20050209000836','79958775865163'); INSERT INTO cur VALUES (854,0,'Jepang','\'\'\'Jepang\'\'\' (\'\'Nippon/Nihon\'\' 日本 (harti aksarana panonpoe, jeung akar/asli), harti literaturna \"asli ti [[sun|panonpoe ]]\") ngarupakeun salah sahiji nagara di [[Asia Wetan]] ayana antara [[Samudera Pacific]] jeung wetaneun Semenanjung [[Korea]]. Tina ngaranna, leuwih umum ditarjamahkeun jadi \"Nagari Panonpoe Terbit,\" asalna tina basa [[China]] jeung ningali posisi Jepang relatif pangwetanna ti Benua Asia. Samemehna Jepang aya hubungan jeung China, disebut oge \'\'Yamato\'\' (大和). \'\'Wa\'\' (倭) ngarupakeun salah sahiji ngaran mimiti China anu dipake keur nyebut Japan, kira-kira waktu Periode [[Three Kingdoms]].\n\nBentuk Jepang siga ranggeuyan rante, pulo-pulo gedena, di kidul ka kaler, [[Kyushu]] (九州), [[Shikoku]] (四国), [[Honshu]] (本州, pulo panggedena), jeung [[Hokkaido]] (北海道). \n\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" width=\"270px\" style=\"margin-left: 10px\"\n|+\'\'\'Nippon (Nihon-koku)
日本国\'\'\'
\n|-\n| style=\"background:#efefef;\" align=\"center\" colspan=2 |\n{| border=\"0\" cellpadding=\"2\" cellspacing=\"0\"\n|-\n| align=\"center\" width=\"130px\" | [[Image:Japan flag large.png|125px|]] || align=\"center\" width=\"130px\" height=\"130px\" | [[Image:Japan_coa.png]]\n|-\n| align=\"center\" width=\"130px\" | ([[Flag of Japan|In Detail]]) || align=\"center\" width=\"130px\" | ([[Imperial Seal]])\n|}\n|-\n| align=\"center\" colspan=2 style=\"border-bottom:3px solid gray;\" | \'\'National [[motto]]: None\'\'\n|-\n| align=center colspan=2 | [[image:LocationJapan.png]]\n|-\n| [[Official language]] || [[Japanese language|Japanese]]\n|-\n| [[Capital]] || [[Tokyo]]1\n|-\n| Largest City || [[Tokyo]]\n|-\n| [[Emperors of Japan|Emperor]] || [[Emperor Akihito of Japan|Akihito]] \n|-\n| [[Prime Minister of Japan|Prime minister]] || [[Junichiro Koizumi|Junichirō Koizumi]]\n|-\n| [[Area]]
 - Total
 - % water || [[List of countries by area|Ranked 60th]]
377,835 [[square kilometre|km²]]
0.8%\n|-\n| [[Population]]
 - Total ([[2003]])
 - [[Population density|Density]] || [[List of countries by population|Ranked 10th]]
127,214,499
335/km²\n|-\n| [[Gross Domestic Product|GDP]] (base exchange rates)
 - Total ([[2002]])
 - GDP/head\n| [[List of economies by GDP|Ranked 2nd (among countries)
Ranked 3rd (among economies)]]
$4.52 trillion
$28,000(ppp)\n|-\n| [[Gross National Product|GNP]]
 - Total ([[2000]])
 - GNP/head\n| Ranked 2nd
$4.85 trillion
$38,000\n|-\n| [[Currency]] || [[Yen]]\n|-\n| [[Time zone]] || [[Coordinated Universal Time|UTC]] +9\n|-\n| [[National anthem]] || [[Kimi Ga Yo]]\n|-\n| [[Top-level domain|Internet TLD]] || .JP\n|-\n| [[List_of_country_calling_codes|Calling Code]] || 81\n|-\n| colspan=\"2\" | 1 Some argue that [[Kyoto]] has this status: see [[Capital of Japan debate]].\n|}\n\n== Origin of Name ==\nThe [[Japanese language|Japanese]] names for Japan are \'\'Nippon\'\' and \'\'Nihon\'\'. They are both written the same in Japanese. The Japanese name \'\'Nippon\'\' is used for most official purposes, including [[Yen|money]], [[stamp]]s, and international [[sporting event]]s. \'\'Nihon\'\' is a more casual term used in Japan. For example, Japanese people call themselves \'\'Nihonjin\'\' and their language \'\'Nihongo\'\': literally \"Japanese People\" and \"Japanese Language\" respectively. In Japan today, Nippon has more of a nationalistic role, and is used more by the elderly, while Nihon is a casual term, and is used by the majority of the Japanese population.\n\nThe [[English language|English]] word for Japan came to the west from early trade routes. The early [[Mandarin (linguistics)|Mandarin Chinese]] word for Japan was recorded by [[Marco Polo]] as \'\'Cipangu\'\'. However, the [[Cantonese]] word for Japan, from which the word \'\'Japan\'\' was probably originally born, is \'\'Jatbun\'\'. In [[Malay language|Malay]] the Cantonese word became \'\'Japang\'\' and was thus encountered by [[Portugal|Portuguese]] traders in [[Malacca]] in the [[16th century]]. It is thought the Portuguese traders were the first to bring the word to [[Europe]]. It was first recorded in English in [[1577]] spelled \'\'Giapan\'\'. \n\nIn English, the official title of the country is simply \"Japan\". Previously, the full title had been the \"Empire of Japan\" but this was changed after the adoption of the post-war constitution. The official Japanese title is \'\'Nihonkoku\'\' (日本国), literally \"Country of Japan.\"\n\n== Sajarah ==\n\'\'Main article: [[History of Japan]]\'\'\n\nArcheological research indicates that Japan had already been occupied by early humans at least 500,000 years ago, during the [[Paleolithic|Lower Paleolithic]] period. Over repeated ice-ages during the last million years, Japan was regularly connected by land bridges to the Asian mainland (by [[Sakhalin]] to the North, and probably [[Kyushu]] to the South), facilitating migrations of humans, animals and plants to the Japanese [[archipelago]] from the area that is now China and Korea.\n\nWith the end of the last [[ice age]] and general warming, the [[Jomon]] culture emerged around 11,000 BC, characterized by a [[mesolithic]] to [[neolithic]] semi-sedentary [[hunter-gatherer]] lifestyle and the manufacture of the earliest known [[pottery]] in the World. It is thought that [[Jomon]] populations were the ancestors of the [[Proto-Japanese]] and today\'s [[Ainu]]. \n\nThe start of the Yayoi period around 300 BC marked the influx from the Asian mainland of new technologies such as rice-farming, as well as rather massive migrations from various part of Asia like [[Korea]] and [[China]], especially around [[Beijing]] and [[Shanghai]], and from the South by marine route. However, several recent studies have pointed out that the Yayoi period is 5 to 6 centuries longer than previously believed, making massive immigrations unneeded in order to explain the increase in population.\n\nAccording to traditional Japanese mythology, Japan was founded in the [[7th century BC]] by the ancestral [[Emperor Jimmu of Japan|Emperor Jimmu]]. During the [[5th century|5th]] and [[6th century|6th centuries]], the [[Chinese written language|Chinese writing system]] and [[Buddhism]] were introduced with other [[China|Chinese]] cultures first via the Korean peninsula and later directly from China. The [[Emperors of Japan|emperors]] were the nominal [[Rulers of Japan|rulers]], but actual power was usually held by powerful court nobles, regents, or \'\'[[shogun]]s\'\' (military governors).\n\nAncient political structure held that, once battles between rivals were finished, the victorious Shogun would migrate to the capital [[Heian]] (fully Heian-kyo-to, \'kyo-to\' meaning capital city, and the full name now shortened to the suffix, \'[[Kyoto]]\') to rule under the grace of the Emperor. However, in the year [[1185]], general [[Minamoto no Yoritomo]] was the first to break this tradition, refusing to relocate and subsequently holding power in [[Kamakura, Kanagawa|Kamakura]], just south of present-day [[Yokohama]]. While this [[Kamakura Shogunate]] was somewhat stable, Japan soon fell into warring factions and suffered through what became known as the Warring States or [[Sengoku Period]]. In the year [[1600]], at the [[Battle of Sekigahara]], Shogun [[Tokugawa Ieyasu]] either co-opted or defeated his enemies and formed the [[Tokugawa Shogunate]] in the small fishing village of [[Edo]] (formerly transcribed as \'Yeddo\'), what is now known as [[Tokyo]] (\'\'eastern capital\'\'). \n\nSince the last half of the [[16th century]], traders from [[Portugal]], [[Spain]], the [[Netherlands]], and [[England]], arrived, as did [[Christianity|Christian]] missionaries. During the first part of the [[17th century]], Japan\'s shogunate suspected that Catholic missionaries were actually forerunners of a military conquest by Iberian powers and ultimately barred all relations with the Europeans except for severely restricted contacts with Protestant Dutch merchants at [[Dejima]] off [[Nagasaki]], though Chinese ships were permitted to enter Nagasaki and Korean envoys to proceed to the capital. This isolation lasted for 251 years, until Commodore [[Matthew Perry (naval officer)|Matthew Perry]] forced the opening of Japan to the West with the [[Convention of Kanagawa]] in [[1854]].\n\nWithin several years, renewed contact with the West profoundly altered Japanese society. Following the 1867-1868 [[Boshin War]] the shogunate was forced to resign, and the emperor was restored to power. The [[Meiji Restoration]] of [[1868]] initiated many reforms. The [[feudalism|feudal system]] was abolished and numerous Western institutions were adopted, including a Western legal system and government, along with other economic, social and military reforms that transformed the [[Empire of Japan]] into a world power. As results of [[Sino-Japanese war]] and [[Russo-Japanese war]], Japan acquired [[Taiwan]] and [[Sakhalin]], and later annexed [[Korea]] in 1910, over Korea\'s immense popular protest.\n\nThe early [[20th century]] saw Japan come under increasing influence of an expansionist military, leading to the invasion of [[Manchuria]], a second [[Sino-Japanese War (1937-1945)|Sino-Japanese War]] ([[1937]]). Japan allied with [[Germany]] and [[Italy]] and formed the Axis Pact. Japanese leaders felt it was necessary to attack the US naval base in [[Pearl Harbor]] ([[1941]]) to ensure Japanese supremacy in Southeast Asia. However, the entry of the [[United States]] into [[World War II]] would slowly tilt the balance in the Pacific against the Japanese. After a long [[Pacific]] campaign, Japan lost [[Okinawa]] in the [[Ryukyu]] islands and was pushed back to the four main islands. The [[United States]] made fierce attacks on [[Tokyo]], [[Osaka]], and other cities by [[strategic bombing]], and [[Hiroshima]] and [[Nagasaki]] with two [[atomic bomb]]s. Japan eventually agreed to an unconditional surrender to the [[United States]] on [[August 15]], [[1945]].\n\nA defeated post-war Japan remained under US occupation until [[1952]], whereafter it embarked on a remarkable economic recovery that returned prosperity to the islands. The success of 1964 Tokyo Olympic Games is regarded as many as the sign that Japan had finally regained its national status. The [[Ryukyu]] islands remained under US occupation until [[1972]] to stabilize [[East Asia]], and a major military presence remains there to this day. Such return included the disputed [[Senkaku Islands]], which claimed by both [[People\'s Republic of China|Mainland China]] and [[Republic of China|Taiwan]]. The [[Soviet Union]] seized the [[Kuril]] islands north of Hokkaido at the end of WWII, and despite the collapse of the Soviet state and friendly relations between countries, [[Russia]] has refused to return these islands. Japan has territorial disputes over the Liancourt Rocks with [[South Korea]], which now occupies the fish-rich territory.\n\n== Politics ==\n\'\'Main article: [[Politics of Japan]]\'\'\n\nJapan is generally considered to be a [[constitutional monarchy]] with a bicameral [[parliament]], the \'\'Kokkai\'\' or [[Diet of Japan|Diet]]. Japan has a royal family led by an [[Emperors of Japan|Emperor]], but under the current constitution he performs only ceremonial duties and holds no real power, not even emergency [[reserve power]]s. The [[executive branch]] is responsible to the Diet, consisting of a [[cabinet (government)|Cabinet]] composed of a [[Prime Minister of Japan|Prime Minister]] and ministers of state, all of whom must be civilians. The Prime Minister must be a member of the Diet and is designated by his colleagues. The Prime Minister has the power to appoint and remove ministers, a majority of whom must be Diet members. Sovereignty, previously embodied in the Emperor, is vested in the [[Japanese people]] by the [[Constitution of Japan|Constitution]], and the Emperor is defined as the symbol of the State and of national unity.\n\nThe [[legislative branch]] consists of a House of Representatives (Lower House or \'\'Shugi-in\'\') containing 480 seats, elected by popular vote every four years, and a House of Councillors (Upper House or \'\'Sangi-in\'\') of 247 seats, whose popularly elected members serve six-year terms. Each house contains officials elected either directly or proportionally by party. There is universal adult (over 20 years old) suffrage with a secret ballot for all elective offices.\n\n[[Liberal Democratic Party]] (LDP) has been in power almost continuously since 1955 (except for 1993) , when it was formed as a merger of the two Japanese [[conservative]] parties, the Liberal and Democratic parties. Today\'s Prime Minster, Junichiro Koizumi is from the LDP. The LDP governs in coalition with the theocratic buddhist New Komeito Party. In opposition are the Democratic Party, the Social Democratic Party, and the Communist Party. Prime Minister [[Junichiro Koizumi]] has introduced radical reform in all fields, like taking steps to de-nationalize [[Japan Post]] as well as the [[Japan Highway Public Corporation]]. Another controversial move was the sending of the SDF (Self Defence Forces) to Iraq without a UN resolution. The opposition DPJ (Democratic Party of Japan) has recently been gaining momentum, gaining more seats than the LDP in the July, 2004 House of Coucillors election where half of the seats were up for election. However, the governing coalition of the LDP and the New Komeito Party maintained their majority.\n\n== Prefectures ==\n\'\'Main article: [[Prefectures of Japan]]\'\'\n\n[[Image:Ja-map.png|right|Map of Japan]]\n\nJapan is subdivided into 47 [[prefecture]]s (ordered by [[ISO 3166-2 codes for Japan|ISO 3166-2]]):\n\n
\n*[[Karafuto prefecture|Karafuto]] (occupied by Russia)\n*[[Hokkaido prefecture|Hokkaido]]\n*[[Aomori prefecture|Aomori]]\n*[[Iwate prefecture|Iwate]]\n*[[Miyagi prefecture|Miyagi]]\n*[[Akita prefecture|Akita]]\n*[[Yamagata prefecture|Yamagata]]\n*[[Fukushima prefecture|Fukushima]]\n*[[Ibaraki prefecture|Ibaraki]]\n*[[Tochigi prefecture|Tochigi]]\n*[[Gunma prefecture|Gunma]]\n*[[Saitama prefecture|Saitama]]\n*[[Chiba prefecture|Chiba]]\n*[[Tokyo prefecture|Tokyo]]\n*[[Kanagawa prefecture|Kanagawa]]\n*[[Niigata prefecture|Niigata]]\n*[[Toyama prefecture|Toyama]]\n*[[Ishikawa prefecture|Ishikawa]]\n*[[Fukui prefecture|Fukui]]\n*[[Yamanashi prefecture|Yamanashi]]\n*[[Nagano prefecture|Nagano]]\n*[[Gifu prefecture|Gifu]]\n*[[Shizuoka prefecture|Shizuoka]]\n*[[Aichi prefecture|Aichi]]\n*[[Mie prefecture|Mie]]\n\n*[[Shiga prefecture|Shiga]]\n*[[Kyoto prefecture|Kyoto]]\n*[[Osaka prefecture|Osaka]]\n*[[Hyogo prefecture|Hyogo]]\n*[[Nara prefecture|Nara]]\n*[[Wakayama prefecture|Wakayama]]\n*[[Tottori prefecture|Tottori]]\n*[[Shimane prefecture|Shimane]]\n*[[Okayama prefecture|Okayama]]\n*[[Hiroshima prefecture|Hiroshima]]\n*[[Yamaguchi prefecture|Yamaguchi]]\n*[[Tokushima prefecture|Tokushima]]\n*[[Kagawa prefecture|Kagawa]]\n*[[Ehime prefecture|Ehime]]\n*[[Kochi prefecture|Kochi]]\n*[[Fukuoka prefecture|Fukuoka]]\n*[[Saga prefecture|Saga]]\n*[[Nagasaki prefecture|Nagasaki]]\n*[[Kumamoto prefecture|Kumamoto]]\n*[[Oita prefecture|Oita]]\n*[[Miyazaki prefecture|Miyazaki]]\n*[[Kagoshima prefecture|Kagoshima]]\n*[[Okinawa prefecture|Okinawa]]\n
\nThe order of this list is from the north to the south, which is commonly accepted in Japan.\n\n== Geography ==\n\'\'Main article: [[Geography of Japan]]\'\'\n\n
[[Image:Japan_global_locator.png]]
\n\nJapan, a country of islands, extends along the eastern or [[Pacific Ocean|Pacific]] coast of [[Asia]]. The main islands, running from north to south, are [[Karafuto]] (Japanese: 1679-1875), [[Hokkaido]], [[Honshu]] (or the mainland), [[Shikoku]], and [[Kyushu]]. [[Mairuppo]] in the disputed [[Kuril Islands]] ([[Japanese language|Japanese]]: 千島列島, Chishima Rettō) is over 800km to the northeast of [[Hokkaido]]; [[Naha]] on [[Okinawa]] in the [[Ryukyu]] archipelago is over 600 km to the southwest of Kyushu. In addition, about 3,000 smaller islands may be counted in the full extent of the [[archipelago]] that comprises greater Japan. About 73% of the country is mountainous, with a chain running through each of the main islands. Japan\'s highest mountain is the famous [[Mount Fuji]] at 3,776 m. Oyakobayama, at the northern end of the [[Kuril Islands]], is a snow-clad peak (2337 m) rising directly out of the sea.\n\nSince so little flat area exists, many hills and mountainsides are cultivated all the way to the summits. As Japan is situated in a [[volcanism|volcanic]] zone along the Pacific deeps, frequent low intensity earth tremors and occasional volcanic activity are felt throughout the islands. Destructive [[earthquake]]s occur several times a century, often resulting in [[tsunami]]s. [[Onsen|Hot springs]] are numerous and have been developed as resorts.\n\nThe [[Japanese Archipelago]] extends from north to south along the eastern coast of the [[Eurasia|Eurasian Continent]], the western shore of the [[Pacific Ocean]]. Japan is a temperate region with four distinct seasons, but because of its great length from north to south, its climate varies from region to region: the far north is very cold in the winter, while the far south is subtropical. The climate is also affected by the seasonal winds blown from the continent to the ocean in winters and vice versa in summers. \n\nLate June and early July are a [[rainy season]] (except in [[Hokkaido]] and islands to the north), as a seasonal rain front or \'\'baiu zensen\'\' (梅雨前線) stays above Japan. In the late summer and early autumn, typhoons develop from tropical depressions generated near the equator, and track from the southwest to the northeast, often bringing heavy rain. \n\nJapan\'s varied geographical features divide it into six principal climatic zones.\n\n*[[Hokkaido]]: Belonging to the cool temperate zone, Hokkaido has long, cold winters and cool summers. The Kuril Islands are fogbound. [[precipitation (meteorology)|Precipitation]] is not heavy, but the islands usually develop deep snowbanks in the winter. \n*[[Sea of Japan]]: The northwest wind in the wintertime brings heavy snowfall. In summers, the region is less hot than the Pacific area, but it sometimes experiences extremely hot temperatures due to the [[Foehn wind]] phenomenon. \n*Central Highland (\'\'[[Chuo-kochi]]\'\'): A typical inland climate, with large temperature differences between summers and winters and between days and nights. Precipitation is not large throughout a year.\n*[[Seto Inland Sea]] (\'\'Setonaikai\'\'): The mountains in [[Chugoku]] and [[Shikoku]] regions block the seasonal winds and bring mild climate and many fine days throughout a year.\n*Pacific Ocean: Experiences cold winters with little snowfall and hot, humid summers due to the southeast seasonal wind.\n*Nansei-shoto ([[Ryukyu]]) or Southwest Islands: Has a subtropical climate with warm winters and hot summers. Precipitation is very heavy, especially during the rainy season, and also due to typhoons.\n\nPolitically and culturally, Japan is commonly divided into ten regions. From north to south, these are [[Karafuto]], [[Hokkaido]] and [[Chishima]], [[Tohoku region]], [[Hokuriku region]], [[Kanto region]], [[Chubu region]], [[Kinki region]] (commonly called [[Kansai]]), [[Chugoku region]], [[Shikoku region]], [[Kyushu region]], and [[Okinawa]], the main island in the [[Ryukyu Islands]].\n\nJapan has outstanding territorial disputes over the [[Kuril Islands]] and [[Sakhalin]] or [[Karafuto]], occupied by Russia, as well as the [[Liancourt Rocks]] (Jp. \'\'Takeshima\'\'), claimed by Korea. The [[Senkaku Islands]] are claimed by China and Taiwan as \"Diaoyutai\".\n\n== Economy ==\n\'\'Main article: [[Economy of Japan]]\'\'\n\nGovernment-industry cooperation, a strong work ethic, mastery of high technology, emphasis on education and a comparatively small defense allocation (1% of [[Gross Domestic Product|GDP]]) have helped Japan advance with extraordinary speed to become one of the largest economic powers in the world along with the US and EU.\n\nNotable characteristics of the economy include the working together of manufacturers, suppliers, distributors and banks in closely-knit groups called [[keiretsu]]; the powerful enterprise unions and \'\'[[shunto]]\'\'; cozy relations with government bureaucrats, and the guarantee of lifetime employment (shushin koyo) for up to a third of the urban labor force, usually big corporations and highly unionized blue-collar factories. Small and medium enterprises, women, and foreign employees typically do not enjoy such benefits. Most of the these features are now eroding, however, and the economy is currently characterized by stagnation.\n\nIndustry, the most important sector of the economy, is heavily dependent on imported raw materials and fuels. The much smaller [[agriculture|agricultural]] sector is highly subsidised and protected, most notably for rice which currently charges a 490% tariff on imported rice and enforces a quota of only 3% of the total rice market. Considerable efforts are expended on developing a better tasting fruits and vegetables and while pricey even by high cost of living in Japan, best products are really the best (if you\'re willing to spend $20 for a single Japanese pear). Usually self-sufficient in [[rice]] (except for its use in making rice crackers and processed foods), Japan must import about 50% of its requirements of other [[grain]] and fodder crops. Japan maintains one of the world\'s largest fishing fleets and accounts for nearly 15% of the global catch, prompting some claims that Japan\'s fishing is leading to overdepletion in fish stocks such as tuna as well as killing whales for \'scientific research\', and the whale meat somehow ending up in seafood restaurants. For three decades overall real economic growth had been spectacular: a 10% average in the [[1960s]], a 5% average in the [[1970s]], and a 4% average in the [[1980s]]. Growth slowed markedly in the [[1990s]] largely because of the after effects of overinvestment during the late 1980s and contractionary domestic policies intended to wring speculative excesses from the stock and real estate markets. Government efforts to revive economic growth have met with little success and were further hampered in [[2000]]-[[2001]] by the slowing of the US and [[Asia]]n economies.\n\n\n\n\nThe crowding of habitable land area and the aging of the population are two major long-run problems as is rising cost of the health care. [[Robotics]] constitutes a key long-term economic strength, with Japan possessing 410,000 of the world\'s 720,000 \"working robots\". Recently, the focus has also been on the [[Anime]] and other contemporary arts.\n\n== Demographics ==\n\'\'Main article: [[Demographics of Japan]]\'\'\n\nJapanese society is known to be ethnically and linguistically very homogeneous, with small populations of primarily North and South [[Koreans]] (1 million), Okinawan (1.5 million), Chinese and [[Taiwan]]ese (0.5 million), Filipinos (0.5 million), and Brazilians (250,000), as well as the indigenous [[Ainu]] minority in [[Hokkaido]]. 99% of the population speaks [[Japanese language|Japanese]] as their first language.\n\nThe Japanese population is one of the most rapidly aging on Earth. Fertility rates dropped in the wake of World War II, and dropped again in the mid-1970\'s, as more women remained in the workplace and refused to get married. Japan now also has the highest [[life expectancy]] in the world. By [[2007]], when Japan\'s population growth is expected to stop completely, over 20% of the population will be over the age of 65. Japanese government planners are currently in a heated debate over how to cope with this problem. [http://www.mofa.go.jp/j_info/japan/socsec/ogawa.html]\n\nMost Japanese people profess to believe in the religions of Shinto and Buddhism, both practiced together, which is normal for Asian religions. Many people, especially those in younger generations, claim to feel that religion is something to stay clear from, pointing out historical reasons such as the role that the nationally enforced [[Shinto]] played in World War II, and more recently [[Aum Shinrikyo]] and its actions. However, Shinto and Buddhist teachings are deeply entangled in the everyday life of Japanese. Often, it is so deep that it takes someone from outside to point it out. Most Japanese people, though they denounce religion, still follow it, but not devoutly and some do not even follow their religion.\n\nSee also: [[Religions of Japan]]\n\n== Culture ==\n\'\'Main article: [[Culture of Japan]]\'\'\n\nJapanese culture consists of the interaction between a strong original [[Jomon]] culture and subsequent influences from the rest of the world. China and Korea were first mostly influential, starting with the development of the [[Yayoi]] culture from around 300BC. Classical Greek and Indian cultural traditions, combined into [[Greco-Buddhism]], influenced the arts and religions of Japan from the 6th century AD, culminating with the introduction of [[Mahayana]] [[Buddhism]]. From the 16th century onward, European influence prevailed, with American influences becoming predominant following the end of [[WWII]].\n\nJapan developed a unique original culture, in its arts ([[ikebana]], [[origami]], [[ukiyo-e]]), [[Japanese crafts|crafts]] ([[Japanese Dolls|dolls]], [[lacquerware]], [[Japanese Pottery|pottery]]), performances ([[bunraku]], [[Japanese traditional dance|dance]], [[kabuki]], [[noh]], [[raku-go]]), and traditions ([[Japanese games|games]], [[onsen]], [[sento]], [[Japanese tea ceremony|tea ceremony]]), as well as a unique [[Japanese Cuisine|cuisine]].\n\nToday, Japan is one of the world\'s largest exporters of popular culture. Japanese [[anime|cartoons]], [[manga|comic books]], [[fashion]], [[Japanese cinema|films]], [[japanese literature|literature]], and [[Music of Japan|music]] have gained popularity around the world, especially in the other countries of Asia. \n\n\'\'See also: [[Katana]], [[Japanese clothing]], [[Japanese Festivals]], [[Japanese New Year]], [[Japanese Sports]], [[Japanese television programs]], [[Tourism in Japan]], [[Japanese media]]\'\'\n\n== Further Reading ==\n\n* Conrad Totman, 2000. \'A History of Modern Japan. Blackwell Publishers.\'\n* C.H. Kwan. 2001. \'Yen Bloc: Toward Economic Integration in Asia.\' Brookings Institution Press.\n* Bernson, Mary Hammond and Elaine Magnusson, eds. MODERN JAPAN: AN IDEA BOOK FOR K-12 TEACHERS. MULTICULTURAL EDUCATION RESOURCE SERIES. Olympia, WA: Office of the State Superintendent of Public Instruction, 1984. ED 252 486. \n* Cogan, John J. and Donald O. Schneider, eds. PERSPECTIVES ON JAPAN: A GUIDE FOR TEACHERS. Washington, DC: National Council for the Social Studies, 1983. ED 236 090. \n* EAST MEETS WEST: MUTUAL IMAGES. Stanford, CA: California Center for Research in International Studies, l980. ED 196 765. \n* Kaderabeck, Leslie. THE JAPANESE AUTOMOBILE WORKER: A MICROCOSM OF JAPAN\'S SUCCESS. 1985. ED 263 041. \n* Murphy, Carole. A STEP BY STEP GUIDE FOR PLANNING A JAPANESE CULTURAL FESTIVAL. 1983. ED 238 748. \n* Wojtan, Linda S. FREE RESOURCES FOR TEACHING ABOUT JAPAN. Bloomington, IN: Midwest Program for Teaching about Japan, Indiana University, 1986. ED 270 3891.\n\n== Miscellaneous topics ==\n\n* [[Japanese calendar]]\n* [[Updated Japan News]]\n* [[Communications in Japan]]\n* [[Education in Japan]]\n* [[Transportation in Japan]]\n* [[Military of Japan]]\n* [[Foreign relations of Japan]]\n* [[Japanese law]]\n* [[Japanese Television and Radio]]\n* [[List of Japanese people]]\n* [[List of Japan-related topics]]\n* [[Ethnic issues in Japan]]\n* [[Japanese cell phone culture]]\n* [[Japanese miniaturization culture]]\n* [[Kofi Annan|visitation of Kofi Annan]]\n\n== External Links ==\n\n=== Official ===\n\n* [http://www.kantei.go.jp/foreign/index-e.html Kantei.go.jp] - Official prime ministerial and cabinet site\n* [http://www.sangiin.go.jp/eng/index.htm Sangi-in.go.jp] - Official site of the House of Councillors\n* [http://www.shugiin.go.jp/index.nsf/html/index_e.htm Shugi-in.go.jp] - Official site of the House of Representatives\n* [http://www.courts.go.jp/english/ehome.htm Courts.go.jp] - Official site of the Japanese Supreme Court\n* [http://www.kunaicho.go.jp/eindex.html Kunaicho.go.jp] - Official site of the Imperial family.\n\n=== Other ===\n\n* [http://www.cia.gov/cia/publications/factbook/geos/ja.html CIA World Factbook -- Japan ]\n* [http://home.kyodo.co.jp/ Kyodo Japan News Wire Service]\n* [http://www.japantoday.com/ Japan Today - Japan news and information portal]\n* [http://newslink.org/nonusajap.html AJR Newslink] - Database of English newspapers in Japan\n* [http://www.thejapanfaq.com/ The Japan FAQ: Know Before You Go]\n* [http://www.businessweek.com/chapter/katz.htm Business Week - Japan: The System That Soured]\n* [http://www.stock-market-crash.net/nikkei.htm The Nikkei Stock Market Crash]\n* [http://www.mofa.go.jp/ Ministry of Foreign Affairs] - Detailed papers on Japan\'s foreign policy, education programs, culture and life.\n* [http://www.japan-zone.com/index.shtml Japan Zone] - Japan Travel Guide, Japanese Popular Culture, History and Japanese Etiquette\n* [http://www.rsf.fr/article.php3?id_article=4116 World-wide press freedom index] - Rank 26 out of 139 countries (3 way tie)\n* [http://www.dmoz.org/Regional/Asia/Japan/ Open Directory Project] - Directory of Japan\n* [http://www.lookjapan.com/ lookjapan.com] -- online magazine about Japan\n* [http://www.japaneselifestyle.com.au/ japaneselifestyle.com.au] -- online resource on Japanese culture and kimono\n* [http://www.generatemusic.com/japan/ Japan for Dummies] Pictures of everyday life in Japan\n* [http://www3.tky.3web.ne.jp/~edjacob/saq.html Japan SAQ (Seldom Asked Questions)]\n* [http://www.androphile.org/preview/Culture/Japan/japan.htm The Beautiful Way of the Samurai] History of Male Love in Japan\n* [http://www.jpop.com/ J-Pop.com] A portal into Japanese pop culture\n* [http://homepage3.nifty.com/kadzuwo/triviana/links_japan_trivia.htm Link of Links on Japan Trivia] (multilingual)\n* [http://wikitravel.org/en/article/Japan Japan travel guide at Wikitravel]\n* [http://www.gotjapan.com/ GotJapan.com] A guide to Traveling, Living, Working, Studying Japanese\n\n{{East_Asia}}\n{{OECD}}\n\n[[Category:Monarchies]]\n\n----\n\n\'\'\'[[Japan (band)|Japan]]\'\'\' is also the name of a band.\n\n[[Category:East Asian countries]] [[Category:Japan]]\n[[af:Japan]]\n[[ar:يابان]]\n[[ca:Japó]]\n[[chr:ᏂᎰᏂ]]\n[[cs:Japonsko]]\n[[da:Japan]]\n[[de:Japan]]\n[[el:Ιαπωνία]]\n[[eo:Japanio]]\n[[es:Japón]]\n[[fi:Japani]]\n[[fr:Japon]]\n[[ga:An tSeapáin]]\n[[he:יפן]]\n[[hu:Japán]]\n[[it:Giappone]]\n[[ja:日本]]\n[[ko:일본]]\n[[la:Iaponia]]\n[[lt:Japonija]]\n[[ms:Jepun]]\n[[nl:Japan]]\n[[no:Japan]]\n[[pl:Japonia]]\n[[pt:Japão]]\n[[ro:Japonia]]\n[[ru:Япония]]\n[[simple:Japan]]\n[[sl:Japonska]]\n[[sv:Japan]]\n[[tl:Hapon]]\n[[uk:Японія]]\n[[ur:نيہون]]\n[[zh-cn:日本/简]]\n[[zh-tw:日本/繁]]','',13,'Budhi','20040720113649','',0,0,0,0,0.542925420004,'20050316081936','79959279886350'); INSERT INTO cur VALUES (855,0,'Gifu_prefecture','[[Category:Chubu region]]\n\n\n\'\'\'Gifu prefecture\'\'\' (岐阜県 \'\'Gifu-ken\'\'), lokasi di [[Chubu]] [[list of regions in Japan|region]] bagian tengah [[Jepang]]. Ibukota Propinsina nyaeta Kota [[Gifu]]\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\'\'\'Gifu prefecture (岐阜県)\'\'\'
\n[[Image:PrefSymbol-Gifu.png|Gifu prefectural symbol]]
\nGifu prefectural symbol\n
[[Capital]][[Gifu]]
[[list of regions in Japan|Region]]:[[Chubu region|Chubu]]
[[Island]]:[[Honshu]]
[[Surface area|Area]]
\n - Total
\n - % water\n
[[List of Japanese prefectures ranked by area|Ranked 7th]]
\n10,598.18 [[square kilometer|km²]]
\n0.2%\n
[[Population]]
\n - Total ([[October 1|Oct. 1]], [[2000]])
\n - [[Density]]\n
[[List of Japanese prefectures by population|Ranked 18th]]
\n2,107,687
\n199/km²\n
[[District]]s:17
[[Municipality|Municipalities]]:99
[[ISO 3166-2:JP|ISO 3166-2]]:JP-21
Symbols
Pref. [[Flower]]:Chinese milk vetch
(Astragalus sinicus)
Pref. [[Tree]]:Japanese yew
(Taxus cuspidata)
Pref. [[Bird]]:Rock ptarmigan
(Lagopus mutus)
[[Image:Japan_gifu_map_small.png]]
\n\n== History ==\n\n== Geography ==\nIt is landlocked and is located [[north]] of [[Aichi Prefecture|Aichi]] in the mountains.\n\n=== Cities ===\n*[[Ena]]\n*[[Gero, Gifu|Gero]]\n*[[Gifu, Gifu|Gifu]] (capital)\n*[[Gujo, Gifu|Gujo]]\n*[[Hashima]]\n*[[Hida, Gifu|Hida]]\n*[[Kakamigahara]]\n*[[Kani]]\n*[[Mino, Gifu|Mino]]\n*[[Minokamo]]\n*[[Mizuho, Gifu|Mizuho]]\n*[[Mizunami]]\n*[[Motosu, Gifu|Motosu]]\n*[[Nakatsugawa]]\n*[[Ogaki]]\n*[[Seki]]\n*[[Tajimi]]\n*[[Takayama]]\n*[[Toki]]\n*[[Yamagata, Gifu|Yamagata]]\n\n===Towns and Villages===\n*[[Anpachi District, Gifu|Anpachi]]\n**[[Anpachi, Gifu|Anpachi]]\n**[[Goudo, Gifu|Goudo]]\n**[[Sunomata, Gifu|Sunomata]]\n**[[Wanouchi, Gifu|Wanouchi]]\n*[[Ena District, Gifu|Ena]]\n**[[Akechi, Gifu|Akechi]]\n**[[Fukuoka, Gifu|Fukuoka]]\n**[[Hirukawa, Gifu|Hirukawa]]\n**[[Iwamura, Gifu|Iwamura]]\n**[[Kamiyahagi, Gifu|Kamiyahagi]]\n**[[Kashimo, Gifu|Kashimo]]\n**[[Kawaue, Gifu|Kawaue]]\n**[[Kushihara, Gifu|Kushihara]]\n**[[Sakashita, Gifu|Sakashita]]\n**[[Tsukechi, Gifu|Tsukechi]]\n**[[Yamaoka, Gifu|Yamaoka]]\n*[[Fuwa District, Gifu|Fuwa]]\n**[[Sekigahara, Gifu|Sekigahara]]\n**[[Tarui, Gifu|Tarui]]\n*[[Hashima District, Gifu|Hashima]]\n**[[Ginan, Gifu|Ginan]]\n**[[Kasamatsu, Gifu|Kasamatsu]]\n**[[Kawashima, Gifu|Kawashima]]\n**[[Yanaizu, Gifu|Yanaizu]]\n*[[Ibi District, Gifu|Ibi]]\n**[[Fujihashi, Gifu|Fujihashi]]\n**[[Ibigawa, Gifu|Ibigawa]]\n**[[Ikeda, Gifu|Ikeda]]\n**[[Kasuga, Gifu|Kasuga]]\n**[[Kuze, Gifu|Kuze]]\n**[[Ono, Gifu|Ono]]\n**[[Sakauchi, Gifu|Sakauchi]]\n**[[Tanigumi, Gifu|Tanigumi]]\n*[[Kaizu District, Gifu|Kaizu]]\n**[[Hirata, Gifu|Hirata]]\n**[[Kaizu, Gifu|Kaizu]]\n**[[Nannou, Gifu|Nannou]]\n*[[Kamo District, Gifu|Kamo]]\n**[[Hichisou, Gifu|Hichisou]]\n**[[Higashishirakawa, Gifu|Higashishirakawa]]\n**[[Kawabe, Gifu|Kawabe]]\n**[[Sakahogi, Gifu|Sakahogi]]\n**[[Shirakawa, Gifu|Shirakawa]]\n**[[Tomika, Gifu|Tomika]]\n**[[Yaotsu, Gifu|Yaotsu]]\n*[[Kani District, Gifu|Kani]]\n**[[Kaneyama, Gifu|Kaneyama]]\n**[[Mitake, Gifu|Mitake]]\n*[[Motosu District, Gifu|Motosu]]\n**[[Kitagata, Gifu|Kitagata]]\n*[[Mugi District, Gifu|Mugi]]\n**[[Horado, Gifu|Horado]]\n**[[Itadori, Gifu|Itadori]]\n**[[Kaminoho, Gifu|Kaminoho]]\n**[[Mugegawa, Gifu|Mugegawa]]\n**[[Mugi, Gifu|Mugi]]\n*[[Ono District, Gifu|Ono]]\n**[[Asahi, Gifu|Asahi]]\n**[[Kiyomi, Gifu|Kiyomi]]\n**[[Kuguno, Gifu|Kuguno]]\n**[[Miya, Gifu|Miya]]\n**[[Nyukawa, Gifu|Nyukawa]]\n**[[Shirakawa, Gifu|Shirakawa]]\n**[[Shokawa, Gifu|Shokawa]]\n**[[Takane, Gifu|Takane]]\n*[[Toki District, Gifu|Toki]]\n**[[Kasahara, Gifu|Kasahara]]\n*[[Yoro District, Gifu|Yoro]]\n**[[Kamiishizu, Gifu|Kamiishizu]]\n**[[Yoro, Gifu|Yoro]]\n*[[Yoshiki District, Gifu|Yoshiki]]\n**[[Kamitakara, Gifu|Kamitakara]]\n**[[Kokufu, Gifu|Kokufu]]\n\n== Economy ==\n\n== Demographics ==\n\n== Culture ==\n\n== Tourism ==\n\n== Prefectural symbols ==\n\n== Miscellaneous topics ==\n\n== External links ==\n*[http://www.pref.gifu.jp/index_e.htm Official Gifu prefecture homepage]\n\n{{Japan}}\n\n[[de:Präfektur Gifu]]\n[[en:Gifu Prefecture]]\n[[eo:Gifu (prefektujo)]]\n[[es:Prefectura de Gifu]]\n[[fr:Préfecture de Gifu]]\n[[ja:岐阜県]]\n[[pt:Gifu]]\n[[zh:岐阜县]]','warnfile Adding:zh,en,eo,es,pt,de,fr',42,'Shizhao','20050303143830','',0,0,1,0,3.9749313e-05,'20050303143830','79949696856169'); INSERT INTO cur VALUES (856,0,'Gifu,_Gifu','[[de:Gifu]][[ja:岐阜市]]\n\n\'\'\'Gifu\'\'\' (岐阜市 \'\'Kota Gifu\'\') ngarupakeun [[cities of Japan|ibukota]] [[Propinsi Gifu ]] di [[Chubu region]] [[Jepang]] Tengah.\n\nDina taun [[2003]], [[populasi]] Kota Gifu diperkirakeun 404,428 jeung [[population density|density]] 2,072.71 urang per [[kilometer pasagi|km²]]. Total luasna 195.12 km².\n\nNgaran \'\'gifu\'\' dimimitian dina [[perioda Sengoku ]] ku [[Oda Nobunaga]], salah sahiji pamingpin di propinsi ayeuna [[Propinsi Aichi ]]; Ngaran heubeulna [[Mino]], manehna ngabogaan kahayang keur ngahijikeun Jepang. The name is after the name of a legendal [[mountain]], Mt. \'\'gi\'\' in ancient [[China]].\n\nThe city was founded on [[July 1]], [[1889]].\n\n== Tumbu kaluar ==\n* \'\'[http://www.city.gifu.gifu.jp/ Official website]\'\' dina basa Jepang','/* External links */',3,'Kandar','20040721091907','',0,0,0,0,0.682989301012,'20050208111611','79959278908092'); INSERT INTO cur VALUES (857,0,'Agrikultur','\'\'\'Agrikultur\'\'\' nyaéta prosés pikeun ngahasilkeun [[pangan]], parab, serat, jeung hasil-hasil séjén nu dipiharep tina budidaya sarupaning [[tutuwuhan]] jeung [[sato]] ingon-ingon. Agrikultur na istilah urang sarua jeung \'\'\'tatanén\'\'\'.\n\n== Ihtisar ==\n\nAgriculture includes both [[Subsistence farming|subsistence agriculture]], which is producing enough [[food]] to meet the needs of the [[farmer]] and family (but no more), and also (almost universally in the \"developed\" nations and increasingly so in other areas) the production of financial income from cultivation of the land or commercial raising of animals ([[animal husbandry]]). Agriculture is the \'\'practice\'\' -- the \'\'study\'\' of these disciplines is called [[Agricultural Science|agricultural science]].\n\nIncreasingly, besides food for humans and [[fodder|animal feeds]], agriculture produces goods such as cut flowers, ornamental and [[Nursery (horticulture)|nursery]] plants, [[fertilizer]]s, [[animal hides]], [[leather]], industrial chemicals ([[starch]], [[ethanol]], and [[plastic]]s), [[fiber]]s ([[cotton]], [[wool]], [[cannabis|hemp]], and [[flax]]), fuels ([[methane]], [[biodiesel]], [[biomass]]), and both legal and illegal [[drugs]] ([[biopharmaceutical]]s, [[tobacco]], [[marijuana]], [[opium]], [[cocaine]]). [[GMO|Genetically engineered]] plants and animals produce specialty drugs. \n\nIn the Western world, use of improved [[genetics]], better management of soil nutrients, and improved [[weed control]] have greatly increased yields per unit area. At the same time, use of mechanization has decreased labor requirements, releasing most of the populace from intense agricultural labor. The developing world is behind by Western measures of productivity, because of unavailability of the education, [[capital (economics)|capital]] and technology base needed to sustain these advances, and usually [[ecoregion]] with less optimal [[climate]]s and [[soil]]s.\n\nModern agriculture depends heavily on engineering and technology and on the biological and physical sciences. [[Irrigation]], [[drainage]], [[conservation]], and sanitary engineering—each of which is important in successful farming—are some of the fields requiring the specialized knowledge of agricultural engineers.\n\nAgricultural chemistry deals with other vital farming concerns, such as the application of fertilizer, insecticides (see [[Pest control]]), and fungicides, soil makeup, analysis of agricultural products, and nutritional needs of farm animals.\n\n[[Plant breeding]] and genetics contribute immeasurably to farm productivity. Genetics has also made a science of livestock breeding. Hydroponics, a method of soilless gardening in which plants are grown in chemical nutrient solutions, may help meet the need for greater food production as the world’s population increases.\n\nThe packing, processing, and marketing of agricultural products are closely related activities also influenced by science. Methods of quick-freezing and dehydration have increased the markets for farm products (see Food Processing and Preservation; Meat Packing Industry).\n\nMechanization, the outstanding characteristic of late 19th- and 20th-century agriculture, has eased much of the backbreaking toil of the farmer. More significantly, mechanization has enormously increased farm efficiency and productivity (see Agricultural Machinery). Animals including horses, oxen, llamas, alpacas, and dogs, however, are still used to cultivate fields, harvest crops, and transport farm products to markets in many parts of the world.\n\nAirplanes and helicopters are used in agriculture for seeding, spraying operations for insect and disease control, transporting perishable products, and fighting forest fires. Radio and television disseminate vital weather reports and other information such as market reports that concern farmers. Computers have become an essential tool for farm management.\n\nAnimal husbandry means breeding and raising animals for meat or to harvest animal products (like milk, eggs, or wool) on a continual basis.\n\nIn recent years, some aspects of industrial [[intensive agriculture]] have been the subject of increasing discussion. The widening sphere of influence held by large seed and chemical companies and meat packers has been a source of concern both within the farming community and for the general public. The patent protection given to companies that develop new types of [[seed]] using [[genetic engineering]] has allowed seed to be licensed to farmers in much the same way that computer software is licensed to users. This has changed the balance of power in favor of the seed companies, allowing them to dictate terms and conditions previously unheard of. Some argue these companies are guilty of [[biopiracy]].\n\n[[Soil]] [[conservation]] and nutrient management have been important concerns since the [[1950s]], with the best farmers taking a [[stewardship]] role with the land they operate.\n\nIncreasing consumer awareness of agricultural issues has led to the rise of [[community-supported agriculture]], [[local food movement]], [[slow food]], and commercial [[organic farming]], though these yet remain fledgling industries.\n\n== Sajarah ==\n\nNangtukeun asal-usul tatanén bisa disebut hésé sabab geus aya méméh budaya [[tulisan]]. Sababaraha ahli keukeuh nyebutkeun yén tatanén geus aya leuwih ti 10000 taun katukang, sedengkeun nu séjén yakin yén pepelakan nu sistimatis pangheubeulna teu leuwih ti 7000 taun katukang. Prakprakan tatanén mindeng dipaké pikeun ngabédakeun jaman [[néolitik]] ti [[jaman batu]] nu saméméhna. Palawija nu munggaran dibudidayakeun ku manusa di antarana [[gandum]] ([[einkorn]] jeung [[emmer]]) sarta [[barley]]. It is clear that farming was invented at least twice, probably more often: once in the [[Fertile Crescent]] during the [[Natufian culture]], and the following [[Pre-Pottery Neolithic A]] and B periods, once in East Asia (wheat and millet), and in [[Mesoamerica|Central America]] (maize). Most likely, there was a gradual transition from a [[hunter-gatherer]] economy to an agricultural one, via a lengthy period when some crops were deliberately planted, and other foods were gathered from the wild. The reasons for the earliest introduction of farming may have included [[climate]] change. Farming allows a much greater density of population than can be supported by hunting and gathering.\n\nAfter [[1492]], the world\'s agricultural patterns were shuffled in the widespread exchange of plants and animals known as the [[Columbian Exchange]]. Crops and animals that were previously only known in the Old World were now transplanted in the New, and vice versa.\n\n== Kawijakan ==\n\n[[Kawijakan tatanén]] mokuskeun kana tujuan jeung cara produksi tatanén. Dina tingkat kawijakan, tujuna umum tatanén di antarana:\n\n*[[Kasakit alatan dahareun|Kasalametan dahareun]]: Mastikeun sangkan asupan dahareun bébas tina kontaminasi.\n*[[Kaamanan dahareun]]: Mastikeun sangkan asupan dahareun saluyu jeung pangabutuh masarakat.\n*[[Kualitas dahareun]]: Mastikeun sangkan asupan dahareun mibanda kualitas nu tetep tur bisa kaukur.\n\n* Konservasi\n* \'\'Environmental impact\'\'\n* Stabiliti ékonomi\n\n== Métode ==\n*[[Hidroponik]]\n*[[Tillage]] by [[plough]]\n*[[Irigasi]] \n*[[Pupuk]] \n*[[Crop rotation]]\n*[[Weed control]]\n*[[Domestikasi]]\n*[[Agricultural fencing|Fencing]]\n*[[Ranching]]\n*[[Tatanén organik]]\n\n== Crops ==\n===World production of major crops in 2002===\n\nIn millions of metric tons, based on [[USDA]] estimates:\n\n:[[Maize]] 624\n:[[Wheat]] 570\n:[[Rice]] 381.1\n:[[Cotton]] 96.5\n\n\'\'Paddy rice\'\' is rice in its as-harvested state. \'\'Milled rice\'\' is rice after it is processed to remove the husk and, sometimes, polish the kernel. [[California]] is the major [[United States|US]] producer of rice.\n\n=== Crop improvement ===\n\n[[Image:Cropscientist.jpg|right|thumbnail|An agriculural scientist records corn growth]]\nDomestication of plants is done in order to increase yield, disease resistance, drought tolerance, ease of harvest, and to improve the taste and [[nutrition]]al value and many other characteristics. Centuries of careful selection and breeding have had enormous effects on the characteristics of crop plants. Plant breeders use greenhouses and other techniques to get as many as three generations of plants per year, so that they can make improvements all the more quickly. Extensive radiation mutagenesis efforts (i.e. primitive genetic engineering) during the [[1950s]] produced the modern commercial varieties of grains such as wheat, corn and barley.\n\nFor example, average yields of corn ([[maize]]) in the USA have increased from around 2.5 tons per hectare (40 bushels per acre) in [[1900]] to about 9.4 t/ha (150 bushels per acre) in [[2001]], primarily due to improvements in genetics. Similarly, worldwide average wheat yields have increased from less than 1 t/ha in [[1900]] to more than 2.5 t/ha in [[1990]]. [[South America]]n average wheat yields are around 2 t/ha, [[Africa]]n under 1 t/ha, [[Egypt]] and Arabia up to 3.5 to 4 t/ha with irrigation. In contrast, the average wheat yield in countries such as [[France]] is over 8 t/ha. Higher yields are due to improvements in genetics, as well as use of intensive farming techniques (use of fertilizers, chemical [[pest control]], growth control to avoid lodging).\n\n[Conversion note: 1 bushel (q) of wheat = 60 pounds (lb) ≈ 27.215 kg. 1 bushel of corn = 56 pounds ≈ 25.401 kg]\n\nVery recently, [[genetic engineering]] has begun to be employed in some parts of the world to speed up the selection and breeding process. The most widely used modification is a herbicide resistance gene that allows plants to tolerate exposure to glyphosate. A less frequently used but more controversial modification causes the plant to produce a toxin to reduce damage from insects (c.f. [[Starlink]]).\n\nThere are specialty producers who raise less common types of livestock or plants.\n\n[[Aquaculture]], the farming of [[fish]], [[shrimp]], and [[algae]], is closely associated with agriculture.\n\n[[Beekeeping|Apiculture]], the culture of bees, traditionally for [[honey]], increasingly for crop [[pollination]].\n\n\'\'See also\'\' : [[botany]], [[List of domesticated plants]], [[List of vegetables]], [[List of herbs]], [[List of fruit]], [[List of domesticated animals]]\n\n== Masalah lingkungan ==\n* Surplus [[nitrogén]] di [[walungan]] jeung [[situ]].\n* Pangaruh ngaruksak [[hérbisida]], [[fungisida]], [[insektisida]], jeung [[biosida]] séjénna.\n* Konversi sagala rupa [[ékosistem]] alami into arable land.\n* [[Érosi]]\n* [[Weeds - Feral Plants and Animals]]\n\n==Tempo ogé==\n\n* [[Agricultural and Food Research Council]]\n* [[Agricultural science]]\n* [[Agricultural sciences basic topics]]\n* [[Arid-zone agriculture]]\n* [[Community-supported agriculture]]\n* [[International agricultural research]]\n* [[List of farm implements]]\n* [[List of subsistence techniques]]\n* [[List of sustainable agriculture topics]]\n* [[Timeline of agriculture and food technology]].\n* [[USA agriculture]]\n\n==Tumbu kaluar==\n* [http://www.nationalpak.com Agriculture of Pakistan, All Agricultural Information]\n* [http://www.fao.org FAO of The UN\'s World Agricultural Information Centre]\n* [http://www.fao.org/waicent/portal/statistics_en.asp FAO of The UN Statistical Databases]\n* [[U.S. Department of Agriculture]]\'s [[Foreign Agricultural Service]] : [http://www.fas.usda.gov/currwmt.html Current World Production, Market and Trade Reports]\n* [[U.S. Department of Agriculture]]\'s [[Agricultural Research Service]] : [http://www.ars.usda.gov/ USDA\'s In-house Research Arm]\n* [[U.S. Department of Agriculture]]\'s [[National Agricultural Library]] : [http://www.nal.usda.gov/ Portal to USDA\'s National Agricultural Library]\n* [http://www.nationalacademies.org/agriculture/ Agriculture] at the [[United States National Academies]]\n* [http://www.dmoz.org/Science/Environment/Agriculture/ Agriculture Directory]\n\n[[ast:Agricultura]]\n[[bg:Земеделие]]\n[[ca:Agricultura]]\n[[cs:Zemědělství]]\n[[cy:Amaeth]]\n[[da:Landbrug]]\n[[de:Landwirtschaft]]\n[[en:Agriculture]]\n[[eo:Agrikulturo]]\n[[es:Agricultura]]\n[[fa:کشاورزی]]\n[[fi:Maataloustiede]]\n[[fr:Agriculture]]\n[[fy:Lânbou]]\n[[gl:Agricultura]]\n[[it:Agricoltura]]\n[[ja:農業]]\n[[ko:농업]]\n[[nah:Millacayotl]]\n[[nds:Landwertschap]]\n[[nl:Landbouw]]\n[[no:Landbruk]]\n[[pl:Rolnictwo]]\n[[pt:Agricultura]]\n[[ro:Agricultură]]\n[[simple:Agriculture]]\n[[sl:Kmetijstvo]]\n[[sv:Jordbruk]]\n[[ta:விவசாயம்]]\n[[tl:Agrikultura]]\n[[uk:Сільське господарство]]\n[[zh:农业]]','HasharBot - warnfile Adding:tl,ast,zh,uk,sl,sv,fa,ca Modifying:zh-cn,zh-tw,nah',0,'81.220.107.14','20041110061351','',0,0,0,0,0.780172571903,'20041201075450','79958889938648'); INSERT INTO cur VALUES (858,0,'Rékayasa_software','\n\n[[Software engineering]] (SE) nyaeta [[profession]] nu mokuskeun kana nyieun sarta ngarawat aplikasi [[Computer software|software]] ngagunakeun [[computer science]], [[project management]], [[domain knowledge]], [[common sense]] sarta kamampu jeung teknologi sejen.\n\n[[List of software engineering topics#Applications|Software applications]] (kaasup [[automatic teller machine|ATMs]], [[compiler]]s, [[database]]s, [[email]], [[embedded system]]s, [[graphics]], [[office applications suite|office suites]], [[operating system]]s, [[robotics]], [[video game]]s, sarta [[world wide web]]) kaasup oge [[value]] ekonomi jeung sosial, ngajadikeun masyarakat leuwih produktif, ningkatkeun kualitas hirup, sarta ngamungkinkeun hal-hal anu teu mungkin dipigawe.\n\n[[List of software engineering topics#Technologies and practices|SE technologies and practices]] (kaasup [[database]]s, [[Programming language|languages]], [[Library (software)|libraries]], [[Design pattern (computer science)|patterns]], [[System platform|platform]]s, [[software development process|processes]], [[Standards (software)|standards]], jeung [[Programming tool|tools]]) ngabantu \"pengembang\", ku ningkatkeun [[productivity]] jeung [[quality]].\n\n[[software engineering demographics|SE community]] kaasup 630,000 praktisi jeung pendidik di [[United States|U.S.]] sarta kira-kira 1,400,000 praktisi di [[European Union|E.U.]], [[Asia]], jeung tempat sejenna; jeung kira-kira 60% dina rekayasa tradisional. [[List of software engineering topics#Notable pioneers|American SE pioneers]] kaasup [[Kent Beck]], [[Barry Boehm]], [[Fred Brooks]], [[Watts Humphrey]], jeung [[David Parnas]].\n\nThere is considerable [[#Debates|debate]] over whether software development should be considered a branch of [[engineering|traditional engineering]], a branch of [[computer science]], an independent scientific field, or a non-scientific craft. This article attempts to be neutral on this issue, but errs on the side of being independent to clarify the differences between fields.\n\nAs of [[2004]], in common parlance the term \'\'software engineering\'\' is used with at least three distinct meanings:\n*As the usual contemporary term for the broad range of activities that was formerly called \'\'programming\'\' or \'\'systems analysis;\'\'\n*As the broad term for the technical analysis of all aspects of the \'\'practice,\'\' as opposed to the \'\'theory\'\' of computer programming;\n*As the term embodying the \'\'advocacy\'\' of a specific approach to computer programming, one that urges that it be treated as an engineering profession rather than an art or a craft, and advocates the codification of recommended practices in the form of \'\'[[Methodology (software engineering)|software engineering methodologies]].\'\'\n\n== Software Engineering matters ==\n\nIn the U.S., software drove about 1/4 of all [[Economics | increase in GDP]] during the [[1990s]] (about $90 billion per year), and 1/6 of all productivity growth (efficiency within GDP) during the late 1990s (about $33 billion per year). Software engineering drove $1 trillion of economic and productivity growth over the last decade. See also [[software engineering economics]].\n\nSoftware engineering changes world [[Society|culture]], wherever people use computers. Email, the world-wide web, and instant messaging enable people to interact in new ways. Software lowers the cost and improves the quality of health-care, fire departments, and other important social services.\n\nSuccessful projects where software engineering methods have been applied include [[Linux]], the [[space shuttle]] software, and [[automatic teller machine]]s. When it is cheaper to run a business or agency with software applications than without, businesses and agencies often invest in [[computers]], [[software]], and [[personnel]].\n\n== Education ==\n\nPeople from many different educational backgrounds make important contributions to SE. The fraction of practitioners who earn computer science or software engineering degrees has been slowly rising. Today about 1/2 of all software engineers earn computer science or software engineering degrees. For comparison, about 3/4 of all traditional engineers earn engineering degrees. \n\n\'\'Software:\'\' About half of all practitioners today have [[computer science]] [[degree]]s, which are the most relevant degrees that are widely available. A small, but growing, number of practitioners have software engineering degrees. Today in the U.S., about 2,000 universities offer computer science degrees and about 50 universities offer software engineering degrees. Most SE practitioners will earn computer science degrees for decades to come, though someday, this may change.\n\n\'\'Domain:\'\' Some practitioners have degrees in application domains, bringing important domain knowledge and experience to projects. In MIS, some practitioners have business degrees. In embedded systems, some practitioners have electrical or computer engineering degrees, because embedded software often requires a detailed understanding of hardware. In medical software, some practitioners have [[medical informatics]] degrees, or general medical or biology degrees.\n\n\'\'Other:\'\' Some practitioners have [[mathematics]], [[science]], [[engineering]], or other technical degrees. Some have [[philosophy]], or other non-technical degrees. And, some have no degrees. Note that [[Barry Boehm]] earned degrees in mathematics and [[Edsger Dijkstra]] earned degrees in physics.\n\nGraduate software engineering degrees have been available from dozens of universities for a decade or so. Undergraduate software engineering degrees are being established at many universities. A new curriculum for undergraduate software engineering degrees is currently being defined by the [[CCSE]].\n\n== Practice ==\n\nPractitioners specialize in many roles in industry ([[analyst]]s, [[Software developer|developer]]s, [[Software testing|tester]]s, [[technical support]], [[manager]]s) and academia ([[educator]]s, [[researcher]]s).\n\nMost software engineers work as employees or contractors. Software engineers work with businesses, government agencies (civilian or military), and non-profit agencies (a school or .org like [[Wikipedia]]). Some software engineers work for themselves as [[free agent]]s.\n\nThere is considerable debate over the future employment prospects for Software Engineers and other IT Professionals. For example, an online futures market called the [http://www.ideosphere.com/fx-bin/Claim?claim=ITJOBS Future of IT Jobs in America] attempts to answer the question as to whether there will be more IT jobs, including software engineers, in 2012 than there were in 2002.\n\n== Debates ==\n\nMany debates are raging within SE. As software becomes more pervasive, we all recognize the need for better [[software]], but we disagree on how.\n\n\'\'Technologies and Practices:\'\' What is the best way to make more and better software? SEs advocate many different technologies and practices, with much disagreement. This debate has gone on for 60 years and may continue forever.\n\n\'\'Identity:\'\' Is SE a branch of computer science, a branch of traditional engineering, or a field that stands on its own? Recently, software engineering has been finding its own identity and emerging as an important field. Yet, some advocate making SE a part of traditional engineering and others advocate keeping SE a part of computer science.\n\n\'\'Professionalism:\'\' What will SEs do about professionalism, licensing, and ethics? Licensing is a polarizing issue. Some fiercely advocate it. Others staunchly oppose it.\n\n\'\'Success:\'\' Is SE a success or a failure? Some look to the enormous economic growth and productivity gains enabled by software and claim that software engineering is a huge success. Others point to the ongoing problems with crashing operating systems and computer viruses and claim that software engineering has failed. How can we reconcile these points of view?\n\nFor more details see [[Debates within software engineering]].\n\n== Current directions for software engineering ==\n\nAspect-oriented programming and agile methods are important emerging SE [[technology|technologies]] and [[practice]]s.\n\n[[Aspect-oriented programming|Aspects]] help programmers deal with \'\'[[ilities]]\'\' by providing tools to add or remove [[boilerplate]] code from many areas in the source code. Aspects describe how all objects or functions should behave in particular circumstances. For example, [[aspect (computer science)|aspect]]s can add [[debugging]], [[logging]], or [[Lock (software engineering)|locking]] control\ninto all objects of particular types. Researchers are currently working to understand how to use aspects to design general-purpose code. Related concepts include [[generative programming]] and [[Template (programming)|templates]].\n\n[[Agile Methods]] guide [[software development]] projects that evolve rapidly with changing [[expectations]] and competitive markets. The heavy, document-driven [[process]]es (like [[CMM]] and [[ISO 9000]]) are fading in [[importance]]. Some people believe that companies and agencies export many of the jobs that can be guided by heavy-weight processes. Related concepts include [[extreme programming]] and [[Lean manufacturing|lean software development]].\n\nThe \'\'[http://www.softwaresystems.org/future.html Future of Software Engineering]\'\' conference (FOSE) held at the ICSE 2000 documented the state of the art of SE in 2000 and listed many problems to be solved over the next decade. The [http://www.dreamsongs.com/Feyerabend/Feyerabend.html Feyerabend project] attempts to discover the future of software engineering by seeking and publishing innovative ideas.\n\nConferences dedicated to inform undergraduate students like the annual \'\'[http://www.cusec.ca Canadian University Software Engineering Conference]\'\' (CUSEC) are also very promissing for the future generation. It is completely organized by undergraduate students and let different Canadian Universities interrested in Software Engineering to host the conference each year. Past guests includes [[Kent Beck]], [[Joel Spolsky]], [[Philippe Kruchten]], [[Hal Helms]], [[Craig Larman]] as well as university professors and students.\n\n== Related articles ==\n* [[History of software engineering]]\n* [[Criticism of software engineering]]\n* [[Debates within software engineering]]\n* [[Comparing software engineering and related fields]]\n* [[List of software engineering topics]]\n* [[List of important publications in computer science#software engineering| Important publications in software engineering]]\n* [[:Category:Software engineering|Wikipedia articles on software engineering]]\n\n[[Category:Software engineering]]\n\n[[ar:هندسة برمجيات]]\n[[de:Softwaretechnik]]\n[[es:Ingeniería de software]]\n[[he:הנדסת תוכנה]]\n[[lt:Programų inžinerija]]\n[[nl:Software engineering]]\n[[ja:ソフトウェア工学]]\n[[pt:Engenharia de software]]\n[[fi:Ohjelmistotuotanto]]\n[[th:วิศวกรรมซอฟต์แวร์]]\n[[zh-cn:软件工程]]','',13,'Budhi','20040817080428','',0,0,0,0,0.855032059762,'20041225124916','79959182919571'); INSERT INTO cur VALUES (859,0,'Basa_Latin','{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" style=\"margin: 0 0 0.5em 1em;\"\n!colspan=\"2\" bgcolor=\"lawngreen\"|\'\'\'Basa Latin\'\'\' (\'\'latina\'\')\n|-\n|Dipaké di\n|[[Karajaan Romawi]]\n|-\n|Wewengkon\n|Bojong Itali\n|-\n|Pamaké\n| -\n|-\n|Dialék\n| -\n|-\n|valign=\"top\"|[[Famili basa jeung basa|Genetik]]
[[Famili basa jeung basa|klasifikasi]]\n|[[Basa Indo-Éropa|Indo-Éropa]]
\n [[Basa Italik|Italik]]
\n  \'\'\'Latin\'\'\'\n|-\n!colspan=\"2\" bgcolor=\"lawngreen\"|Status resmi\n|-\n|[[Basa resmi]]\n|valign=\"top\"|[[Kota Vatican]]\n|-\n|Regulated by\n|none\n|-\n!colspan=\"2\" bgcolor=\"lawngreen\"|Sandi basa\n|-\n|[[ISO 639]]-1\n|la\n|-\n|ISO 639-2\n|lat\n|-\n|[[SIL]]\n|LTN\n|}\n\'\'\'Basa Latin\'\'\' atawa \'\'\'Latén\'\'\' baheulana ngarupakeun [[basa]] asli nu dipaké di wewengkon sabudeureun [[Roma]] nu disebut [[Latium]]. Boga pangaruh badag nalika jadi basa formal [[Karajaan Romawi]].\n\nSadaya [[Basa Romawi]] diturunkeun tina basa Latin, sarta loba kekecapan nu asalna tina kecap Latin kapanggih ogé dina basa-basa modern séjénna kayaning [[basa Inggris]]. Leuwih ti éta, di dunya Kulon, basa Latin geus jadi \'\'[[lingua franca]]\'\', basa nu diteuleuman sarta dilarapkeun pikeun kaperluan ilmiah sarta pulitik, salila leuwih ti sarébu taun, nu kalindih ku [[basa Prancis]] dina [[abad ka-18]] sarta basa Inggris ahir [[abad ka-19]]. Kiwari jadi [[Latin (Ecclesiastical)|basa resmi]] [[Garéja Katolik Roma]], kaasup salaku basa resmi nasional [[Kota Vatikan]]. Basa Latin ogé masih dipaké, bareng jeung [[basa Yunani]], pikeun nangtukeun ngaran nu dipaké dina [[klasifikasi ilmiah]] mahluk hirup.\n\n==Main features==\n\nLatin has an extensive flectional system, which mainly operates by appending strings to a fixed stem. Inflection of nouns and adjectives is termed \"[[declension]]\", that of verbs, \"[[Grammatical conjugation|conjugation]]\". There are five declensions of nouns, and four conjugations for verbs. The six noun forms (or \"cases\") are:\n#[[nominative case|nominative]] (subjects and predicate nominatives), \n#[[genitive case |genitive]] (relation, often possession), \n#[[dative case|dative]] (indirect objects), \n#[[accusative case|accusative]] (direct objects, some prepositional phrases), \n#[[ablative case|ablative]] (separation, source, cause, or instrument),\n#[[vocative case|vocative]] (direct address). \n\nIn addition, there exists in some nouns a [[locative case|locative case]] used to express place (normally expressed by the ablative with a preposition such as IN), but this hold-over from Indo-European is only found in the names of lakes, cities, towns, similar locales, and a few other words.\n\n==Basa Latin jeung \'\'Romans\'\'==\n\nSaruntagna Karajaan Romawi, basa Latin robah jadi rupa-rupa [[basa Romans]]. These were for many centuries only spoken languages, Latin being still used for writing. (E.g. Latin was the official language of [[Portugal]] until [[1296]] when it was replaced by [[Portuguese language|Portuguese]].)\n\nActually the Romance languages are not derived from [[Classical Latin]] but rather from the spoken [[Vulgar Latin]]. Latin and Romance differ (for example) in that Romance had distinctive stress whereas Latin had distinctive length of vowels. In [[Italian language|Italian]] and [[Sardo logudorese]], there is distinctive length of consonants and stress, in [[Spanish language|Spanish]] only distinctive stress, and in [[French language|French]] even stress is no longer distinctive.\n\nAnother major distinction between Romance and Latin is that Romance languages, excluding Romanian, have lost their case endings in most words except for some pronouns. [[Romanian language|Romanian]] still has five cases (though the [[ablative case|ablative]] is no longer represented).\n\n==Basa Latin jeung basa Inggris==\n\nTatabasa Inggris teu sacara langsung diturunkeun tina tatabasa Latin. Attempts to make English grammar fit Latin rules — such as the contrived prohibition against the [[split infinitive]] — have not worked successfully in regular usage. However, as many as half the words in English come to us through Latin, including many words of Greek origin first adopted by the Romans, not to mention the thousands of French, Spanish, and Italian words of Latin origin that have also enriched English. \n\nNalika [[abad ka-16]] nepi ka [[abad ka-18]], panulis-panulis Inggris nyipta loba pisan kecap-kecap anyar nu diturunkeun tina akar kecap basa Latin jeung Yunani. Kecap-kecap ieu, euyeub ku rasa jeung harti. Loba kecap-kecapna nu kungsi dipaké terus kapopohokeun, tapi sabagian mah aya kénéh, kayaning \'\'imbibe\'\', \'\'extrapolate\'\', jeung \'\'inebriation\'\'.\n\n== Tempo ogé ==\n\n=== Ngeunaan basa Latin ===\n* [[Tatabasa Latin]]\n* [[Foném Latin]]\n* [[Latin declension]]\n* [[Konjugasi Latin]]\n* [[Léxikon Latin]]\n* [[ablative absolute]]\n* [[susunan aksara Latin]]\n\n===Ngeunaan sastra Latin===\n* [[Sastra Latin]]\n* [[Pabukon Klasik Loeb]]\n* [[Latin proverbs]]\n* [[Daptar frase Latin]]\n* [[Daptar Latin proverbs]]\n* [[Brocard]]\n* [[Daptar kecap-kecap Latin atawa Yunani nu ilahar dipaké dina ngaran sistimatis]]\n* [[Carmen Possum]]\n\n===Jejer séjén nu patali===\n* [[Kakaisaran Romawi]]\n* [[Latin Anyar]]\n\n==Tumbu kaluar==\n*\'\'\'[http://la.wikipedia.org/ Wikipédia Latin]\'\'\'\n\n* [http://www.perseus.tufts.edu/ The Perseus Project] has many useful pages for the study of classical languages and literatures, including [http://www.perseus.tufts.edu/cgi-bin/resolveform?lang=Latin an interactive Latin dictionary].\n*[http://www.ethnologue.com/show_language.asp?code=LTN Ethnologue report for Latin]\n*Free online courses in Latin\n**http://www.sprachprofi.de.vu/latin\n**http://wikibooks.org/wiki/Latin\n*[http://www.thelatinlibrary.com The Latin Library] contains many Latin etexts\n*[http://www.textkit.com Textkit] has Latin textbooks and etexts.\n*[http://www.websters-online-dictionary.org/definition/Latin-english/ Latin - English Dictionary]: from Webster\'s Rosetta Edition.\n* [http://www.language-reference.com Language reference] Cross-foreign-language lexicon powered by its own search engine. All cross combinations between Latin and French, German, Italian, Spanish.\n\n[[ca:Llatí]] [[da:Latin]] [[de:Latein]] [[en:Latin]] [[es:Latín]] [[eo:Latina lingvo]] [[cy:Lladin]]\n[[fr:Latin]] [[id:Latin]] [[la:Lingua Latina]] [[hu:Latin]] [[nds:Latinsch]] [[nl:Latijn]] [[ja:%E3%83%A9%E3%83%86%E3%83%B3%E8%AA%9E]] [[pl:%C5%81acina]] [[ro:Latină]] [[simple:Latin]] [[sl:latinščina]] [[sr:Латински језик]] [[sv:Latin]] [[zh:拉丁语]]\n\n[[Category:Basa geus lastari]]\n[[Category:Basa Itali]]\n[[Category:Romawi Kuna]]','',3,'Kandar','20050308065705','',0,0,0,0,0.137486231112,'20050308065705','79949691934294'); INSERT INTO cur VALUES (860,0,'Statistical_inference','Topik di handap ieu biasana kaasup kana \'\'\'interpretasi data statistik\'\'\'. Istilah anu leuwih formal keur topik ieu nyaeta \'\'\'statistical inference\'\'\'.\n#[[Statistical assumptions]]\n#[[Likelihood principle]]\n#[[Estimating parameters]]\n#[[Testing statistical hypotheses]]\n#[[Revising opinions in statistics]]\n\n:[[planning statistical research]] -- [[summarizing statistical data]]\n\nback to [[Statistik]]\n----\n\'\'\'Statistical inference\'\'\' nyaeta kaputusan ngeunaan hiji populasi tina \"pengambilan\" sampel sacara acak atawa, leuwih umum, ngeunaan proses acak tina hasil \"observasi\" dina periode waktu anu ditangtukeun. Di jerona kaasup:\n\n#[[titik estimasi]]\n#[[interval estimasi]]\n#[[hypothesis testing]] (or [[significance]] testing)\n#prediction\n\nAya sababaraha pamikirian anu beda ngeunaan \"justifikasi\" statistical inference. Didasarkeun kana sababaraha ide ngeunaan fenomena nyata leuwih kaharti lamun dimodelkeun sabage [[kamungkinan|probability]].\n#[[frequency probability]]\n#[[personal probability]]\n#[[Bayesian probability]]\n#[[pilihan probabiliti]]\n\nbalik ka [[Statistik]]','',13,'Budhi','20041226001855','',0,0,1,0,0.753388133251,'20041226001855','79958773998144'); INSERT INTO cur VALUES (861,0,'Populasi',':\'\'Keur ngalarapkeun kecap \'\'populasi\'\' dina statistik, tempo [[populasi statistik]].\'\'\n\nDina basa nu leuwih umum, \'\'\'populasi\'\'\' ngarupakeun kumpulan \"masarakat\" —atawa [[organisme]] [[spésiés]] tinangtu—nu hirup di hiji rohangan [[géografi|géografis]]. \n\nPopulasi diulik ku rupa-rupa cara jeung disiplin. Dina [[dinamika populasi]], struktur ukuran, umur, jeung jenis kelamin, mortality, paripolah reproduktif, sarta \'\'pertumbuhan\'\' hiji populasi diulik. \'\'\'[[Démografi]]\'\'\' ngarupakeun ulikan dinamika populasi [[manusa]]. Aspék séjén diulikna dina [[sosiologi]], [[ékonomi]], jeung [[géografi]]. Populasi tutuwuhan jeung sasatoan diulikna dina [[biologi]], hususna dina cabang [[ékologi]] nu katelah [[biologi populasi]] sarta na [[genetik populasi]]. In biology, a \'\'population\'\' denotes a breeding group whose members breed mostly or solely among themselves, usually as a result of physical isolation, although biologically they could breed with any members of the [[species]]. \n\n\'\'\'[[Population density]]\'\'\' is a measure of the number of people or organisms per unit of area. Variants may express the population per unit of habitable, inhabited, productive (or potentially productive), or cultivated area. A particular geographic area of [[land]] is said to have a [[carrying capacity]], representing the maximum population which it can support. Some observers of human societies believe that the concept of carrying capacity also applies to human population, and that unchecked population growth can result in a \"[[Malthusian catastrophe]]\". Others dispute this view.\n---- \n\'\'\'Population\'\'\' may also mean the \'\'process\'\' of populating a [[geography|geographic]] area, as by procreation or immigration.\n\n== Tempo ogé ==\n* [[Biological dispersal]]\n\n==Tumbu kaluar==\n* Department of Economic and Social Affairs, [http://www.un.org/esa/population/ Population Division]. [[United Nations]].\n* \"\'\'[http://www.populationworld.com/ Populasi Dunya]\'\'\". PopulationWorld.com.\n\n[[Category:Ékologi]]\n\n[[bg:Население]] [[de:Einwohnerzahl]] [[el:Πληθυσμός]] [[en:Population]] [[es:Población]] [[fr:Population]] [[hu:Popul%C3%A1ci%C3%B3]] [[it:Popolazione]] [[ja:人口]] [[nl:Bevolking]] [[pl:Populacja]] [[pt:População]] [[ru:Население]] [[simple:Population]] [[sv:Befolkning]] [[zh:人口]]','',13,'Budhi','20040908023657','',0,0,0,0,0.53652775918,'20041016135004','79959091976342'); INSERT INTO cur VALUES (862,0,'Otomotif','[[Image:Automobiles.jpg|300px|thumb|right|Automobiles, or \"Cars\".]]\n\n\'\'\'Otomobil\'\'\', biasana disebut \'\'\'mobil\'\'\' atawa \'\'\'[[treuk]]\'\'\', ngarupakeun [[wheel]]ed [[vehicle]] nu mawa [[mesin]]na sorangan. Older terms include \'\'\'horseless carriage\'\'\' and \'\'\'motor car\'\'\', with \"motor\" referring to what is now usually called the engine. It has seats for the [[driving|driver]] and, almost without exception, for at least one passenger.\n\n== Umum ==\n\nAutomobiles are designed to [[travel]] on [[road]]s, although some, notably [[sport utility vehicle]]s, allow [[off-road]] driving. Roads and [[highway]]s are shared with other [[traffic]] such as [[motorcycle]]s, [[tractor trailer]]s, and [[farm]] implements.\n\nThe typical vehicle has an [[internal combustion engine]], although in [[2001]], [[hybrid car]]s powered by [[gas-electric hybrid engine]]s began to enter the market. Other vehicles run on [[electricity]] and [[fuel cell]]s, though these are not widely available [[as of 2004]]. While most cars have four wheels, three-wheeled automobiles have also been built, but are not common due to stability problems. Some [[gyrocar]], two wheeled automobiles have been built as well, using gyroscopic stabilization.\n\nThere are many [[car classification|classes]] of car and [[car body style]]s.\n\n== Sajarah ==\n\nThe first vehicles were [[steam engine]] powered, then [[electric vehicle]]s were produced by a small number of manufacturers. Later on [[gasoline]] and [[diesel engine]]s were implemented.\n\nSteam-powered self propelled vehicles were devised in the late [[18th century]]. [[Nicolas-Joseph Cugnot]] successfully demonstrated such a vehicle as early as [[1769]]. \n\n===Popularity===\nCugnot\'s invention initially saw little application in his native [[France]], and the center of innovation passed to [[Britain]], where [[Richard Trevithick]] was running a steam-carriage in [[1801]]. Such vehicles were vogue for a time, and over the next decades such innovations as hand brakes, multi-speed transmissions, and improved speed and [[steering]] were developed. Some were commercially successful in providing [[mass transit]], until a backlash against these large speedy vehicles resulted in passing laws that self-propelled vehicles on public roads in Britain must be proceeded by a man on foot waving a red flag and blowing a horn. This effectively killed road auto development in the UK for most of the rest of the [[19th century]], as inventors and engineers shifted their efforts to improvements in [[railway]] [[locomotive]]s. The red flag law was not repealed until [[1896]].\n\nThe many varieties of [[automobile racing]] collectively constitute one of the most popular categories of sport in the world.\n\n===Innovation===\n[[Image:Oldtimer-Dashboard.jpg|300px|thumb|right|The [[dashboard]] of an [[Oldtimer]] from the early [[20th century]].]]\nIt is generally claimed that the first automobiles with gasoline powered [[internal combustion engine]]s were completed almost simultaneously in [[1886]] by [[Germany|German]] inventors working independently: [[Carl Benz]] on 3 July 1886 in [[Mannheim]], resp. [[Gottlieb Daimler]] and [[Wilhelm Maybach]] in [[Stuttgart]] (also inventors of the first motor bike). A major breakthrough came with the historic drive of [[Berta Benz]] in 1888. Steam, electric, and gasoline powered autos competed for decades, with gasoline internal combustion engines achieving dominence in the [[1910s]].\n\nThe first automobile [[patent]] in the [[United States]] was granted to [[Oliver Evans]] in [[1789]]; in [[1804]] Evens demonstrated his first successful self-propelled vehicle, which not only was the first automobile in the USA but was also the first [[amphibious vehicle]], as his steam-powered vehicle was able to travel on [[wheel]]s on land and via a [[paddle wheel]] in the water. On [[November 5]], [[1895]], [[George B. Selden]] was granted a United States patent for a [[two-stroke cycle|two-stroke]] automobile engine. This patent did more to hinder than encourage development of autos in the USA until it was overturned on a challenge by [[Henry Ford]].\n\nThe large scale, production-line manufacturing of affordable automobiles was debuted by [[Oldsmobile]] in [[1902]], then greatly expanded by [[Henry Ford]] in the 1910s. Early automobiles were often referred to as \'horseless carriages\', and did not stray far from the design of their predecessor. Through the period from 1900 to the mid [[1920s]], development of automotive technology was rapid, due in part to a huge (hundreds) number of small manufacturers all competing to gain the world\'s attention. Key developments included electric [[ignition system|ignition]] and the electric self-starter (both by Charles Kettering, for the [[Cadillac automobile|Cadillac]] Motor Company in 1910-1911), independent suspension, and four-wheel brakes.\n\n[[Image:BMW530d-Dashboard.jpg|300px|thumb|right|The dashboard of a modern car, a [[BMW 5-Series|BMW 530d]] in [[2003]].]]\nBy the [[1930s]], most of the technology used in automobiles had been invented, although it was often re-invented again at a later date and credited to someone else. For example, [[front-wheel drive]] was re-introduced by Andre [[Citroën]] with the launch of the [[Traction Avant]] in [[1934]], though it appeared several years earlier in road cars made by Alvis and [[Cord Automobile|Cord]], and in racing cars by Miller (and may have appeared as early as [[1897]]). After 1930, the number of auto manufacturers declined sharply as the industry consolidated and matured. Since [[1960]], the number of manufacturers has remained virtually constant, and innovation slowed. For the most part, \"new\" automotive technology was a refinement on earlier work, though these refinements were sometimes so extensive as to render the original work nearly unrecognizable. The chief exception to this was electronic [[electronic control unit|engine management]], which entered into wide use in the [[1960s]], when electronic parts became cheap enough to be mass-produced and rugged enough to handle the harsh environment of an automobile. Developed by [[Robert Bosch GmbH|Bosch]], these electronic systems have enabled automobiles to drastically reduce exhaust emissions while increasing efficiency and power.\n\n===Regulation===\n\nIn almost every nation, laws have been enacted governing the operation of motor vehicles. Most of this legislation, including limits on allowable speed and other [[rules of the road]], are designed to ensure the smooth flow of [[traffic]] and simultaneously protect the safety of vehicle occupants, bicyclists, and pedestrians.\n\nIn [[1965]], in [[California]], legislation was introduced to regulate exhaust emissions, the first such legislation in the world. Answering this new interest in environmental and public safety issues, the [[Department of Transportation]] (DOT) and the [[Environmental Protection Agency]] (EPA) both introduced legislation in [[1968]] which substantially altered the course of automotive development. Since the US market was the largest in the world (and California the largest market in the US), manufacturers worldwide were forced to adapt. For the first time, safety devices were mandatory, as were controls on harmful emissions. Prior to this legislation, even seat belts were considered extra-cost options by many manufacturers. Other countries followed by introducing their own safety and environmental legislation. In time, meeting regulations became the main challenge for the engineers designing new cars. In the decade from [[1975]] to [[1985]], the world\'s manufacturers struggled to meet the new regulations, some producing substandard cars with reduced reliability as a result. However, by the end of this period, everyone had learned how to handle the newly regulated environment. The manufacturers discovered that safety and environmentalism sold cars, and some began introducing environmental and safety advances on their own initiative.\n\n===Environmental improvements===\n\nAmong the first environmental advances are the so-called alternative fuels for the internal combustion engine, which have been around for many years. Early in automotive history, before gasoline was widely available at corner pumps, cars ran on many fuels, including [[kerosene]] (paraffin) and coal gas. [[Alcohol as a fuel|Alcohol fuels]] were used in [[Auto racing|racing]] cars before and just after [[World War II]]. Today, [[methanol]] and [[ethanol]] are used as petrol extenders in some countries, notably in [[Australia]] and the [[United States]]. In countries with warmer climate, such as [[Brazil]], alcohol derived from [[sugar cane]] is often used as a substitute fuel.\n\nIn many countries, plentiful supplies of [[natural gas]] have seen [[methane]] sold as compressed natural gas (CNG) and [[propane]] sold as [[liquified petroleum gas]] (LPG) alongside petrol and diesel fuels since the [[1970s]]. While a standard automotive engine will run on these fuels with very low exhaust emissions, there are some performance differences, notably a loss of power due to the lower energy content of the alternative fuels. The need to equip filling stations and vehicles with pressurized vessels to hold these gaseous fuels and more stringent safety inspections means that they are only economical when used for a long distance or if there are installation incentives. They are most economical where petrol has high taxes and the alternative fuels do not.\n\n===Renewable energy and the future===\n\nWith heavy [[tax]]es on fuel, particularly in [[Europe]] and tightening environmental [[law]]s, particularly in [[California]] [[United States|USA]], and the possibility of further restrictions on [[greenhouse gas]] emissions, work on alternative power systems for vehicles continues. \n\n[[Diesel]]-powered cars can run with little or no modification on 100% pure [[biodiesel]], a fuel that can be made from [[vegetable oil]]s. Many cars that currently use gasoline can run on ethanol, a fuel made from plant sugars. Most cars that are designed to run on gasoline are capable of running with 15% ethanol mixed in, and with a small amout of redesign, gasoline-powered vehicles can run on ethanol concentrations as high as 85%. All petrol fueled cars can run on [[LPG]]. There has been some concern that the ethanol-gasoline mixtures prematurely wear down seals and gaskets.\n\nAttempts at building viable [[battery (electricity)|battery]]-powered electric vehicles continued throughout the [[1990s]] (notably [[General Motors]] with the [[EV1]]), but cost, speed and inadequate driving range made them uneconomical.\n\nCurrent research and development is centred on \"[[Hybrid electric vehicle|hybrid]]\" vehicles that use both electric and combustion (pollution) power, and longer-term efforts are based around electric vehicles powered by [[fuel cells]]. \n\nOther alternatives being explored involve methane and [[hydrogen car|hydrogen-burning vehicles]], fuel cells, and even the stored energy of compressed air (see [[Air Engine]]).\n\n==Safety==\n[[Car accident|Accidents]] seem as old as automobile vehicles themselves. [[Joseph Cugnot]] crashed his steam-powered \"Fardier\" against a wall in [[1770]]. The first recorded automobile fatality was [[Bridget Driscoll]] in [[August 17]], [[1896]] in [[London, England]]. \n\nEvery year more than a million people are killed and about 50 million people are wounded in traffic (according to [[World Health Organisation|WHO]] estimates), either by crashing into something, or by being crashed into. Major factors in accidents include driving under the influence of [[alcohol]] or other drugs, inattentive driving, overtired driving, road hazards such as snow, potholes and animals, and reckless driving. Special safety features have been built into cars for years, some for the safety of car\'s occupants only, some for the safety of others.\n\nThere are standard tests for safety in new automobiles, like the [[EuroNCAP]]. Despite these technological advances, the death toll of car accidents remains high: about 40,000 people die every year in the US, a number which increases annually in line with rising population and increased travel (although the rate per capita and per mile travelled decreases steadily), with similar trends in [[Europe]]. The death toll is expected to nearly double worldwide by [[2020]]. A much higher number of accidents result in injury or permanent [[disability]].\n\n===See also===\n*[[Car safety]]\n*[[Unsafe at Any Speed]] by [[Ralph Nader]]\n*[[Crash test dummy]]\n*[[How to Build]]\n\n==Major possible subsystems==\n\n*[[engine]]\n**[[carburetor]] or [[fuel injection]]\n**[[fuel pump]]\n**[[engine configuration]]: [[Wankel engine|Wankel]] or [[reciprocating engine|reciprocating]] ([[v engine|V]], [[inline engine|inline]], [[flat engine|flat]]).\n**[[electronic control unit|engine management system]]s\n**[[exhaust]] system\n**[[ignition system]]\n**[[Automobile self starter|self starter]]\n**[[Automobile emissions control|emissions control]] devices\n**[[turbo-charger]]s and [[supercharger]]s\n**[[front engine]]\n**[[rear engine]]\n**[[mid engine]]\n\n*drivetrain\n**[[transmission (automobile)|transmission]] ([[gearbox]])\n***[[manual transmission]]\n***[[semi-automatic transmission]]\n***[[fully-automatic transmission]]\n**Layout\n***[[FF layout]]\n***[[FR layout]]\n***[[MR layout]]\n***[[RR layout]]\n**Drive Wheels\n***[[2 wheel drive]]\n***[[4 wheel drive]]\n***[[Front wheel drive]]\n***[[Rear wheel drive]]\n***[[All wheel drive]]\n**[[differential (mechanics)|differential]]\n***[[limited slip differential]] \n**[[axle]]\n**[[Live axle]]\n\n*[[brake]]s\n**[[disc brake]]s\n**[[drum brake]]s\n**[[anti-lock braking system]]s (ABS)\n\n*[[wheel]]s and [[tire]]s\n**[[custom wheel]]s\n\n*[[steering]]\n**[[rack and pinion]]\n**[[Ackermann steering geometry]]\n**[[Castor angle]]\n**[[Camber angle]]\n**[[Kingpin]]\n\n*[[suspension (vehicle)|suspension]]\n**[[MacPherson strut]]\n**[[wishbone suspension|wishbone]]\n**[[double wishbone]]\n**[[multi-link suspension|multi-link]]\n**[[torsion beam suspension|torsion beam]]\n**[[semi-trailing arm suspension|semi-trailing arm]]\n**[[axle]]\n\n*body\n**[[crumple zone]]s\n**[[monocoque]] (or unibody) construction\n**[[suicide doors]]\n\n*interior equipment\n**passive safety\n***[[seat belt]]s\n***[[airbag]]s\n***[[child safety lock]]s\n**controls\n***[[dashboard]]\n**seats\n**ancillary equipment such as [[car audio|stereos]], [[air conditioning]], [[cruise control]], positioning systems, cup holders, etc.\n\n*exterior equipment\n**[[windshield]]\n\n==Related articles==\n\n*[[ambulance]]\n*[[armored car]]\n*[[carfree movement]]\n*[[crash]]\n*[[diesel cycle]]; [[four-stroke cycle]]; [[two-stroke cycle]]; [[Miller cycle]]; [[Atkinson Cycle]]\n*[[effects of the automobile on society]]\n*[[forklift]]\n*[[future of the car]]\n*[[flying car]]\n*[[High_occupancy_vehicle|High Occupancy Vehicle]] (HOV)\n*[[license plate]]\n*[[List of famous automobiles]]\n*[[list of automobile manufacturers]]\n*[[parking meter]]\n*[[parking ramp]]\n*[[power transfer]]\n*[[Reclaim the Streets]]\n*[[road]]\n*[[road safety]]\n*[[tank]]\n*[[traffic law]]\n*[[truck]]\n*[[urban car]]\n*[[Woodie]]\n*[[Stirling engine]]\n\n==Tumbu kaluar==\n*[http://www.euroncap.com/ EuroNCAP]\n*[http://www-fars.nhtsa.dot.gov/ U.S. Department of Transport Fatal Accident Statistics]\n*[http://www.ntsb.gov/ National Transportation Safety Board]\n*[http://www.bankrate.com/brm/news/insur/19981106c.asp What to expect after an auto accident]\n*[http://members.tripod.com/~tcotrel/accidentadvice.html What to do in the Event of an Auto Accident]\n*[http://www.fact-sheets.com/cars/ Automotive Fact Sheets]\n*{{wia}}\n\n==Mobil, baheula jeung kiwari==\n\n{| cellspacing=\"0\" cellpadding=\"2\" border=\"0\" width=\"60%\" align=\"center\"\n|- valign=\"middle\"\n|\n[[Image:hudson.phaeton.1917.750pix.jpg|thumb|300px|Hudson Phaeton|1917 Hudson Phaeton]]\n|\n[[Image:Late_model_Ford_Model_T.jpg|thumb|300px|Ford Model T|\'\'circa 1920s Ford Model T]]\n|- valign=\"middle\"\n|\n[[Image:austin.berkeley.1934.750pix.jpg|thumb|300px|Austin Berkeley|1934 Austin Berkeley]]\n|\n[[Image:1942Jeep.jpeg|thumb|300px|Jeep|1942 Jeep]]\n|- valign=\"middle\"\n|\n[[Image:53102chaika.jpg|thumb|300px|GAZ Chaika parade car|circa 1960 GAZ Chaika parade car]]\n|\n[[Image:64biscayne.jpg|thumb|300px|Chevrolet Biscayne|1964 Chevrolet Biscayne]]\n|- valign=\"middle\"\n|\n[[Image:wolseley.6slash110.1967.750pix.jpg|thumb|300px|1967 BMC Wolseley 6/110]]\n|\n[[Image:1967-VW-Beatle.jpg|thumb|300px|VW Beetle|1967 VW Beetle]]\n|- valign=\"middle\"\n|\n[[Image:Falcon.jpg|thumb|300px|Ford XB Falcon GT 351|1973 Australian Ford XB Falcon GT 351]]\n|\n[[Image:1984-Side-Slant-400x300.jpg|thumb|300px|Porsche 928|1984 [[Porsche 928]]]]\n|- valign=\"middle\"\n|\n[[Image:Mini_cooper.jpg|thumb|300px|Mini|1985 [[British Leyland]] Mini]]\n|\n[[Image:vw_golf_mk1_cabrio.jpg|thumb|300px|VW Golf Cabrio|1988 VW Golf Cabrio]]\n|- valign=\"middle\"\n|\n[[Image:91saturn.jpg|thumb|300px|Saturn SL-1|1991 Saturn SL-1]]\n|\n[[Image:ford.focus.2000.750pix.jpg|thumb|300px|2000 Ford Focus wagon]]\n|- valign=\"middle\"\n|\n[[Image:Hummer H2.jpg|thumb|300px|2003 Hummer H2]]\n|\n[[Image:BMW MINI.jpg|thumb|300px|2004 MINI Cooper S]]\n|- valign=\"middle\" align=\"center\"\n|colspan=\"2\"|\n[[image:Airflow.jpg|thumb|center|400px|1937 Chrysler Airflow (left), 2002 Chrysler PT Cruiser]]\n|- valign=\"middle\" align=\"center\"\n|colspan=\"2\"|\n[[image:ionbowlinggreen.jpg|thumb|center|500px|2003 Saturn ION2 (left), 2003 Chevrolet Corvette]]\n|}\n\n\n\n\n\n\n\n\n \n\n\n \n\n\n\n\n\n[[Category:Mobil]]\n\n[[da:Bil (køretøj)]] [[de:Automobil]] [[en:Automobile]] [[es:Automóvil]] [[eo:Aŭtomobilo]]\n[[fr:Automobile]] [[he:מכונית]] [[la:Autocinetum]] [[nl:Auto]] [[ja:自動車]] [[no:Bil]] [[pl:Samochód]] [[ro:Automobil]] [[ru:Автомобиль]] [[fi:Auto]] [[sv:Bil]] [[tr:Otomobil]] [[zh:汽车]] [[tokipona:tomo tawa]]','',3,'Kandar','20040810041501','',0,0,0,0,0.690197244142,'20050316081936','79959189958498'); INSERT INTO cur VALUES (863,0,'Rékayasa_sipil','Dina watesan modern, \'\'\'téhnik sipil\'\'\' \"meluas\" jadi [[rékayasa]] numana kabagi dina sababaraha bagian nyaeta \"perencanaan\", konstruksi jeung perawatan struktur nu aya hubunganna jeung bumi, cai atawa peradaban jeung prosesna. Ayeuna téhnik sipil oge nyakup jalan, struktur, sumber cai, cai kotor, kontrol banjir atawa lalu lintas.\n\nEngineering has developed from observations of the ways natural and manmade systems react and from the development of empirical equations that provide bases for design. Civil engineering is the broadest of the engineering fields. In fact engineering was once divided into only two fields--military and civil. All the engineering specialties have derived from civil engineering. Civil engineering is still an umbrella field comprised of many related specialities.\n\n==Widang dina Téhnik Sipil==\n===Téhnik Sipil Umum===\nGeneral civil engineering is concerned with the overall interface of fixed projects with the greater world. General civil engineers work closely with surveyors and specialized civil engineers to fit and serve fixed projects within their given site, community and terrain by designing grading, drainage (flood control), paving, water supply, sewer service, electric and communications supply and land (real property) divisions. General engineers spend much of their time visiting project sites, developing community/neighborhood consensus, and preparing construction plans.\n\n===Rekayasa Struktur===\n[[Structural engineering]] is concerned with the design of bridges, buildings, offshore oil platforms, dams etc. [[Structural design]] and [[structural analysis]] are components of [[structural engineering]] and a key component in the structural design process. \nThis involves computing the stresses and forces at work within a structure. \nThere are some structural engineers who work in non-typical areas, designing aircraft, spacecraft and even biomedical devices. \n\n===Rekayasa Geoteknik===\nSupporting structural engineering is the field of [[geotechnical engineering]]. The importance of geotechnical engineering can hardly be overstated: buildings must be connected to the ground. [[Geotechnical engineering]] is concerned with soil properties, foundations, footings, soil-structure interaction and soil dynamics.\n\n===Rekayasa Lalulintas===\n[[Transportation engineering]] is concerned with [[queueing theory]] and traffic flow planning, roadway geometric design and driver behavior patterns. Simulation of traffic operation is performed through use of trip generation, traffic assignment algorithims which can be highly complex computational problems.\n\n===Téhnik Lingkungan===\n[[Environmental engineering]] deals with the treatment of chemical, biological, and/or thermal waste, the purification of water and air, and the [[remediation]] of sites impacted by prior waste disposal. Among the topics covered by environmental engineering are [[water purification]], [[sewage treatment]], and [[hazardous waste]] management. Environmental engineering is related to the fields of [[hydrology]], [[geohydrology]] and [[meteorology]] insofar as knowledge of water and flows are required to understand pollutant transport. Environmental engineers are also involved in pollution reduction, [[green engineering]] and [[industrial ecology]].\n\nEnvironmental engineering is the modern term for [[Sanitary engineering]]. Some other terms in use are [[public health engineering]] and [[environmental health engineering]].\n\n===Rekayasa Hidrolika===\n[[Hydraulic engineering]] is concerned with the flow and conveyance of fluids, principally water. This area of engineering is, of course, intimately related to the design of bridges, dams, channels, canals, and levees, and to both sanitary and environmental engineering.\n\n===Manajemen Konstruksi===\n[[Construction engineering]] involves planning and execution of the designs from transportation, site development, hydraulic, environmental, structural and geotechnical engineers.\n\n===Elmu Material===\nCivil engineering also includes [[material science]]. \nEngineering materials include concrete, steel and recently, polymers and ceramics with potential engineering application.\n\n==Karir==\nA popular misconception is that civil engineering is far from the exciting frontiers in [[mathematics]] and [[computer science]]. In actuality, much of what is now [[computer science]] was driven by work in civil engineering, where structural and network analysis problems required parallel computations and development of advanced algorithms.\n\nThere are also civil engineers who work in the area of [[safety engineering]], applying [[Metoda Monte Carlo|probabilistic methods]] to structural design, safety analysis and even estimates of insurance losses due to natural and man-made hazards.\n\n== Tempo oge ==\n\n* [[American Society of Civil Engineers]]\n* [[Civil engineer]]\n* [[Institution of Civil Engineers]]\n* [[List of civil engineers]]\n* [[List of historic civil engineering landmarks]]\n* [[Landscape Architecture]]\n\n[[category:rékayasa]]\n\n[[de:Bauingenieurwesen]]\n[[fr:Génie civil]]\n[[ja:土木工学]]\n[[nl:Civiele techniek]]\n[[sv:Väg och vattenbyggnadsteknik]]','/* Karir */',13,'Budhi','20041230010033','',0,0,1,0,0.108616241304,'20041230010033','79958769989966'); INSERT INTO cur VALUES (865,0,'Kamungkinan','[[Category:Probability theory]]\nKecap \'\'\'\'\'probability\'\'\'\'\' asalna tina basa [[Latin]] \'\'probare\'\' (ngabuktikeun, atawa nyoba). \nSacara teu resmi, \'\'probable\'\' ngarupakeun salah sahiji kecap anu digunakeun keur kajadian jeung kanyaho anu teu pasti, kecap sejenna atawa anu rada bisa ngagantina nyaeta ku \'\'likely\'\', \'\'risky\'\', \'\'hazardous\'\', \'\'uncertain\'\', and \'\'doubtful\'\', gumantung kana konteksna.\n\'\'Chance\'\', \'\'odds\'\', jeung \'\'bet\'\' ngarupakeun kecap sejen anu ngagambarkeun kaayaan anu sarua. Heunteu saperti dina [[classical mechanics|theory of mechanics]] nu nangtukeun harti pasti tina saperti dina watesan \'\'gawe\'\' jeung \'\'gaya\'\', dina [[tiori probabiliti]] nyobaan keur ngitung dina notasi \'\'probable\'\'.\n\n\n==Historical remarks==\n\nProbability theory, as applied to observations, was largely a\n[[nineteenth century ]]development. [[Gambling]] shows that there has been an interest in quantifying the ideas of probability for millennia, but exact mathematical descriptions of use in these types of problems only arose much later. \n\nThe doctrine of probabilities dates as far back as [[Pierre de Fermat]] and [[Blaise Pascal]] (1654). [[Christiaan Huygens]] (1657) gave the first scientific treatment of the subject. [[Jakob Bernoulli]]\'s \'\'Ars Conjectandi\'\' (posthumous, 1713) and [[Abraham de Moivre]]\'s Doctrine of Chances (1718) treated the subject as a branch of mathematics. \n\nThe theory of errors may be traced back to [[Roger Cotes]]\'s \'\'Opera Miscellanea\'\' (posthumous, 1722), but a memoir prepared by Simpson in 1755 (printed 1756) first applied the theory to the discussion of errors of observation. The reprint (1757) of this memoir lays down the axioms that positive and negative errors are equally probable, and that there are certain assignable limits within which all errors may be supposed to fall; continuous errors are discussed and a probability curve is given.\n\n[[Pierre-Simon Laplace]] (1774) made the first attempt to deduce a rule for the combination of observations from the principles of the theory of probabilities. He represented the law of probability of errors by a curve y = \\phi(x), x being any error and y its probability, and laid down three properties of this curve: (1) It is symmetric as\nto the y-axis; (2) the x-axis is an asymptote, the probability of the error \\infty being 0; (3) the area enclosed is 1, it being certain that an error exists. He deduced a formula for the mean of three observations. He also gave (1781) a formula for the law of facility of error (a term due to Lagrange, 1774), but one which led to unmanageable equations. Daniel Bernoulli (1778) introduced the principle of the maximum product of the probabilities of a system of concurrent errors.\n\nThe [[method of least squares]] is due to [[Adrien-Marie Legendre]] (1805), who introduced it in his \'\'Nouvelles méthodes pour la détermination des orbites des comètes\'\'. In ignorance of Legendre\'s contribution, an Irish-American writer, [[Robert Adrain]], editor of \"The Analyst\" (1808), first deduced the law of facility of error, \n\n:\\phi(x) = ce^{-h^2 x^2}\n\nc and h being constants depending on precision of observation. He gave two proofs, the second being essentially the same as Herschel\'s (1850). Gauss gave the first proof which seems to have been known in Europe (the third after Adrain\'s) in 1809. Further proofs were given by Laplace (1810, 1812), Gauss (1823), Ivory (1825, 1826), Hagen (1837), [[Bessel]] (1838), Donkin (1844,\n1856), and Crofton (1870). Other contributors were Ellis (1844), [[De Morgan]] (1864), [[Glaisher]] (1872), and Schiaparelli (1875). Peters\'s (1856) formula for r, the probable error of a single observation, is well known.\n\nIn the [[nineteenth century]] authors on the general theory included Laplace, Lacroix (1816), Littrow (1833), [[Adolphe Quetelet]] (1853), [[Richard Dedekind]] (1860), Helmert (1872), Laurent (1873), Liagre, Didion, and Pearson. [[Augustus De Morgan]] and [[George Boole]] improved the exposition of the theory. \n\nOn the geometric side (see [[integral geometry]]) contributors to \'\'The Educational Times\'\' were influential (Miller, Crofton, McColl, Wolstenholme, Watson, and Artemas Martin).\n\n==Concepts==\n\nThere is essentially one set of mathematical rules for manipulating probability; these rules are listed under \"Formalization of probability\" below.\n(There are other rules for quantifying uncertainty,\nsuch as the [[Dempster-Shafer theory]] and [[fuzzy logic]],\nbut those are essentially different and not compatible with the laws of probability as they are usually understood.)\nHowever, there is ongoing debate over what, exactly, the rules apply to; this is the topic of [[probability interpretations]].\n\nThe general idea of probability is often divided into two related concepts:\n\n* [[Aleatory probability]], which represents the likelihood of future events whose occurrence is governed by some \'\'random\'\' physical phenomenon. This concept can be further divided into physical phenomena that are predictable, in principle, with sufficient information, and phenomena which are essentially unpredictable. Examples of the first kind include tossing [[dice]] or spinning a [[roulette]] wheel, and an example of the second kind is [[radioactive decay]].\n\n* [[Epistemic probability]], which represents our uncertainty about propositions when one lacks complete knowledge of causative circumstances. Such propositions may be about past or future events, but need not be. Some examples of epistemic probability are to assign a probability to the proposition that a proposed law of physics is true, and to determine how \"probable\" it is that a suspect committed a crime, based on the evidence presented.\n\nIt is an open question whether aleatory probability is reducible to epistemic probability based on our inability to precisely predict every force that might affect the roll of a die, or whether such uncertainties exist in the nature of reality itself, particularly in [[quantum physics|quantum]] phenomena governed by Heisenberg\'s [[uncertainty principle]]. Although the same mathematical rules apply regardless of which interpretation is chosen, the choice has major implications for the way in which probability is used to model the real world.\n\n==Formalization of probability==\n\nSaperti [[theory|teori]] sejen, [[tiori probabiliti]] is a representation of probabilistic concepts in formal terms -- that is, in terms that can be considered separately from their meaning. \nThese formal terms are manipulated by the rules of mathematics and logic, and any results are then interpreted or translated back into the problem domain.\n\nThere have been at least two successful attempts to formalize probability, namely the [[Kolmogorov]] formulation and the [[Richard Threlkeld Cox|Cox]] formulation.\nIn Kolmogorov\'s formulation,\n[[set]]s are interpreted as events and probability itself as a [[measure]] on a class of sets.\nIn Cox\'s formulation,\nprobability is taken as a primitive (that is, not further analyzed) and the emphasis is on constructing a consistent assignment of probability values to propositions.\nIn both cases,\nthe laws of probability are the same, except for technical details:\n\n# a probability is a number between 0 and 1;\n# the probability of an event or proposition and its complement must add up to 1; and \n# the [[joint probability]] of two events or propositions is the product of the probability of one of them and the probability of the second, [[conditional probability|conditional]] on the first.\n\nThe reader will find an exposition of the Kolmogorov formulation in the [[tiori probabiliti]] article, and in the [[Cox\'s theorem]] article for Cox\'s formulation. See also the article on [[probability axioms]].\n\n=== Representation and interpretation of probability values ===\n\nThe probability of an event is generally represented as a [[real number]] between 0 and 1. An \'\'impossible\'\' event has a probability of exactly 0, and a \'\'certain\'\' event has a probability of 1, but the converses are not always true: probability 0 events are not always impossible, nor probability 1 events certain. \nThe rather subtle distinction between \"certain\" and \"probability 1\" is treated at greater length in the article on \"[[almost surely]]\".\n\nMost probabilities that occur in practice are numbers between 0 and 1, indicating the event\'s position on the continuum between impossibility and certainty. The closer an event\'s probability is to 1, the more likely it is to occur. \n\nFor example, if two events are assumed equally probable, such as a flipped coin landing heads-up or tails-up, we can express the probability of each event as \"1 in 2\", or, equivalently, \"50%\" or \"1/2\".\n\nProbabilities are equivalently expressed as [[odds]], which is the ratio of the probability of one event to the probability of all other events. \nThe odds of heads-up, for the tossed coin, are (1/2)/(1 - 1/2), which is equal to 1/1. This is expressed as \"1 to 1 odds\" and often written \"1:1\". \n\nOdds \'\'a\'\':\'\'b\'\' for some event are equivalent to probability \'\'a\'\'/(\'\'a\'\'+\'\'b\'\').\nFor example, 1:1 odds are equivalent to probability 1/2, and 3:2 odds are equivalent to probability 3/5.\n\nThere remains the question of exactly what can be assigned probability, and how the numbers so assigned can be used; this is the question of [[probability interpretations]].\nThere are some who claim that probability can be assigned to any kind of an uncertain logical proposition; this is the [[Bayesian probability|Bayesian]] interpretation.\nThere are others who argue that probability is properly applied only to propositions concerning sequences of repeated experiments or sampling from a large population; this is the [[frequency probability|frequentist]] interpretation.\nThere are several other interpretations which are variations on one or the other of those, or which have less acceptance at present.\n\n=== Sebaran ===\n\nA [[probability distribution]] is a function that assigns probabilities to events or propositions. For any set of events or propositions there are many ways to assign probabilities, so the choice of one distribution or another is equivalent to making different assumptions about the events or propositions in question.\n\nThere are several equivalent ways to specify a probability distribution.\nPerhaps the most common is to specify a [[probability density function]].\nThen the probability of an event or proposition is obtained by [[integration|integrating]] the density function.\nThe distribution function may also be specified directly.\nIn one dimension, the distribution function is called the [[cumulative distribution function]].\nProbability distributions can also be specified via [[moment]]s or the [[characteristic function]], or in still other ways.\n\n\nA distribution is called a \'\'\'discrete distribution\'\'\' if it is defined on a [[countable]], [[discrete]] set, such as a subset of the integers.\nA distribution is called a \'\'\'continuous distribution\'\'\' if it has a continuous distribution function, such as a polynomial or exponential function.\nMost distributions of practical importance are either discrete or continuous, but there are examples of distributions which are neither.\n\n\nImportant discrete distributions include the discrete [[sebaran seragam]], [[sebaran Poisson]], [[sebaran binomial]], the [[negative binomial distribution]] and the [[Maxwell-Boltzmann distribution]].\n\nSebaran kontinyu anu penting nyaeta [[sebaran normal]], [[sebaran gamma]], [[sebaran-t student]], sarta [[sebaran eksponensial]].\n\n== Probability in mathematics ==\n\n[[Probability axioms]] form the basis for mathematical [[probability theory]]. Calculation of probabilities can often be determined using [[combinatorics]] or by applying the axioms directly. Probability applications include even more than [[statistics]], which is usually based on the idea of [[probability distribution]]s and the [[central limit theorem]].\n\nTo give a mathematical meaning to probability, consider flipping a \"fair\" coin. Intuitively, the probability that heads will come up on any given coin toss is \"obviously\" 50%; but this statement alone lacks [[mathematical rigor]] - certainly, while we might \'\'expect\'\' that flipping such a coin 10 times will yield 5 heads and 5 tails, there is no \'\'guarantee\'\' that this will occur; it is possible for example to flip 10 heads in a row. What then does the number \"50%\" mean in this context?\n\nOne approach is to use the [[law of large numbers]]. In this case, we assume that we can perform any number of coin flips, with each coin flip being independent - that is to say, the outcome of each coin flip is unaffected by previous coin flips. If we perform \'\'N\'\' trials (coin flips), and let \'\'N\'\'H be the number of times the coin lands heads, then we can, for any \'\'N\'\', consider the ratio \'\'N\'\'H/\'\'N\'\'.\n\nAs \'\'N\'\' gets larger and larger, we expect that in our example the ratio \'\'N\'\'H/\'\'N\'\' will get closer and closer to 1/2. This allows us to \'\'define\'\' the probability Pr(\'\'H\'\') of flipping heads as the [[mathematical limit]], as \'\'N\'\' approaches infinity, of this sequence of ratios: \n\n:\\Pr(H) = \\lim_{N \\to \\infty}{N_H \\over N} \n\nIn actual practice, of course, we cannot flip a coin an infinite number of times; so in general, this formula most accurately applies to situations in which we have already assigned an \'\'a priori\'\' probability to a particular outcome (in this case, our \'\'assumption\'\' that the coin was a \"fair\" coin). The law of large numbers then says that, given Pr(\'\'H\'\'), and any arbitrarily small number ε, there exists some number \'\'n\'\' such that for all \'\'N\'\' > \'\'n\'\',\n\n:\\left| \\Pr(H) - {N_H \\over N}\\right| < \\epsilon\n\nIn other words, by saying that \"the probability of heads is 1/2\", we mean that, if we flip our coin often enough, \'\'eventually\'\' the number of heads over the number of total flips will become arbitrarily close to 1/2; and will then stay \'\'at least\'\' as close to 1/2 for as long as we keep performing additional coin flips.\n\nThe \'\'a priori\'\' aspect of this approach to probability is sometimes troubling when applied to real world situations. For example, in the play \'\'[[Rosencrantz and Guildenstern are Dead]]\'\' by [[Tom Stoppard]], a character flips a coin which keeps coming up heads over and over again, a hundred times. He can\'t decide whether this is just a random event - after all, it is possible (although unlikely) that a fair coin would give this result - or whether his assumption that the coin is fair is at fault.\n\n\n=== Remarks on probability calculations ===\n\nThe difficulty of probability calculations lie in determining the number of possible events, counting the occurrences of each event, counting the total number of possible events. Especially difficult is drawing meaningful conclusions from the probabilities calculated. An amusing probability riddle, the [[Monty Hall problem]] demonstrates the pitfalls nicely.\n\nTo learn more about the basics of [[probability theory]], see the article on [[probability axiom]]s and the article on [[Bayes\' theorem]] that explains the use of conditional probabilities in case where the occurrence of two events is related.\n\n\n== Applications of probability theory to everyday life ==\n\nA major effect of probability theory on everyday life is in [[risk]] assessment and in trade on [[commodity markets]]. Governments typically apply probability methods in [[environment regulation]] where it is called \"[[pathway analysis]]\", and are often [[measuring well-being]] using methods that are stochastic in nature, and choosing projects to undertake based on their perceived probable effect on the population as a whole, statistically. It is not correct to say that [[statistics]] are involved in the modelling itself, as typically the assessments of [[risk]] are one-time and thus require more fundamental probability models, e.g. \"the probability of another 9/11\". A [[law of small numbers]] tends to apply to all such choices and perception of the effect of such choices, which makes probability measures a political matter.\n\nA good example is the effect of the perceived probability of any widespread Middle East conflict on oil prices - which have ripple effects in the economy as a whole. An assessment by a commodity trade that a war is more likely vs. less likely sends prices up or down, and signals other traders of that opinion. Accordingly, the probabilities are not assessed independently nor necessarily very rationally. The theory of [[behavioral finance]] emerged to describe the effect of such [[groupthink]] on pricing, on policy, and on peace and conflict.\n\nIt can reasonably be said that the discovery of rigorous methods to assess and combine probability assessments has had a profound effect on modern society. A good example is the application of [[game theory]], itself based strictly on probability, to the [[Cold War]] and the [[mutual assured destruction]] doctrine. Accordingly, it may be of some importance to most citizens to understand how odds and probability assessments are made, and how they contribute to reputations and to decisions, especially in a [[democracy]].\n\nAnother significant application of probability theory in everyday life is [[reliability]]. Many consumer products, such as [[automobiles]] and consumer electronics, utilize [[reliability theory]] in the design of the product in order to reduce the probability of failure. The the probability of failure is also closely associated with the product\'s [[warranty]].\n\n== Tempo oge ==\n* [[Bayesian probability]]\n* [[Bernoulli process]]\n* [[Cox\'s theorem]]\n* [[Decision theory]]\n* [[Games of chance]]\n* [[Game theory]]\n* [[Information theory]]\n* [[Law of averages]]\n* [[Law of large numbers]]\n* [[Normal distribution]]\n* [[Random fields]]\n* [[Statistik]]\n** [[List of statistical topics]]\n* [[Stochastic process]]\n* [[Variabel acak]]\n* [[Wiener process]]\n\n== External links ==\n\n* [[Edwin Thompson Jaynes]]. \'\'Probability Theory: The Logic of Science\'\'. Preprint: Washington University, (1996). -- [http://omega.albany.edu:8008/JaynesBook.html HTML] and [http://bayes.wustl.edu/etj/prob/book.pdf PDF]\n* [http://www.csse.monash.edu.au/~footy Probabilistic football prediction competition], [http://www.csse.monash.edu.au/~footy/about.shtml probabilistic scoring] and [http://www.csse.monash.edu.au/~footy/bibliography.shtml further reading].\n* \"\'\'[http://www.npr.org/display_pages/features/feature_1697475.html The Not So Random Coin Toss], Mathematicians Say Slight but Real Bias Toward Heads\'\'\". [[NPR]].\n*[http://www.benbest.com/science/theodds.html Figuring the Odds (Probability Puzzles)]\n\n== Quotations ==\n* [[Damon Runyon]], \"It may be that the race is not always to the swift, nor the battle to the strong - but that is the way to bet.\"\n* [[Pierre-Simon Laplace]] \"It is remarkable that a science which began with the consideration of games of chance should have become the most important object of human knowledge.\" \'\'Théorie Analytique des Probabilités\'\', 1812.\n* [[Richard von Mises]] \"The unlimited extension of the validity of the exact sciences was a characteristic feature of the exaggerated rationalism of the eighteenth century\" (in reference to Laplace). \'\'Probability, Statistics, and Truth,\'\' p 9. Dover edition, 1981 (republication of second English edition, 1957).\n\n[[de:Wahrscheinlichkeit]]\n[[fr:Probabilité]]\n[[he:הסתברות]]\n[[it:Probabilità]]\n[[ja:確率]]\n[[pl:Prawdopodobie%C5%84stwo]]\n[[ro:Probabilitate]]\n[[sv:Sannolikhet]]','/* Applications of probability theory to everyday life */',0,'133.66.133.191','20041228001753','',0,0,0,0,0.586134385591,'20050101215719','79958771998246'); INSERT INTO cur VALUES (866,0,'Mékanika_klasik','\'\'\'Classical mechanics\'\'\' is a model of the [[physics]] of [[force (physics)|forces]] acting upon bodies. It is often referred to as \"\'\'\'Newtonian mechanics\'\'\'\" after [[Isaac Newton|Newton]] and his [[Newton\'s laws of motion|laws of motion]]. \'\'\'Classical mechanics is subdivided into [[statics]] (which models objects at rest), kinematics (which models objects in motion), and [[dynamics]] (which models subjected to forces). See also [[mechanics]].\n\nClassical mechanics produces very accurate results within the domain of everyday experience. It is superseded by [[special relativity|relativistic mechanics]] for systems moving at large [[velocity|velocities]] near the speed of light, [[quantum mechanics]] for systems at small distance scales, and [[quantum field theory|relativistic quantum field theory]] for systems with both properties. Nevertheless, classical mechanics is still very useful, because (i) it is much simpler and easier to apply than these other theories, and (ii) it has a very large range of approximate validity. Classical mechanics can be used to describe the motion of human-sized objects (such as [[top]]s and [[baseball]]s), many astronomical objects (such as [[planet]]s and [[galaxy|galaxies]]), and certain microscopic objects (such as organic [[molecule]]s.)\n\nAlthough classical mechanics is roughly compatible with other \"classical\" theories such as classical [[electrodynamics]] and [[thermodynamics]], there are inconsistencies discovered in the late 19th century that can only be resolved by more modern physics. In particular, classical nonrelativistic electrodynamics predicts that the [[speed of light]] is a constant relative to an [[Luminiferous aether|aether medium]], a prediction that is difficult to reconcile with classical mechanics and which led to the development of [[special relativity]]. When combined with classical thermodynamics, classical mechanics leads to the [[Gibbs paradox]] in which [[entropy]] is not a well-defined quantity and to the [[ultraviolet catastrophe]] in which a [[black body]] is predicted to emit infinite amounts of energy. The effort at resolving these problems led to the development of [[quantum mechanics]].\n\n== Description of the theory ==\n\nThe following introduces the basic concepts of classical mechanics. For simplicity, it uses a \'\'point particle\'\', which is an object with negligible size. The motion of a point particle is characterized by a small number of parameters: its position, mass, and the forces applied to it. Each of these parameters is discussed in turn.\n\nIn reality, the kind of objects which classical mechanics can describe always have a non-zero size. True point particles, such as the [[electron]], are properly described by [[quantum mechanics]]. Objects with non-zero size have more complicated behavior than hypothetical point particles, because their internal configuration can change - for example, a baseball can spin while it is moving. However, the results for point particles can be used to study such objects by treating them as composite objects, made up of a large number of interacting point particles. Such composite objects behave like point particles, provided they are small compared to the distance scales of the problem, which indicates that the use of point particles is internally consistent.\n\n=== Position and its derivatives ===\n\nThe \'\'position\'\' of a point particle is defined with respect to an arbitrary fixed point in [[space]], which is sometimes called the \'\'origin\'\', \'\'\'O\'\'\'. It is defined as the [[vector (spatial)|vector]] \'\'\'r\'\'\' from \'\'\'O\'\'\' to the particle. In general, the point particle need not be stationary, so \'\'\'r\'\'\' is a function of \'\'t\'\', the [[time]] elapsed since an arbitrary initial time. In pre-Einstein relativity (known as [[Galilean relativity]]), time is considered an absolute in all [[reference frame]]s.\n\n==== Velocity ====\nThe \'\'[[velocity]]\'\', or the [[calculus|rate of change]] of position with time, is defined as the [[derivative]] of the position with respect to time or\n\n: \\mathbf{v} = {d\\mathbf{r} \\over dt}.\n\nIn classical mechanics, velocities are directly additive and subtractive. For example, if one car traveling East at 60 km/h passes another car traveling East at 50 km/h, from the perspective of the car it passes it is traveling East at 60−50 = 10 km/h. From the perspective of the faster car, the slower car is moving 10 km/h to the West. What if the car is traveling north? Velocities are directly additive as vector quantities; they must be dealt with using vector analysis.\n\nMathematically, if the velocity of the first object in the previous discussion is denoted by the vector v = vd and the velocity of the second object by the vector u = ue where v is the speed of the first object, u is the speed of the second object, and d and e are [[unit vector]]s in the directions of motion of each particle respectively, then the velocity of the first object as seen by the second object is:\n\n:v\' = v - u\n\nSimilarly:\n\n:u\' = u - v\n\nWhen both objects are moving in the same direction, this equation can be simplified to:\n\n:v\' = ( v - u ) d\n\nOr, by ignoring direction, the diference can be given in terms of speed only:\n\n:v\' = v - u\n\n==== Acceleration ====\n\nThe \'\'[[acceleration]]\'\', or rate of change of velocity, is the [[derivative]] of the velocity with respect to time or\n\n: \\mathbf{a} = {d\\mathbf{v} \\over dt}.\n\nThe acceleration vector can be changed by changing its magnitude, changing its direction, or both. If the magnitude of \'\'\'v\'\'\' decreases, this is sometimes referred to as \'\'deceleration\'\' or \'\'retardation\'\'; but generally any change in the velocity, including deceleration, is simply referred to as acceleration.\n\n==== Frames of reference ====\n\nThe following consequences can be derived about the perspective of an event in two reference frames, \'\'S\'\' and S\', where S\' is traveling at a relative speed of \'\'u\'\' to \'\'S\'\'.\n\n* v\' = v - u (the velocity of a particle from the perspective of S\' is slower by \'\'u\'\' than from the perspective of S)\n* a\' = a (the acceleration of a particle remains the same regardless of reference frame)\n* F\' = F (since F = \'\'m\'\'a) (the force on a particle remains the same regardless of reference frame; see [[Newton\'s laws of motion|Newton\'s law]])\n* the [[speed of light]] is not a constant\n* the form of [[Maxwells equations|Maxwell\'s equations]] is not preserved across reference frames\n\n=== Forces; Newton\'s second law ===\n\n[[Newton\'s laws of motion|Newton\'s second law]] relates the [[mass]] and velocity of a particle to a vector quantity known as the [[Force (physics)|force]]. If \'\'m\'\' is the mass of a particle and \'\'\'F\'\'\' is the vector sum of all applied forces (i.e. the \'\'net\'\' applied force, Newton\'s second law states that\n\n: \\mathbf{F} = {d(m \\mathbf{v}) \\over dt}.\n\nThe quantity \'\'m\'\'\'\'\'v\'\'\' is called the [[momentum]]. Typically, the mass \'\'m\'\' is constant in time, and Newton\'s law can be written in the simplified form\n\n: \\mathbf{F} = m \\mathbf{a}\n\nwhere \'\'\'a\'\'\' is the acceleration, as defined above. It is not always the case that \'\'m\'\' is independent of \'\'t\'\'. For example, the mass of a [[rocket]] decreases as its propellant is ejected. Under such circumstances, the above equation is incorrect and the full form of Newton\'s second law must be used.\n\nNewton\'s second law is insufficient to describe the motion of a particle. In addition, it requires a value for \'\'\'F\'\'\', obtained by considering the particular physical entities with which the particle is interacting. For example, a typical [[resistive force]] may be modelled as a function of the velocity of the particle, for example:\n\n: \\mathbf{F}_{\\rm R} = - \\lambda \\mathbf{v}\n\nwith λ a positive constant. Once independent relations for each force acting on a particle are available, they can be substituted into Newton\'s second law to obtain an [[differential equation|ordinary differential equation]], which is called the \'\'equation of motion\'\'. Continuing the example, assume that friction is the only force acting on the particle. Then the equation of motion is\n\n: - \\lambda \\mathbf{v} = m \\mathbf{a} = m {d\\mathbf{v} \\over dt}.\n\nThis can be [[integration|integrated]] to obtain\n\n: \\mathbf{v} = \\mathbf{v}_0 e^{- \\lambda t / m}\n\nwhere \'\'\'v\'\'\'0 is the initial velocity. This means that the velocity of this particle [[exponential decay|decays exponentially]] to zero as time progresses. This expression can be further integrated to obtain the position \'\'\'r\'\'\' of the particle as a function of time.\n\nImportant forces include the [[gravity|gravitational force]] and the [[Lorentz force]] for [[electromagnetism]]. In addition, Newton\'s third law can sometimes be used to deduce the forces acting on a particle: if it is known that particle A exerts a force \'\'\'F\'\'\' on another particle B, it follows that B must exert an equal and opposite \'\'reaction force\'\', -\'\'\'F\'\'\', on A.\n\n=== Energy ===\n\nIf a force \'\'\'F\'\'\' is applied to a particle that achieves a displacement δ\'\'\'r\'\'\', the \'\'work done\'\' by the force is the scalar quantity\n\n: \\delta W = \\mathbf{F} \\cdot \\delta \\mathbf{r} .\n\nIf the mass of the particle is constant, and δ\'\'W\'\'total is the total work done on the particle, obtained by summing the work done by each applied force, from Newton\'s second law: \n\n: \\delta W_{\\rm total} = \\delta T \\,,\n\nwhere \'\'T\'\' is called the [[kinetic energy]]. For a point particle, it is defined as\n\n: T = {m |\\mathbf{v}|^2 \\over 2}.\n\nFor extended objects composed of many particles, the kinetic energy of the composite body is the sum of the kinetic energies of the particles.\n\nA particular class of forces, known as \'\'conservative forces\'\', can be expressed as the [[gradient]] of a scalar function, known as the [[potential energy]] and denoted \'\'V\'\':\n\n: \\mathbf{F} = - \\nabla V.\n\nIf all the forces acting on a particle are conservative, and \'\'V\'\' is the total potential energy, obtained by summing the potential energies corresponding to each force\n\n: \\mathbf{F} \\cdot \\delta \\mathbf{r} = - \\nabla V \\cdot \\delta \\mathbf{r} = - \\delta V\n: \\Rightarrow - \\delta V = \\delta T\n: \\Rightarrow \\delta (T + V) = 0.\n\nThis result is known as \'\'conservation of energy\'\' and states that the total [[energy]], E = T + V, is constant in time. It is often useful, because many commonly encountered forces are conservative.\n\n=== Further results ===\n\nNewton\'s laws provide many important results for composite bodies. See [[angular momentum]]. \n\nThere are two important alternative formulations of classical mechanics: [[Lagrangian mechanics]] and [[Hamiltonian mechanics]]. They are equivalent to Newtonian mechanics, but are often more useful for solving problems. These, and other modern formulations, usually bypass the concept of \"force\", instead referring to other physical quantities, such as energy, for describing mechanical systems.\n\n=== Example ===\n\nConsider two reference frames, one of which is traveling at a relative speed of \'\'u\'\' to the other. For example, for a car passing another car at a relative speed of 10 km/h, \'\'u\'\' is 10 km/h.\n\nTwo reference frames \'\'S\'\' and S\', with S\' traveling at a relative speed of \'\'u\'\' to \'\'S\'\'; an event has space-time coordinates of (\'\'x\'\',\'\'y\'\',\'\'z\'\',\'\'t\'\') in \'\'S\'\' and (x\',y\',z\',t\') in S\'.\n\nThe space-time coordinates of an event in [[Galilean-Newtonian relativity]] are governed by the set of formulas which defines a [[group transformation]] known as the [[Galilean transformation]]: \n\nAssuming time is considered an absolute in all reference frames, the relationship between space-time coordinates in reference frames differing by a relative speed of \'\'u\'\' in the \'\'x\'\' direction (let \'\'x\'\' = \'\'ut\'\' when x\' = 0) is:\n\n:x\' = \'\'x\'\' - \'\'ut\'\'\n:y\' = \'\'y\'\'\n:z\' = \'\'z\'\'\n:t\' = \'\'t\'\'\n\nThe set of formulas defines a [[group transformation]] known as the [[Galilean transformation]] (informally, the \'\'Galilean transform\'\'). \n\n== History ==\n\nThe [[Greece|Greeks]], and [[Aristotle]] in particular, were the first to propose that there are abstract principles governing nature.\n\nOne of the first scientists who suggested abstract laws was [[Galileo Galilei]] who may have performed the famous experiment of dropping two cannon balls from the [[Leaning Tower of Pisa|tower of Pisa]]. (The theory and the practice showed that they both hit the ground at the same time.) Though the reality of this experiment is disputed, he did carry out quantitative experiments by rolling balls on an [[inclined plane]]; his correct theory of accelerated motion was apparently derived from the results of the experiments. \n\nSir Isaac Newton was the first to propose the three laws of motion (the law of inertia, his second law mentioned above, and the law of action and reaction), and to prove that these laws govern both everyday objects and celestial objects.\n\nNewton also developed the calculus which is necessary to perform the mathematical calculations involved in classical mechanics.\n\nAfter Newton the field became more mathematical and more abstract.\n\n== See also ==\n\n* [[Edmund Halley]] -- [[List of equations in classical mechanics]]\n* [[List of publications in physics#Classical mechanics| important publications in classical mechanics]]\n\n==Further reading==\n* [[Richard Feynman|Feynman, Richard Phillips]], \'\'Six Easy Pieces\'\'. ISBN 0201408252\n* Feynman, Richard Phillips, and Roger Penrose, \'\'Six Not So Easy Pieces\'\'. March 1998. ISBN 0201328410\n* Feynman, Richard Phillips, \'\'Lectures on Physics\'\'. ISBN 0738200921\n* Kleppner, D. and Kolenkow, R. J., \'\'An Introduction to Mechanics\'\', McGraw-Hill (1973). ISBN 0070350485\n\n==External links==\n\n* Rosu, Haret C., \"\'\'[http://arxiv.org/abs/physics/9909035 Classical Mechanics]\'\'\". Physics Education. 1999. [arxiv.org : physics/9909035]\n* Horbatsch, Marko, \"\'\'[http://www.yorku.ca/marko/PHYS2010/index.htm Classical Mechanics Course Notes]\'\'\".\n\n{{Physics-footer}}\n\n[[da:Klassisk mekanik]]\n[[de:Klassische Mechanik]]\n[[el:Κλασική Μηχανική]]\n[[es:Mecánica clásica]]\n[[et:Klassikaline mehhaanika]]\n[[fr:Mécanique newtonienne]]\n[[hr:Klasična mehanika]]\n[[it:Meccanica classica]]\n[[ja:古典力学]]\n[[hu:Klasszikus mechanika]]\n[[nl:Klassieke mechanica]]\n[[no:Klassisk mekanikk]]\n[[pl:Mechanika klasyczna]]\n[[ro:Mecanica clasică]]\n[[zh:经典力学]]\n\n[[Category:Classical mechanics]]','',13,'Budhi','20040720071526','',0,0,0,1,0.901150308969,'20040721025423','79959279928473'); INSERT INTO cur VALUES (867,0,'Tiori_probabiliti','[[Category:Probability theory]]\n\'\'\'Tiori probabiliti\'\'\' ngarupakeun elmu [[matematik]] ngeunaan [[kamungkinan|probabiliti]] atawa kamungkinan.\n\nMatematikawan mikirkeun yen probabiliti salaku angka dina interval tina 0 ka 1 keur nangtukeun \"kajadian\" numana bener-bener kajadian atawa henteu kajadian dina bentuk acak. Probabiliti P(E) nangtukeun kajdian E dumasa kana [[probability axioms]].\n\nThe probability that an event E occurs \'\'given\'\' the known occurrence of an event F is the \'\'\'[[conditional probability]]\'\'\' of E \'\'\'given\'\'\' F; its numerical value is P(E \\cap F)/P(F) (as long as P(F) is nonzero). If the conditional probability of E given F is the same as the (\"unconditional\") probability of E, then E and F are said to be [[statistical independence|independent]] events. That this relation between E and F is symmetric may be seen more readily by realizing that it is the same as saying\nP(E \\cap F) = P(E)P(F).\n\nTwo crucial concepts in the theory of probability are those of a [[variabel acak]] and of the [[probability distribution]] of a random variable; see those articles for more information.\n\n==A somewhat more abstract view of probability==\n\n\"Pure\" mathematicians usually take probability theory to be the study of probability spaces and random variables — an approach introduced by [[Andrey Nikolaevich Kolmogorov]] in the [[1930s]]. A [[probability space]] is a triple (Ω, \'\'F\'\', \'\'P\'\'), where\n\n*Ω is a non-empty set, sometimes called the \"sample space\", each of whose members is thought of as a potential outcome of a random experiment. For example, if 100 voters are to be drawn randomly from among all voters in California and asked whom they will vote for governor, then the set of all sequences of 100 Californian voters would be the sample space Ω.\n\n*\'\'F\'\' is a [[sigma-algebra]] of subsets of Ω whose members are called \"events\". For example the set of all sequences of 100 Californian voters in which at least 60 will vote for Schwarzenegger is identified with the \"event\" that at least 60 of the 100 chosen voters will so vote. To say that \'\'F\'\' is a sigma-algebra necessarily implies that the complement of any event is an event, and the union of any (finite or countably infinite) sequence of events is an event. \n\n*P is a probability measure on \'\'F\'\', i.e., a [[measure (mathematics)|measure]] such that P(Ω) = 1.\n\nIt is important to note that \'\'P\'\' is defined on \'\'F\'\' and not on Ω. \nWith Ω denumerable we can define \'\'F\'\' := powerset(Ω) which is trivially a sigma-algebra and the biggest one we can create using Ω. \nIn a discrete space we can therefore omit \'\'F\'\' and just write (Ω, \'\'P\'\') to define it. If on the other hand Ω is non-denumerable and we use \'\'F\'\' = powerset(Ω) we get into trouble defining our probability measure \'\'P\'\' because \'\'F\'\' is too \'huge\'. So we have to use a smaller sigma-algebra \'\'F\'\' (eg. the [[Borel algebra]] of Ω). We call this sort of probability space a continuous probability space and are led to questions in [[measure theory]] when we try to define \'\'P\'\'.\n\n[[Variabel acak]] is a [[measurable function]] on Ω. For example, the number of voters who will vote for Schwarzenegger in the aforementioned sample of 100 is a random variable.\n\nIf \'\'X\'\' is any random variable, the notation \'\'P\'\'(\'\'X\'\' ≥ 60) is shorthand for \'\'P\'\'({ ω in Ω : \'\'X\'\'(ω) ≥ 60 }), so that \"\'\'X\'\' ≥ 60\" is an \"event\".\n\n==Philosophy of application of probability==\n\nSome statisticians will assign probabilities only to events that they think of as random, according to their relative frequencies of occurrence, or to subsets of populations as proportions of the whole; those are \'\'\'frequentists\'\'\'. Others assign probabilities to propositions that are uncertain according either to [[personal probability|subjective]] degrees of belief in their truth, or to logically justifiable degrees of belief in their truth. Such persons are [[Bayesian probability|Bayesians]]. A Bayesian may assign a probability to the proposition that there was life on Mars a billion years ago, since that is uncertain; a frequentist would not assign such a probability, since it is not a random event that has a long-run relative frequency of occurrence.\n\n==Tempo oge==\n\n*[[expectation]]\n*[[likelihood]]\n*[[probability]]\n*[[probability axioms]]\n*[[probability distribution]]\n*[[variabel acak]]\n*[[statistical independence]]\n*[[varian]]\n*[[List of publications in statistics]]\n\n\n[[bg:Теория на вероятностите]]\n[[de:Wahrscheinlichkeitstheorie]]\n[[eo:Teorio de Probabloj]]\n[[es:Probabilidad]]\n[[fr:Théorie des probabilités]]\n[[lt:Tikimybių teorija]]\n[[nl:kansrekening]]\n[[no:Sannsynlighetsteori]]\n[[pl:Teoria prawdopodobieństwa]]\n[[sv:Sannolikhetsteori]]\n[[zh:概率论]]','/* Tempo oge */',13,'Budhi','20041224215443','',0,0,1,0,0.672937061951,'20041231123527','79958775784556'); INSERT INTO cur VALUES (868,0,'Basa_Itali','\'\'\'Italian\'\'\' is a [[Romance languages|Romance language]] spoken by about 70 million people, most of whom live in [[Italy]]. Standard Italian is based on [[Tuscany|Tuscan]] dialects and is somewhat intermediate between the languages of Southern [[Italy]] and the Gallo-Romance languages of the North. The long-established Tuscan standard has, over the last few decades, been slightly eroded by the variety of Italian spoken in Milan, the economic capital of Italy. Italian has double (or long) consonants, like [[Latin]] (but unlike most modern Romance languages, e.g. [[French language|French]] and [[Spanish language|Spanish]]). As in most Romance languages (with the notable exception of French), stress is distinctive. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Italian (\'\'Italiano\'\')
Spoken in:[[Italy]] and 29 other countries
Region:[[Southern Europe]]
Total speakers: 70 Million
[[List of languages by total speakers|Ranking]]:19
[[Language families and languages|Genetic]]
[[Language families and languages|classification]]:
\n[[Indo-European language family|Indo-European]]
\n [[Italic languages|Italic]]
\n  [[Romance languages|Romance]]
\n   [[Italo-Western languages|Italo-Western]]
\n    [[Italo-Dalmatian languages|Italo-Dalmatian]]
\n     \'\'\'Italian\'\'\'
\n
Official status
Official language of:[[Italy]], [[Switzerland]], [[San Marino]], [[Slovenia]], [[Vatican City]]
Regulated by:[[Accademia della Crusca]]
Language codes
[[ISO 639]]-1: it
ISO 639-2:ita
[[SIL]]:ITN
\n\n==History==\n\nThe origins of italian language are very complex and mostly formalized by [[Dante Alighieri]] mixing south italian dialects, especially from [[Sicilian dialect|Sicilian]], with his native [[Tuscan dialect|Tuscan]] (\"supposed\" to be derived from [[Etruscan language|Etruscan]] and [[Oscan language|Oscan]]).\nThose older italian dialects were hardly influenced by the [[Occitan language|Occitan]] bring by the [[Bards|Bard]] escaping from [[France]] centuries before under Emperor [[Frederick II Holy Roman Emperor]].\nOf the major [[Romance languages]], which were derived from [[Latin language]], Italian is the closest to Latin, although there are other langauges spoken in [[Italy]] which are even closer to Latin, for example [[Sardo logudorese]] language. \n\nItalians say that the best spoken Italian is \'\'lingua toscana in bocca romana\'\' - \'the Tuscan tongue, in a Roman mouth.\' The formative influence on establishing the Tuscan as the elite speech is generally agreed to have been [[Dante Alighieri|Dante]]\'s \'\'[[Divine Comedy|Commedia]],\'\' to which [[Boccaccio]] affixed the title \'\'Divina\'\' in the 14th century. \n\nThe economic power that [[Tuscany]] had at the time, specially considering [[Pisa]]\'s influence, gave its dialect weight, though Venetian remained widespread in the markets and streets of the [[Terra Firma]]. Also, the increasing cultural relevance of [[Florence, Italy|Florence]] in the period of \'\'[[Umanesimo]]\'\' (before [[Renaissance|Rinascimento]]) made its \'\'vulgare\'\' become a standard in art, quickly imported to [[Rome]].\n\n==Classification==\n\nItalian is a member of the [[Italo-Dalmatian languages|Italo-Dalmatian]] group of languages, which is part of the [[Italo-Western languages|Italo-Western]] grouping of the [[Romance languages]], which are a subgroup of the [[Italic languages|Italic]] branch of [[Indo-European language family|Indo-European]].\n\n==Geographic distribution==\n\nItalian is the official language of [[Italy]], [[San Marino]] and an official language in the [[Canton Ticino|Ticino]] and [[Graubünden|Grigioni]] cantons or regions of [[Switzerland]]. It is also the second official language in [[Vatican City]] and in some areas of [[Istria]] in [[Slovenia]] and [[Croatia]] with an Italian minority. It is widely used by immigrant groups in [[Luxembourg]], the [[United States]], [[Brazil]], [[Argentina]] and [[Australia]], and is also spoken in neighbouring [[Malta]] and [[Albania]]. It is spoken, to a much lesser extent, in parts of [[Africa]] formerly under Italian rule such as [[Somalia]], [[Libya]] and [[Eritrea]]. \n\n===Official status===\n\nItalian is an official language of [[Italy]], [[San Marino]], [[Switzerland]], [[Slovenia]] and [[Vatican City]].\n\n===Dialects===\n\nThe [[dialect]]s of Italian identified by the [[Ethnologue]] are Tuscan, Abruzzese, Pugliese (Apulian), Umbrian, Laziale, Central Marchigiano, Cicolano-Reatino-Aquilano, and Molisan. Other dialects are Milanese, Brescian, Bergamasc, Venetian, Modenese, Bolognese, Sicilian, Sardian, and so on, essentially one per city.\nMany of the so-called dialects of Italian spoken around the country are different enough from standard Italian to be considered separate [[language]]s by most [[linguist]]s.\n\nA link to an Italian site with translation features between Italian dialects and Italian: [http://www.dialettando.com]\n\n\n\n==Sounds==\n\nDescription of the sound set of the language. Can include phoneme charts and example words for each phoneme like in [[French language]]. If there is significant discussion here, it is probably best to divide the section into vowels and consonants subsections.\n===Vowels===\n\nItalian has seven vowel phonemes: /a/, /e/, /ɛ/, /o/, /ɔ/, /u/. The words /\'peska/ (fishing) and /\'pɛska/ (peach), both spelled as \"pesca\", show that /e/ and /ɛ/ are in fact two different phonemes. Similarly, the words /\'bot:e/ (barrel) and /\'bɔt:e/ (beatings), both spelled as \"botte\", discriminate /o/ and /ɔ/.\n\n===Consonants===\n\nTwo symbols in a table cell denote the voiceless and voiced consonant, respectively.\n\n{| border=2 cellpadding=2\n!\n![[bilabial consonant|bilabial]]\n![[labiodental consonant|labiodental]]\n![[dental consonant|dental]]\n![[alveolar consonant|alveolar]]\n![[postalveolar consonant|postalveolar]]\n![[palatal consonant|palatal]]\n![[velar consonant|velar]]\n|-\n![[plosive consonant|plosive]]\n|p b\n|\n|t d\n|\n|\n|\n|k g\n|-\n![[nasal consonant|nasal]]\n|m\n|\n|n\n|\n|\n|ɲ\n|\n|-\n![[trill consonant|trill]]\n|\n|\n|\n|r\n|\n|\n|\n|-\n![[flap consonant|flap]]\n|\n|\n|\n|ɾ\n|\n|\n|\n|-\n![[fricative consonant|fricative]]\n|\n|f v\n|\n|s z\n|ʃ\n|\n|\n|-\n![[affricate consonant|affricate]]\n|\n|\n|\n|ʦ ʣ\n|ʧ ʤ\n|\n|\n|-\n![[lateral consonant|lateral]]\n|\n|\n|\n|l\n|\n|ʎ\n|\n|}\n\nThe sound [ŋ] is an [[allophone]] of /n/ when followed by a velar consonant, i.e., /k/ or /g/.\n\nItalian has geminate, or double, consonants, which are distinguished by length. Length is distinctive for all [[consonant]]s except for /z/, /ʃ/, /ʦ/, /ʣ/, /ʎ/ /ɲ/ . \nGeminate plosives and affricates are realized as lengthened closures. Geminate fricatives, nasals, and /l/ are realized as lengthened [[continuant]]s. Geminate /ɾ/ is realized as the trill [r:].\n\n\n\n==Grammar==\n\n===Pronouns===\n\nPersonal pronouns in the subject of a sentence are usually unnecessary in Italian, because the verb ending provides information about the subject (apart some exceptions), and hence the pronouns are used only to emphasize the subject.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
SingularPlural
1st Person\'\'\'io\'\'\' - I\'\'\'noi\'\'\' - we
2nd Person\n\'\'\'tu\'\'\' - you (one person, familiar)\n\n\'\'\'voi\'\'\' - you (plural, familiar)\n
3rd Person\n\'\'\'lei\'\'\' - she
\n\'\'\'Lei\'\'\' - you (one person, polite)
\n\'\'\'lui\'\'\' - he\n
\'\'\'loro\'\'\' - they
\n\'\'\'Loro\'\'\' - you (plural, polite)
\n\n\'\'\'Lei\'\'\' and \'\'\'Loro\'\'\' (sometimes written with a capitalized L) have special meaning in addition to their meanings as \"she\" and \"they\". \'\'\'Lei\'\'\' is the polite form of \'\'\'tu\'\'\' (which is only used for individuals one is familiar with, family members, for children, or for praying to a god), and similarly, \'\'\'Loro\'\'\' is the polite form of \'\'\'voi\'\'\' (but \'\'\'voi\'\'\' or \'\'\'Voi\'\'\' too is a polite form).\n\n\n===Verbs===\n\nItalian verb [[infinitive]]s have one of three endings, either \'\'-are\'\', \'\'-ere\'\', or \'\'-ire\'\'. Most Italian verbs are regular.\n\nQuestions are formed by a rising intonation at the end of the sentence, as in most European languages (see examples below).\n\n====Present Indicative Regular Conjugation Patterns====\n\nThis is the basic conjugation pattern used to indicate that something is occurring now.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
-areSingularPlural
1st Person-o-iamo
2nd Person-i-ate
3rd Person-a-ano
\n\n\'\'Example:\'\'\n\'\'\'mangiare\'\'\', \"to eat\".\n:\'\'\'Io mangio.\'\'\' (or just \'\'\'Mangio.\'\'\') \'\'I eat\'\'.\n:\'\'\'Antonio mangia.\'\'\' \'\'Antonio eats.\'\'\n:\'\'\'Antonio mangia?\'\'\' \'\'Does Antonio eat?\'\'\n:\'\'\'Mangia Antonio?\'\'\' \'\'Does Antonio eat?\'\'\n\n\'\'\'guardare\'\'\', \"to watch\"\n:\'\'\'Noi guardiamo la televisione.\'\'\' (or just \'\'\'Guardiamo la televisione.\'\'\') \'\'We watch television.\'\'\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
-ereSingularPlural
1st Person-o-iamo
2nd Person-i-ete
3rd Person-e-ono
\n\n\'\'Example:\'\'\n\'\'\'leggere\'\'\', \"to read\"\n:\'\'\'Leggono i libri.\'\'\' \'\'They read books.\'\'\n:\'\'\'Leggo il giornale.\'\'\' \'\'I read the newspaper.\'\'\n\nSome regular -ire verbs conjugate normally, and some conjugate according to the -isco pattern. There is no way to tell other than to memorize which are which.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
-ire (normal form)SingularPlural
1st Person-o-iamo
2nd Person-i-ite
3rd Person-e-ono
\n\n\'\'Example:\'\'\n\'\'\'partire\'\'\', \"to leave\"\n:\'\'\'Partite.\'\'\' \'\'You leave.\'\' (plural; used if talking to two or more persons one is familiar with.)\n:\'\'\'Parti.\'\'\' \'\'You leave.\'\' (singular; used if talking to only one person one is familiar with.)\n:\'\'\'Partono.\'\'\' Depending on context, could mean either \'\'You leave\'\' (if addressing more than one person formally), or could also mean \'\'They leave.\'\' \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
-ire (\'\'-isco\'\' form)SingularPlural
1st Person-isco-iamo
2nd Person-isci-ite
3rd Person-isce-iscono
\n\n\'\'Example:\'\'\n\'\'\'capire\'\'\', \"to understand\".\n: \'\'\'Io capisco\'\'\' or just \'\'\'Capisco.\'\'\' \"I understand.\"\n: \'\'\'Capisci?\'\'\' \"Do you understand?\"\n\n\n\n==Writing system==\n\nItalian is written using the [[Latin alphabet]]. Italian uses both [[acute accent]] and [[grave accent]] for marking words with irregular stress.\n\n==Examples==\n\n*cheers (generic toast): \'\'salute\'\' /sa\"lute/ (sall-OO-teh); \'\'cincin\'\' /tSin\"tSin/ (cheen-CHEEN)\n*English: \'\'inglese\'\' /iN\"glEze/ (ing-GLAY-zay)\n*good-bye: \'\'arrivederci\'\' /ar:ive\"dErtSi/ (a-ree-veh-DARE-chee)\n*hello: \'\'ciao\'\' /\"tSAo/ (CHAH-oh) (informal); \'\'buon giorno\'\' /\"bwon \"dZOrno/ (bwon JAWR-noh) (good morning), \'\'buona sera\'\' /\"bwona \"s:era/ (BWO-na SAY-ra) (good evening)\n*how much? \'\'quanto\'\' /\"kwAnto/ (KWAN-tuh) (masculine); \'\'quanta\'\' /\"kwAnta/ (KWAN-tah) (feminine)\n*I don\'t understand: \'\'non capisco\'\' /\"noN ka\"pisko/ (known kah-PEES-kuh)\n*Italian: \'\'italiano\'\' /ita\"ljano/ (ee-tah-LYAN-oh)\n*no: \'\'no\'\' /no/ (nuh)\n*please: \'\'per favore\'\' /\"per favOre/ (per fa-VOAR-ay)\n*sorry: \'\'scusa\'\' /\"skuza/ (SKOO-zah) (familiar); \'\'scusi\'\' /\"skuzi/ (SKOO-zee) (polite)\n*thank you: \'\'grazie\'\' /\"gratzje/ (GRAT-zyeh)\n*that one: \'\'quello\'\' /\"kwEl:o/ (KWEL-luh) (masculine); \'\'quella\'\' /\"kwEl:a/ (KWEL-lah) (feminine)\n*where\'s the bathroom?: \'\'dov\'è il bagno?\'\' /do\"vE il \"baJo/ (duh-vay-eel-BA-\"spanish ñ\"-uh)\n*yes: \'\'sì\'\' /si/ (see)\n*\'\'\'cara\'\'\' or \'\'\'cara mia\'\'\' \'\'(feminine)\'\'; \'\'\'caro\'\'\' or \'\'\'caro mio\'\'\' \'\'(masculine)\'\' - approximately means \'\'my darling\'\' or \'\'my dear\'\'; common term of endearment.\n\nSee [[Common phrases in different languages]] and [[Italian proverbs]].\n\n==External links==\n\n*[http://www.ethnologue.com/show_language.asp?code=ITN Ethnologue report for Italian]\n*[http://www.sprachprofi.de.vu/english/it.htm Free online resources for learners]\n*[http://www.websters-online-dictionary.org/definition/Italian-english/ Italian - English Dictionary]\n*[http://wordreference.com/index.htm/ WordReference.com Italian Dictionary]\n\n[[Category:Romance languages]]\n[[Category:Languages of Switzerland]]\n[[Category:Languages of Italy]]\n\n[[de:Italienische Sprache]]\n[[eo:Itala lingvo]] \n[[et:Itaalia keel]]\n[[fr:Italien]] \n[[it:Lingua Italiana]] \n[[ja:イタリア語]] \n[[la:Lingua Italica]]\n[[nl:Italiaans]] \n[[pl:Język włoski]] \n[[pt:Italiano]]\n[[ro:Limba italiană]]\n[[sl:ItalijanŠČina]]\n[[he:איטלקית]]','',13,'Budhi','20040720111712','',0,0,0,1,0.762445291394,'20040720111712','79959279888287'); INSERT INTO cur VALUES (869,0,'Panonpoé','{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" style=\"margin-left:1em\"\n|+ \'\'\'Panonpoé\'\'\'\n|-\n| colspan=\"2\" align=\"center\" | [[image:panonpoé.jpeg|thumb|300px|Srangéngé]]\n|-\n! bgcolor=\"#ffffc0\" colspan=\"2\" align=\"center\" | \'\'\'Data observasi\'\'\'\n|-\n! align=\"left\" | Jarak rata-rata ti Marcapada\n| [[1 E11 m|150,000,000 km]]
(93,000,000 mi)\n|-\n! align=\"left\" | [[Apparent magnitude|Visual brightness]] (V)\n| −26.8m\n|-\n! align=\"left\" | [[Absolute magnitude]]\n| 4.8m\n|-\n! bgcolor=\"#ffffc0\" colspan=\"2\" align=\"center\" | \'\'\'Physical characteristics\'\'\'\n|-\n! align=\"left\" | Diameter\n| [[1 E9 m|1,392,000]] [[kilometer|km]]\n|-\n! align=\"left\" | Relative diameter (dS/dE)\n| 109\n|-\n! align=\"left\" | Oblateness\n| ~9×10-6\n|-\n! align=\"left\" | Surface area\n| [[1 E18 m²|6.09]] [[scientific notation|×]] 1012 [[square kilometre|km²]]\n|-\n! align=\"left\" | Volume\n| [[1 E27 m³|1.41]] × 1027 [[cubic metre|m³]]\n|-\n! align=\"left\" | Mass\n| [[1 E30 kg|1.9891]] × 1030 [[kilogram|kg]]\n|-\n! align=\"left\" | Relative mass to Earth\n| 333,400\n|-\n! align=\"left\" | Density\n| 1.411 g/cm³\n|-\n! align=\"left\" | Relative density to Earth\n| 0.26\n|-\n! align=\"left\" | Relative density to [[cai|water]]\n| 1.409\n|-\n! align=\"left\" | Surface [[gravity]]\n| 274 m s-2\n|-\n! align=\"left\" | Relative surface gravity\n| 27.9 [[gee|g]]\n|-\n! align=\"left\" | Escape velocity\n| 618 km/s\n|-\n! align=\"left\" | Surface temperature\n| 5780 [[Kelvin|K]]\n|-\n! align=\"left\" | Temperature of [[corona]]\n| 5 × 106 K\n|-\n! align=\"left\" | [[Luminosity]] (LS)\n| 3.827 × 1026 [[joule|J]] s-1\n|-\n! bgcolor=\"#ffffc0\" colspan=\"2\" align=\"center\" | \'\'\'[[Orbit|Orbital]] characteristics\'\'\'\n|-\n! align=\"left\" | Period of rotation\n|  \n|-\n| align=\"right\" | At equator:\n| 27d 6h 36m\n|-\n| align=\"right\" | At 30° latitude:\n| 28d 4h 48m\n|-\n| align=\"right\" | At 60° latitude:\n| 30d 19h 12m\n|-\n| align=\"right\" | At 75° latitude:\n| 31d 19h 12m\n|-\n! align=\"left\" | Period of orbit around
galactic centre\n| 2.2 × 108 years\n|-\n! bgcolor=\"#ffffc0\" colspan=\"2\" align=\"center\" | \'\'\'[[photosphere|Photospheric]] composition\'\'\'\n|-\n! align=\"left\" | [[Hydrogen]]\n| 73.46 %\n|-\n! align=\"left\" | [[Helium]]\n| 24.85 %\n|-\n! align=\"left\" | [[Oxygen]]\n| 0.77 %\n|-\n! align=\"left\" | [[Carbon]]\n| 0.29 %\n|-\n! align=\"left\" | [[Iron]]\n| 0.16 %\n|-\n! align=\"left\" | [[Neon]]\n| 0.12 %\n|-\n! align=\"left\" | [[Nitrogen]]\n| 0.09 %\n|-\n! align=\"left\" | [[Silicon]]\n| 0.07 %\n|-\n! align=\"left\" | [[Magnesium]]\n| 0.05 %\n|-\n! align=\"left\" | [[Sulfur]]\n| 0.04 %\n|}\n\'\'\'Panonpoé\'\'\' nyaéta [[béntang]] na [[tatasurya]] urang. [[Planét]] [[Marcapada|Bumi]] jeung sakabéh dulurna, boh [[planét terestrial]] atawa [[raksasa gas]], [[orbit|ngurulingan]] Panonpoé. Nu séjénna nu ngurilingan Panonpoé kayaning [[astéroid]], [[météoroid]], [[komét]], [[objék Trans-Neptunius]], jeung, tangtu bae, [[kebul]].\n\n== Ciri fisik jeung nu séjénna ==\n\nThe Sun is a [[main sequence]] star, with a [[spectral class]] of G2, meaning that it is somewhat bigger and hotter than the average star but far smaller than a [[blue giant]] star. A G2 star has a [[main sequence]] lifetime of about 10 billion years, and the Sun is probably about 5 billion years old, as determined by [[nucleocosmochronology]].\n\nThe Sun is a near-perfect sphere, with an oblateness estimated at about 9 millionths, which means the polar diameter differs from the equatorial by at most 10 km or so. This is in good part because the centrifugal effect of the Sun\'s rather sedate rotation is 18 million times weaker than its surface gravity (at the equator).\n\nAt the center of the Sun, where its density is 1.5 × 105 kg m-3, thermonuclear reactions ([[nuclear fusion]]) convert hydrogen into helium. 3.8 × 1038 [[proton|protons]] (hydrogen nuclei) are converted to helium every second. This releases energy which escapes from the surface of the Sun in the form of [[electromagnetic radiation]] and [[neutrino]]s (and to a smaller extent as the kinetic and thermal energy of solar wind plasma and as the energy in the Sun\'s magnetic field). [[Physics|Physicists]] are able to replicate thermonuclear reactions with [[hydrogen bomb]]s. Sustained nuclear fusion on Earth for electricity generation may be possible in the future, with nuclear fusion reactors.\n\nAll [[matter]] in the Sun is in the form of [[plasma]] due to its extreme temperature. This makes it possible for the Sun to rotate faster at its equator than it does at higher latitudes, since the Sun is not a solid body. The differential rotation of the Sun\'s latitudes causes its [[magnetic field]] lines to become twisted together over time, causing magnetic field loops to erupt from the Sun\'s surface and trigger the formation of the Sun\'s dramatic [[sunspot]]s and [[solar prominence]]s. The solar activity cycle includes old magnetic fields being stripped off the Sun\'s surface starting from one pole and ending at the other.\n\nThe [[corona]] has 1011 atoms/m3, and the [[photosphere]] has 1023 atoms/m3.\n\nFor some time it was thought that the number of [[neutrino]]s produced by the nuclear reaction in the Sun was only one third of the number predicted by theory, a result that was termed the [[solar neutrino problem]]. When it was recently found that neutrinos had mass, and could therefore transform into harder-to-detect varieties of neutrinos while en route from the Sun to Earth, measurement and theory were reconciled.\n\nTo obtain an uninterrupted view of the Sun, the [[European Space Agency]] and [[NASA]] cooperatively launched the [[Solar and Heliospheric Observatory]] (SOHO) on [[December 2]], [[1995]].\n\nObservation of the Sun can reveal such phenomena as:\n\n* [[Sunspot]]s\n* [[Facula]]e\n* [[Granule]]s\n* [[Solar flare]]s\n* [[Solar prominence]]s\n** [[quiescent prominence]]s\n** [[eruptive prominence]]s\n*[[Coronal mass ejection]]\n\n\'\'\'Caution: looking directly at the Sun can damage the [[retina]] and one\'s [[eyesight]].\'\'\'\n\nThe [[Astronomical symbols|astronomical symbol]] for the Sun is a [[circle with a point at its centre]].\n\n[[Image:panonpoé_SOHO.gif|thumb|300px|Ngontabna panonpoé nu karékam ku alat [[Solar and Heliospheric Observatory|SOHO]]]].\n\n===Tempo ogé===\n* [[Astronomical twilight]]\n* [[Solar radiation]]\n* [[Solar radius]]\n* [[Solar energy]]\n* [[Solar wind]]\n** [[Aurora borealis]]\n** [[Aurora australis]]\n* [[Photosphere]]\n* [[Chromosphere]]\n* [[Corona]]\n* [[Airglow]]\n* [[Eclipse]]\n* [[Timeline of solar astronomy]]\n* [[Solar deity]]\n* [[Daystar]]\n\n===Tumbu kaluar===\n* [http://sohowww.nascom.nasa.gov/data/realtime-images.html Current SOHO snapshots]\n* [http://soi.stanford.edu/data/farside/index.html Far-Side Helioseismic Holography] from [http://www.stanford.edu Stanford]\n* [http://sunearth.gsfc.nasa.gov/eclipse/eclipse.html NASA Eclipse homepage]\n* [http://sohowww.nascom.nasa.gov/ Nasa SOHO (Solar & Heliospheric Observatory) satellite]\n* [http://soi.stanford.edu/results/sounds.html Solar Sounds] from [http://www.stanford.edu Stanford] \n* [http://www.spaceweather.com Spaceweather.com]\n
\n\n{{Footer_SolarSystem}}\n\n[[Category:Tatasurya]]\n[[Category:Béntang]]\n\n[[ar:شمس]]\n[[id:Matahari]]\n[[ms:Matahari]]\n[[ca:Sol]]\n[[cs:Slunce]]\n[[cy:Haul]]\n[[da:solen]]\n[[de:Sonne]]\n[[en:Sun]]\n[[et:Päike]]\n[[es:Sol]]\n[[eo:Suno]]\n[[fr:Soleil]]\n[[hr:Sunce]]\n[[he:השמש]]\n[[ia:Sol]]\n[[it:Sole]]\n[[ku:Roj]]\n[[la:Sol]]\n[[lt:Saulė]]\n[[hu:Nap (égitest)]]\n[[nah:Tonatiuh]]\n[[ja:太陽]]\n[[nl:Zon]]\n[[no:Solen]]\n[[nds:Sünn]]\n[[pl:Słońce]]\n[[pt:Sol]]\n[[ro:Soare]]\n[[ru:Солнце]]\n[[simple:Sun]]\n[[sk:Slnko]]\n[[sl:Sonce]]\n[[fi:Aurinko]]\n[[sv:Solen]]\n[[uk:Сонце]]\n[[zh:太阳]]','',3,'Kandar','20041201070148','',0,0,0,0,0.629052082835,'20050126082014','79958798929851'); INSERT INTO cur VALUES (870,0,'Data_mining','\'\'\'Data mining\'\'\', oge dipikanyaho salaku \'\'\'pangaweruh-pamanggih dina database (KDD)\'\'\', nyaeta kabiasaan neangan sacara otomatis tina simpenan [[data]] nu loba keur pola. Keur migawekeun ieu, data mining make teknik komputer tina [[statistik]] sarta [[Pattern recognition|pola rekonstruksi]].\n\nData mining has been defined as \"The nontrivial extraction of implicit, previously unknown, and potentially useful information from data\" [1] and \"The science of extracting useful information from large data sets or databases\" [2]. Although it is usually used in relation to analysis of data, data mining, like [[artificial intelligence]], is an umbrella term and is used with varied meaning in a wide range of contexts.\n\nUsed in the technical context of [[data warehousing]] and analysis data mining is neutral. However, it sometimes has a more pejorative usage that implies imposing patterns (and particularly causal relationships) on data where none exist. This imposition of irrelevant, misleading or trivial attribute correlation is more properly criticized as \"data dredging\" in the statistical literature.\n\nUsed in this latter sense, data dredging implies scanning the data for any relationships, and then when one is found coming up with an interesting explanation. (This is also referred to as \"overfitting the model\".) The problem is that large data sets invariably happen to have some exciting relationships peculiar to that data. Therefore any conclusions reached are likely to be highly suspect. In spite of this, some exploratory data work is always required in any applied statistical analysis to get a feel for the data, so sometimes the line between good statistical practice and data dredging is less than clear. \n\nA more significant danger is finding correlations that do not really exist. Investment analysts appear to be particularly vulnerable to this. In his book [[Where Are the Customers\' Yachts?]] ISBN 0471119792 (1940), [[Fred Schwed, Jr]], wrote: \"There have always been a considerable number of pathetic people who busy themselves examining the last thousand numbers which have appeared on a roulette wheel, in search of some repeating pattern. Sadly enough, they have usually found it.\"\n\nMost data mining efforts are focused on developing a finely-grained, highly detailed model of some large data set. In [[Data Mining For Very Busy People]] [3], researchers at [[West Virginia University]] and the [[University of British Columbia]] discuss an alternate method that involves finding the minimal differences between elements in a data set, with the goal of developing simpler models that represent relevant data.\n\nThere are also privacy concerns associated with data mining. For example, if an employer has access to medical records, they may screen out people with diabetes or have had a heart attack. Screening out such employees will cut costs for insurance, but it creates ethical and legal problems. \n\nData mining government or commercial data sets for national security or law enforcement purposes has also raised privacy concerns. [4]\n\nThere are many legitimate uses of data mining. For example, a database of prescription drugs taken by a group of people could be used to find combinations of drugs with an adverse reactions. Since the combination may occur in only 1 out of 1000 people, a single case may not be apparent. A project involving pharmacies could reduce the number of drug reactions and potentially save lives. Unfortunately, there is also a huge potential for abuse of such a database.\n\nBasically, data mining gives information that wouldn\'t be available otherwise. It must be properly interpreted to be useful. When the data collected involves individual people, there are many questions concerning privacy, legality, and ethics.\n\nThe [[a priori algorithm]] is the most fundamental algorithm used in data mining.\n\n==Tempo oge==\n*[[Database]]\n*[[Data warehouse]]\n*[[Document warehouse]]\n*[[Machine learning]]\n*[[Pattern recognition]]\n*[[Statistics]]\n*[[Artificial intelligence]]\n*[[Statistik deskriptif]]\n*[[Hypothesis testing]]\n*[[Loyalty card]]\n*[[Business intelligence]]\n*[[Business performance management]]\n*[[Text mining]]\n\n==Rujukan==\n[1] W. Frawley and G. Piatetsky-Shapiro and C. Matheus, Knowledge Discovery in Databases: An Overview. AI Magazine , Fall 1992, pgs 213-228.\n\n[2] D. Hand, H. Mannila, P. Smyth: Principles of Data Mining. MIT Press, Cambridge, MA, 2001.\n\n[3] T. Menzies, Y. Hu, [[Data Mining For Very Busy People]]. IEEE Computer, October 2003, pgs 18-25.\n\n[4] K.A. Taipale, [http://www.stlr.org/cite.cgi?volume=5&article=2 Data mining and Domestic Security: Connecting the Dots to Make Sense of Data], [http://www.advancedstudies.org/ Center for Advanced Studies in Science and Technology Policy]. 5 Columbia Sci. & Tech. L. Rev 2 (December 2003).\n\n==Tumbu kaluar==\n* [http://www.bitpipe.com/rlist/term/Data-Mining.html Data Mining whitepapers, webcasts and case studies]\n\n\n\n[[de:Data-Mining]]\n[[fr:Exploration de données]]\n[[nl:Datamining]]\n[[ja:データマイニング]]\n[[pl:Eksploracja danych]]\n\n[[Category: Data management]]','',13,'Budhi','20050218014903','',0,0,0,0,0.058349923258,'20050218014903','79949781985096'); INSERT INTO cur VALUES (871,0,'Data','\'\'Alternate uses: See [[Data (disambiguation)]]\'\'\n\n\'\'\'Datum\'\'\' nyaeta \'\'[[statement]] nu ditarima dina [[face value]]\'\'.\n\'\'\'Data\'\'\' bentuk loba tina \'\'[[datum]]\'\'. \nHal nu penting dina kelas nu gede nyaeta [[measurement|ukuran]] atawa [[observation|panalungtikan]] tina [[variable|variabel]].\nHal ieu saperti wilangan, kecap atawa gambar.\n\n==Etymology==\nThe word \'\'data\'\' is the \nplural of [[Latin]] \'\'datum\'\', neuter past participle of \'\'dare\'\', \"to give\",\nhence \"something given\".\nThe [[past participle]] of \"to give\" has been used for millennia,\nin the sense of a statement accepted at face value;\none of the works of [[Euclid]], circa 300 BC,\nwas the \'\'Dedomena\'\' (in Latin, \'\'Data\'\').\nIn discussions of problems in geometry, mathematics, engineering, and so on,\nthe terms \'\'givens\'\' and \'\'data\'\' are used interchangeably.\nSuch usage is the origin of \'\'data\'\' as a concept in [[computer science]]:\n\'\'data\'\' are numbers, words, images, etc., accepted as they stand.\n\n==Usage in English==\nIn English,\nthe word \'\'[[datum]]\'\' is still used in the general sense of \"something given\",\nand more specifically in [[cartography]], [[geography]], and [[geology]] to mean a reference point, reference line, or reference surface.\nThe Latin plural \'\'data\'\' is also used as a plural in English,\nbut it is also commonly treated as a [[mass noun]] and used in the [[singular]].\nFor example,\n\"This is all the data from the experiment\". \nThis usage is inconsistent with the rules of Latin grammar,\nwhich would suggest \"These are the data ...\",\neach measurement or result being a single \'\'datum\'\'.\nHowever,\ngiven the variety and irregularity of [[English plural]] constructions,\nthere seem to be no grounds for arguing that \'\'data\'\' is incorrect as a singular mass noun in English.\n\n==Uses of \'\'data\'\' in computing==\n\'\'Raw data\'\' are [[number]]s, [[character]]s, [[image]]s or other outputs from devices to convert physical quantities into symbols,\nin a very broad sense. \nSuch data are typically further [[process|processed]] by a human or [[input]] into a [[computer]], [[storage|stored]] and processed there, or transmitted ([[output]]) to another human or computer.\n\'\'Raw data\'\' is a relative term; data processing commonly occurs by stages,\nand the \"processed data\" from one stage may be considered the \"raw data\" of the next.\n\nMechanical computing devices are classified according to the means by which they represent data. An [[analog computer]] represents a datum as a voltage, distance, position, or other physical quantity. A [[digital computer]] represents a datum as a sequence of symbols drawn from a fixed [[alphabet]]. The most common digital computers use a binary alphabet, that is, an alphabet of two characters, typically denoted \"0\" and \"1\". More familiar representations, such as numbers and letters, are then constructed from the binary alphabet.\n\nSome special forms of data are distinguished. A [[computer program]] is a collection of data which can be interpreted as instructions. Most computer languages make a distinction between programs and the other data on which programs operate, but in some languages, notably [[Lisp]] and similar languages, programs are essentially indistinguishable from other data. It is also useful to distinguish [[metadata]], that is, a description of other data. The prototypical example of metadata is the library catalog, which is a description of the contents of books.\n\n==Meaning of a data and information==\nData on its own has no meaning, only when interpreted by some kind of [[data processing system]] does it take on meaning and become [[information]].\nPeople or computers can find [[pattern|patterns]] in data to perceive information, and information can be used to enhance [[knowledge]]. Since knowledge is prerequisite to [[wisdom]], we always want more data and information. But, as modern societies verge on [[information overload]], we especially need better ways to find patterns. \n\n==Tempo oge== \n[[data processing]] -- [[data mining]] -- [[data warehouse]] -- [[datasheet]] -- [[Data recovery]] -- [[Database]]\n\n\'\'This article (or an earlier version of it) contains material from [[FOLDOC]], used with [[Public Domain Resources/Foldoc license|permission]].\'\'\n\n[[da:Data]]\n[[de:Daten]]\n[[fa:داده]]\n[[ko:데이터]]\n[[ja:データ]]\n[[pt:Dados]]\n[[sv:Data]]\n[[simple:Data]]','',13,'Budhi','20050218024228','',0,0,0,0,0.113002429303,'20050218024228','79949781975771'); INSERT INTO cur VALUES (872,0,'Abad_ka-19','([[Abad ka-18]] - \'\'\'abad ka-19\'\'\' - [[abad ka-20]] - [[Abad|daptarna]])\n\nSalaku catetan [[waktu]] nu kaliwat, \'\'\'abad ka-19\'\'\' nyaéta [[abad]] taun-taunna antara [[1801]]-[[1900]].\n\nAbad ka-19 mindeng pisan ditujul ku sajarahwan salaku \"mangsa isme\", nu nyirikeun lobana [[isme]] nu tumuwuh dina mangsa harita. No other century could boast the massive social changes that took place in the 1800\'s. While the 20th century was the century of [[politics]] and science, the 19th was the century of society. For the first time, the rights of the workers and common man were being questioned. Rarely in previous times did such a massive movement across Europe, into the Americas, and even parts of Asia occur. [[1848]] alone felt the effects of the new ideas as European cities from [[Paris]] to [[Vienna]] were in uprise. The 19th century was a contrast from old to new, the old monarchies and feudal systems to the new capitalist world and [[democracy]]. The 19th century was the opening stage for the modern world.\n\n== Kajadian ==\n* The [[Little Ice Age]] ended.\n* [[Napoleon Bonaparte|Napoleon]], who conquers much of Europe, is ultimately defeated in [[1815]]; some old European regimes are restored, others not.\n* The modern city of [[Singapore]] is established when Sir [[Thomas Stamford Raffles]] of the [[British East India Company]] acquires land on the island from the Sultan of [[Johore]] in [[1819]].\n* The \'\'[[Libertadores]]\'\' lead most of [[Latin America]] to independence.\n* [[Industrial Revolution]] continues and spreads, developments include the [[Rail Transport]], [[telegraph]], and [[telephone]].\n* [[Belgium]] becomes independent in 1830 after a massive uprising against the Dutch. Leopold becomes the first king of Belgium.\n* [[Belgium]] will be the second industrial power in the world by the middle of the 19th century.\n* [[Leopold II of Belgium|Leopold II]], son of [[Leopold I of Belgium|Leopold]], becomes the second king of Belgium. He buys the gigantic territory of [[Congo Free State|Congo]] in Africa with his own fortune and will later (1908) offer it to Belgium.\n* Discovery of the relationships between magnetism and electricity and light by [[Hans Christian Orsted|Hans Christian Ørsted]] and [[James Clerk Maxwell]]. (See:[[electromagnetism]])\n* Mass migration from [[Europe]] to the [[United States]].\n* During the reign of [[Victoria of the United Kingdom|Queen Victoria]], the [[United Kingdom]] experiences the [[Victorian Age]], which is the age in which the United Kingdom is the leading economic power in the world.\n* Political revolution and constitutional reform across Europe severely limits powers of monarchs, advances democracy.\n* The religious revival of the [[Second Great Awakening]] in the eastern [[United States]] and [[Canada]] gives rise to unique, American, [[Christian]] religions during the era of [[Restorationism]]\n* [[Gold]] discovered in [[Australia]] and throughout the west of the [[United States]], leading to huge increases in national wealth and encouraging mass migration of free settlers there.\n* [[Crimean War]] fought between [[Russia]] and an alliance of the [[United Kingdom of Great Britain and Ireland|United Kingdom]], [[France]], the [[Ottoman Empire]], [[1854]] to [[1856]].\n* [[Slavery]] ended in British colonies and in America. See [[American Civil War]], [[1861]] to [[1865]]. End of global slave trade enforced by British navy.\n* [[Charles Darwin]] revolutionizes biology with his theories of [[evolution]], [[1858]].\n* [[Europe|Europeans]] conquer and colonize most of [[History of Africa|Africa]] and parts of [[Asia]].\n* [[Karl Marx]] writes the [[The Communist Manifesto|Communist Manifesto]], encouraging workers to revolt against owners.\n* [[Meiji Restoration]] in [[1868]] opens [[Japan]] to modern influences and returns the emperor to power.\n* [[History of Germany|Germany]] and [[Italy/History|Italy]] are formed as nations, uniting from groups of small kingdoms and city states. \n* [[Railroad|Railroads]] make fast mass transit available to many. [[Transcontinental railroad]]s built, including the [[Panama Railway]] in [[1855]], the [[First Transcontinental Railroad (North America)|US Transcontinental Railroad]] finished in [[1869]] linking to west in the [[United States]], and the [[Canadian National Railway]] in [[1885]].\n* The [[Suez Canal]] is opened, connecting Europe and the Mediterranean to the Indian Ocean and Asia in [[1869]].\n* The [[British]] begin their so-called \"forward movement\" to extend control over the [[Malay States]] with the signing of the [[Pangkor Treaty]] in [[1874]].\n* The electric [[telegraph]] and undersea cables make instant global communication possible for the first time.\n* [[Postage Stamp]]s and diamond-shaped paper sheets which folded to form [[envelopes]] for carrying letters devised and introduced in [[Great Britain]], and soon thereafter in many other countries, leading to establishment of the [[Universal Postal Union]].\n* Manufactured goods become widely available by mail order\n\n==Inohong==\n===Pamingpin dunya===\n* [[Alexander II ti Rusia]], Sar\n* [[Otto von Bismarck]], pulitisi Jérman\n* [[Simón Bolívar]] South American Liberator\n* [[Empress Dowager Cixi]] of China\n* [[Franz Joseph]], Kaisar Austria\n* [[Abraham Lincoln]], présidén AS\n* [[Napoleon Bonaparte]], Kaisar Prancis\n* [[Napoleon III ti Prancis|Napoleon III]], Kaisar Prancis\n* [[José de San Martín]], South American Liberator\n* [[Victoria ti Inggris|Ratu Victoria]], Ratu Karajaan Inggris\n* [[Giuseppe Garibaldi]], unifier of Italy\n\n===Élmuwan===\n* [[Gregor Mendel]], ahli biologi\n* [[Charles Darwin]], ahli biologi\n* [[Thomas Alva Edison]], inventor\n* [[Gottlob Frege]], ahli matematik, logika, jeung filsafat\n* [[Carl Friedrich Gauss]], ahli matematik, fisika, jeung astronomi\n* [[Louis Pasteur]], ahli biologi\n* Dr. [[John Snow]], the founder of epidemiology\n\n===Seniman===\n* [[Ludwig van Beethoven]], composer\n* [[Antonio de La Gandara]], painter\n* [[Johann Wolfgang von Goethe]], author, thinker\n* [[Giuseppe Verdi]], composer\n* [[Richard Wagner]], composer\n* [[Antonin Dvorak]], composer\n* [[Vincent van Gogh]], painter\n\n===Sastrawan===\n* [[Samuel Taylor Coleridge]], poet, critic, thinker\n* [[Charles Dickens]], author\n* [[Benjamin Disraeli]], novelist and politician\n* [[Victor Hugo]], author\n* [[Edgar Allan Poe]], author\n* [[Mark Twain]] (Samuel Clemens), author\n\n===Ageman===\n* [[Joseph Smith, Jr.]], religious leader, founder of [[Mormonism]]\n* [[Brigham Young]], Mormon religious leader\n* [[Nikolai of Japan]], religious leader who introduced [[Eastern Orthodox|Eastern Orthodoxy]] into Japan.\n\n===Filsafat===\n* [[Friedrich Nietzsche]]\n\n===Pulitik===\n* [[Karl Marx]], ahli filsafat pulitis jeung ékonomi\n* [[William Morris]], social reformer\n\n\n== Inventions, discoveries, introductions ==\n* [[Automobile]]\n* [[Electric light]]\n* [[Film|Motion pictures]]\n* [[Phonograph]]\n* [[Photography]]\n* [[Repetition rifle]]\n* [[Railroad]] [[Locomotive]]\n* [[Steamship]]\n* [[Telegraph]]\n* [[Telephone]]\n\n==Dékade jeung taun==\n{| border=\"0\" cellpadding=\"5\"\n|style=\"background: #eeeeee\"|\'\'\'[[1790-an]]\'\'\'\n|[[1790]]\n|[[1791]]\n|[[1792]]\n|[[1793]]\n|[[1794]]\n|[[1795]]\n|[[1796]]\n|[[1797]]\n|[[1798]]\n|[[1799]]\n|-\n|style=\"background: #ffddcc\"|\'\'\'[[1800-an]]\'\'\'\n|[[1800]]\n|style=\"background: #ffeedd\"|[[1801]]\n|style=\"background: #ffeedd\"|[[1802]]\n|style=\"background: #ffeedd\"|[[1803]]\n|style=\"background: #ffeedd\"|[[1804]]\n|style=\"background: #ffeedd\"|[[1805]]\n|style=\"background: #ffeedd\"|[[1806]]\n|style=\"background: #ffeedd\"|[[1807]]\n|style=\"background: #ffeedd\"|[[1808]]\n|style=\"background: #ffeedd\"|[[1809]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1810-an]]\'\'\'\n|[[1810]]\n|[[1811]]\n|[[1812]]\n|[[1813]]\n|[[1814]]\n|[[1815]]\n|[[1816]]\n|[[1817]]\n|[[1818]]\n|[[1819]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1820-an]]\'\'\'\n|[[1820]]\n|[[1821]]\n|[[1822]]\n|[[1823]]\n|[[1824]]\n|[[1825]]\n|[[1826]]\n|[[1827]]\n|[[1828]]\n|[[1829]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1830-an]]\'\'\'\n|[[1830]]\n|[[1831]]\n|[[1832]]\n|[[1833]]\n|[[1834]]\n|[[1835]]\n|[[1836]]\n|[[1837]]\n|[[1838]]\n|[[1839]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1840-an]]\'\'\'\n|[[1840]]\n|[[1841]]\n|[[1842]]\n|[[1843]]\n|[[1844]]\n|[[1845]]\n|[[1846]]\n|[[1847]]\n|[[1848]]\n|[[1849]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1850-an]]\'\'\'\n|[[1850]]\n|[[1851]]\n|[[1852]]\n|[[1853]]\n|[[1854]]\n|[[1855]]\n|[[1856]]\n|[[1857]]\n|[[1858]]\n|[[1859]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1860-an]]\'\'\'\n|[[1860]]\n|[[1861]]\n|[[1862]]\n|[[1863]]\n|[[1864]]\n|[[1865]]\n|[[1866]]\n|[[1867]]\n|[[1868]]\n|[[1869]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1870-an]]\'\'\'\n|[[1870]]\n|[[1871]]\n|[[1872]]\n|[[1873]]\n|[[1874]]\n|[[1875]]\n|[[1876]]\n|[[1877]]\n|[[1878]]\n|[[1879]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1880-an]]\'\'\'\n|[[1880]]\n|[[1881]]\n|[[1882]]\n|[[1883]]\n|[[1884]]\n|[[1885]]\n|[[1886]]\n|[[1887]]\n|[[1888]]\n|[[1889]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1890-an]]\'\'\'\n|[[1890]]\n|[[1891]]\n|[[1892]]\n|[[1893]]\n|[[1894]]\n|[[1895]]\n|[[1896]]\n|[[1897]]\n|[[1898]]\n|[[1899]]\n|-\n|style=\"background: #ffddcc\"|\'\'\'[[1900-an]]\'\'\'\n|style=\"background: #ffeedd\"|[[1900]]\n|[[1901]]\n|[[1902]]\n|[[1903]]\n|[[1904]]\n|[[1905]]\n|[[1906]]\n|[[1907]]\n|[[1908]]\n|[[1909]]\n|}\n\n[[af:19de eeu]]\n[[ast:Sieglu XIX]]\n[[bg:19 век]]\n[[ca:Segle XIX]]\n[[cs:19. století]]\n[[da:19. århundrede]]\n[[de:19. Jahrhundert]]\n[[el:19ος αιώνας]]\n[[en:19th century]]\n[[eo:19-a jarcento]]\n[[es:Siglo XIX]]\n[[et:19. sajand]]\n[[fi:1800-luku]]\n[[fr:XIXe siècle]]\n[[fy:19e ieu]]\n[[he:המאה ה-19]]\n[[hr:19. stoljeće]]\n[[hu:19. század]]\n[[io:19ma yar-cento]]\n[[it:XIX secolo]]\n[[ja:19世紀]]\n[[ko:19세기]]\n[[ku:Sedsala 19\'an]]\n[[la:Saeculum 19]]\n[[lb:19. Joerhonnert]]\n[[nl:19e eeuw]]\n[[no:19. århundre]]\n[[pl:XIX wiek]]\n[[pt:Século XIX]]\n[[ro:Secolul XIX]]\n[[ru:XIX век]]\n[[simple:19th century]]\n[[sl:19. stoletje]]\n[[sv:1800-talet]]\n[[tr:19. yüzyıl]]\n[[uk:19 століття]]\n[[wa:19inme sieke]]\n[[zh:19世纪]]','',3,'Kandar','20050215082323','',0,0,0,0,0.455424139954,'20050215082323','79949784917676'); INSERT INTO cur VALUES (873,0,'Titik_estimasi','Dina [[statistik]], \'\'\'titik estimasi\'\'\' ngalibatkeun [[statistical sample|sampel]] [[data]] keur ngitung hiji nilai anu ngarupakeun \"best guess\" tina [[parameter]] populasi (fixed atawa random) nu teu dipikanyaho.\n\nDina kaayaan nu leuwih formal, ngarupakeun pamakean titik [[estimator|estimasi]] tina data.\n\n\'\'Pendekatan, metoda...\'\'','',13,'Budhi','20040906040817','',0,0,0,0,0.658967837533,'20040906040839','79959093959182'); INSERT INTO cur VALUES (874,0,'Statistical_sample','Hiji \'\'\'sampel\'\'\' mangrupakeun bagian tina hiji [[populasi statistik|populasi]] anu ditalungtik sabenerna. Dina elmu pangaweruh praktis, urang merlukeun yen sampel dipilih ku rupa-rupa cara supaya mere gambaran [[bias (statistics)|bias]] tina populasi. Lamun [[statistical inference|kaputusan statistik]] bakal digunakeun, mangka kudu aya jalan keur nganyahokeun probibiliti dina milih unggal sampel. Lamun probabiliti tina sampel nu beda sakabehna sarua, upamana, métodena disebut [[sampel acak basajan|sampling acak basajan]].\n\n\'\'Tempo ogé\'\': [[Sampling (statistics)]]','',3,'Kandar','20041124054924','',0,0,0,0,0.857828195141,'20041124054924','79958875945075'); INSERT INTO cur VALUES (875,0,'Prinsip_likelihood','In [[statistik]],\nthe \'\'\'likelihood principle\'\'\' is a controversial principle of [[statistical inference]] which asserts that all of the [[information]] in a [[Sampling (statistics)|sample]] is contained in the [[likelihood function]].\n\nA [[likelihood function]] is a [[conditional probability|conditional probability distribution]] considered as a function of its second argument, holding the first fixed. For example, consider a model which gives the [[probability density function]] (in the discrete case, a probability mass function) of observable [[random variable]]s \'\'X\'\' as a function of a parameter θ.\nThen for a specific value of \'\'x\'\', the function L(θ) = P(\'\'X\'\' = \'\'x\'\' | θ) is a likelihood function of θ. Two likelihood functions are considered equivalent if either is a scalar multiple of the other; the likelihood principle says that all information relevant to inferences about the value of θ is found in the equivalence class.\n\n==Conto==\n\nAnggap\n\n*\'\'X\'\' jumlah sukses dina lima kali [[Bernoulli trial|percobaan Bernoulli]] nu [[statistical independence|bebas]], mibanda probabiliti sukses θ dina unggal percobaan, sarta\n*\'\'Y\'\' ngarupakeun jumlah percobaan Bernoulli bebas nu diperlukeun keur meunang tilu sukses, nu mibanda oge probabiliti sukses θ unggal percobaan.\n\nMangka observasi yen \'\'X\'\' = 3 nyababkeun fungsi likelihood \n\n:L(\\theta)=10\\theta^3(1-\\theta)^2\n\nsarta observasi yen \'\'Y\'\' = 5 nyababkeun fungsi likelihood \n\n:L(\\theta)=6\\theta^3(1-\\theta)^2.\n\nIeu sarua sabab hasil kali skala. Prinsip likelihood nyebutkeun yen kaputusan nu digambarkuen ngadeukeutan nilai θ kudu sarua dina dua kasus eta.\n\nBeda antara observing \'\'X\'\' = 3 jeung observing \'\'Y\'\' = 5 ngan ukur dina [[desain percobaan]]: dina hiji kasus, hiji mibanda kaputusan jentre keur nyoba lima kali; dinu sejenna, nyoba tilu sukses nu di-observasi. \'\'Hasil\'\'-na sarua dina dua kasus eta. Sanajan kitu, prinsip likelihood kadangkala netepkeun yen:\n\n:\'\'Kaputusan kudu gumantung \'\'\'ngan kana hasil\'\'\' percobaan, sarta \'\'\'lain kana desain\'\'\' percobaan.\'\'\n\n==Hukum likelihood==\n\nA related concept is the \'\'\'law of likelihood\'\'\', the notion that the extent to which the evidence supports one parameter value or hypothesis against another is equal to the ratio of their likelihoods.\nThat is, P(\'\'X\'\' | \'\'a\'\')/P(\'\'X\'\' | \'\'b\'\') is the degree to which the data \'\'X\'\' support parameter value or hypothesis \'\'a\'\' against \'\'b\'\'.\nIf this ratio is 1, the evidence is indifferent,\nand if greater or less than 1, the evidence supports \'\'a\'\' against \'\'b\'\' or vice versa.\n\nCombining the likelihood principle with the law of likelihood yields the consequence that the parameter value which maximizes the likelihood function is the value which is most strongly supported by the evidence.\nThis is the basis for the widely-used [[maximum likelihood|method of maximum likelihood]].\n\n== Historical remarks ==\n\nThe likelihood principle was first identified by that name in print in 1962\n(Barnard et al., Birnbaum, and Savage et al.),\nbut arguments for the same principle, unnamed, and the use of the principle in applications goes back to the works of [[Ronald A. Fisher|R.A. Fisher]] in the [[1920]]s. \nThe law of likelihood was identified by that name by [[Ian Hacking|I. Hacking]] (1965).\nMore recently the likelihood principle as a general principle of inference has been championed by [[Anthony W.F. Edwards]].\nThe likelihood principle has been applied to the [[philosophy of science]] by [[Richard M. Royall|R. Royall]].\n\n== Arguments for and against the likelihood principle ==\n\nThe likelihood principle is not universally accepted. \nSome widely-used methods of conventional statistics,\nfor example many [[tes hipotesa statistik|significance test]]s, are not consistent with the likelihood principle. By contrast, a [[likelihood-ratio test]] is based on the principle. \nLet us briefly consider some of the arguments for and against the likelihood principle.\n\n===Arguments in favor of the likelihood principle===\n\nFrom a Bayesian point of view, the likelihood principle is a consequence that falls out of [[Bayes\' theorem]].\nAn observation \'\'A\'\' enters the formula,\n\n:P(B|A) = \\frac{P(A|B)\\;P(B)}{P(A)} \n = \\frac{P(A|B)\\;P(B)}{\\sum_{B\'}P(A|B\')\\;P(B\')}\n\nonly through the likelihood function, P(A|B).\nIn general,\nobservations come into play through the likelihood function,\nand only through the likelihood function;\nno other mechanism is needed.\n\n===Arguments against the likelihood principle===\n\nThe likelihood principle implies that any event that did not happen has no effect on an inference, since if an unrealized event does affect an inference then there is some information not contained in the likelihood function.\nHowever, unrealized events do play a role in some common statistical methods.\nFor example, the result of a [[tes hipotesa statistik|significance test]] depends on the probability of a result as extreme or more extreme than the observation.\nThus, to the extent that such methods are accepted, the likelihood principle is denied.\n\nThe likelihood principle also yields results which seems to some people to be apparently paradoxical results.\nA commonly cited example is the [[optional stopping problem]].\nSuppose I tell you that I tossed a coin 10 times and observed 7 heads. \nYou might make some inference about the probability of heads. \nSuppose now I tell that I tossed the coin until I observed 7 heads, and I tossed it 10 times. Will you now make some different inference?\n\nThe likelihood function is the same in both cases: it is proportional to\n\n:p^7 \\; (1-p)^3\n\nAccording to the likelihood principle,\nthe inference should be the same in either case.\nBut this may seem to be something fishy;\nit might seem possible to \'\'argue to a foregone conclusion\'\'\nby simply tossing the coin enough.\nSuch apparently-paradoxical results of this kind are considered\nevidence against the likelihood principle.\n\n== References ==\n\n* G.A. Barnard, G.M. Jenkins, and C.B. Winsten. \"Likelihood Inference and Time Series\", \'\'J. Royal Statistical Society\'\', series A, 125:321-372, 1962.\n\n* Allan Birnbaum. \"On the foundations of statistical inference\". \'\'J. Amer. Statist. Assoc.\'\' 57(298):269–326, 1962. \'\'(With discussion.)\'\'\n\n* Anthony W.F. Edwards. \'\'Likelihood\'\'. 1st edition 1972 (Cambridge University Press), 2nd edition 1992 (Johns Hopkins University Press).\n\n* Anthony W.F. Edwards. \"The history of likelihood\". \'\'Int. Statist. Rev.\'\' 42:9-15, 1974.\n\n* [[Ronald A. Fisher]]. \"On the Mathematical Foundations of Theoretical Statistics\", \'\'Phil. Trans. Royal Soc.\'\', series A, 222:326, 1922. \'\'(On the web at: [http://www.library.adelaide.edu.au/digitised/fisher/18pt1.pdf])\'\'\n\n* Ian Hacking. \'\'Logic of Statistical Inference\'\'. Cambridge University Press, 1965.\n\n* Richard M. Royall. \'\'Statistical Evidence: A Likelihood Paradigm\'\'. London: Chapman & Hall, 1997.\n\n* Leonard J. Savage et al. \'\'The Foundations of Statistical Inference.\'\' 1962.\n\n== External links ==\n\n* Anthony W.F. Edwards. \"Likelihood\". http://www.cimat.mx/reportes/enlinea/D-99-10.html\n\n* Jeff Miller. [http://members.aol.com/jeff570/l.html Earliest Known Uses of Some of the Words of Mathematics (L)]\n\n* John Aldrich. [http://www.economics.soton.ac.uk/staff/aldrich/fisherguide/prob+lik.htm Likelihood and Probability in R. A. Fisher’s Statistical Methods for Research Workers]\n\n[[Category:Statistics]]','/* Arguments against the likelihood principle */',0,'220.31.240.165','20050104034808','',0,0,0,0,0.341190863094,'20050104034808','79949895965191'); INSERT INTO cur VALUES (876,0,'Asumsi_statistik','[[Statistik]], saperti dina sakabeh widang matematik teu nyimpulkeun hiji hal nu tina tina nu euweuh. Dina usaha neangan kasimpulan nu bener ngeunaan [[populasi statistik]], ilaharna diperlukeun keur nyieun sababaraha anggapan mimiti. Ieu kudu dijieun sacara \'\'hati-hati\'\', sabab kasalahan dina nyieun anggapan baris ngakibatkeun kana kasimpulan nu kacida salahna.\n\nAnggapan nu ilahar dipake dia statistik nyaeta:\n\n#observasi antara variabel ngarupakeun hal nu bebas (tempo [[statistical independence|kabebasan statistik]])\n#kasalahan observasi bebas tina potensi efek nu ngabingungkeun\n#observasi pasti atawa ngadeukeutan kana normal(tempo [[sebaran normal]])\n#tingkat ka-linieran pakait keur lobana rangsangan(tempo [[linear regression|regresi linier]])','',13,'Budhi','20040908025637','',0,0,0,0,0.498473500599,'20040908025655','79959091974362'); INSERT INTO cur VALUES (877,0,'Manusa','\n\n\n\n\n\n\n\n
Humans
{{StatusSecure}}
[[Image:Human.png]]
Image of a man and woman, taken from
the [[Pioneer 11]] spacecraft image.
(Public domain image)
{{taxonomy}}
\n\n\n\n\n\n\n\n\n
{{Regnum}}:[[Animal]]ia
{{Phylum}}:[[Chordate|Chordata]]
{{Subphylum}}:[[vertebrate|Vertebrata]]
{{Classis}}:[[Mammal]]ia
{{Ordo}}:[[Primate]]s
{{Familia}}:[[Hominid]]ae
{{Genus}}:\'\'\'\'\'[[Homo (genus)|Homo]]\'\'\'\'\'
{{Species}}:\'\'\'\'\'sapiens\'\'\'\'\'
\n
[[Binomial name]]
\'\'\'\'\'Homo sapiens\'\'\'\'\'
\n[[Linnaeus]], 1758
\n\'\'\'Manusa\'\'\' (\'\'\'\'\'Homo sapiens\'\'\'\'\') ngarupakeun hiji [[spésiés]] ti \'\'[[Great Ape]]\'\' jeung hiji-hijina spésiés nu salamet ti genus \'\'[[Homo (genus)|Homo]]\'\'. Spésiés ieu biasa disebut \'\'man\'\', \'\'mankind\'\', atawa \'\'humanity\'\' and its members as \'\'humans\'\', \'\'human beings\'\', \'\'persons\'\' or \'\'people\'\'. Jalu déwasa disebutna lalaki, sedengkeun nu bikang disebut awéwé. There is only one extant [[subspecies]], \'\'H. sapiens sapiens\'\'. Humans are notable for their increased [[intelligence]] and the ability to use [[language]].\n\n==Asal-usul==\n\n\'\'Artikel utama: [[Évolusi manusa]]\'\'\n\nDulur [[évolusi]]onér nu pangdeukeutna ka manusa nyéta dua spésiés [[simpanse]] \'\'[[Pan troglodytes]]\'\' (\"\'\'common chimp\'\'\") jeung \'\'[[Pan paniscus]]\'\' (\"\'\'pygmy chimp\'\'\" atawa \"Bonobo\"), sarta ka nu darajat duduluranana leuwih handap [[Hominoidae|hominoid]] séjénna kayaning [[orangutan]] jeung [[gorilla]]. Penting dicatet, yén manusa ukur babagi hiji \'\'common ancestor\'\' jeung nu kasarebut tadi, henteu diturunkeun sacara langsung ti maranéhna. Para ahli biologi geus ngabandingkeun runtuyan [[pasangan basa]] [[DNA]] antara manusa jeung simpanse, sarta ngira-ngira béda genetikna ukur [http://www.pnas.org/cgi/content/abstract/99/21/13633 5%]. Hasil ngira-ngira nunjukkeun yén karuhun manusa misah ti simpanse 5 jutaan taun ka tukang, sedengkeun ti gorilla kira 8 juta taun ka tukang. However, recent news reports of a hominid skull approximately 7 million years old already showing a divergence from the ape lineage strongly suggests an earlier divergence. Some scientists argue that bonobos, chimpanzees and, possibly, gorillas should be lumped into the genus \'\'[[Homo (genus)|Homo]]\'\', but this is currently a minority opinion.\n\nLoba golongan agamis anu kabeuratan jeung kontroversi ngeunaan [[Évolusi Homo sapiens|tiori évolusi manusa]] ti hiji \'\'common ancestor\'\' jeung hominoid séjénna. Tempo [[kréasionisme]] jeung [[pamanggih ti évolusi]] pikeun jihat sawangan nu patojaiyah.\n\n== Ciri fisik ==\n\n[[Awak]] manusa didadarkeun na kumpulan artikel [[anatomi manusa]]. Manusa ngabogaan loba pisan [[range of variability|range]] of [[human variability|variability]] dina ciri pisik jeung karakter lainna. \n\nThe evolution of \'\'Homo sapiens\'\' is characterized by a number of important trends:\n* expansion of the [[brain cavity]] and [[brain]] itself, which is typically about [[1 E-3 m3|1,400 cm³]] in volume, well over twice that of a chimpanzee or gorilla. Some [[physical anthropology|physical anthropologists]] argue that a reorganization of the structure of the brain is more important than cranial expansion itself. \n* [[canine tooth]] reduction.\n* [[bipedal locomotion]]\n* descent of the [[larynx]] (which makes possible the production of the complex sound known as vocal [[language]]).\n\n[[image:Rorongkong.jpg|thumbnail|150px|right|Rorongkong manusa]] \nHow these trends are related, in what ways they have been adaptive, and what their role is in the evolution of complex social organization and culture, are matters of ongoing debate among physical anthropologists.\n\nAlthough body size is highly heritable, it is also significantly influenced by [[environment]]al and [[culture|cultural]] factors such as [[diet (nutrition)|diet]]. The mean height of an American adult female is 162 [[centimetre|cm]] (64 [[inch|in]]) and the mean weight is 62 [[kilogram|kg]] (137 [[pound|lb]]). Males are typically larger: 175 cm (69 in) and 78 kilograms (172 lb). Humans vary substantially around these means, and the means themselves have varied depending on locality and historical factors.\n\nHuman children, typically weighing 3-4 kilograms (6-9 pounds) and 50-60 centimetres (20-24 inches) in height, are born after a nine-month [[gestation]] period. Helpless at birth, they continue to grow for some years, typically reaching [[sexual maturity]] at around 12-15 years of age. Boys continue growing for some time after this, often only reaching their maximum height around the age of 18. \n\nHuman [[life expectancy]] at birth is approaching 80 years in wealthy nations, with the assistance of [[science]] and [[technology]]. The number of centenarians in the world was estimated [http://www.sacbee.com/content/lifestyle/seniors/story/6745838p-7696920c.html] at about 50,000 in [[2003]]. The maximum human [[life span]] is thought to be about 120 years. \n\nSee also [[human physical appearance]].\n\n==Ciri méntal==\n\nManusa nganggap manéhna salaku organisme pangpinterna di karajaan sato. Manusa mibanda nisbah [[otak manusa|otak]] ka beurat awak pangbadagna ti sakabéh sato badag ([[lumba-lumba]] kadua; [[hiu]] pangluhurna di dunya [[lauk]]; sedengkeun [[octopus]] pangluhurna di dunya [[invertebrata]]). Najan ieu teu ngarupakeun ukuran absolut (inasmuch as a minimum brain-mass is necessary for certain \"housekeeping\" functions), nisbah massa otak ka massa awak mémang méré cicirén nu hadé pikeun kapinteran rélatif ([[Carl Sagan]], [[The Dragons of Eden]], 38).\n\nKamampuhan manusa kana abstraksi teu paralél na karajaan sato. Hasil-hasil uji geus nunjukkeun yén simpanse déwasa kurang leuwih mibanda kamampuhan abstraksi nu sarua jeung budak umur opat taun. \n\n[[Pattern recognition]] is another area for which human beings are mentally \nwell-suited. \n\n[[Mikir]], [[IQ]], [[Memory]], [[Invention]], [[Élmu]], [[Filosofi]], [[Pangaweruh]], [[Atikan]],\n[[Consciousness]]\n\n==Ciri émosional==\n\n[[Émosi]], [[Tresna]], [[Cua]], [[Bungah]], jsb.\n\n==Ciri spiritual==\n\n[[Agama]] miara yén di sagigireun sifat fisik jeung méntalna, umat manusa ogé mibanda sifat spiritual; seueur nu yakin yén ayana sifat spiritual ieu nu ngabédakeun umat manusa ti mahluk séjén. Sabalikna, kaom atéis yakin yén manusa teu mibanda aspék spiritual, sahingga teu bina ti nu séjén.\n\n[[Roh]], [[Conscience]], [[Agama]], [[Moralitas]], [[Prayer]], [[Worship]], etc.\n\n== [[Habitat]] ==\n\nHabitat asli nalika manusa ngalaman évolusi nyéta di [[sabana]] Afrika (tempo [[Vagina gentium]], [[Environment of Evolutionary Adaptedness]]). Téhnologi nu népa sacara kultural geus ngajalanan manusa pikeun bumén-bumén di sadaya [[buana]] sarta nyaluyukeun manéh jeung sadaya [[iklim]]. Within the last few decades, humans have been able to temporarily inhabit Antarctica, the ocean depths, and [[outer space]], although permanent habitation of these three environments is not yet possible. Humans, with a population of about six billion, are one of the most numerous [[mammal]]s on Earth. \n\nMost humans (61%) live in the [[Asia]]n region. The vast majority of the remainder live in the [[Americas]] (14%), [[Africa]] (13%) and [[Europe]] (12%), with only 0.3% in Australia. See [[list of countries by population]] and [[list of countries by population density]]. \n\nBeing primates, humans\' original life style is hunting/gathering, which is adapted to the savannah where they evolved. Other human life styles are [[nomad]]ism (often linked to animal herding) and permanent settlements made possible by the development of agriculture. Humans have a great capacity for altering their habitats by various methods, such as [[agriculture]], [[irrigation]], [[urban planning]] and [[construction]], and activities accessory to those, such as [[transportation]] and [[manufacturing]] goods. \n\nPermanent human settlements are dependent on proximity to [[cai|water]] and, depending on the lifestyle, other natural resources such as fertile land for growing [[crops]] and grazing [[livestock]] or, seasonally by populations of [[hunting|prey]]. With the advent of large-scale trade and transportation infrastructure, immediate proximity to these resources has become less necessary, and in many places these factors are no longer the driving force behind growth and decline of population.\n\n===[[Populasi]]===\n\nA sizable minority - around 2.5 of a total of 6.3 [[billion]] people - live in [[urban]] surroundings. [[Urbanisation]] is expected to rise drastically during the [[21st century]]. Problems for humans in [[city|cities]] include various forms of [[pollution]], [[crime]] and [[poverty]], especially in inner city and [[suburb]]an slums.\n\nHumans living on Antarctica, under the ocean, or in space are part of scientific, military, or industrial expeditions, and habitation of these environments is temporary. \n\nLife in space has thus far been temporary living, with up to ten humans in space at a given time (seven on the [[Space Shuttle]], three on [[Mir]]) and currently around three in the [[International Space Station]]. This is a direct result of humans\' vulnerability to [[ionizing radiation]]. Prior to 1961, all humans were restricted to the earth; [[Yuri Gagarin]] was the first human to travel into [[space]]. At various periods between 1969 and 1974, up to two humans spent varying amounts of time on the [[Moon]]. As of yet, residencies or human explorations on other [[planet]]s have not come to be.\n\n== Ngabandingkeun \'\'Homo sapiens\'\' jeung spésiés séjén ==\n\nHumans often consider themselves to be the dominant species on [[Earth]], and the most advanced in intelligence and ability to manage their environment. This belief is especially strong in Western culture, and is based in part on the [[Bible|Biblical]] [[Creation]] story in which [[Adam]] is explicitly given dominion over the Earth and all of its creatures.\n\nBiologists and scientists in general, though, do not consider \"dominant\" to be a useful term, because the adaptive value of any trait or complex of traits depends on the niche and is highly mutable. From a scientific standpoint, \'\'Homo sapiens\'\' certainly is among the most generalized species on [[Earth]]. Smaller and simpler animals such as [[bacteria]] and [[insect]]s greatly surpass humans in population size and [[diversity]] of species, but few single species occupy as many diverse environments as humans. Many other species, for example, are adapted to specific environments, whereas humans rely on the use of fire and on tools such as clothing and manufactured [[shelter]], which are themselves often produced and used through complex social interactions.\n\nVarious attempts have been made to identify a single behavioral characteristic that distinguishes humans from all other animals, e.g. the ability to make and use tools (building shelter, [[weaving]] fabrics for clothing); the ability to alter the environment; language; and the development of complex social relationships and structures. Considered in isolation, however, these differences are not absolute, as ethologists have recorded such behaviors in many species. Apes and even [[bird]]s, for example, are known to \"fish\" for [[insect]]s using blades of grass or twigs, and even to shape the tools for that purpose. For these reasons, the idea that making and using tools is a defining characteristic of humans is often considered outdated, though of course no other animal uses tools to the same degree or with the same flexibility as \'\'Homo sapiens\'\'. Similarly, other animals often have methods of [[communication]], but the degree to which humans create and use complex [[grammar]] and abstract concepts in language has not been seen in any other species.\n\n[[Noam Chomsky|Chomskian]] [[linguistics]] holds that a distinguishing feature of humans is that they are the only extant species with a [[universal grammar|language instinct]] - a genetic predisposition that produces a brain mechanism whose function is to acquire a language by observing those around us. Dolphins may also have this trait as they show dialect.\n\nSome anthropologists think that these readily observable characteristics (tool-making and language) are based on less easily observable mental processes that might be unique among humans: the ability to think symbolically. That is, humans can think abstractly about concepts and ideas. They can question, use [[logic]], understand [[mathematics|mathematical]] concepts, and so on in ways greater than other animals are known to do, although several species have demonstrated some abilities in these areas. In any case, the idea that these abilities distinguish humans from other species is the basis of the name \'\'Homo sapiens\'\', sometimes translated as \"Man the Thinker\". It should be noted, however, that the extinct species of the \'\'Homo\'\' genus (e.g. \'\'[[Homo neanderthalensis]]\'\', \'\'[[Homo erectus]]\'\') were also adept tool makers and there is some evidence that they may have had linguistic skills.\n\nWhile humans have all these characteristics, from the biological viewpoint the question \"What single characteristic distinguishes humans from all other animals?\" is an odd one: it is not a question that is usually asked of [[cat]]s, [[dolphin]]s, or song [[sparrow]]s. Finding other species that shape tools or can use sign language may shed light on human [[evolution]], but it doesn\'t erase the differences or similarities between humans and other species.\n\n== Kagiatan manusa ==\n\n* [[Kahirupan pribadi|Kahirupan]]\n* [[Kaahlian]]\n* [[Ngimpi]], [[Saré]], [[Hudang]]\n* [[Human communication]]\n** [[Interpersonal communication]]\n*** [[Ngomong]], [[Nguping]]\n*** [[Nulis]] & [[Maca (kagiatan)|Maca]]\n* [[Mikir]], [[Pangaweruh]]\n* [[Paripolah manusa]]\n* [[Periode manusa]]\n\n== [[Élmu]] ngeunaan manusa==\n*[[Antropologi]]\n*[[Linguistik]]\n*[[Psikologi]]\n*[[Sosiologi]]\n\n== Tempo ogé ==\n* [[budak]] & [[orok]]\n* [[peradaban]]\n* [[énvironmentalisme]]\n* [[Évolusi Homo sapién]]\n* [[biologi manusa]]\n* [[human condition]]\n* [[ékologi manusa]]\n* [[human variability]]\n* [[humanoid]]\n* [[lalaki]] & [[awéwé]]\n\n==Tumbu kaluar==\n* [http://www.modernhumanorigins.com/ Hiji Sawangan ngeunaan Asal-usul Manusa Modern]\n* [http://tolweb.org/tree?group=Homo_sapiens&contgroup=Homo Tangkal Kahirupan]\n\n[[Category:Homo (taksa)]]\n[[Category:Kera]]\n[[Category:Tepas]]\n[[Category:Manusa]]\n\n[[ca:Homo sapiens sapiens]] [[da:Menneske]] [[de:Mensch]] [[en:Human]] [[eo:Homo]] [[es:Homo sapiens]] [[el:Άνθρωπος]] [[fi:Ihminen]] [[fr:Homo Sapiens]] [[gl:Ser Humano]] [[hr:čovjek]] [[it:Uomo]] [[ja:%E3%83%9B%E3%83%A2%E3%83%BB%E3%82%B5%E3%83%94%E3%82%A8%E3%83%B3%E3%82%B9]] [[ko:인간]] [[nah:Tlaca]] [[nl:Mens]] [[nds:Minsch]] [[pl:Cz%B3owiek]] [[pt:Homo sapiens]] [[ro:Om]] [[ru:Человек]] [[simple:Human]] [[sl:človek]] [[sv:Människan]] [[uk:Людина]] [[zh:人]]','/* Tumbu kaluar */',3,'Kandar','20041124073325','',0,0,0,0,0.289414942399,'20050208111611','79958875926674'); INSERT INTO cur VALUES (878,0,'Pangaweruh','\'\'\'\'\'Pangaweruh\'\'\'\'\' nyaeta hiji watesan nu loba harti gumantung kana konteksna, sanajan kitu leuwih raket hubunganna jeung sababaraha konsep saperti [[meaning]], [[information]], [[instruction]], [[communication]], [[representation]], [[learning]] jeung [[mental stimulus]]. \n\nKnowledge is distinct from information. Both knowledge and information consist of true statements, but knowledge is information that has a purpose or use. Philosophers would describe this as [[information]] associated with [[intentionality]]. The study of knowledge is called [[epistemology]].\n\nA common definition of knowledge is that it consists of [[theory of justification|justified]] [[truth|true]] [[belief]]. This definition derives from [[Plato]]\'s [[Theaetetus]]. It is considered to set out necessary, but not sufficient, conditions for some statement to count as knowledge.\n\nWhat constitutes knowledge, certainty and [[truth]] are controversial issues. These issues are debated by [[philosopher]]s, [[social science|social scientists]], and [[history|historians]]. [[Ludwig Wittgenstein]] wrote \"On Certainty\" - aphorisms on these concepts - exploring relationships between knowledge and certainty. A thread of his concern has become an entire field, the [[philosophy of action]].\n\n==Deriving knowledge==\n\nOne way of deriving and verifying knowledge is from tradition or from generally recognized [[appeal to authority|authority]]. Knowledge may also be claimed for the pronouncements of secular or [[religion|religious]] authority such as the [[state]] or the [[church]].\n\nIn [[Judaism|Jewish]], [[Christianity|Christian]] and [[Islam]]ic traditions, there has always been a considerable tension on the issue of authority versus experience in the formation of knowledge. Early [[Christian philosophy]] contrasted [[revelation]] from God with knowledge gained by reason. [[St. Augustine]] for instance put the knowledge of classical philosophers, especially [[Plato]], into a Christian framework. [[Experimental knowledge]] was discounted. [[Early Muslim philosophy]], especially the [[Mutazilite]] school, medieval [[Jewish philosophy]], and later Christian work, especially that of [[Thomas Aquinas]], focused on [[Aristotle]]\'s views. These were vast controversies stretching over centuries. The (eventually dominant) [[Asharite]] school of Islamic scholars, for instance, strongly rejected most views of Aristotle, while the [[Roman Catholic]] tradition generally embraced them. Such efforts to provide an ethical or spiritual basis for the foundations of knowledge continue to this day in the [[sociology of knowledge]], [[Islamization of knowledge]], and the many and varied strains of [[economics]].\n\nA second way to derive knowledge is by [[observation]] and [[experiment]]. It is not free of [[uncertainty]], as [[error]]s of observation or interpretation may occur, and any [[sense]] can be deceived by [[illusion|illusions]].\n\nKnowledge may also be derived by [[logic|reason]] from either traditional, authoritative, or experiential sources or a combination of them. Inferential knowledge is based on [[logic|reasoning]] from facts or from other inferential knowledge such as a theory.\n\n== Ngabédakeun \'\'nyaho yén\'\' (\'\'knowing that\'\') ti \'\'nyaho kumaha\'\' (\'\'knowing how\'\') ==\n\nSuppose that Fred says to you: \"The fastest [[swimming]] stroke is the [[front crawl]]. One performs the front crawl by oscillating the legs at the hip, and moving the arms in an approximately circular motion\". Here, Fred has [[propositional knowledge]] of swimming and how to perform the front crawl.\n\nHowever, if Fred acquired this propositional knowledge from an [[encyclopedia]], he will not have acquired the [[skill]] of swimming: he has some propositional knowledge, but does not have any [[know-how]]. In general, one can demonstrate know-how by performing the task in question, but it is harder to demonstrate propositional knowledge.\n\n== Inferential vs. factual knowledge ==\n\nKnowledge may be factual or inferential. Factual knowledge is based on direct [[observation]]. It is still not free of [[uncertainty]], as [[error|errors]] of observation or interpretation may occur, and any [[sense]] can be deceived by [[illusion|illusions]]. \n\nInferential knowledge is based on [[logic|reasoning]] from facts or from other inferential knowledge such as a [[theory]]. Such knowledge may or may not be [[verification|verifiable]] by observation or [[testing]]. For example, all knowledge of the [[atom]] is inferential knowledge. The distinction between factual knowledge and inferential knowledge has been explored by the discipline of [[general semantics]]. \n\n\n\n== The problem of justification ==\n\nIn philosophy, knowledge is held to be a belief that is true, actionable and \'\'justified\'\'. But how do we justify that our beliefs are true knowledge?\n\nJustification and evidence are both epistemic features of belief. Justification and evidence are, in other words, both qualities that indicate that the belief is true. We could try out other epistemic features in the definition of knowledge, if we wanted to. Instead of \"justified true belief\" or \"true belief with evidence,\" we could say that knowledge is \"rational true belief\" or \"warranted true belief.\" For our purposes, the differences between these different options don\'t matter. The whole point is that, to be knowledge, a belief has to have some positive epistemic feature; it can\'t be arbitrary or random or irrational. The [[Theory of justification]] deals with these issues in more detail.\n\nAnother problem with defining knowledge is known as the \"[[Gettier problem]]\". The Gettier problem arises when we give certain kinds of counterexamples to the JTB (justified true belief) definition. A counterexample is a case where the definition applies, but the word defined doesn\'t; or a case where the word defined applies, but the definition doesn\'t. Gettier counterexamples are examples where the definition, justified, true belief applies; but one nevertheless still doesn\'t have knowledge, so the word \"knowledge\" doesn\'t apply in that case. \n\n=== Externalist responses ===\n\nGettier\'s article was published in 1963. Right after that, for a good decade or more, there was an enormous number of articles trying to supply the missing fourth condition of knowledge. The big project was to try to figure out the \"X\" in the equation, Knowledge = belief + truth + justification + X. Whenever someone proposed an answer, someone else would come up with a new counterexample to shoot down that definition.\n\nSome of the proposed solutions involve factors external to the agent. These responses are therefore called [[externalism]]. For example, one externalist response to the Gettier problem is to say that the justified, true belief must be caused (in the right sort of way) by the relevant facts.\n\n== Skepticism ==\n\nWhen scientists or philosophers ask \"Is knowledge possible?\", they mean to say \"Am I ever sufficiently justified in believing something in order to have knowledge?\" Adherents of [[Philosophical skepticism]] often say \"no\". Philosopical skepticism is the position which critically examines whether the knowledge and perceptions people have is true; adherents of this position hold that one can never obtain true knowledge, since justification is never certain. This is a different position from [[Scientific skepticism]], which is the practical stance that one should not accept the veracity of claims until solid evidence is produced.\n\n==Tempo ogé==\n\n[[Epistemology]] | [[Truth]] | [[Wisdom]] | [[Belief]] | [[Truth]] | [[Epistemology]] | [[Information]] | [[knowledge relativity]] | [[Semantic memory]] | \n[[Analytic proposition]] | \n[[Business intelligence]] | \n[[Cognition]] | \n[[Cognitive ontology]] | \n[[Confirmation (sacrament)]] | \n[[Data]] | \n[[Deconstruction]] | \n[[Definition]] | \n[[Education]] | \n[[Encyclopedia Galactica]] | \n[[Encyclopedia]] | \n[[Epistemology]] | \n[[Esoteric knowledge]] | \n[[Experience]] | \n[[Expertise]] | \n[[Feedback]] | \n[[Guild]] | \n[[How-to]]\'s | \n[[Ignorance]] |\n[[Information]] |\n[[Information good]] |\n[[Information pyramid]] |\n[[Intellectual worker]] | \n[[Internet research]] |\n[[Intuition]] | \n[[Knowledge (philosophy)]] | \n[[Knowledge creation]] | \n[[Knowledge engineering]] | \n[[Knowledge management]] | \n[[Knowledge representation]] | \n[[KnowledgeWeb Project]] | \n[[Left-Hand Path]] | \n[[List of philosophical topics]] | \n[[Market transparency]] | \n[[Metalibrary]] | \n[[Mind mapping]] | \n[[Nihilism]] | \n[[Ontological distinction]] | \n[[OpenFacts]] | \n[[Personal experience]] |\n[[Philosophical skepticism]] | \n[[Philosophy]] | \n[[Procedural knowledge]] | \n[[Profession]] | \n[[Propositional knowledge]] (Contains some material that should probably be copied/moved over!)  | \n[[Research]] | \n[[Science education]] | \n[[Science]] | \n[[Scientific method]] | \n[[Scientific revolution]] | \n[[Scientific enterprise]] | \n[[Situated learning]] | \n[[Storage]] | \n[[Streetwise]] | \n[[Technocracy]] | \n[[Test (student assessment)]] | \n[[Text mining]] | \n[[Truth]] |\n[[Understanding]] | \n[[Voluntary simplicity]] | \n[[World view]] |\n\n== Tumbu kaluar ==\n\n* [http://polywog.navpoint.com/philosophy/epistemology/gettier_prob/ The Gettier problem: Justified true belief?]\n* [http://www.princeton.edu/~jimpryor/courses/epist/notes/gettier.html Theory of Knowledge: The Gettier problem]\n\n== Acuan ==\n\n* Creath, Richard, \"Induction and the Gettier Problem\", Philosophy and Phenomenological Research, Vol.LII, No.2, June 1992.\n* Feldman, Richard, \"An Alleged Defect in Gettier Counterexamples\", Australasian Journal of Philosophy, 52 (1974): 68-69.\n* Gettier, Edmund, \"Is Justified True Belief Knowledge?\", Analysis 23 (1963): 121-23.\n* Goldman, Alvin I., \"Discrimination and Perceptual Knowledge\", Journal of Philosophy, 73.20 (1976), 771-791.\n* Hetherington, Stephen, \"Actually Knowing\", The Philosophical Quarterly, Vol.48, No. 193, October 1998.\n* Lehrer, Keith and Thomas D. Paxon, Jr., \"Knowledge: Undefeated Justified True Belief\", The Journal of Philosophy, 66.8 (1969), 225-237.\n* Levi, Don S., \"The Gettier Problem and the Parable of the Ten Coins\", Philosophy, 70, 1995.\n* Swain, Marshall, \"Epistemic Defeasibility\", American Philosophical Quarterly, Vol.II, No.I, January 1974.\n[[Category:Filosofi]] [[Category:Étnik]] [[Category:Pangaweruh]] [[Category:Épistemologi]]\n\n[[da:Viden]] [[de:Wissen]] [[en:Knowledge]] [[ja:知識]] [[nl:Kennis]] [[pl:Wiedza]]\n[[simple:Knowledge]] [[zh:知识]]','/* See also */',3,'Kandar','20050203130950','',0,0,0,0,0.339331170236,'20050203130950','79949796869049'); INSERT INTO cur VALUES (879,0,'Tiori_statistik','\'\'\'Tiori statistik\'\'\' ngawengku sababaraha topik, nyaeta:\n\n[[Model statistik]] sumber data sarta cara ngarumuskeun masalah:\n#[[survey sampling|Sampling]] ti hiji populasi nu tinangtu/kawates\n#Measuring [[observational error]] and refining procedures\n#Studying statistical [[multivariate statistics|relations]] \n\n[[Ngarencanakeun panalungtikan statistik]] pikeun ngukur jeung ngontrol [[kasalahan amatan]] (Ing. \'\'observational error\'\'):\n\n#[[Desain percobaan]] keur nangtukeun éfék \'\'perlakuan\'\'\n#[[Survey sampling]] pikeun ngadadarkeun populasi alami\n\n[[Summarizing statistical data]] in conventional forms (also known as [[statistik deskriptif]])\n\n#Milih [[kasimpulan statistik]] keur ngajelaskeun sampel\n#Fitting [[probability distribution]]s to sample data\n\n[[Interpreting statistical data]] is the final objective of all research:\n\n#Common [[statistical assumptions|assumptions]] that we make\n#[[Likelihood principle]]\n#[[Estimating parameters]]\n#[[Tes hipotesa statistik]]\n#[[Revising opinions in statistics]]\n\n==Tempo ogé==\n\n[[probability]], [[statistik]], [[daptar jejer statistis]]','',13,'Budhi','20050104035446','',0,0,1,0,0.332679183843,'20050104035446','79949895964553'); INSERT INTO cur VALUES (880,0,'Tiori_kamungkinan','[[Category:Probability theory]]\n\'\'\'Probability theory\'\'\' is the [[Mathematics|mathematical]] study of [[probability]].\n\nMathematicians think of probabilities as numbers in the interval from 0 to 1 assigned to \"events\" whose occurrence or failure to occur is random. Probabilities P(E) are assigned to events E according to the [[probability axioms]].\n\nThe probability that an event E occurs \'\'given\'\' the known occurrence of an event F is the \'\'\'[[conditional probability]]\'\'\' of E \'\'\'given\'\'\' F; its numerical value is P(E \\cap F)/P(F) (as long as P(F) is nonzero). If the conditional probability of E given F is the same as the (\"unconditional\") probability of E, then E and F are said to be [[statistical independence|independent]] events. That this relation between E and F is symmetric may be seen more readily by realizing that it is the same as saying\nP(E \\cap F) = P(E)P(F).\n\nTwo crucial concepts in the theory of probability are those of a [[random variable]] and of the [[probability distribution]] of a random variable; see those articles for more information.\n\n==A somewhat more abstract view of probability==\n\n\"Pure\" mathematicians usually take probability theory to be the study of probability spaces and random variables — an approach introduced by [[Andrey Nikolaevich Kolmogorov]] in the [[1930s]]. A [[probability space]] is a triple (Ω, \'\'F\'\', \'\'P\'\'), where\n\n*Ω is a non-empty set, sometimes called the \"sample space\", each of whose members is thought of as a potential outcome of a random experiment. For example, if 100 voters are to be drawn randomly from among all voters in California and asked whom they will vote for governor, then the set of all sequences of 100 Californian voters would be the sample space Ω.\n\n*\'\'F\'\' is a [[sigma-algebra]] of subsets of Ω whose members are called \"events\". For example the set of all sequences of 100 Californian voters in which at least 60 will vote for Schwarzenegger is identified with the \"event\" that at least 60 of the 100 chosen voters will so vote. To say that \'\'F\'\' is a sigma-algebra necessarily implies that the complement of any event is an event, and the union of any (finite or countably infinite) sequence of events is an event. \n\n*P is a probability measure on \'\'F\'\', i.e., a [[measure (mathematics)|measure]] such that P(Ω) = 1.\n\nIt is important to note that \'\'P\'\' is defined on \'\'F\'\' and not on Ω. \nWith Ω denumerable we can define \'\'F\'\' := powerset(Ω) which is trivially a sigma-algebra and the biggest one we can create using Ω. \nIn a discrete space we can therefore omit \'\'F\'\' and just write (Ω, \'\'P\'\') to define it. If on the other hand Ω is non-denumerable and we use \'\'F\'\' = powerset(Ω) we get into trouble defining our probability measure \'\'P\'\' because \'\'F\'\' is too \'huge\'. So we have to use a smaller sigma-algebra \'\'F\'\' (eg. the [[Borel algebra]] of Ω). We call this sort of probability space a continuous probability space and are led to questions in [[measure theory]] when we try to define \'\'P\'\'.\n\nA [[random variable]] is a [[measurable function]] on Ω. For example, the number of voters who will vote for Schwarzenegger in the aforementioned sample of 100 is a random variable.\n\nIf \'\'X\'\' is any random variable, the notation \'\'P\'\'(\'\'X\'\' ≥ 60) is shorthand for \'\'P\'\'({ ω in Ω : \'\'X\'\'(ω) ≥ 60 }), so that \"\'\'X\'\' ≥ 60\" is an \"event\".\n\n==Philosophy of application of probability==\n\nSome statisticians will assign probabilities only to events that they think of as random, according to their relative frequencies of occurrence, or to subsets of populations as proportions of the whole; those are \'\'\'frequentists\'\'\'. Others assign probabilities to propositions that are uncertain according either to [[personal probability|subjective]] degrees of belief in their truth, or to logically justifiable degrees of belief in their truth. Such persons are [[Bayesian probability|Bayesians]]. A Bayesian may assign a probability to the proposition that there was life on Mars a billion years ago, since that is uncertain; a frequentist would not assign such a probability, since it is not a random event that has a long-run relative frequency of occurrence.\n\n==Tempo oge==\n\n*[[expectation]]\n*[[likelihood]]\n*[[probability]]\n*[[probability axioms]]\n*[[probability distribution]]\n*[[random variable]]\n*[[statistical independence]]\n*[[varian]]\n*[[List of publications in statistics]]\n\n\n[[bg:Теория на вероятностите]]\n[[de:Wahrscheinlichkeitstheorie]]\n[[eo:Teorio de Probabloj]]\n[[es:Probabilidad]]\n[[fr:Théorie des probabilités]]\n[[lt:Tikimybių teorija]]\n[[nl:kansrekening]]\n[[no:Sannsynlighetsteori]]\n[[pl:Teoria prawdopodobieństwa]]\n[[sv:Sannolikhetsteori]]\n[[zh:概率论]]','/* See also */',13,'Budhi','20040907101329','',0,0,0,0,0.066594096863,'20041231123527','79959092898670'); INSERT INTO cur VALUES (881,0,'Tiori_kaputusan','\'\'\'Decision theory\'\'\' is an interdisciplinary area of study, related to and of interest to practitioners in [[matematik]], [[statistik]], [[economics]], [[philosophy]], [[management]] and [[psychology]]. It is concerned with the optimal decisions to be taken under particular circumstances.\n\n==Normative and descriptive decision theory==\n\nMost of decision theory is \'\'normative\'\' or \'\'prescriptive\'\', i.e. it is concerned with identifying the best decision to take, assuming an ideal decision taker who is fully informed, able to compute with perfect accuracy, and fully rational. However, since it is obvious that people do not typically behave in optimal ways, there is also a related area of study, which is a \'\'descriptive\'\' or \'\'positive\'\' discipline, attempting to describe what people will actually do. Since the normative, optimal decision often creates hypotheses for testing against actual behaviour, the two fields are closely linked. Furthermore it is possible to relax the assumptions of perfect information, rationality and so forth in various ways, and produce a series of different prescriptions or predictions about behaviour, allowing for further tests of the kind of decision-making that occurs in practice.\n\n==What kinds of decision need a theory?==\n\nDecision theory is only relevant in decisions that are difficult for some reason. A few types of decision have attracted particular attention:\n*riskless choice between incommensurable commodities\n*choice under uncertainty\n*intertemporal choice\n*social decisions\n\n===Choice between incommensurable commmodities===\n\nThis area is concerned with the decision whether to have, say, one ton of guns and 3 tons of butter, or 2 tons of guns and 1 ton of butter. This is the classic subject of study of [[microeconomics]] and is rarely considered under the heading of decision theory, but such choices are often in fact part of the issues that are considered within decision theory.\n\n===Choice under uncertainty=== \n\nThis area represents the heartland of decision theory. [[Daniel Bernoulli]] stated that, when faced with a number of actions each of which could give rise to more than one possible outcome with different probabilities, the rational procedure is to identify all possible outcomes, determine their values (positive or negative) and the probabilities that they will result from each course of action, and multiply the two to give an \'\'expected value\'\'. The action to be chosen should be the one that gives rise to the highest total expected value. In reality people do not behave like this, at least if \"value\" is taken to mean \"objective financial value\" - otherwise no-one would either gamble or take out insurance. Within behavioural decision theory, this has led to various dilutions of the expected value theory; for example, objective probabilities can be replaced by subjective estimates, and objective values by subjective utilities, giving rise to the [[subjectively expected utility]] or SEU theory. The [[prospect theory]] of [[Daniel Kahneman]] and [[Amos Tversky]] is another alternative to the expected value model within behavioural decision theory.\n\n[[Pascal\'s Wager|Pascal\'s wager]] is a classic example of a choice under uncertainty. The uncertainty, according to [[Blaise Pascal|Pascal]], is whether or not God exists. And the personal belief or non-belief in God is the choice to be made.\n\n===Intertemporal choice===\n\nThis area is concerned with the kind of choice where different actions lead to outcomes that are realised at different points in time. If I receive a windfall of several thousand dollars, I could spend it on an expensive holiday, giving me immediate pleasure, or I could invest it in a pension scheme, giving me an income at some time in the future. What is the optimal thing to do? The answer depends partly on factors such as the expected rates of interest and inflation, my life expectancy, and my confidence in the pensions industry. However even with all those factors taken into account, human behaviour again deviates greatly from the predictions of prescriptive decision theory, leading to alternative models in which, for example, objective interest rates are replaced by subjective discount rates.\n\n===Social decisions===\n\nSome decisions are difficult because of the need to take into account how other people in the situation will respond to the decision that is taken. The analysis of such social decisions is the business of [[game theory]], and is not normally considered part of decision theory, though it is closely related.\n\n==Complex decisions==\n\nOther areas of decision theory are concerned with decisions that are difficult simply because of their complexity, or the complexity of the organisation that has to take them. In such cases the issue is not the deviation between real and optimal behaviour, but the difficulty of determining the optimal behaviour in the first place.\n\n==References==\n\n* Robert Clemen. \'\'Making Hard Decisions: An Introduction to Decision Analysis\'\', 2nd edition. Belmont CA: Duxbury Press, 1996. \'\'(covers normative decision theory)\'\'\n* D.W. North. \"A tutorial introduction to decision theory\". \'\'IEEE Trans. Systems Science and Cybernetics\'\', 4(3), 1968. Reprinted in Pearl & Shafer. \'\'(also about normative decision theory)\'\'\n* Glenn Shafer and Judea Pearl, editors. \'\'Readings in uncertain reasoning\'\'. Morgan Kaufmann, San Mateo, CA, 1990.\n\n[[Category:Social philosophy]]','',13,'Budhi','20040720120341','',0,0,0,0,0.661785766325,'20041225124916','79959279879658'); INSERT INTO cur VALUES (882,0,'Nagarawan','The term \'\'\'statesman\'\'\' is a respectful term used to refer to [[diplomat]]s, [[politician]]s, and other notable figures of [[state]]. It is often used in the context of international or foreign affairs, e.g., \"a meeting of statesmen.\" [[Foreign minister]]s are often called statesmen, for example, while more local level officials, such as [[mayor]]s are not. \n\nWhether or not an individual actually \'\'is\'\' a statesman, is generally a matter of opinion, although in some cases there is little controversy. Politicians who are regarded as statesmen are usually old, with long careers. \n\nThe term most frequently refers to individuals associated with a [[government]]al shift from [[monarchy|monarchism]] to [[republic|republicanism]]. Geneally, one can use the word as a [[euphemism]] for \'\'[[politician]]\'\'. When a politician retires, he is often referred to as a \"respected elder statesman\" by his supporters.\n\n==Quote==\n*[[Aristotle]] -- \"What the statesman is most anxious to produce is a certain [[morality|moral]] [[character]] in his fellow [[citizen]]s, namely a disposition to [[virtue]] and the performance of virtuous [[action]]s.\"\n\n[[nl:Staatsman]]','',13,'Budhi','20040720120441','',0,0,0,1,0.473407865257,'20040720120441','79959279879558'); INSERT INTO cur VALUES (883,0,'Politisi','A \'\'\'politician\'\'\' is an individual involved in [[politics]], sometimes this may include [[political science|political scientists]]. In other settings, a politician is a type of [[political figure]].\n\nIn Western [[democracy|democracies]], the term is generally restricted to those either holding or seeking elected office for themselves, rather than specialists employed by such people. Such a distinction is less clear in non-democratic forms of [[government]]. \n\nSome common offices for politicians can include:\n*[[President]]\n*[[Prime Minister]]\n*[[Senator]]\n*[[Member of Parliament]]\n*[[Governor]]\n*[[Minister]]\n*[[Councillor]]\n*[[Mayor]]\n*[[School board]] member\n\nSome examples of famous politicians:\n\n* [[Kofi Annan]] - [[United Nations Secretary-General]]\n* [[Clement Attlee]] - British post-war [[Prime Minister]]\n* [[Lazaro Cardenas]] - President of [[Mexico]]\n* [[Winston Churchill]] - wartime Prime Minister of the [[United Kingdom]]\n* [[Indira Gandhi]] - Prime Minister of [[India]]\n* [[Mohandas Gandhi]] - Nationalist leader of [[India]]\n* [[Thomas Jefferson]] - [[Founding Father]] of the [[United States]]\n* [[Petra Kelly]] - Founder of the [[Green Party]]\n* [[Abraham Lincoln]] - [[President of the United States|President]] of the United States\n* [[Paul Martin Jr.]] - Prime Minister of [[Canada]]\n* [[Hun Sen]] Prime Minister of [[Cambodia]]\n* [[Pierre Trudeau]] - Prime Minister of [[Canada]]\n* [[Olof Palme]] - Prime Minister of [[Sweden]]\n* [[Vladimir Putin]] - President of [[Russia]]\n* [[Romano Prodi]] - President of the [[European Commission]]\n* [[Franklin Delano Roosevelt]] - U.S. war-time [[President of the United States|President]]\n* [[Sun Yat-sen]] - [[Kuomintang]] Leader, Revolutionary leader of the [[Republic of China]]\n\nSee [[List of Japanese politicans]], [[List of British politicians]], [[List of New Zealand politicians]]\n\n==External Link==\n* [http://politicalgraveyard.com/chrono/by-year.html List of American Politicians by Year Born or Died]\n\n[[Category:Lists of people by occupation|Politicians]]\n\n[[de:Politiker]]\n[[en:Politician]]\n[[es:Político]]\n[[fr:Personnalité politique]]\n[[ja:政治家]]\n[[nl:Politicus]]\n[[sl:Politik]]\n[[uk:Політик]]','warnfile Adding:sl,en,es,fr',42,'Shizhao','20050303143920','',0,0,1,0,0.605566385484,'20050303143920','79949696856079'); INSERT INTO cur VALUES (884,0,'Status','[[de:Status]][[fr:Status]][[sv:Status]]\n\'\'\'Status\'\'\' is a state, condition or situation. \"Status\" often refers to [[social status]].\n\n*[[Status quo]]\n*[[Establishment]]\n*[[Conservative]]\n*[[Status symbol]]\n\n{{disambig}}','',13,'Budhi','20040720120633','',0,0,0,1,0.096520779699,'20040720120633','79959279879366'); INSERT INTO cur VALUES (885,0,'Basa_Jérman','\'\'\'German\'\'\' \'\'(Deutsch)\'\', a member of the western group of [[Germanic languages]], is one of the world\'s major [[language]]s. It is the language with the most native speakers in the [[European Union]]. It is spoken primarily in [[Germany]], [[Austria]], [[Liechtenstein]], the major part of [[Switzerland]], [[Luxembourg]], the \'\'Südtirol\'\' ([[South Tyrol]]) region of [[Italy]], the [[Opole Voivodship|Opole (\'\'Oppeln\'\') Voivodship]] of [[Poland]], the [[German_speaking_community_in_Belgium| East Cantons]] of [[Belgium]], parts of [[Romania]], [[Alsace]] (Elsass) and part of the Lorraine region of [[France]]. Additionally, several former colonial possessions of these countries, such as [[Namibia]], have sizable German-speaking populations, and there are German-speaking minorities in several eastern European countries, including [[Russia]], [[Hungary]] and [[Slovenia]], and in [[North America]] as well as some Latin American countries, like [[Argentina]] and in [[Brazil]], mainly in the states of [[Rio Grande Do Sul]], [[Santa Catarina]], [[Paraná]] e [[Espírito Santo]].\n\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" width=\"300\"\n! colspan=\"2\" bgcolor=lawngreen style=\"font-size:120%\"|German (\'\'Deutsch\'\')\n|-\n| valign=\"top\"|Spoken in:\n|[[Germany]], [[Switzerland]], [[Austria]], and 38 other countries.\n|-\n| valign=\"top\"|Region:\n| -\n|-\n| valign=\"top\"|Total speakers:\n|120 Million\n|-\n| valign=\"top\"|[[List of languages by total speakers|Ranking]]:\n|9\n|-\n| valign=\"top\"|[[Language families and languages|Genetic]]
[[Language families and languages|classification]]:\n|[[Indo-European languages|Indo-European]]
\n [[Germanic languages|Germanic]]
\n  [[West Germanic languages|West]]
\n   [[High German languages|High German]]
\n    [[German languages|German]]
\n     [[Middle German languages|Middle German]]
\n      [[East Middle German languages|East Middle German]]
\n       \'\'\'German\'\'\'\n|-\n! colspan=\"2\" bgcolor=lawngreen|Official status\n|-\n| valign=\"top\"|Official language of:\n| valign=\"top\"|[[Germany]], [[Liechtenstein]], [[Austria]], [[Belgium]], [[Italy]], [[Switzerland]], [[Luxembourg]], [[Denmark]], [[Namibia]], [[Poland]] and others\n|-\n| valign=\"top\"|Regulated by:\n| valign=\"top\"| -\n|-\n! colspan=\"2\" bgcolor=lawngreen|Language codes\n|-\n|[[ISO 639]]-1||de\n|-\n|ISO 639-2(B)||ger\n|-\n|ISO 639-2(T)||deu\n|-\n|[[SIL]]||GER\n|}\n\nThe [[Amish]] and some [[Mennonites]] also speak a dialect of German. Approximately 120 million people, or a quarter of all Europeans, speak German. German is the third most popular foreign language taught worldwide, and the second most popular in [[Europe]] (after English), the [[United States|USA]] and [[East Asia]] (Japan). It is an official language of the [[European Union]].\n\n==History==\nThe [[dialect]]s subject to the [[second Germanic sound shift]] during medieval times are regarded as part of the modern German language.\n\nAs a consequence of the colonization patterns, the [[Völkerwanderung]] (pronounced: [\'fœlk6vand@rUN]), the routes for trade and communication (chiefly the rivers), and of physical isolation (high mountains and deep forests) very different regional dialects developed. \nThese dialects, sometimes mutually unintelligible, were used across the [[Holy Roman Empire]].\n\nAs Germany was divided into many different [[state]]s, the only force working for a unification or [[standard language|standardization]] of German was a long process of several hundred years, in which writers tried to write and in a way, that was understood in the largest area.\n\nWhen [[Martin Luther]] translated the [[Bible]] (the [[New Testament]] in [[1521]] and the [[Old Testament]] in [[1534]]) he based his translation mainly on this already developed language, which was the most widely understood language at this time. In the beginning, copies of the Bible had a long list for each region, which translated words unknown in the region into the regional dialect. [[Roman Catholics]] rejected Luther\'s translation in the beginning and tried to create their own Catholic standard (\'\'Gemaines Deutsch\'\'). It took until the middle of the 18th century to create a standard, that was widely accepted, thus ending the period of [[Early New High German]]. \n\nGerman used to be the language of commerce and government in the [[Habsburg Empire]], which encompassed a large area of Central and Eastern Europe. Until the mid-nineteenth century it was essentially the language of townspeople throughout most of the Empire. It indicated that the speaker was a [[merchant]], an urbanite, not their nationality. Some towns, such as [[Prague]] and Budapest were gradually [[Germanisation|Germanized]] in the years after their incorporation into the Habsburg domain. Others, such as [[Bratislava]] (\'\'Pressburg\'\'), were originally settled during the Habsburg period and were primarily German at that time. A few towns such as [[Milano]] remained primarily non-German. However, most towns such as Prague, [[Budapest]], Bratislava, [[Zagreb]], and [[Ljubljana]] which later became national capitals were for the time primarily German, although they were surrounded by country that spoke other languages. \n\nUntil about 1800, Standard German was almost only a written language. In this time people in urban, northern Germany, who spoke dialects very different from Standard German learnt it almost like a foreign language and tried to pronounce it as close to the spelling as possible. Later this spoken form spread southward.\n\nMedia and written works are almost all produced in this [[variety (linguistics)|variety]] of [[High German]] (usually called Standard German in English or \'\'Hochdeutsch\'\' in German), which is understood in all areas of German languages (except by pre-school children in areas which speak only dialect - but in the age of TV even they usually learn to understand Standard German before school age).\n\nThe first dictionary of the [[Brothers Grimm]], the 16 parts of which were issued between [[1852]] and [[1960]], remains the most comprehensive guide to the words of the German language.\nIn [[1860]], grammatical and orthographical rules first appeared in the \'\'Duden Handbook\'\'.\nIn [[1901]], this was declared the standard definition of the German language in these matters.\nOfficial revisions of some of these rules were not issued until [[1998]].\n\n==Classification==\nGerman is a member of the West branch of the [[Germanic languages|Germanic]] family of languages, which in turn is part of the [[Indo-European language family]].\n\n===Official status===\nGerman is the only official language in [[Germany]], [[Liechtenstein]] and [[Austria]]; it shares official status in [[Belgium]] (with [[French (language)|French]] and [[Dutch (language)|Dutch]]), [[Italy]] (with [[Italian (language)|Italian]], French and [[Slovenian (language)|Slovenian]]), [[Switzerland]] (with French, Italian and [[Romansh]]), [[Luxembourg]] (with French and [[Luxembourgish language|Luxembourgish]]), and [[Denmark]] (with [[Danish language|Danish]]). It is one of the 20 official languages of the [[European Union]].\n\nIt is also a minority language in [[France]], [[Russia]], [[Kazakhstan]], [[Tajikistan]], [[Poland]], [[Romania]], [[Togo]], [[Cameroon]], the [[United States|USA]], [[Namibia]], [[Brazil]], [[Paraguay]], [[Hungary]], [[Czech Republic]], [[Slovakia]], [[the Netherlands]], [[Slovenia]], [[Ukraine]], [[Croatia]], [[Moldavia]], [[Australia]], [[Latvia]], [[Estonia]] and [[Lithuania]].\n\nGerman was once the lingua franca of central, eastern and northern Europe. Increasing influence from the [[English language]] has affected German recently. However, German remains one of the most popular foreign languages taught worldwide, and is more popular than French as a foreign language in Europe. 38% of all European citizens say they can converse in German.\n\n===Dialects===\nThe term \"German\" is used for several dialects of Germany and surrounding countries [[German speaking areas of America|and in North America]].\n\nThe dialects of Germany are typically divided into [[Low German]] and [[High German]].\nThe Low German dialects, or [[Low Saxon]] as they are sometimes known more precisely, are more closely related to [[Lower Franconian]] languages like [[Dutch language|Dutch]] than to the High German dialects, and from a linguist\'s perspective are not part of the German language proper.\nThe High German dialects spoken by Germanic communities in the former Soviet union and [[Ashkenazi Jew]]s have several unique features, and are usually considered the separate language [[Yiddish]].\nThere are also distinctive dialects of German which are or were primarily spoken in North America, including [[Pennsylvania German language|Pennsylvania German]], [[Texas German]], and [[Hutterite German]].\n\nThe modern dialects of German proper are divided into [[Middle German language|Middle German]] and [[Upper German language|Upper German]]; Standard German is based on Middle German, while [[Austrian language|Austrian]] and [[Swiss German]] dialects are Upper German.\nA moderately complete listing of these dialects may be found at [[High German]].\n\n\n\n\n\n==Grammar==\n\'\'Main article: [[German grammar]]\'\'\n\n\n\n==Writing system==\nGerman is written using the [[Latin alphabet]]. In addition to the 26 standard letters, German has three vowels with [[Umlaut]], namely \'\'ä\'\', \'\'ö\'\' and \'\'ü\'\', as well as a special symbol for \"ss\", which is only used in special cases: [[ß|ß]]. Until recently, however, German was printed in Gothic [[black letter|black letters]] ([[Fraktur]], or [[typeface#Schwabacher|Schwabacher]]) and written in [[Sütterlin]]. These variants of the Latin alphabet are very different from the serif or sans serif [[typeface|typefaces]] used today, and are difficult for the untrained to read.\n\n==Orthography==\n\'\'Main article: [[German pronunciation]]\'\'. \n\n==Examples==\n* [[Common phrases in different languages]]\n* [[List of German expressions in English]]\n\n==See also==\n* [[Umlaut]], [[ß|ß]]\n* [[German spelling reform]]\n* [[Germish]]\n* [[German family name etymology]]\n* [[Ethnic German]]\n\n==Names of the German language in other languages==\n\nBecause of the turbulent history of both Germany and the German language, the names that other peoples have chosen to use to refer to it varies more than for most other languages.\n\nIn general, the names for the German language can be arranged in five groups according to their origin:\n\n{| border=\"0\" cellpadding=\"5\"\n|- valign=\"top\"\n| \'\'\'1.\'\'\' From the proto-Germanic word for \"people\", \"folk\":\n\n*[[Chinese language|Chinese]]: \'\'德语\'\' (\'\'de2 yu3\'\')\n*[[Danish language|Danish]]: \'\'tysk\'\'\n*[[Dutch language|Dutch]]: \'\'Duits\'\'\n*[[German language|German]]: \'\'Deutsch\'\'\n*[[Icelandic language|Icelandic]]: \'\'þysk\'\'\n*[[Italian language|Italian]]: \'\'tedesco\'\'\n*[[Japanese language|Japanese]]: \'\'ドイツ語\'\' (\'\'doitsu-go\'\')\n*[[Korean language|Korean]]: \'\'독어\'\', \'\'德語\'\' (\'\'tog-ŏ\'\')\n*[[Latvian language|Latvian]]: \'\'vācu\'\' or \'\'vāciešu\'\'\n*[[Norwegian language|Norwegian]]: \'\'tysk\'\'\n*[[Swedish language|Swedish]]: \'\'tyska\'\'\n*[[Vietnamese language|Vietnamese]]: \'\'tiếng Đức\'\'\n*[[Yiddish]]: \'\'daytsch\'\' or \'\'daytsh\'\'\n\n| \'\'\'2.\'\'\' From the name of the Germanic people:\n\n*[[Albanian language|Albanian]]: \'\'gjermanishte\'\'\n*[[English language|English]]: \'\'German\'\'\n*[[Esperanto language|Esperanto]]: \'\'germana lingvo\'\'\n*[[Greek language|Greek]]: \'\'Γερμανικά\'\'\n*[[Hebrew language|Hebrew]]: \'\'גרמנית\'\' (\'\'germanit\'\')\n*[[Irish language|Irish]]: \'\'Gearmáinis\'\'\n*[[Romanian language|Romanian]]: \'\'germană\'\'\n\n| \'\'\'3.\'\'\' From the name of the Saxonian tribe:\n\n*[[Estonian language|Estonian]]: \'\'saksa\'\'\n*[[Finnish language|Finnish]]: \'\'saksa\'\'\n\n|- valign=\"top\"\n| \'\'\'4.\'\'\' From the Old Slavic word for \"mute\":\n\n*[[Bulgarian language|Bulgarian]]: \'\'немски\'\'\n*[[Czech language|Czech]]: \'\'němčina\'\'\n*[[Hungarian language|Hungarian]]: \'\'német\'\'\n*[[Polish language|Polish]]: \'\'niemiecki, niemczyzna\'\'\n*[[Romanian language|Romanian]]: \'\'nemțește\'\'\n*[[Russian language|Russian]]: \'\'неме́цкий\'\'\n*[[Slovak language|Slovak]]:\'\'nemčina\'\'\n*[[Slovenian language|Slovenian]]: \'\'nemščina\'\'\n*[[Ukrainian language|Ukrainian]]: \'\'німецький\'\'\n\n| \'\'\'5.\'\'\' From the name of the Alemannian tribe:\n\n*[[French language|French]]: \'\'allemand\'\'\n*[[Portuguese language|Portuguese]]: \'\'alemão\'\'\n*[[Spanish language|Spanish]]: \'\'alemán\'\'\n*[[Turkish language|Turkish]]: \'\'Alman\'\'\n*[[Welsh language|Welsh]]: \'\'Almaeneg\'\'\n\n|}\n\n==External links==\n* [http://www.ethnologue.com/show_language.asp?code=GER Ethnologue report for German]\n* [http://www.sprachprofi.de.vu/english/d.htm Free online resources for learners]\n* [http://www.vds-ev.de Verein Deutsche Sprache] (in German)\n* A beginning [http://wikibooks.org/wiki/German German Language Textbook] under development at [http://wikibooks.org/ Wikibooks]\n* [http://www.diwa.info/ Sprachatlas des Deutschen Reichs] Project publishing the 19th century \'\'Linguistic Atlas of the German Empire\'\'\n===Phrase and word translations===\n* [http://dict.cc Another English-German Dictionary]\n* [http://www.websters-online-dictionary.org/definition/German-english/ German - English Dictionary]: from [http://www.websters-online-dictionary.org Webster\'s Online Dictionary] - the Rosetta Edition.\n* [http://www.online-dictionary.biz/english/german German dictionary] German-English-German dictionary.\n* [http://dict.leo.org/ The LEO Online Dictionary] German-English-German dictionary.\n\n== Reference ==\n* [[George O. Curme]], \'\'[[A Grammar of the German Language]]\'\' (1904, 1922) - the most complete and authoritative work in English\n\n[[Category:High German languages]]\n[[Category:Languages of Belgium]]\n[[Category:Languages of France]]\n[[Category:Languages of Italy]]\n[[Category:Languages of Switzerland]]\n[[Category:Uvular R]]\n\n[[af:Duits]]\n[[az:German_qrupu]]\n[[da:Tysk sprog]]\n[[de:Deutsche Sprache]]\n[[et:Saksa keel]]\n[[es:Idioma alemán]]\n[[eo:Germana lingvo]]\n[[fr:Allemand]]\n[[he:גרמנית]]\n[[ja:ドイツ語]]\n[[ko:게르만어]]\n[[la:Lingua Germanica moderna (theotisca)]]\n[[nl:Duits]]\n[[no:Tysk språk]]\n[[nds:Düütsch]]\n[[pl:Język niemiecki]]\n[[pt:Língua alemã]]\n[[ro:Limba germană]]\n[[simple:German language]]\n[[sl:Nemščina]]\n[[sv:Germanska språk]]\n[[tokipona:toki Tosi]]\n[[zh-cn:德语]]\n[[zh-tw:德語]]','',13,'Budhi','20040720120742','',0,0,0,1,0.771545930659,'20040720120742','79959279879257'); INSERT INTO cur VALUES (886,0,'List_of_national_and_international_statistical_services','== National statistical services ==\n*[[Australia]]: [[Australian Bureau of Statistics]]\n*[[Brazil]]: Brazilian Institute of Geography and Statistics ([[IBGE]])\n*[[Belgium]]: [[Statistics Belgium]]\n*[[Canada]]: [[Statistics Canada]]\n*[[Colombia]]: Departamento Administrativo Nacional de Estadistica ([[DANE]])\n*[[Denmark]]: Danmarks statistik - http://www.dst.dk\n*[[France]]: [[National Institute for Statistics and Economic Studies]]\n*[[Germany]]: [[Statistisches Bundesamt]] - http://www.destatis.de\n*[[Greece]]: [[National Statistical Service of Greece]]\n*[[India]]: [[Indian Statistical Institute]]\n*[[India]]: [[Indian Agricultural Statistics Research Institute]]\n*[[Ireland]]: [[Central Statistics Office of Ireland]]\n*[[The Netherlands]]: [[Centraal Bureau voor de Statistiek]] - http://www.cbs.nl\n*[[New Zealand]]: [[Statistics New Zealand]]\n*[[Portugal]]: [[Instituto Nacional de Estatistica]] - http://www.ine.pt/\n*[[Sweden]]: [[Statistics Sweden]] - http://www.scb.se/\n*[[United Kingdom]]: [[Office for National Statistics]] (ONS)\n*[[USA]]: [[FedStats]]\n*[[USA]]: [[United States Census Bureau]]\n*[[USA]]: [[Bureau of Labor Statistics]]\n\n== International statistical services ==\n*[[Eurostat]]\n*[[United Nations]] Statistics Division - http://unstats.un.org\n*[[UNESCO]] Institute for Statistics - http://www.uis.unesco.org\n*[http://cs3-hq.oecd.org/scripts/stats/source/alpha.asp?Let=INT Worldwide statistical sources]\n\n== See also ==\n*[[Statistics]]\n*[[List of statistical topics]]\n*[[List of academic statistical associations]]','',13,'Budhi','20040720120912','',0,0,0,1,0.76502472291,'20050209000836','79959279879087'); INSERT INTO cur VALUES (887,0,'Sénsus','\'\'\'Sénsus\'\'\' nyaeta proses keur neangan informasi ngeunaan unggal anggota dina populasi (henteu ngan keur populasi [[manusa]]). Sénsus ieu mangrupa métode pikeun ngumpulkeun data [[statistik]].\n\n{{pondok}}\n\n[[da:Folketælling]]\n[[de:Volkszählung]]\n[[en:Census]]\n[[es:Censo]]\n[[fr:Recensement]]\n[[ja:国勢調査]]\n[[simple:Census]]\n[[sl:Popis prebivalstva]]\n[[uk:Перепис населення]]\n[[zh:人口普查]]','',3,'Kandar','20050225083952','',0,0,0,0,0.082517976445,'20050303211247','79949774916047'); INSERT INTO cur VALUES (888,0,'Kasimpulan_statistik','\'\'\'Kasimpulan statistik\'\'\' atawa \'\'\'summary statistics\'\'\' diperlukeun mun susunan observasi hayang disimpulkeun sarta hayang ngajelaskeun sagampang-gampangna. Statistikawan umumna nyoba ngajelaskeun observasi dina \n# ukuran lokasi, atawa [[central tendency]], saperti [[arithmetic mean]]\n# ukuran [[dispersi statistik]] saperti [[simpangan baku]]\n# ukuran bentuk distribusi saperti [[skewness]] atawa [[kurtosis]]\n\n[[Median]], [[mode]], sarta [[interquartile mean]] ngarupakeun ukuran lokasi oge. Keur ngajelaskeun [[dispersi statistik]], urang bisa make [[rentang (statistik)|rentang]], [[interquartile range]], atawa [[simpangan mutlak]].\n\n[[Koefisien Gini]] asalna diwangun keur ngukur kateusaruaan panghasilan, tapi bisa oge dipake keur kaperluan sejenna.\n\n\nbalik ka [[tiori statistik]] -- [[summarizing statistical data]]','',3,'Kandar','20050208062828','',0,0,0,0,0.300758376858,'20050208062828','79949791937171'); INSERT INTO cur VALUES (889,0,'Statistik_deskriptif','\'\'\'Statistik déskriptif\'\'\' nyaéta hiji cabang [[statistik]] nu denotes any of the many techniques used to summarize a set of data. In a sense, we are using the data on members of a set to describe the set. Téhnikna biasana digolongkeun kana:\n# Déskripsi grafis nu migunakeun grafik pikeun ngajinekkeun data.\n# Déskripsi tabular nu maké tabel pikeun nyimpulkeun data.\n# Déskripsi paramétrik nu ngaéstimasi the values of certain parameters which we assume to complete the description of the set of data.\n\nSacara umum, data statistis bisa didadarkeun salaku daptar \'\'subjék\'\' atawa \'\'unit\'\' katut data nu patali jeung masing-masingna. Although most research uses many data types for each Unit, we will limit ourselves to just one data item each for this simple introduction. \n\nWe have two objectives for our summary:\n\n#We want to choose a [[statistic]] that shows how different \'\'units\'\' seem similar. Statistical textbooks call the solution to this objective, a \'\'measure of [[central tendency]].\'\'\n#We want to choose another [[statistic]] that shows how they differ. This kind of statistic is often called a \'\'measure of [[statistical variability]]\'\'.\n\nWhen we are summarizing a quantity like length or weight or age, it is common to answer the first question with the \'\'\'[[arithmetic mean]],\'\'\' the \'\'\'[[median]],\'\'\' or the \'\'\'[[mode]].\'\'\' Sometimes, we choose specific values from the [[cumulative distribution function]] called [[quantile]]s.\n\nUkuran variabiliti ilahar keur [[quantitative data|data kuantitatip]] nyaeta [[varian]]; akar kuadratna nyaeta [[simpangan baku]]; [[rentang (statistik) | rentang]]; [[interquartile range]]; sarta [[simpangan mutlak]].\n\nTempo oge\n* [[statistical regularity]]\n* [[planning statistical research]]\n* [[statistical inference]]\n* [[kasimpulan statistik]]\n* [[data mining]]\n\n[[de:Deskriptive Statistik]]\n[[fr:Statistique descriptive]]','',13,'Budhi','20041224233800','',0,0,0,0,0.168588880062,'20041224234252','79958775766199'); INSERT INTO cur VALUES (890,0,'Bayesian_statistics','#REDIRECT [[Bayesian inference]]','',0,'220.31.240.165','20040722002915','',0,1,0,0,0.784726655476,'20040722002915','79959277997084'); INSERT INTO cur VALUES (891,0,'Probability_interpretations','The word \'\'[[probability]]\'\' has been used in a variety of ways since it was first coined in relation to [[games of chance]].\n\nThere are two broad categories of probability interpretations: [[frequentism|Frequentists]] assign probabilities only to random events according to their relative frequencies of occurrence or to subsets of populations as proportions of the whole. [[Bayesian probability|Bayesians]] assign probabilities to any statement, even when no random process is involved, as a way to represent its plausibility. As such, the scope of Bayesian inquiries include the scope of frequentist inquiries.\n\n== [[Epistemology|Epistemological]] controversy ==\n\nWhile frequentism is widely accepted as a scientific tool, the use of Bayesian probability often raises the philosophical debate as to whether it can contribute valid [[theory of justification|justifications]] of [[belief]]. \n\nIn order to resolve a particular problem using probability theory, Bayesians will accept to apply a particular probability model, such as the [[urn model]], to a [[thought experiment]]. The issue is that for a given problem, multiple [[thought experiment]]s could apply, and choosing one is a matter of intuition or belief. The \"[[sunrise problem]]\"\" illustrates the issue. A particular version of this issue is the [[reference class problem]].\n\n== Practical controversy ==\n\nThe difference of view has also many implications for the methods by which statistics is practiced, and for the way in which conclusions are expressed. When comparing two hypotheses and using some information, frequency methods would typically result in the rejection or non-rejection of the original hypothesis with a particular degree of confidence, while Bayesian methods would suggest that one hypothesis was more probable than the other. \n\nAs a possible solution, the [[pilihan probabiliti|eclectic view]] accepts both interpretations: depending on the situation, one selects one of the 2 interpretations for pragmatic, or principled, reasons.\n\n== Axiomatic probability ==\n\nThe mathematics of probability can be developed on an entirely axiomatic basis that is independent of any interpretation: see the articles on [[probability theory]] and [[probability axioms]] for a detailed treatment.\n\n== Tempo ogé ==\n* [[Frequentism]]\n* [[Bayesian probability]]\n* [[Pilihan probabiliti]]\n* [[Sunrise problem]]','/* See also */',13,'Budhi','20041226002303','',0,0,1,0,0.819957643198,'20041226002303','79958773997696'); INSERT INTO cur VALUES (892,0,'Bayesian_probability','\'\'\'Bayesianism\'\'\' ngarupakeun [[philosophical]] tenet that the mathematical theory of [[kamungkinan|probability]] applies to the degree of plausibility of statements, or to the degree of belief of rational agents in the truth of statements; when used with [[Bayes theorem]], it then becomes [[Bayesian inference]]. \nThis is in contrast to [[frequentism]], which rejects degree-of-belief interpretations of mathematical probability, and assigns probabilities only to random events according to their relative frequencies of occurrence.\nThe Bayesian interpretation of probability allows probabilities assigned to random events, \nbut also allows the assignment of probabilities to any other kind of statement.\n\nWhereas a frequentist and a Bayesian might both assign probability 1/2 to the event of getting a head when a coin is tossed, only a Bayesian might assign probability 1/1000 to personal belief in the proposition that there was life on Mars a billion years ago, without intending to assert anything about any relative frequency.\n\n== Sajarah kamungkinan Bayesian ==\n\n\"Bayesian\" probability is named after [[Thomas Bayes]], who proved a special case of what is called [[Bayes\' theorem]]. \n(However, the term \"Bayesian\" came into use only around [[1950]],\nand in fact it is not clear that Bayes would have endorsed the very broad interpretation of probability now called \"Bayesian\".)\n[[Pierre-Simon Laplace|Laplace]] independently proved a more general version of Bayes\' theorem and put it to good use in solving problems in celestial mechanics, medical statistics and, by some accounts, even jurisprudence. \n\nFor instance, [[Pierre-Simon Laplace|Laplace]] estimated the mass of Saturn, given orbital data that were available to him from various astronomical observations. He presented the result together with an indication of its uncertainty, stating it like this: `It is a bet of 11000 to 1 that the error in this result is not within 1/100th of its value\'. He would have won the bet, as another 150 years\' accumulation of data has changed the estimate by only 0.63%. \n\nThe general outlook of Bayesian probability,\npromoted by Laplace and several later authors,\nhas been that the laws of probability apply equally to propositions of all kinds.\nSeveral attempts have been made to ground this intuitive notion in formal demonstrations.\nOne line of argument is based on [[betting]],\nas expressed by [[Bruno de Finetti]] and others.\nAnother line of argument is based on probability as an extension of ordinary [[logic]] to degrees of belief other than 0 and 1.\nThis argument has been expounded by [[Harold Jeffreys]], [[Richard Threlkeld Cox|Richard T. Cox]], and [[Edwin Thompson Jaynes|Edwin Jaynes]].\nOther well-known proponents of Bayesian probability have included \n[[L. J. Savage]], [[Frank P. Ramsey]], [[John Maynard Keynes]], [[B.O. Koopman]].\n\nThe frequentist interpretation of probability was preferred by some of the most influential figures in statistics during the first half of the twentieth century, \nincluding [[Ronald A. Fisher|R.A. Fisher]], [[Egon Pearson]], and [[Jerzy Neyman]]. \nThus for some decades the Bayesian interpretation fell out of favor. \nBeginning about [[1950]] and continuing into the present day,\nthe work of Savage, Koopman, [[Abraham Wald]], and others has led to broader acceptance.\n\n==Rupa-rupa kamungkinan Bayesian==\n\nThe terms \'\'subjective probability\'\', \'\'personal probability\'\', \'\'epistemic probability\'\' and \'\'logical probability\'\' describe some of the schools of thought which are customarily called \"Bayesian\". These overlap but there are differences of emphasis. There are also Bayesians who do not accept the subjectivity. The main protagonists of the objectivist school are [[Edwin Thompson Jaynes]] (who died in 1998) and [[Harold Jeffreys]]. Perhaps the main protagonist now living is James Berger of Duke University. There are still others, such as Jose Bernardo, who accept some degree of subjectivity but who believe there is a need for \"reference priors\" in many practical situations.\n\nAdvocates of \'\'\'logical probability\'\'\' would like to codify techniques whereby if two people have the same information relevant to the truth of an uncertain proposition, then they would assign the same probability. No one has any idea how to do that except in simple cases, and then the validity of proposed methods is subject to philosophical controversy. The proponents of this view include Sir [[Harold Jeffreys]], [[Richard Threlkeld Cox]], and [[Edwin Thompson Jaynes|Edwin Jaynes]]. Its critics challenge the suggestion that it is possible or necessary in the absence of information to start with an objective prior belief which would be acceptable to all.\n\n\'\'\'Subjective probability\'\'\' is supposed to measure how sure an individual is of an uncertain proposition.\n\n== Bayesian jeung kamungkinan nu remen digunakeun ==\n\nThe Bayesian approach is in contrast to the concept of \'\'[[frequency probability]]\'\' where probability is held to be derived from observed or imagined frequency distributions or proportions of populations. The difference has many implications for the methods by which [[statistik]] is practiced when following one model or the other, and also for the way in which conclusions are expressed. When comparing two hypotheses and using some information, frequency methods would typically result in the rejection or non-rejection of the original hypothesis with a particular degree of confidence, while Bayesian methods would suggest that one hypothesis was more probable than the other or that the expected loss associated with one was less than the expected loss of the other.\n\nBayes\' theorem is often used to update the plausibility of a given statement in light of new evidence. \nFor example, Laplace estimated the mass of Saturn (described above) in this way.\nAccording to the [[frequency probability]] definition, however, the [[probability theory|laws of probability]] are not applicable to this problem. This is because the mass of Saturn is a constant and not a random variable, therefore, it has no frequency distribution and so the laws of probability cannot be used.\n\n== Pamakean kamungkinan Bayesian ==\n\nToday, there are a variety of applications of personal probability that have gained wide acceptance. Some schools of thought emphasise [[Cox\'s theorem]] and Jaynes\' [[principle of maximum entropy]] as cornerstones of the theory, while others may claim that Bayesian methods are more general and give better results in practice than [[frequency probability]]. See [[Bayesian inference]] for applications and [[Bayes\' Theorem]] for the mathematics.\n\n[[Bayesian inference]] is proposed as a model of the [[scientific method]]. It is claimed that updating probabilities via [[Bayes\' theorem]] is similar to the scientific method, in which one starts with an initial set of beliefs about the relative plausiblity of various [[hypothesis|hypotheses]], collects new information (for example by conducting an [[experiment]]), and adjusts the original set of beliefs in the light of the new information to produce a more refined set of beliefs of the plausibility of the different hypotheses. See [[Bayesian inference]] for more information in this regard.\n\n== Tempo oge ==\n\n* [[uncertainty]]\n* [[inference]]\n* [[Doomsday argument]] for a controversial use of Bayesian inference\n\n== Tumbu kaluar jeung rujukan ==\n\n* [http://www.inference.phy.cam.ac.uk/mackay/itila/book.html On-line textbook: Information Theory, Inference, and Learning Algorithms], by [[David MacKay]], has many chapters on Bayesian methods, including introductory examples; compelling arguments in favour of Bayesian methods (in the style of [[Edwin Thompson Jaynes|Edwin Jaynes]]); state-of-the-art [[Monte Carlo method]]s, [[message-passing method]]s, and [[Calculus of variations|variational methods]]; and examples illustrating the intimate connections between Bayesian inference and [[data compression]].\n\n* http://www-groups.dcs.st-andrews.ac.uk/history/Mathematicians/Ramsey.html\n\n* David Howie: \'\'Interpreting Probability, Controversies and Developments in the Early Twentieth Century\'\', Cambridge University Press, 2002, ISBN 0521812518\n\n* Jeff Miller [http://members.aol.com/jeff570/b.html \"Earliest Known Uses of Some of the Words of Mathematics (B)\"]\n\n* Paul Graham [http://www.paulgraham.com/better.html \"Bayesian spam filtering\"]\n[[Category:Probability and statistics]]\n\n[[Category:Probability and statistics]]\n\n[[de:Bayesscher Wahrscheinlichkeitsbegriff]]\n[[pl:Prawdopodobieństwo subiektywne]]','/* Bayesian jeung kamungkinan nu remen digunakeun */',13,'Budhi','20041225125138','',0,0,1,0,0.620818286492,'20050101215719','79958774874861'); INSERT INTO cur VALUES (893,0,'Uncertainty','\'\'\'Uncertainty\'\'\' is an inevitable part of the assertion of [[pangaweruh]], see [[Bayesian probability]].\n\n[[Mathematician]]s handle uncertainty using [[probability theory]], [[Dempster-Shafer theory]], [[fuzzy logic]]. See also [[probability]].\n\nExamples where uncertainty is important:\n\n* Investing in financial markets such as the stock market.\n* Uncertainty is designed into [[game]]s, most notably in [[gambling]], where [[chance]] is central to [[play]].\n* In [[physics]] in certain situations, uncertainty has been elevated into a principle, the [[uncertainty principle]].\n* In [[meteorology|weather forcasting]] it is now commonplace to include data on the degree of uncertainty in a [[weather forecast]].\n* Uncertainty is often an important factor in [[economics]].\n* In [[metrology]],uncertainty is built into all [[measuring instruments]] (scales, oscilloscopes, force gages, rulers, thermometers, etc). The procedure for calculating measurement uncertainty has been documented by the National Institute for Standards and Technology ([[NIST]]) in their publication NIST Technical Note 1297 \"Guidelines for Evaluating and Expressing the Uncertinty of NIST Measurement Results\". The uncertainty of the result of a measurement generally consists of several components which may be grouped into two categories according to the method used to estimate their numerical values:\n*# those which are evaluated by [[statistical]] methods,\n*# those which are evaluated by other means.\n\n== Further reading ==\n* [http://www.nytimes.com/2002/07/31/science/31PART.html?todaysheadlines New York Times article, \"Studies Suggest Unknown Form of Matter Exists\"] by Ames Glanz, July 31, 2002\n* [http://www.fasor.com/iso25/bibliography_of_uncertainty.htm Bibliography of Papers Regarding Measurement Uncertainty]','',13,'Budhi','20040720130938','',0,0,0,0,0.819929137276,'20040720130938','79959279869061'); INSERT INTO cur VALUES (894,0,'Statistik_téhnik','\'\'\'Engineering statistics\'\'\' is a branch of [[statistik]] that has two subtopics which are particular to [[engineering]]:\n# [[Quality control]] and [[process control]] use statistics as a tool to manage conformance to specifications of manufacturing processes and their products.\n# [[Time and methods engineering]] use statistics to study repetitive operations in manufacturing in order to set standards and find optimum (in some sense) manufacturing procedures.','',0,'220.31.240.165','20040720134346','',0,0,0,0,0.283352149317,'20040720134346','79959279865653'); INSERT INTO cur VALUES (895,0,'Bayes\'_theorem','\'\'\'Teorema Bayes\'\'\' ngarupakeun hasil dina [[tiori probabiliti]], which gives the [[conditional probability|conditional]] [[probability distribution]] of a [[variabel acak]] \'\'A\'\' given \'\'B\'\' in terms of the conditional probability distribution of variable \'\'B\'\' given \'\'A\'\' and the [[conditional probability|marginal probability distribution]] of \'\'A\'\' alone.\n\nIn the context of [[Bayesian probability theory]] and [[statistical inference]], the marginal probability distribution of \'\'A\'\' alone is usually called the \'\'[[prior probability distribution]]\'\' or simply the \'\'prior\'\'. The conditional distribution of \'\'A\'\' given the \"data\" \'\'B\'\' is called the \'\'[[posterior probability distribution]]\'\' or just the \'\'posterior\'\'.\n\nAs a mathematical [[theorem]], Bayes\' theorem is valid regardless of whether one adopts a [[frequentism|frequentist]] or a [[Bayesian probability|Bayesian]] interpretation of [[probability]].\nHowever, there is disagreement as to what kinds of variables can be substituted for \'\'A\'\' and \'\'B\'\' in the theorem; this topic is treated at greater length in the articles on [[Bayesian probability]] and [[frequency probability|frequentist probability]].\n\n==Historical remarks==\n\nBayes\' theorem is named after the Reverend [[Thomas Bayes]] (1702–61). Bayes worked on the problem of computing a distribution for the parameter of a binomial distribution (to use modern terminology); his work was edited and presented posthumously (1763) by his friend Richard Price, in \'\'An Essay towards solving a Problem in [[the Doctrine of Chances]]\'\'. Bayes\' results were replicated and extended by [[Pierre-Simon Laplace|Laplace]] in an essay of 1774, who apparently was not aware of Bayes\' work.\n\nOne of Bayes\' results (Proposition 5) gives a simple description of [[conditional probability]], and shows that it does not depend on the order in which things occur:\n\n:\'\'If there be two subsequent events, the probability of the second b/N and the probability of both together P/N, and it being first discovered that the second event has also happened, the probability I am right \'\'[i.e. the conditional probability of the first event being true given that the second has happened]\'\' is P/b.\'\' \n\nThe main result (Proposition 9 in the essay) derived by Bayes is the following: assuming a uniform distribution for the prior distribution of the binomial parameter \'\'p\'\', the probability that \'\'p\'\' is between two values \'\'a\'\' and \'\'b\'\' is \n\n\n:\n\\frac {\\int_a^b \\begin{pmatrix} n+m \\\\ m \\end{pmatrix} p^m (1-p)^n\\,dp}\n {\\int_0^1 \\begin{pmatrix} n+m \\\\ m \\end{pmatrix} p^m (1-p)^n\\,dp}\n\n\nwhere \'\'m\'\' is the number of observed successes and \'\'n\'\' the number of observed failures. His preliminary results, in particular Propositions 3, 4, and 5, imply the result now called Bayes\' Theorem (as described below), but it does not appear that Bayes himself emphasized or focused on that result.\n\nWhat is \"Bayesian\" about Proposition 9 is that Bayes presented it as a probability for the parameter \'\'p\'\'. That is, not only can one compute probabilities for experimental outcomes, but also for the parameter which governs them, and the same algebra is used to make inferences of either kind. Interestingly, Bayes actually states his question in a way that might make the idea of assigning a probability distribution to a parameter palatable to a frequentist. He supposes that a billiard ball is thrown at random onto a billiard table, and that the probabilities \'\'p\'\' and \'\'q\'\' are the probabilities that subsequent billiard balls will fall above or below the first ball. By making the binomial parameter \'\'p\'\' depend on a random event, he cleverly escapes a philosophical quagmire that he most likely was not even aware was an issue.\n\n==Statement of Bayes\' theorem==\n\nBayes\' theorem is a relation among conditional and marginal probabilities. It can be viewed as a means of incorporating information, from an observation, for example, to produce a modified or updated probability distribution.\n\nSuppose the marginal probability density function or probability mass function of a random variable \'\'X\'\' is\n\n:f_X(x) \\;\n\n(be very careful to distinguish between the capital \'\'X\'\' and the lower-case \'\'x\'\' above!). This is the \'\'prior probability distribution\'\' of \'\'X\'\'. Suppose the conditional probability density function or probability mass function of \'\'Y\'\' given \'\'X\'\' = \'\'x\'\' (a function of \'\'y\'\') is\n\n:f_{Y\\mid X=x}(y).\n\nAs a function of \'\'x\'\', this is the [[likelihood function]]\n\n:L_{X\\mid Y=y}(x) = f_{Y\\mid X=x}(y).\n\nThe likelihood function is not a probability density function or a probability mass function for \'\'X\'\', since it need not integrate (or sum) over \'\'x\'\' to produce 1.\n\nBayes theorem says:\n\n::\'\'\'To get the posterior probability distribution of \'\'X\'\' (i.e., the conditional probability distribution of \'\'X\'\' given \'\'Y\'\'), multiply the prior probability density function (or mass function) for \'\'X\'\' by the likelihood function, and then normalize to produce a probability distribution.\'\'\'\n\n\"Normalize\" means to multiply or divide by a constant to make the resulting function a probability density function or a probability mass function. Thus the posterior probability density function is\n\n:f_{X\\mid Y=y}(x)={f_X(x) L_{X\\mid Y=y}(x) \\over \\mbox{constant}}.\n\nThe [[normalizing constant]] in the denominator is\n\n:\\int_{-\\infty}^\\infty f_X(x) L_{X\\mid Y=y}(x)\\,dx.\n\nIn the discrete case, one would have a sum rather than an integral. If one takes the [[measure (mathematics)|measure-theoretic]] viewpoint, either is an integral.\n\n===Conto===\n\nSuppose the proportion \'\'R\'\' of voters who will vote \"yes\" in a referendum is [[sebaran seragam]] between 0 and 1. That is the prior probability distribution of \'\'R\'\'. A random sample of 10 voters is taken, and it is found that seven of them will vote \"yes\". The conditional distribution of the number \'\'X\'\' of voters in this small sample who will vote \"yes\", given that (capital) \'\'R\'\' is some particular number (lower-case) \'\'r\'\', is a [[sebaran binomial]] with parameters 10 and \'\'r\'\', i.e., it is the distribution of the number of \"successes\" in 10 [[statistical independence|independent]] [[Bernoulli trial]]s with probability \'\'r\'\' of success on each trial. One therefore has\n\n:f_{X\\mid R=r}(x)={10 \\choose x}r^x (1-r)^{10-x}.\n\nSince \'\'X\'\' was observed to be 7, the likelihood function is\n\n:L(r)={10 \\choose 7}r^7 (1-r)^3\n\nfor 0 ≤ \'\'r\'\' ≤ 1. The prior probability density function is\n\n:f_R(r)=1\\ \\mbox{if}\\ 0\\leq r\\leq 1\n\nand 0 otherwise. Multiplying the prior by the likelihood, we get\n\n:f_R(r)L(r)={10 \\choose 7}r^7 (1-r)^3\n\nif 0 ≤ \'\'r\'\' ≤ 1, and 0 otherwise. Integrating, we get\n\n:\\int_0^1 r^7(1-r)^3\\,dr=1/1320,\n\nso the posterior probability density function is\n\n:f_{R\\mid X=7}(r)=1320r^7 (1-r)^3\n\nfor \'\'r\'\' between 0 and 1, and 0 otherwise.\n\nOne may be interested in the probability that more than half the voters will vote \"yes\". The \'\'prior probability\'\' that more than half the voters will vote \"yes\" is 1/2, by the symmetry of the [[sebaran seragam]]. The posterior probability that more than half the voters will vote \"yes\", i.e., the conditional probability given the outcome of the opinion poll -- that seven of the 10 voters questioned will vote \"yes\" -- is\n\n:1320\\int_{1/2}^1 r^7(1-r)^3\\,dr=0.88671875\n\nabout an \"89% chance\".\n\n==Derivation in the discrete case==\n\nTo derive Bayes\' theorem in the discrete case, note first from the definition of conditional probability that\n\n:P(A|B) P(B) = P(A, B) = P(B|A) P(A)\\,\n\ndenoting by \'\'P\'\'(\'\'A\'\',\'\'B\'\') the [[joint probability]] of \'\'A\'\' and \'\'B\'\'.\nDividing the left- and right-hand sides by \'\'P\'\'(\'\'B\'\'), we obtain\n\n:P(A|B) = \\frac{P(B | A) P(A)}{P(B)}\n\nwhich is Bayes\' theorem.\n\nEach term in Bayes\' theorem has a conventional name.\nThe term \'\'P\'\'(\'\'A\'\') is called the \'\'[[prior probability]]\'\' of \'\'A\'\'.\nIt is \"prior\" in the sense that it precedes any information about \'\'B\'\'.\n\'\'P\'\'(\'\'A\'\') is also the \'\'[[marginal probability]]\'\' of \'\'A\'\'.\nThe term \'\'P\'\'(\'\'A\'\'|\'\'B\'\') is called the \'\'[[posterior probability]]\'\' of \'\'A\'\', given \'\'B\'\'. It is \"posterior\" in the sense that it is derived from or entailed by the specified value of \'\'B\'\'.\nThe term \'\'P\'\'(\'\'B\'\'|\'\'A\'\'), for a specific value of \'\'B\'\', is called the \'\'[[likelihood function]]\'\' for \'\'A\'\' given \'\'B\'\' and can also be written as \'\'L\'\'(\'\'A\'\'|\'\'B\'\').\nThe term \'\'P\'\'(\'\'B\'\') is the prior or marginal probability of \'\'B\'\', and acts as the \'\'[[normalizing constant]]\'\'.\n\n===Alternative forms of Bayes\' theorem===\n\nBayes\' theorem is often embellished by noting that\n\n:P(B) = P(A, B) + P(A^C, B) = P(B|A) P(A) + P(B|A^C) P(A^C)\\,\n\nso the theorem can be restated as\n\n:P(A|B) = \\frac{P(B | A) P(A)}{P(B|A)P(A) + P(B|A^C)P(A^C)}\\, ,\n\nwhere \'\'A\'\'\'\'C\'\' is the [[Complement (set theory)#Absolute complement|complement]]ary event of \'\'A\'\'. More generally, where {\'\'A\'\'\'\'i\'\'} forms a [[partition]] of the event space,\n\n:P(A_i|B) = \\frac{P(B | A_i) P(A_i)}{\\sum_j P(B|A_j)P(A_j)}\\, ,\n\nfor any \'\'A\'\'\'\'i\'\' in the partition.\n\nSee also the [[law of total probability]].\n\n===Bayes\' theorem for probability densities===\n\nThere is also a version of Bayes\' theorem for continuous distributions.\nIt is somewhat harder to derive, since probability densities, \nstrictly speaking, are not probabilities,\nso Bayes\' theorem has to be established by a limit process;\nsee Papoulis (citation below), Section 7.3 for an elementary derivation.\nBayes\' theorem for probability densities is formally similar to the theorem for probabilities:\n\n: f(x|y) = \\frac{f(y|x)\\,f(x)}{f(y)} \n\nand there is an analogous statement of the law of total probability:\n\n: f(x|y) = \\frac{f(y|x)\\,f(x)}{\\int_{-\\infty}^{\\infty} f(y|x)\\,f(x)\\,dx}\n \n\nAs in the discrete case,\nthe terms have standard names. \n\'\'f\'\'(\'\'x\'\', \'\'y\'\') is the joint distribution of \'\'X\'\' and \'\'Y\'\',\n\'\'f\'\'(\'\'x\'\'|\'\'y\'\') is the posterior distribution of \'\'X\'\' given \'\'Y\'\'=\'\'y\'\',\n\'\'f\'\'(\'\'y\'\'|\'\'x\'\') = \'\'L\'\'(\'\'x\'\'|\'\'y\'\') is (as a function of \'\'x\'\') the likelihood function of \'\'X\'\' given \'\'Y\'\'=\'\'y\'\',\nand \'\'f\'\'(\'\'x\'\') and \'\'f\'\'(\'\'y\'\') are the marginal distributions of \'\'X\'\' and \'\'Y\'\' respectively, with \'\'f\'\'(\'\'x\'\') being the prior distribution of \'\'X\'\'.\n\nHere we have indulged in a conventional abuse of notation,\nusing \'\'f\'\' for each one of these terms, \nalthough each one is really a different function;\nthe functions are distinguished by the names of their arguments.\n\n=== Extensions of Bayes\' theorem ===\n\nTheorems analogous to Bayes\' theorem hold in problems with more than two variables.\nThese theorems are not given distinct names,\nas they may be [[mass production|mass-produced]] by applying the laws of probability.\nThe general strategy is to work with a decomposition of the joint probability, and to marginalize (integrate) over the variables that are not of interest.\nDepending on the form of the decomposition,\nit may be possible to prove that some integrals must be 1,\nand thus they fall out of the decomposition;\nexploiting this property can reduce the computations very substantially.\nA [[Bayesian network]] is essentially a mechanism for automatically generating the extensions of Bayes\' theorem that are appropriate for a given decomposition of the joint probability.\n\n==Examples==\n\nTypical examples that use Bayes\' theorem assume the philosphy underlying [[Bayesian probability]] that uncertainty and degrees of belief can be measured as probabilities. For worked out examples, please see the article on the examples of [[Bayesian inference#Simple examples of Bayesian inference|Bayesian inference]].\n\n== References ==\n\n=== Versions of the essay ===\n\n* Thomas Bayes (1763), \"An Essay towards solving a Problem in the Doctrine of Chances\", \'\'Philosophical Transactions of the Royal Society of London\'\', 53.\n\n* Thomas Bayes (1763/1958) \"Studies in the History of Probability and Statistics: IX. Thomas Bayes\'s Essay Towards Solving a Problem in the Doctrine of Chances\", \'\'Biometrika\'\' 45:296-315 \'\'(Bayes\'s essay in modernized notation)\'\'\n\n* Thomas Bayes [http://www.stat.ucla.edu/history/essay.pdf \"An essay towards solving a Problem in the Doctrine of Chances\"] \'\'(Bayes\'s essay in the original notation)\'\'\n\n=== Commentaries ===\n\n* G.A. Barnard. (1958) \"Studies in the History of Probability and Statistics: IX. Thomas Bayes\'s Essay Towards Solving a Problem in the Doctrine of Chances\", \'\'Biometrika\'\' 45:293-295 \'\'(biographical remarks)\'\'\n\n* Daniel Covarrubias [http://www.stat.rice.edu/~blairc/seminar/Files/danTalk.pdf \"An Essay Towards Solving a Problem in the Doctrine of Chances\"] \'\'(an outline and exposition of Bayes\'s essay)\'\'\n\n* Stephen M. Stigler (1982) \"Thomas Bayes\' Bayesian Inference,\" \'\'Journal of the Royal Statistical Society\'\', Series A, 145:250-258 \'\'(Stigler argues for a revised interpretation of the essay -- recommended)\'\'\n\n* [[Isaac Todhunter]] (1865) \'\'A History of the Mathematical Theory of Probability from the time of Pascal to that of Laplace\'\', Macmillan. Reprinted 1949, 1956 by Chelsea and 2001 by Thoemmes.\n\n=== Additional material ===\n\n* Pierre-Simon Laplace (1774), \"Mémoire sur la Probabilité des Causes par les Événements,\" \'\'Savants Étranges\'\' 6:621-656, also \'\'Oeuvres\'\' 8:27-65.\n\n* Pierre-Simon Laplace (1774/1986), \"Memoir on the Probability of the Causes of Events\", \'\'Statistical Science\'\', 1(3):364--378.\n\n* Stephen M. Stigler (1986), \"Laplace\'s 1774 memoir on inverse probability,\" \'\'Statistical Science\'\', 1(3):359--378.\n\n* Stephen M. Stigler (1983), \"Who Discovered Bayes\'s Theorem?\" The American Statistician, 37(4):290-296.\n\n* Jeff Miller. [http://members.aol.com/jeff570/b.html Earliest Known Uses of Some of the Words of Mathematics (B)] (\'\'very informative -- recommended\'\')\n\n* [[Athanasios Papoulis]] (1984), \'\'Probability, Random Variables, and Stochastic Processes\'\', second edition. New York: McGraw-Hill.\n\n== Tempo oge ==\n\n* [[Raven paradox]]\n* [[Prosecutor\'s fallacy]]\n* [[Revising opinions in statistics]]\n* [[Occam\'s razor]]\n* [[Bayesian inference]]\n\n\n\n\n\n\n\n[[Category:Probability theory]]\n[[Category:Theorems]]\n\n[[de:Bayes-Theorem]]\n[[fr:Théorème de Bayes]]\n[[it:Teorema di Bayes]]\n[[nl:Theorema van Bayes]]\n[[pl:Twierdzenie Bayesa]]','',13,'Budhi','20041224215052','',0,0,1,0,0.65640093603,'20041231123527','79958775784947'); INSERT INTO cur VALUES (896,0,'Probability_distribution','[[de:Wahrscheinlichkeitsverteilung]] \n[[en:Probability distribution]]\n[[es:distribución de probabilidad]]\n[[ja:確率分布]] \n[[nl:kansverdeling]]\n[[sv:sannolikhetsfördelning]] \n[[pl:Rozkład zmiennej losowej]]\n\nDina [[matematik]], \'\'\'probabiliti sebaran\'\'\' nangtukeun unggal [[interval (mathematics)|interval]] tina [[real number]] [[kamungkinan]], mangka kitu [[probability axioms]] \'\'terpenuhi\'\'. Dina watesan teknik, probabiliti sebaran nyaeta [[probability measure|probabiliti ukuran]] numana domain mangrupa [[Borel algebra]] dina kaayaan riil.\n\nProbabiliti sebaran dina kasus husus ngarupakeun notasi nu leuwih tina [[probability measure|probabiliti ukuran]], which is a function that assigns probabilities satisfying the [[Kolmogorov axioms]] to the measurable sets of a [[measurable space]].\n\nEvery [[random variable]] gives rise to a probability distribution, and this distribution contains most of the important information about the variable. If \'\'X\'\' is a random variable, the corresponding probability distribution assigns to the interval [\'\'a\'\', \'\'b\'\'] the probability Pr[\'\'a\'\' ≤ \'\'X\'\' ≤ \'\'b\'\'], i.e. the probability that the variable \'\'X\'\' will take a value in the interval [\'\'a\'\', \'\'b\'\'].\n\nThe probability distribution of the variable \'\'X\'\' can be uniquely described by its [[cumulative distribution function]] \'\'F\'\'(\'\'x\'\'), which is defined by\n:\nF(x) = {\\rm Pr} \\left[ X \\le x \\right]\n\n\nfor any \'\'x\'\' in \'\'\'R\'\'\'. \n\nA distribution is called \'\'discrete\'\' if its cumulative distribution function consists of a sequence of finite jumps, which means that it belongs to a [[discrete random variable]] \'\'X\'\': a variable which can only attain values from a certain finite or [[countable]] set. \nA distribution is called \'\'continuous\'\' if its cumulative distribution function is [[continuous]], which means that it belongs to a random variable \'\'X\'\' for which Pr[ \'\'X\'\' = \'\'x\'\' ] = 0 for all \'\'x\'\' in \'\'\'R\'\'\'.\n\nThe so-called \'\'absolutely continuous distributions\'\' can be expressed by a [[probability density function]]: a non-negative [[Lebesgue integration|Lebesgue integrable]] function \'\'f\'\' defined on the reals such that\n\n:\n{\\rm Pr} \\left[ a \\le X \\le b \\right] = \\int_a^b f(x)\\,dx\n\n\nfor all \'\'a\'\' and \'\'b\'\'. That discrete distributions do not admit such a density is unsurprising, but there are continuous distributions like the [[devil\'s staircase]] that also do not admit a density.\n\nThe \'\'support\'\' of a distribution is the smallest closed set whose complement has probability zero.\n\n== Jejer penting dina sebaran probabiliti ==\n\nSababaraha sebaran probabiliti kacida pentingna dina teori atawa pamakean dibere ngaran nu husus:\n* Sebaran diskrit\n** Dina kaayaan terhingga\n*** [[degenerate distribution|Sebaran \'\'degenerate\'\']] dina \'\'x\'\'0, numana \'\'X\'\' ngarupakeun nilai penting dicokot jadi nilai \'\'x0\'\'. This does not look random, but it satisfies the definition of [[random variable]]. This is useful because it puts deterministic variables and random variables in the same formalism.\n*** The discrete [[sebaran seragam|uniform distribution]], where all elements of a finite [[set theory|set]] are equally likely. This is supposed to be the distribution of a balanced coin, an unbiased die, a casino roulette or a well-shuffled deck. Also, one can use measurements of quantum states to generate uniform random variables. All these are \"physical\" or \"mechanical\" devices, subject to design flaws or perturbations, so the uniform distribution is only an approximation of their behaviour. In digital computers, [[Pseudorandom number sequence|pseudo-random number generators]] are used to produced a [[randomness|statistically random]] discrete uniform distribution.\n*** The [[Bernoulli distribution]], which takes value 1 with probability \'\'p\'\' and value 0 with probability \'\'q\'\'=1-\'\'p\'\'.\n*** [[Sebaran binomial]], nu ngajelaskeun jumlah kasuksesan dina deret tina percobaan bebas Enya/Henteu.\n*** The [[hypergeometric distribution]], which describes the number of successes in the first \'\'m\'\' of a series of \'\'n\'\' independent Yes/No experiments, if the total number of successes is known.\n** With infinite support\n*** The [[geometric distribution]], a discrete distribution which describes the number of attempts needed to get the first success in a series of independent Yes/No experiments.\n*** The [[negative binomial distribution]], a generalization of the geometric distribution to the \'\'n\'\'th success.\n*** The [[Poisson distribution]], which describes the number of rare events that happen in a certain time interval.\n*** The [[Boltzmann distribution]], a discrete distribution important in [[statistical physics]] which describes the probabilities of the various discrete energy levels of a system in [[thermal equilibrium]]. It has a contiuous analogue. Special cases include\n**** The [[Gibbs distribution]]\n**** The [[Maxwell-Boltzmann distribution]]\n**** The [[Bose-Einstein distribution]]\n**** The [[Fermi-Dirac distribution]]\n*** The [[zeta distribution]] has uses in applied statistics and statistical mechanics, and perhaps may be of interest to number theorists.\n* Continuous distributions\n** Supported on a finite interval\n*** [[sebaran seragam]] dina [\'\'a\'\',\'\'b\'\'], numana sakabeh titik dina interval nu kawengku mibanda ajen nu ampir sarua.\n*** [[Sebaran beta]] dina [0,1], ngarupakeun sebaran seragam dina kasus husus, nu dipake dina estimasi probabiliti sukses.\n*** The [[Triangular distribution]] on [a, b]\n** Supported on semi-infinite intervals, usually [0,∞)\n*** [[Sebaran eksponensial]], which describes the time between consecutive rare random events in a process with no memory.\n*** [[Sebaran gamma]], nu ngajelaskeun waktu salila \'\'n\'\' consecutive rare random events occur in a process with no memory.\n*** The [[Erlang distribution]], which is a special case of the gamma distribution with integral shape parameter, developed to predict waiting times in [[queuing systems]].\n*** The [[Log-normal distribution]], describing variables which can be modelled as the product of many small independent positive variables.\n*** The [[Weibull distribution]], of which the exponential distribution is a special case, is used to model the lifetime of technical devices.\n*** [[Sebaran chi-kuadrat]], nu ngarupakeun jumlah kuadrat \'\'n\'\' variabel random Gauss bebas. Ieu ngarupakeun kasus husus dina sebaran Gamma, sarta dipake dina tes goodness-of-fit dina [[statistik]].\n*** [[Sebaran-F]], numana sebaran rasio dua sebaran variabel normal, dipake dina [[analisa varian]].\n** Supported on the whole real line\n*** [[Sebaran normal]], disebut oge Gaussian atawa kurva bel. It is ubiquitous in nature and statistics due to the [[central limit theorem]]: every variable that can be modelled as a sum of many small independent variables is approximately normal.\n*** [[Sebaran-t student]], dipake keur nga-\'\'estimasi\'\' mean nu teu dipikanyaho dina populasi \'\'Gaussian\'\'.\n*** [[Sebaran Cauchy]], conto sebaran nu teu ngabogaan [[nilai ekspektasi]] atawa [[varian]]. Dina fisika biasana disebut Lorentzian, sarta ieu sebaran tina tetapan energi teu stabil dina mekanika kuantum. Dina fisika partikel, the extremely short-lived particles associated to such unstable states are called [[resonance]]s.\n* Joint distributions\n** Two or more random variables on the same sample space\n*** [[Bivariate distribution]]\n*** [[Conditional distribution]]\n*** [[Multivariate distribution]]\n*** [[Multinomial distribution]], a generalization of the [[sebaran binomial]].\n*Sebaran nilai-matrix\n**[[sebaran Wishart]]\n**[[Matrix normal distribution]]\n**[[Matrix T distribution]]\n**[[Normal-inverse Wishart distribution]]\n\n== Tempo oge ==\n[[daptar jejer statistis]] -- [[random variable]] -- [[cumulative distribution function]] -- [[probability density function]] -- [[likelihood]]','add english xlink',0,'128.2.156.14','20050209020426','',0,0,0,0,0.517549230958,'20050209020426','79949790979573'); INSERT INTO cur VALUES (897,0,'Daptar_jejer_statistis','Mangga tambahkeun artikel Wikipedia ngeunaan [[statistik]] anu teu aya dina jejer di handap ieu.\n\nParobahan anu aya hubunganna jeung kaca di handap ieu bakal ditujukeun kana kaca panganyarna tina eta jejer. Keur nempo parobahan anyar dina \"kaca\" ieu, tempo oge kaca sajarah.\n\nTempo oge [[list of probability topics]], jeung [[daptar statistikawan]].\n\n__NOTOC__\n{{compactTOC}}\n\n==A==\n*[[Accuracy and precision]]\n*[[Algoritma keur ngitung varian]]\n*[[Alignments of random points]]\n*[[Analisa conjoint]]\n*[[Analisa varian]]\n*[[Ancillary statistic]]\n*[[Anomali deret waktu]]\n*[[Arithmetic mean]]\n*[[Autoregressive conditional heteroskedasticity]]\n\n==B==\n*[[Baseball statistics]]\n*[[Bayesian inference]]\n*[[Bayesian model comparison]]\n*[[Bias (statistics)]]\n*[[Chebyshev\'s inequality|Bienaymé-Chebyshev inequality]]\n*[[Binary classification]]\n*[[Box plot]]\n*[[Ladislaus Bortkiewicz]]\n\n==C==\n*[[Calibration (probability)]] - subjective probability\n*[[Canonical correlation]]\n*[[Central limit theorem]]\n*[[Characteristic function]]\n*[[Chebyshev\'s inequality]]\n*[[Common- and special-causes]]\n*[[Completeness (statistics)]]\n*[[Concrete illustration of the central limit theorem]]\n*[[Conditional distribution]]\n*[[Confidence band]]\n*[[Consistency (statistics)]]\n*[[Control chart]]\n*[[Correlation]]\n*[[Correlation implies causation (logical fallacy)]]\n*[[Covariance matrix]]\n*[[Cricket statistics]]\n*[[Cronbach\'s alpha]]\n*[[Cross tab]]\n*[[Cross-validation]]\n*[[Cumulant]]\n*[[Curve fitting]]\n*[[Harald Cramér]]\n*[[Cramér-Rao inequality]]\n\n==D==\n*[[Daptar asosiasi statistis akademik]]\n*[[Daptar Statistikawan]]\n*[[Data clustering]]\n*[[Data point]]\n*[[Data random]]\n*[[De Finetti\'s theorem]]\n*[[Decision theory]]\n*[[Demographics]]\n*[[Demography]]\n**[[Demographic statistics]]\n**[[Illustration of density estimation]]\n*[[Deret waktu]]\n*[[Desain percobaan]]\n*[[Dinamika populasi]]\n*[[Dinamika sistim]]\n*[[Dispersi statistik]]\n*[[Dutch book]]\n\n==E==\n*[[Ekologi kaliru]]\n*[[Economic statistics]]\n*[[Edgeworth series]]\n*[[Efek ukuran]]\n*[[Efficiency (statistics)]]\n*[[Empirical Bayes method]]\n*[[A. K. Erlang]]\n*[[Errors and residuals in statistics]]\n*[[Estimator]]\n*[[Estimasi densiti]]\n*[[Estimasi statistik]]\n*[[Expectation-maximization algorithm]]\n*[[Exploratory data analysis]]\n*[[Exponential family]]\n*[[Extreme value theory]]\n\n==F==\n*[[F-test]]\n*[[Factor analysis]]\n*[[False positive]]\n*Daftar jejer [[Fenomena statistik]]\n*[[Ronald Fisher]]\n*[[Fisher\'s exact test]]\n*[[Fisher\'s linear discriminator]]\n\n==G==\n*[[G-test]]\n*[[Galton-Watson process]]\n*[[Gauss-Markov theorem]]\n*[[Géostatistik]]\n*[[William Sealey Gosset]]\n*[[Graeco-Latin square]]\n\n==H==\n\n*[[Heteroscedasticity]]\n*[[Histogram]]\n*[[Homoscedasticity]]\n\n==I==\n*[[Illustration of the central limit theorem]]\n*[[Independent components analysis]]\n*[[Independent identically-distributed random variables]]\n*[[Informasi Fisher]]\n*[[Information geometry]]\n*[[Interaction (statistics)]]\n*[[Interpolasi Pareto]]\n*[[Interquartile range]]\n*[[Interval estimasi]]\n*[[Interval kapercayaan]]\n\n==J==\n*[[Jajal pamanggih]]\n\n==K==\n*[[Kalibrasi (statistik)]] - \'\'masalah kalibrasi dina statistik\'\'\n*[[Kaputusan statistik]]\n*[[Kasimpulan statistik]]\n*[[Koefisien Gini]]\n*[[Kolmogorov-Smirnov tes]]\n*[[Komposisi data]]\n*[[Kovarian]]\n*[[Kriging]]\n*[[Kuadrat leutik]]\n*[[Kuiper\'s test]]\n*[[Kurtosis]]\n*[[Kurva Hubbert]]\n*[[Kurva Lorenz]]\n\n==L==\n*[[Latin square]]\n*[[Latin hypercube sampling]]\n*[[Law of large numbers]]\n*[[Learning theory (statistics)]]\n*[[Level of measurement]]\n*[[Lies, damned lies, and statistics]]\n*[[Life expectancy]]\n*[[Likelihood principle]]\n*[[Likelihood-ratio test]]\n*[[Linear regression]]\n*[[List of probability topics]]\n*[[Logit]]\n*[[Loss function]]\n\n==M==\n*[[Machine learning]]\n*[[Mann-Whitney U]]\n*[[Margin kasalahan]]\n*[[Marginal distribution]]\n*[[Maximum likelihood]]\n*[[Mean kuadrat kasalahan]]\n*[[Level of measurement|Measurement, level of]]\n*[[Memorylessness]]\n*[[Meta-analysis]]\n*[[Metoda inpormasi leherbotol]]\n*[[Model grapik]]\n*[[Model linier]]\n*[[Model statistik]]\n*[[Moment (mathematics)]]\n*[[Moment-generating function]]\n*[[Multidimensional scaling]]\n*[[Multiple comparisons]]\n*[[Multivariate statistics]]\n\n==N==\n*[[List of national and international statistical services|National and international statistical services]]\n*[[Negative binomial distribution]]\n*[[Neyman-Pearson lemma]]\n*[[Nonprobability sampling]]\n*Normal probability plot -- see [[rankit]]\n*[[Null hypothesis]]\n\n==O==\n*[[Odds]]\n*[[Odds-ratio]]\n*[[Order statistik]]\n*[[Outlier]]\n*[[Overfitting]]\n\n==P==\n*[[Page\'s trend test]]\n*[[Paket statistik]]\n*[[Parameter lokasi]]\n*[[Parameter statistik]]\n*[[Percentile rank]]\n*[[Paleostatistics]]\n*[[Pilihan probabiliti]]\n*[[Karl Pearson]]\n*[[Pearson product-moment correlation coefficient]]\n*[[Pitman-Koopman-Darmois theorem]]\n*[[Planning statistical research]]\n*[[Poisson distribution]]\n*[[Poisson process]]\n*[[Populasi statistik]]\n*[[Prediction interval]]\n*[[Prediksi linier]]\n*[[Principal components analysis]]\n*[[Prior probability distribution]]\n*[[Kamungkinan|Probability]]\n*[[Probability of error]]\n*[[Probability theory]]\n*[[Prosecutor\'s fallacy]]\n*[[P-value]]\n*[[Pythagorean expectation]]\n\n==Q==\n*[[Q test]]\n*[[Quantile]]\n*[[Quantitative psychological research]]\n*[[Quantitative research]]\n*[[Quartile]]\n*[[Adolphe Quetelet]]\n\n==R==\n*[[Random sampling]]\n*[[Randomized controlled trial]]\n*[[Range (statistics)]]\n*[[Rankit]]\n*[[Rao-Blackwell theorem]]\n*[[Rasio bencana]]\n*[[Rasio korelasi]]\n*[[Raw score]]\n*[[Receiver operating characteristic]]\n*[[Régrési Deming]]\n*[[Regression toward the mean]]\n*[[Rejection sampling]]\n*[[Reliability (psychometric)]]\n*Residual. See [[errors and residuals in statistics]].\n*[[Autoregressive conditional heteroskedasticity]]\n*[[Rothamsted Experimental Station]]\n*[[Rule of succession]]\n*[[Rumus prediksi Spearman-Brown]]\n\n==S==\n*[[Sampling (statistics)]]\n**[[simple random sampling]]\n**[[systematic sampling]]\n**[[stratified sampling]]\n**[[cluster sampling]]\n**[[multistage sampling]]\n*[[Scatterplot]]\n*[[Sebaran beta]]\n*[[Sebaran binomial]]\n*[[Sebaran chi-kuadrat]]\n*[[Sebaran eksponensial]]\n*[[Sebaran-F]]\n*[[Sebaran frekuensi]]\n*[[Sebaran gamma]]\n*[[Sebaran Log-normal]]\n*[[Sebaran normal]]\n*[[Sebaran sampling]]\n*sebaran-t; tempo [[Sebaran-t student]]\n*[[Sebaran-t student]]\n*[[Sebaran Weibull]]\n*[[Sebaran Wishart]]\n*[[Sekuen random]]\n*[[Sekuen Halton]]\n*[[Selection bias]]\n*[[Semivarian]]\n*[[Sensitivity (tests)]]\n*[[Simpangan baku]]\n*[[Simpangan mean]]\n*[[Simpangan mutlak]]\n*[[Simpson\'s paradox]]\n*[[Skewness]]\n*[[Skor standar]]\n*[[Spearman\'s rank correlation coefficient]]\n*[[Specificity]]\n*[[SPSS]]\n*[[Spurious relationship]]\n*[[St. Petersburg paradox]]\n*[[Standar kasalahan (statistis)|Standar kasalahan]]\n*[[Standardized (statistics)]]\n*[[Statistik]]\n*[[Statistik bisnis]]\n*[[Statistik deskriptif]]\n*[[Statistik matematis]]\n*[[Statistik non-parametrik]]\n*[[Statistik parametrik]]\n*[[Statistik sosial]]\n*[[Statistik terapan]]\n*[[Statistical arbitrage]]\n*[[Statistical assembly]]\n*[[Statistical efficiency]]\n*[[Statistical independence]]\n*[[Statistical inference]]\n*[[Statistical noise]]\n*[[Statistical power]]\n*[[Statistical process control]]\n*Statistical range -- see [[range (statistics)]]\n*[[Statistical regularity]]\n*[[Statistical sample]]\n*[[Statistical significance]]\n*[[Statistical unit]]\n*[[Statistical variability]]\n*[[Statistics Belgium]]\n*[[Statistics New Zealand]]\n*[[Stein\'s lemma]]\n*[[Studentized residual]]\n*[[Student\'s t-test]]\n*[[Sufficiency (statistics)]]\n*[[Survey sampling]]\n*[[Survival analysis]]\n*[[Survivor function]]\n\n==T==\n*[[Taguchi methods]]\n*[[Titik estimasi]]\n*[[Teorema Cochran]]\n*[[Téoréma Lehmann-Scheffé]]\n*[[Tes nilai tengah]]\n*[[Tes chi-kuadrat]]\n*[[Tes hipotesa statistik]]\n*[[Testing hypotheses suggested by the data]]\n*[[Tiori statistik]]\n*[[Tolerance interval]]\n*[[Trend estimation]]\n*[[Truncated mean]]\n*[[Type I error]]\n*[[Type II error]]\n\n==U==\n*[[U test]]\n*[[Uji kuadrat-chi Pearson]] (salah sahiji sempalan tes kuadrat-chi, topik anu ilaharna aya dina [[chi-square test]])\n*[[Uncomfortable science]]\n*[[Urn problem]]s\n\n==V==\n*[[Varian]]\n*[[VC dimension]]\n*[[Vysochanskiï-Petunin inequality]]\n\n==W==\n\n==X==\n\n==Y==\n*[[Yates\' correction for continuity]]\n\n==Z==\n*[[Zipf-Mandelbrot law]]\n\n[[Category:Daptar jejer]]\n\n[[en:List of statistical topics]] [[sv:Lista över statistikartiklar]]\n[[zh-cn:统计学主题列表]]','/* T */',3,'Kandar','20050208063055','',0,0,0,0,0.22301872411,'20050208063055','79949791936944'); INSERT INTO cur VALUES (898,0,'Kriging','\'\'\'Kriging\'\'\' nyaeta teknik [[regression]] anu digunakeun dina [[géostatistik]]. Ngaran ieu digunakeun sasuai jeung nu manggihkeunna nyaeta, [[Danie G. Krige]]. Dina komunitas [[statistik]], leuwih umum disebut \'\'\'[[Gaussian process]] regression\'\'\'.\n\nKriging bisa dipikaharti leuwih jentre dina bentuk [[Bayesian inference]]. Kriging dimimitian ku [[prior probability distribution|prior]] [[probability distribution|distribution]] dina [[Fungsi (matematik)|fungsi]]. Mimiti ieu meunang ngitung dina Gaussian process: N sampel ti hiji fungsi bakal [[sebaran normal|kasebar sacara normal]], dimana [[kovarian]] antara dua sampel teh ngarupakeun fungsi covariance (atawa [[kernel (mathematics)|kernel]]) ti proses Gauss dina dua titik lokasi spasial.\n\nSaterusna susunan data ditalungtik, unggal nilai digabungkeun ku lokasi spasial. Ayeuna, nilai anyar bisa \'\'diprediksi\'\' di unggal lokasi spasial anyar, ku kombinasi Gauss awal jeung Gaussian [[likelihood]] unggal nilai observasi. Hasilna [[posterior]] distribusi oge Gaussian, numana mean jeung covariance leuwih sederhana diitung tina nilai observasi, variance-na, jeung matrix kernel asalna teh ti awal (prior).\n\nDumasar kana \"sudut pandang\" [[géologi]], Kriging ngagunakeun pangaweruh awal ngeunaan sebaran spasial mineral: pangaweruh awal ieu teh nyaeta kumaha dongengna mineral bisa mangrupakeun fungsi ruang. Saterusna, ditambahkeun angka-angka konsentrasi mineral, Kriging bisa \"memprediksi\" konsentrasi mineral dina titik anu teu katalungtik. \n\n== External link ==\n* [http://www.ai-geostats.org/ AI-GEOSTATS is the main information server about geostatistics and spatial statistics]\n* [http://www.cs.toronto.edu/~carl/gp.html The Gaussian processes web site]\n\n[[Category:Statistik]][[Category:Géologi]]','',13,'Budhi','20041224212039','',0,0,1,0,0.784151885092,'20041224212039','79958775787960'); INSERT INTO cur VALUES (899,0,'Géostatistik','[[it:Geostatistica]]\n\n\'\'\'Géostatistik\'\'\' make teori [[stochastic process|proses stokastik]] jeung [[statistical inference|kasimpulan statistik]] keur nalungtik fenomena geografi. Géostatistik geus ilahar digunakeun dina widang geo-sciences. Metoda Géostatistik oge dipake di [[petroleum geology|geologi minyak]], [[hydrogeology|hidrogeologi]], [[meteorology|meteorologi]], [[oceanography|oseanografi]], [[geochemistry|geokimia]], [[forestry|kahutanan]], [[environmental control|kontrol lingkungan]], [[landscape ecology|ekologi lanskap]], [[agriculture|pertanian]] (hususna keur [[precision farming|kacocogan tatanen]]) jeung sajabana.\n\nKonsep dasar géostatistik nyaeta yen skala mangrupakeun \'\'variasi spasial\'\'. Data spasial \"terikat\" nunjukeun yen [[variability|variabiliti]] hampir sarua \"tanpa\" ningali lokasi titik data. Sanajan kitu, data spatial dina sababaraha kasus lain ngarupakeun data \"terikat\". Nilai data nu mana raket sacara spatial ngabogaan \"variabiliti\" anu saeutik dibandingkeun jeung nilai numana leuwih jauh antara hiji kanu sejenna. Sifat pola ieu beda-beda tina hiji susunan data ka susunan data nu sejenna; unggal susunan data mibanda fungsi nu \"unik\" sarta jarak antara dua titik data. Variabilitas ieu ilaharna diitung salaku fungsi nu disebut [[semivarian]].\n\nSpatial [[autocorrelation]] bisa diitung ngagunakeun [[correlogram]]s, [[covariance function]]s jeung [[variogram]]s (=[[semivariogram]]s).\n\nTopik anu aya hubunganna: [[statistik]], [[géologi]], [[GIS]], [[remote sensing]], [[kriging]]\n\nRujukan:\n# Galli, A., Wackernagel, H.: Multivariate geostatistical methods for spatial data analysis. 1987\n# Sharov, A: Quantitative Population Ecology, 1996, http://www.ento.vt.edu/~sharov/PopEcol/popecol.html\n# Shine, J.A., Wakefield, G.I.: A comparison of supervised imagery classification using analyst-chosen and geostatistically-chosen training sets, 1999, http://www.geovista.psu.edu/sites/geocomp99/Gc99/044/gc_044.htm\n\n\n\n== Tumbu kaluar ==\n\n[http://www.ai-geostats.org AI-GEOSTATS is the main resource on the internet about geostatistics and spatial statistics]','',0,'133.66.133.191','20050218050419','',0,0,0,0,0.863130778476,'20050218050419','79949781949580'); INSERT INTO cur VALUES (900,0,'Géologi','\'\'\'Géologi\'\'\' (tina basa [[Greek language|Greek]] γη- (\'\'ge-\'\', \"bumi\") and λογος (\'\'logos\'\', \"kecap\", \"alesan\")) nyaeta [[élmu]] jeung pangajaran ngeunaan [[bumi]], kaasup kajadiannana, strukturna, sifat fisikna, sajarah, jeung proses \'\'pembentukannana\'\'. Kecap mimitina digunakeun dina perasaan ku [[Jean-André de Luc]] (1727 - 1817) dina [[1778]] jeung dikenalkeun ku [[Horace-Bénédict de Saussure]] (1740 - 1799) dina taun [[1779]] salaku watesan nu tetep. [Watesan nu leuwih kolot mimiti digunakeun ku [[Richard de Bury]] (1286 - 1345). Anjeunna ngagunakeun geologi keur ngabedakeun antara ka-bumian jeung theological jurisprudence.]\n\n\'\'Géologi\'\' kadang kala digunakeun ampir sarua jeung elmu ngeunaan sistem panonpoe (solar system). Sanajan kitu, watesan anu husus nyaeta \'\'selenology\'\' (elmu ngeunaan bulan), \'\'areology\'\' (Mars), jst., oge digunakeun.\n\n== Sajarah ==\n\n[[Georg Agricola]] (1494-1555) nulis buku mimiti sacara sistimatis ngeunaan [[mining]] jeung proses [[smelting]], \'\'De re metallica libri XII\'\', sarta apendiks \'\'Buch von den Lebewesen unter Tage\'\' (buku ngeunaan \"pembentukan\" bumi). Subjek tulisanna saperti [[wind energy]], [[water power|hydrodynamic power]], melting cookers, transport of [[ore]]s, extraction of [[soda]], [[sulfur]] and [[alum]], jeung isu administrasi. Buku ieu diterbitkeun dina taun[[1556]].\n\n[[James Hutton]] nu ngamimitian ngeunaan geologi modern. Dina taun [[1785]] manehna presentasi paper nu judulna \'\'Theory of the Earth\'\' di [[Royal Society of Edinburgh]]. Dina paper-na, anjeunna nerangkeun yen Bumi kudu leuwih kolot tinimbang perkiraan samemehna, hal ieu keur ngajelaskeun perlu waktu nu lila sangkan gunung ngalaman [[erosion|eroded]], sarta keur [[sediment]] ngabentuk batuan anyar di dasar laut, nu ngandelan di wewengkon kering.\n\nFollowers of Hutton were known as plutonists because they believed that some rocks were formed by [[vulcanism]] which is the deposition of lava from volcanoes, as opposed to the neptunists, who believed that all rocks had settled out of a large ocean whose level gradually dropped over time.\n\n[[William Smith (geologist)|William Smith]] (1769-1839) drew some of the first geological maps and began the process of ordering [[Rock strata|rock strata]] (layers) by examining the fossils contained in them.\n\n[[Sir Charles Lyell]] first published his famous book, Principles of Geology, in [[1830]] and continued to publish new revisions until he died in [[1875]]. He successfully promoted the doctrine of [[Uniformitarianism|uniformitarianism]]. This theory states that slow geological processes occurred throughout the earth\'s history, and are still occurring today. In contrast, [[Catastrophism|catastrophism]] is the theory that Earth\'s features formed in single, catastrophic events and remained unchanged thereafter. (Hutton believed in uniformitarianism, but the idea was not widely accepted at the time.)\n\nThe theory of [[Continental drift|continental drift]] was proposed by [[Alfred Wegener]] in [[1912]] and by Arthur Holmes, but wasn\'t broadly accepted until the [[1960s]] when the theory of [[plate tectonics]] was developed.\n\nSee also: [[Timeline of geology]]\n\n== Fields ==\n\nThere are many different fields within the discipline of Geology, and it would be hard to list all of them. Some include, however: [[geochemistry]], [[hydrogeology]] (or [[geohydrology]]), [[petroleum geology]], [[economic geology]], [[soil science]], [[climatology]], [[biogeology]], [[geodetics]] and [[geophysics]].\n\nSubdisciplines within geology proper include [[structural geology]], [[sedimentology]] and [[stratigraphy]], [[mineralogy]] (study of minerals), [[petrology]] (study of rocks), [[geomorphology]] (study of landforms), [[seismology]] (also a field in [[geophysics]]) and [[volcanology]] (the study of volcanoes).\n\nThere is also [[engineering geology]], which supports [[Téhnik sipil|civil engineering]], especially [[geotechnical engineering]], and [[geological engineering]]. The difference between geological engineering and engineering geology is real: geological engineers are licensed as engineers, engineering geologists are licensed as geologists.\n\n==Regional Geology==\n*[[Geology of the Alps]]\n*[[Genesee River: Glacial Geology]] \'\'(New York, Pennsylvania)\'\'\n\n==National Geology==\n\n*[[Geology of Australia]]\n**[[Geology of Victoria]]\n\n*[[Geology of the United States of America]]\n**[[List_of_California-related_topics#Geology_of_California|Geology of California]]\n**[[Geology of the Grand Canyon area]]\n\n*[[Geology of the United Kingdom]]\n\n==See also==\n* [[List of geology topics]]\n* [[cycles]]\n* [[geologist]]\n* [[geologic timescale]]\n* [[mineral]]\n* [[Geological features of the Solar System]]\n* [[International Union of Geological Sciences]] (IUGS)\n* [[List of publications in geology|Important publications in geology]]\n\n==Tumbu kaluar==\n* James Hutton\'s [http://www.mala.bc.ca/~johnstoi/essays/Hutton.htm Theory of the Earth]\n\n[[ar:جيولوجيا]] [[bs:Geologija]] [[ca:Geologia]] [[cy:Daeareg]] [[da:Geologi]] [[de:Geologie]] [[en:Geology]] [[eo:Geologio]] [[es:Geología]][[et:Geoloogia]] [[fi:Geologia]] [[fr:Géologie]] [[gl:Xeoloxía]] [[hr:Geologija]] [[ia:Geologia]] [[it:Geologia]] [[ja:地質学]] [[la:Geologia]] [[hu:Geológia]] [[nl:Geologie]] [[no:Geologi]] [[pl:Geologia]] [[pt:Geologia]] [[sr:Геологија]] [[sv:Geologi]]\n[[vo:Talav]] [[zh-cn:地质学]]\n\n[[Category:Géologi]]','/* External link */',3,'Kandar','20040818053032','',0,0,0,0,0.960345907584,'20040930031619','79959181946967'); INSERT INTO cur VALUES (901,0,'Sebaran_normal','[[de:Normalverteilung]] [[it:variabile casuale normale]] [[ja:正規分布]] [[nl:normale verdeling]] [[sv:normalfördelning]][[pl:rozkład normalny]]\n\n[[Image:Gaussian-pdf.png|thumb|300px|[[Probability density function]] of Gaussian distribution (bell curve).]]\n\n\'\'\'Normal distribution\'\'\' (distribusi normal) mangrupakeun hal anu penting dina [[probability distribution]] di loba widang. \nBiasa oge disebut \'\'\'Gaussian distribution\'\'\', hususna dina widang [[fisika]] jeung [[rékayasa]]. \nDina kaayaan sabenerna kumpulan distribusi mibanda bentuk anu sarupa, bedana ngan dina parameter \'\'location\'\' jeung \'\'scale\'\': [[nilai ekspektasi|mean]] jeung [[simpangan baku]]. \'\'\'Standard normal distribution\'\'\' nyaeta distribusi normal anu mibanda nilai \'\'mean\'\' sarua jeung nol sarta nilai standar deviasi sarua jeung hiji. Sabab bentuk grafik [[probability density function|probability density]] mangrupa [[bell]], sering disebut \'\'\'bell curve\'\'\'.\n\n== Sajarah ==\n\nDistribusi normal mimiti dikenalkeun ku [[Abraham de Moivre|de Moivre]] dina artikel taun [[1733]] (dicitak ulang edisi kaduana dina \'\'[[The Doctrine of Chances]]\'\', [[1738]]) dina kontek \"pendekatan\" [[sebaran binomial]] keur \'\'n\'\' anu loba. Hasil de Moivre diteruskeun ku [[Pierre Simon de Laplace|Laplace]] dina bukuna \'\'[[Analytical Theory of Probabilities]]\'\' ([[1812]]), mangsa kiwari disebut [[Theorem of de Moivre-Laplace]]. \n\nLaplace ngagunakeun distribusi normal keur [[analysis of errors]] dina percobaanna. [[Method of least squares]] nu kacida pentingna dikenalkeun ku [[Adrien Marie Legendre|Legendre]] dina taun [[1805]]. [[Carl Friedrich Gauss|Gauss]], oge ngakukeun yen manehna geus make metoda anu sarua ti mimiti taun [[1794]], justified it rigorously in [[1809]] by assuming a normal distribution of the errors.\n\nIstilah \"bell curve\" ngacu ka [[Jouffret]] nu ngagunakeun watesan \"bell surface\" dina taun [[1872]] keur [[multivariate normal distribution|bivariate normal]] dina komponen bebas (independent). Istilah \"sebaran normal\" \"ditemukan\" sacara sewang-sewangan ku [[Charles S. Peirce]], [[Francis Galton]] jeung [[Wilhelm Lexis]] kira-kira taun [[1875]] [Stigler]. This terminology is unfortunate, since it reflects and encourages the fallacy that \"everything is Gaussian\". (See the discussion of \"occurrence\" below).\n\nYen sebaran disebut sebaran \'\'normal\'\' atawa \'\'Gaussian\'\', ngagantikeun sebaran \'\'de Moivrean\'\',\nis just an instance of [[Stigler\'s law of eponymy]]:\n\"No scientific discovery is named after its original discoverer\".\n\n== Spesifikasi sebaran normal ==\n\nAya sababaraha jalan keur nangtukeun random variable. Anu paling ngagambarkeun nyaeta probability density function (plot at the top), which represents how likely each value of the random variable is. The cumulative density function is a conceptually cleaner way to specify the same information, but to the untrained eye its plot is much less informative (see below). Equivalent ways to specify the normal distribution are: the moments, the [[cumulant]]s, the [[characteristic function]], the [[moment-generating function]], and the cumulant-[[generating function]]. Some of these are very useful for theoretical work, but not intuitive. See [[probability distribution]] for a discussion.\n\nAll of the [[cumulant]]s of the normal distribution are zero, except the first two.\n\n=== Fungsi probabiliti densiti ===\n\n[[Probability density function|Fungsi probabiliti densiti]] dina \'\'\'sebaran normal\'\'\' numana mean μ jeung simpangan baku σ (sarua jeung, [[varian]] σ2) mangrupakeun conto \'\'\'[[Gaussian function]]\'\'\',\n:f(x) = {1 \\over \\sigma\\sqrt{2\\pi} }\\,e^{-{(x-\\mu )^2 / 2\\sigma^2}}\n(Tempo oge [[exponential function]] jeung [[pi]].) Lamun [[random variable]] \'\'X\'\' ngabogaan distribusi ieu, bisa dituliskeun \'\'X\'\' ~ N(μ, σ2). Lamun μ = 0 jeung σ = 1, distribusi disebut \'\'standard normal distribution\'\', rumusna\n\n:f(x) = {1 \\over \\sqrt{2\\pi} }\\,e^{-{x^2 / 2}}\n\nGambar diluhur nunjukeun grafik probability density function tina sebaran normal numana μ = 0 jeung sababaraha nila σ.\n\nFor all normal distributions,\nthe density function is symmetric about its mean value. About 68% of the area under the curve is within one standard deviation of the mean, 95.5% within two standard deviations, and 99.7% within three standard deviations. The [[inflection point|inflection points]] of the curve occur at one standard deviation away from the mean.\n\n=== Fungsi Kumulatif Distribusi ===\n\n[[Cumulative distribution function]] (saterusna disebut \'\'cdf\'\') hartina probabilitas dimana nilai variabel \'\'X\'\' leuwih leutik tinimbang \'\'x\'\', jeung digambarkeun dina watesan fungsi densiti nyaeta \n\n:\\Pr(X \\le x) = \\int_{-\\infty}^x \\frac{1}{\\sigma\\sqrt{2\\pi}} e^{-(u-\\mu)^2/(2\\sigma^2)}\\,du\n\nStandar normal cdf, sacara konvensional dilambangkeun ku \\Phi, ngarupakeun nilai cdf umum di-evaluasi ku \\mu=0 jeung \\sigma=1,\n\n:\\Phi(z) = \\int_{-\\infty}^z {1 \\over \\sqrt{2\\pi} }\\,e^{-{x^2 / 2}}\\,dx\n\nThe standard normal cdf can be expressed in terms of a [[special function]] called the [[error function]], as\n\n:\\Phi(z) = \\frac{1}{2} (1+\\mbox{erf}\\,\\frac{z}{\\sqrt{2}})\n\nThe following graph shows the cumulative distribution function for values of \'\'z\'\' from -4 to +4: \n\n[[Image:Cumulative_normal_distribution.png]]\n\nOn this graph, we see the probability that a standard normal variable has a value less than 0.25 is approximately equal to 0.60.\n\n=== Generating functions ===\n\n==== Moment generating function ====\n\n==== Fungsi karakteristik ====\n\n[[characteristic function|Fungsi karakteristik]] dihartikeun salaku [[nilai ekspektasi]] \ne^{itX}.\nKeur sebaran normal, ieu bisa ditembongkeun dina fungsi karakteristik nyaeta \n\n:\\phi_X(t)=E\\left[e^{itX}\\right]=\\int_{-\\infty}^{\\infty} \\frac{1} {\\sigma\\sqrt{2\\pi}}\\,e^{-{(x-\\mu )^2 / 2\\sigma^2}}\\,e^{itx}\\,dx = e^{i\\mu t-\\sigma^2 t^2/2}\n\nsaperti nu katempo ku kuadrat eksponen nu lengkep.\n\n== Properties ==\n\n# If \'\'X\'\' ~ N(μ, σ2) and \'\'a\'\' and \'\'b\'\' are [[real number|real numbers]], then \'\'aX + b\'\' ~ N(\'\'a\'\'μ + b, (\'\'a\'\'σ)2).\n# If \'\'X\'\'1 ~ N(μ1, σ12) and \'\'X\'\'2 ~ N(μ2, σ22), and \'\'X\'\'1 and \'\'X\'\'2 are \'\'independent\'\', then \'\'X\'\'1 + \'\'X\'\'2 ~ N(μ1 + μ2, σ12 + σ22).\n# If \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' are [[Statistical independence|independent]] standard normal variables, then \'\'X\'\'12 + ... + \'\'X\'\'\'\'n\'\'2 has a [[sebaran chi-kuadrat]] with \'\'n\'\' degrees of freedom.\n\n=== Standardizing normal random variables ===\n\nAs a consequence of Property 1, it is possible to relate all normal random variables to the standard normal.\n\nIf \'\'X\'\' is a normal random variable with mean μ and variance σ2, then\n\n: Z = \\frac{X - \\mu}{\\sigma} \n\nis a standard normal random variable: \'\'Z\'\'~N(0,1). \nAn important consequence is that the cdf of a general normal distribution is therefore\n\n:\\Pr(X\n\nConversely, if \'\'Z\'\' is a standard normal random variable, then \n\n:X=\\sigma Z+\\mu \\,\n\nis a normal random variable with mean μ and variance σ2. \n\nThe standard normal distribution has been tabulated, and the other normal distributions are simple transformations of the standard one. \nTherefore, one can use tabulated values of the cdf of the standard normal distribution to find values of the cdf of a general normal distribution.\n\n=== Generating normal random variables ===\n\nFor computer simulations, it is often useful to generate values that have a normal distribution.\nThere are several methods; the most basic is to invert the standard normal cdf. More efficient methods are also known.\nOne such method is the [[Box-Muller transform]]. \nThe Box-Muller transform takes two [[sebaran seragam|uniformly distributed]] values as input and maps them to two normally distributed values.\nThis requires generating values from a uniform distribution, for which many methods are known. See also [[random number generator]]s.\n\nThe Box-Muller transform is a consequence of Property 3 and the fact that the chi-square distribution with two degrees of freedom is an exponential random variable (which is easy to generate).\n\n=== The central limit theorem ===\n\nThe normal distribution has the very important property that\nunder certain conditions, the distribution of a sum of a large number of [[statistical independence|independent variables]] is approximately normal.\nThis is the so-called [[central limit theorem]].\n\nThe practical importance of the central limit theorem is that the normal distribution can be used as an approximation to some other distributions.\n\n* [[Sebaran binomial]] mibanda parameter \'\'n\'\' sarta \'\'p\'\' ngadeukeutan kana normal keur \'\'n\'\' nu badag sarta \'\'p\'\' teu deukeut ka 1 atawa 0. \'\'Pendekatan\'\' sebaran normal mibanda mean μ = \'\'np\'\' sarta simpangan baku σ = (\'\'n p\'\' (1 - \'\'p\'\'))1/2.\n\n* A [[Poisson distribution]] with parameter λ is approximately normal for large λ. The approximating normal distribution has mean μ = λ and standard deviation σ = √λ.\n\nWhether these approximations are sufficiently accurate depends on the purpose for which they are needed, and the rate of convergence to the normal distribution.\nIt is typically the case that such approximations are less accurate in the tails of the distribution.\n\n\n== Occurrence ==\n\n\'\'Approximately\'\' normal distributions occur in many situations, as a result of the [[central limit theorem]].\nWhen there is reason to suspect the presence of a large number of small effects \'\'acting additively\'\', it is reasonable to assume that observations will be normal. \nThere are statistical methods to empirically test that assumption.\n\nEffects can also act as \'\'\'multiplicative\'\'\' (rather than additive) modifications. In that case, the assumption of normality is not justified, and it is the [[logarithm]] of the variable of interest that is normally distributed. The distribution of the directly observed variable is then called [[log-normal distribution|log-normal]]. \n\nFinally, if there is a single external influence which has a large effect on the variable under consideration, the assumption of normality is not justified either. This is true even if, when the external variable is held constant, the resulting distributions are indeed normal. The full distribution will be a superposition of normal variables, which is not in general normal. This is related to the theory of errors (see below).\n\nTo summarize, here\'s a list of situations where approximate normality \nis sometimes assumed. For a fuller discussion, see below.\n*In counting problems (so the central limit theorem includes a discrete-to-continuum approximation) where [[reproductive family|reproductive random variables]] are involved, such as\n**Binomial random variables, associated to yes/no questions;\n**Poisson random variables, associates to [[rare events]];\n*In physiological measurements of biological specimens:\n**The \'\'logarithm\'\' of measures of size of living tissue (length, height, skin area, weight);\n**The \'\'length\'\' of \'\'inert\'\' appendages (hair, claws, nails, teeth) of biological specimens, \'\'in the direction of growth\'\'; presumably the thickness of tree bark also falls under this category;\n**Other physiological measures may be normally distributed, but there is no reason to expect that \'\'a priori\'\';\n*Measurement errors are \'\'assumed\'\' to be normally distributed, and any deviation from normality must be explained;\n*Financial variables \n**The \'\'logarithm\'\' of interest rates, exchange rates, and inflation; these variables behave like compound interest, not like simple interest, and so are multiplicative;\n**Stock-market indices are supposed to be multiplicative too, but some researchers claim that they are [[log-Lévy]] variables instead of [[log-normal distribution|lognormal]];\n**Other financial variables may be normally distributed, but there is no reason to expect that \'\'a priori\'\';\n*Light intensity\n**The intensity of laser light is normally distributed;\n**Thermal light has a [[Bose-Einstein statistics|Bose-Einstein]] distribution on very short time scales, and a normal distribution on longer timescales due to the central limit theorem.\n\nOf relevance to biology and economics is the fact that complex systems tend to display [[power law]]s rather than normality.\n\n=== Photon counts ===\n\nLight intensity from a single source varies with time, and is usually assumed to be normally distributed. However, quantum mechanics interprets measurements of light intensity as [[photon]] counting. Ordinary light sources which produce light by thermal emission, should follow a [[Poisson distribution]] or [[Bose-Einstein distribution]] on very short time scales. On longer time scales (longer than the [[coherence time]]), the addition of independent variables yields an approximately normal distribution. The intensity of laser light, which is a quantum phenomenon, has an exactly normal distribution.\n\n=== Measurement errors ===\n\nRepeated measurements of the same quantity are expected to yield results which are clustered around a particular value. If all major sources of errors have been taken into account, it is \'\'assumed\'\' that the remaining error must be the result of a large number of very small \'\'additive\'\' effects, and hence normal. Deviations from normality are interpreted as indications of systematic errors which have not been taken into account. Note that this is the \'\'central \'\'\'assumption\'\'\'\'\' of the mathematical [[theory of errors]].\n\n=== Physical characteristics of biological specimens ===\n\nThe overwhelming biological evidence is that bulk growth processes of living tissue proceed by multiplicative, not additive, increments, and that therefore measures of body size should at most follow a lognormal rather than normal distribution. Despite common claims of normality, the sizes of plants and animals is approximately lognormal. The evidence and an explanation based on models of growth was first published in the classic book\n\n:Huxley, Julian: Problems of Relative Growth (1932)\n\nDifferences in size due to sexual dimorphism, or other polymorphisms like the worker/soldier/queen division in social insects, further make the joint distribution of sizes deviate from lognormality. \n\nThe assumption that linear size of biological specimens is normal leads to a non-normal distribution of weight (since weight/volume is roughly the 3rd power of length, and gaussian distributions are only preserved by linear transformations), and conversely assuming that weight is normal leads to non-normal lengths. This is a problem, because there is no \'\'a priori\'\' reason why one of length, or body mass, and not the other, should be normally distributed. Lognormal distributions, on the other hand, are preserved by powers so the \"problem\" goes away if lognormality is assumed. \n\n* blood pressure of adult humans is supposed to be normally distributed, but only after separating males and females into different populations (each of which is normally distributed) \n* The length of inert appendages such as hair, nails, teet, claws and shells is expected to be normally distributed if measured in the direction of growth. This is because the growth of inert appendages depends on the size of the root, and not on the length of the appendage, and so proceeds by \'\'additive\'\' increments. Hence, we have an example of a sum of very many small lognormal increments approaching a normal distribution. Another plausible example is the width of tree trunks, where a new thin ring if produced every year whose width is affected by a large number of factors.\n\n=== Financial variables ===\n\nBecause of the exponential nature of [[interest]] and [[inflation]], financial indicators such as [[interest rate]]s, [[share|stock]] values, or [[commodity]] [[price]]s make good examples of \'\'multiplicative\'\' behaviour. As such, they should not be expected to be normal, but lognormal. \n\n[[Benoît Mandelbrot]], the popularizer of [[fractals]], has claimed that even the assumption of lognormality is flawed.\n\n=== Lifetime ===\n\nOther examples of variables that are \'\'not\'\' normally distributed include the lifetimes of humans or mechanical devices. Examples of distributions used in this connection are the [[sebaran eksponensial]] (memoryless) and the [[Weibull distribution]]. In general, there is no reason that [[waiting times]] should be normal, since they are not directly related to any kind of additive influence.\n\n=== Test scores ===\n\nThe IQ score of an individual for example can be seen as the result of many small additive influences: many genes and many environmental factors all play a role.\n\n* [[IQ|IQ scores]] and other ability scores are approximately normally distributed. For most IQ tests, the mean is 100 and the standard deviation is 15.\n\n\'\'Criticisms: test scores are discrete variable associated with the number of correct/incorrect answers, and as such they are related to the binomial. Moreover (see [http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&selm=b26c3b%241s3c%40odds.stat.purdue.edu this USENET post]), raw IQ test scores are customarily \'massaged\' to force the distribution of IQ scores to be normal. Finally, there is no widely accepted model of intelligence, and the link to IQ scores let alone a relationship between influences on intelligence and \'\'\'additive\'\'\' variations of IQ, is subject to debate.\'\'\n\n== Further reading ==\n\n*See also [[multivariate normal distribution]].\n\n== External links and references==\n\n*[http://ce597n.www.ecn.purdue.edu/CE597N/1997F/students/michael.a.kropinski.1/project/tutorialMichael A. Kropinski\'s normal distribution tutorial]\n* S. M.Stigler: \'\'Statistics on the Table\'\', Harvard University Press 1999, chapter 22. History of the term \"normal distribution\".\n* [http://members.aol.com/jeff570/mathword.html Earliest Known uses of some of the Words of Mathematics]. See: [http://members.aol.com/jeff570/n.html] for \"normal\", [http://members.aol.com/jeff570/g.html] for \"Gaussian\", and[http://members.aol.com/jeff570/e.html] for \"error\".\n* [http://members.aol.com/jeff570/stat.html Earliest Uses of Symbols in Probability and Statistics]. See Symbols associated with the Normal Distribution.\n\n[[Category:Probability and statistics]]','/* Generating normal random variables */',13,'Budhi','20041224031917','',0,0,1,0,0.81294566617,'20041224031917','79958775968082'); INSERT INTO cur VALUES (902,0,'Sebaran-t_student','[[it:variabile casuale t di Student]]\n\nDina [[kamungkinan]] jeung [[statistik]], \'\'\'sebaran-t\'\'\' atawa \'\'\' sebaran Student\'\'\' loba digunakeun keur nga-estimasi [[nilai ekspektasi|mean]] tina populasi [[sebaran normal|nu kasebar sacara normal]] dina waktu ukuran sampelna leutik. Dasar nu kawentar [[Student\'s t-test|Student\'s \'\'t\'\'-test]] nyaeta keur [[statistical significance]] tina dua sampel [[mean]] anu beda, sarta [[interval kapercayaan]] keur dua populasi means anu beda.\n\nAsal tiori ngeunaan sebaran-\'\'t\'\' mimiti dipublikasi dina taun 1908 ku [[William Sealey Gosset]] dina paper nu ditulis pseudonym \'\'\'\'\'Student\'\'\'\'\'. Tiori Tes-\'\'t\'\' sarta hal nu pakait leuwih dipikaharti dina tulisan-tulisan [[Ronald A. Fisher|R.A. Fisher]], nu nyebut ieu sebaran ku \"Student\'s distribution\".\n\nStudent\'s distribution loba digunakeun lamun (saperti digunakeun dina statistik praktis) populasi [[simpangan baku]] teu dipikanyaho sarta bakal di-estimasi tina data. Dina buku teksbook dijelaskeun yen simpangan baku lamun dipikanyaho aya dua tipe nyaet: (1) dina hal ukuran sampel kacida gedena yen salah sahiji keur nganyahokeun simpangan baku tina data ku cara nga-estimasi [[varian]] lamun varian pasti, jeung (2) keur ngagambarkeun alesan sacara matematik, numana masalah estimasi simpangan baku kadangkadal \"diabaikan\" sabab lain ngarupakeun hal anu kudu dijelaskeun ku pangarang atawa instruktur.\n\n==Kumaha sebaran-\'\'t\'\' student loba dipake==\n\nAnggap \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun [[variabel acak]] [[statistical independence|bebas]] nu kasebar normal mibanda nilai ekspektasi μ sarta [[varian]] σ2. Saterusna\n\n:\\overline{X}_n=(X_1+\\cdots+X_n)/n\n\ndijadikeun \"sample mean\", sarta\n\n:S_n^2=\\frac{1}{n-1}\\sum_{i=1}^n\\left(X_i-\\overline{X}_n\\right)^2\n\ndijadikeun \"sample variance\". Saperti anu ditempo di handap ieu\n\n:Z=\\frac{\\overline{X}_n-\\mu}{\\sigma/\\sqrt{n}}\n\nngarupakeun sebaran normal nu mibanda mean 0 sarta variance 1. Gosset nalungtik hubungan kualitas jadi,\n\n:T=\\frac{\\overline{X}_n-\\mu}{S_n/\\sqrt{n}}\n\nsarta nembongkeun yen \'\'T\'\' ngabogaan [[probability density function]]\n\n:f(t) = \\frac{\\Gamma((\\nu+1)/2)}{\\sqrt{\\nu\\pi\\,}\\,\\Gamma(\\nu/2)} (1+t^2/\\nu)^{-(\\nu+1)/2}\n\nnumana ν sarua jeung \'\'n\'\' − 1.\nSebaran \'\'T\'\' eta ayeuna disebut \'\'\'sebaran\'\'\'-\'\'\'\'\'t\'\'.\nParameter ν sacara konvensional disebut angka \'\'\'degrees of freedom atawa tingkat kabebasan\'\'\'. Sebaran gumantung kana nilai ν, lain kana nilai μ atawa σ;\nheunteu gumantungna ieu sebaran kana nilai μ jeung σ ngajadikeun sebaran-\'\'t\'\'-penting boh dina tiori sarta praktek.\n\n==Kumaha cara make sebaran \'\'t\'\'-student==\n\nInterval dina titik ahir nyaeta\n\n:\\overline{X}_n\\pm A\\frac{S_n}{\\sqrt{n}}\n\nnumana \'\'A\'\' nyaeta pendekatan titik-persentasi sebaran -\'\'t\'\', ngarupakeun [[interval kapercayaan]] keur μ. Saterusna, lamun nilai mean tina susunan observasi dipikanyaho maka bisa disebutkeun aya alesan keur merkirakeun yen data ngaboogan sebaran normal, bisa digunakeun sebaran-\'\'t\'\' keur nge-tes confidence limits nu sacara tiori mean kaasup nilai nu diprediksi - saperti nilai prediksi dina [[null hypothesis]].\n\nHasil ieu digunakeun dina [[Student\'s t-test|Student\'s \'\'t\'\'-test]]: beda antara dua sampel mean tina dua sebaran normal bakal mibanda kasebar sacara normal, sebaran-\'\'t\'\' bisa digunakeun keur ngetes beda ieu nu sacara alesan statistik bisa diperkirakeun bakal jadi nol.\n\nAngka statistik sejen nunjukeun yen sebaran-\'\'t\'\' keur sampel anu ukuran sedeng aya dina kaayaan [[null hypothesis]] nu dipiharep, sabab kitu bentuk sebaran-\'\'t\'\' jadi dasar keur tes signifikan di kaayaan sejen nu sarua hadena waktu ngetes beda dua mean. Contona, sebaran [[Spearman\'s rank correlation coefficient]], rho, dina kasus null (taya korelasi) nembongkeun hasil nu hade ku pendekatan sebaran-\'\'t\'\' keur ukuran sample leuweih ti 20.\n\nTempo [[prediction interval]] keur conto sejen nu make distribusi ieu.\n\n==Tiori lanjutan==\n\nHasil Gosset\'s bisa netepkeun hal nu leuwih umum. (Keur conto tempo Hogg and Craig, Bagean 4.4 and 4.8.) Anggap \'\'Z\'\' ngabogaan [[sebaran normal]] nu mibanda mean 0 sarta variance 1. Anggap \'\'V\'\' ngabogaan [[sebaran chi-kuadrat]] nu mibanda ν tingkat kabebasan. Terus kira-kira yen \'\'Z\'\' sarta \'\'V\'\' ngarupakeun [[statistical independence|bebas]] (tempo [[teorema Cochran]]). Mangka rasio\n\n: \\frac{Z}{\\sqrt{V/\\nu\\ }} \n\nngabogaan sebaran-\'\'t\'\' nu mibanda ν tingkat kabebasan. \n\nKeur sebaran-\'\'t\'\' nu mibanda ν tingkat kabebasan,\nnilai ekspektasi 0,\nsarta [[varian]] ν/(ν − 2) lamun ν > 2. [[Skewness]] na 0 sarta [[kurtosis]] na 6/(ν − 4) lamun ν > 4.\n\n[[Cumulative distribution function]] dijelaskeun\n[[incomplete beta function]],\n\n:\\int_{-\\infty}^t f(u)\\,du = \\left\\{ \n\\begin{matrix} 1 - \\frac{1}{2} I_x(\\nu/2,1/2) & \\mbox{if}\\quad t > 0 \\\\ \\\\\n\\frac{1}{2} I_x(\\nu/2,1/2) & \\mbox{otherwise}\n\\end{matrix}\\right.,\n\nnu mibanda\n\n:x = \\frac{1}{1+t^2/\\nu}.\n\nSebaran-\'\'t\'\' aya hubunganna jeung [[sebaran-F]] nyaeta: nilai kuadrat \'\'t\'\' nu mibanda ν tingkat kabebasan disebarkeun salaku \'\'F\'\' nu mibanda nilai 1 sarta ν tingkat kabebasan.\n\nSakabeh fungsi probability density sebaran-\'\'t\'\' digambarkeun dina bentuk bel salaku variabel [[sebaran normal]] nu mibanda nilai mean 0 sarta varian 1, iwal ti ngabogaan nilai nu leuwih handap sarta ngalegaan bentuk belna. Salaku jumlah tingkat kabebasan anu nambahan, sebaran-\'\'t\'\' ngadeukeutan sebaran normal nu mibanda nilai mean 0 sarta varian 1. \n\nGambar di handap ieu nunjukeun densitas sebaran-\'\'t\'\' dina kaayaan beuki naekna nilai ν. \nSebaran normal ditempokeun dina garis biru keur perbandingan.\nCatetan yen sebaran-\'\'t\'\' (garis beureum) jadi rapet jeung sebaran normal lamun ν oge ningkat.\nKeur ν = 30 sebaran-\'\'t\'\' persis sarua jeung sebaran normal.\n\n
\n\n\n\n\n\n \n
Density of the \'\'t\'\'-distribution for 1, 2, 3, 5, 10, and 30 df
[[Image:T distribution 1df.png|240px]] [[Image:T distribution 2df.png|240px]] [[Image:T distribution 3df.png|240px]]
[[Image:T distribution 5df.png|240px]] [[Image:T distribution 10df.png|240px]] [[Image:T distribution 30df.png|240px]]
\n
\n\n==Sumber sejen==\n\n* \"Student\" (W.S. Gosset) (1908) The probable error of a mean. \'\'Biometrika\'\' 6(1):1--25. \n\n* M. Abramowitz and I. A. Stegun, eds. (1972) \'\'Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables.\'\' New York: Dover. \'\'(See Section 26.7.)\'\'\n\n* R.V. Hogg and A.T. Craig (1978) \'\'Introduction to Mathematical Statistics\'\'. New York: Macmillan.\n\n== Tumbu kaluar ==\n\n* [http://members.aol.com/jeff570/s.html Earliest Known Uses of Some of the Words of Mathematics (S)] \'\'(Remarks on the history of the term \"Student\'s distribution\")\'\'\n\n[[Category:Probability and statistics]]','/* Kumaha cara make sebaran \'\'t\'\'-student */',13,'Budhi','20041225044456','',0,0,1,0,0.351281690109,'20041225044456','79958774955543'); INSERT INTO cur VALUES (903,0,'Interval_kapercayaan','Dina [[statistik]], \'\'\'interval kapercayaan (confidence interval)\'\'\' ngarupakeun bentuk nu ilahar tina [[interval estimasi]]. Lamun \'\'U\'\' jeung \'\'V\'\' ngarupakeun statistik (i.e., [[variabel acak]] nu \"bisa diobservasi\" ) numana [[probability distribution|sebaran kamungkinan]] gumantung kana sababaraha [[parameter]] θ nu teu katalungtik, jeung hubunganna \n\n:P(U<\\theta\n\nsaterusna random interval (\'\'U\'\',\'\'V\'\') nyaeta \'\'\'\"90% interval kapercayaan keur θ\"\'\'\'.\n\n==Kumaha bisa salah harti interval kapercayaan==\n\nHal nu matak kataji dina kasalahan nangtukeun kaputusan saperti nu bakal dijelaskeun. Urang ngagunakeun hurup gede \'\'U\'\' jeung \'\'V\'\' keur variabel acak; ilaharna ngagunakeun hurup leutik \'\'u\'\' jeung \'\'v\'\' keur nilai nu ka observasi. Salah harti dina nyimpulkeun nyaeta yen\n\n:P(u<\\theta\n\nsanggeus data di-observasi, sebaran probabiliti kondisional θ, tina data nu diberekeun dijadikeun kasimpulan. Conto, anggap \'\'X\'\' [[sebaran normal|kasebar normal]] mibanda nilai ekspektasi θ sarta varian 1. (Jelas pisan yen teu realistik keur nangtukeun nilai varian, sedengkeun nilai ekspektasi kudu disimpulkeun tina data, tapi ieu ngan sakadar keur conto nu basajan). Variabel acak \'\'X\'\' ka-observasi. (Variabel acak \'\'X\'\' − θ salah sahiji conto nu \'\'teu\'\' ka-observasi, nilaina gumantung kana θ.) Mangka \'\'X\'\' - θ kasebar normal mibanda nilai ekspektasi 0 sarta varian 1; saterusna\n\n:P(-1.645\n\nAkibatna\n\n:P(X-1.645<\\theta\n\nmangka interval ti \'\'X\'\' − 1.645 nepi ka \'\'X\'\' + 1.645 mibanda interval kapercayaan 90% keur θ. Tapi waktu \'\'X\'\' = 82 ka-observasi, naha bisa disebutkeun yen \n\n:P(82-1.645<\\theta<82+1.645)=0.9\\ \\mbox{?}\n\nKasimpulan eta teu nuturkeun hukum probabiliti sabab θ lain \"variabel acak\"; i.e., taya sebaran probabiliti nu nangtukeun hal eta. Interval kapercayaan sacara umum mangrupa metoda [[frequentism|frekuensi]], i.e., dipake ku anu naksir \"probabilti 90%\" salaku \"90% kajadian dina sakabeh kasus\". Conto, θ sarua jeung massa planet Neptunus, sarta sacara acak urang ngukur kasalahan rata-rata 90% tina waktu tetapan mangka massa tina wilangan ieu jeung wilangan nu bakal aya ngarupakeun nilai nu bener. Massa lain ngarupakeun hal nu acak. Sanajan kitu, mun urang boga nilai ukuran 82 satuan, urang teu bisa nyebutkeun yen hal eta aya dina 90% keur sakabeh kasus, massa antara 82 − 1.645 jeung 82 + 1.645. \n\nTapi lamun probabiliti ditaksir salaku tingkat kapercayaan tinimbang frekuensi relatif dina kajadian variabel acak, i.e., dina hal ieu make [[Bayesian probability|Bayesians]] tinimbang frekuensi, bisa disebutkeun \'\'yen\'\' urang yakin 90% massa antara 82 − 1.645 jeung 82 + 1.645? Loba jawaban keur hal ieu anu diusulkeun sarta sacara filosofi kontroversial. Jawaban lain dumasar kana teorema matematik, tapi kana filosofi.\n\nKeur nu nganut metoda frekuensi, cara ngajelaskeun interval kapercayaan saperti kieu: \"\'\'Interval kapercayaan ngagambarkeun nilai keur parameter populasi keur ngabedakeun antara estimasi parameter jeung observasi taya [[statistically significant|hartina sacara statistik]] dina tingkat 10%\'\'\". Kritik metoda frekuensi nyaeta nyumputkeun kaayaan nu sabenerna sarta pamahaman kana ieu metoda bisa dijelaskeun saperti kieu: \"\'\'Lamun populasi parameter aya di jero interval kapercayaan, mangka probiliti nu di estimasi bakal milu ka observasi atawa bakal deukeut kana parameter, hartina kurang atawa sarua jeung 90%\'\'\". Nu make metoda Bayesian, lamun maranehna ngahasilkeun interval kapercayaan, sacara jelas bakal ngomong \"\'\'Kuring percaya yen parameter di kanyataanna dina interval kapercayaan 90%\'\'\".\n\n==Conto praktis kongkrit==\n\nDina kaca ieu salah sahiji conto nu leuwih ilahar dipake. Anggap \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun sampel bebas tina populasi sebaran normal nu mibanda mean μ sarta variance σ2. Tempo\n\n:\\overline{X}=(X_1+\\cdots+X_n)/n,\n\n:S^2=\\frac{1}{n-1}\\sum_{i=1}^b\\left(X_i-\\overline{X}\\,\\right)^2.\n\nMangka\n\n:T=\\frac{\\overline{X}-\\mu}{S/\\sqrt{n}}\n\nmibanda [[sebaran-t student]] numana \'\'n\'\' − 1 nyaeta tingkat kabebasan. Catetan yen ieu sebaran teu gumantung kana nilai parameter μ and σ2 nu teu ka-observasi; i.e., ngarupakeun \'\'pivotal quantity\'\'. Lamun \'\'c\'\' ngarupakeun persentil nu ka-95 tina ieu sebaran, mangka\n\n:P\\left(-c\n\n(Catetan: \"95\" sarta \"90\" bener; ieu sering dipake keur ngurangan kasalahan.)\n\nAkibatna\n\nP\\left(\\overline{X}-cS/\\sqrt{n}<\\mu<\\overline{X}+cS/\\sqrt{n}\\right)=0.9\n\nsarta urang mibanda confidence interval 90% keur μ.\n\n==Tempo oge==\n\n* [[prediction interval]]','',13,'Budhi','20041225044655','',0,0,1,0,0.544072815936,'20041225044655','79958774955344'); INSERT INTO cur VALUES (904,0,'Interval_estimasi','Dina [[statistik]], \'\'\'interval estimasi\'\'\' nyaéta digunakeunana [[data]] [[Sampling (statistics)|sampel]] pikeun ngitung nilai [[interval (mathematics)|interval]] nu mungkin tina [[paraméter populasi]] nu teu dipikanyaho. Bentuk nu ilahar tina interval estimasi nyaéta [[interval kapercayaan]] (métode nu [[frequentism|mindeng dipaké]]) sarta [[credible interval|interval nu hadé dipakéna]] (métode [[Bayesian probability|Bayesian]]).\n\n\n{{pondok}}\n\n[[en:Interval estimation]]','',13,'Budhi','20041225044611','',0,0,1,0,0.149172253045,'20050303211247','79958774955388'); INSERT INTO cur VALUES (905,0,'Sampling_(statistics)','\'\'\'Sampling\'\'\' ngarupakeun bagean tina [[statistical practice]] nu musatkeun kana pamilihan individu observasi nu diharepkeun bakal ngahasilkeun pangaweruh ngeunaan [[populasi]] anu ditalungtik, husuna keur kaperluan [[statistical inference]]. Sabagian ti eta, hasil tina [[probability theory]] jeung [[tiori statistik]] bisa digunakeun keur panunjuk dina kaperluan praktis.\n\nProses sampling ngabogaan lima tahapan, nyaeta:\n\n* Hartikeun populasi anu ditalungtik \n* Husukeun heula [[sampling frame]], [[set]] barang atawa kajadian anu mungkin keur diukur\n* Hususkeun [[sampling method]] keur pamilihan barang atawa kajadian tina frame\n* Sampling jeung ngumpulkeun data\n* Review proses sampling\n\n==Harti Populasi==\n\nSuksesna statistik praktis dumasar kana pokus [[problem definition]]. Sacara tipe, we seek to take action on some population, for example when a [[batch]] of material from [[batch production|production]] must be released to the customer or sentenced for scrap or rework. Alternatively, we seek knowledge about the [[cause system]] of which the population is an outcome, for example \nwhen a researcher performs an experiment on rats with the intention of gaining insights into [[biochemistry]] that can be applied for the benefit of [[humans]]. In the latter case, the population of concern can be difficult to specify, as it is in the case of measuring some physical characteristic such as the [[electrical conductivity]] of [[copper]].\n\nHowever, in all cases, time spent in making the population of concern precise is always well spent, often because it raises many issues, ambiguities and questions that would otherwise have been overlooked at this stage.\n\n==Sampling frame==\n\nIn the most straightforward case, such as the sentencing of a batch of material from production ([[acceptance sampling by lots]]), it is possible to identify and measure every single item in the population and to include any one of them in our sample. However, in the more general case this is not possible. There is no way to identify all rats in the set of all rats. There is no way to identify every voter at a forthcoming election (in advance of the election). \n\nThese imprecise populations are not amenable to sampling in any of the ways below and to which we could apply statistical theory.\n\nAs a remedy, we seek a \'\'sampling frame\'\' which has the property that we can identify every single element and include any in our sample. For example, in an electoral poll, possible sampling frames include:\n\n* Electoral register\n* Telephone directory\n* Shoppers in Anytown, High Street on the Monday afternoon before the election.\n\nThe sampling frame must be representative of the population and this is a question outside the scope of statistical theory demanding the judgement of experts in the particular subject matter being studied. All the above frames omit some people who will vote at the next election and contain some people who will not. People not in the frame have no prospect of being sampled. Statistical theory tells us about the uncertainties in extrapolating from a sample to the frame. In extrapolating from frame to population its role is motivational and suggestive.\n\nIn defining the frame, practical, economic, ethical and technical issues need to be addressed. The need to obtain timely results may prevent extending the frame far into the future.\n\nThe difficulties can be extreme when the population and frame are [[disjoint]]. This is a particular problem in [[forecasting]] where inferences about the future are made from historical [[data]]. In fact, in [[1703]], when [[Jacob Bernoulli]] proposed to [[Gottfried Leibniz]] the possibility of using historical mortality data to predict the [[probability]] of early death of a living man, [[Gottfried Leibniz]] recognised the problem in replying:\n\n\'\'Nature has established patterns originating in the return of events but only for the most part. New illnesses flood the human race, so that no matter how many experiments you have done on corpses, you have not thereby imposed a limit on the nature of events so that in the future they could not vary.\'\'\n\nHaving established the frame, there are a number of ways of organising it to improve efficiency and effectiveness.\n\n===Simple sampling===\n\nIn this case, all elements of the frame are treated equally and it is not subdivided or partitioned. One of the sampling methods below is applied to the whole frame.\n\n===[[Stratified sampling]]===\n\nWhere the population embraces a number of distinct categories, the frame can be organised by these categories into separate \'\'strata\'\' or [[demographics]]. One of the sampling methods below is then applied to each \'\'stratum\'\' separately, maintaining the same balance in numbers as exists in the population and resulting in an improvement in precision.\n\n===Cluster sampling===\n\nWhere items in the population are clustered, sampling can reflect this to minimise costs. For example, in a national survey by personal interview, many people will be remotely located and costly to reach. [[Cluster sampling]] locates the frame in areas of concentrated habitation.\n\n===[[Multistage sampling]]===\n\n...\n\n==Sampling method==\n\nWithin any of the types of frame identified above, a variety of sampling methods can be employed, individually or in combination.\n\n===Random sampling===\n\nIn [[simple random sampling|Random sampling]], every combination of items from the frame, or stratum, has an equal probability of occurring. It guarantees that the sample is representative of the frame but is infeasible in many practical situations. It is a type of [[probability sampling]].\n\n===Systematic sampling===\n\nSelecting (say) every tenth name from the telephone directory is simple to implement and is an example of [[systematic sampling]]. Though simple to implement, asymmetries and biases in the structure of the data can lead to [[bias (statistics)|bias]] in results. It is a type of [[nonprobability sampling]]\n\n===Mechanical sampling===\n\n[[Mechanical sampling]] occurs typically in sampling [[solid]]s, [[liquid]]s and [[gas]]es, using devices such as grabs, scoops, [[thief probe]]s, the [[coliwasa]] and [[riffle splitter]]. \n\nMechanical sampling is not [[randomness|random]] and is a type of [[nonprobability sampling]]. Care is needed in ensuring that the sample is representative of the frame. Much work in this area was developed by [[Pierre Gy]].\n\n===Convenience sampling===\n\nSometimes called, \'\'grab\'\' sampling, this is the method of choosing items arbitrarily and in an unstructured manner from the frame. Though almost impossible to treat rigorously, it is the method most commonly employed in many practical situations.\n\n===Ukuran sampel===\n\nWhere the frame and population are identical, statistical theory yields exact recommendations on sample size. However, where it is not straightforward to define a frame representative of the population, it is more important to understand the [[cause system]] of which the population are outcomes and to ensure that all sources of variation are embraced in the frame. Large number of observations are of no value if major sources of variation are neglected in the study.\n\n==Sampling and data collection==\n\nGood data collection involves:\n\n* Following the defined sampling process\n* Keeping the data in time order\n* Noting comments and other contextual events\n* Recording non-responses\n\n==Review of sampling process==\n\nAfter sampling, a review should be held of the exact process followed in sampling, rather than that intended, in order to study any effects that any divergences might have on subsequent analysis. A particular problem is that of \'\'non-responses\'\'.\n\n===Non-responses===\n\nIn [[survey]] sampling, many of the individuals identified as part of the sample may be unwilling to participate or impossible to contact. In this case, there is a risk of differences, between (say) the willing and unwilling, leading to [[bias (statistics)|bias]] in conclusions. This is often \naddressed by follow-up studies which make a repeated attempt to contact the unresponsive and to characterise their similarities and differences with the rest of the frame.\n\n==Bibliography==\n\n* Cochran, W G (1977) \'\'Sampling Techniques\'\'\n* Deming, W E (1975) On probability as a basis for action, \'\'The American Statistician\'\', 29(4), pp146-152\n* Gy, P (1992) \'\'Sampling of Heterogeneous and Dynamic Material Systems: Theories of Heterogeneity, Sampling and Homogenizing\'\'\n\n==Related topics==\n\n*[[statistik]]\n*[[marketing research]], [[quantitative marketing research]]\n*[[sample space]], [[statistical sample]]\n\n==External Links==\n\n* [http://gsociology.icaap.org/methods/sampling.html Links to Sampling Guides]\n\n[[da:Stikprøve]]\n[[es:muestreo]]','',3,'Kandar','20050208063441','',0,0,0,0,0.168701777779,'20050208063441','79949791936558'); INSERT INTO cur VALUES (906,0,'Populasi_(Statistik)','In [[statistik]], a \'\'\'statistical population\'\'\' is a [[set]] of entities concerning which [[statistical inference]]s are to be drawn, often based on a random sample taken from the population. For example, if we were interested in generalizations about crows, then we would describe the set of crows that is of interest. Notice that if we choose a population like \'\'all crows\'\', we will be limited to observing crows that exist now or will exist in the future. Probably, [[geography]] will also constitute a limitation in that our resources for studying crows are also limited.\n\n\"Population\" is also used to refer to a set of measurements or values. Suppose, for example, we are interested in the set of all adult crows now alive in the county of Kent, and we want to know the mean weight of these birds. For each bird in the population of crows there is a weight, and the set of these weights is called the \"population of weights\".\n\n\'\'\'See also:\'\'\' [[population]], [[statistics]], [[statistical sample]]\n[[da:Population (statistik)]]\n[[es:Población estadística]]','fix da es',8,'Suisui','20040909032854','',0,0,1,0,0.470963555142,'20040909032854','79959090967145'); INSERT INTO cur VALUES (907,0,'Mean','Dina [[statistik]], \'\'\'\'\'mean\'\'\'\'\' (rata-rata) mibanda dua harti:\n* \'\'[[average]]\'\' basa Inggris sapopoe, leuwih cocog lamun disebut [[arithmetic mean]], dibandingkeun jeung [[geometric mean]] atawa [[harmonic mean]]. The average biasa oge disebut sample mean (rata-rata sampel).\n* [[nilai ekspektasi]] tina [[variabel acak]], biasa disebut oge population mean (rata-rata populasi).\n\nSampel mean biasa dipake keur [[estimator]] ti [[central tendency]] saperti populasi mean. Sanajan kitu, estimator sejen oge dipake. Contona, [[median]] leuwih [[robust]] estimator keur central tendency tinimbang sampel mean.\n\nKeur nilai-real [[variabel acak]] \'\'X\'\', mean nyaeta [[nilai ekspektasi]] \'\'X\'\'.\nLamun ekspektsi euweuh, variabel random teu ngabogaan mean.\n\nKeur [[data set]], mean ngan sakadar jumlah sakabeh observasi dibagi ku lobana observasi. \nKeur ngajelaskeun \'\'komunal\'\' tina susuna data, geus ilahar dipake [[simpangan baku]] keur ngajelaskeun sabaraha beda tina observasi.\nSimpangan baku ngarupakeun akar kuadrat tina \'\'average\'\' deviasi kuadrat tina mean.\n\nMean ngarupakeun nilai unik ngeunaan jumlah kuadrat deviasi nu minimum. \nLamun ngitung jumlah kuadrat deviasi tina ukuran [[central tendency]] sejen, eta bakal leuwih gede tinimang keur mean.\nIeu nerangkeun kunaon simpangan baku sarta mean ilahar dipake babarengan dina laporan statistik.\n\nAlternatip keur ngukur dispersi nyaeta simpangan mean, sarua jeung \'\'average\'\' [[simpangan mutlak]] tina mean. Ieu kurang sensitip keur \'\'outlier\'\', tapi kurang nurut waktu kombinasi susunan data.\n\nNilai mean tina fungsi, f(x), dina interval, a, bisa diitung (ngagunakeun proses limit dina definisi susunan data) saperti:\n\n:E(f(X))=\\frac{\\int_a^b f(x)\\,dx}{b-a}.\n\nCatetan, teu sakabeh [[probability distribution]] ngabogaan mean atawa [[varian]] - tempo [[sebaran Cauchy ]] keur contona.\n\nDi handap ngarupakeun kasimpulan tina sabaraba metoa keur ngitung meman tina susunan wilangan \'\'n\'\'.Tempo [[table of mathematical symbols]] keur nerangkeun simbol nu dipake.\n\n==Aritmetik Mean==\nThe [[arithmetic mean]] is the \"standard\" average, often simply called the \"mean\". It is used for many purposes but also often \'\'abused\'\' by incorrectly using it to describe [[skewness|skewed]] distributions, with highly misleading results. The classic example is average income - using the arithmetic mean makes it appear to be much higher than is in fact the case. Consider the scores {1, 2, 2, 2, 3, 9}. The arithmetic mean is 3.16, but five out of six scores are below this!\n\n: \\bar{x} = {1 \\over n} \\sum_{i=1}^n{x_i} \n\n==Geometrik Mean==\nThe [[geometric mean]] is an average which is useful for sets of numbers which are interpreted according to their product and not their sum (as is the case with the arithmetic mean). For example rates of growth.\n\n: \\bar{x} = \\sqrt[n]{\\prod_{i=1}^n{x_i}} \n\n==Harmonik Mean==\nThe [[harmonic mean]] is an average which is useful for sets of numbers which are defined in relation to some [[unit]], for example [[speed]] (distance per unit of time). \n\n: \\bar{x} = \\frac{n}{\\sum_{i=1}^n \\frac{1}{x_i}} \n\n==Generalized Mean==\nThe [[generalized mean]] is an abstraction of the Arithmetic, Geometric and Harmonic Means.\n\n: \\bar{x}(m) = \\sqrt[m]{\\frac{1}{n}\\sum_{i=1}^n{x_i^m}} \n\nBy choosing the appropriate value for the parameter \'\'m\'\' we can get the arithmetic mean (\'\'m\'\' = 1), the geometric mean (\'\'m\'\' -> 0) or the harmonic mean (\'\'m\'\' = -1)\n\nThis could be generalised further as \n: \\bar{x} = f^{-1}\\left({\\frac{1}{n}\\sum_{i=1}^n{f(x_i)}}\\right) \n\nand again a suitable choice of an invertible f(\'\'x\'\') will give the arithmetic mean with f(\'\'x\'\')=\'\'x\'\', the geometric mean with f(\'\'x\'\')=log(\'\'x\'\'), and the harmonic mean with f(\'\'x\'\')=1/\'\'x\'\'.\n\n==Weighted Mean==\nThe [[weighted mean]] is used, if one wants to combine average values from samples of the same population with different sample sizes:\n\n: \\bar{x} = \\frac{\\sum_{i=1}^n{w_i \\cdot x_i}}{\\sum_{i=1}^n {w_i}} \n\nThe weights w_i represent the bounds of the partial sample. In other applications they represent a measure for the reliability of the influence upon the mean by respective values. \n\n==Truncated mean==\nSometimes a set of numbers (the [[data]]) might be contaminated by inaccurate outliers, i.e. values which are much too low or much too high. In this case one can use a [[truncated mean]]. It involves discarding given parts of the data at the top or the bottom end, typically an equal amount at each end, and then taking the arithmetic mean of the remaining data. The number of values removed is indicated as a percentage of total number of values.\n\n==Interquartile mean==\nThe [[interquartile mean]] is a specific example of a truncated mean. It is simply the arithmetic mean after removing the lowest and the highest quarter of values. \n: \\bar{x} = {2 \\over n} \\sum_{i=(n/4)+1}^{3n/4}{x_i} \nassuming the values have been ordered.\n\n==Tempo oge==\n*[[Arithmetic-geometric mean]]\n*[[Geometric-harmonic mean]]\n*[[Arithmetic-harmonic mean]]\n*[[Central tendency]]\n*[[Statistik deskriptif]]\n*[[Kurtosis]]\n*[[Median]]\n*[[Mode]]\n*[[Summary statistics]]\n\n==Tumbu kaluar==\n*[http://www.sengpielaudio.com/calculator-geommean.htm Comparison between artihmetic and geometric mean of two numbers]\n\n[[de:Mittelwert]]\n[[fi:artimeettinen keskiarvo]]\n[[it:media]]\n[[ja:平均]]\n[[nl:gemiddelde]]','',13,'Budhi','20041224090621','',0,0,1,0,0.349609452928,'20041224090621','79958775909378'); INSERT INTO cur VALUES (908,0,'Average','Dina [[matematik]], aya loba metoda keur ngitung \'\'\'average\'\'\' atawa [[central tendency]] tina hiji susunan \'\'n\'\' data. Metoda anu umum dipake, jeung geus umum dijadikeun acuan keur ngitung \'\'the average\'\', nyaeta [[arithmetic mean]]. Bisa dilongok [[table of mathematical symbols]] keur nerangkeun simbol anu digunakeun.\n\n==Aritmetik Mean==\n\n[[Arithmetic mean]] nyaeta standar \"average\", biasa dipake keur nyebut \"[[mean]]\". It is used for many purposes and may be \'\'abused\'\' by using it to describe [[skew|skewed]] distributions, with highly misleading results.\nA classic example is [[average income]]. The arithmetic mean may be used to imply that most people\'s incomes are higher than is in fact the case. When presented with an \"average\" one may be led to believe that \'\'most\'\' people\'s incomes are near this number. This \"average\" (arithmetic mean) income \'\'is\'\' higher than most people\'s incomes, because high income [[outlier|outliers]] skew the result higher (in contrast, the [[median]] income \"resists\" such skew). However, this \"average\" says nothing about the number of people near the median income (nor does it say anything about the modal income that most people are near). Nevertheless, because one might carelessly relate \"average\" and \"most people\" one might incorrectly assume that most people\'s incomes would be higher (nearer this inflated \"average\") than they are. Consider the scores {1, 2, 2, 2, 3, 9}. The arithmetic mean is 3.17, but five out of six scores are below this!\n\n: \\bar{x} = {1 \\over n} \\sum_{i=1}^n{x_i} \n\n==Median==\n\n[[Median]] nyaeta \'\'nilai sahandapeun 50% tina skor nu aya\'\', atawa \'\'nilai tengah\'\'. Dina kaayaan skor genap, mangka media ngarupakeun nilai rata-rata tina dua nilai tengah eta. It is primarily used for skewed distributions, which it represents more accurately than the arithmetic mean. (Consider {1, 2, 2, 2, 3, 9} again: the median is 2, in this case, a much better indication of central tendency than the arithmetic mean of 3.16.)\n\n==Mode==\n\nThe [[Mode]] is simply \'\'the most frequent score\'\'. It is most useful where the scores are not numeric: for example, while the mode {1, 2, 2, 2, 3, 9} is 2, the mode of {apple, apple, banana, orange, orange, orange, peach} is \'\'orange\'\'.\n\n==Other averages== \n\nThe [[geometric mean]], [[harmonic mean]], [[generalized mean]], [[weighted mean]], [[truncated mean]], and [[interquartile mean]] are described in their own articles and in the [[Mean]] article. \n\n==Related articles==\n\n* [[Batting average]]\n* [[Earned run average]]\n* [[Dow Jones Industrial Average]]\n* [[Number average molecular weight]]\n* [[Weight average molecular weight]]\n\n==Bacaan salajengna==\n\n*[[Darrell Huff]], \'\'How to lie with statistics\'\', Victor Gollancz, 1954 (ISBN 0393310728).\n\n==Tumbu kaluar==\n\n*[http://www.sengpielaudio.com/calculator-geommean.htm Calculations and comparisons between arithmetic and geometric mean between two values]\n\n\n[[de:Mittelwert]] [[en:Average]] [[it:Media]] [[ja:平均]] [[nl:Gemiddelde]] [[no:Gjennomsnitt]]','/* Median */',13,'Budhi','20041224222427','',0,0,1,0,0.834168644545,'20041224222427','79958775777572'); INSERT INTO cur VALUES (909,0,'Central_tendency','\'\'\'\'\'Central tendency\'\'\'\'\' ngarupakeun watesan anu digunakeun dina sababaraha widang [[empirical research|panalungtikan empiris]] keur \"acuan\" anu ku ahli statistik kadangkala disebut \"location\". Hiji \"measure of central tendency\" sejenna nyaeta [[location parameter]] atawa [[statistik]] digunakeun keur ngir-ngira location parameter. Contona nyaeta:\n\n#[[Arithmetic mean]], jumlah sakabeh data dibagi ku jumlah observasi dina susunan data.\n#[[Median]], nilai anu ngabagi dua kaluhur jeung kahandap dina susunan data.\n#[[Mode]], nilai anu pangseringna muncul dina susunan data.\n\nConto sejenna nyaeta midrange (rata-rata tina nilai pangluhurna jeung panghandapna dina data atawa distribusi), jeung [[truncated mean]] dipake ngitung angka dina widang olahraga ku sababaraha kasus khusus ti [[interquartile mean]]. \n\n==Tempo oge==\n*[[Average]]\n*[[Mean]]\n*[[summary statistics]] \n*[[tiori statistik]]','',3,'Kandar','20050208062948','',0,0,0,0,0.903633036606,'20050208062948','79949791937051'); INSERT INTO cur VALUES (910,0,'Statistis','[[en:Statistic]] [[it:statistica]][[de:Statistik]][[fr:statistiques]]\nA \'\'\'statistic\'\'\' (singular) is used to indicate the result of applying a statistical [[algorithm]] to a [[Data set|set of data]]. In the calculation of the [[arithmetic mean]], for example, the algorithm directs us to sum all the [[data]] values and divide by the number of data items. In this case, we call the mean a statistic. To be complete in describing any use of a statistic, one must describe both the procedure and the data set.\n\nThe popular use of the term to mean a single measurement, or \'\'[[datum]]\'\', differs from this meaning. A statistician would normally call an individual person\'s height a statistic only if that person were chosen randomly from some population of interest, but more often would use the term to refer to, for example, the [[median]] height of a group of people.\n\nOften the concept is defined by saying that a statistic is an \'\'observable\'\' [[random variable]]. Statisticians often contemplate a parametrized family of [[probability distribution]]s, any member of which could be the distribution of some measurable aspect of each member of a [[populasi statistik]] from which a sample is drawn randomly. The value of the parameter is \'\'not observable\'\', since it depends on the whole population rather than on the sample. For example, the parameter may be the average height of 25-year-old men in North America. The height of the members of a sample of 100 such men are measured; the average of those 100 numbers is a statistic; the average of the heights of all members of the population is not a statistic (unless that has somehow also been ascertained). The \'\'difference\'\' between that observable sample average and the unobservable population average is an example of a random variable that is not a statistic; the reason it is \'\'random\'\' is that the sample was chosen randomly.\n\nTempo oge: [[statistik]] jeung [[tiori statistik]]','',3,'Kandar','20050208063322','',0,0,0,0,0.65089287872,'20050208063322','79949791936677'); INSERT INTO cur VALUES (911,0,'Arithmetic_mean','Dina [[matematik]] jeung [[statistik]], \'\'\'arithmetic [[mean]]\'\'\' tina susunan data nyaeta jumlah sakabeh anggota dibagi ku jumlah \"item\" dina eta susunan. (Kecap \'\'set\'\' digunakeun perhaps somewhat loosely; for example, the number 3.8 could occur more than once in such a \"set\".) The arithmetic mean is what pupils are taught very early to call the \"[[average]].\" If the set is a [[populasi statistik]], then we speak of the \'\'\'population mean\'\'\'. If the set is a [[sampling (statistics)|statistical sample]], we call the resulting [[statistik]] a \'\'\'sample mean\'\'\'.\n\nThe mean may be conceived of as an estimate of the [[median]]. When the mean is not an accurate estimate of the median, the set of numbers, atawa [[sebaran frekuensi]], is said to be [[skewness|skewed]].\n\nWe denote the set of data by X = {x1, x2, ..., xn}. The symbol µ (Greek: mu) is used to denote the arithmetic mean of a population. We use the name of the variable, X, with a horizontal bar over it as the symbol (\"X bar\") for a sample mean. Both are computed in the same way:\n\n:\\overline{x}={\\rm arithmetic\\ mean}=(x_1+\\cdots+x_n)/n.\n\nThe arithmetic mean is greatly influenced by [[outlier]]s. For instance, reporting the \"average\" annual income in Redmond, Washington as the arithmetic mean of all annual incomes would yield a surprisingly high number because of [[Bill Gates]]. These distortions occur when the mean is different from the median, and the median is a superior alternative when that happens.\n\nIn certain situations, the arithmetic mean is the wrong concept of \"average\" altogether. For example, if a stock rose 10% in the first year, 30% in the second year and fell 10% in the third year, then it would be incorrect to report its \"average\" increase per year over this three year period as the arithmetic mean (10% + 30% + (-10%))/3 = 10%; the correct average in this case is the [[geometric mean]] which yields an average increase per year of only 8.8%.\n\nLamun X nyaeta [[variabel acak]], mangka [[nilai ekspektasi]] X bisa ditempo tina watesan-panjang mean aritmetik nyaeta kajadian unggal \'\'pengulangan\'\' \'\'pengukuran\'\' X. Ieu dipibanda ku [[law of large numbers|hukum wilangan gede]]. Salaku hasil, sampel mean dipake keur estimasi nilai ekspektasi nu teu dipikanyaho.\n\nNote that several other \"means\" have been defined, including the [[generalized mean]], the [[generalised f-mean|generalized f-mean]], the [[harmonic mean]], the [[arithmetic-geometric mean]], and the [[weighted mean]].\n\n==Lambang sejenna==\nAritmetik mean kadangkala dilambangkeun make notasi jumlah, nyaeta:\n\n:\\overline{x} = \\frac1n\\sum_{i=1}^N x_i\n\n==Tempo ogé==\n[[mean]], [[average]], [[kasimpulan statistik]], [[varian]], [[central tendency]], [[simpangan baku]], [[inequality of arithmetic and geometric means]]\n\n(Waktu dipake salaku \'\'kata benda\'\', kecap \"arithmetic\" is pronounced with the accent on the second syllable, but when used in the present sense, as an adjective, the accent is on the \'\'third\'\' syllable: \"arithMETic\")\n\n==Tumbu kaluar==\n*[http://www.sengpielaudio.com/calculator-geommean.htm Calculations and comparisons between arithmetic and geometric mean between two numbers]\n*[http://www.cut-the-knot.org/Generalization/means.shtml Arithmetic and geometric means]\n\n[[de:Mittelwert]] [[en:Average]] [[es:Media aritmética]] [[fr:Moyenne arithmétique]] [[nl:Rekenkundig gemiddelde]] [[ja:算術平均]] [[no:Gjennomsnitt]] [[pl:Średnia arytmetyczna]]','',13,'Budhi','20050104234750','',0,0,0,0,0.336151678737,'20050104234750','79949895765249'); INSERT INTO cur VALUES (912,0,'Nilai_ekspektasi','Sacara umum \'\'\'harepan\'\'\' (Ing. \'\'expectation\'\', \'\'ékspéktasi\'\')) nyaéta tetempoan nu leuwih mungkin ngeunaan kajadian. Hasil nu kurang nguntungkeun ngakibatkeun naékna [[émosi]] \'\'\'kateupanujuan\'\'\'. Lamun sababaraha kajadian ngarupakeun hal nu teu sakabéhna diperkirakeun disebutna [[surprise]]. Tempo ogé [[antisipasi]].\n----\nDina [[kamungkinan]] (hususna dina [[judi]]), \'\'\'nilai harepan\'\'\' (atawa \'\'\'harepan\'\'\') tina variabel acak ngarupakeun jumlah probabiliti unggal hasil nu mungkin tina sababaraha percobaan ku hasilna (\"nilai\"). Mangka, ieu gambaran rata-rata ngeunaan hiji \"harepan\" keur meunang unggal tarohan lamun éta tarohan identik teu sarua unggal waktu \'\'pengulangan\'\'. Catetan, nilai eta sorangan teu bisa di-ekspektasi sacara umum, saperti teu mirip atawa kajadian nu teu mungkin.\n\nContona, [[Roulette]] Amerika ngabogaan 38 hasil kamungkinan. Tarohan disimpen dina hiji angka bayaran 35-ka-1 (ieu hartina yen manehna mayar 35 kali tarohan, sabalikna oge alungan manehna dibalikeun, bareng jeung 36 kali dina alunganna). Mangka nilai ekspektasi hasil kauntungan tina unggal $1 alungan dina hiji wilangan nyaeta, tempo 38 sakabeh hasil nu mungkin: ( -1 × 37/38 ) + ( 35 × 1/38 ), ieu kira-kira -0.0526. Sanajan hiji ekspektasi, dina average, leungit leuwih ti 5 keur unggal dollar alungan.\n\nSacara umum, lamun \'\'X\'\' ngarupakeun [[variabel acak]] dihartikeun dina [[probability space|rohangan probabiliti]] (Ω, \'\'P\'\'), mangka \'\'\'nilai ekspektasi\'\'\' E\'\'X\'\' tina \'\'X\'\' dirumuskeun salaku\n\n:\\operatorname{E}X = \\int_\\Omega X dP\n\nnumana ngagunakeun [[Lebesgue integration|integral Lebesgue]]. Catetan yen teu sakabeh variabel random ngabooan nilai ekspektasi, lamun integralna teu aya. Dua variabel [[probability distribution|sebaran probabiliti]] nu sarua bakal ngabogaan nilai ekspektasi nu sarua.\n\nLamun \'\'X\'\' nyaeta [[discrete random variable|variabel random diskrit]] mibanda nilai\'\'x\'\'1, \'\'x\'\'2, ... sarta probabiliti pakait \'\'p\'\'1, \'\'p\'\'2, ... nu ditambahkeun ka 1, mangka E\'\'X\'\' bisa iitung salaku jumlah atawa [[infinite series|deret]]\n\n\n:\\operatorname{E}X = \\sum_i p_i x_i\n\nsaperti dina conto \'\'gambling\'\' di luhur.\n\n\nLamun [[probability distribution|sebaran probabiliti]] \'\'X\'\' aya dina [[probability density function|fungsi probabiliti densiti]] \'\'f\'\'(\'\'x\'\'), mangka nilai ekspektasi bisa diitung ku \n\n:\\operatorname{E}X = \\int_{-\\infty}^\\infty x f(x) dx.\n\nOperator nilai ekspektasi (atawa \'\'\'operator ekspektasi\'\'\') E ngarupakeun [[linear operator|linier]] di hal ieu\n:E(\'\'aX\'\' + \'\'bY\'\') = \'\'a\'\' E\'\'X\'\' + \'\'b\'\' E\'\'Y\'\'\nkeur unggal dua variabel random \'\'X\'\' jeung \'\'Y\'\' (nu perlu dihartikeun dina rohangan probabiliti nu sarua) sarta dua [[real number|wilangan riil]] \'\'a\'\' jeung \'\'b\'\'.\n\nNilai ekspektasi \'\'power\'\' \'\'X\'\' disebut \'\'moments\'\' \'\'X\'\'; [[moment about the mean|moments about the mean]] \'\'X\'\' oge dihartikeun salaku nilai ekspektasi nu penting. \n\nUmumna, operator nilai ekspektasi teu multiplicative, contona E(\'\'XY\'\') teu sarua jeung E\'\'X\'\' E\'\'Y\'\', iwal ti lamun \'\'X\'\' jeung \'\'Y\'\' variabel [[statistical independence|bebas]]. Bedana, sacara umum, ningkat jadi [[kovarian]] jeung [[correlation|korelasi]].\n\nUntuk estimasi nilai ekspektasi variabel random, bisa dipake nilai ukuran \'\'pengulangan\'\' variabel sarta \'\'perhitungan\'\' hasil tina [[arithmetic mean]]. Estimasi ieu nilai ekspektasi nu sabenerna sarta sipat nga-\'\'minimal\'\'-keun kuadrat kasalahan nilai nilai ekspektasi.\n\n[[de:Erwartungswert]]\n[[es:Valor esperado]]\n[[fr:Espérance mathématique]]\n[[ja:期待値]]\n[[nl:Verwachting (wiskunde)]]','',3,'Kandar','20050107085407','',0,0,0,0,0.600357228238,'20050107085407','79949892914592'); INSERT INTO cur VALUES (913,0,'Weighted_mean','Misalna aya susunan data, X={x1, x2, ..., xn} jeung hubungan beuratna , W={w1, w2, ..., wn} \'\'\'weighted mean\'\'\' diitung make rumus \n\n:\n\\bar{x} = \\frac{ \\sum_{i=1}^n w_i \\cdot x_i}{\\sum_{i=1}^n w_i}\n\n\nCatetan yen lamun kabeh beuratna sarua, weighted mean sarua jeung [[arithmetic mean]].\n\nBalik ka [[summary statistics]] -- [[central tendency]]\n\n\'\'\'Tempo oge:\'\'\' [[average]]','',13,'Budhi','20040721003026','',0,0,0,1,0.955652206184,'20040721003026','79959278996973'); INSERT INTO cur VALUES (914,0,'Median','[[de:Median]][[ja:メジアン]][[nl:Mediaan]][[pl:Mediana]]\n\n\'\'\'Median\'\'\' ngagambarkeun harti teknis \'\'middle\'\' (tengah) dumasar kana \"perasaan\". \n\n==Median dina Statistik==\nDina [[statistik]], kecap \'\'\'median\'\'\' ngarupakeun nilai anu ngabagi sampel satengah kaluhur jeung satengah kahandap. Keur manggihkeun \'\'median\'\', susun data observasi ti nilai panghandapna nepi ka pangluhurna terus pilih salah sahiji anu di tengah. If there are an even number of observations, take the [[mean]] of the two middle values. When we use the \'\'median\'\' to describe what the observations have in common, there are several choices for a measure of variability, the [[range]], the [[interquartile range]], sarta [[simpangan mutlak]]. Since the median is the same as the \'\'second quartile\'\', its calculation is illustrated in the article on [[quartile]]s.\n\nThe median is primarily used for [[skewness|skewed]] distributions, which it represents more accurately than the [[arithmetic mean]]. Consider the set {1, 2, 2, 2, 3, 9}. The median is 2 in this case, as is the [[mode]], and it might be seen as a better indication of [[central tendency]] than the [[arithmetic mean]] of 3.166....\n\nThe median is also the central point which minimises the average of the absolute deviations; in the example above this would be (1+0+0+0+1+7)/6=1.5 using the median, while it would be 1.944... using the mean. \n\nEven though [[sorting algorithm|sorting]] \'\'n\'\' items takes in general [[Big O notation|O]](\'\'n\'\' log \'\'n\'\') operations, by using a [[recursion|recursive]] \"Divide-and-Conquer\" algorithm the median of \'\'n\'\' items can be computed with only O(\'\'n\'\') operations. \n\nCalculation of medians is a popular technique in [[summary statistics]] and [[summarizing statistical data]], since it is simple to understand and easy to calculate, while also giving a measure that is more robust in the presence of [[outlier]] values than is the [[mean]]. The difference between the median and the mean is less than or equal to one [[standard deviation]].\n\n==Median of a Triangle==\nIn a [[triangle]], a \'\'\'median\'\'\' is a line joining a [[vertex]] to the midpoint of the opposite side. It divides the triangle into two parts of equal [[area]]. The three medians intersect in the triangle\'s [[centroid]] or [[center of mass]], and two-thirds of the length of each median is between the vertex and the centroid, while one-third is between the centroid and the midpoint of the opposite side.\n\nAny other lines which divide the area of the triangle into two equal parts do not pass through the centroid. \n\n==Median strip of a road==\nOn an [[expressway]], [[motorway]], or [[autobahn]], the \'\'\'median\'\'\' is the strip of [[lawn|grass]] or the [[wall]] which separates opposing [[lane]]s of [[traffic]]. This is necessary because of [[safety]] concerns, due to the high speed of [[automobile]]s on both sides, and the potential [[danger]] of a disastrous head-on [[collision]] at the combined [[velocity|speed]] of both [[vehicle]]s. \n\nMedians function secondarily as \"green areas\", beautifying [[road|roadways]]. Some [[jurisdiction]]s [[mowing|mow]] their medians, others scatter [[wildflower]] [[seed]]s which [[germinate]] and re-seed themselves every [[year]], while still others create extensive plantings of [[tree|trees]], [[shrub|shrubs]], [[Perennial plant|herbaceous perennials]] and decorative [[Poaceae|grasses]]. Where space is at a premium, dense [[hedge]]s of shrubs filter the headlights of oncoming traffic and provide a resilient barrier.\n\n==See also==\n*[[Median number]]','/* Median dina Statistik */',13,'Budhi','20040918230847','',0,0,0,0,0.938354771556,'20041229220056','79959081769152'); INSERT INTO cur VALUES (915,0,'Variabel_acak','\'\'\'Variabel acak\'\'\' bisa disebut hasil operasi analisa numerik non-deterministik atawa \"nga-bentuk\" percobaan non deterministik keur ngahasilkeun hasil [[random|acak]]. Conto, ngagorolongkeun duit receh jeung ngarekam hasilna dina variabel random nu hasilna { 1, 2, 3, 4, 5, 6 }. Milih jalma sacara acak jeung ukur jangkungna ngarupakeun conto sejen tina variabel random.\n\nSacara matematik, variabel random diartikeun hiji [[measurable function|fungsi ukuran]] tina [[probability space|rohangan probabiliti]] keur [[measurable space|ukuran rohangan]]. Ukuran rohangan nyaeta nilai variabel ruang nu mungkin, umumna dicokot keur dijadikeun [[real number|wilangan riil]] nu mibanda [[Borel algebra|Borel σ-algebra]], sarta bakal salawasna dipake dina ieu ensiklopedia, iwal tina dina hal husus.\n\n=== Fungsi Distribusi ===\n\nLamun variabel random \'\'X\'\':Ω->\'\'\'R\'\'\' aya dina ruang probabiliti (Ω, \'\'P\'\') diberekeun, urang bisa nanyakeun saperti kieu \"Sabaraha mungkin nilai \'\'X\'\' leuwih gede tinimbang 2?\". Ieu sarua jeung kamungkinan kajadian {\'\'s\'\' dina Ω : \'\'X\'\'(\'\'s\'\') > 2} nu salawasna ditulis P(\'\'X\'\' > 2) keur nyingketna.\n\nSakabeh rekaman rentang hasil kamungkinan tina nilai-real variabel random \'\'X\'\' bakal ngahasilkeun [[probability distribution]] \'\'X\'\'. Sebaran kamungkinan \"poho\" ngeunaan bagean ruang probabiliti dipake keur ngartikeun \'\'X\'\' jeung ngan direkam dina variasi nilai \'\'X\'\'. Saperti sebaran kamngkinan salawasna kawengku dina [[cumulative distribution function]] \n\n:F_X(x) = \\operatorname{P}(X < x)\n\nsarta kadangkala make oge [[probability density function]]. Dina watesan [[measure theory|measure-theoretic]], dipake variabel random \'\'X\'\' keur \"push-forward\" ukuran \'\'P\'\' dina Ω kana ngukur d\'\'F\'\' dina \'\'\'R\'\'\'. \nDina kaayaan ruang probabiliti Ω ngarupakeun alat tenis dipake keur ngajamin ayana variabel random sarta kadang-kadang keur nyusunna. Dina kaperluan praktis, leuwih ilahar dina sakabeh ruang Ω sarta nyimpen hiji ukuran dina \'\'\'R\'\'\' nu nangtukeun ukuran 1 ka sakabeh garis rill, contona dipake dina sebaran probabiliti keur gaganti variabel acak.\n\n=== Fungsi variabel random ===\n\nLamun urang ngabogaan variabel random \'\'X\'\' on Ω jeung hiji [[measurable function|fungsi ukuran]] \'\'f\'\':\'\'\'R\'\'\'->\'\'\'R\'\'\', maka \'\'Y\'\'=\'\'f\'\'(\'\'X\'\') oge jadi variabel random dina Ω, salila fungsi komposisi ukuran bisa diukur. Sababaraha prosedur ngijinkeun keur ngarobah tina ruang probabiliti (Ω,P) kana (\'\'\'R\'\'\',dF\'\'X\'\') bisa dipake keur nangtukeun sebaran probabiliti \'\'Y\'\'. \nFungsi sebaran kumulatif \'\'Y\'\' nyaeta \n\n:F_Y(y) = \\operatorname{P}(f(X) < y).\n\n==== Conto ==== \n\nAnggap \'\'X\'\' nilai-riil variabel acak sarta anggap \'\'Y\'\' = \'\'X\'\'2. Mangka, \n\n:F_Y(y) = \\operatorname{P}(X^2 < y).\n\nLamun \'\'y\'\' < 0, mangka P(\'\'X\'\'2 ≤ \'\'y\'\') = 0, mangka \n\n:F_Y(y) = 0\\qquad\\hbox{if}\\quad y < 0.\n\nLamun \'\'y\'\' ≥ 0, mangka\n\n:\\operatorname{P}(X^2 < y) = \\operatorname{P}(|X| < \\sqrt{y})\n = \\operatorname{P}(-\\sqrt{y} < X < \\sqrt{y}),\n\nmangka\n\n:F_Y(y) = F_X(\\sqrt{y}) - F_X(-\\sqrt{y})\\qquad\\hbox{if}\\quad y \\ge 0.\n\n=== Momen ===\n\nSebaran probabiliti variabel random salawasna dicirikeun ku jumlah paramater nu saeutik, oge mibanda \'\'interpretasi\'\' praktis. Contona, ieu cukup dipikanyaho salaku \"nilai average\". Hal ieu kawengku ku konsep matematik [[nilai ekspektasi]] variabel random, dilambangkeun ku E[\'\'X\'\']. Catetan yen ilaharna , E[\'\'f\'\'(\'\'X\'\')] \'\'\'teu\'\'\' sarua jeung \'\'f\'\'(E[\'\'X\'\']). Mangsa \"nilai average\" dipikanyaho, mangka sabaraha jauh tipikal nilai \'\'X\'\' tina nilai average, patarosan ieu dijawab ku [[varian]] sarta [[simpangan baku]] variabel random.\n\nMathematically, this is known as the (generalised) [[problem of moments]]: for a given class of random variables \'\'X\'\', find a collection {\'\'fi\'\'} of functions such that the expectation values E[\'\'fi\'\'(\'\'X\'\')] fully characterize the distribution of the random variable \'\'X\'\'.\n\n=== Equivalence of random variables ===\n\nThere are saveral different senses in which random variables can be considered to be equivalent. Two random variables can be equal, equal almost surely, equal in mean, or equal in distribution.\n\nIn increasing order of strength, the precise definition of these notions of equivalence is given below.\n\n==== Equality in distribution ====\n\nTwo random variables \'\'X\'\' and \'\'Y\'\' are \'\'equal in distribution\'\' if\n\n:\\operatorname{P}(X \\le x) = \\operatorname{P}(Y \\le x)\\quad\\hbox{for all}\\quad x.\n\nTo be equal in distribution, random variables need not be defined on the same probability space, but without loss of generality they can be made into independent random variables on the same probability space. The notion of equivalence in distribution is associated to the following notion of distance between probability distributions,\n\n:d(X,Y)=\\sup_x|\\operatorname{P}(X \\le x) - \\operatorname{P}(Y \\le x)|,\n\nwhich is the basis of the [[Kolmogorov-Smirnov test]]. \n\n==== Equality in mean ====\n\nTwo random variables \'\'X\'\' and \'\'Y\'\' are \'\'equal in p-th mean\'\' if the \'\'p\'\'th moment of |\'\'X\'\' − \'\'Y\'\'| is zero, that is, \n\n:\\operatorname{E}(|X-Y|^p) = 0.\n\nEquality in \'\'p\'\'th mean implies equality in \'\'q\'\'th mean for all \'\'q\'\'<\'\'p\'\'. As in the previous case, there is a related distance between the random variables, namely\n\n:d_p(X, Y) = \\operatorname{E}(|X-Y|^p).\n\n==== Almost sure equality ====\n\nTwo random variables \'\'X\'\' and \'\'Y\'\' are \'\'equal almost surely\'\' if, and only if, the probability that they are different is zero:\n\n:\\operatorname{P}(X \\neq Y) = 0.\n\nFor all practical purposes in probability theory, this notion of equivalence is as strong as actuall equality. It is associated to the following distance:\n\n:d_\\infty(X,Y)=\\sup_\\omega|X(\\omega)-Y(\\omega)|,\n\nwhere \'sup\' in this case represents the [[essential supremum]] in the sense of [[measure theory]].\n\n==== Equality ====\n\nFinally, two random variables \'\'X\'\' and \'\'Y\'\' are \'\'equal\'\' if they are equal as functions on their probability space, that is,\n\n:X(\\omega)=Y(\\omega)\\qquad\\hbox{for all}\\quad\\omega\n\n=== Convergence ===\n\nMuch of mathematical statistics consists in proving convergence results for certain [[sequence]]s of random variables; see for instance the [[law of large numbers]] and the [[central limit theorem]].\n\nThere are various senses in which a sequence (\'\'X\'\'\'\'n\'\') of random variables can converge to a random variable \'\'X\'\'. These are explained in the article on [[convergence of random variables]].\n\n=== Conto ===\n\nDi handap ieu ngarupakeun conto tina integer random i, 1 ≤ i ≤ 100:\n\n17 12 17 89 64\n4 62 6 82 80\n61 100 19 7 35\n4 23 43 49 69\n4 81 64 52 33\n59 56 56 46 25\n2 44 34 73 58\n48 94 18 65 47\n73 16 69 26 26\n65 35 65 64 2\n59 36 52 77 52\n14 79 42 71 82\n60 28 72 96 77\n72 78 58 71 44\n99 41 41 80 53\n67 7 66 49 86\n94 85 47 27 1\n6 86 50 32 26\n60 79 94 53 72\n98 78 46 73 50\n49 3 77 57 56\n23 20 70 1 58\n42 72 16 84 96\n44 42 76 19 71\n57 17 34 66 68\n63 100 37 38 68\n52 52 42 86 15\n53 76 59 43 94\n67 21 74 73 85\n16 12 45 57 7\n4 22 23 74 15\n63 80 65 76 88\n39 39 100 96 85\n64 16 55 62 50\n71 27 48 95 96\n30 65 33 71 50\n39 1 70 99 55\n74 2 74 98 48\n99 90 28 66 41\n17 80 35 8 30\n85 41 68 18 46\n86 91 40 20 43\n71 95 48 40 79\n88 77 49 81 52\n15 8 11 51 26\n99 8 28 37 47\n37 17 30 27 39\n33 65 8 31 73\n48 96 41 78 9\n89 72 16 61 48\n73 90 39 34 7\n41 1 87 48 83\n41 64 61 47 71\n2 35 66 74 29\n74 7 61 22 46\n46 4 59 23 79\n33 7 31 41 54\n63 91 81 58 66\n83 24 37 84 16\n55 9 52 92 69\n44 27 57 38 70\n37 33 23 24 18\n74 20 87 73 28\n85 34 31 76 25\n6 38 15 73 16\n79 83 94 21 52\n34 19 66 5 97\n33 100 63 36 100\n4 63 84 8 21\n21 92 60 72 22\n25 80 23 8 10\n10 63 44 14 86\n47 17 45 4 18\n21 44 27 88 10\n92 90 27 54 73\n68 13 15 68 31\n4 83 46 97 97\n32 12 66 66 87\n100 75 99 75 73\n16 86 90 66 51\n59 80 87 40 35\n21 76 65 74 73\n26 41 17 67 88\n54 42 62 98 78\n19 29 60 79 19\n76 13 95 68 76\n86 47 91 23 25\n50 57 27 97 30\n16 82 5 7 31\n72 64 18 32 100\n54 18 51 66 38\n74 91 75 41 81\n21 32 96 78 90\n9 82 21 84 80\n65 72 52 17 81\n50 1 90 14 45\n11 76 91 31 20\n93 30 30 66 10\n20 37 89 3 71\n35 96 82 11 4\n\n----\nSee also: [[discrete random variable]], [[continuous random variable]], [[probability distribution]], [[randomness]], [[random vector]], [[random function]], [[generating function]]\n[[de:Zufallsvariable]] \n[[fr:Variable aléatoire]] \n[[it:variabile casuale]] \n[[nl:stochastische variabele]]\n[[pl:Zmienna losowa]] \n[[sv:stokastisk variabel]]','/* Fungsi variabel random */',13,'Budhi','20041229223737','',0,0,0,0,0.734840331941,'20041229223737','79958770776262'); INSERT INTO cur VALUES (916,0,'Varian','\'\'Artikel ieu ngeunaan matematik. Tempo oge [[variance (land use)]].\'\'\n\n----\n\nDina [[tiori probabiliti]] sarta [[statistik]], \'\'\'varian\'\'\' tina [[variabel acak]] ngarupakeun ukuran tina [[statistical dispersion]], nu nembongkeun sabaraha jauh tina [[nilai ekspektasi]] nu dijelaskeun di dieu.\n\'\'\'Varian\'\'\' nilai-[[real number|real]] [[variabel acak]] ngarupakeun [[momen mean]] nu kadua, oge [[cumulant]] nu kadua (cumulants beda jeung central moments ngan dina tingkat 4 atawa saluhureunna). \n\n== Harti ==\nLamun μ = E(\'\'X\'\') ngarupakeun [[nilai ekspektasi]] tina variabel acak \'\'X\'\', mangka varian nyaeta \n\n:\\operatorname{var}(X)=\\sigma^2=\\operatorname{E}((X-\\mu)^2),\n\ncontona, varian ngarupakeun nilai ekspektasi kuadrat simpangan \'\'X\'\' tina mean-na sorangan. Jadi varian ngarupakeun \'\'simpangan mean kuadrat\'\'. Varian variabel random\'\'X\'\' dituliskeun salaku var(\'\'X\'\').\n\nCatetan loba sebaran, saperti [[sebaran Cauchy]], teu ngabogaan varian sabab nyimpang tina integral. Dina hal sejen, lamun sebaran teu ngabogaan nilai ekspektasi, mangka teu ngabogaan varian oge. Hal nu teu bener: sebaran ngabogaan nilai ekspektasi tapi teu ngabogaan varian.\n\n== Sipat ==\n\nLamun varian dihartikeun, bisa disimpulkeun yen varian teu pernah negatip sabab kuadrat bakal positip atawa nol. Lamun metoda keur ngitung varian hasilna negatip, geus tangtu aya kasalahan, ilaharna dina nangtukeun algoritma. Satuan varian nyaeta kuadrat tina satuan sebaran. Mangka, varian tina susunan ukuran jangkung dina sentimeter nyaeta sentimeter kuadrat. Kanyataan ieu kurang merenah sarta statistikawan leuwih ilahar ngagunakeun akar varian, [[simpangan baku]] sarta ngagunakeun ieu nilai salaku kasimpulan dispersi.\n\nIeu bisa dibuktikeun sacara gampang tina harti yen varian moal gumantung kana nilai mean \\mu. Dina hal ieu, lamun variabel \"disimpen\" antara \'\'b\'\' jadi \'\'X\'\'+\'\'b\'\', varian hasil variabel random beulah kenca teu kacekel. Sacara jelas, lamun variabel dikalikeun ku faktor skala \'\'a\'\', varian ngarupakeun hasil kali nyaeta \'\'a2\'\'. Sacara resmi, lamun \'\'a\'\' jeung \'\'b\'\' ngarupakeun konstanta riil sarta \'\'X\'\' ngarupakeun [[variabel acak]] mangka varian dihartikeun ku,\n\n:\\operatorname{var}(aX+b)=a^2\\operatorname{var}(X)\n\n[[Formula]] sejen keur varian saperti dina garis lurus nu dumasar kana harti di luhur nyaeta:\n:\\operatorname{var}(X)=\\operatorname{E}(X^2) - (\\operatorname{E}(X))^2.\nIeu ngarupakeun rumus nu geus ilahar dipake keur ngitung varian dina kaperluan praktis.\n\nSalah sahiji alesan varian leuwih sering dipake tinimbang ukuran [[statistical dispersion|dispersi]] sejenna nyaeta yen varian jumlah [[variabel acak]] bebas sarua jeung jumlah varian-na. (Kaayaan nu leuwih lemah tinimbang bebas, disebutna \"uncorrelatedness\" atawa taya hubungan). Sacara umum,\n:\\operatorname{var}(X+Y) =\\operatorname{var}(X) + \\operatorname{var}(Y)\n + 2 \\operatorname{cov}(X, Y).\nDi dieu \\operatorname{cov} nyaeta [[kovarian]], sarua jeung nol keur variabel nu taya hubungan.\n\n== Populasi varian jeung sampel varian ==\nDina statistik, konsep varian oge digunakeun keur ngajelaskeun susunan data. Waktu susunan data ngarupakeun [[populasi]], mangka disebut \'\'populasi varian\'\'. Waktu susunan data ngarupakeun [[statistical sample|sample]], mangka disebutna \'\'sampel varian\'\'.\n\nPopulasi varian tina populasi \'\'yi\'\' dimana \'\'i = 1, 2, ..., N\'\' dirumuskeun ku \n:\\sigma^2 = \\frac{1}{N} \\sum_{i=1}^N\n \\left( y_i - \\mu \\right) ^ 2,\ndimana \\mu ngarupakeun populasi mean. Dina praktek, waktu kaayaan populasi gede, geus ilahar yen teu mungkin manggihkeun nilai populasi varian nu pasti, sabab kawengku ku waktu, beaya jeung sumber sejenna.\n\nMetoda nu geus ilahar dipake keur estimasi populasi varian nyaeta [[sampling (statistics)|sampling]]. Waktu estimasi populasi varian ngagunakeun \'\'n\'\' [[random sample]]s \'\'xi\'\' dimana \'\'i = 1, 2, ..., n\'\', nuturkeun rumus di handap ieu ngarupakeun [[bias (statistics)|unbiased]] [[estimator]]:\n\n:s^2 = \\frac{1}{n-1} \\sum_{i=1}^n\n \\left( x_i - \\overline{x} \\right) ^ 2,\n\ndimana \\overline{x} ngarupakeun sampel mean.\n\nCatetan yen \'\'n-1\'\' dina pembagi diluhur jelas beda jeung persamaan keur ngitung populasi varian. Sumber nu geus ilahar ngabingungkeun nyaeta watesan \'\'sampel varian\'\' jeung notasi \'\'s2\'\' bisa jadi nempo kana unbiased estimator sejen tina populasi varian nu dirumuskeun di luhur, sarta kumaha cara mastikeun varian tina sampel, diitung ku \'\'n\'\' tinimbang \'\'n-1\'\'.\n\nSacara rasa, ngitung varian ku ngabagi make \'\'n\'\' tinimbang \'\'n-1\'\' mere hasil populasi varian \'\'underestimate\'\'. Hal ieu sabab urang ngagunakeun sampel mean \\overline{x} keur estimasu populasi mean \\mu, nu teu dipikanyaho. Dina prakten, keur \'\'n\'\' nu gede, bedana salawasna kurang ti hiji.\n\n\'\'Tempo oge [[algoritma keur ngitung varian]].\'\'\n\n== Generalisasi ==\nLamun \'\'X\'\' ngarupakeun nilai-[[vector (spatial)|vector]]- variabel random, nu mibanda nilai dina\'\'R\'\'\'\'n\'\', sarta dipinkanyaho salaku vektor kolom, mangka generalisasi sacara alami tina varian nyaeta E((\'\'X\'\' − μ)(\'\'X\'\' − μ)′), numana μ = E(\'\'X\'\') sarta \'\'X\'\' ′ ngarupakeun transpos \'\'X\'\', sarta jadi vektor baris. Varian ieu ngarupakeun nonnegative-definite matriks kuadrat, umumna dianggap salaku [[covariance matrix]].\n\nLamun \'\'X\'\' ngarupakeun nilai-kompleks variabel random, mangka varian nyaeta E((\'\'X\'\' − μ)(\'\'X\'\' − μ)*), numana \'\'X\'\'* ngarupakeun [[complex conjugate]] \'\'X\'\'. Varian ieu ngarupakeun angka riil nonnegative.\n\n== Sajarah ==\nWatesan varian mimiti dikenalkeun ku [[Ronald Fisher]] taun 1918 dina \'\'paper\'\'-na \'\'[[The Correlation Between Relatives on the Supposition of Mendelian Inheritance]]\'\'\n\nTempo oge: [[simpangan baku]], [[arithmetic mean]], [[skewness]], [[kurtosis]], [[statistical dispersion]]\n\n[[es:varianza]] [[it:varianza]] [[ja:分散]] [[de:Varianz]] [[pl:wariancja]]','',13,'Budhi','20041224210606','',0,0,1,0,0.389304518881,'20041224210606','79958775789393'); INSERT INTO cur VALUES (917,0,'Simpangan_baku','Dina [[kamungkinan|probability]] jeung [[statistik]], \'\'\'simpangan baku \'\'\' biasa digunakeun keur ngukur [[statistical dispersion]]. Simpangan baku diartikeun ogé [[akar kuadrat]] tina [[varian]]. Hal ieu dimaksudkeun keur ngukur \"dispersi\" nyaéta 1) angka non-négatif; jeung 2) has the same units as the data.\n\nBisa dibédakeun antara simpangan baku σ ([[sigma]]) tina \'\'populasi\'\' atawa [[random variable]], jeung simpangan baku \'\'s\'\' tina \'\'sampel\'\'. Rumusna dijelaskeun di handap.\n\nWatesan simpangan baku dina statistik mimiti dikenalkeun ku [[Karl Pearson]] (\'\'On the dissection of asymmetrical frequency curves\'\', [[1894]]).\n\n==Interprétasi jeung Pamakéan==\n\nSacara gampang, simpangan baku nyebutkeun sabaraha jauh unggal anggota sampel atawa populasi tina nilai [[mean]] sampel atawa populasi. Nilai simpangan baku anu gede nunjukkeun yen anggota anggota nu dimaksud jauh tina \'\'mean\'\'. Nilai simpangan baku leutik nunjukkeun yen anggota nu dimaksud raket atawa aya sabudeureun \'\'mean\'\'.\n\nConto, susunan {0,5,9,14} jeung {5,6,8,9} ngabogaan nilai \'\'mean\'\' 7, tapi nilai susunan data nu kadua ngabogaan nilai simpangan baku anu leuwih leutik.\n\nSimpangan baku oge biasa dipake keur ngukur kateupastian. Conto dina elmu fisika, waktu ngalakukeun \"pengulangan\" [[measurement]]s simpangan baku tina pengukuran nyaeta [[accuracy and precision|precision]] tina eta pengukuran. Waktu keur mutuskeun yen ukuran sarua jeung prediksi, ukuran simpangan baku ngarupakeun hal anu kacida pentingna: lamun ukuran kacida jauhna tina prediksi (ku jarak ukuran simpangan baku), bisa dianggap yen ukuran patojaiah jeung prediksi. Hal ieu ngajadikeun pamikiran yen rentang nilaina kaluar tina anu diperkirakeun lamun prediksina bener. Tempo [[prediction interval]].\n\n==Harti jeung cara pondok ngukur simpangan baku==\n\nAnggap nilai tina hiji populasi \'\'x\'\'1,...,\'\'x\'\'\'\'N\'\' (nu ngarupakeun [[real number]]). [[Mean]] populasi dirumuskeun ku\n\n:\\overline{x}=\\frac{1}{N}\\sum_{i=1}^N x_i\n\n(tempo [[addition|summation notation]]) sarta simpangan baku populasi dirumuskeun ku\n\n:\\sigma = \\sqrt{\\frac{1}{N} \\sum_{i=1}^N (x_i - \\overline{x})^2}\n\nCara gampang ngitung simpangan baku dina jumlah nu sarua dirumuskeun ku\n\n:\\sigma = \\sqrt{{\\sum_{i=1}^N{{x_i}^2}\\over{N}}-\\left({\\sum_{i=1}^N{x_i}\\over{N}}\\right)^2}\n\nSimpangan baku [[random variable]] \'\'X\'\' diartikeun ku\n\n:\\sigma = \\sqrt{\\operatorname{E}((X-\\operatorname{E}X)^2)} = \\sqrt{\\operatorname{E}(X^2) - (\\operatorname{E}(X))^2}\n\nCatetan yen teu sakabeh variabel random mibanda simpangan baku, lamun [[nilai ekspektasi]] euweuh. Lamun variabel random \'\'X\'\' dicokot tina nilai \'\'x\'\'1,...,\'\'x\'\'\'\'N\'\' ku probabiliti nu sarua, simpangan baku bisa diitung make rumus samemehna.\n\nDina kaayan nilai sampel \'\'x\'\'1,...,\'\'x\'\'\'\'n\'\' ti populasi nu gede, sababaraha pangarang ngartikeun \'\'sampel simpangan baku\'\' ku\n\n:\ns = \\sqrt{\\frac{1}{n-1} \\sum_{i=1}^N (x_i - \\overline{x})^2}\n\n\nAlesan keur harti ieu yen \'\'s\'\'2 ngarupakeun [[unbiased estimator]] keur [[varian]] σ2 ti populasi. Catetan \'\'s\'\' sorangan \'\'lain\'\' unbiased estimator keur simpangan baku σ; hal ieu cenderung underestimate ti populasi simpangan baku.\n\n==Aturan keur data sebaran normal==\n\nDina praktekna, biasa diasumsikeun yen data ngabogaaan [[sebaran normal]]. Lamun asumsi ieu bisa diyakinkeun, mangka nilai 68% dina 1 simpangan baku jauh tina mean, nilai 95% dina dua simpangan baku jauh tina mean, sarta nilai 99.7% nutupan dijero 3 simpangan baku tina mean. Ieu dikanyahokeun salaku \"aturan 68-95-99.7\".\n\n==Hubungan simpangan baku jeung \'\'mean\'\'==\n\nMean jeung simpangan baku tina susunan data ngarupakeun hal nu raket sarta umumna ditulis babarengan. Hal nu penting, simpangan baku nyaeta ukuran \"alami\" [[statistical dispersion|dispersi statistik]] lamun pusat data diukur ku mean. Rumus pastina nyaeta: suppose \'\'x\'\'1,...,\'\'x\'\'\'\'N\'\' are real numbers and define the function\n:\\sigma(r) = \\sqrt{\\frac{1}{N} \\sum_{i=1}^N (x_i - r)^2}\nNgagunakeun [[calculus|kalkulus]], teu hese keur nembongkeun yen σ(\'\'r\'\') mibanda \'\'unique minimum\'\' keur \n:r = \\overline{x}\n\n==Interpretasi geometrik==\n\nKeur ngarti geometri leuwih jentre, urang mimitian ku populasi tina tilu nilai, \'\'x\'\'1,\'\'x\'\'2,\'\'x\'\'3. Hartina yen titik \'\'P\'\'= (\'\'x\'\'1,\'\'x\'\'2,\'\'x\'\'3) aya dina \'\'\'R\'\'\'3. Anggap garis \'\'L\'\' = {(\'\'r\'\',\'\'r\'\',\'\'r\'\') : \'\'r\'\' aya dina \'\'\'R\'\'\'}. Ieu ngarupakeun \"diagonal utama\" nu ngaliwatan aslina. Lamun tilu nilai tadi sarua, mangka simpangan baku sarua jeung nol sarta \'\'P\'\' bakal nutupan \'\'L\'\'. Mangka taya alesan ke nganggap simpangan baku pakait jeung \'\'jarak\'\' \'\'P\'\' ka \'\'L\'\'. Ieu ngarupakeun kasus nu bener. Pindah ortogonalitas ti \'\'P\'\' kana garis \'\'L\'\', salah sahiji titik sasaran \n:R = (\\overline{x},\\overline{x},\\overline{x})\nnumana kordinat nilai mean dimimitian. Aljabar sederhana nunjukeun yen jarak antara \'\'P\'\' jeung \'\'R\'\' (hartina sarua jeung jarak antara \'\'P\'\' jeung garis \'\'L\'\') dirumuskeun ku σ√\'\'3\'\'. Rumus analogna (3 digantikeun ku \'\'N\'\') oge \'\'valid\'\' keur populasi nilai \'\'N\'\' values; mangka saterusna dina\'\'\'R\'\'\'\'\'N\'\'.\n\n==Simpangan baku salaku tingkat kapercayaan==\n\nDina percobaan ilmiah, hiji kapercayaan tina ukuran kajadian ngarupakeun hasil tina signal tinimbang ngan sakadar tina ramalan statistik. Mangka luhurna tingkat kapercayaan, ngarupakeun ukuran kajadian tinimbang ramalan.\n\n== Artikel pakait ==\n*[[Chebyshev\'s inequality]]\n*[[saturation (color theory)]]\n*[[root mean square]]\n*[[mean]]\n*[[skewness]]\n*[[kurtosis]]\n*[[raw score]]\n*[[skor standar]]\n\n\n[[de:Standardabweichung]]\n[[it:Deviazione standard]] \n[[ja:標準偏差]] \n[[nl:Standaarddeviatie]] \n[[sv:Standardavvikelse]]','/* Harti jeung cara pondok ngukur simpangan baku */',13,'Budhi','20040917004655','',0,0,0,0,0.892913613884,'20041226005019','79959082995344'); INSERT INTO cur VALUES (918,0,'Dispersi_statistik','Ukuran \'\'\'dispersi statistik\'\'\' kudu ngahasilkeun angka nol lamun sakabeh data identik, sarta kudu naek lamun data leuwih bareda. Ukuran dispersi pangpentingna nyaeta [[simpangan baku]], akar kuadrat [[varian]].\n\nUkuran sejenna kaasup [[rentang (statistik)|rentang]], [[interquartile range]], sarta [[simpangan mutlak|rata-rata simpangan mutlak]], sarta dina kasus kategori variabel random, [[entropy|entropi]] diskrit. Tara pernah negatip; nilai pangleutikna nu mungkin nyaeta nol. \n\nUkuran dispersi statistik sabagian dipake lamun lokasi invariant, sarta liniér dina skala. Maka lamun variabel random \'\'X\'\' ngabogaan dispersi \'\'SX\'\' mangka [[linear transformation|transpormasi liniér]] \'\'Y\'\' = \'\'aX\'\' + \'\'b\'\' keur [[real number|wilangan riil]] \'\'a\'\' jeung \'\'b\'\' kudu mibanda dispersi \'\'SY\'\' = \'\'aSX\'\'. \n\nTempo oge [[kasimpulan statistik]].','',13,'Budhi','20041224233828','',0,0,1,0,0.47268017124,'20041224233828','79958775766171'); INSERT INTO cur VALUES (919,0,'Karl_Pearson','\'\'\'Karl Pearson\'\'\' ([[March 27]], [[1857]] – [[April 27]], [[1936]]) loba kontribusina dina pengembangan [[statistics]] saperti disiplin elmu nu sarius. Anjeunna ngadegkeun Jurusan Applied Statistics di [[University College London]] taun [[1911]]; ngarupakeun [[university]] mimiti nu ngabogaan jurusan statistik di dunya. \n\n=== Biography ===\n\nKarl Pearson was born in London on the 27th March, [[1857]]. He was educated privately at University College School, after which he went to [[King\'s College, Cambridge]] to study mathematics. He then spent part of [[1879]] and [[1880]] studying medieval and 16th-century [[German literature]] at the universities of [[Berlin]] and [[Heidelberg]] – in fact, he became sufficiently knowledgeable in this field that he was offered a post in the German department at [[Cambridge University]]. \n\nHis next career move was to [[Lincoln\'s Inn]], where he read [[law]] until [[1881]] (although he never practised).\nAfter this, he returned to [[mathematics]], deputising for the mathematics [[professor]] at King\'s College London in 1881 and for the professor at University College London in [[1883]]. In [[1884]], he was appointed to the Goldshmid Chair of Applied Mathematics and Mechanics at University College London. [[1891]] saw him also appointed to the professorship of [[Geometry]] at [[Gresham College]]; here he met W.F.R. Weldon, a zoologist who had some interesting problems requiring quantitative solutions. The collaboration, in [[biometry]] and [[evolution]]ary theory, was a fruitful one and lasted until Weldon died in [[1906]]. Weldon introduced Pearson to [[Francis Galton]], who was interested in aspects of evolution such as heredity and [[eugenics]]. \n\nGalton died in [[1911]] and left the residue of his estate to the [[University of London]] for a Chair in Eugenics. Pearson was the first holder of this chair, in accordance with Galton\'s wishes. He formed the Department of Applied Statistics (with financial support from the [[Drapers\' Company]]), into which he incorporated the Biometric and Galton laboratories. He remained with the department until his retirement in [[1933]], and continued to work until his death in [[1936]]. \n\nPearson married Maria Sharpe in [[1890]], and between them they had 2 daughters and a son. The son, [[Egon Sharpe Pearson]], succeeded him as head of the Applied Statistics Department at University College. \n\nAside from his professional life, Pearson was active as a prominent freethinker and socialist. He gave lectures on such issues as \"the woman\'s question\" (this was the era of the suffragette movement in the UK) and upon [[Karl Marx]]. His commitment to [[socialism]] and its ideals led him to refuse the offer of being created an OBE ([[British honours system|Officer of the Order of the British Empire]]) in [[1920]], and also to refuse a [[Knighthood]] in 1935.\n\nPearson\'s views on eugenics, however, would be considered deeply [[racism|racist]] today. According to a [http://www.bbc.co.uk/history/genes/eugenics/beginnings.shtml BBC report on the history of genetics], \"Pearson was a fanatic – a cold, calculating measurer of man who claimed to be a socialist, but loathed the working class.\" Pearson openly advocated \"war\" against \"inferior races,\" and saw this as a logical implication of his scientific work on human measurement: \"My view – and I think it may be called the scientific view of a nation,\" he wrote, \"– is that of an organized whole, kept up to a high pitch of internal efficiency by insuring that its numbers are substantially recruited from the better stocks, and kept up to a high pitch of external efficiency by contest, chiefly by way of war with inferior races.\"\n\n=== Awards from professional bodies ===\n\nPearson achieved widespread recognition across a range of disciplines and his membership of, and awards from, various professional bodies reflects this: \n\n*1896: elected Fellow of the [[Royal Society]]\n*1898: awarded the [[Darwin Medal]]\n*1911: awarded the honorary degree of LLD from [[St Andrews University]]\n*1911: awarded a DSc from University of London\n*1920: offered (and refused) the OBE\n*1932: awarded the Rudolf Virchow medal by the Berliner Anthropologische Gesellschaft\n*1935: offered (and refused) a knighthood\n\nHe was also elected an Honorary Fellow of King\'s College Cambridge, the Royal Society of Edinburgh, University College London and the Royal Society of Medicine, and a Member of the Actuaries\' Club. \n\n=== Contributions to statistics ===\n\nPearson\'s work was all-embracing in the wide application and development of mathematical statistics, and encompassed the fields of [[biology]], [[epidemiology]], anthropometry, [[medicine]] and social [[history]]. In [[1901]], with Weldon and Galton, he founded the journal \'\'Biometrika\'\' whose object was the development of statistical theory. He edited this journal till his death. He also founded the journal \'\'Annals of Eugenics\'\' (now \'\'Annals of Human Genetics\'\') in [[1925]]. He published the \'\'Drapers\' Company Research Memoirs\'\' largely to provide a record of the output of the Department of Applied Statistics not published elsewhere. \n\nPearson\'s thinking underpins many of the `classical\' statistical methods which are in common use today. Some of his main contributions are: \n\n#\'\'\'[[Linear regression]] and [[correlation]].\'\'\' Pearson was instrumental in the development of this theory. One of his classic data sets involves the regression of sons\' height upon that of their fathers\'. Pearson built a 3-dimensional model of this data set (which remains in the care of the Statistical Science Department) to illustrate the ideas. The [[Pearson product-moment correlation coefficient]] is named after him. \n#\'\'\'Classification of distributions.\'\'\' Pearson\'s work on classifying [[probability distribution]]s forms the basis for a lot of modern statistical theory; in particular, the [[exponential family]] of distributions underlies the theory of [[generalized linear models]].\n#[[Uji kuadrat-chi Pearson]]. Bagean tina [[tes chi-kuadrat]], tes kapercayaan statistik.\n\n=== Publications ===\n\n* \'\'The New Werther\'\' ([[1880]])\n* \'\'The Trinity, A Nineteenth Century Passion Play\'\' ([[1882]])\n* \'\'Die Fronica\'\' ([[1887]])\n* \'\'The Ethic of Freethought\'\' ([[1886]])\n* \'\'The Grammar of Science\'\' ([[1892]])\n* \'\'On the dissection of asymmetrical frequency curves\'\' ([[1894]])\n* \'\'Skew variation in homogeneous material\'\' ([[1895]])\n* \'\'Regression, heredity and panmixia\'\' ([[1896]])\n* \'\'On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to hove arisen from random sampling\'\' ([[1900]])\n* \'\'Tables for Statisticians and Biometricians\'\' (([[1914]]))\n* \'\'Tables of Incomplete Beta Function\'\' ([[1934]])\n* \'\'The life, letters and labours of [[Francis Galton]]\'\' (3 vol.: [[1914]], [[1924]], [[1930]]). Available in full at http://galton.org\n\n=== External links ===\n\n* The [http://www-groups.dcs.st-andrews.ac.uk/~history/index.html MacTutor History of Mathematics] archive at St. Andrews University includes biographies of mathematicians and statisticians (including Pearson), as well as general information on the history of mathematics. \n* John Aldrich\'s [http://www.economics.soton.ac.uk/staff/aldrich/kpreader.htm Karl Pearson: a Reader\'s Guide] contains many useful links to further sources of information. \n* Gavan Tredoux\'s Francis Galton site, [http://galton.org galton.org], contains Pearson\'s biography of Francis Galton, and several other papers - in addition to nearly all of Galton\'s own published works.\n\n=== Further reading ===\n\nMost of the biographical information above is taken from A list of the papers and correspondence of Karl Pearson (1857-1936) held in the Manuscripts Room, University College London Library, compiled by M.Merrington, B.Blundell, S.Burrough, J.Golden and J.Hogarth and published by the Publications Office, University College London, 1983. See http://www.ucl.ac.uk/stats/history/pearson.html.\n\nFurther references which may be of use are: \n\n* Eisenhart, Churchill (1974): Dictionary of Scientific Biography, pp.447-73. New York, 1974. \n* Filon, L.N.G. and Yule, G.U. (1936): Obituary Notices of the Royal Society of London, Vol. ii, No.5, pp.73-110. \n* Pearson, E.S. (1938): Karl Pearson: an appreciation of some aspects of his life and work. Cambridge University Press.\n\n[[Category:Statisticians|Pearson, Karl]]\n\n[[it:Karl Pearson]]\n[[nl:Karl Pearson]]','/* Contributions to statistics */',13,'Budhi','20041224205342','',0,0,1,0,0.306067030554,'20041224205342','79958775794657'); INSERT INTO cur VALUES (920,0,'Sigma','#\'\'\'Sigma\'\'\' (aksara kapital Σ, aksara leutik σ, pilihan ς) nyaéta [[aksara Yunani]]. Tempo [[Sigma (aksara)]].\n#Aksara kapital Σ dipaké pikeun lambang operator ngajumlah nu ngahasilkeun [[dérét (matematik)|dérét]] na [[matematik]].\n#Aksara kapital Σ dipaké pikeun lambang [[alfabét]] husus hiji [[basa]], or of some other object dependent on an alphabet; expressed in mathematical terms, eg \"the language defined by alphabet Σ={a,b,c} and the rules ...\"\n#Aksara leutik σ dipaké pikeun lambang [[simpangan baku]] populasi na statistik.\n#The lower-case letter σ is used as a symbol for the [[divisor function]] in number theory.\n#Aksara leutik σ dipaké pikeun lambang [[konstanta Stefan-Boltzmann]] dina radiasi fisika.\n\n[[da:Sigma]] \n[[de:Sigma]] \n[[en:Sigma]]\n[[es:Sigma]]','',3,'Kandar','20050315104427','',0,0,0,0,0.041607326382,'20050315104427','79949684895572'); INSERT INTO cur VALUES (921,0,'Akar_kuadrat','Dina [[matematik]], \'\'\'akar kuadrat\'\'\' [[real number|wilangan riil]] [[non-negative|non-negatip]] \'\'x\'\' dilambangkeun ku \\sqrt x sarta ngagambarkeun wilangan riil non-négatip nu ngarupakeun \'\'kuadrat\'\' (hasil kali tina wilangan éta sorangan) nyaéta \'\'x\'\'.\n\nContona, \\sqrt 9 = 3 saprak 3^2 = 3 \\times 3 = 9.\n\nConto ieu nembongkeun yén akar kuadrat bisa dipaké keur ngaréngsékeun [[quadratic equation|persamaan kuadrat]] saperti x^2=9 atawa leuwih ilahar ax^2+bx+c=0.\n\nNgalegaan tina konsep akar kuadrat keur wilangan riil négatip nyaéta dina [[wilangan imajinér]] jeung [[wilangan kompléks]].\n\nAkar kuadrat mindeng mangrupa \'\'[[wilangan irasional]]\'\', requiring an infinite, non-repeating series of digits in their [[decimal]] representation. For example, \\sqrt 2 cannot be written exactly in finite or repeating decimal form. Equivalently, it cannot be represented by a [[fraction]] whose numerator and denominator are [[integer]]s. Nonetheless, it is exactly the length of the [[diagonal]] of a [[square]] with side length 1. The discovery that \\sqrt 2 is irrational is attributed to the [[Pythagoreans]].\n\n[[Tabel lambang matematis|Lambang]] akar kuadrat (√) munggaran dipaké dina [[abad ka-16]]. Diduga asalna tina bentuk singget pikeun [[r]], tina [[Basa Latin]] \'\'radix\'\' (hartina \"[[akar (matematik)|akar]]\").\n\n== Sipat ==\n\nThe following important properties of the square root functions are valid for all positive real numbers \'\'x\'\' and \'\'y\'\':\n\n:\\sqrt{xy} = \\sqrt{x} \\sqrt{y}\n:\\sqrt{\\frac{x}{y}} = \\frac{\\sqrt{x}}{\\sqrt{y}}\n:\\sqrt{x^2} = \\left|x\\right| for every real number \'\'x\'\' (see [[absolute value]])\n:\\sqrt{x} = x^{\\frac{1}{2}}\n\n[[Fungsi (matematik)|Fungsi]] akar kuadrat umumna metakeun [[rational number|wilangan rasional]] ka [[algebraic number|wilangan aljabar]]; √\'\'x\'\' is rational if and only if \'\'x\'\' is a rational number which, after cancelling, is a [[fraction (mathematics)|fraction]] of two [[perfect square|perfect squares]]. In particular, √2 is [[irrational number|irrational]]. \n\nIn [[geometry|geometrical]] terms, the square root function maps the [[area]] of a [[square]] to its side length.\n\nSuppose that \'\'x\'\' and \'\'a\'\' are reals, and that \'\'x\'\'2=\'\'a\'\', and we want to find \'\'x\'\'. A common mistake is to \"take the square root\" and deduce that \'\'x\'\' = √\'\'a\'\'. This is incorrect, because the square root of \'\'x\'\'2 is not \'\'x\'\', but the absolute value |\'\'x\'\'|, one of our above rules. Thus, all we can conclude is that |\'\'x\'\'| = √\'\'a\'\', or equivalently \'\'x\'\' = ±√\'\'a\'\'.\n\nIn [[calculus]], for instance when proving that the square root function is [[continuous]] or [[derivative|differentiable]] or when computing certain [[limit (mathematics)|limit]]s, the following identity often comes handy:\n\n:\\sqrt{x} - \\sqrt{y} = \\frac{x-y}{\\sqrt{x} + \\sqrt{y}}\n\nIt is valid for all non-negative numbers \'\'x\'\' and \'\'y\'\' which are not both zero.\n\nThe function \'\'f\'\'(\'\'x\'\') = √\'\'x\'\' has the following graph, made up of half a [[parabola]] lying on its side:\n\n[[Image:Square_root.png]]\n\nThe function is continuous for all non-negative \'\'x\'\', and [[derivative|differentiable]] for all positive \'\'x\'\' (it is not differentiable for \'\'x\'\'=0 since the [[slope]] of the [[tangent]] there is [[infinite|∞]]). Its derivative is given by \n:f\'(x) = \\frac{1}{2\\sqrt x}\nIts [[Taylor series]] about \'\'x\'\' = 1 can be found using the [[binomial theorem]]:\n\n:\\sqrt{x+1}=1 +\n\\sum_{n=1}^\\infty \n{ (-1)^{n+1} (2n-2)!\n\\over\nn! (n-1)! 2^{2n-1} }x^n\n\n: = 1 + \\frac{1}{2}x - \\frac{1}{8}x^2 + \\frac{1}{16} x^3 - \\frac{5}{128} x^4 + \\dots\n\nfor |\'\'x\'\'| < 1.\n\n== Computing square roots ==\n\n=== Calculators ===\n[[calculator|Pocket calculator]]s typically implement good routines to compute the [[exponential function]] and the [[natural logarithm]], and then compute the square root of \'\'x\'\' using the identity\n:\\sqrt{x} = e^{\\frac{1}{2}\\ln x}\nThe same identity is exploited when computing square roots with [[logarithm table]]s or [[slide rule]]s.\n\n=== Babylonian method ===\nA commonly used algorithm for approximating √\'\'x\'\' is known as the \"Babylonian method\" and is based on [[Newtons method|Newton\'s method]]. It proceeds as follows:\n#start with an arbitrary positive start value \'\'r\'\' (the closer to the root the better)\n#replace \'\'r\'\' by the average of \'\'r\'\' and \'\'x/r\'\'\n#go to 2\nThis is a quadratically convergent algorithm, which means that the number of correct digits of \'\'r\'\' roughly doubles with each step.\n\nThis algorithm works equally well in the [[p-adic numbers]], but cannot be used to identify real square roots with p-adic square roots; it is easy, for example, to construct a sequence of rational numbers by this method which converges to +3 in the reals, but to -3 in the 2-adics.\n\n=== An exact \"long-division like\" algorithm ===\nThis method, while much slower than the Babylonian method, has the advantage that it is exact: if the given number has a square root whose decimal representation terminates, then the algorithm terminates and produces the correct square root after finitely many steps. It can thus be used to check whether a given integer is a [[square number]].\n\nWrite the number in decimal and divide it into pairs of digits starting from the decimal\npoint. The numbers are laid out similar to the long division algorithm and the final square root will appear above the original number.\n\nFor each iteration:\n# Bring down the most significant pair of digits not yet used and append them to any remainder. This is the \'\'current value\'\' referred to in steps 2 and 3.\n# If r denotes the part of the result found so far, determine the greatest digit x that does not make y = x(20r + x) exceed the current value. Place the new digit x on the quotient line.\n# Subtract y from the current value to form a new remainder.\n# If the remainder is zero and there are no more digits to bring down the algorithm has terminated. Otherwise continue with step 1.\n\n\nExample: What is the square root of 152.2756?\n\n ____1__2._3__4_\n | 01 52.27 56 1\n x 01 1*1=1 1\n ____ __\n 00 52 22\n 2x 00 44 22*2=44 2\n _______ ___\n 08 27 243\n 24x 07 29 243*3=729 3\n _______ ____\n 98 56 2464\n 246x 98 56 2464*4=9856 4\n _______\n 00 00 Algorithm terminates: answer is 12.34\n\nAlthough demonstrated here for base 10 numbers, the procedure works for\nany [[numeral system|base]], including [[Binary numeral system|base 2]]. In the description above, \'\'\'20\'\'\' means double\nthe number base used, in the case of binary this would really be\n\'\'\'100\'\'\'. The algorithm is in fact much easier to perform in base 2, as in every step only the two digits 0 and 1 have to be tested. See [[Shifting nth-root algorithm]].\n\n===Pell\'s equation===\n[[Pell\'s equation]] yields a method for finding rational approximations of square roots of integers.\n\n===Finding square roots in the head===\nBased on Pell\'s equation there is a methode to calculate the square root in the head, by simply subtraction of odd numbers.\n\nEx: Square root of 27 is:\n 1) 27-1 = 26\n 2) 26-3 = 23\n 3) 23-5 = 18\n 4) 18-7 = 11\n 5) 11-9 = 2 First number is 5\n\n 2 x 100 = 200 and 5 x 20 + 1 = 101\n 1) 200-101 = 99 Next number is 1\n\n 99 x 100 = 9900 and 51 x 20 + 1 = 1021\n 1) 9900-1021 = 8879\n 2) 8879-1023 = 7856\n 3) 7856-1025 = 6831\n 4) 6831-1027 = 5804\n 5) 5804-1029 = 4775\n 6) 4775-1031 = 3744\n 7) 3744-1033 = 2711\n 8) 2711-1035 = 1676\n 9) 1676-1037 = 639 Next number is 9\n\nThe result gives us 5.19 as the square root of 27\n\n=== Continued fraction methods ===\nQuadratic irrationals, that is numbers involving square roots in the form (\'\'a\'\'+√b)/\'\'c\'\', have periodic [[continued fraction]]s. This makes them easy to calculate recursively given the period. For example, to calculate √2, we make use of the fact that √2-1 = [0;2,2,2,2,2,...], and use the recurrence relation\n: \'\'a\'\'\'\'n+1\'\'=1/(2+a\'\'n\'\') with \'\'a\'\'0=0\nto obtain √2-1 to some specific precision specified through \'\'n\'\' levels of recurrence, and add 1 to the result to obtain √2.\n\n== Square roots of complex numbers ==\n\nTo every non-zero [[complex number]] \'\'z\'\' there exist precisely two numbers \'\'w\'\' such that \'\'w\'\'2 = \'\'z\'\'. The usual definition of √\'\'z\'\' is as follows: if \'\'z\'\' = \'\'r\'\' exp(\'\'i\'\'φ) is represented in polar coordinates with -π < φ ≤ π, then we set √\'\'z\'\' = √\'\'r\'\' exp(\'\'i\'\'φ/2). Thus defined, the square root function is [[holomorphic function|holomorphic]] everywhere except on the non-positive real numbers (where it isn\'t even [[continuous]]). The above Taylor series for √(1+\'\'x\'\') remains valid for complex numbers \'\'x\'\' with |\'\'x\'\'| < 1.\n\nWhen the number is in rectangular form the following formula can be used:\n\n:\\sqrt{x+iy} = \\sqrt{\\frac{\\left|x+iy\\right| + x}{2}} \\pm i \\sqrt{\\frac{\\left|x+iy\\right| - x}{2}}\n\nwhere the sign of the imaginary part of the root is the same as the sign of the imaginary part of the original number.\n\nNote that because of the discontinuous nature of the square root function in the complex plane, the law √(\'\'zw\'\') = √(\'\'z\'\')√(\'\'w\'\') is in general \'\'\'not true\'\'\'. Wrongly assuming this law underlies several faulty \"proofs\", for instance the following one showing that -1 = 1:\n\n:-1 = i \\times i = \\sqrt{-1} \\times \\sqrt{-1} = \\sqrt{-1 \\times -1} = \\sqrt{1} = 1\n\nThe third equality cannot be justified. (See [[invalid proof]].)\n\nHowever the law can only be wrong up to a factor -1, √(\'\'zw\'\') = ±√(\'\'z\'\')√(\'\'w\'\'), is true for either ± as + or as - (but not both at the same time). Note that √(\'\'c\'\'2) = ±\'\'c\'\', therefore √(\'\'a\'\'2\'\'b\'\'2) = ±\'\'ab\'\' and therefore √(\'\'zw\'\') = ±√(\'\'z\'\')√(\'\'w\'\'), using \'\'a\'\' = √(\'\'z\'\') and \'\'b\'\' = √(\'\'w\'\').\n\n== Square roots of matrices and operators ==\n\nIf \'\'A\'\' is a [[positive definite]] matrix or operator, then there exists precisely one positive definite matrix or operator \'\'B\'\' with \'\'B\'\'2 = \'\'A\'\'; we then define √\'\'A\'\' = \'\'B\'\'. \n\nMore generally, to every [[normal operator|normal]] matrix or operator \'\'A\'\' there exist normal operators \'\'B\'\' such that \'\'B\'\'2 = \'\'A\'\'. In general, there are several such operators \'\'B\'\' for every \'\'A\'\' and the square root function cannot be defined for normal operators in a satisfactory manner. Positive definite operators are akin to positive real numbers, and normal operators are akin to complex numbers.\n\n== Square roots of the first 20 positive integers ==\n\n√ 1 = 1
\n√ 2 ≈1.4142135623 7309504880 1688724209 6980785696 7187537694 8073176679 7379907324 78462
\n√ 3 ≈1.7320508075 6887729352 7446341505 8723669428 0525381038 0628055806 9794519330 16909
\n√ 4 = 2
\n√ 5 ≈2.2360679774 9978969640 9173668731 2762354406 1835961152 5724270897 2454105209 25638
\n√ 6 ≈2.4494897427 8317809819 7284074705 8913919659 4748065667 0128432692 5672509603 77457
\n√ 7 ≈2.6457513110 6459059050 1615753639 2604257102 5918308245 0180368334 4592010688 23230
\n√ 8 ≈2.8284271247 4619009760 3377448419 3961571393 4375075389 6146353359 4759814649 56924
\n√ 9 = 3
\n√10 ≈3.1622776601 6837933199 8893544432 7185337195 5513932521 6826857504 8527925944 38639
\n√11 ≈3.3166247903 5539984911 4932736670 6866839270 8854558935 3597058682 1461164846 42609
\n√12 ≈3.4641016151 3775458705 4892683011 7447338856 1050762076 1256111613 9589038660 33818
\n√13 ≈3.6055512754 6398929311 9221267470 4959462512 9657384524 6212710453 0562271669 48293
\n√14 ≈3.7416573867 7394138558 3748732316 5493017560 1980777872 6946303745 4673200351 56307
\n√15 ≈3.8729833462 0741688517 9265399782 3996108329 2170529159 0826587573 7661134830 91937
\n√16 = 4
\n√17 ≈4.1231056256 1766054982 1409855974 0770251471 9922537362 0434398633 5730949543 46338
\n√18 ≈4.2426406871 1928514640 5066172629 0942357090 1562613084 4219530039 2139721974 35386
\n√19 ≈4.3588989435 4067355223 6981983859 6156591370 0392523244 4936890344 1381595573 28203
\n√20 ≈4.4721359549 9957939281 8347337462 5524708812 3671922305 1448541794 4908210418 51276\n\n[[Category:Mathematics]]\n\n[[da:Kvadratrod]]\n[[de:Quadratwurzel]]\n[[en:Square root]]\n[[es:Raíz cuadrada]]\n[[fi:Neliöjuuri]]\n[[fr:Racine carrée]]\n[[is:Ferningsrót]]\n[[it:Radice quadrata]]\n[[ja:平方根]]\n[[nl:Vierkantswortel]]\n[[pl:Pierwiastek kwadratowy]]\n[[pt:Raiz quadrada]]\n[[sv:Kvadratrot]]\n[[zh:平方根]]','warnfile Adding:zh,en,pl,fi,es,is Modifying:pt',42,'Shizhao','20050303143814','',0,0,1,0,0.202872013768,'20050303143814','79949696856185'); INSERT INTO cur VALUES (922,0,'Chebyshev\'s_inequality','[[es:Desigualdad de Chebyshev]]\n[[it:Diseguaglianza di Cebicev]]\n[[pl:Nierówność Czebyszewa]]\n\n\'\'\'Chebyshev\'s inequality\'\'\' (or \'\'\'Tchebysheff\'s inequality\'\'\'), named in honor of [[Pafnuty Chebyshev]], is a result in [[probability theory]] that gives a lower bound for the probability that a value of a [[variabel acak]] with finite [[varian]] lies within a certain distance from the variable\'s [[nilai ekspektasi|mean]]; equivalently, the theorem provides an upper bound for the probability that values lie outside the same distance from the mean. The theorem applies even to non \"bell-shaped\" distributions and puts bounds on how much of the data is or is not \"in the middle\".\n\n\'\'Theorem.\'\' Let \'\'X\'\' be a random variable with mean μ and finite variance σ2. Now, for any [[real number]] \'\'k\'\' > 0,\n\n:P(\\left|X-\\mu\\right|\\geq k\\sigma)\\leq\\frac{1}{k^2}.\n\nOnly the cases \'\'k\'\' > 1 provide useful information.\n\nFor illustration, assume Wikipedia articles are on average 1000 characters long with a [[standard deviation]] of 200 characters. From Chebyshev\'s inequality we can then deduce that at least 75% of Wikipedia articles have a length between 600 and 1400 characters (\'\'k\'\' = 2).\n\nAnother consequence of the theorem is that for any [[probability distribution|distribution]] with mean μ and finite standard deviation σ, at least half of the values lie in the interval (μ − √2 σ, μ + √2 σ).\n\nThe bounds provided by Chebyshev\'s inequality cannot, in general, be improved upon; it is possible to construct a random variable where the Chebyshev bounds are exactly equal to the true probabilities. Typically, however, the theorem will provide rather loose bounds.\n\nThe theorem can be useful despite these loose bounds because it applies to a wide variety of variables, including those that are nothing close to [[normal distribution|normally distributed]], and because the bounds are easy to calculate.\n\nChebyshev\'s inequality is used for proving the [[law of large numbers | weak law of large numbers]].\n\nA one-tailed variant with \'\'k\'\' > 0, is \n\n:P(X-\\mu \\geq k\\sigma)\\leq\\frac{1}{1+k^2}.\n\nA stronger result applicable to unimodal probability distributions is the [[Vysochanskiï-Petunin inequality]].\n\n== Tempo oge ==\n\n*[[Markov\'s inequality]].\n*[[Table of mathematical symbols]]','',13,'Budhi','20041224214528','',0,0,1,0,0.185490936127,'20041224214528','79958775785471'); INSERT INTO cur VALUES (924,0,'Estimating_parameters','Informasi ngeunaan \'\'\'estimating parameters\'\'\' bisa ditempo oge dina;\n\n*[[titik estimasi]]\n*[[Interval estimasi]].\n\n{{disambig}}','',13,'Budhi','20041224044607','',0,0,1,0,0.529257562258,'20041224044607','79958775955392'); INSERT INTO cur VALUES (925,0,'Paraméter','A \'\'\'parameter\'\'\' is a measurement or value on which something else depends.\n\nFor example, a \'\'parametric equaliser\'\' is a tone control circuit that allows the frequency of maximum cut or boost to be set by one control, and the size of the cut or boost by another. These settings, the frequency and level of the peak or trough, are two of the \'\'\'parameters\'\'\' of a frequency response curve, and in a two-control equaliser they completely describe the curve. More elaborate parametric equalisers may allow other parameters to be varied, such as \'\'skew\'\'. These \'\'\'parameters\'\'\' each describe some aspect of the response curve seen as a whole, over all frequencies. By way of contrast, a \'\'graphic equaliser\'\' provides individual level controls for various frequency bands, each of which acts only on that particular frequency band. \n\nIn [[matematik]] there is little difference in meaning between \'\'\'parameter\'\'\' and \'\'\'argument of a function\'\'\'. It is usually a matter of convention (and therefore a historical accident) whether some or all the arguments of a function are called parameters. The best way to explain this is to illustrate it with examples.\n\nIn [[computing]] the parameters passed to a function subroutine are more normally called \'\'arguments\'\'.\n\nIn [[logika]], by some authors (eg Prawitz, \"Natural Deduction\"; Paulson, \"Designing a theorem prover\") the parameters passed to (or operated on by) an \'\'open predicate\'\' are called \'\'parameters\'\'. Parameters locally defined within the predicate are called \'\'variables\'\'. This extra effort pays off when defining substitution (without this distinction special provision has to be made to avoid variable capture). Others (maybe most) just call parameters passed to (or operated on by) an open predicate \'\'variables\'\', and when defining substitution have to distinguish between \'\'free variables\'\' and \'\'bound variables\'\'.\n\n== Analytic geometry ==\n\nIn [[analytic geometry]], curves are often given as the image of some function. The argument of the function is invariably called \"the parameter\". A circle of radius 1 centered at the origin can be specified in more than one form: \n* \"implicit\" form\n:x^2+y^2=1\n* \"parametric\" form\n:(x,y)=(\\cos t,\\sin t)\n:where \'\'t\'\' is the \"parameter\".\nA somewhat more detailed description can be found [[persamaan paramétrik|here]].\n\n== Mathematical analysis ==\n\nIn [[mathematical analysis]], one often considers \"integrals dependent on a parameter\". These are of the form\n:F(t)=\\int_{x_0(t)}^{x_1(t)}f(x,t)\\,dx\nNow, if we performed the substitution \'\'x\'\'=\'\'g\'\'(\'\'y\'\'), it would be called a \"change of variable\".\n\n== Probability theory ==\n\nIn [[probability theory]], one may describe the [[probability distribution|distribution]] of a [[random variable]] as belonging to a \'\'family\'\' of [[probability distribution]]s, distinguished from each other by the values of a finite number of \'\'parameters\'\'. For example, one talks about \"a [[Poisson distribution]] with mean value λ\", or \"a [[normal distribution]] with mean μ and variance σ2\". The latter formulation and notation leaves some ambiguity whether σ or σ2 is the second parameter; the distinction is not always relevant.\n\nIt is possible to use the sequence of [[moment (mathematics)|moments]] (mean, mean square, ...) or [[cumulant]]s (mean, variance, ...) as parameters for a probability distribution.\n\n== Statistics ==\n\nIn [[statistics]], the probability framework above still holds, but attention shifts to [[statistical estimation|estimating]] the parameters of a distribution based on observed data, or [[Hypothesis testing|testing hypotheses]] about them. In [[classical statistics|classical estimation]] these parameters are considered \"fixed but unknown\", but in [[Bayesian probability|Bayesian estimation]] they are random variables with distributions of their own.\n\nStatistics are mathematical characteristics of samples which are used as estimates of parameters, mathematical characteristics of the populations from which the samples are drawn. For example, the \'\'sample mean\'\' (\\overline X) is an estimate of the \'\'mean\'\' parameter (μ) of the population from which the sample was drawn.\n\n== Computer ==\n\nOn the [[computer]], parameters are used to differentiate behavior or pass input data to computer programs or their subprograms. See [[parameter (computer science)|parameter]] for detail.\n\nSee also: [[Parametrization]] (i.e. [[coordinate system]]).','/* Analytic geometry */',3,'Kandar','20040827041141','',0,0,0,0,0.931316439496,'20041231121518','79959172958858'); INSERT INTO cur VALUES (926,0,'Aplikasi','A software \'\'\'application\'\'\' (or \'\'app\'\' for short) is a [[Computer_program|computer program]], or collection of programs, designed to provide useful functionality to [[end_user|end users]]. Typical examples of applications are [[word processors]], [[spreadsheet|spreadsheets]], [[accounting]] programs, and [[media player]]s.\n\nMultiple applications bundled together are sometimes referred to as an \'\'\'application suite\'\'\'. [[Microsoft Office]], which bundles together a word processor, spreadsheet and several other applications, is a typical example.\n\nThe term \'\'application\'\' can be used to distinguish [[application software|this type of program]] from the other main grouping of software called [[system software]] which is software concerned with managing or utilizing aspects of the computer system itself such as [[Operating_system|operating systems]], [[Device_driver|device drivers]], and [[Compiler|compilers]].\n\n\'\'See also:\'\' [[application software]], [[web application]], [[database applications]]\n\n----\nAn \'\'\'application\'\'\' is also a call for a job.\n\n[[Category:Computer terminology]]\n[[Category:Software engineering]]\n[[da:Applikation (datalogi)]] [[de:Anwendungsprogramm]] [[fr:Noms et utilisation de logiciels]] [[ja:アプリケーションソフトウェア]] [[nl:Applicatie]][[simple:Application]]','',13,'Budhi','20040721012206','',0,0,0,1,0.94313772998,'20040721012206','79959278987793'); INSERT INTO cur VALUES (927,0,'Extreme_value_theory','\'\'\'Extreme value theory\'\'\' is a branch of [[statistik]] dealing with the extreme deviations from the median of [[probability distribution]]s. The general theory sets out to assess the type of probability distributions generated by processes. \n\nTwo approaches exist today: \n\n# Most common at this moment is the tail-fitting approach based on the second theorem in extreme value theory (Theorem II Pickands (1975), Balkema and de Haan (1974)).\n# Basic theory approach as described in the book by Burry (reference 2).\nIn general this conforms to the first theorem in extreme value theory (Theorem I Fisher and Tippett (1928), and Gnedenko (1943)).\n\nThe difference between the two theorems is due to the nature of the data generation. For theorem I the data are generated in full range, while in theorem II data is only generated when it surpasses a certain threshold (POT\'s models or Peak Over Threshold).\nThe POT approach has been developed largely in the insurance business, where only losses (pay outs) above a certain threshold are accessible to the insurance company. Strangely this approach is often applied to theorem I cases which poses problems with the basic model assumptions.\n\nExtreme value theory is important for assessing [[risk]] for highly unusual events, such as [[100-year flood]]s.\n\nApplications of extreme value theory include predicting the probability distribution of:\n* extreme [[flood]]s\n* the amounts of large [[insurance]] losses\n* [[equity risk]]s\n* day to day [[market risk]]\n* the size of [[freak wave]]s\n\n==History of extreme value theory==\n\nFounded by the German mathematician, pacifist, and anti-Nazi campaigner [[Emil Gumbel|Emil Julius Gumbel]] who described the [[Gumbel distribution]] in the [[1950s]].\n\n==References==\n\n* Gumbel, E.J. (1958). \'\'Statistics of Extremes\'\'. Columbia University Press.\n* Burry K.V. (1975). \'\'Statistical Methods in Applied Science\'\'. John Wiley & Sons.\n* Pickands, J. (1975). \'\'Statistical inference using extreme order statistics\'\', Annals of Statistics, \'\'\'3\'\'\', 119-131.\n* Balkema, A., and L. de Haan (1974). \'\'Residual life time at great age\'\', Annals of Probability, \'\'\'2\'\'\', 792-804.\n* Fisher, R.A., and L. H. C. Tippett (1928). \'\'Limiting forms of the frequency distribution of the largest and smallest member of a sample\'\', Proc. Cambridge Phil. Soc., \'\'\'24\'\'\', 180-190.\n* Gnedenko, B.V. (1943), \'\'Sur la distribution limite du terme maximum d\'une serie aleatoire\'\', Annals of Mathematics, \'\'\'44\'\'\', 423-453\n\n==See also==\n\n* [[hydrogeology]], [[meteorology]], [[extreme weather]], [[freak wave]]\n\n\n==External links==\n\n* [http://www.approximity.com/papers/evt_wp.pdf Easy non-mathematical introduction]\n* [http://www.cs.chalmers.se/Stat/Research/researchgroups/extreme.html Extreme value theory group at Chalmers University]\n* [http://fenews.com/1999/Issue11/089904.html The Extreme Value Approach to VaR ? An Introduction]\n* [http://www.unige.ch/ses/metri/gilli/evtrm/evtrm.pdf Extreme Value Theory for Tail-Related Risk Measures]\n* [http://citeseer.nj.nec.com/gavin00extreme.html Extreme value theory an empirical analysis of equity risk]\n* http://www.itl.nist.gov/div898/handbook/apr/section1/apr163.htm','',13,'Budhi','20040721013102','',0,0,0,0,0.696442487508,'20040817061153','79959278986897'); INSERT INTO cur VALUES (928,0,'Statistik_bisnis','\'\'\'Statistik bisnis\'\'\' ngarupakeun cabang [[applied statistics]] loba dipake keur ngumpulkeun data salaku hasil tina bisnis atawa lembaga pamarentah. Sipat sumber ieu pengulangan nu angger tina deret data. Hal ieu ngajadikeun [[deret waktu]] penting keur bisnis statistik.\n\nSababaraha teknik [[Marketing]] oge dipake leuwih [[Multivariate statistics]] lanjut dina segmen pasar, manajemen merk sarta teknik posisi produk.','',13,'Budhi','20041004003338','',0,0,0,0,0.471757542096,'20041004003338','79958995996661'); INSERT INTO cur VALUES (929,0,'Statistik_ékonomi','[[it:Statistica economica]] [[nl:Econometrie]] [[sv:Ekonometri]] [[de:Ökonometrie]]\n\n\'\'\'\'\'Econometrics\'\'\'\'\' literally means \'economic measurement\'. It is the branch of [[economics]] that applies [[statistics|statistical methods]] to the [[empirical]] study of economic theories and relationships. It is a combination of [[mathematical economics]], statistics, economic statistics and economic theory. \n\nThe two main purposes of econometrics are to give empirical content to economic theory and also to empirically verify economic theory. For example, econometrics could empirically verify if indeed a given demand curve slopes downward as economic theory would suggest. Empirical content is also given in that a numerical value would be given to this slope, while economic theory alone is usually mute on actual specific values.\n\nAn econometrician often changes qualitative statements into a quantitative mathematical form that lends itself to measurement. These statements can then be empirically proven, disproven, measured, and compared. Econometrics differs from statistics done in other fields since controlled experiments are often impractical, so econometics has to frequently deal with data as is.\n\nArguably the most important tool of econometrics is regression analysis (for an overview of a linear implementation of this framework, see [[linear regression]]).\n\nEconometric analysis can often be divided into [[time-series analysis]] and [[cross-sectional analysis]]. Time-series analysis examines variables over time, such as the effect of interest rates on national expenditure. Cross-sectional analysis studies relationship between different variables at a point in time. For instance, the relationship between income, locality, and personal expenditure. When time-series analysis and cross-sectional analysis are conducted simultaneously on the same [[Statistical sample|sample]], it is called [[panel analysis]]. If the sample is different each time, it is called pooled cross section data.\n\nA simple example of a relationship in econometrics is:\n\n:Personal Expenditure = Propensity to Spend * Income + random error \n\nThis statement asserts that the amount a person spends is dependent on their [[income]] and their willingness to spend [[money]]. If we can observe personal expenditure and income, techniques such as [[Linear regression|regression analysis]] can then be applied to find the value of the coefficients, here just the propensity to spend. The estimated coefficient can then be compared across samples (such as different countries or income brackets) and conclusions made. \n\nThe above example can also be used to illustrate the many difficulties facing the applied econometrician. For instance, do we really know that the above relationship is correct? Perhaps the true relationship between personal expenditure and income is non-linear (that is, curved). Even if we know the correct theory, it is not certain we can meaure personal expenditure and income correctly. For instance, the value of work by e.g. [[homemaker]]s is not recorded although it contributes to income. There are also a variety of statistical pitfalls that potentially lead to incorrect conclusions. Econometrics has dealt extensively with such issues. Often it turns out to be difficult to fully implement the resulting methods in practice.\n\nIn order to classify business and industry, econometricians rely on two main systems: [[SIC]] codes and more recently [[NAICS]] codes.\n\n==People==\n\n[[Nobel Prize]] for [[Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel|Economic Sciences]] recipients in the field of econometrics:\n\n* [[Jan Tinbergen]] and [[Ragnar Frisch]] were awarded in [[1969]] (the first Nobel Price for Economic Sciences) for having developed and applied dynamic models for the analysis of economic processes\n* [[Lawrence Klein]] was awarded in [[1980]] for his computer modeling work in the field.\n* Econometrician [[Daniel McFadden]] was awarded in [[2000]]. He founded the econometrics lab at the [[University of California, Berkeley]].\n* [[Robert Engle]] and [[Clive Granger]] were awarded in [[2003]] for work on analysing economic time series. Engle pioneered the method of [[autoregressive conditional heteroskedasticity]] (ARCH) and Granger the method of [[cointegration]].','',13,'Budhi','20040721020212','',0,0,0,1,0.571864949806,'20050208111611','79959278979787'); INSERT INTO cur VALUES (930,0,'Fisika_statistis','[[sl:statistična fizika]]\n\n\'\'\'Statistical physics\'\'\' is one of the [[fundamental]] [[theory | theories]] of [[physics]], dealing with mathematical description of nature. Statistical physics can describe a wide variety of fields which are treated statistically due to their inherently [[probabilistic]] nature. Examples include problems such as [[nuclear reaction]]s, and topics in the fields of biology, chemistry, neurology and even sociology.\n\nThe term \'\'\'\'\'statistical physics\'\'\'\'\' encompasses [[statistics|statistical]] approaches to [[classical mechanics]] and [[quantum mechanics]]. [[Statistical mechanics]] is then often used as a synonym. When the [[context]] requires a distinction, one uses the terms \'\'classical statistical mechanics\'\' and \'\'quantum statistical mechanics\'\'. \n\nA statistical approach can work well in classical systems when the number of [[degrees of freedom]] (and so the number of variables) is so large that exact solution is not possible, or not really useful. \'\'\'Statistical mechanics\'\'\' can also describe work in [[non-linear dynamics]], [[chaos theory]], thermal physics, [[fluid dynamics]], or [[plasma physics]].\n\nAlthough some problems in statistical physics can be solved analytically using approximations and expansions, most current research utilizes the large processing power of modern computers to simulate or approximate solutions. A common approach to statistical problems is to use a [[Monte Carlo simulation]], to yield insight into the dynamics of a complex system.','',13,'Budhi','20040721020304','',0,0,0,1,0.370372547475,'20040817052311','79959278979695'); INSERT INTO cur VALUES (931,0,'Démografi','\'\'\'Démografi\'\'\' nyaéta élmu ngeunaan [[dinamika populasi]] manusa, nu ngawengku panalungtikan ukuran, struktur, jeung sébaran populasi, sarta kumaha parobahan populasi sajalan jeung nyérélékna waktu ku ayana nu babar, maot, [[migrasi (manusa)|migrasi]], jeung [[ngolotan|nambahna umur]]. Analisis démografis bisa nujul ka masarakat sagemblengna atawa ka golongan nu ditangtukeun ku kriteria kayaning atikan, bangsa, ageman, atawa suku.\n\n==Data jeung métode== \n\nDemography relies on the use of large amounts of data, including [[census]] returns and records of births, marriages and deaths. The earliest modern census was carried out in [[United Kingdom|Britain]] in [[1801]]. See also [[demographic statistics]]. \n\nIn many countries, particularly in the third world, reliable demographic data are still difficult to obtain. For example, during the 1980s the population of [[Nigeria]] was widely estimated to be around 110 million, before it was established to be as little as 89 million (without adjustment for undercounting) in a census carried out in 1991.\n\n==Konsép-konsép penting==\n\nKonsép-konsép nu penting dina démografi di antarana:\n* \'\'\'laju babar kasar\'\'\', jumlah nu babar per saréwu jalma per taun \n* \'\'\'laju kasuburan umum\'\'\', jumlah nu babar per saréwu wanoja umur subur (biasana dianggap antara umur 15-49 taun, atawa nepi ka 44 taun) per taun \n* laju \'\'\'kasuburan spésifik-umur\'\'\', jumlah nu babar per saréwu wanoja nu umurna digolong-golongkeun (biasana umur 15-19, 20-24 jst.) per taun\n* The \'\'\'crude death rate\'\'\', the annual number of deaths per 1000 people. \n* The \'\'\'infant mortality rate\'\'\', the annual number of deaths of children less than 1 year old per thousand live births. \n* The \'\'\'expectation of life\'\'\' (or [[life expectancy]]), the number of years which an individual at a given age can expect to live at present mortality levels. \n* The \'\'\'total fertility rate\'\'\', the number of live births per woman completing her reproductive life, if her childbearing at each age reflected current age-specific fertility rates. \n* The \'\'\'gross reproduction rate\'\'\', the number of daughters who would be born to a woman completing her reproductive life at current age-specific fertility rates. \n* The \'\'\'net reproduction rate\'\'\' is the number of daughters who would be born to a woman according to current age-specific fertility and mortality rates. \n\nNote that the crude death rate as defined above and applied to a whole population can give a misleading impression. For example, the number of deaths per 1000 people can be higher for developed nations than in less-developed countries, despite standards of health being better in developed countries. This is because developed countries have relatively more older people, who are more likely to die in a given year, so that the overall mortality rate can be higher even if the mortality rate at any given age is lower. A more complete picture of mortality is given by a [[Life table|life table]] which summarises mortality separately at each age. A life table is necessary to give a good estimate of life expectancy.\n\n==History==\n\nAmong the earliest contributions to demography were the works of [[Thomas Malthus]]. Malthus concluded that, if unchecked, populations would be subject to [[exponential growth]]. He feared that population growth would tend to outstrip growth in food production, leading to ever increasing famine and poverty (see [[Malthusian catastrophe]]). Later more sophisticated and realistic models were presented by e.g. [[Gompertz]] and [[Pierre_Fran%E7ois_Verhulst|Verhulst]].\n\n==The demographic transition==\n\nContrary to Malthus\' predictions, natural population growth in most developed countries has diminished to close to zero, without being held in check by famine or lack of resources, as people in developed nations have shown a tendency to have fewer children. The fall in population growth has occurred despite large rises in life expectancy in these countries.\n\nSimilar trends are now becoming visible in ever more developing countries, so that far from spiralling out of control, world population growth is expected to slow markedly in the next century, coming to an eventual standstill. The change is likely to be accompanied by major shifts in the proportion of world population in particular regions. \n\nThis pattern of population growth, with slow growth in preindustrial societies, followed by fast growth as the society develops and industrialises, followed by slow growth again as it becomes more affluent, is known as the [[demographic transition]]. \n\nThe term [[demographics]] is often used erroneously for demography, but refers rather to selected population characteristics as used in marketing or opinion research.\n\n==Tumbu kaluar==\n\n* [http://www.prb.org/ The Population Reference Bureau ] has two introduction to demography texts on line. \"Population Handbook\" and \"Population: A Lively Introduction\".\n* [http://gsociology.icaap.org/report/demsum.html Brief review of world basic demographic trends] Review of world changes in population and growth, infant mortality, fertility and age distributions.\n* [http://gsociology.icaap.org/report/socsum.html Brief review of world socio-demographic trends] Review of world changes in urbanization, education and ethnolinguistic fractionalization.\n\n[[de:Demografie]] [[fr:Démographie]] [[nl:Demografie]] [[zh:人口学]][[pt:Demografia]]','/* Konsép-konsép penting */',3,'Kandar','20041218135504','',0,0,0,0,0.778851433088,'20041218135504','79958781864495'); INSERT INTO cur VALUES (932,0,'Multivariate_statistics','\'\'\'Multivariate statistik\'\'\' atawa \'\'\'analisa multivariate statistik\'\'\' dina [[statistik]] ngajelaskeun kumpulan prosedur kaasup [[statistical observation|observation]] jeung [[statistical analysis|analysis]] nu leuwih ti hiji [[statistical variable]] dina sawaktu.\n\nAya sababaraha model, nu gumantung kana tipe analisana nyaeta:\n# [[Canonical correlation analysis]] tries to establish whether or not there are linear relationships among two sets of variables (covariates and response).\n#Regression analysis attempts to determine a linear formula that can describe how some variables respond to changes in others .\n# [[Principal components analysis]] attempts to determine a smaller set of synthetic variables that could explain the original set.\n# Discriminant function or [[canonical variate analysis]] attempt to establish whether a set of variables can be used to distinguish between two or more groups.\n# [[Principal coordinate analysis]] attempts to determine a set of synthetic variables that best preserves the distance relationships between records.\n# [[Linear discriminant analysis]] (LDA) computes a linear predictor from two sets of normally distributed data to allow for classification of new observations.\n# [[Logistic regression]] allows to perform a regression analysis to estimate and test the influence of [[covariate|covariates]] on a binary response.\n# Metoda analisa varian multivariet ([[MANOVA]]) ngalegaan tina metoda [[analisa varian]] keur ngawengku kasus dimana aya leuwih ti hiji variabel sarata variabel terikat teu bisa dikombinasikeun.','',13,'Budhi','20040908000054','',0,0,0,0,0.825287267484,'20040908000054','79959091999945'); INSERT INTO cur VALUES (947,0,'Central_limit_theorem','[[de:Zentraler Grenzwertsatz]] [[it:Teorema del limite centrale]] [[pl:Centralne twierdzenie graniczne]]\n\n\'\'\'Teorema central limit\'\'\' ngarupakeun hasil susunan konvergen-lemah dina [[probability theory]]. Intuitively, they all express the fact that any sum of many [[statistical independence|independent]] identically distributed [[random variable]]s is approximately [[normal distribution|normally distributed]]. These results explain the ubiquity of the normal distribution.\n\nThe most important and famous result is simply called \'\'The Central Limit Theorem\'\'; it is concerned with independent variables with identical distribution whose expected value and variance are finite. \nSeveral generalizations exist which do not require identical distribution but incorporate some condition which guarantees that none of the variables exert a much larger influence than the others. Two such conditions are the \'\'Lindeberg condition\'\' and the \'\'Lyapunov condition\'\'. Other generalizations even allow some \"weak\" dependence of the random variables.\n\nThe reader may find it helpful to consider this [[illustration of the central limit theorem]].\n\n== \"The\" central limit theorem ==\n\nTempo X1,X2,X3,... be a [[sequence]] of random variables which are defined on the same [[probability space]], share the same [[probability distribution]] D and are [[statistical independence|independent]]. Assume that both the [[nilai ekspektasi]] μ and the [[simpangan baku]] σ of D exist and are finite. \n\nConsider the sum :Sn=X1+...+Xn.\nThen the expected value of \'\'S\'\'\'\'n\'\' is \'\'n\'\'μ and its [[simpangan baku]] is σ \'\'n\'\'½. Furthermore, informally speaking, the distribution of Sn approaches the [[normal distribution]] N(\'\'n\'\'μ,σ2\'\'n\'\') as \'\'n\'\' approaches ∞.\n\nIn order to clarify the word \"approaches\" in the last sentence, we standardize \'\'S\'\'\'\'n\'\' by setting \n\n:Z_n = \\frac{S_n - n \\mu}{\\sigma \\sqrt{n}}\n\nThen the distribution of \'\'Z\'\'\'\'n\'\' [[convergence|converges]] towards the [[sebaran normal |standard normal distribution]] N(0,1)\nas \'\'n\'\' approaches ∞ (this is [[convergence in distribution]]). This means: if Φ(\'\'z\'\') is the cumulative distribution function of N(0,1), then for every [[real number]] \'\'z\'\', we have\n\n:\\lim_{n \\to \\infty} \\mbox{Pr}(Z_n \\le z) = \\Phi(z),\nor, equivalently,\n\n\n:\\lim_{n\\rightarrow\\infty}\\mbox{Pr}\\left(\\frac{\\overline{X}_n-\\mu}{\\sigma/\\sqrt{n}}\\leq z\\right)=\\Phi(z)\nwhere\n:\\overline{X}_n=S_n/n=(X_1+\\cdots+X_n)/n\nis the \"sample mean\".\n\n=== Proof of the central limit theorem ===\n\nFor a theorem of such fundamental importance to [[statistics]] and [[applied probability]], the central limit theorem has a remarkably simple proof using [[characteristic function]]s. It is similar to the proof of a (weak) [[law of large numbers#a weaker law and proof|law of large numbers]]. For any [[random variable]], \'\'Y\'\', with zero mean and unit variance (var(\'\'Y\'\') = 1), the characteristic function of \'\'Y\'\' is, by [[Taylor\'s theorem]],\n\n:\\varphi_Y(t) = 1 - {t^2 \\over 2} + o(t^2), \\quad t \\rightarrow 0.\n\nLetting \'\'Y\'\'\'\'i\'\' be (\'\'X\'\'\'\'i\'\' − μ)/σ, the standardised value of \'\'X\'\'\'\'i\'\', it is easy to see that the standardised mean of the observations X1, X2, ..., X\'\'n\'\' is just\n\n:Z_n = \\frac{\\overline{X}_n-\\mu}{\\sigma/\\sqrt{n}} = \\sum_{i=1}^n {Y_i \\over \\sqrt{n}}.\n\nBy simple [[characteristic function#properties|properties]] of characteristic functions, the characteristic function of \'\'Z\'\'\'\'n\'\' is\n\n:\\left[\\varphi_Y\\left({t \\over \\sqrt{n}}\\right)\\right]^n = \\left[ 1 - {t^2 \n\\over 2n} + o\\left({t^2 \\over n}\\right) \\right]^n \\, \\rightarrow \\, e^{-t^2/2}, \\quad n \\rightarrow \\infty.\n\nBut, this limit is just the characteristic function of a standard normal distribution, N(0,1), and the central limit theorem follows from the [[Lévy continuity theorem]], which confirms that the convergence of characteristic functions implies convergence in distribution.\n\n=== Convergence to the limit ===\n\nIf the third central moment E((\'\'X\'\'1 − μ)3) exists and is finite, then the above convergence is [[uniform convergence|uniform]] and the speed of convergence is at least on the order of 1/\'\'n\'\'½ (see [[Berry-Esséen theorem]]).\n\nPictures of a distribution being \"smoothed out\" by summation (showing original distribution and three subseqent convolutions):\n\n[[Image:Central_limit_thm_1.png|240px]]\n[[Image:Central_limit_thm_2.png|240px]]\n[[Image:Central_limit_thm_3.png|240px]]\n[[Image:Central_limit_thm_4.png|240px]]\n\n(See [[Illustration of the central limit theorem]] for further details on these images.)\n\nAn equivalent formulation of this limit theorem starts with \'\'A\'\'\'\'n\'\' = (\'\'X\'\'1 + ... + \'\'X\'\'\'\'n\'\') / \'\'n\'\' which can be interpreted as the mean of a random sample of size \'\'n\'\'. The expected value of \'\'A\'\'\'\'n\'\' is μ and the standard deviation is σ / \'\'n\'\'½. If we normalize \'\'A\'\'\'\'n\'\' by setting \'\'Z\'\'\'\'n\'\' = (\'\'A\'\'\'\'n\'\' - μ) / (σ / \'\'n\'\'½), we obtain the same variable \'\'Z\'\'\'\'n\'\' as above, and it approaches a standard normal distribution.\n\nNote the following apparent \"paradox\": by adding many independent identically distributed \'\'positive\'\' variables, one gets approximately a normal distribution. But for every normally distributed variable, the probability that it is negative is non-zero! How is it possible to get negative numbers from adding only positives? \nThe reason is simple: the theorem applies to terms centered about the mean. Without that standardization, the distribution would, as intuition suggests, escape away to infinity.\n\n===Alternative statements of the theorem===\n\nThe density of the sum of two or more independent variables is the [[convolution]] of their densities (if these densities exist). \nThus the central limit theorem can be interpreted as a statement about the properties of density functions under convolution:\nthe convolution of a number of density functions tends to the normal density as the number of density functions increases without bound,\nunder the conditions stated above.\n\nSince the [[characteristic function]] of a convolution is the product of the characteristic functions of the densities involved, \nthe central limit theorem has yet another restatement:\nthe product of the characteristic functions of a number of density functions tends to the characteristic function of the normal density as the number of density functions increases without bound,\nunder the conditions stated above.\n\nAn equivalent statement can be made about [[Fourier transform]]s, \nsince the characteristic function is essentially a Fourier transform.\n\n== Lyapunov condition ==\n\nLet \'\'X\'\'\'\'n\'\' be a sequence of independent random variables defined on the same probability space. Assume that \'\'X\'\'\'\'n\'\' has finite expected value μ\'\'n\'\' and finite standard deviation σ\'\'n\'\'. We define\n\n:s_n^2 = \\sum_{i = 1}^n \\sigma_i^2\n\nAssume that the third central moments\n\n:r_n^3 = \\mbox{E}\\left({\\left| X_n - \\mu_n \\right|}^3 \\right)\n\nare finite for every \'\'n\'\', and that\n\n:\\lim_{n \\to \\infty} \\frac{r_n}{s_n} = 0\n\n(This is the Lyapunov condition).\nWe again consider the sum Sn=X1+...+Xn. The expected value of \'\'S\'\'\'\'n\'\' is \'\'m\'\'\'\'n\'\' = ∑\'\'i\'\'=1..\'\'n\'\'μ\'\'i\'\' and its standard deviation is \'\'s\'\'\'\'n\'\'. If we normalize \'\'S\'\'\'\'n\'\' by setting \n\n:Z_n = \\frac{S_n - m_n}{s_n}\n\nthen the distribution of \'\'Z\'\'\'\'n\'\' converges towards the standard normal distribution N(0,1) as above.\n\n== Lindeberg condition ==\n\nIn the same setting and with the same notation as above, we can replace the Lyapunov condition with the following weaker one: for every ε > 0\n\n:\n \\lim_{n \\to \\infty} \\sum_{i = 1}^{n} \\mbox{E}\\left(\n \\frac{(X_i - \\mu_i)^2}{s_n^2}\n :\n \\left| X_i - \\mu_i \\right| > \\epsilon s_n\n \\right) = 0\n\n\n(where E( \'\'U\'\' : \'\'V\'\' > \'\'c\'\') denotes the conditional expected value: the expected value of \'\'U\'\' given that \'\'V\'\' > \'\'c\'\'.) Then the distribution of the normalized sum \'\'Z\'\'\'\'n\'\' converges towards the standard normal distribution N(0,1).\n\n== Non-independent case ==\n\nThere are some theorems which treat the case of sums of non-independent variables, for instance the \'\'m-dependent central limit theorem\'\', the \'\'martingale central limit theorem\'\' and the \'\'central limit theorem for mixing processes\'\'.\n\n:\'\'track these down\'\'\n\n== Tumbu kaluar ==\n\n*[http://www.math.csusb.edu/faculty/stanton/m262/central_limit_theorem/clt.html Central Limit Theorem Java]\n\n[[Category:Probability theory]]\n[[Category:Theorems]]','/* External links */',13,'Budhi','20041224031345','',0,0,1,0,0.065651435436,'20041224091813','79958775968654'); INSERT INTO cur VALUES (948,0,'Statistical_independence','Dina [[tiori probabiliti]], to say that two [[event (probability theory)|events]] are \'\'\'independent\'\'\' intuitively means that knowing whether or not one of them occurs makes it neither more probable nor less probable that the other occurs. For example, the event of getting a \"1\" when a die is thrown and the event of getting a \"1\" the second time it is thrown are independent.\n\nHal nu sarupa, waktu urang nyebutkeun dua [[variabel acak]] bebas, we intuitively mean that knowing something about the value of one of them does not yield any information about the value of the other. For example, the number appearing on the upward face of a die the first time it is thrown and that appearing the second time are independent.\n\n== Kajadian bebas ==\n\nIf two events \'\'A\'\' and \'\'B\'\' are [[independent]], then the [[conditional probability]] of \'\'A\'\' given \'\'B\'\' is the same as the \"unconditional\" (or \"marginal\") probability of \'\'A\'\', i.e.,\n\n:P(A\\mid B)=P(A).\n\nThere are at least two reasons why this statement is not taken to be the definition of independence: (1) the two events \'\'A\'\' and \'\'B\'\' do not play symmetrical roles in this statement, and (2) problems arise with this statement when events of probability 0 are involved.\n\nWhen one recalls that the conditional probability P(\'\'A\'\' | \'\'B\'\') is given by\n\n:P(A\\mid B)={P(A \\cap B) \\over P(B)},\n\none sees that the statement above is equivalent to\n\n:P(A \\cap B)=P(A)P(B).\n\nHere \'\'A\'\' ∩ \'\'B\'\' is the [[intersection (set theory)|intersection]] of \'\'A\'\' and \'\'B\'\', i.e., it is the event that both events \'\'A\'\' and \'\'B\'\' occur. Thus we could say:\n\nThus the standard definition says:\n\n:Two events \'\'A\'\' and \'\'B\'\' are \'\'\'independent\'\'\' [[iff]] P(\'\'A\'\' ∩ \'\'B\'\')=P(\'\'A\'\')P(\'\'B\'\').\n\nMore generally, and collection of events -- possibly more than just two of them -- are \'\'\'mutually independent\'\'\' precisely if for any finite subset \'\'A\'\'1, ..., \'\'A\'\'\'\'n\'\' of the collection we have\n\n:P(A_1 \\cap \\cdots \\cap A_n)=P(A_1)\\,\\cdots\\,P(A_n).\n\nThis is called the \'\'multiplication rule\'\' for independent events.\n\nIf any two of a collection of random variables are independent, they may nonetheless fail to be mutually independent; this is called [[pairwise independence]].\n\n== Independent random variables ==\n\nTwo random variables \'\'X\'\' and \'\'Y\'\' are independent iff for any numbers \'\'a\'\' and \'\'b\'\' the events [\'\'X\'\' ≤ \'\'a\'\'] and [\'\'Y\'\' ∈ \'\'b\'\'] are independent events as defined above. Similarly an arbitrary collection of random variables -- possible more than just two of them -- is independent precisely if for any finite collection \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' and any finite set of numbers \'\'a\'\'1, ..., \'\'a\'\'\'\'n\'\', the events [\'\'X\'\'1 ≤ \'\'a\'\'1], ..., [\'\'X\'\'\'\'n\'\' ≤ \'\'a\'\'\'\'n\'\'] are independent events as defined above.\n\nThe measure-theoretically inclined may prefer to substitute events [\'\'X\'\' ∈ \'\'A\'\'] for events [\'\'X\'\' ≤ \'\'a\'\'] in the above definition, where \'\'A\'\' is any [[Borel algebra|Borel set]]. That definition is exactly equivalant to the one above when the values of the random variables are [[real number]]s. It has the advantage of working also for complex-valued random variables or for random variables taking values in any [[topological space]].\n\nLamun \'\'X\'\' sarta \'\'Y\'\' bebas, mangka [[nilai ekspektasi|operator ekspektasi]] \'\'E\'\' mibanda sipat nu hade \n\n:E[\'\'X\'\'· \'\'Y\'\'] = E[\'\'X\'\'] · E[\'\'Y\'\']\n\nsarta keur [[varian]] mibanda\n\n:var(\'\'X\'\' + \'\'Y\'\') = var(\'\'X\'\') + var(\'\'Y\'\').\n\nLamun \'\'X\'\' jeung \'\'Y\'\' bebas, [[kovarian]] cov(\'\'X\'\',\'\'Y\'\') sarua jeung nol; dina hal sejen mibanda\n\n:var(\'\'X\'\' + \'\'Y\'\') = var(\'\'X\'\') + var(\'\'Y\'\') + 2 cov(\'\'X\'\', \'\'Y\'\').\n\n(\'\'Pernyataan\'\' sabalikna yen lamun dua variabel bebas mangka kovarian-na sarua jeung nol ngarupakeun hal nu teu bener. Tempo [[uncorrelated|taya hubungan]].)\n\nFurthermore, if \'\'X\'\' and \'\'Y\'\' are independent and have [[probability density function|probability densities]] \'\'f\'\'\'\'X\'\'(\'\'x\'\') and \'\'f\'\'\'\'Y\'\'(\'\'y\'\'), then the combined random variable (\'\'X\'\',\'\'Y\'\') has a joint density\n\n:\'\'f\'\'\'\'XY\'\'(\'\'x\'\',\'\'y\'\') d\'\'x\'\' d\'\'y\'\' = \'\'f\'\'\'\'X\'\'(\'\'x\'\') \'\'f\'\'\'\'Y\'\'(\'\'y\'\') d\'\'x\'\' d\'\'y\'\'.\n\n== Conditionally independent random variables ==\n\nWe define random variables \'\'X\'\' and \'\'Y\'\' to be \'\'[[conditional independence|conditionally independent]] given\'\' random variable \'\'Z\'\' if\n\n: P[(\'\'X\'\' in \'\'A\'\') & (\'\'Y\'\' in \'\'B\'\') | \'\'Z\'\' in \'\'C\'\'] = P[\'\'X\'\' in \'\'A\'\' | \'\'Z\'\' in \'\'C\'\'] · P[\'\'Y\'\' in \'\'B\'\' | \'\'Z\'\' in \'\'C\'\'] \nfor any Borel subsets \'\'A\'\', \'\'B\'\' and \'\'C\'\' of the real numbers.\n\nIf \'\'X\'\' and \'\'Y\'\' are conditionally independent given \'\'Z\'\', then\n: P[(\'\'X\'\' in \'\'A\'\') | (\'\'Y\'\' in \'\'B\'\') & (\'\'Z\'\' in \'\'C\'\')] \n:= P[(\'\'X\'\' in \'\'A\'\') | (\'\'Z\'\' in \'\'C\'\')]\nfor any Borel subsets \'\'A\'\', \'\'B\'\' and \'\'C\'\' of the real numbers. That is, given \'\'Z\'\', the value of \'\'Y\'\' does not add any additional information about the value of \'\'X\'\'.\n\nIndependence can be seen as a special kind of conditional independence, since probability can be seen as a kind of conditional probability given no events.\n\n[[it:Indipendenza stocastica]]','',13,'Budhi','20041224215001','',0,0,1,0,0.844974127526,'20041231123527','79958775784998'); INSERT INTO cur VALUES (949,0,'Pitulung:_Eusi','----\n\'\'Bagian ti Séri [[Wikipedia:Community Information Directory|Informasi Komunitas]]\'\'\n----\nWikipédia ngarupakeun hiji énsiklopédi bébas nu disusun sabilulungan ku nu maracana. Artikel ieu dimaksudkeun salaku tungtunan sarta sagala rupana ngeunaan maca, nulis, jeung kumaha cara ilubiung di ieu situs.\n(Kumargi teu acan lengkep, kanggo langkung paos mangga buka [http://en.wikipedia.org/wiki/Help:Contents lambaran pitulung dina vérsi Inggris])\n\n== Ngeunaan Wikipédia ==\n\n* [[Wikipédia:Ngeunaan|Ngeunaan Wikipédia]]\n* [[Wikipédia:Wilujeng sumping|Wilujeng sumping, baraya anyar!]]\n* [[Wikipédia:NLD|Nu loba ditanyakeun, NLD]]\n\n== Kumaha cara migawéna? ==\n\'\'Tempo ogé: [[Wikipédia:CARA|Cara Wikipédia]]\'\'.\n\n* Cara [[Wikipédia:ngalanglang|ngalanglang Wikipédia]]\n* Cara [[Wikipédia:Néangan|néang artikel]]\n* [[Wikipédia:Cara ngédit kaca]]. Anjeun bisa nyobaan ngédit kaca di [[wikipédia:Kotrétan|kotrétan]].\n* [[Wikipédia:Cara ngamimitian kaca|Cara ngamimitian kaca]]\n* Cara [[Wikipédia:Kaca omongan|maké kaca Omongan]]\n* Cara [[Wikipédia:Kawijakan migunakeun gambar|ngasupkeun gambar na kaca]]\n* Cara [[Wikipédia:Parobahan anyar|maké kaca \'\'Parobahan Anyar\'\']]\n* Cara [[Wikipédia:Parobahan nu patali|maké kaca \'\'Parobahan nu Patali\'\']]\n* Cara [[Wikipédia:Tombol Jung|maké tombol \'\'Jung\'\']]\n* [[Wikipédia:Cara log in|Cara log in]]\n* Cara [[Wikipédia:Pitulung préferénsi pamaké|ngatur préferénsi]]\n* [[Wikipédia:Cara ngarobah ngaran (mindahkeun) kaca|]]\n* Cara [[Wikipédia:redirect|maké kaca redirect]]\n* [[Wikipédia:Cara malikkeun kaca ka vérsi saméméhna|Cara malikkeun kaca ka vérsi saméméhna]]\n* Cara [[Wikipédia:Disambiguation|nyieun kaca-kaca keur jejer-jejer nu mibanda sababaraha harti]]\n* Cara [[Wikipédia:Tumbu antarbasa|numbukeun artikel ka Wikipédia dina basa séjén]]\n* Cara [[Wikipédia:Kawijakan ngahapus|ngahapus kaca]]\n* Cara [[Wikipédia:TeX markup|ngédit rumus matematik]]\n* [[Wikipédia:Cara ngédit artikel nu panjang pisan sahingga teu bisa diédit ku anjeun|Cara ngédit artikel nu panjang pisan sahingga teu bisa diédit ku anjeun]]\n* Cara [[Wikipédia:Graphics tutorials|ngahasilkeun grafik keur jero kaca]]\n* Cara [[Wikipédia:Boilerplate text|nambahkeun teks \'\'boilerplate\'\' keur nu maraca]]\n* Cara [[Wikipédia:Contact us|contact us]]\n* Cara [[Wikipédia:Browser_notes#Textarea_tools|ngédit maké éditor éksternal]]\n* Cara [[Wikipédia:How to use tables|maké tabel]], atawa [http://meta.wikipedia.org/wiki/MediaWiki_User%27s_Guide:_Using_tables]\n* [[Wikipédia:Cara numbukeun ka proyek nu sarupa|Cara numbukeun ka proyek nu sarupa]]\n\n== Wawar jeung bahan pikeun bobotoh ==\n\n* [[Wikipedia:Policies and guidelines|Kawijakan jeung Tungtunan pikeun bobotoh]]\n* [[Wikipedia:Glossary|Glosarium istilah-istilah ilahar Wikipédia]]\n* [[Wikipedia:How to write a great article|Cara nulis artikel nu rongkah]]\n* [[Wikipedia:Public domain resources|Bahan-bahan domain umum]]\n* [[Wikipedia:Manual of Style|Tungtunan gaya]]\n* [[Wikipedia:WikiProject|ProyekWiki]], tungtunan nulis jeung gayana keur widang nu spésifik.\n* [[Wikipedia:Utilities|Wikipedia utilities]], tempat ngumpulna tumbu ka kaca-kaca nu mangpaat keur \"baranggawé\" di Wikipédia.\n\n==Panglawungan==\n* [[Wikipedia:Contact us|Contact us]]\n* [[Wikipédia: Padungdengan| Padungdengan]], forum keur nanyakeun masalah nu teu kajawab di dieu atawa di [[Wikipédia:NLD|NLD]].\n* [[Wikipedia:Reference desk|Reference desk]], ménta artikel atawa béja. Tempo ogé [[artikel nu kungsi dipénta]].\n* [[Wikipedia:Mailing lists|Wikipédia mailing lists]]\n* [[Wikipedia:IRC channels|Ngobrol jeung user séjén di IRC]]\n* [[Wikipedia:Bug reports|Bug reports and feature requests]]\n* [[Wikipedia:Wikipedians|Wikipédiawan]]\n* [http://meta.wikipedia.com/ Meta Wikipedia], a site that works alongside the main Wikipedia project. Here you can post essays and discussions about topics related to Wikipedia.\n* [[Wikipedia:Contingency Page For When The Main Wikipedia Server Is Down|Contingency page for when the main Wikipedia server is down]] \n\n[[ar:ويكيبيديا:مساعدة]] [[cy:Wicipedia:Help]] [[da:Wikipedia:Hjælp]] [[de:Wikipedia:Hilfe]] [[el:Wikipedia:Help]] [[en:Wikipedia:Help]] [[eo:Vikipedio:Helpo]] [[es:Wikipedia:Ayuda]] [[hi:विकिपीडिया:सहायता]] [[fr:Wikipédia:Aide]] [[he:ויקיפדיה:עזרה]]\n[[hi:विकिपीडिया:सहायता]] [[ja:Wikipedia:ヘルプ]] [[no:Wikipedia:Hjelp]] [[pl:Wikipedia:Pomoc]] [[simple:Wikipedia:Help]]\n[[sr:%D0%92%D0%B8%D0%BA%D0%B8%D0%BF%D0%B5%D0%B4%D0%B8%D1%98%D0%B0:%D0%9F%D0%BE%D0%BC%D0%BE%D1%9B]] [[sv:Wikipedia:Hjälp]] [[vi:Wikipedia:Tr%E1%BB%A3 gi%C3%BAp]] [[zh:Wikipedia:%E5%B8%AE%E5%8A%A9]]','/* Ngeunaan Wikipédia */',3,'Kandar','20050215054251','',0,0,1,0,0.17352958637,'20050215054251','79949784945748'); INSERT INTO cur VALUES (951,6,'Anatomi_otot.jpg','Gambar ieu ngarupakeun salinan ti gambar [http://en.wikipedia.org/wiki/Image:ENC_plate_1-143_750px.jpeg Wikipédia versi Inggris].','',3,'Kandar','20040721083830','',0,0,0,0,0.154262400375924,'20041029095009','79959278916169'); INSERT INTO cur VALUES (952,4,'Upload_log','','uploaded \"Abu_Abdullah_Muhammad_bin_Musa_al-Khwarizmi.png\": Ti Wikipedia English',13,'Budhi','20040901061555','sysop',0,0,0,0,0.866349166134698,'20040901061555','79959098938444'); INSERT INTO cur VALUES (953,0,'Statistik_terapan','\'\'\'Statistik terapan\'\'\' migunakeun [[statistik]] jeung [[tiori statistik]] dina kaayaan nu sabenerna.\n\nSing saha bae anu ngarasa \"komit\" kana observasi empiris hartina aya kanyaho umum bisa ngagunakeun statistik salaku alat panalungtikan. Hal ieu kaasup [[élmu]] tapi teu kaasup [[sajarah]] jeung [[seni]]. Contona, [[ékonométrik]] loba ngagunakeun statistik terapan keur \"mempelajari\" [[ékonomi]].\n\nDi satiap widang, diperlukan \"observasi\", potensial \"rekonstruksi\" keur ngurangan kasalahan dina observasi jeung rencana panunglutikan keur ngontrol [[observational error]].\n\n== Tumbu kaluar ==\n* [http://mbhs.edu/~steind00/ Some applets about applied statistics]\n* [http://gsociology.icaap.org/methods/statontheweb.html Parabot statistik bébas di Internét]\n\n\n{{pondok}}','',3,'Kandar','20041122082542','',0,0,0,0,0.376561272599,'20050303211247','79958877917457'); INSERT INTO cur VALUES (954,0,'Sajarah','\'\'\'\'\'Sajarah\'\'\'\'\' geus ilahar digunakeun salaku watesan umum keur béja ngeunaan jaman [[baheula]], saperti dina \"sajarah géologis Bumi\". Lamun dilarapkeun salaku hiji widang ulikan, \'\'sajarah\'\' hartina \'\'\'sajarah manusa\'\'\', nyéta ingetan/kajadian kahirupan sosial manusa baheula nu karékam.\n\nIstilah \'\'sajarah\'\' asalna tina basa Yunani \'\'historia,\'\' \"an account of one\'s inquiries,\" nu sacara [[étimologi]]s sarua jeung kecap Inggris \'\'\'story\'\'\'. Sababaraha sarjana féminis malah maké istilah \'\'herstory\'\' pikeun kecap \'\'history\'\'.\n\nSajarawan migunakeun sabararaha rupa sumber, kaasup tulisan atawa rekaman cetakan, wawancara ([[oral history]]), jeung [[arkéologi]]. Different approaches may be more common in some periods than others, and the study of history has its fads and fashions (see [[historiography]] and the [[history of history]]). The events that occurred prior to human records are known as [[prehistory]].\n\n[[Knowledge]] of history is often said to encompass both knowledge of past events and [[historical thinking]] skills. \n\n\'\'See also\'\': [[History of the world]]\n\n==Classifications==\n\nA very large amount of historical information is available in [[Wikipedia]], and several different ways of classifying it are given below.\n\n
\n\'\'\'History classified by location\'\'\'\n\n* [[History of Africa|Africa]]\n* [[History of the Americas|Americas]]\n* [[History of Asia|Asia]]\n* [[History of Europe|Europe]]\n* [[History of Oceania|Oceania]]\n* [[History of Antarctica|Antarctica]]\n \n\n\'\'\'History classified by date\'\'\':\n\n* [[Centuries]]\n* [[Decades]]\n* [[The 20th century in review|Century in review]]\n* [[Periodization]]\n* [[List of time periods|List of named time periods]]\n* [[List of timelines]]\n
\n\n===Academic classification===\n\n* [[Prehistory]]\n* [[Ancient history]]\n* [[Modern history]], including [[early modern history]]\n* [[Pre-Columbian]] history of the Americas \'\'also see [[Mesoamerica]]\'\'\n* [[Middle Ages|Medieval European history]]\n* [[History of Europe]]\n* [[History of Africa|African history]]\n* [[History of Latin America|Latin American history]]\n* [[History of Asia]]\n* [[History of the Middle East]]\n* [[History of Australasia]] (Australia, New Guinea, Micronesia, Melanesia, Polynesia)\n* [[History of Islam|Islamic history]]\n* [[History of Christianity]]\n* [[Jewish history]]\n* [[History of medicine]]\n* [[History of science and technology]]\n* [[Intellectual history]]\n\n===Miscellaneous classifications===\n(\'\'Not necessarily part of academic history studies\'\')\n\n\n* [[Cultural movement]]s\n* [[Diaspora studies]]\n* [[Economic history]]\n* [[History of art]]\n* [[History of cinema]]\n* [[History of economic thought]]\n* [[History of ideas]]\n* [[Biography|History of individuals]] (biography)\n* [[History of literature]]\n* [[History of mathematics]]\n* [[History of mental illness]]\n* [[History of philosophy]]\n* [[History of physics]]\n* [[History of present-day nations and states]]\n* [[History of religions]]\n* [[History of theater]]\n* [[Historiography]]\n* [[Extinct_countries,_empires,_etc.|History of extinct nations and states]]\n* [[Legal history]]\n* [[Microhistory]]\n* [[Military history]]\n* [[Philosophy of history]]\n* [[Psychohistory]]\n* [[History of the Pacific Islands]]\n\n\n=== Ideological classifications ===\nAlthough certain amount of bias in history studies is inescapable, national bias being probably the most important, history can also be studied from a narrow [[ideology|ideological]] perspective, perhaps one that the practitioners feel is usually ignored. For example:\n\n* [[Marxist history]];\n* [[Feminist history]] (also called \'\'herstory\'\');\n\nA form of historical speculation known commonly as [[virtual history]] (also called \"counterfactual history\") been adopted by some historians as a means of assessing and exploring the possible outcomes if certain events had not occurred or had occurred in a different way to that which they did. This is somewhat similar to the [[alternative history]] genre in fiction.\n\nYou may also want to see [[dubious historical resources]] and [[historical myths]] for a list of false beliefs and histories which were once or are now popular and widespread, but which are proven to be false or dubious.\n\n\'\'Guidelines for history on Wikipedia can be found at [[Wikipedia:History]].\'\'\n\n==Tempo ogé==\n*[[Arkéologi]]\n*[[Évolusi Homo sapiens]]\n*[[Parobahan sosial]]\n*[[Historian]]\n*[[List of historians]]\n*[[List of historians by area of study]]\n*[[List of historic travellers]]\n*[[Futurologi]]\n*[[Psychohistory]]\n*[[Pseudohistory]] for more about uncritical history.\n*[[History painter]]\n\n==Tumbu kaluar==\n* [http://www.younghistorians.com/ A history resource for kids]\n*An attempt at [[NPOV]] history with a \"Chronology of Events in History, Mythology, and Folklore\": http://www.b17.com/family/lwp/frameset/frameset.html\n*\"Timelines of History,\" A collection of timelines organized by time, location and subject matter: http://timelines.ws\n* [http://www.state.gov/r/pa/ei/bgn/ U.S. State Department Background Notes]\n* [http://www.fordham.edu/halsall/ Internet History Sourcebooks] Collections of public domain and copy-permitted historical texts presented cleanly (without advertising or excessive layout) for educational use.\n* [http://world-history-blog.blogspot.com World History Blog]\n* [http://www.simaqianstudio.com History Forum Simaqianstudio]\n\n[[Category:Sajarah]]\n\n[[af:Geskiedenis]] [[ar:تاريخ]] [[az:Tarix]] [[bg:История]] [[ca:Història]] [[cs:Dějepis]] [[cy:Hanes]] [[da:Historie]] [[de:Geschichte]] [[el:Ιστορία]] [[en:History]] [[es:Historia]] [[eo:Historio]] [[et:Ajalugu]] [[fr:Histoire]] [[fy:Skiednis]] [[ko:역사]] [[hr:Povijest]] [[it:Storia]] [[ia:Historia]] [[sw:Historia]] [[la:Historia]] [[lb:Geschicht]] [[lv:Vesture]] [[nl:Geschiedenis]] [[ja:歴史]] [[no:Historie]] [[pl:Historia]] [[pt:História]] [[ro:Istorie]] [[ru:История]] [[simple:History]] [[sl:Zgodovina]]\n[[sr:Историја]] [[sv:Historia]] [[tr:Tarih]]\n[[ur:%D8%AA%D8%A7%D8%B1%D9%8A%D8%AE]] [[zh-cn:历史]] [[zh-tw:歷史]]','',13,'Budhi','20040901071210','',0,0,0,0,0.923842463141,'20041005085201','79959098928789'); INSERT INTO cur VALUES (955,0,'Specialized_terminology','#REDIRECT [[technical terminology]]','',13,'Budhi','20040721222220','',0,1,0,1,0.715417303944,'20040721222220','79959278777779'); INSERT INTO cur VALUES (956,0,'Statistik_psikologis','\"Panggunaan\" [[statistik]] keur [[psychology]]. Sasabaraha widang anu umum dipake nyaeta:\n#[[psychometrics]]\n#[[learning theory (education)|learning theory]]\n#[[perception]]\n#[[human development]]\n#[[abnormal psychology]]\n\n:[[biostatistics]] -- [[psychology]]','',13,'Budhi','20040721222438','',0,0,0,1,0.106821135202,'20041226002643','79959278777561'); INSERT INTO cur VALUES (957,0,'Statistik_sosial','\'\'\'Statistik social\'\'\' nyaeta pamakean sistim ukuran [[statistik]] keur nalungtik paripolah [[manusa]] dina lingkungan [[social|sosial]]. Ieu bisa dipikanyaho ku cara [[poll|jajal pamanggih]] ti sabagian grup masarakat, evaluasi sabagian data ngeunaan grup masarakat, atawa ku panalungtikan jeung analisa statistik susunan data nu pakait jeung masarakat sarta paripolahna.\n\nBiasan, ahli sosial mateakeun dina [[Program evaluation|evaluasi]] kualitas [[service|palayanan]] sabagian grup organisasi, dina analisa paripolah grup masarakat dina lingkunganna, atawa dina nangtukeun naon nu butuh jeung kahayang masarakat ngaliwatan [[Sampling|sampling]] statistik.','',13,'Budhi','20040906043754','',0,0,0,0,0.506257483506,'20040906043754','79959093956245'); INSERT INTO cur VALUES (958,0,'Ngarencanakeun_panalungtikan_statistik','Loba ilmuwan nu ngamimitian panalungtikan ku patarosan ngeunaan dunya tempat urang hirup. Keur ahli statistik, patarosan ieu bisa di-klasifikasi-keun kana sababaraha hal. \n\n#Urang mimitian ku hal ngeunaan \'\'Unit\'\' tunggal, saperti organisma biologi, hasil ti pabrik, a plot of ground, hiji blok kota jeung \'\'hal\'\' sejenna anu ku urang hayang dipikharti. Dina pangajaran ieu, urang bisa mokuskeun kana hal anu sifatna \'\'dinamis\'\' tina Unit; kumaha \"variasi\" dina waktu ? Naha bisa nga-identifikasi aspek nu ngontrol ka hal sejenna ? (Tingali [[research subject]].)\n#Kadangkala, urang mikaresep \'\'Unit\'\' anu mungkin sabenerna alat, that is, we are interested in the Unit because of a \'\'population\'\' to which it belongs or an \'\'environment\'\' in which it resides. Our desire to describe a population may be satisfied by a statistical report on a \'\'sample\'\' from that population. The methodology is to select a sample and observe just the Units which are selected and then to summarize our results and interpret their meaning for the population. When we deliberately manipulate something in the process of observation, we call it an \'\'experiment\'\'. When we attempt to observe the Units without affecting them, we call it a \'\'survey\'\'.\n#Kadangkala, urang hayang ngarti kana \'\'internal workings\'\' Unit saperti nu katingal dina komponenna sarta kumaha pakuat pakaitna hiji jeung nu sejenenna. [[Physiology]] salah sahiji conto widang nu kaasup kana tipe ieu.\n\nIn much research, we use all three modes at different stages. A useful synthesis of this kind of thinking was provided by [[Ludwig von Bertalanffy]].\n\nIn every type of research, we must be concerned with managing the [[observational error]] that is inherent in all empirical research. We can increase the precision of our research by \n#using a more precise instrument (eg., a more powerful telescope)\n#increasing the number of observations so the \'\'constant\'\' we try to measure stands out better against the \'\'noise\'\'.\n#changing the design of our research. This last approach can become very technical, so we will postpone its discussion until [[optimum experimental design]].\n\nSee also: [[statistik]] -- [[statistical regularity]] -- [[model statistik]] -- [[summarizing statistical data]] -- [[interpreting statistical data]] --[[desain percobaan]] -- [[survey sampling]]\n\n\n[[en:Planning statistical research]]','',3,'Kandar','20041229073123','',0,0,0,0,0.922955191193,'20041229073123','79958770926876'); INSERT INTO cur VALUES (959,0,'Kémometrik','[[nl:Chemometrie]]\n\'\'\'Chemometrics\'\'\' is the application of mathematical or statistical methods to chemical data.\nThe International Chemometrics Society (ICS) offers the following definition:\n\nChemometrics is the science of relating measurements made on a chemical system or process to the state of the system via application of mathematical or statistical methods.\n\nChemometric research spans a wide area of different methods which can be applied in chemistry. There are techniques for collecting good data (optimization of experimental parameters, [[desain percobaan]], [[kalibrasi]], [[signal processing]]) and for getting information from these data ([[statistics]], [[pattern recognition]], [[model]]ing, structure-property-relationship estimations).\n\nChemometrics tries to build a bridge between the methods and their application in chemistry.\n\n==See Also==\n*[[QSPR]]\n\n==External links==\n*[http://www.disat.unimib.it/chm/Links%20Chemometrics.htm Link collection]','',13,'Budhi','20041229225811','',0,0,1,0,0.162785362062,'20041229225811','79958770774188'); INSERT INTO cur VALUES (960,0,'Statistical_process_control','\'\'\'Statistical Process Control\'\'\', or \'\'\'SPC\'\'\' is a method for achieving [[quality control]] in manufacturing processes. It was pioneered by [[Walter A. Shewhart]] and taken up by [[W. Edwards Deming]] with significant effect by the [[United States|Americans]] during the [[World War II]] to improve aircraft production. Deming was also instrumental in introducing SPC techniques into [[Japan]]ese industry after that war.\n\nThe technique hinges on the observation that any manufacturing process is subject to seemingly random variations, which are said to have \'\'common causes\'\', and non-random variations, which are said to have \'\'special causes\'\'. A common cause might be air movement in the manufacturing environment, which causes variations that are outside the control of manufacturing operatives. A special cause might be the fact that the operative has a hang-over. Management can usually determine special causes for manufacturing defects by consulting the workforce, but dealing with common causes is a management responsibility.\n\nSPC relies on measuring variation in manufacturing output and setting \'\'control limits\'\' based on observations of variations arising solely from common causes. A process that is \"in control\" is expected to generate output that is within the control limits. If the process produces an \"out of control\" point, one would not necessarily assume the process had moved to an \"out of control\" state but would try to locate the special cause(s) for this condition. Only if special causes could not be found would an assumption be made that there might be new common causes to be identified. One aspect of process quality improvement is achieved as these common causes are found and corrected - special causes have no bearing on the overall quality improvement process.\n\nThe main quality improvement process consists of the intentional varying the production process to achieve a smaller range of control limits (Tempo, keur conto, [[desain percobaan]]). It has been shown that manufacturing processes can achieve control limits which are a tenth of the specified manufacturing [[tolerance#Tolerance in Engineering|tolerance]]. Such a process can achieve zero defects - because even articles that are outside the control limits due special causes are still within the specified tolerances. The reduction in waste and inspection resources can make processes subject to SPC far more efficient, and the predictablility implied by processes that are in control allows further savings to be made by adopting [[just in time]] inventory control.\n\nProcesses may have outputs that can be measured as \'\'variables\'\' or as \'\'attributes\'\'. Variables are characteristics of a product that can be measured on a continuous scale. An example of a variable would be the length or width of a product or part. An attribute is an aspect or characteristic of a product that cannot be put on a linear scale. For example, a light bulb will either light or fail to light. \"Good/bad\" is an attribute, as is the \'\'number\'\' of defects.\n\nThere are several types of commonly used process control charts. Among them are X-Bar, R Chart; P Chart; NP Chart; C Chart; and U Chart. Each chart has a specific area of application.\n\nSee also:\n*[[Total Quality Management|TQM]]\n\n\n{{pondok}}','',13,'Budhi','20041224104156','',0,0,1,0,0.351063679602,'20050303211247','79958775895843'); INSERT INTO cur VALUES (961,0,'Daptar_asosiasi_statistis_akademik','==List of associations and societies==\n*[[American Statistical Association]] \n*Belgian Statistical Society \n*Danish Society For Theoretical Statistics \n*Finnish Statistical Society \n*French Statistical Society \n*German Statistical Society \n*Hong Kong Statistical Society \n*[[Indian Statistical Institute]] \n*Institute of Mathematical Statistics \n*International Association for Statistical Education \n*International Biometric Society \n*International Chinese Statistical Association \n*International Environmetrics Society \n*International Society For Bayesian Analysis \n*International Society For Clinical Biostatistics \n*International Statistical Institute \n*Irish Statistical Association \n*Italian Statistical Society \n*Japanese Statistical Society \n*Mexican Statistical Association \n*Netherlands Society For Statistics And Operational Research \n*New Zealand Statistical Association \n*[[Royal Statistical Society]] (RSS) \n*South African Statistical Association \n*Statisticians In The Pharmaceutical Industry (PSI) \n*Statistical Society of Australia Inc \n*Statistical Society of Canada \n*Swedish Statistical Society\n\n==Tempo oge==\n*[[Statistik]]\n*[[List of statistical topics]]\n*[[List of national and international statistical services]]\n\n==External link==\n*[http://www.rss.org.uk/links/ Royal Statistical Society links]','',13,'Budhi','20040721223705','',0,0,0,1,0.244799329082,'20040721223705','79959278776294'); INSERT INTO cur VALUES (962,0,'Daptar_layanan_statistis_international','== National statistical services ==\n*[[Australia]]: [[Australian Bureau of Statistics]]\n*[[Brazil]]: Brazilian Institute of Geography and Statistics ([[IBGE]])\n*[[Belgium]]: [[Statistics Belgium]]\n*[[Canada]]: [[Statistics Canada]]\n*[[Colombia]]: Departamento Administrativo Nacional de Estadistica ([[DANE]])\n*[[Denmark]]: Danmarks statistik - http://www.dst.dk\n*[[France]]: [[National Institute for Statistics and Economic Studies]]\n*[[Germany]]: [[Statistisches Bundesamt]] - http://www.destatis.de\n*[[Greece]]: [[National Statistical Service of Greece]]\n*[[India]]: [[Indian Statistical Institute]]\n*[[India]]: [[Indian Agricultural Statistics Research Institute]]\n*[[Ireland]]: [[Central Statistics Office of Ireland]]\n*[[The Netherlands]]: [[Centraal Bureau voor de Statistiek]] - http://www.cbs.nl\n*[[New Zealand]]: [[Statistics New Zealand]]\n*[[Portugal]]: [[Instituto Nacional de Estatistica]] - http://www.ine.pt/\n*[[Sweden]]: [[Statistics Sweden]] - http://www.scb.se/\n*[[United Kingdom]]: [[Office for National Statistics]] (ONS)\n*[[USA]]: [[FedStats]]\n*[[USA]]: [[United States Census Bureau]]\n*[[USA]]: [[Bureau of Labor Statistics]]\n\n== International statistical services ==\n*[[Eurostat]]\n*[[United Nations]] Statistics Division - http://unstats.un.org\n*[[UNESCO]] Institute for Statistics - http://www.uis.unesco.org\n*[http://cs3-hq.oecd.org/scripts/stats/source/alpha.asp?Let=INT Worldwide statistical sources]\n*[[PARIS21]] http://www.paris21.org\n\n== See also ==\n*[[Statistik]]\n*[[List of statistical topics]]\n*[[List of academic statistical associations]]','',13,'Budhi','20040721223749','',0,0,0,1,0.766170725583,'20050209000836','79959278776250'); INSERT INTO cur VALUES (963,0,'Daptar_Statistikawan','[[Statistikawan]] atawa jalma nu mere kontribusi kana tiori [[statistik]], atawa hal anu aya hubunganna jeung [[kamungkinan]], atawa [[machine learning]]:\n\n* [[Peter Armitage]]\n* [[Thomas Bayes]]\n* [[Ladislaus Bortkiewicz]]\n* [[George Box]]\n* [[Pafnuty Chebyshev]]\n* [[Alexey Chervonenkis]]\n* [[William Cochran]]\n* (Sir) [[David R. Cox]]\n* [[Richard Threlkeld Cox]]\n* [[Harald Cramér]] (Sweden, [[1893]] - [[1985]])\n* [[Bruno de Finetti]]\n* [[W. Edwards Deming]]\n* [[Persi Diaconis]]\n* (Sir) [[Richard Doll]]\n* [[Francis Ysidro Edgeworth]]\n* [[A. K. Erlang]]\n* (Sir) [[Ronald A. Fisher]]\n* [[Francis Galton]]\n* [[Seymour Geisser]]\n* [[Corrado Gini]]\n* [[I. J. Good]]\n* [[William Sealey Gosset]] (known as \"Student\")\n* [[Emil Julius Gumbel]]\n* [[Pierre Gy]]\n* [[Austin Bradford Hill]]\n* [[Edwin Thompson Jaynes]]\n* [[Harold Jeffreys]]\n* [[David Kendall]]\n* (Sir) [[Maurice Kendall]]\n* [[Alfred J. Lotka]]\n* [[Prasanta Chandra Mahalanobis]]\n* [[Matosaburo Masuyama]]\n* [[Jerzy Neyman]]\n* [[Egon Pearson]]\n* [[Karl Pearson]]\n* [[Edwin James George Pitman]]\n* [[Adolphe Quetelet]]\n* [[C. R. Rao]] \n* [[Herbert Robbins]]\n* [[Leonard Jimmy Savage]]\n* [[Walter A. Shewhart]]\n* [[Mike Dugas]]\n* [[P. V. Sukhatme]]\n* [[Genichi Taguchi]]\n* Pafnuty Tchebycheff, see [[Pafnuty Chebyshev]]\n* Pafnuty Tchebyscheff, see [[Pafnuty Chebyshev]]\n* [[Leonard H. C. Tippett]]\n* [[John Tukey]]\n* [[Vladimir Vapnik]] (Russia, ~[[1935]] - )\n* [[Samuel Wilks]]\n* [[Frank Yates]]\n* [[Marvin Zelen]]\n* [[Carl Eric Sarndal]]\n* [[Alexander Mood]]\n* [[Franklin Graybill]]\n* [[Duane Boes]]\n* [[Michael Hidiroglou]]\n* [[Yves Berger]]\n\n\n\'\'See also:\'\' [[List of mathematicians]] | [[List of people by occupation]] | [[List of people]]\n\n[[Category:Statisticians]]\n[[Category:Lists of people by occupation|Statisticians]]','',13,'Budhi','20040817031928','',0,0,0,0,0.864301511955,'20050101215719','79959182968071'); INSERT INTO cur VALUES (964,0,'Machine_learning','\'\'\'Machine learning\'\'\' is an area of [[artificial intelligence]] involving developing techniques to allow computers to \"learn\". More specifically, machine learning is a method for creating computer programs by the analysis of data sets, rather than the intuition of engineers.\n\nMachine learning [[algorithm]]s are organized into a [[taxonomy]], based on the desired outcome of the algorithm. Common algorithm types include:\n\n* [[supervised learning]] --- where the algorithm generates a function that maps inputs to desired outputs.\n* [[unsupervised learning]] --- where the algorithm generates a model for a set of inputs.\n* [[reinforcement learning]] --- where the algorithm learns a policy of how to act given an observation of the world.\n* [[learning to learn]] --- where the algorithm learns its own [[inductive bias]] based on previous experience.\n\nThe performance and computational analysis of machine learning algorithms is a branch of [[statistik]] known as [[learning theory (statistics)|learning theory]].\n\nSee also [[List of important publications in computer science#Machine Learning| Important publications in machine learning]].\n\n== Bibliography ==\n\n* Mitchell, T. (1997). \'\'Machine Learning\'\', McGraw Hill. ISBN 0070428077\n\n[[Category:Machine learning]][[Category:Computer vision]]\n\n[[fr:Apprentissage automatique]]\n[[it:Apprendimento Automatico]]\n[[zh:机器学习]]','',13,'Budhi','20040721224056','',0,0,0,0,0.005098632074,'20041231122801','79959278775943'); INSERT INTO cur VALUES (965,0,'Fénoména_statistis','Observable [[statistics|statistical]] [[phenomena]]\n* [[Regression toward the mean]]\n* [[Simpson\'s paradox]]\n* [[Statistical variability]]\n* [[Statistical independence]]\n* [[Correlation]]\n* [[Zipf-Mandelbrot law]]','',13,'Budhi','20040721224144','',0,0,0,1,0.232212134745,'20040904064417','79959278775855'); INSERT INTO cur VALUES (966,0,'Daptar_publikasi_widang_statistik','Di handap ieu daftar \'\'\'publikasi penting\'\'\' dina [[statistik]], dikumpulkeun dumasar kana widang garapan.\n\nThere are some reasons why a particular publication might be regarded as important:\n*\'\'\'Topic creator\'\'\' - A publication that created a new topic\n*\'\'\'Breakthrough\'\'\' - A publication that changed scientific knowledge significantly\n*\'\'\'Introduction\'\'\' - A publication that is a good introduction or survey of a topic\n*\'\'\'Impact\'\'\' - A publication which had a major impact on the world or on the research\n*\'\'\'Latest and greatest\'\'\' - The current most advanced result in a topic\n\n\n==Foundations==\n\n===\'\'[[The Doctrine of Chances]]\'\'===\n*[[Abraham de Moivre]]\n\n\'\'\'Deskripsi:\'\'\' Buku ieu ngawanohkeun konsep [[sebaran normal]] ngadeukeutan kana [[sebaran binomial]]. Dina akibat, de Moivre ngabuktikeun versi lemah tina [[central limit theorem|teorema central limit]]. Kadang-kadang hasilna disebut oge [[theorem of de Moivre-Laplace|teorema de Moivre-Laplace]].\n\n\n\'\'\'Importance:\'\'\' Topic creator, Breakthrough, Impact\n\n===\'\'An Essay Toward Solving a Problem in the Doctrine of Chances\'\'===\n* [[Thomas Bayes]]\n* [http://www.york.ac.uk/depts/maths/histstat/essay.ps Online version]\n\n\'\'\'Description:\'\'\' In this paper [[Bayes\' theorem]] was first introduced.\nIt has a vast impact on [[statistics]] since then and keeps being important these days.\n\n\'\'\'Importance:\'\'\' Topic creator, Breakthrough, Impact\n\n== See also ==\n* [[List of publications in Science]]\n* [[List of publications in mathematics]]\n* [[List of publications in computer science]]','/* \'\'[[The Doctrine of Chances]]\'\' */',13,'Budhi','20040907094527','',0,0,0,0,0.246247155707,'20040907094527','79959092905472'); INSERT INTO cur VALUES (967,0,'Prosés_stokastik','[[Category:Stochastic processes]]\n\n\'\'\'Proses stokastik\'\'\' nyaeta [[Fungsi (matematik)|fungsi]] [[random|acak]]. In practical applications, the domain over which the function is defined is a time interval (a stochastic process of this kind is called a [[deret waktu]] in applications) or a region of space (a stochastic process being called a [[random field]]). Familiar examples of time series include [[stock market]] and [[exchange rate]] fluctuations, signals such as speech, audio and video; medical data such as a patient\'s EKG, EEG, blood pressure or temperature; and random movement such as [[Brownian motion]] or [[random walk|random walks]]. Examples of random fields include static images, random topographies (landscapes), or composition variations of an inhomogeneous material.\n\n== Definition ==\n\nMathematically, a stochastic process is usually defined as an indexed collection of [[random variable|random variables]] \n\n:\'\'f\'\'\'\'i\'\' : \'\'W\'\' → \'\'\'R\'\'\', \n\nwhere \'\'i\'\' runs over some [[index set]] \'\'I\'\' and \'\'W\'\' is some [[probability space]] on which the random variables are defined. \n\nThis definition captures the idea of a random function in the following way. To make a function\n\n:\'\'f\'\' : \'\'D\'\' → \'\'\'R\'\'\' \n\nwith [[function domain|domain]] \'\'D\'\' and [[range]] \'\'\'R\'\'\' into a random function, means simply making the value of the function at each point of \'\'D\'\', \'\'f\'\'(\'\'x\'\'), into a [[random variable]] with values in \'\'R\'\'. The domain \'\'D\'\' becomes the index set of the stochastic process, and a particular stochastic process is determined by specifying the joint probability distributions of the various random variables \'\'f\'\'(\'\'x\'\'). \n\nNote, however, that the definition of stochastic process as an indexed collection of random variables is much more general than the case where the indices are points of the domain of the random function.\n\n=== Implications of the definition ===\n\nOf course, the mathematical definition of a [[Fungsi (matematik)|function]] includes the case \"a function from {\'\'1\'\',...,\'\'n\'\'} to \'\'\'R\'\'\' is a [[vector (spatial)|vector]] in \'\'\'R\'\'\'\'\'n\'\'\", so [[multivariate random variable|multivariate random variables]] are a special case of stochastic processes.\n\nFor our first [[infinite]] example, take the domain to be \'\'\'N\'\'\', the [[natural numbers]], and our range to be \'\'\'R\'\'\', the [[real numbers]]. Then, a function \'\'f\'\' : \'\'\'N\'\'\' → \'\'\'R\'\'\' is a [[sequence]] of real [[number|numbers]], and a stochastic process with domain \'\'\'N\'\'\' and range \'\'\'R\'\'\' is a random sequence. The following questions arise:\n# How is a [[random sequence]] specified? \n# How do we find the answers to typical questions about sequences, such as \n## what is the [[probability distribution]] of the value of \'\'f\'\'(\'\'i\'\')?\n## what is the [[probability]] that \'\'f\'\' is [[bounded]]? \n## what is the probability that \'\'f\'\' is [[monotonic]]?\n## what is the probability that \'\'f\'\'(\'\'i\'\') has a [[limit]] as \'\'i\'\'→∞?\n## if we construct a [[series]] from \'\'f\'\'(\'\'i\'\'), what is the probability that the series [[convergence|converges]]? What is the probability [[distribution]] of the sum?\n\nAnother important class of examples is when the domain is not a [[discrete space]] such as the natural numbers, but a [[continuous space]] such as the [[unit interval]] [0,1], the positive real numbers [0,∞) or the entire [[real line]], \'\'\'R\'\'\'. In this case, we have a different set of questions that we might want to answer:\n# How is a random function specified? \n# How do we find the answers to typical questions about functions, such as \n## what is the probability distribution of the value of \'\'f\'\'(\'\'x\'\') ?\n## what is the probability that \'\'f\'\' is bounded/[[integrable]]/[[continuous]]/[[differentiable]]...? \n## what is the probability that \'\'f\'\'(\'\'x\'\') has a limit as \'\'x\'\'→∞ ?\n## what is the probability distribution of the integral \\int_a^b f(x)\\,dx?\n\nThere is an effective way to answer all of these questions, but it is rather technical (see \'\'Constructing Stochastic Processes\'\' below).\n\n=== Interesting special cases ===\n\n*[[Homogeneous process]]es: processes where the domain has some [[symmetry]] and the finite-dimensional probability distributions also have that symmetry. Special cases include [[stationary process|stationary processes]], also called time-homogeneous. \n*[[process with independent increments|Processes with independent increments]]: processes where the domain is at least partially ordered and, if \'\'x\'\'1 <...< \'\'xn\'\', all the variables \'\'f\'\'(\'\'x\'\'k+1) − \'\'f\'\'(\'\'xk\'\') are independent. [[Markov chain|Markov chains]] are a special case.\n*[[Markov process]]es are those in which the future is \'\'conditionally\'\' independent of the past \'\'given\'\' the present.\n*[[point process|Point processes]]: random arrangements of points in a space \'\'S\'\'. They can be modelled as stochastic processes where the domain is a sufficiently large family of subsets of \'\'S\'\', ordered by inclusion; the range is the set of natural numbers; and, if A is a subset of B, \'\'f\'\'(\'\'A\'\') ≤ \'\'f\'\'(\'\'B\'\') with probability 1.\n*[[Gaussian process|Gaussian processes]]: processes where all linear combinations of coordinates are [[normal distribution|normally distributed]] random variables.\n*[[Poisson process]]es\n*[[Gauss-Markov process]]es: processes that are both Gaussian and Markov\n*[[Martingale]]s -- processes with constraints on the expectation\n*[[Galton-Watson process]]es\n*[[Elevator paradox]]\n*[[Branching process]]es\n*[[Bernoulli process]]es\n\n=== Conto ===\n\n\'\'What is a suitable elementary example to develop in full? Maybe [[coin-tossing]] or [[random walk]]?\'\'\n\n== Constructing stochastic processes ==\n\nIn the ordinary [[axiomatization]] of [[tiori probabiliti]] by means of [[measure theory]], the problem is to construct a [[sigma-algebra]] of [[measurable set|measurable subsets]] of the space of all functions, and then put a finite [[measure]] on it. For this purpose one traditionally uses a method called [[Kolmogorov]] extension. \n\nThere is at least one alternative axiomatization of probability theory by means of [[expectation|expectations]] on [[C-star algebra|algebras of observables]]. In this case the method goes by the name of [[Gelfand-Naimark-Segal]] construction.\n\nThis is analogous to the two approaches to measure and integration, where one has the choice to construct measures of sets first and define integrals later, or construct integrals first and define set measures as integrals of characteristic functions.\n\n=== The Kolmogorov extension ===\n\nThe Kolmogorov extension proceeds along the following lines: assuming that a [[probability measure]] on the space of all functions \'\'f\'\' : \'\'X\'\' → \'\'Y\'\' exists, then it can be used to specify the probability distribution of finite-dimensional random variables [\'\'f\'\'(\'\'x\'\'1),...,\'\'f\'\'(\'\'xn\'\')]. Now, from this \'\'n\'\'-dimensional probability distribution we can deduce an \'\'(n-1)\'\'-dimensional [[marginal probability distribution]] for [\'\'f\'\'(\'\'x\'\'1),...,\'\'f\'\'(\'\'x\'\'\'\'n\'\'-1)]. There is an obvious compatibility condition, namely, that this marginal probability distribution be the same as the one derived from the full-blown stochastic process. When this condition is expressed in terms of [[probability density function|probability densities]], the result is called the [[Chapman-Kolmogorov equation]]. \n\nThe [[Kolmogorov extension theorem]] guarantees the existence of a stochastic process with a given family of finite-dimensional [[probability distribution|probability distributions]] satisfying the Chapman-Kolmogorov compatibility condition.\n\n==== Separability, or what the Kolmogorov extension does not provide ====\n\nRecall that, in the Kolmogorov axiomatization, [[measurable]] sets are the sets which have a probability or, in other words, the sets corresponding to yes/no questions that have a probabilistic answer. \n\nThe Kolmogorov extension starts by declaring to be measurable all sets of functions where finitely many coordinates [\'\'f\'\'(\'\'x\'\'1),...,\'\'f\'\'(\'\'xn\'\')] are restricted to lie in measurable subsets of \'\'Yn\'\'. In other words, if a yes/no question about \'\'f\'\' can be answered by looking at the values of at most finitely many coordinates, then it has a probabilistic answer. \n\nIn measure theory, if we have a [[countably infinite]] collection of measurable sets, then the union and intersection of all of them is a measurable set. For our purposes, this means that yes/no questions that depend on countably many coordinates have a probabilistic answer.\n\nThe good news is that the Kolmogorov extension makes it possible to construct stochastic processes with fairly arbitrary finite-dimensional distributions. Also, every question that one could ask about a sequence has a probabilistic answer when asked of a random sequence. The bad news is that certain questions about functions on a continuous domain don\'t have a probabilistic answer. One might hope that the questions that depend on uncountably many values of a function be of little interest, but the really bad news is that virtually all concepts of [[calculus]] are of this sort. For example:\n#[[bounded|boundedness]]\n#[[continuity]]\n#[[differentiability]] \nall require knowledge of uncountably many values of the function. \n\nOne solution to this problem is to require that the stochastic process be [[separable]]. In other words, that there be some countable set of coordinates {\'\'f\'\'(\'\'xi\'\')} whose values determine the whole random function \'\'f\'\'. \n\n=== The algebraic approach ===\n\nIn the algebraic axiomatization of probability theory, one of whose main proponents was [[Irving Segal|Segal]], the primary concept is not that of probability of an event, but rather that of a random variable. Probability distributions are determined by assigning an expectation to each random variable. The measurable space and the probability measure arise from the random variables and expectations by means of well-known representation theorems of analysis. One of the important features of the algebraic approach is that apparently infinite-dimensional probability distributions are not harder to formalize than finite-dimensional ones.\n\nRandom variables are assumed to have the following properties:\n# complex constants are random variables;\n# the sum of two random variables is a random variable;\n# the product of two random variables is a random variable;\n# addition and multiplication of random variables are both commutative; and\n# there is a notion of conjugation of random variables, satisfying (\'\'ab\'\')*=\'\'b\'\'*\'\'a\'\'* and \'\'a\'\'**=\'\'a\'\' for all random variables \'\'a\'\',\'\'b\'\', and coinciding with complex conjugation if \'\'a\'\' is a constant.\n\nThis means that random variables form complex abelian *-algebras. If \'\'a\'\'=\'\'a\'\'*, the random variable \'\'a\'\' is called \"real\".\n\nAn expectation \'\'E\'\' on an algebra \'\'A\'\' of random variables is a normalized, positive linear functional. What this means is that\n# \'\'E\'\'(1)=1;\n# \'\'E\'\'(\'\'a\'\'*\'\'a\'\')≥0 for all random variables \'\'a\'\';\n# \'\'E\'\'(\'\'a\'\'+\'\'b\'\')=\'\'E\'\'(\'\'a\'\')+\'\'E\'\'(\'\'b\'\') for all random variables \'\'a\'\' and \'\'b\'\'; and\n# \'\'E\'\'(\'\'za\'\')=\'\'zE\'\'(\'\'a\'\') if \'\'z\'\' is a constant.\n\n== Bibliography ==\n\n*[Box and Jenkins] Time Series Analysis Forecasting And Control,  George Box, Gwilym Jenkins,  Holden-Day (1976)  ISBN 0-8162-1104-3\n\n*[Doob] Stochastic Processes, J. L Doob, John Wiley & Sons (1953) Library of Congress Catalog Number: 52-11857\n\n*[Gardiner] Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences,  Second edition,  C.W. Gardiner, Springer Verlag (1985) ISBN 3-540-15607-0\n\n*[Iyanaga and Kawada] Encyclopedic Dictionary Of Mathematics Volume II, edited by Shokichi Iyanaga and Yukiyosi Kawada, translated by Kenneth May,  MIT Press (1980)  ISBN 0-262-59010-7\n\n*[Karlin and Taylor]  A First Course In Stochastic Processes,  second edition,  Samuel Karlin, Howard Taylor, Academic Press (1975)  ISBN 0-12-398552-8\n\n*[Neftci] An Introduction To The Mathematics Of Financial Derivatives, Salih Neftci, Academic Press (1996)  ISBN 0-12-515390-2\n\n*[Parzen]Stochastic Processes, Emmanuel Parzen,  Holden-Day (San Francisco 1962)  ISBN 0-8162-6664-6\n\n*[Vanmarcke] Random Fields: Analysis and Synthesis, Erik VanMarcke, MIT Press (1983)  ISBN 0-262-22026-1  
 \n\n[[de:stochastische Prozesse]]\n[[it:Processo stocastico]]','/* Implications of the definition */',13,'Budhi','20041224212518','',0,0,1,0,0.334960308082,'20041225232059','79958775787481'); INSERT INTO cur VALUES (968,0,'Autocorrelation','\'\'\'Autocorrelation\'\'\' ngarupakeun salah sahiji alat matematik anu remen digunakeun dina [[signal processing]] keur analisa fungsi atawa deret nilai, saperti domain waktu [[signal|signals]]. It is the [[cross-correlation]] of a signal with itself. Autocorrelation is useful for finding repeating patterns in a signal, such as determining the presence of a periodic signal which has been buried under noise, or identifying the fundamental frequency of a signal which doesn\'t actually contain that frequency component, but implies it with many harmonic frequencies.\n\nThe continuous autocorrelation \'\'Rf(τ)\'\' is the continuous cross-correlation of \'\'f(t)\'\' with itself, at lag \'\'τ\'\', and is defined as:\n\n:R_f(\\tau) = f^*(-\\tau) * f(\\tau) = \\int_{-\\infty}^{\\infty} f(t+\\tau)f^*(t)\\, dt\n\nwhere \'\'f*\'\' represents the [[complex conjugate]]. For a real function, \'\'f*\'\' = \'\'f\'\'.\n\nFormally, the discrete autocorrelation \'\'R\'\' at lag \'\'j\'\' for signal \'\'xn\'\' is \n\n\n:R(j) = \\sum (x_n-m)(x_{n-j}-m )\n\nwhere \'\'m\'\' is the [[average]] value (expected value) of \'\'xn\'\'. Quite frequently, autocorrelations are calculated for zero-centered signals, that is, for signals with zero mean. The autocorrelation definition then becomes \n\n\n:R(j) = \\sum x_n x_{n-j}\n\nwhich is the definition of [[autocovariance]].\n\nMulti-dimensional autocorrelation is defined similarly. For example, in three dimensions the autocorrelation would be defined as \n\n\n:R(j,k,l) = \\sum (x_{n,m,p}-m)(x_{n-j,m-k,p-l}-m)\n\n\n\nIn the following, we will describe properties of one-dimensional autocorrelations only, since most properties are easily transferred from the one-dimensional case to the multi-dimensional cases.\n\nA fundamental property of the autocorrelation is symmetry, \'\'R(i) = R(-i)\'\', which is easy to prove from the definition.\n\nSince autocorrelation is a specific type of cross-correlation, it maintains all the properties of cross-correlation, and has a few specific properties of its own:\n\nThe autocorrelation of a white noise signal will have a strong peak at τ=0 and will be close to 0 for all other τ. This shows that white noise has no periodicity. \n\nThe autocorrelation function is related to the [[Fourier transform]] by the equations\n\nR(\\tau) = \\int_{-\\infty}^\\infty G(f) e^{j 2 \\pi f \\tau} \\, df\n\nG(f) = \\int_{-\\infty}^\\infty R(\\tau) e^{- j 2 \\pi f \\tau} \\, d\\tau\n\n\'\'This needs a lot more work...\'\'\n\n==Pamakean==\n\nOne application of autocorrelation is the measurement of the duration of [[light]] pulses produced by [[laser]]s. Very short duration light pulses (with durations of less than approximately 100 [[femtosecond]]s) produced by [[modelocking|modelocked]] lasers cannot easily be measured by [[optoelectronic]] methods, since the response time of [[photodiode]]s and [[oscilloscope]]s are at best of the order of 200 femtoseconds. Instead, an autocorrelation method is used. An \'\'\'optical autocorrelator\'\'\' is a device which splits a beam of light into two beams, and then (after passing one of the beams through an adjustable [[delay line]]) recombines the beams in a manner similar to a [[Michelson interferometer]]. The recombined beams are mixed in a [[nonlinear optics|nonlinear optical]] device (usually a second harmonic generation [[crystal]]).\n\nPlotting the resulting optical signal as a function of the delay between the two arms of the autocorrelator produces an autocorrelation signal of the original input. From this, the duration of the input pulses can be found (if a particular pulse shape is inferred). The technique allows the measurement of pulse durations down to approximately 3 femtoseconds, without needing high-[[bandwidth]] electronics, as long as the pulses are part of a repetitive pulse train.\n\n==Tumbu kaluar==\n* [http://mathworld.wolfram.com/Autocorrelation.html MathWorld: Autocorrelation]','/* Applications */',13,'Budhi','20040901012858','',0,0,0,0,0.229069664715,'20040903011030','79959098987141'); INSERT INTO cur VALUES (969,0,'Bayesian_inference','\'\'\'Bayesian inference\'\'\' nyaeta [[statistical inference]] (kaputusan statistik) numana sagala kamungkinan [[Probability interpretations|interpreted]] lain salaku frekuensi atawa proporsi atawa sabangsana, tapi leuwih condong kana tingkat kapercayaan. Ngaran ieu asalna kusabab sering ngagunakeun [[Bayes\' theorem]] dina widang ieu. Bayes\' theorem ngarupakeun ngaran sanggeus [[Thomas Bayes]] anu mimiti ngenalkeun ieu metoda.\n\n== Kajadian jeung metoda ilmiah ==\n\nAhli statistik Bayes ngaku yen metoda kaputusan Bayes ngarupakeun bentuk formal tina [[scientific method]] kaasup dina ngumpulkeun [[evidence]] numana kahareupna atawa jalan keur nangtukeun hiji [[hypothesis]]. Dina hal ieu bisa jadi teu pasti salawasna, sanajan kitu lobana kumpulan kajadian bakal ngajadikeun naekna tingkat kapercayaan hipotesa pangluhurna (salawasna 1) atawa panghandapna (salawasna 0). Teorema Bayes nyadiakeun metoda keur naksir tingkat kapercayaan dina waktu informasi anyar ngan saeutik. [[Bayes\' theorem]] nyaeta \n:P(A|e) = P(A)\\frac{P(e | A) }{P(e)}\nKeur kaperluan urang, (A) dijadikeun hipotesa [[Induction (philosophy)|induced]] tina sababaraha susunan observasi. (e) dijadikeun hipotesa konfirmasi tina observasi.\n*Watesan \'\'P\'\'(\'\'A\'\'|\'\'e\'\') disebut \'\'[[posterior probability]]\'\' ti \'\'A\'\', given \'\'e\'\'.\n*Watesan \'\'P\'\'(\'\'A\'\') disebut \'\'[[prior probability]]\'\' ti \'\'A\'\'.\n*Watesan \'\'P\'\'(\'\'e\'\') disebut prior probability ti \'\'e\'\'.\nFaktor [[Likelihood]]: Pecahan\n:\\frac{P(e | A) }{P(e)}\nngarupakeun faktor skala, probabilitas observasi hasil tina hipotesa dibagi ku probabilitas hipotesa observasi nu ngarupakeun kajadian \'\'independen\'\' dina hipotesa. Hasil ukuran ieu ngakibatkeun yen hipotesa ayana dina probabilitas nu dijieun tina observasi. Kulantaran kitu hasil observasi bakal jadi teu sahade lamun hipotesa bener, sarta faktor skala bakal jadi gede. \n\nPerkalian faktor skala ieu ku probabilitas observasi nu bener bakal ngahasilkeun probabilitas hipotesa nu bener oge, saperti nu diberekeun ku observasi. \n\nPagawean konci dina nyieun kaputusan tangtuna ngararancang prior probabiliti dina observasi jeung hipotesa. Lamun prior probabiliti nembongkeun nilai \'\'objektif\'\', maka bisa digunakeun keur nangtukeun ukuran objektif hipotesa probabiliti. Tapi, taya jalan nu jelas keur nangtukeun objektif probabiliti. Hal anu teu mungkin keur migawe pendekatan dina nangtukeun hiji probabilitas bis nangtukeun sakabeh hipotesa nu mungkin.\n\nAlternatifna, jeung sering dipake, probabiliti dicokot salaku \'\'tingkat kapercayaan subjektif\'\' ti bagian partisipan. Teori saterusna nangtukeun ukuran rasio kepercayaan tina observasi nu dijadikeun subjek kapercayaan dina hipotesa. Tapi hasil dina kasus ieu masih keneh nyesakeun subjektif dina posterior probabiliti. Sabab kitu teorema bisa digunakeun keur ngarasionalkeun kapercayaan dina sababaraha hipotesa, tapi nolak objektifitas. Sababaraha skema teu bisa dipake, contona, sifat objektif dina nangtukeun konflik paradigma sain.\n\nDina loba kasus, akibat kajadian bisa disimpulkeun dina rasio [[likelihood]], nu digambarkeun dina [[Likelihood principle#The law of likelihood|the law of likelihood]]. Hal ieu bisa dikombinasikeun jeung [[prior probability]] keur ngagambarkeun tingkat kapercayaan asli sarta kajadian pangtukangna nu dicokot dina perhitungan. Samemeh kaputusan dijieun, [[loss function]] oge diperlukeun keur nimbangkeun gambaran akibat tina kasalahan nangtukeun kaputusan.\n\n== Conto sederhana Kaputusan Bayes ==\n\n=== From which bowl is the cookie? ===\n\nTo illustrate, suppose there are two bowls full of cookies. Bowl #1 has 10 chocolate chip and 30 plain cookies, while bowl #2 has 20 of each. Our friend Fred picks a bowl at random, and then picks a cookie at random. We may assume there is no reason to believe Fred treats one bowl differently from another, likewise for the cookies. The cookie turns out to be a plain one. How probable is it that Fred picked it out of bowl #1? \n\nIntuitively, it seems clear that the answer should be more than a half, since there are more plain cookies in bowl #1. The precise answer is given by Bayes\' theorem. Let \'\'H\'\'1 corresponds to bowl #1, and \'\'H\'\'2 to bowl #2. \nIt is given that the bowls are identical from Fred\'s point of view, thus \'\'P\'\'(\'\'H\'\'1) = \'\'P\'\'(\'\'H\'\'2), and the two must add up to 1, so both are equal to 0.5. \nThe \"data\" \'\'D\'\' consists in the observation of a plain cookie. From the contents of the bowls, we know that P(\'\'D\'\' | \'\'H\'\'1) = 30/40 = 0.75 and P(\'\'D\'\' | \'\'H\'\'2) = 20/40 = 0.5. Bayes\' formula then yields\n:\n\\begin{matrix} P(H_1 | D) &=& \\frac{P(H_1) \\cdot P(D | H_1)}{P(H_1) \\cdot P(D | H_1) + P(H_2) \\cdot P(D | H_2)} \\\\ \\\\ \\ & =& \\frac{0.5 \\times 0.75}{0.5 \\times 0.75 + 0.5 \\times 0.5} \\\\ \\\\ \\ & =& 0.6 \\end{matrix}\n\nBefore observing the cookie, the probability that Fred chose bowl #1 is the prior probability, \'\'P\'\'(\'\'H\'\'1), which is 0.5.\nAfter observing the cookie, we revise the probability to \'\'P\'\'(\'\'H\'\'1|\'\'D\'\'), which is 0.6.\n\n===False positives in a medical test===\n\n[[False positive]]s are a problem in any kind of [[test]]: no test is perfect, and sometimes the test will incorrectly report a positive result. For example, if a test for a particular [[disease]] is performed on a [[patient]], then there is a chance (usually small) that the test will return a positive result even if the patient does not have the disease. The problem lies, however, not just in the chance of a false positive prior to testing, but determining the chance that a positive result is in fact a false positive. As we will demonstrate, using Bayes\' theorem, if a condition is rare, then the majority of positive results may be false positives, even if the test for that condition is (otherwise) reasonably accurate.\n\nSuppose that a test for a particular disease has a very high success rate: \n* if a tested patient has the disease, the test accurately reports this, a \'positive\', 99% of the time (or, with probability 0.99), and\n* if a tested patient does not have the disease, the test accurately reports that, a \'negative\', 95% of the time (\'\'i.e.\'\' with probability 0.95).\nSuppose also, however, that only 0.1% of the population have that disease (\'\'i.e.\'\' with probability 0.001). We now have all the information required to use Bayes\' theorem to calculate the probability that, given the test was positive, that it is a false positive.\n\nLet \'\'A\'\' be the event that the patient has the disease, and \'\'B\'\' be the event that the test returns a positive result. Then, using the second alternative form of Bayes\' theorem ([[Bayes\'_theorem#Alternative forms of Bayes\' theorem|above]]), the probability of a \'\'true\'\' positive is\n\n:\\begin{matrix}P(A|B) &= &\\frac{0.99 \\times 0.001}{0.99\\times 0.001 + 0.05\\times 0.999}\\, ,\\\\ ~\\\\ &\\approx &0.019\\, .\\end{matrix}\n\nand hence the probability of a false positive is about  (1 − 0.019) = 0.981.\n\nDespite the apparent high accuracy of the test, the incidence of the disease is so low (one in a thousand) that the vast majority of patients who test positive (98 in a hundred) do not have the disease. (Nonetheless, this is 20 times the proportion before we knew the outcome of the test! The test is not useless, and re-testing may improve the reliability of the result.) In particular, a test must be very reliable in reporting a negative result when the patient does not have the disease, if it is to avoid the problem of false positives. In mathematical terms, this would ensure that the second term in the denominator of the above calculation is small, relative to the first term. For example, if the test reported a negative result in patients without the disease with probability 0.999, then using this value in the calculation yields a probability of a false positive of roughly 0.5.\n\nIn this example, Bayes\' theorem helps show that the accuracy of tests for rare conditions must be very high in order to produce reliable results from a single test, due to the possibility of false positives. (The probability of a \'false negative\' could also be calculated using Bayes\' theorem, to completely characterise the possible errors in the test results.)\n\n=== In the courtroom ===\nBayesian inference can be used to coherently assess additional evidence of guilt in a court setting. \n\n*Let G be the event that the defendent is guilty. \n\n*Let E be the event that the defendent\'s DNA matches DNA found at the crime scene. \n\n*Let p(E | G) be the probability of seeing event E assuming that the defendent is guilty. (Usually this would be taken to be unity.)\n\n*Let p(G | E) be the probability that the defendent is guilty assuming the DNA match event E\n\n*Let p(G) be the probability that the defendent is guilty, based on the evidence other than the DNA match.\n\nBayesian inference tells us that if we can assign a probability p(G) to the defendent\'s guilt before we take the DNA evidence into account, then we can revise this probability to the conditional probability p(G | E), since\n\n:p(G | E) = p(G) p(E | G) / p(E)\n\nSuppose, on the basis of other evidence, a juror decides that there is a 30% chance that the defendent is guilty. Suppose also that the forensic evidence is that the probability that a person chosen at random would have DNA that matched that at the crime scene was 1 in a million, or 10-6.\n\nThe event E can occur in two ways. Either the defendent is guilty (with prior probability 0.3) and thus his DNA is present with probability 1, or he is innocent (with prior probability 0.7) and he is unlucky enough to be one of the 1 in a million matching people.\n\nThus the juror could coherently revise his opinion to take into account the DNA evidence as follows:\n\n:p(G | E) = 0.3 × 1.0 /(0.3 × 1.0 + 0.7 × 10-6) = 0.99999766667.\n\nIn the United Kingdom, Bayes\' theorem was explained by an [[expert witness]] to the jury in the case of Regina versus Denis Adams. The case went to Appeal and the Court of Appeal gave their opinion that the use of Bayes\' theorem was inappropriate for jurors.\n\n===Search theory===\n\nIn May 1968 the US nuclear submarine Scorpion (SSN 589) failed to arrive as expected at her home port of Norfolk, Virginia. The US Navy was convinced that the vessel had been lost off the Eastern seabord but an extensive search failed to discover the wreck. The US Navy\'s deep water expert, John Craven, believed that it was elsewhere and he organised a search south west of the Azores based on a controversial approximate triangulation by hydrophones. He was allocated only a single ship, the USNS Mizar, and he took advice from a firm of consultant mathematicians in order to maximise his resources. A Bayesian search methodology was adopted. Experienced submarine commanders were interviewed to construct hypotheses about what could have caused the loss of the Scorpion. The sea area was divided up into grid squares and a probability assigned to each square, under each of the hypotheses, to give a number of probability grids, one for each hypothesis. These were then added together to produce an overall probability grid. The probability attached to each square was then the probability that the wreck was in that square. A second grid was constructed with probabilities that represented the probability of successfully finding the wreck if that square were to be searched and the wreck were to be actually there. This was a known function of water depth. The result of combining this grid with the previous grid is a grid which gives the probability of finding the wreck in each grid square of the sea if it were to be searched. This sea grid was systematically searched in a manner which started with the high probability regions first and worked down to the low probability regions last. Each time a grid square was searched and found to be empty its probability was reassessed using [[Bayes\' theorem]]. This then forced the probabilities of all the other grid squares to be reassessed (upwards), also by Bayes\' theorem. The use of this approach was a major computational challenge for the time but it was eventually successful and the Scorpion was found in October of that year. Suppose a grid square has a probability p of containing the wreck and that the probability of successfully detecting the wreck if it is there is q. If the square is searched and no wreck is found then, by Bayes, the revised probability of the wreck being in the square is given by\n\n p\' = \\frac{p(1-q)}{(1-p)+p(1-q)}\n\n== More mathematical examples ==\n\n=== Naive Bayes classifier ===\n\n\'\'See:\'\' [[naive Bayesian classification]].\n\n=== Posterior distribution of the binomial parameter ===\n\nIn this example we consider the computation of the posterior distribution for the binomial parameter.\nThis is the same problem considered by Bayes in Proposition 9 of his essay.\n\nWe are given \'\'m\'\' observed successes and \'\'n\'\' observed failures in a binomial experiment.\nThe experiment may be tossing a coin, drawing a ball from an urn, or asking someone their opinion, among many other possibilities.\nWhat we know about the parameter (let\'s call it \'\'a\'\') is stated as the prior distribution, \'\'p\'\'(\'\'a\'\').\n\nFor a given value of \'\'a\'\',\nthe probability of \'\'m\'\' successes in \'\'m\'\'+\'\'n\'\' trials is \n\n: p(m,n|a) = \\begin{pmatrix} n+m \\\\ m \\end{pmatrix} a^m (1-a)^n \n\nSince \'\'m\'\' and \'\'n\'\' are fixed, and \'\'a\'\' is unknown,\nthis is a likelihood function for \'\'a\'\'.\nFrom the continuous form of the law of total probability we have\n\n: p(a|m,n) = \\frac{p(m,n|a)\\,p(a)}{\\int_0^1 p(m,n|a)\\,p(a)\\,da}\n = \\frac{\\begin{pmatrix} n+m \\\\ m \\end{pmatrix} a^m (1-a)^n\\,p(a)}\n {\\int_0^1 \\begin{pmatrix} n+m \\\\ m \\end{pmatrix} a^m (1-a)^n\\,p(a)\\,da}\n\n\nFor some special choices of the prior distribution \'\'p\'\'(\'\'a\'\'), \nthe integral can be solved and the posterior takes a convenient form.\nDina sabagean,\nlamun \'\'p\'\'(\'\'a\'\') ngarupakeun [[sebaran beta]] nu mibanda parameter \'\'m\'\'0 sarta \'\'n\'\'0,\nmangka \'\'posterior\'\' oge sebaran beta nu mibanda parameter \'\'m\'\'+\'\'m\'\'0 jeung \'\'n\'\'+\'\'n\'\'0.\n\nA \'\'conjugate prior\'\' is a prior distribution, such as the beta distribution in the above example, which has the property that the posterior is the same type of distribution.\n\nWhat is \"Bayesian\" about Proposition 9 is that Bayes presented it as a probability for the parameter \'\'p\'\'. That is, not only can one compute probabilities for experimental outcomes, but also for the parameter which governs them, and the same algebra is used to make inferences of either kind. Interestingly, Bayes actually states his question in a way that might make the idea of assigning a probability distribution to a parameter palatable to a frequentist. He supposes that a billiard ball is thrown at random onto a billiard table, and that the probabilities \'\'p\'\' and \'\'q\'\' are the probabilities that subsequent billiard balls will fall above or below the first ball. By making the binomial parameter \'\'p\'\' depend on a random event, he cleverly escapes a philosophical quagmire that he most likely was not even aware was an issue.\n\n=== Aplikasi komputer ===\nKaputusan Bayesian geus dipake dina widang [[artificial intelligence]] jeung [[expert system]]. Teknik kaputusan Bayesian geus dijadikeun dasar dina sabagean tenik komputer [[pattern recognition]] mimiti taun 1950 katompernakeun. \n\nMimiti tumuwuhna dina migunakeun kaputusan Bayesian keur filter [[spamming|spam]]. Contona: [[Bogofilter]], [[SpamAssassin]] jeung [[Mozilla]]. \n\nIn some applications [[fuzzy logic]] is an alternative to Bayesian inference. Fuzzy logic and Bayesian inference, however, are mathematically and semantically not compatible: You cannot, in general, understand the \'\'degree of truth\'\' in fuzzy logic as probability and vice versa.\n\n==Tempo oge:== \n* [[Thomas Bayes]]\n* [[Bayesian model comparison]]\n* [[Bayesian probability]]\n* [[Occam\'s Razor]]\n* [[Minimum description length]]\n* [[Gaussian process regression]]\n\n==Tumbu kaluar==\n* [http://www.inference.phy.cam.ac.uk/mackay/itila/ On-line textbook: Information Theory, Inference, and Learning Algorithms], by [[David MacKay]], has many chapters on Bayesian methods, including introductory examples; compelling arguments in favour of Bayesian methods; state-of-the-art [[Monte Carlo methods]], [[message-passing methods]], and [[variational methods]]; and examples illustrating the intimate connections between Bayesian inference and [[data compression]]. \n* [http://citeseer.nj.nec.com/30545.html Naive Bayesian learning paper]\n* [http://citeseer.nj.nec.com/heckerman96tutorial.html A Tutorial on Learning With Bayesian Networks]\n\n[[Category:Statistics]]','/* Posterior distribution of the binomial parameter */',13,'Budhi','20040917061633','',0,0,0,0,0.197486714552,'20041231124514','79959082938366'); INSERT INTO cur VALUES (971,0,'Metoda_Monte_Carlo','\'\'\'Metoda Monte Carlo\'\'\' nyaeta [[algoritma]] keur ngarengsekeun rupa-rupa masalah dina [[computation|itung-itungan make komputer]] ngagunakeun wilangan acak (atawa leuwih sering disebut [[pseudo-random number|wilangan bayangan]]), ngarupakeun hal sabalikna tina algoritma deterministik. Metoda Monte Carlo penting kacida dina [[computational physics|komputasi fisik]] sarta aplikasi nu pakait, jeung bisa dipake dina rupa-rupa itungan [[quantum chromodynamics|kromodinamika kuantum]] keur ngarancang [[heat shield|pamisah panas]] sarta bentuk [[aerodynamics|aerodinamika]]. Metoda ieu geus kabuktian efisien keur ngarengsekeun persamaan integro-differential di kondisi medan radian, sarta metoda ieu geus digunakeun keur \"\'\'itungan\'\'\" [[global illumination|iluminasi global]] nu ngahasilkeun photo-realistic images of virtual 3d models, digunakeun dina [[video games]], [[architecture|arsitektur]], [[design|disain]], animasi komputer dina [[film]] sarta efek hususna, sarta widang-widang sejenna.\n\nMonte Carlo, kawentar keur [[casino|kasino]], nginjeum istilahna sabab metoda ieu ngagunakeun [[randomness|kaayaan acak]] sarta ngagunakeun \"\'\'pengulangan\'\'\" keur manggihkeun solusi nu panghadena. Narikna, metoda Monte Carlo teu merlukeun random numbers nu sabenerna keur digunakeun dina \"perhitungan\". Teknik ieu leuwih gampang dipake tinimbang deterministik, sekuen pseudo-random, gampang keur diuji sarta simulasi ulang. Sakadar kualitas nu penting keur nyieun [[simulation|simulasi]] nu hade keur nyieun sekuen pseudo-random deukeut kana kaayaan \"acak\" nu dipikahayang. Metoda ieu bakal [[sebaran seragam|kasebar seragam]] atawa nuturkeun sebaran nu dipikahayang lamun jumlah wilanganna gede tina sekuen nu ditempo.\n \nSabab merlukeun algoritma \"\'\'pengulangan\'\'\" sarta \'\'number\'\' nu loba keur kaperluan \'\'perhitungan\'\', Monte Carlo ngarupakeun metoda \'\'penyeimbang\'\' keur komputasi make [[computer|komputer]], make sababaraha teknik [[computer simulation|simulasi komputer]].\n\n\'\'\'Algoritma Monte Carlo\'\'\' nyaeta bentuk numeris metoda Monte Carlo nu dipake keur manggihkeun solusi dina masalah mathematika (nu ngabogaan variabel loba) nu harese direngsekeun, contona, make [[integral calculus|kalkulus integral]], atawa metoda numeris sejenna. Metoda ieu leuwih hade tinimbang metoda sejenna lamun [[dimension|dimensi]] tina masalah leuwih loba.\n\n==Sajarah==\n\nMetoda Monte Carlo asalna tina \"pemakaian\" praktis dina ngaran nu leuwih umum saperti \"statistical sampling\". Sabaraha ahli nyebutkeun yen \"[[Monte Carlo]]\" ngarupakeun referensi kawentar dina kasino, sarta dipopulerkeun ku ahlina dina widang eta saperti [[Stanislaw Marcin Ulam]], [[Enrico Fermi]], [[John von Neumann]] sarta [[Nicholas Metropolis]]. Ahli sejenna nyebutkeun yen metoda ieu mimiti didiskusikeun ku ahli nu hadir dina konferensi di Monte Carlo.\n\nMetoda ngitung random mimiti loba nu make dina mangsa pre-electronic computing. Metoda ieu beuki kawentar sanggeus digunakeun Fermi dina [[1930]], waktu anjeunna make metoda random keur ngitung sifat anyar [[neutron]]. Metoda Monte Carlo jadi inti [[simulation]]s nu diperlukeun dina [[Manhattan Project]]. Sanajan kitu, sanggeus komputer elektronik dijieun (mimiti taun [[1945]]) metoda Monte Carlo mimiti ditalungtik leuwih jero.\n\n==Integrasi==\n\nMetoda deterministic [[numerical integration]] dipake ku cara nyokot sajumlah kajadian dina ruang sampel tina hiji fungsi. Sacara umum, hasil tina pagawean ieu hade keur fungsi hiji variabel. Kusabab kitu, keur fungsi [[vector space|vector]]s, metoda \'\'deterministic quadrature\'\' teu efisien. Keur integrsi numerik vektor dua-dimensi, diperlukeun ruang titik grid anu sarua dina \"permukaan\" dua dimensi. Contona keur grid 10x10 diperlukeun 100 titik. Lamun vektor ngabogaan 100 dimensi, jarak grid nu sarua merlukeun 10100 titik – hal ieu taya alesan keur bisa diitung. 100 [[dimension]]s hartina teu mungkin keur diitung, saperti dina loba masalah fisik, \"dimension\" sarua jeung [[degree of freedom]], sarta dina simulasi tilu-dimensi, di dinya aya tilu \'\'degrees of freedom\'\' per partikel. \n\nMetoda Monte Carlo nunjukkeun cara make \'\'exponential time-increase\'\'. Saperti fungsi anu ngabogaan alesan [[well-behaved]], hal ieu bisa di-\'\'estimasi\'\' ku milih sacara \'\'random\'\' tina ruang 100-dimensi, sarta nyokot sababaraha tipe \'\'average\'\'. Make [[central limit theorem]], metoda ieu bakal ditempokeun ku \'\'konvergen\'\'-na 1/\\sqrt{N} – contona titik sampel lipat opat bakal boga satengah kasalahan, gumantung kana jumlah dimenasi.\n\n\'\'Perbaikan\'\' tina metoda ieu nyaeta cara nyieun atawa milih titik \'\'random\'\', tapi leuwih dipikaresep datangna kana integral ti wewengkon nu konsentrasi loba tinimbang ti wewengkon nu konsentrasi saeutik. Dina basa sejen, titik sahenteuna ngagambarkeun bentuk nu hampir sarua jeung \'\'integrand\'\'. Teu salawasna dina pemodelan komputer mere hasil nu nyugemakeun dina integrasi mimiti, sanajan kitu aya metoda sejen keur masalah ieu; dimimitian ku nyieun fungsi integrasi anu sederhana, salah sahijina bakal didiskusikeun dina topik di handap ieu.\n\n\'\'Pendekatan\'\' anu ampir sarua ngagunakeun [[low-discrepancy sequence]]s ku [[quasi-Monte Carlo method]]. Metoda Quasi-Monte Carlo sok leuwih efisien dina integrasi numeris sabab sekuen \"ngeusi\" wewengkon leuwih hade dina rasa sarta sampel penting nu dijieun tina simulasi konvergen keur ngahasilkeun solusi jadi leuwih gancang.\n\n===Metoda Integrasi===\n* Metoda sampling langsung\n** [[Importance sampling]] \n** [[Stratified sampling]]\n** [[Recursive stratified sampling]]\n** [[VEGAS algorithm]]\n* [[Random walk Monte Carlo]] kaasup [[Markov chain]]s\n** [[Metropolis-Hastings algorithm]]\n\n==Optimisasi==\n\nHal sejen anu kuat sarta kawentar dina aplikasi keur \'\'random numbers\'\' dina simulasi numeris nyaeta [[optimization (mathematics)|numerical optimisation]]. Masalah ieu salawasna make fungsi nga-\'\'minimal\'\'-keun vektor dina dimensi anu gede. Loba masalah anu bisa direngsekeun ku cara ieu; contona program [[computer chess]] geus nunjukeun kumaha carana langkah nu optimal keur meunangkeun tarung, sebutkeun, 10 langkah nu ngahasilkeun evaluasi panghadena ka tahap ahir. [[Traveling salesman problem]] contoh lain dina masalah optimasi. Didieu oge aya sababaraha conto aplikasi dina masalah desain rekayasa, saperti [[multidisciplinary design optimization]].\n\nLolobana optimasi Monte Carlo didasarkeun kana [[random walk]]s. Intina, program ieu bakal dijieun dina wanda ruang multi-dimensi, condong pindah ti fungsi luhur ka fungsi handap, sanajan kitu kadang-kadang pindahna tibalik tina [[gradient]].\n\n===Metoda Optimasi===\n\n* [[Stochastic tunneling]]\n* [[simulated annealing]]\n* [[genetic algorithm]]s\n* Parallel Tempering\n\n==Metoda sejen==\n\n* Diffusion and quantum Monte Carlo\n* Semiconductor charge transport and the like\n* Quasi-random numbers and self avoiding walks\n* Assorted random models, e.g. [[self-organised criticality]]\n\n==Tempo oge==\n*[[LURCH]]\n*[[Quasi-Monte Carlo method]]\n\n==Tumbu kaluar jeung sumber séjén==\n* P. Kevin MacKeown, \'\'Stochastic Simulation in Physics\'\', [[1997]], ISBN 981-3083-26-3\n* Harvey Gould & Jan Tobochnik, \'\'An Introduction to Computer Simulation Methods, Part 2, Applications to Physical Systems\'\', [[1988]], ISBN 020116504X\n\n[[de:Monte-Carlo-Algorithmus]] [[ja:モンテカルロ法]]\n[[zh-cn:蒙特·卡罗方法]]','',13,'Budhi','20041230005407','',0,0,0,0,0.864713865269,'20050208191941','79958769994592'); INSERT INTO cur VALUES (972,0,'Analisis_numeris','\'\'\'Analisis numeris\'\'\' ngarupakeun cabang ti [[matematik terapan]] nu \"mempelajari\" metoda jeung [[algorithm]]s keur manggihkeun (mendekati) \"solusi numerik\" keur sababaraha masalah matematik, ngagunakeun sekuen anu \"terhingga\" dina [[arithmetic]] jeung operasi [[logika]]. Solusi masalah numerik lolobana diwangun ku teori [[linear algebra]].\n\n==Panganteur umum==\n\nMétoda nu hade ngabogaan tilu ciri di handap ieu:\n\n*\'\'Akurat\'\' - \"pendekatan numerik\" sabisa mungkin kudu akurat. Hal ieu merlukan algoritma ngarah [[Numerical stability|stabil]] sacara numerik, saperti nu rek diterangkeun dina bagian saterusna.\n*\'\'Kuat\'\' - algoritma kudu mecahkeun masalah kalayan hade. Ieu hartina yen analisis numerik kudu ngingetkeun nu make, lamu hasilna teu akurat. Kusabab kitu kudu ngamungkinkeun keur \"memperkirakeun\" kasalahan.\n*\'\'Gancang\'\' - ngitung panggancangna, ngarupakeun metoda nu panghadena. \n\nUrang kudu salawasna merhatikeun ieu karakter. Keur conto, geus ilahar kajadian yen hiji metoda panggancangna, sedengkeun metoda sejenna pang-akurat-na. Ieu hartina euweuh algoritma anu hade dina sakabeh kasus.\n\nSabalikan dina analisis numeris merlukeun [[axioma]], [[téoréma]] matematika, jeung [[bukti]] dina téori, ogé bisa ngagunakeun hasil [[émpiris]] tina kaluaran komputasi keur nalungtik métode anyar jeung analisis masalah. Hal ieu ngarupakeun karakter anu unik lamun dibandingkeun jeung élmu matematika lianna.\n\n===Conditioning and stability===\n\nA [[well-conditioned problem|well-conditioned mathematical problem]] is, roughly speaking, one whose solution changes by only a small amount if the problem data are changed by a small amount. The analogous concept for the numerical algorithm for solving the problem is that of [[numerical stability]]: an algorithm for solving a well-conditioned problem is numerically stable if the result of the algorithm changes only a small amount if the data change a little. This means that any error committed in the early stages will not grow in an uncontrolled manner.\n\nAn algorithm that solves a well-conditioned problem may or may not be numerically stable. An art of numerical analysis is to find a stable algorithm for solving a mathematical problem.\n\nThe study of the generation and propagation of round-off errors in the cause of a computation is an important part of numerical analysis. Subtraction of two nearly equal numbers is an ill-conditioned operation, producing \ncatastrophic [[loss of significance]]. \n\nThe effect of round-off error is partly quantified in the [[condition number]] of an [[operator]].\n\n===Komputer salaku alat pikeun analisis numeris===\n\n[[Komputer]] ngarupakeun alat penting pikeun analisis numeris, but the field predates computers by many centuries, and actually computers were invented to a large extent in order to solve numerical problems, not the other way around. [[Taylor series|Taylor approximation]] is a product of the seventeenth and eighteenth centuries that is still very important. The [[logarithm]]s of the sixteenth century are no longer vital to numerical analysis, but the associated and even prehistoric notion of [[interpolation]] continues to solve problems for us.\n\n[[Floating point number]] representations are used extensively in modern computers: for many problems, their behavior can be unexpected, unless care is taken using numerical analysis to ensure that they will not misbehave.\n\n===Software===\n\nIf a computer is to execute some numerical method, this method has to be implemented in some way. The [[Netlib]] repository contains various collections of software routines for numerical problems. Commercial products implementing many different numerical algorithms include the IMSL and NAG libraries; a free alternative is the [[GSL|GNU Scientific Library]]. A different approach is taken by the [[Numerical Recipes]] library, where emphasis is placed on clear understanding of algorithms.\n\nThere are a number of computer programs used for performing numerical calculations:\n\n\n* [[MATLAB]] is a widely-used program for performing numerical calculations. It comes with its own programming language, in which numerical algorithms can be implemented. \n* [[GNU Octave]] is a free near-clone of Matlab.\n* [[R (programming language)|R]] is a widely used system with a focus on data manipulation and statistics. Several hundred freely downloadable specialized packages are available.\n* [[Scilab]]. \n\nMany [[computer algebra system|computer algebra systems]] such as [[Mathematica]] or [[Maple_computer_algebra_system|Maple]] (free systems include [[calc]] and [[Yacas]]) can also be used for numerical computations.\n\n==Areas of study==\n\n===Computing values of functions===\n\nOne of the simplest problems is the evaluation of a function at a given point. But even evaluating a polynomial is not straightforward: the [[Horner scheme]] is often more efficient than the obvious method. Generally, it is important to estimate and control [[round-off error]]s arising from the use of [[floating point]] arithmetic.\n\n===Interpolation, extrapolation and regression===\n\n[[Interpolation]] solves the following problem: given the value of some unknown function at a number of points, what value does that function have at some other point between the given points? A very simple method is to use [[linear interpolation]], which assumes that the unknown function is linear between every pair of successive points. This can be generalized to [[polynomial interpolation]], which is sometimes more accurate but suffers from [[Runge\'s phenomenon]]. Other interpolation methods use localized functions like [[spline (mathematics)|spline]]s or [[wavelet]]s.\n\n[[Extrapolation]] is very similar to interpolation, except that now we want to find the value of the unknown function at a point which is outside the given points.\n\n[[Regression]] is also similar, but it takes into account that the data is imprecise. Given some points, and a measurement of the value of some function at these points (with an error), we want to determine the unknown function. The [[least squares]]-method is one popular way to achieve this.\n\n===Solving equations===\n\nAnother fundamental problem is computing the solution of some given equation. Two cases are commonly distinguished, depending on whether the equation is linear or not.\n\nMuch effort has been put in the development of methods for solving systems of linear equations. Standard methods are [[Gauss-Jordan elimination]] and [[LU-factorization]]. [[Iterative method]]s such as the [[conjugate gradient method]] are usually preferred for large systems.\n\n[[Root-finding algorithm]]s are used to solve nonlinear equations (they are so named since a root of a function is an argument for which the function yields zero). If the function is [[derivative|differentiable]] and the derivative is known, then [[Newton\'s method]] is a popular choice. [[Linearization]] is another technique for solving nonlinear equations.\n\n===Optimization===\n\'\'Main article: [[Optimization (mathematics)]].\'\'\n\nOptimization problems ask for the point at which a given function is maximized (or minimized). Often, the point also has to satisfy some [[constraint]]s. \n\nThe field of optimization is further split in several subfields, depending on the form of the objective function and the constraint. For instance, [[linear programming]] deals with the case that both the objective function and the constraints are linear. A famous method in linear programming is the [[simplex method]].\n\nThe method of [[Lagrange multipliers]] can be used to reduce optimization problems with constraints to an unconstrained optimization problems.\n\n===Evaluating integrals===\n\'\'Main article: [[Numerical integration]].\'\'\n\nNumerical integration, also known as numerical [[quadrature]], asks for the value of a definite [[integral]]. Popular methods use some [[Newton-Cotes formula]], for instance the midpoint rule or the trapezoid rule, or [[Gaussian quadrature]]. However, if the dimension of the integration domain becomes large, these methods become prohibitively expansive. In this situation, one may use a [[Monte Carlo method]].\n\n===Differential equations===\n\'\'Main articles: [[Numerical ordinary differential equations]], [[Numerical partial differential equations]].\'\'\n\nNumerical analysis is also concerned with computing (in an approximate way) the solution of [[differential equation]]s, both ordinary differential equations and [[partial differential equation]]s.\n\nPartial differential equations are solved by first discretizing the equation, bringing it into a finite-dimensional subspace. This can be done by a [[finite element method]], a [[finite difference]] method, or (particularly in engineering) a [[finite volume method]]. The theoretical justification of these methods often involves theorems from [[functional analysis]]. This reduces the problem to the solution of an algebraic equation.\n\n==Buku==\n\nBefore modern [[computer]]s were widely available, numerical analysis was done primarily by hand computation. Eventually large books were produced with formulas and tables of data such as interpolation points and function coeficients. Using these tables, often calculated out to 16 decimal places or more for some functions, one could look up values to plug into the formulas given and achieve very good numerical estimates of some functions. The canonical work in the field is the [[NIST]] publication edited by Abramowitz and Stegun, an 1000 plus page book of a very large number of commonly used formulas and functions and their values at many points. The function values are no longer very useful when a computer is available, but the large listing of formulas can still be very handy. The book is out of print, but is available in scanned form, with a link provided below.\n\n==Tempo ogé==\n\n*[[List of numerical analysis topics]]\n*[[Prosés Gram-Schmidt]]\n*[[List of important publications in mathematics#Numerical analysis| Publikasi penting ngeunaan analisis numerik]]\n\n==Tumbu kaluar==\n\n*[http://dmoz.org/Science/Math/Numerical_Analysis/ Numerical analysis DMOZ category]\n*[http://www.nr.com Numerical Recipes Homepage - with free, complete downloadable books]\n*[http://www.convertit.com/Go/ConvertIt/Reference/AMS55.ASP?Res=200&Page=0 Abramowitz and Stegun book in online, scanned form]\n\n\n[[Category:Numerical analysis]]\n\n[[de:Numerische Mathematik]] [[en:Numerical analysis]] [[es:Análisis numérico]][[sv:Beräkningsvetenskap]]','/* Books */',3,'Kandar','20041220132901','',0,0,0,0,0.760289605595,'20050128065809','79958779867098'); INSERT INTO cur VALUES (973,0,'Gaussian_quadrature','Dina [[analisis numeris]], \'\'\'quadrature rule\'\'\' ngarupakeun salah sahiji \"pendekatan\" [[integral|definite integral]] tina [[Fungsi (matematik)|function]], biasana \"dinyatakan\" salaku jumlah beurat tina nilai fungsi dina titik husus dijero domain integration.\n(Tempo [[numerical integration]] keur \"quadrature rules\" lianna.)\nDina \'\'n\'\'-titik\'\'\'Gaussian quadrature rule\'\'\', dingaranan ieu sanggeus [[Carl Friedrich Gauss]], ngarupakeun quadrature rule constructed to yield an exact result for [[polynomial]]s of degree 2\'\'n\'\' − 1, \nby a suitable choice of the \'\'n\'\' points \'\'x\'\'\'\'i\'\' and \'\'n\'\' weights \'\'w\'\'\'\'i\'\'.\nThe domain of integration for such a rule is conventionally taken as [-1, 1], \nso the rule is stated as\n\n:\\int_{-1}^1 f(x)\\,dx \\approx \\sum_{i=1}^n w_i f(x_i)\n\nIt can be shown (see Press, et al., or Stoer and Bulirsch) that the evaluation points are just the [[root (mathematics)|root]]s of a polynomial belong to a class of [[orthogonal polynomials]].\n\n== Rules for the basic problem ==\n\nFor the integration problem stated above,\nthe associated polynomials are [[Legendre polynomials]].\nSome low-order rules for solving the integration problem are listed below.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Number of points, \'\'n\'\'Weights, \'\'w\'\'\'\'i\'\'Points, \'\'x\'\'\'\'i\'\'
120
21, 1-√(1/3), √(1/3)
35/9, 8/9, 5/9-√(3/5), 0, √(3/5)
\n\n== Change of interval for Gaussian quadrature ==\n\nAn integral over [\'\'a\'\', \'\'b\'\'] must be changed into an integral over [-1, 1] before applying the Gaussian quadrature rule. This change of interval can be done in the following way:\n\n:\n\\int_a^b f(t)\\,dt = \\frac{b-a}{2} \\int_{-1}^1 f\\left(\\frac{b-a}{2}x \n+ \\frac{a+b}{2}\\right)\\,dx \n\n\nAfter applying the Gaussian quadrature rule, the following approximation is obtained:\n\n:\n\\frac{b-a}{2} \\sum_{i=1}^n w_i f\\left(\\frac{b-a}{2}x_i + \\frac{a+b}{2}\\right)\n\n\n== Other forms of Gaussian quadrature ==\n\nThe integration problem can be expressed in a slightly more general way by introducing a weighting function ω into the integrand,\nand allowing an interval other than [-1, 1].\nThat is, the problem is to calculate \n\n: \\int_a^b \\omega(x)\\,f(x)\\,dx \n\nfor some choices of \'\'a\'\', \'\'b\'\', and ω.\nFor \'\'a\'\' = -1, \'\'b\'\' = 1, and ω(\'\'x\'\') = 1, \nthe problem is the same as that considered above.\nOther choices lead to other integration rules.\nSome of these are tabulated below.\nEquation numbers are given for Abramowitz and Stegun (A&S).\n\n\n\n \n \n \n \n\n\n \n \n \n \n\n \n \n \n \n\n\n \n \n \n \n\n\n \n \n \n \n\n
\'\'\'Interval\'\'\' \'\'\'ω(\'\'x\'\')\'\'\' \'\'\'Orthogonal polynomials\'\'\' \'\'\'A&S\'\'\'
[-1, 1] 1\\, [[Legendre polynomials]] Eq. 25.4.29
[-1, 1] \\frac{1}{\\sqrt{1 - x^2}} [[Chebyshev polynomials]] Eq. 25.4.38
[0, ∞) e^{-x}\\, [[Laguerre polynomials]] Eq. 25.4.45
(-∞, ∞) e^{-x^2} [[Hermite polynomials]] Eq. 25.4.46
\n\n=== Error estimates ===\n\nThe error of a Gaussian quadrature rule can be stated as follows (theorem 3.6.24 in Stoer and Bulirsch).\nFor an integrand which has 2\'\'n\'\' continuous derivatives,\n\n: \\int_a^b \\omega(x)\\,f(x)\\,dx - \\sum_{i=1}^n w_i\\,f(x_i)\n = \\frac{f^{(2n)}(\\xi)}{(2n)!} \\, \\|p_n\\|^2 \n\nfor some ξ in (\'\'a\'\', \'\'b\'\'), where \'\'p\'\'\'\'n\'\' is the orthogonal polynomial of order \'\'n\'\'.\n\nStoer and Bulirsch remark that this error estimate is inconvenient in practice,\nsince it may be difficult to estimate the 2\'\'n\'\'\'th derivative,\nand furthermore the actual error may be much less than a bound established by the derivative.\nAnother approach is to use two Gaussian quadrature rules of different orders,\nand to estimate the error as the difference between the two results. \nFor this purpose,\nGauss-Kronrod rules can be useful.\n\n=== Gauss-Kronrod rules ===\n\nIf the interval [\'\'a\'\', \'\'b\'\'] is subdivided,\nthe evaluation points of the new subintervals generally do not coincide with the previous evaluation points,\nand thus the integrand must be evaluated at every point.\n\'\'Gauss-Kronrod rules\'\' are Gaussian quadrature rules that are modified to make some of the evaluation points coincide after subdivision.\nThe difference between the results before and after subdivision can be taken as an estimate of the error of approximation,\nso such an approach can increase the accuracy achieved for a given number of function evaluations.\nThe algorithms in QUADPACK (see below) are based on Gauss-Kronrod rules.\n\n== References ==\n\n* Milton Abramowitz and Irene A. Stegun, eds. \'\'Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables\'\'. New York: Dover, 1972. \'\'(See Section 25.4.)\'\'\n\n* Robert Piessens, Elise de Doncker-Kapenga, C.W. Überhuber, D.K. Kahaner. \'\'QUADPACK, A subroutine package for automatic integration\'\'. Springer Verlag, 1983. \'\'(Reference guide for QUADPACK.)\'\'\n\n* William H. Press, Brian P. Flannery, Saul A. Teukolsky, William T. Vetterling. \'\'Numerical Recipes in C\'\'. Cambridge, UK: Cambridge University Press, 1988. \'\'(See Section 4.5.)\'\'\n\n* Josef Stoer and Roland Bulirsch. \'\'Introduction to Numerical Analysis\'\'. New York: Springer-Verlag, 1980. \'\'(See Section 3.6.)\'\'\n\n== External links ==\n\n* QUADPACK (part of SLATEC): description [http://www.netlib.org/slatec/src/qpdoc.f], source code [http://www.netlib.org/slatec/src]. QUADPACK is a collection of algorithms, in [[Fortran]], for numerical integration based on Gauss-Kronrod rules. [[SLATEC]] (at [[Netlib]]) is a large public domain library for numerical computing.\n\n[[Category:Numerical analysis]]','',13,'Budhi','20041224212555','',0,0,1,0,0.776656707645,'20041224212555','79958775787444'); INSERT INTO cur VALUES (974,0,'Bisnis','Sacara harti sajarah, watesan \'\'\'bisnis\'\'\' nunjukkeun aktivitas atawa karesep. Kecap ieu hartina beuki ngalegaan jadi (dimimitian dina [[18th century]]) sarua jeung \"an individual [[commerce|commercial]] enterprise\". Oge dina harti nu leuwih umum \"a nexus of commercial activities\".\n\nPeople establish businesses in order to perform [[economic]] activities. With some exceptions (such as [[cooperative]]s, corporate bodies, [[non-profit organization]]s and institutions of [[government]]), businesses exist to produce [[profit]]. In other words, the owners and operators of a business have as one of their main objectives to receive or generate a financial return for their time, effort and [[capital]]. \n\nOne can classify businesses in many different ways. [[service|Service businesses]] offer intangible [[product (business)|products]] and typically have different, usually smaller, [[capital]] requirements than [[manufacturer]]s. [[distribution (business)|Distributors]] will have different [[inventory]] control needs than a [[retail]]er or manufacturer. \n\nMost legal [[jurisdiction]]s specify the forms that a business can take, and a body of [[commercial law]] has developed for each type. Some common types include [[partnership]]s, [[corporation]]s (also called limited liability companies), and [[sole proprietorship]]s. \n\nAn [[industry]] can consist of a group of related businesses, such as the [[entertainment]] industry or the [[dairy]] industry. This definition resembles one of the more general meanings of \"business\", and the terms \'\'business\'\' and \'\'industry\'\' sometimes appear interchangeable. Thus a [[fisherman]] might say either (more colloquially) that he is in the \"[[fishing]] business\" or (somewhat grandiosely) that he works in the \"fishing industry\". Similarly, the word \"[[trade]]\" may serve as an equivalent of both \"business\" and \"industry\": Victorians might despise those \"in trade\", and one can still refer to working \"in the rag trade\", for example.\n\n\n\n== Jejer bisnis ==\n\n[[Wikipédia]] boga leuwih ti 1200 artikel bisnis jeung ékonomi, jadi teu sadayana dibéréndélkeun di dieu. Di dieu didaptarkeun sababaraha cabang bisnis nu utama. Pikeun jejer nu leuwih husus, tempo di subdaptarna.\n\n*[[Accounting]]\n**[[List of accounting topics]]\n*[[Advertising]]\n*[[Banking]]\n*[[Big Business]]\n*[[Business intelligence]]\n*[[Business school]]s\n*[[Capitalism]]\n*[[Commerce]]\n*[[Commercial law]]\n**[[List of business law topics]]\n*[[Companies]]\n**[[List of companies]]\n*[[Competition]]\n*[[Consumer electronics]]\n*[[Economics]]\n**[[Financial economics]]\n**[[Home economics]]\n**[[List of economics topics]]\n*[[Electronic commerce]]\n*[[business ethics|Ethics]]\n**[[List of business ethics, political economy, and philosophy of business topics]]\n*[[Finance]]\n**[[List of finance topics]]\n*[[Industry]]\n*[[Intellectual property]]\n*[[International trade]]\n**[[List of international trade topics]]\n*[[Insurance]]\n*[[Investment]]\n**[[Equity investment]]\n**[[Institutional Fund Management]]\n*[[List of business theorists]]\n*[[List of corporate leaders]]\n*[[List of commercial pairs]]\n*[[List of popular business books]]\n*[[Organizational development]]\n**[[List of human resource management topics]]\n**[[Administrative Assistant]]\n*[[Management]]\n**[[List of management topics]]\n*[[Management information systems]]\n**[[List of information technology management topics]]\n*[[Manufacturing]]\n**[[List of production topics]]\n*[[Marketing]]\n**[[List of marketing topics]]\n*[[Mass media]]\n*[[Process management]]\n**[[List of process management topics]]\n*[[Project management]]\n**[[List of project management topics]]\n*[[Real Estate]]\n**[[List of real estate topics]]\n*[[Small business]]\n*[[Tax]]\n*[[Theory of constraints]]\n**[[List of theory of constraints topics]]\n\n[[Category:Daptar jejer]]\n\n[[cs:Obchod]] [[da:Erhvervsliv]] [[de:Geschäft]] [[en:Business]] [[es:Negocios e industrias]] [[nl:Industrie in Nederland]] [[ja:ビジネス]] [[zh:工商业]]','/* Cutatan */',3,'Kandar','20050208085702','',0,0,0,0,0.528095735483,'20050208085702','79949791914297'); INSERT INTO cur VALUES (975,0,'Unbiased_estimator','#REDIRECT [[Bias (statistics)]]','',13,'Budhi','20040722012907','',0,1,0,1,0.927041809506,'20040722013016','79959277987092'); INSERT INTO cur VALUES (976,0,'Bias_(statistik)','Dina [[statistik]], [[estimator]] anu \'\'\'bias\'\'\' nyaeta hiji kaayaan numana nilai rata-rata saluhureun atawa sahandapeun nu ditaksir. Aya dua panilaian anu beda, hiji nempo kana kaayaan nu kacida gorengna, panempo sejenna nyaeta kana kaayaan dina waktu hasil nyieunna leuwih kapake sarta leuwih deukeut kana bebeneran tinimbang kana kaayaan \"unbiased.\" \n\n==The bad kind==\n\nOne meaning is involved in what is called a biased [[statistical sample|sample]]: If some elements are more likely to be chosen in the sample than others, and those that are have a higher or lower value of the quantity being estimated, the outcome will be higher or lower than the true value.\n\nA famous case of what can go wrong when using a biased sample is found in the 1936 US presidential election polls. The \'\'Literary Digest\'\' held a poll that forecast that [[Alfred E. Landon]] would defeat [[Franklin Delano Roosevelt]] by 57% to 43%. [[George Gallup]], using a much smaller sample (300,000 rather than 2,000,000), predicted Roosevelt would win, and he was right. What went wrong with the \'\'Literary Digest\'\' poll? They had used lists of telephone and automobile owners to select their sample. In those days, these were luxuries, so their sample consisted mainly of middle- and upper-class citizens. These voted in majority for Landon, but the lower classes voted for Roosevelt. Because their sample was biased towards wealthier citizens, their result was incorrect.\n\nThis kind of bias is usually regarded as a worse problem than [[statistical noise]]: Problems with statistical noise can be lessened by enlarging the sample, but a biased sample will not go away that easily. In particular, a [[meta-analysis]] will distill good data for studies that themselves suffer from statistical noise, but a meta-analysis of biased studies will be biased itself.\n\n==The sometimes-good kind==\n\nAnother kind of \'\'\'bias\'\'\' in statistics does not involve biased samples, but does involve the use of a statistic whose average value differs from the value of the quantity being estimated. Suppose we are trying to estimate the parameter \\theta using an [[estimator]] \\hat{\\theta} (that is, some function of the observed data). Then the bias of \\hat{\\theta} is defined to be\n\n:\n\\operatorname{E}(\\hat{\\theta})-\\theta.\n\n\nIn words, this would be \"the expected value of the estimator \\hat{\\theta} minus the true value \\theta\". This may be rewritten as\n\n\n:\n\\operatorname{E}(\\hat{\\theta}-\\theta).\n\n\nwhich would read \"the expected value of the difference between the estimator and the true value\" (the expected value of \\theta is \\theta). \n\nFor example, suppose \'\'X1, ..., Xn\'\' are independent and identically distributed random variables, each with a [[sebaran normal]] with expectation μ and variance σ2. Let\n\n:\\overline{X}=(X_1+\\cdots+X_n)/n\n\nbe the \"sample average\", and let\n\n:S^2=\\frac{1}{n}\\sum_{i=1}^n(X_i-\\overline{X}\\,)^2\n\nbe a \"sample variance\". Then \'\'S\'\'2 is a \"biased estimator\" of σ2 because\n\n:\\operatorname{E}(S^2)=\\frac{n-1}{n}\\sigma^2\\neq\\sigma^2.\n\nHowever, this biased estimator is, by the commonly used criterion of \"mean squared error\", actually better (but only very slightly) than the unbiased estimator that results from putting \'\'n − 1\'\' in the denominator where \'\'n\'\' appears in the definition of \'\'S\'\'2 above. Even then the [[square root]] of the unbiased estimator of the population [[varian]] is not an unbiased estimator of the population [[simpangan baku]]; for a non-linear function \'\'f\'\' and an unbiased estimator \'\'U\'\' of a parameter \'\'p\'\', \'\'f\'\'(\'\'U\'\') is usually not an unbiased estimator of \'\'f\'\'(\'\'p\'\'). \n\nA far more extreme case of a biased estimator being better than any unbiased estimator is well-known: Suppose \'\'X\'\' has a [[Poisson distribution]] with expectation λ. It is desired to estimate\n\n:\\operatorname{P}(X=0)^2=e^{-2\\lambda}.\\quad\n\nThe only function of the data constituting an unbiased estimator is\n\n:\\delta(X)=(-1)^X.\\quad\n\nIf the observed value of \'\'X\'\' is 100, then the estimate is 1, although the true value of the quantity being estimated is obviously very likely to be near 0, which is the opposite extreme. And if \'\'X\'\' is observed to be 101, then the estimate is even more absurd: it is -1, although the quantity being estimated obviously must be positive. The (biased) [[maximum likelihood|maximum-likelihood estimator]]\n\n:e^{-2X}\\quad\n\nis better than this unbiased estimator in the sense that the [[mean kuadrat kasalahan]]\n\n:e^{-4\\lambda}-2e^{\\lambda(1/e^2-3)}+e^{\\lambda(1/e^4-1)}\n\nis smaller. Compare the unbiased estimator\'s MSE of\n\n:1-e^{-4\\lambda}\n\nThe MSE is a function of the true value λ. The bias of the maximum-likelihood estimator is:\n\n:e^{-2\\lambda}-e^{\\lambda(1/e^2-1)}.\n\nThe bias of maximum-likelihood estimators can be substantial. Consider a case where \'\'n\'\' tickets numbered from 1 through to \'\'n\'\' are placed in a box and one is selected at random, giving a value \'\'X\'\'. If \'\'n\'\' is unknown, then the maximum-likelihood estimator of \'\'n\'\' is \'\'X\'\', even though the expectation of \'\'X\'\' is only \'\'n\'\'/2; we can only be certain that \'\'n\'\' is at least \'\'X\'\' and is probably more. In this case, the natural unbiased estimator is 2\'\'X\'\'.\n\n==Tempo ogé==\n\n*[[bias]] disambiguation\n*[[confirmation bias]]\n*[[publication bias]]\n*[[selection bias]]\n\n\n[[es:sesgo]]','',13,'Budhi','20050218012847','',0,0,0,0,0.318493885136,'20050218012847','79949781987152'); INSERT INTO cur VALUES (977,0,'Hirup','\'\'\'Hirup\'\'\' ngarupakeun konsép multiharti tanpa dadaran nu basajan, sabab mindeng dilarapkeun kana rupa-rupa hal. \'\'[[WordNet]]\'\' méré opat welas harti pikeun kecap \"life\", sedengkeun Kamus Wéb [[Longman]] méré 35 harti.\n\nArtikel ieu ngadadarkeun harti utama dina [[élmu hirup]]; tumbu ka harti séjén bisa ditempo di bagian [[Hirup#Artikel nu patali|artikel nu patali]] di handap.\n\n==Ngahartikeun konsép hirup==\n\n\'\'\'Hirup\'\'\' mibanda sababaraha harti dina jihat biologi —\n\n* \"hirup\" nu nujul ka prosés nu keur lumangsung nu nu patali jeung mahluk hirup;\n* \"hirup\" nu nujul ka mangsa antara [[babar|wedal]] jeung [[paéh]]na hiji [[organisme]];\n* \"hirup\" nu nujul ka \'\'kaayaan/wujud\'\' nalika geus dilahirkeun saméméh paéh.\n\nSésa bagian ieu museur ka harti nu ahir — naon nu jadi dasar pikeun nyebutkeun yén hiji éntitas téh hirup (mahluk hirup)? \n\nIt would be relatively straightforward to offer a practical set of guidelines if one\'s only concern were life on [[Earth]] as we know it (see [[biosphere]]), but as soon as one considers questions about life\'s [[Origin of life (disambiguation)|origin]]s on Earth, or the possibility of [[extraterrestrial life]], or the concept of [[artificial life]], it becomes clear that the question is fundamentally difficult and comparable in many respects to the problem of defining [[intelligence (trait)|intelligence]].\n\n===A conventional definition===\n\nIn [[biology]], an [[entity]] has traditionally been considered to be alive if it exhibits all the following phenomena at least once during its [[existence]]:\n\n#[[Growth]]\n#[[Metabolism|Metabolism]], consuming, transforming and storing [[energy]]/[[mass]]; growing by absorbing and reorganizing mass; excreting waste\n#Motion, either moving itself, or having internal motion\n#[[Reproduction|Reproduction]], the ability to create entities that are similar to itself\n#Response to [[stimulus|stimuli]] - the ability to measure properties of its surrounding [[environment]], and act upon certain conditions.\n\nThese criteria are not without their uses, but their disparate nature makes them unsatisfactory from a number of perspectives; in fact, it is not difficult to find counterexamples and examples that require further elaboration. For example, according to the above definition, one could say:\n\n*[[fire]] is alive. (This could be remedied by adding the requirement of locality, where there is an obvious feature that delineates the spatial extension of the living being, such as a [[cell membrane]].)\n*male [[mule]]s are not alive as they are [[sterility|sterile]] and cannot reproduce.\n*[[virus (biology)|viruses]] are not alive as they do not grow.\n\n[[Biologist]]s who are content to focus on terrestrial [[organism]]s often note some additional signs of a \"living organism\", including these:\n# Living organisms contain [[molecular]] components such as: [[carbohydrate]]s, [[lipid]]s, [[nucleic acid]]s, and [[protein]]s.\n# Living organisms \'\'require\'\' both energy and matter in order to continue living.\n# Living organisms are composed of at least one [[cell (biology)|cell]].\n# Living organisms maintain [[homeostasis]]. \n# [[Species]] of living organisms will [[evolution|evolve]].\n\nAll life on Earth is based on the [[chemistry]] of [[carbon]] compounds. Some assert that this must be the case for all possible forms of life throughout the universe; others describe this position as \'[[carbon chauvinism]]\'.\n\n===Other definitions===\nOther definitions include:\n*[[Francisco Varela]] and [[Humberto Maturana]]\'s definition of life (also widely used by [[Lynn Margulis]]) as an [[autopoiesis|autopoietic]] (self-producing), [[cai|water]] based, [[lipid]]-[[protein]] bound, [[carbon]] metabolic, [[nucleic acid]] replicated, protein readout [[system]]\n*\"a system of inferior negative feedbacks subordinated to a superior positive [[feedback]]\" ([http://www.mol.uj.edu.pl/~benio/cyber_def_life.pdf J. theor Biol. 2001])\n*Tom Kinch\'s definition of life as a highly organized auto-cannibalizing system naturally emerging from conditions common on planetary bodies, and consisting of a population of replicators capable of mutation, around each set of which a homeostatic metabolizing organism, which actively helps reproduce and/or protect the replicator(s), has evolved\n*[[Stuart Kauffman]]\'s definition of life as an [[autonomous agent|autonomous agent or autonomous agents]] capable of reproducing itself or themselves, and of completing at least one [[thermodynamic work cycle]]\n\n===Descent with modification: a \"useful\" characteristic===\n\nA useful characteristic upon which to base a definition of life is that of [[common descent|descent]] with modification: the ability of a life form to produce offspring that are like its parent or parents, but with the possibility of some variation due to [[chance]]. Descent with modification is sufficient by itself to allow [[evolution]], assuming that the variations in the offspring allow for differential survival. The study of this form of heritability is called [[genetics]]. In all known life forms (assuming [[prion]]s are not counted as such), the genetic material is primarily [[DNA]] or the related molecule, [[RNA]]. Another exception might be the [[software]] code of certain forms of [[computer virus (computing)|viruses]] and programs created through [[genetic programming]], but whether [[computer]] programs can be alive even by this definition is still a matter of some contention.\n\n===Exceptions to the common definition===\n\nNote that many individual organisms are incapable of reproduction and yet are still generally considered to be \"alive\"; see [[mule]]s and [[ant]]s for examples. However, these exceptions can be accounted for by applying the definition of life on the level of entire [[species]] or of individual [[gene]]s. (For example, see \'\'[[kin selection]]\'\' for information about one way by which non-reproducing individuals can still enhance the spread of their genes and the survival of their species.)\n\nViruses reproduce, flames grow, some software programs mutate and evolve, future software programs will probably evince (even high-order) behavior, machines move, and proto-life, consisting of metabolizing cells without reproduction apparatus, can have existed. Still, some would not call these entities alive. Generally, all five characteristics are required for a population to be considered alive.\n\n==Origin of life==\n\n\'\'Main article:\'\' [[Origin of life]]\n\nThere is no truly \"standard\" model of the origin of life, however most currently accepted models build in one way or another upon the following discoveries, which are listed in a rough order of postulated emergence:\n\n#Plausible pre-biotic conditions result in the creation of the basic small molecules of life. This was demonstrated in the [[Miller experiment|Urey-Miller experiment]].\n#[[Phospholipid]]s spontaneously form [[lipid bilayer]]s, the basic structure of a [[cell membrane]].\n#Procedures for producing random [[RNA]] molecules can produce \"[[ribozyme]]s\", which are able to produce more of themselves under very specific conditions.\n\nThere are many different hypotheses regarding the path that might have been taken from simple organic molecules to protocells and metabolism. Many of the possibilities have tended to fall into either \"[[gene]]s-first\" or \"[[metabolism]]-first\", a recent trend is the emergence of hybrid models that combine aspects of both.\n\n==The possibility of extraterrestrial life==\n\n[[As of 2004]], [[Earth]] is the only planet in the [[universe]] known by humans to support life. The question of whether life exists elsewhere in the universe remains open, but analyses such as the [[Drake equation]] have been used to estimate the probability of such life existing. There have been a number of false alarms of life elsewhere in the universe, but none of these apparent discoveries have so far survived scientific scrutiny.\n\nCurrently, the closest that scientists have come to finding extraterrestrial life is fossil evidence of possible [[bacteria]]l life on [[Mars (planet)|Mars]] (via the [[ALH84001]] meteorite). Searches for extraterrestrial life are presently focusing on planets and moons believed to possess liquid water, presently or in the past. Recent evidence from the NASA rovers [[MER-A|Spirit]] and [[MER-B|Opportunity]] supports the theory that Mars once had surface water. See \'\'\'[[Life on Mars]]\'\'\' for further discussion.\n\n[[Jupiter (planet)|Jupiter]]\'s moons are also considered good candidates for extraterrestrial life, especially [[Europa (moon)|Europa]], which seems to possess oceans of liquid water.\n\n==Related articles==\n*[[Afterlife]]\n*[[Artificial life]]\n*[[Biological life cycle]]\n*[[Half-life]]\n*[[Life Coaching]]\n*[[Life cycle]]\n*[[Life estate]]\n*[[Life expectancy]]\n*[[Life imprisonment]]\n*[[Life insurance]]\n*[[Life insurance tax shelter]]\n*[[Life peer]]\n*[[Life support]]\n*[[Life-death-rebirth deity]]\n*[[Materialism]] \n*[[Meaning of life]]\n*[[Origin of life]]\n*[[Origin of life (disambiguation)]]\n*[[Personal life]]\n*[[President for Life]]\n*[[Quality of life]]\n*[[Real life]]\n*[[Reincarnation]]\n*[[Still life]]\n*[[The Answer to Life, the Universe, and Everything]]\n*[[Tree of life]]\n*[[Value of life]] \n*[[Vitalism]]\n*[[Wheel of Life]]\n\n==Acuan==\n*Kauffman, Stuart. The Adjacent Possible: A Talk with Stuart Kauffman. Retrieved Nov. 30, 2003 from [[http://www.edge.org/3rd_culture/kauffman03/kauffman_index.html|http://www.edge.org/3rd_culture/kauffman03/kauffman_index.html]]\n\n==Tumbu kaluar==\n*[http://www.edge.org/3rd_culture/kauffman03/kauffman_index.html \"The Adjacent Possible: A Talk with Stuart Kauffman\"]\n\n[[ca:Vida]] [[da:Liv]] [[de:Leben (Biologie)]] [[en:Life]] [[es:Vida]] [[fi:Elämä]]\n[[fr:Vie]] [[ms:Benda hidup]] [[nl:Leven]] [[simple:Life]] [[zh-cn:生命]] [[zh-tw:生命/繁]]','',3,'Kandar','20041122084537','',0,0,0,0,0.807489640455,'20050302051215','79958877915462'); INSERT INTO cur VALUES (978,0,'Énzim','\'\'\'Énzim\'\'\' mangrupa [[protéin]], atawa [[kompléks protéin]], nu [[katalis|ngatalisan]] [[réaksi kimiawi]] dina awak [[organisme]]. Na jero [[sél (biologi)|sél biologis]] téh lumangsung loba pisan réaksi kimiawi, nu mun tanpa énzim bakal lambat pisan sahingga moal ngadukung [[hirup|kahirupan]]. Énzim ngagancangkeun réaksi nepi ka rébuan kali lipet. \n\n\'\'Énzim RNA\'\' atawa \"[[ribozim]]\" dijieunna tina RNA, lain protéin. Umumna ribozim ukur ngatalisan \'\'[[RNA splicing]]\'\'.\n\n==Struktur==\nHiji énzim bisa mangrupa [[protéin]] badag nu diwangun ku sababaraha ratus [[asam amino]], atawa sababaraha protéin nu polah babarengan salaku hiji unit.\n\nÉnzim ngandung [[sisi aktif]], [[sisi beungkeut]] nu meungkeut [[substrat]] nalika réaksi dikatalisan. \n\nUnggal bagéan énzim biasana mibanda tujuan/pungsi pangatur atawa struktural.\n\n==Pungsi==\nÉnzim ngatalisan réaksi kimiawi.\n\n===Peran énzim dina réaksi kimiawi===\nÉnzim bisa ngagabungkeun dua atawa leuwih réaksi sahingga réaksi nu sacara térmodinamis nguntungkeun bisa dipaké pikeun \"nyetir\" réaksi séjénna nu sacara térmodinamis teu nguntungkeun. Salasahiji conto nu pangilaharna nyaéta énzim nu ngamangpaatkeun défosforilasi [[Adénosin trifosfat|ATP]] pikeun réaksi kimiawi séjén nu teu patali.\n\n===Laju réaksi dimédiasi énzim===\nÉnzim bisa ningkatkeun [[laju réaksi]] ku jalan milih atawa narabas jalur réaksi nu [[énergi aktivasi]]na handap, sahingga leuwih gampang kajadian réaksina. The overall [[rate of enzyme mediated reactions]] depends on many factors.\n\n[[image:aktivasi.png]]
\n\'\'Diagram réaksi katalitis, nunjukkeun énergi nu dipikabutuh (E) ngalawan waktu (t). \'\'\n\nSubstrat (A jeung B) perlu énergi nu badag (\'\'E\'\'1) pikeun ngahontal kaayaan transisi A...B, nu saterusna jadi produk ahir (AB). Énzimna (E) nyiptakeun \'\'microenvironment\'\' sahingga A jeung B bisa ngahontal kaayaan transisi (A...E...B) kalawan leuwih gampang, ngurangan jumlah énergi nu dipikabutuh (\'\'E\'\'2). Hasilna, réaksina leuwih gampang sahingga ningkatkeun laju réaksi.\n\n===Kaspésifikan===\nÉnzim biasana spésifik dina réaksi nu dikatalisanana sarta [[substrat]] nu aub dina réaksina. Sipat struktur kompleméntér antara énzim jeung substrat ngarupakeun hal nu penting dina hal ieu (Gbr. 2). \n\n[[image:two_substrates.png]]
\n\'\'\'Gambar 2:\'\'\' Hiji énzim (E) ngatalisan réaksi dua substrat (S1 jeung S2) pikeun ngabentuk hiji hasil (P). Énzim bisa migawé nepi ka sababaraha yuta réaksi katalitik unggal detikna. Pikeun nangtukeun laju maximum réaksi énzimatik, konsentrasi substrat dironjatkeun nepi ka kabentukna hasil aya dina laju nu tetep (Gbr. 3). Ieu ngarupakeun laju maximum (\'\'V\'\'max, tina \'\'velocity\'\') énzim. Dina kaayaan kieu, sadaya loka aktif énzim pinuh/jenuh ku substrat. Hal ieu diajengkeun taun 1913 ku [[Leonor Michaelis]] jeung [[Maud Menten]]. Kusabab konsentrasi substrat nalika \'\'\'V\'\'\'max teu bisa diukur sacara tepat, énzim dicirikeun ku konsentrasi substrat nalika laju réaksina satengah ti maximumna. Konsentrasi substrat ieu disebut [[konstanta Michaelis-Menten]] (\'\'K\'\'M). Lolobana énzim nuturkeun [[kinetik Michaelis-Menten]].\n\n===Jalur métabolis===\nSababaraha énzim bisa gawé bareng ngawangun hiji susunan husus, nyiptakeun [[jalur métabolis]]. Dina hiji jalur métabolis, hiji énzim nyokot produk énzim séjén salaku substrat. Satutasna réaksi katalitis, produkna dibikeun ka énzim séjénna. Produk ahir jalur sarupa kitu kadang jadi [[inhibitor]] pikeun salasahiji énzim-énzim na awal jalur (biasana lengkah kahiji nu teu bisa balik, disebut \'\'committed step\'\'), sahingga ngatur jumlah produk ahir nu dijieun ku jalur éta.\n\n[[image:feedback_inhibition.png]]
\n\'\'\'Gambar 6:\'\'\' Mékanisme inhibisi eupan-balik nu ilahar.\n# The basic feedback inhibition mechanism, where the product (P) inhibits the committed step (A->B).
\n# \'\'Sequential feedback inhibition.\'\' The end products P1 and P2 inhibit the first committed step of their individual pathway (C->D or C->F). If both products are present in abundance, all pathways fron C are blocked. This leads to a buildup of C, which in turn inhibits the first common committed step A->B.\n# \'\'Enzyme multiplicity.\'\' Each end product inhibits both the first individual committed step and one of the enzymes performing the first common committed step.\n# \'\'Concerted feedback inhibition.\'\' Each end product inhibits the first individual committed step. \'\'Together\'\', they inhibit the first common committed step.\n# \'\'Cumulative feedback inhibition.\'\' Each end product inhibits the first individual committed step. Also, each end product \'\'partially\'\' inhibits the first common committed step.\n\n==Modél mékanis-kuantum katalisis énzim==\nKuliah \"Quantum Theory of some Biochemical Reactions\" nu didugikeun na Kongrés Biofisis Internasional IV (Moscow, 1972) ku [[Revaz Dogonadze|R.R. Dogonadze]] jeung [[Zurab Urushadze|Z.D. Urushadze]] ngarumuskeun modél [[mékanik kuantum|mékanis kuantum]] munggaran ngeunaan bentuk pangbasajanna katalisis énzim. Taun 1972-1973, hasil gawé M.V. Volkenshtein, R.R. Dogonadze, A.K. Madumarov, Z.D. Urushadze, jeung Yu.I. Kharkats ngarumuskeun modél (fisik) mekanis-kuantum katalisis énzim. Karya ieu ngabuktikeun peran [[konformasi|transformasi konformasional]] dina réaksi katalitis.\n\n==Énzim jeung kaséhatan==\n\nÉnzim dipikabutuh ku organisme hirup, gangguan na \'\'hiji énzim\'\' ti kira 2.000 nu aya na awak urang bisa ngakibatkeun kasakit parna nu bisa nepi ka tiwasna. Hiji conto kasakit nu disababkeun ku gangguan fungsi hiji énzim nyaéta [[fénilketonuria]] (PKU). Énzim [[fénilalanin hidroxilase]], nu kuduna ngarobah asam amino ésénsil fénilalanin jadi tirosin teu bisa meta, sahingga fénilalanin numpuk nu ngakibatkeun rétardasi méntal.\n\nÉnzim na awak manusa bisa ogé dipangaruhan ku inhibitor. [[Aspirin]], misalna, nyegah énzim nu ngahasilkeun [[prostaglandin]] (\'\'messenger\'\' [[inflamasi]]), sahingga suppressing pain and inflammation. Énzim ogé dimangpaatkeun dina produk sapopoé kayaning deterjén, nu nyepetkeun réaksi kimia meresihan papakéan (misalna, meresihan noda getih).\n\n==Énzim cerna jeung métabolik==\n\nGizi pikeun sato gumantung ka [[énzim cerna]] kayaning [[amilase]], [[tripsin]], jeung [[kimotripsin]] na ciduh. Peran utamana nyéta pikeun nyerna dahareun sahingga zat gizina sadia pikeun prosés na bagian awak nu mikabutuhna.\n\nGolongan énzim séjénna nyaéta [[énzim métabolik]], nu peranna pikeun ngatalisan réaksi kimia dina unggal prosés na jero awak. Kalolobaan sél urang (iwal ti [[éritrosit]]), bakal hanaang ku oxigén najan oxigénna ngalayah lamun énzimna, sitokrom oxidase teu meta. Énzim ogé dipikabutuh pikeun kontraksi jeung rélaxasi otot. Mémang nyatana, tanpa dua golongan énzim ieu, kahirupan (cerna jeung métabolik) moal aya.\n\n== Konvénsi ngaran énzim ==\n\nDumasar konvénsi umum, ngaran hiji énzim ngawengku dadaran naon hancana, ditambah ahiran \"-ase\". Contona [[dehidrogénase alkohol]] jeung [[polimérase DNA]]. [[Kinase]] ngarupakeun énzim nu mindahkeun gugus [[fosfat]]. \n[[International Union of Biochemistry and Molecular Biology]] (IUBMB) geus ngembangkeun hiji sistim [[tatangaran]] pikeun énzim, nyéta [[nomer EC]]; unggal énzim digambarkeun ku hiji runtuyan opat angka nu dimimitian ku \"EC\". Nomer kahiji sacara lega ngagolongkeun énzim-énzim dumasar mékanismena:\n* EC 1 \'\'Oxidoreduktase\'\': ngatalisan réaksi [[oxidasi]]/réduksi\n* EC 2 \'\'Transferase\'\': mindahkeun [[gugus fungsi]] (misalna gugus métil atawa fosfat)\n* EC 3 \'\'Hidrolase\'\': ngatalisan [[hidrolisis]] rupa-rupa beungkeut\n* EC 4 \'\'Liase\'\': megatkeun rupa-rupa beungkeut ku cara nu lian ti hidrolisis jeung oxidasi\n* EC 5 \'\'Isomérase\'\': ngatalisan parobahan [[isomér]]isasi na hiji molekul\n* EC 6 \'\'Ligase\'\': ngagabungkeun dua molekul ku [[beungkeut kovalén]]\n\nTatangaran nu lengkep bisa disungsi di http://www.chem.qmul.ac.uk/iubmb/enzyme/\n\n== Énzim jeung kelas-kelas énzim ==\n*[[Adénilat siklase]]: meta dina [[transduksi sinyal]] ku jalan ngarobah [[Adénosin trifosfat|ATP]] jadi [[AMP siklik]]\n*[[Alkohol dehidrogénase]]: ngarecah [[alkohol]] jadi [[aldehid]] na ati jalma; nyiptakeun alkohol na [[férméntasi]] [[kapang]]\n*[[Alkalin fosfatase]]\n*[[Amilase]]: ngarecah aci jadi [[maltosa]], aya na [[ciduh]] sarta ogé dikaluarkeun ku pankréas\n*[[Énzim pangubah angioténsin]]\n*[[ATPase]]: énzim-énzim nu ngahidrilosis [[Adénosin trifosfat|ATP]] jadi [[ADP]] jeung [[fosfat]] anorganik pikeun ngarojong réaksi séjén nu sacara énergetik teu dipisuka\n*[[ATP sintase]]: nyipta ATP tina ADP, fosfat anorganik, jeung énergi\n*[[Autolisin]]: istilah umum pikeun énzim-énzim nu nyababkeun paéhna sél\n*Béta-galaktosidase: tempo laktase.\n*[[Beta-laktamase]]: ngancurkeun [[pénisilin]], mangrupa faktor wedukna [[baktéri]]\n*[[Katalase]]: ngarobah [[hidrogén péroxida]] jadi oxigén jeung cai\n*[[Kitinase]]: ngarecah [[kitin]]\n*[[Kolinésterase]]\n*[[Kimosin]]: better known as rennet, contained in the stomachs of many animals and causes milk to curdle\n*[[Kimotripsin]]: bisa nyerna [[protéin]]\n*[[Koénzim Q - sitokrom c réduktase]]: meta dina [[ranté alih éléktron]] ku jalan ngaréduksi [[sitokrom c]] sarta ngompa [[proton]] meuntas mémbran\n*[[Sitokrom c oxidase]]: titik ahir ranté alih éléktron, dimana [[oxigén]] diréduksi jadi cai\n*[[Sitokrom c peroxidase]] takes reducing equivalents from [[sitokrom c]] sarta ngaréduksi hidrogén péroxida jadi cai\n*[[Déiodinase]]: ngaktifkeun [[hormon tiroid]] ku jalan ngaleupaskeun [[iodin]]\n*[[Diastase]]: ngarecah [[aci]] jadi [[glukosa]]\n*[[Dihidrofolat réduktase]]: ngaréduksi [[asam folat|asam dihidrofolat]] jadi asam tétrahidrofolat]]\n*[[DNA girase]]\n*[[Glutamat dékarboxilase]]: nyintésis neurotransmitter [[GABA]] na otak\n*[[Glutation péroxidase]]: ngajaga sél ku jalan ngarobah [[hidrogén péroxida]] jadi cai\n*[[Isomérase]]: sadaya énzim nu ngarobah molekul hiji jadi salasahiji bentuk[[isomer]]na\n*[[Kinase]]: sadaya énzim nu ngatalisan alih gugus [[fosfat]]\n*[[Laktase]] (atawa béta-galaktosidase): ngarecah [[laktosa]] jadi [[galaktosa]] jeung [[glukosa]]\n*[[Ligase]]: sadaya énzim nu bisa nyambungkeun (\"\'\'ligate\'\'\") dua molekul ku [[beungkeut kovalén]]\n*[[Liase]]: sadaya énzim nu bisa ngaleungitkeun hiji gugus tina hiji molekul sahingga ngabentuk hiji beungkeut ganda atawa sabalikna.\n*[[Monoamina oxidase]] (MAO): ngoxidasi certain [[neurotransmitter]]s and biologically active amines\n*[[NADH déhidrogénase]]: kompléx kahiji na [[ranté alih éléktron]], mindahkeun [[éléktron]] ti [[NADH]] ka [[koénzim Q]] \n*[[Nitrogénase]]\n*[[Ornitin dékarboxilase]]: ngolah [[ornitin]] dina hambalan awal ngahasilkeun [[poliamina]]\n*[[Péroxidase]]: golongan énzim nu bisa ngarobah [[hidrogén péroxida]] atawa sanyawa sabangsana\n*[[Fénilalanin hidroxilase]] (PAH): \n*[[Fosfolipase]]\n*[[Polimérase]]: ngawangun ranté panjang [[polimér]] [[asam nukléat]] tina komponén-komponénna\n*[[Protéase]] (péptidase): énzim nu neukteuk [[beungkeut péptida]] [[protéin]]\n*[[Protéin kinase]]: énzim nu ngalihkeun hiji gugus fosfat ka hiji résidu [[asam amino]] na hiji protéin\n*[[Protéin fosfatase]]: énzim nu nyokot gugus fosfat tina résidu asam amino hiji protéin\n*[[Énzim réstriksi]]: énzim nu neukteuk [[DNA]] atawa [[RNA]] dina posisi nu tangtu\n*\'\'[[Reverse transcriptase]]\'\': digunakeun ku [[rétrovirus]] pikeun nranskripsikeun informasi tina [[RNA]] jadi [[DNA]]\n*[[RubisCO|Ribulosa bisfosfat karboxilase]]: fixes carbon in green plants.\n*[[RNAse]]: énzim nu bisa ngarecah [[RNA]] jadi nukléotida komponénna\n*[[Superoxida dismutase]]: ngarobah [[superoxida]] jadi [[oxigén]] jeung [[hidrogén péroxida]]\n*[[Tirosin kinase]]: énzim nu ngalihkeun gugus fosfat ka résidu [[tirosin]] na hiji protéin\n*[[Tirosinase]]\n*[[Uréase]]: ngahidrolisis [[uréa]] jadi [[karbon dioxida]] jeung [[amonia]]\n*[[Xantin oxidase]]: ngoxidasi [[hipoxantin]] jadi [[xantin]] sarta salajengna jadi [[asam urat]]\n\n==Purifikasi==\nKusabab énzim ngarupakeun [[protéin]], purifikasi énzim dimimitian ku [[purifikasi protéin]]. Unggal hambalan na prosedur purifikasi diponcorong kaaktifan énzimna.\n\n==Étimologi==\nTina [[basa Yunani]]: \"\'\'in ferment\'\'\".\n\n== Rujukan ==\n* Koshland D. The Enzymes, v. I, ch. 7, Acad. Press, New York, 1959\n* Perutz M. Proc.Roy.Soc., B 167, 448, 1967\n* M.V. Volkenshtein, R.R. Dogonadze, A.K. Madumarov, Z.D. Urushadze, Yu.I. Kharkats. Theory of Enzyme Catalysis.- \'\'Molekuliarnaya Biologia\'\', Moscow, \'\'\'6\'\'\', 1972, pp. 431-439 (Basa RusiaI, ihtisar dina basa Inggris)\n* M.V. Volkenshtein, R.R. Dogonadze, A.K. Madumarov, Z.D. Urushadze, Yu.I. Kharkats. Electronic and Conformational Interactions in Enzyme Catalysis.- In: E.L. Andronikashvili (Ed.), \'\'Konformatsionnie Izmenenia Biopolimerov v Rastvorakh\'\', Publishing House \"Nauka\", Moscow, 1973, pp. 153-157 (Basa Rusia, ihtisar dina basa Inggris)\n* R.R. Dogonadze, Z.D. Urushadze, V.K. Khidureli. Calculation of Kinetic Parameters of Reactions with the Conformational Transformations.- In: E.L. Andronikashvili (Ed.), \'\'Konformatsionnie Izmenenia Biopolimerov v Rastvorakh\'\', Publishing House \"Metsniereba\", Tbilisi, 1975, pp. 368-375 (Basa Rusia)\n\n== Tumbu kaluar ==\n* [http://us.expasy.org/enzyme/ ExPASy enzyme database], tumbu ka data sekuens [[Swiss-Prot]], éntri-éntri na database séjén sarta panéang pustaka nu patali\n* [http://www.biochem.ucl.ac.uk/bsm/enzymes/ PDBsum] tumbu ka data struktur énzim 3-D nu dipikanyaho dina [[Bang Data Protéin]]\n* [http://www.brenda.uni-koeln.de BRENDA], comprehensive compilation of information and literature references about all known enzymes; requires payment by commercial users\n* [http://bioinformatics.weizmann.ac.il/cards/ Weizmann Institute\'s Genecards Database], extensive database of protein properties and their associated genes.bling bling, fool\n\n[[Category:Énzim]]\n[[da:Enzym]] [[de:Enzym]] [[en:Enzyme]] [[eo:Enzimo]] [[es:Enzima]] [[fr:Enzyme]] [[ja:酵素]] [[nl:Enzym]] [[pl:Enzym]] [[simple:Enzyme]] [[sv:enzym]] [[it:Enzima]]','/* Tumbu kaluar */',3,'Kandar','20050208084914','',0,0,0,0,0.330117399958,'20050208084914','79949791915085'); INSERT INTO cur VALUES (979,0,'Timeline_of_geology','\'\'\'[[Timeline]] of [[geology]]\'\'\': see also [[geologic timescale]].\n\n* [[1620]] - [[Francis Bacon]] notices the jigsaw fit of the opposite shores of the Atlantic Ocean\n* [[1669]] - [[Nicolas Steno]] puts forward his theory that sedimentary strata had been deposited in former seas, and that fossils were organic in origin\n* [[1701]] - [[Edmund Halley]] suggests using the salinity and evaporation of the Mediterranean to determine the age of the Earth\n* [[1743]] - Sir [[Christopher Packe]] produces a geological map of south-east England\n* [[1746]] - [[Jean Etienne Guettard]] presents the first mineralogical map of [[France]] to the [[French Academy of Sciences]].\n* [[1760]] - [[John Michell]] suggests earthquakes are caused by one layer of rocks rubbing against another\n* [[1776]] - [[James Keir]] suggests that some rocks, such as those at the [[Giant\'s Causeway]], might have been formed by the crystallisation of molten lava\n* [[1779]] - [[Buffon|Comte de Buffon]] speculates that the Earth is older than the 6,000 years suggested by the Bible\n* [[1785]] - [[James Hutton]] presents paper entitled Theory of the Earth - earth must be old\n* [[1799]] - [[William Smith (geologist)|William Smith]] produces the first large scale geological map, of the area around [[Bath]]\n* [[1809]] - [[William Maclure]] conducts the first geological survey of the eastern United States\n* [[1830]] - Sir [[Charles Lyell]] publishes book, Principles of Geology, which describes the world as being several hundred million years old\n* [[1837]] - [[Louis Agassiz]] begins his glaciation studies which eventually demonstrate that the Earth has had at least one [[ice age]]\n* [[1862]] - [[Lord Kelvin]] attempts to find the age of the Earth by examining its cooling time and estimates that the Earth is between 20--400 million years old\n* [[1903]] - [[George Darwin]] and [[John Joly]] claim that radioactivity is partially responsible for the Earth\'s heat\n* [[1907]] - [[Bertram Boltwood]] proposes that the amount of lead in uranium and thorium ores might be used to determine the Earth\'s age and crudely dates some rocks to have ages between 410--2200 million years\n* [[1911]] [[Arthur Holmes]] uses radioactivity to date rocks, the oldest being 1.6 billion years old\n* [[1912]] - [[Alfred Wegener]] proposes that all the continents once formed a single landmass called Pangaea that broke apart via [[continental drift]]\n* [[1913]] - [[Albert Michelson]] measures [[tide]]s in the solid body of the Earth\n* [[1935]] - [[Charles Richter]] invents a logarithmic scale to measure the intensity of [[earthquake]]s\n* [[1953]] - [[Maurice Ewing]] and [[Bruce Heezen]] discover the [[Great Global Rift]] running along the [[Mid-Atlantic Ridge]]\n* [[1960]] - [[Harry Hess]] proposes that new sea floor might be created at mid-ocean rifts and destroyed at deep sea trenches\n* [[1963]] - [[F.J. Vine]] and [[D.H. Matthews]] explain the stripes of magnetized rocks with alternating magnetic polarities running parallel to mid- ocean ridges as due to sea floor spreading and the periodic geomagnetic field reversals\n* [[1980]] - Physicist [[Luis Alvarez]], his son, geologist [[Walter Alvarez]], and others propose that the impact of a large extra-terrestrial object caused the [[extinction]] of the [[dinosaur]]s at the [[Cretaceous-Tertiary_extinction_event|end of the Cretaceous Period]], about 65 million years ago.\n\n[[Category:Science timelines]]','',0,'133.66.133.191','20040722071133','',0,0,0,1,0.687323749385,'20040722071220','79959277928866'); INSERT INTO cur VALUES (980,0,'Geologic_timescale','A [[timeline]] of [[geologic period]]s in accordance with the dates and nomenclature proposed by the [[International Commission on Stratigraphy]].\n\n(not shown to scale)\n\n{| border=\"1\" cellspacing=\"0\" cellpadding=\"2\"\n|-\n! style=\"background:#efefef;\" | Years Ago3,6\n! style=\"background:#efefef;\" | [[Epoch]]\n! style=\"background:#efefef;\" colspan=\"2\" | [[Geologic period|Period/Age]]4,5\n! style=\"background:#efefef;\" | [[Era]]\n! style=\"background:#efefef;\" | [[Eon]]\n! style=\"background:#efefef;\" | Major Events\n|-\n| Present day\n| [[Holocene]]\n| colspan=\"2\" rowspan=\"2\" | [[Quaternary]]\n| rowspan=\"7\" | [[Cenozoic]]\n| rowspan=\"17\" | [[Phanerozoic]]\n|  \n|-\n| 11,430\n| [[Pleistocene]]\n| Extinction of many large [[mammal]]s. Evolution of fully modern [[human]]s\n|-\n| 1.81 million\n| [[Pliocene]]\n| rowspan=\"5\" | [[Tertiary]]\n| rowspan=\"2\" | [[Neogene]]\n| rowspan=\"3\" |  \n|-\n| 5.33 million\n| [[Miocene]]\n|-\n| 23.0 million\n| [[Oligocene]]\n| rowspan=\"3\" | [[Paleogene]]\n|-\n| 37.2 million\n| [[Eocene]]\n| Appearance of first \"modern\" [[mammals]]\n|-\n| 55.8 million\n| [[Paleocene]]\n|  \n|-\n| 65.5 million* \n| rowspan=\"25\" |  \n| colspan=\"2\" | [[Cretaceous]]\n| rowspan=\"3\" | [[Mesozoic]]\n| [[Dinosaur]]s reach peak, become extinct. Primitive [[placenta]]l mammals\n|-\n| 146 million\n| colspan=\"2\" | [[Jurassic]]\n| [[Marsupial]] mammals, first [[bird]]s, first [[flowering plants]]\n|-\n| 200 million\n| colspan=\"2\" | [[Triassic]]\n| First dinosaurs, [[Monotreme|Egg-laying mammals]]\n|-\n| 251 million* \n| colspan=\"2\" | [[Permian]]\n| rowspan=\"7\" | [[Paleozoic]]\n| [[Permian extinction]] event- 95% of life on Earth becomes extinct\n|-\n| 299 million\n| rowspan=\"2\" | [[Carboniferous]]1\n| [[Pennsylvanian]]\n| Abundant insects, first [[reptile]]s, [[coal]] forests\n|-\n| 318 million\n| [[Mississippian]]\n| Large primitive [[tree]]s\n|-\n| 359 million\n| colspan=\"2\" | [[Devonian period|Devonian]]\n| First [[Amphibia|amphibians]], [[clubmoss]]es and [[horsetail]]s appear, [[progymnosperms]] (first seed bearing plants) appear\n|-\n| 416 million*\n| colspan=\"2\" | [[Silurian]]\n| First land plant fossils \n|-\n| 443 million* \n| colspan=\"2\" | [[Ordovician]]\n| [[Invertebrate]]s dominant\n|-\n| 488 million* \n| colspan=\"2\" | [[Cambrian]]\n| Major diversification of life in the [[Cambrian explosion]]\n|-\n| 542 million* \n| colspan=\"2\" | [[Ediacaran]]\n| rowspan=\"3\" | [[Neoproterozoic]]\n| rowspan=\"10\" | [[Proterozoic]]2\n| First [[metazoa|multi-celled animals]]\n|-\n| 600 million \n| colspan=\"2\" | [[Cryogenian]]\n| Possible [[snowball Earth]] period\n|-\n| 850 million \n| colspan=\"2\" | [[Tonian]]\n| rowspan=\"4\" |  \n|-\n| 1.0 billion\n| colspan=\"2\" | [[Stennian]]\n| rowspan=\"3\" | [[Mesoproterozoic]]\n|-\n| 1.2 billion\n| colspan=\"2\" | [[Ectasian]]\n|-\n| 1.4 billion\n| colspan=\"2\" | [[Calymmian]]\n|-\n| 1.6 billion\n| colspan=\"2\" | [[Statherian]]\n| rowspan=\"4\" | [[Paleoproterozoic]]\n| First [[Eukaryota|Complex single-celled life]]\n|-\n| 1.8 billion\n| colspan=\"2\" | [[Orosirian]]\n| rowspan=\"6\" |  \n|-\n| 2.05 billion\n| colspan=\"2\" | [[Rhyacian]]\n|-\n| 2.3 billion\n| colspan=\"2\" | [[Siderian]]\n|-\n| 2.5 billion\n| colspan=\"2\" rowspan=\"5\" |  \n| [[Neoarchean]]\n| rowspan=\"4\" | [[Archaean]]2\n|-\n| 2.8 billion\n| [[Mesoarchean]]\n|-\n| 3.2 billion\n| [[Paleoarchean]]\n|-\n| 3.6 billion\n| [[Eoarchean]]\n| [[Prokaryote|Simple single-celled life]]\n|-\n| 3.8 billion\n|  \n| [[Hadean]]2,7\n| 4.1 billion- Oldest known rock;
4.4 billion- Oldest known mineral;
4.57 billion- Formation of [[Earth]]\n|}\n\n1) In North America, the Carboniferous is subdivided into [[Mississippian]] and [[Pennsylvanian]] Periods.\n\n2) The [[Proterozoic]], [[Archean]] and [[Hadean]] are often collectively referred to as [[Precambrian|Precambrian Time]], and sometimes also as the [[Cryptozoic]].\n\n3) Dates are slightly uncertain with differences of a few percent between various sources being common. This is largely due to uncertainties in [[radiometric dating]] and the problem that deposits suitable for [[radiometric dating]] seldom occur exactly at the places in the geologic column where we would most like to have them. Dates with an * are radiometrically determined based on internationally agreed to [[GSSP|GSSPs]]. The dates quoted above are according to the [[International Commission on Stratigraphy]] 2004 time scale. All dates given are for the end of the interval in question.\n\n4) Paleontologists often refer to [[faunal stage]]s rather than geologic Periods. The Stage Nomenclature is quite complex. See [http://flatpebble.nceas.ucsb.edu/cgi-bin/bridge.pl?action=startScale Harland] for an excellent time ordered list of faunal stages. Also see the article on [[GSSP|GSSPs]].\n\n5) In common usage the [[Tertiary]]-[[Quaternary]] and [[Palaeogene|Paleogene]]-[[Neogene]]-[[Quaternary]] Periods are treated as equivalents to the [[Mesozoic]] and [[Paleozoic]] Periods. The term \'Period|Age\' (e.g. \'[[Neogene]] Period|Age\') is sometimes used instead of \'Period\'.\n\n6) The time shown in the \"Years Ago\" column is that of the end of the interval named beside it.\n\n7) [[Hadean]] was sometimes called [[Priscoan]].\n\n----\n{{Timeline Geological Timescale}}\n\n==See also==\n\n* [[Fossils and the geological timescale]]\n* [[Cosmological timeline]]\n* [[Lunar geologic timescale]]\n* [[Anthropocene]]\n* [[Logarithmic timeline]]\n\n==References==\n* [http://www.stratigraphy.org/geowhen/ GeoWhen Database ]\n* [http://www.stratigraphy.org/gssp.htm International Commission on Stratigraphy Time Scale ] \n\n[[Category:Geologic timescale]]\n\n[[ast:Escala de los tiempos xeolóxicos]]\n[[cy:Cyfnodau Daearegol]]\n[[da:Jordens historie]]\n[[de:Geologische Zeitskala]]\n[[en:Geologic timescale]]\n[[eo:Tera Biografio]]\n[[es:Geología histórica]]\n[[et:Geokronoloogiline skaala]]\n[[fr:Échelle des temps géologiques]]\n[[he:לוח הזמנים הגיאולוגי]]\n[[it:Ere geologiche]]\n[[ja:地質時代]]\n[[nl:Geologisch tijdvak]]\n[[pl:Tabela stratygraficzna]]\n[[pt:Geologia histórica]]\n[[ru:Геохронологическая шкала]]\n[[sv:Geologisk tidsskala]]\n[[uk:Геохронологічна таблиця]]\n[[zh:地质时代]]','HasharBot - warnfile Adding:ru,en,he,eo,ast,uk,pt',0,'81.220.107.14','20041110061405','',0,0,0,0,0.936910962657,'20041229220433','79958889938594'); INSERT INTO cur VALUES (981,0,'Sebaran_Cauchy','\'\'\'Sebaran Cauchy\'\'\' ngarupakeun [[probability distribution]] nu mibanda [[probability density function]]\n\n: f(x) = \\frac{1}{s\\pi[1 + ((x-t)/s)^2]} \n\ndimana \'\'t\'\' nyaeta \'\'parameter lokasi\'\' jeung \'\'s\'\' nyaeta \'\'parameter skala\'\'. Kasus husus lamun \'\'t\'\' = 0 jeung \'\'s\'\' = 1 disebut \'\'\'standar sebaran Cauchy\'\'\' nu mibanda probability density function\n\n: f(x) = \\frac{1}{\\pi (1 + x^2)}. \n\nSebaran Cauchy salawasna dipake conto keur ngahartikeun sebaran nu teu ngabogaan [[mean]], [[varian]] atawa [[moment (mathematics)|moments]] pangluhurkeun, sanajan [[mode]] jeung [[median]] duanana dihartikeun sarua jeung nol.\n\nLamun \'\'U\'\' jeung \'\'V\'\' ngarupakeun dua [[sebaran normal]] [[variabel acak]] bebas nu mibanda [[nilai ekspektasi]] 0 jeung [[varian]] 1, saterusna rasio \'\'U\'\'/\'\'V\'\' ngabogaan standar sebaran Cauchy.\n\nLamun \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun variabel random [[statistical independence|independent]], mibanda standar Cauchy, mangka sampel mean (\'\'X\'\'1 + ... + \'\'X\'\'\'\'n\'\')/\'\'n\'\' sarua ngabogaan standar sebaran Cauchy. Ieu conto keur ngabuktikeun yen hipotesa varian terhingga dina [[central limit theorem]] teu bisa dileungitkeun (sanajan bisa digantikeun ku nu sejen, dina kasus asumsi lemah). Keur nempo yen ieu bener, itung [[characteristic function|fungsi karakteristik]]\n\n:\\varphi(t)=E\\left(e^{it\\overline{X}}\\right)\n\nnumana \\overline{X} ngarupakeun sampel mean.\n\nSebaran Cauchy ngarupakeun [[sebaran-t student]] nu ngan mibanda hiji tingkat kabebasan.\n\nSebaran Cauchy kadangkala disebut \'\'\'sebaran Lorentz\'\'\'.\n\n[[de:Cauchy-Verteilung]]\n[[es:Distribución de Cauchy]]\n[[it:Variabile casuale di Cauchy]]\n\n== Tumbu kaluar ==\n* [http://mathworld.wolfram.com/CauchyDistribution.html MathWorld Cauchy Distribution]','',13,'Budhi','20041224103559','',0,0,1,0,0.903803482607,'20041224103559','79958775896440'); INSERT INTO cur VALUES (982,0,'Organisme','Dina [[biologi]] jeung [[ékologi]], \'\'\'organisme\'\'\' hartina [[mahluk hirup]].\n\n[[Asal-usul hirup]] sarta hubungan antara turunan pentingna ngarupakeun kontroversi. Dua hambalan nu utama bisa dibédakeun: [[prokariot]] jeung [[eukariot]]. Prokariot sacara umum dianggap ngawakilan dua [[tilu sistim karajaan|karajaan]] nu béda, nyaéta [[baktéri]] jeung [[Archaea]], nu antara masing-masing teu leuwih deukeut batan ka eukariot. Jungkrang antara prokariot jeung eukariot pada nganggap salaku tumbu penting nu pegat dina sajarah évolusionér. Dua [[organél]] eukariotik, nyéta [[mitokondria]] jeung [[kloroplas]], umumna dianggap diturunkeun ti baktéri [[hipotésis éndosimbiotik|éndosimbiotik]].\n\nFrase \'\'organisme kompléx\'\' ngagambarkeun organisme naon baé nu mibanda sél leuwih ti hiji (multisélular).\n\nCicirén nu biasana kapanggih di rupa-rupa organisme di antarana:\n* Usik\n* [[Dahar]]\n* [[Réspirasi]]\n* [[Tumuwuh]]\n* [[Baranahan]]\n* Kapekaan kana rangsangan\n\nTapi, hal-hal di luhur teu lumaku salawasna. Loba organisme nu teu bisa usik sacara mandiri, sarta teu ngaréspon sacara langsung ka lingkunganana. [[Mikroorganisme]] kayaning baktéri teu bisa ngalaksanakeun réspirasi, tapi malah migunakeun jalur kimiawi nu séjénna. Ogé loba organisme nu teu bisa baranahan.\n\n\'\'\'Organisasi Biologis\'\'\'\n\n*[[Atom]]\n**[[Molekul]]\n***[[Makromolekul]]\n****[[Organél]]\n*****[[Sél (biologi)|Sél]]\n******[[Jaringan]]\n*******[[Organ]]\n********[[Sistim Organ]]\n*********Organisme\n\n\'\'\'Organisasi lingkungan\'\'\'\n*[[Populasi]]\n**[[Komunitas]]\n***[[Ékosistim]]\n****[[Biosfir]]\n\n== Klasifikasi ==\n\nArtikel di handap ieu mangrupa titik bubuka pikeun béja ngeunaan klasifikasi organisme:\n* [[Klasifikasi ilmiah]] \n* [[Tata ngaran binomial]]\n* [[spésiés]]\n* [[subspésiés]]\n\n== Virus ==\n[[Virus]] dianggap lain organisme husus sabab teu mibanda kamampuh baranahan atawa [[métabolisme]] nu mandiri. Sabenerna mah pajeulit ieu téh, sabab sababaraha [[parasit]] jeung [[éndosimbiont]] teu mampuh hirup kalawan mandiri. Najan virus teu miboga [[énzim]] jeung molekul nu sakuduna aya na organisme hirup, maranéhna bisa migunakeun \'mesin genetik\' sél inangna. Asal-usulna can kapanggih, tapi aya kamungkinan mangrupa turunan ti inangna.\n\n== Umur hirup ==\nSalasahiji ukuran dasar organisme nyaéya [[umur hirup]]na. Sababaraha sato hirupna ngan itungan sapoé, sedengkeun sababaraha tutuwuhan bisa hirup réwuan taun. [[Senescence|Aging]] is important when determining life span of most organisms, bacterium, a virus or even a [[prion]].\n\n==Tumbu kaluar==\n*[http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Root NCBI Taxonomy entry: root] (rich)\n*[http://www.species2000.org/ Species 2000 Indexing the world\'s known species]. Species 2000 has the objective of enumerating all known species of plants, animals, fungi and microbes on Earth as the baseline dataset for studies of global biodiversity. It will also provide a simple access point enabling users to link from here to other data systems for all groups of organisms, using direct species-links.\n*[http://tolweb.org/tree/phylogeny.html The Tree of Life].\n*[http://news.bbc.co.uk/1/hi/sci/tech/944790.stm BBCNews: 27 September, 2000, When slime is not so thick] Citat: \"...It means that some of the lowliest creatures in the plant and animal kingdoms, such as slime and amoeba, may not be as primitive as once thought....\"\n**[http://www.spaceref.com/news/viewpr.html?pid=4742 SpaceRef.com, July 29, 1997: Scientists Discover Methane Ice Worms On Gulf Of Mexico Sea Floor]\n***[http://www.science.psu.edu/iceworms/iceworms.html The Eberly College of Science: Methane Ice Worms discovered on Gulf of Mexico Sea Floor] download Publication quality photos\n**[http://www.sb-roscoff.fr/Ecophy/PDF/00-Fisher-NatWis.pdf Artikel, 2000: Methane Ice Worms: Hesiocaeca methanicola. Colonizing Fossil Fuel Reserves]\n**[http://www.spaceref.com/news/viewnews.html?id=339 SpaceRef.com, May 04, 2001: Redefining \"Life as We Know it\"] \'\'Hesiocaeca methanicola\'\' In 1997, Charles Fisher, professor of biology at Penn State, discovered this remarkable creature living on mounds of methane ice under half a mile of ocean on the floor of the Gulf of Mexico.\n*[http://news.bbc.co.uk/1/hi/sci/tech/2585235.stm BBCNews, 18 December, 2002, \'Space bugs\' grown in lab] Citat: \"...\'\'Bacillus simplex\'\' and \'\'Staphylococcus pasteuri\'\'...\'\'Engyodontium album\'\'...The strains cultured by Dr Wainwright seemed to be resistant to the effects of UV - one quality required for survival in space....\"\n*[http://news.bbc.co.uk/1/hi/sci/tech/3003946.stm BBCNews, 19 June, 2003, Ancient organism challenges cell evolution] Citat: \"...\"It appears that this organelle has been conserved in evolution from prokaryotes to eukaryotes, since it is present in both,\"...\"\n*[http://www.anselm.edu/homepage/jpitocch/genbios/surveybi04.html Saint Anselm College: Survey of representatives of the major Kingdoms] Citat: \"...Number of [[kingdom (biology)|kingdom]]s has not been resolved...Bacteria present a problem with their diversity...[[Protista]] present a problem with their diversity...\", [http://www.anselm.edu/homepage/jpitocch/genbios/bi04syllabsu03.html Interactive Syllabus for General Biology - BI 04, Saint Anselm College, Summer 2003]\n*[http://www.personal.psu.edu/users/j/s/jsf165/Bio110.html Jacob Feldman: Stramenopila]\n*[http://www.abc.net.au/science/news/enviro/EnviroRepublish_828525.htm The largest organism in the world may be a fungus carpeting nearly 10 square kilometers of an Oregon forest, and may be as old as 8500 years.]\n\n==Tempo ogé==\n*[[superorganisme]]\n\n[[da:Organisme]] [[de:Lebewesen]] [[en:Organism]] [[fr:Organisme vivant]] [[ja:生物]] [[nl:Organisme]] [[pl:Organizm]] [[pt:Organismo]] [[sv:Organismer]] [[zh:生物]]','/* Life span */',3,'Kandar','20041123101603','',0,0,0,0,0.880693124086,'20041123101603','79958876898396'); INSERT INTO cur VALUES (983,0,'Karbohidrat','[[Image:D-fruktosa.png|88px|right|thumb|[[Fruktosa]] dina bentuk ranté-lempeng]]\n\'\'\'Karbohidrat\'\'\' (nurutkeun basa \'\'hidrat karbon\'\') nyaéta [[sanyawa kimiawi]] nu pungsina salaku perantara [[biologi|biologis]] primér pikeun neundeun atawa maké [[énergi]]; bentuk séjénna ngaliwatan [[gajih]] jeung [[protéin]]. Karbohidrat nu kaitung kompléks disebut [[polisakarida]]. \n\n== Struktur ==\n[[Image:D-glukosa.png|88px|right|thumb|[[Glukosa]] dina bentuk ranté-lempeng]]\nKarbohidrat murni ngandung [[atom]] [[karbon]], [[hidrogén]], jeung [[oksigén]]; dina [[nisbah]] 1:2:1 [[mol (unit)|molar]], nu méré [[rumus]] umum C\'\'x\'\'H2\'\'x\'\'O\'\'x\'\'. Tapi, loba karbohidrat penting nyimpang ti ieu rumus, kayaning [[déoksiribosa]]. Sakapeung sanyawaan nu ngandung unsur séjén ogv diaku salaku karbohidrat, kayaning [[kitin]], nu ngandung [[nitrogén]].\n\nKarbohidrat nu pangbasajanna nyaéta [[monosakarida]], nu mangrupa [[aldehid]] jeung [[keton]] leutik ranté-lempeng nu loba katambah ku gugus [[hidroksil]], biasana hiji di unggal karbon iwal gugus fungsionalnya. Karbohidrat séjén diwangun ku unit-unit monosakarida nu paregat ku [[hidrolisis]]. Nu ieu digolongkeun kana [[disakarida]], [[oligosakarida]], atawa [[polisakarida]], gumantung kana jumlah unit monosakarida nu nyusunna.\n\n==Monosakarida==\n[[Image:Ribosa.png|160px|left|thumb|[[Ribosa]]]]\n[[Monosakarida]] bisa dibagi jadi [[aldosa]], nu mibanda gugus [[aldehid]] na atom karbon kahiji, sarta [[ketosa]], nu husus mibanda gugus keton na atom karbon kadua. Bisa ogé dibagi-bagi jadi [[triosa]], [[tétrosa]], [[péntosa]], [[héksosa]], jeung saterusna gumantung jumlah atom karbon nu dipimilikna. Conto gampang, [[glukosa]] ngarupakeun [[aldohéksosa]], [[fruktosa]] mangrupa [[ketohéksosa]], sedengkeun [[ribosa]] mangrupa [[aldopéntosa]].\n\nSalajengna, ungal atom karbon nu boga gugus hidroksil (iwal nu mimiti jeung panungtung) boga sipat [[aktivitas optik|aktif optis]], sahingga karbohidrat bisa dibédakeun deui sanajan struktur dasarna sarua. Misal, [[galaktosa]] ngarupakeun aldohéksosa, tapi boga sipat nu béda ti glukosa sabab susunan atom-atomna teu sarua.\n\nStruktur ranté-lempeng nu digambarkeun di dieu ukur salasahiji tina bentuk monosakarida nu bisa jadi. Gugus aldehid atawa keton bisa meungkeut gugus gugus hidroksil ti atom karbon nu séjén ngabentuk [[hémiasétal]] atawa [[hémiketal]], nu dina kasus ieu aya sasak oksigén antara dua atom karbon, ngabentuk cingcin hétérosiklik. Cingcin nu diwangun ku lima jeung genep atom disebut bentuk furanosa jeung piranosa, nu aya dina kasatimbangan jeung bentuk ranté-lempeng.\n\nKudu ditengetkeun yén bentuk cingcin mibanda hiji deui karbon nu optik aktif batan bentuk ranté-lempeng, sarta ogé mibanda bentuk \'\'alfa\'\' jeung \'\'béta\'\' nu bulak-balik dina kasatimbangan. Ngan, mun aya réaksi karbohidrat jeung alkohol jadi [[asétal]] atawa [[ketal]], dua bentuk éta jadi béda. Ieu ngarupakeun tipe dasar tumbu antara unit-unit monosakarida tina karbohidrat nu leuwih gedé.\n\n== Disakarida ==\n\nDisakarida molekulna diwangun ku dua unit monosakarida. Beungkeutan antara dua gula éta ngawujud tina leupasna hiji atom hidrogén (H) ti hiji molekul jeung hiji gugus hidroksil ti nu hiji deui.\nDisakarida nu paling umum nyaéta [[sukrosa]] (gula bodas - dijieun tina hiji glukosa jeung hiji fruktosa), [[laktosa]] (gula susu - dijieun tina hiji glukosa jeung hiji galaktosa) sarta [[maltosa]] (dijieun tina dua glukosa).
\n[[Rumus kimiawi]] pikeun disakarida ieu nyaéta C12H22O11.\n\n==Gizi==\n[[Image:starchy-foods..jpg|thumb|Sababaraha sumber nu beunghar ku karbohidrat kompléks]]\n\nKalawan teges, karbohidrat teu dipikabutuh pikeun [[gizi manusa]] sabab protéin bisa dirubah jadi karbohidrat - diet tradisional aya nu ampir enol persén karbohidrat, bari jagjag walagri kalawan sampurna. Ngan, karbohidrat merlukeun cai nu (rélatif) leuwih saeutik pikeun nyerna batan protéin atawa lemak, sarta ogé mangrupa sumber penting énergi.\n\'\'\' Tempo ogé \'\'\'\n:[[Biokimia]]\n:[[Makromolekul]]\n\n===Katabolisme===\nAya tilu [[jalur métabolik]] [[katabolisme]] karbohidrat:\n#[[Glikolisis]]\n#[[Daur asam sitrat]]\n#[[Fosforilasi oksidatif]]\n\n===Simpenan [[glikogén]]===\nDisimpen pikeun dipaké nalika glukosa teu diserep ku saluran pencernaan.\n\n==Sumber-sumber karbohidrat==\n*[[Tutuwuhan]]\n\n==Tumbu kaluar==\n*[http://www.chem.qmw.ac.uk/iupac/2carb/ IUPAC-IUBMB Joint Commission on Biochemical Nomenclature (JCBN): Carbohydrate Nomenclature]\n* [http://www.cem.msu.edu/~reusch/VirtualText/carbhyd.htm Carbohydrates detailed]\n* [http://www.carbohydrate-counter.org/about-carbohydrates.php Ihtisar Karbohidrat]\n* [http://www.carb-counter.org/ Carb Counter]\n\n[[da:Kulhydrat]] [[de:Kohlenhydrate]] [[en:Carbohydrate]] [[es:Hidrato de carbono]]\n[[fi:Hiilihydraatti]] [[fr:Hydrates de carbone]] [[id:karbohidrat]] [[ja:炭水化物]] [[pl:Węglowodan]] [[zh:碳水化合物]]\n\n[[Category:Karbohidrat]]','',3,'Kandar','20041229052826','',0,0,1,0,0.073398151935,'20041229052826','79958770947173'); INSERT INTO cur VALUES (984,0,'Protéin','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n\'\'\'Protéin\'\'\' ngarupakeun [[sanyawa organik]] kompléks nu beurat molekulna gedé nu diwangun ku [[asam amino]] nu disambungkeun ku [[beungkeut péptida]]. Protéin ésénsil pikeun struktur jeung pungsi sadaya [[sél (biologi)|sél]] hirup ogé [[virus]].\nLoba protéin nu mangrupa [[énzim]] atawa [[subunit protéin|subunit]] énzim. Protéin séjén maénkeun pungsi struktural atawa mékanis, kayaning nu ngabentuk urat jeung sandi \"[[sitoskeleton]]\". Protéin ogé mangrupa sumber asupan pikeun [[organisme]] nu teu ngahasilkeun énergina sorangan tina cahya panonpoé. \n\nProtéin béda jeung [[karbohidrat]] utamana tina kandunganana nu loba [[nitrogén]] sarta saeutik [[walirang]] di sagigireun [[karbon]], [[oksigén]], jeung [[hidrogén]].\nProtéin ngarupakeun unsur utama [[hirup|mahluk hirup]] sarta mangrupa salasahiji golongan [[molekul]] utama nu diulik dina [[biokimia]]; munggaran kapanggih ku [[Jons Jacob Berzelius]] taun [[1838]].\n\n==Struktur==\nProtéin ngarupakeun ranté asam amino nu [[tilepan protéin|nilep]] jadi struktur 3-diménsi nu has. Bentuk nu ngawujud tina tilepan alami protéin disebutna \'\'[[bentuk asal]]\'\', nu ditangtukeun ku urutan asam aminona. Biokimiawan ngabédakeun struktur protéin jadi opat:\n* \'\'[[Struktur primér]]\'\': urutan asam amino \n* \'\'[[Struktur sékundér]]\'\': substruktur nu kapola--[[héliks alfa]] jeung [[lambar béta]]--atawa bagéan ranté nu [[koil acak|dianggap teu mibanda bentuk stabil]]. Struktur sékundér sipatna lokal, hartina bisa aya sababaraha motif sékundér dina hiji molekul protéin\n* \'\'[[Struktur térsiér]]\'\': the overall shape of a single protein molecule; the spatial relationship of the secondary structural motifs to one another\n* \'\'[[Struktur kuarternér]]\'\': bentuk atawa struktur nu dihasilkeun tina ngahijina sababaraha molekul protéin, biasana disebut \'\'subunit [[subunit protéin|protéin subunit]]\'\', nu pungsina salaku bagéan tina himpunan nu leuwih badag atawa [[kompléks protéin]].\n\nTambahan pikeun hambalan-hambalan struktur ieu, protéin bisa géséh antaran sababaraha struktur nu sarupa dina ngajalankeun pungsi biologisna. Dina kontéks susunan ulang ieu, struktur térsiér atawa kuarternérna biasa disebut salaku \"[[konformasi]]\", sedengkeun transisi di antarana disebut \'\'\'parobahan konformasi\'\'\'.\n\nStruktur primér ngawujud ku [[beungkeut péptida]] [[beungkeut kovalén|kovalén]], nu dijieun nalika [[biosintésis protéin|translasi]]. Struktur térsiér ngawujud ku ayana [[beungkeut hidrogén]], interaksi [[hidrofob|hidrofobik]], interaksi ionik, jeung/atawa [[beungkeut disulfida]]. \n\nProsés nalika struktur nu leuwih luhur ngawujud disebutna [[tilepan protéin]] (\'\'protein folding\'\') nu ngarupakeun kosékuénsi tina struktur primér. Najan polipéptida bisa mibanda leuwih ti hiji konformasi nilep nu stabil, unggal konformasi mibanda aktivitas biologis masing-masing, sarta ngan hiji konformasi nu dianggap konformasi aktif atawa asal.\n\nDua tungtung ranté asam amino disebutna [[tungtung terminal-C|terminal karboksi]] (terminal-C) jeung [[tungtung terminal-N|terminal amino]] (terminal-N) dumasar ayana gugus bébas na tungtungna.\n\n== Bang Data Protéin (\'\'The Protein Data Bank\'\', PDB) ==\nStruktur protéin bisa ditangtukeun ku [[kristalografi]] sinar-X, [[résonansi magnetik inti]] (nuclear magnetic resonance, NMR), jeung [[difraksi neutron]]. Struktur protéin nu diungkab ku métode ieu biasana disimpen di Bank Data Protéin nu bisa diaksés kalawan bébas di http://www.rcsb.org. Nepi ka Juni 2004, ampir 25,000 struktur protéin geus disimpen di dinya. Database ieu ogé nyimpen struktur asam nukléat kayaning [[DNA]] jeung [[RNA]], sarta saeutik data [[karbohidrat]].\n\n==Fungsi==\nProtéin milu sacara praktis na unggal fungsi nu dipigawé ku sél, kaasup pangaturan fungsi sélular kayaning [[transduksi sinyal]] jeung [[métabolisme]].\nPikeun conto, [[katabolisme]] protéin merlukeun ukur sababaraha énzim nu diistilahan [[protéase]].\n\n===Mékanisme pangaturan protéin===\nRupa-rupa molekul jeung ion bisa meungkeut sisi spésifik dina protéin. Sisi ieu disebutna [[sisi pameungkeut]] nu némbongkeun [[spésifisitas kimiawi]]. Partikel nu kabeungkeut disebutna [[ligan]]. Kakuatan beungkeutan protéin-ligan ngarupakeun sipat sisi pameungkeut nu dikenal salaku [[afinitas]].\n\nKusabab protéin milu sacara praktis na unggal fungsi nu dipigawé ku sél, mékanisme pikeun ngatur fungsi ieu gumantung ka kumaha ngatur aktivitas protéin. Pangaturan bisa mangrupa ngatur [[bentuk]] atawa [[kadar]] protéinna. Sababaraha bentuk pangaturan di antarana:\n\n*[[Modulasi allostérik]]: nalika bengkeutan hiji ligan na hiji situs na protéin mangaruhan beungkeutan ligan na situs séjén.\n*[[Modulasi kovalén]]: nalika modifikasi kovalén hiji protéin mangaruhan beungkeutan hiji ligan atawa sababaraha aspék séjén pungsi protéin.\n\n== Kabinékaan ==\nProtéin umumna mangrupa molekul badag, aya nu [[beurat molekular]]na nepi ka 3,000,000 (protéin otot [[titin]] mibanda subunit ranté tunggal 27000 asam amino). Ranté panjang asam amino kitu nu disebut sacara umum salaku protéin, nu pondok mah biasa disebut \"polipéptida,\" \"péptida\", atawa \"oligopéptida\" (jarang kasebut). Watesan pangbédana teu tangtu, najan polipéptida leutik kamungkinanana pikeun mibanda struktur tersiér sarta loba nu lumaku sarupaning [[hormon]] (saperti [[insulin]]) batan salaku énzim atawa unsur struktural.\n\nSacara umum protéin digolongkeun kana serat (filaméntos) leyur atawa nu patali-mémbran (tempo [[protéin membran integral]]). Ampir sakabéh [[katalis]] biologis nu dipikawanoh salaku [[énzim]] mangrupa protéin (sababaraha untuyan [[RNA]] dina ahir abad ka-20 geus ditunjukkeun mibanda sipat katalitik ogé). [[Panukeur]] (\'\'exchanger\'\') sarta [[kanal ion]] patali-membran nu mindahkeun substratna ti hiji tempat ka nu séjénna tapi teu dirobah; [[reséptor]], nu teu ngarobah substratna tapi ukur ngagiserkeun bentuk nalika meungkeut; sarta [[antibodi]], nu katémbong taya gawé lian ti meungkeut, sakabéhna ngarupakeun protéin ogé. Bahan serat nu nyusun [[sitoskeleton]] sél sarta kalolobaan struktur sato ogé mangrupa protéin: mikrotubul, [[aktin]], filamén panengah, [[kolagén]], sarta [[keratin]] ngarupakeun bagéan ti kulit, rambut, jeung \'\'[[cartilage]]\'\'. GOlongan séjén protéin motor kayaning [[myosin]], kinesin, jeung dynein. [[Otot]] sabagéan badagna diwangun ku protéin [[myosin]] jeung [[actin]].\n\n==Migawé protéin==\n\nProtéin mah pilihan dina nangtukeun ayana di mana téh, ukur bisa kapanggih dina kaayaan aktif atawa [[bentuk asal]] dina rentang [[pH]] nu heureut sarta dina kaayaan leyuran nu kadar [[éléktrolit]]na saeutik, ogé moal kapanggih dina [[cai sulingan]]. Protéin nu leungiteun bentuk asalna disebut \'\'[[denatured]]\'\'. Protéin kitu umumna teu mibanda [[struktur sekundér]] iwal koil acak. Protéin na bentuk asalna mindeng ogé disebut salaku nilep, \'\'folded\'\'.\n\nSalasahiji papanggihan abad ka-20 nu luar biasa nyaéta yén bentuk asal jeung \'\'denatured\'\' protéin bisa dibulak-balikkeun ku cara ngatur kalawan ati-ati kaayaan leyuran (misal ku [[dialisis]] bahan kimiawi nu ngakibatkeun denaturasi), protéin nu \'\'denatured\'\' bisa balik deui jadi bentuk asalna. Bahasan ngeunaan kumaha protéin bisa aya dina bentuk asalna ngarupakeun salasahiji lapang penting dina ulikan biokimia, disebutna ulikan [[tilepan protéin]].\n\nNgaliwatan [[rékayasa genetik]], para panalungtik bisa ngarobah urutan (ku kituna strukturna ogé), [[protein targeting|\"targeting\"]], karentanan kana pangaturan, sarta sipat-sipat protéin séjénna. Urutan genetik protéin nu béda bisa digabungkeun pikeun nyieun protéin [[chimera (protein)|\"chimeric\"]] nu mibanda sipat gabungan. Cara \"matri\" kieu ngawakilan salasahiji alat pangpentingna pikeun ahli biologi sél jeung molekular pikeun ngarobah jeung nalungtik kamaha gawéna sél. Lapang séjén panalungtikan protéin nyaéta ngusahakeun ngaréka protéin nu mibanda sipat atawa fungsi nu samasakali anyar, hiji widang nu katelah [[rékayasa protéin]] (\'\'protein engineering\'\').\n\n==Protéin jeung gizi== \n\nPikeun [[karnivora]], protéin ngarupakeun bagian panglobana dina [[nutrisi|kadaharanana]]. [[Métabolisme]] protéin dina jero awak ngaleupaskeun [[amonia]], zat nu toxik pisan. Salajengna dina ati ieu amonia dirobah jadi [[uréa]], bahan kimiawi nu leuwih teu toxik, nu [[ékskrési|dikaluarkeun]] dina [[urin|cikiih]]. Sababaraha sato malah ngarubah amonia jadi [[asam urat]].\n\n=== Gizi protéin pikeun manusa===\n\nDina jihat pangabutuh nutrisi manusa, protéin kabagi dina dua wujud: \'\'\'protéin lengkep\'\'\' nu ngandung sakabéh dalapan [[asam amino ésénsil|asam amino]] nu manusa teu bisa nyieunna, sedengkeun \'\'\'protéin teu lengkep\'\'\' kakurangan atawa ngan ngandung salasahiji/sawaréhna. Awak manusa bisa ngamangpaatkeun sakabéh asam amino nu diékstraks tina dahareun pikeun sintésis protéin anyar, tapi nu teu ésénsil teu kudu diasupan tina dahareun, sabab sél urang bisa nyieun sorangan. Dahareun turunan-[[sato]] ngandung sadaya asam amino, sedengkeun tatangkalan biasana ngandung sababaraha asam amino nu leuwih loba.\n\n==Tempo ogé==\n* [[Biokimia]]\n* [[Kristalografi]]\n* [[Dénaturasi protéin]]\n* [[Intéin]]\n* [[Péptida]]\n* [[Prion]]\n* [[Protéinoid]]\n* [[Protein structure prediction]]\n* [[Protein targeting]]\n* [[Protéom]]\n* [[Protéomik]]\n* [[Struktur Génomik]]\n\n[[Category:Binaraga]]\n[[Category:Protéin]]\n\n[[ca:Proteïna]]\n[[da:Protein]]\n[[de:Protein]]\n[[en:Protein]]\n[[eo:Proteino]]\n[[es:Proteína]]\n[[fi:Proteiini]]\n[[fr:Protéine]]\n[[he:חלבון]]\n[[it:Proteine]]\n[[ja:蛋白質]]\n[[ko:단백질]]\n[[minnan:Nn̄g-pe̍h-chit]]\n[[nl:Eiwit]]\n[[pl:Białko]]\n[[pt:Proteína]]\n[[ru:Белок]]\n[[simple:Protein]]\n[[sl:Beljakovina]]\n[[sv:Protein]]\n[[th:โปรตีน]]\n[[tr:Protein]]\n[[zh:蛋白质]]','warnfile Adding:th,pt,ru,tr,ca,it,sl,simple,he,minnan',42,'Shizhao','20050303143934','',0,0,1,0,0.233500878435,'20050303143934','79949696856065'); INSERT INTO cur VALUES (985,0,'Atikan','\'\'\'Atikan\'\'\' nyakup [[teaching]] jeung [[learning]] hususna [[skill]]s, and also something less tangible but more profound: the imparting of [[knowledge]], good [[judgement]] and [[wisdom]]. One of the fundamental goals of education is to impart [[culture]] across the generations (see [[socialization]]).\n\n==Sawangan==\nAtikan dimimitan mangsa keur [[baby]] lahir sarta sapanjang hirup. Atikan oge bisa dimimitian samemeh jabang bayi lahir saperti sababaraha \"orangtua\" nu ngadengekeun lagu atawa maca buku mangsa kakandungan nu diharepkeun bakal mere atikan ka bayina. For some, the struggles and triumphs of daily life are far more instructive than formal [[school]]ing (Thus [[Mark Twain]]: \"I never let school interfere with my education.\") [[Family]] members have an educational effect which is quite profound — often more profound than they realize — though family teaching techniques may be highly informal.\n\nFormal education occurs when society makes a commitment to educate people, usually the young. Formal education can be systematic and thorough, but the sponsoring group may seek selfish advantages when shaping impressionable young scholars.\n\nLife-long or [[adult education]] has become widespread. Many [[adult]]s have given up the notion that only [[child]]ren belong in school. Many adults are enrolled in [[post-secondary education]] schools, both part-time and full time, where they are often classified as [[non-traditional students]] in order to distinguish them administratively from young adults entering directly from high school.\n\nComputing devices can change when and where we learn. This is the computer based or networked learning structure, in which people contribute to each others\' education. It is defined as [[online education]] (a subset of [[distance education]]), the [[European Graduate School]] as a University operates during the summer, it serves as a meeting point for people that has participated in online forums through the academic year, this methodology is a break to the traditional educational system.\n\n==Categories==\n:[[Classical education]] – [[reading education|Reading]] – [[Math education|Math]] – [[Language education|Language]] – [[Science education|Science]] – [[Ethics]] – [[Physical education]] – [[Religious education]] – [[Music#Education|Music education]]\n\n== Challenges in education ==\n=== In well-developed countries ===\n* Entertaining world distract student\'s attention\n:see [[Current issues in teaching]]\n* [[Program evaluation|Program Evaluation]] Answering questions such as does education \"work\", or how to improve education.\n\n=== In developing countries ===\n* Small incomes of teachers\n* People unaware the importance of education\n* Economical pressure of parents who want their children to work as laborers\n* [[Program evaluation|Program Evaluation]] \n\n==Formal education==\n:[[Early childhood education]] – [[Primary education]] – [[Secondary education]] – [[Tertiary education]] – [[Quaternary education]]– [[Higher education]] – [[Vocational education]] – [[Post-secondary education]] – [[University]] – [[College]] – [[School]] – [[Further education]]\n\n==Student activism==\n:[[Student activism]] – [[Student-led school change]] – [[Student Developed Education Policy]]\n\n==Educational policy==\n:[[Literacy]] – [[Standardized testing and public policy|Testing & policy]]– [[Education reform]] – [[School choice]] – [[Charter schools]] – [[Meaningful student involvement]] – [[Student voice]] – [[Student Developed Education Policy]] – [[Social promotion]]\n\n==Informal and alternative education==\n:[[Early instruction]] – [[Home schooling]] – [[Unschooling]] – [[Lifelong education]] – [[Democratic Schools]] – [[Alternative school]] – [[Montessori method]] – [[Waldorf school]] – [[Online education]] – [[Distance education]] – [[Museum]] – [[Planetarium]] – [[Nature center]] – [[deschooling]]– [[political education]]\n\n==Extracurricular education==\n:[[Academic Decathlon]] – [[University Interscholastic League]] (UIL) – [[International science olympiad]]\n\n==Theory and methodology==\n:[[Philosophy of education]] – [[Teaching method]] – [[Instructional theory]] – [[Learning theory (education)|Learning theory]] – [[Learning disability]] – [[Instructional technology]] – [[Education Psychology]] – [[Behaviorism]] – [[Problem-based learning]] – [[Active learning]] – [[Outcome-based education]] – [[Reggio Emilia approach]] – [[Cooperative education]] – [[collaborative learning]] – [[Transformative learning]] – [[experiential education]] – [[Situated learning]] – [[Adult education]] – [[Critical pedagogy]]\n\n==Education by country==\n:[[Atikan dumasar ka nagara]] – [[Daftar sakola jeung paguron luhur dumasar nagara]]\n\n==Education and parents==\n*[http://www.parentsrightscoalition.org/ Parents\'_Rights_Coalition]\n*[[British Columbia Parents and Teachers for Life]]\n\n==Biographies==\n*[[F. Matthias Alexander]]\n*[[Catherine Baker]]\n*[[Benjamin Bloom]]\n*[[Garth Boomer]]\n*[[Jim Cummins]]\n*[[John Dewey]]\n*[[Hermann Ebbinghaus]]\n*[[Moshe Feldenkrais]]\n*[[Paulo Freire]]\n*[[Robert M. Gagne]]\n*[[Ivan Illich]]\n*[[Maria Montessori]]\n*[[A.S. Neill]]\n*[[Seymour Papert]]\n*[[Ivan Pavlov]]\n*[[Johann Heinrich Pestalozzi]]\n*[[Jean Piaget]]\n*[[Plato]]\n*[[Neil Postman]]\n*[[Jean-Jacques Rousseau]]\n*[[B.F. Skinner]]\n*[[Lev Vygotsky]]\n\n[[Category:Education]]\n[[Category:Topic lists]]\n\n[[bg:Образование]]\n[[da:Uddannelse]]\n[[de:Pädagogik]]\n[[eo:Edukado]]\n[[es:Educación]]\n[[fr:Éducation]]\n[[he:חינוך]]\n[[ia:education]]\n[[id:Pendidikan]]\n[[it:formazione]]\n[[ja:教育]]\n[[ms:Pendidikan]]\n[[nl:Onderwijs]]\n[[pt:instrução]]\n[[ro:Educaţie]]\n[[sl:izobraževanje]]\n[[sw:Elimu]]\n[[tr:E%C4%9Fitim]]\n[[vo:Dugäl]] \n[[uk:Освіта]]\n[[zh:教育]]','/* Overview */',13,'Budhi','20040816224416','',0,0,0,0,0.724428259174,'20041229235111','79959183775583'); INSERT INTO cur VALUES (986,0,'Daftar_sakola_jeung_paguron_luhur_dumasar_nagara','This is a \'\'\'list of [[university|universities]], sorted by country\'\'\'. The list also includes [[college]]s and other educational instutitutions providing [[higher education]], meaning [[tertiary education|tertiary]], [[quaternary education|quaternary]] and in some cases [[post-secondary education]].\n\n*[[List of universities in Albania]]\n*[[List of universities in Australia]]\n*[[List of universities in Austria]]\n*[[List of universities in Belgium]]\n*[[List of universities in Bolivia]]\n*[[List of universities in Brazil]]\n*[[List of universities in Canada]]\n*[[List of universities in Chile]]\n*[[List of universities in Mainland China]]\n*[[List of universities in the Czech Republic]]\n*[[List of universities in Denmark]]\n*[[List of universities in Estonia]]\n*[[List of universities in Finland]]\n*[[List of universities in France]]\n*[[List of universities in Germany]]\n*[[List of universities in Greece]]\n*[[List of universities in Greenland]]\n*[[List of universities in Guatemala]]\n*[[List of universities in Honduras]]\n*[[List of universities in Hong Kong]]\n*[[List of universities in Hungary]]\n*[[Daftar paguron luhur di Indonesia]]\n*[[List of universities in Iceland]]\n*[[List of universities in India]]\n*[[List of universities in Ireland]]\n*[[List of universities in Israel]]\n*[[List of universities in Italy]] \n*[[Daftar paguron luhur di Jepang]]\n*[[List of universities in Macau]]\n*[[List of universities in Malaysia]]\n*[[List of universities in Mexico]]\n*[[List of universities in the Netherlands]]\n*[[List of universities in New Zealand]]\n*[[List of universities in Norway]]\n*[[List of universities in Pakistan]]\n*[[List of universities in the Philippines]]\n*[[List of universities in Poland]]\n*[[List of universities in Portugal]]\n*[[List of universities in Russia]]\n*[[List of universities in Saudi Arabia]]\n*[[List of universities in Serbia and Montenegro]]\n*[[List of universities in Singapore]]\n*[[List of universities in Slovenia]]\n*[[List of universities in South Africa]]\n*[[List of universities in South Korea]]\n*[[List of universities in Spain]]\n*[[List of universities in Sweden]]\n*[[List of universities in Switzerland]]\n*[[List of universities in Taiwan]]\n*[[List of universities in Thailand]]\n*[[List of universities in Turkey]]\n*[[List of universities in the Ukraine]]\n*[[List of universities in Venezuela]]\n*[[List of colleges and universities in the United States]]\n**[[List of colleges and universities in the United States#Puerto Rico|List of colleges and universities in Puerto Rico]]\n*[[List of British universities|List of universities in the United Kingdom]]\n\n*[[List of international universities]]\n\n==See also== \n*[[List of colleges and universities]]\n*[[Education by country]]\n*[[Mega university]]\n\n[[Category:Lists of colleges and universities]]\n[[es:Lista de universidades por país]]\n[[th:รายชื่อสถาบันอุดมศึกษาในประเทศต่างๆ แบ่งตามประเทศ]]\n[[uk:Список вищих навчальних закладів за країною]]\n[[zh:世界各国大学列表]]','',13,'Budhi','20040722121846','',0,0,0,0,0.931188400337,'20040722122443','79959277878153'); INSERT INTO cur VALUES (987,0,'Daftar_paguron_luhur_di_Indonesia','Di handap ieu daptar universitas di [[Indonésia]]:\n==Universitas Negri==\n* [[Universitas Indonésia]] (jalaloka: http://www.ui.ac.id/ )\n* [[Universitas Diponegoro]] (jalaloka: http://www.undip.ac.id/ )\n* [[Universitas Gadjah Mada]] (jalaloka: http://www.ugm.ac.id/ )\n* [[Universitas Pajajaran]] (jalaloka: http://www.unpad.ac.id/ )\n* [[Universitas Sriwijaya]] (jalaloka: http://www.unsri.ac.id/ )\n\n==Universitas swasta==\n* [[Universitas Atmajaya]] (jalaloka: http://www.atmajaya.ac.id/ )\n* [[Universitas Atmajaya Jogjakarta]] (jalaloka: http://www.uajy.ac.id/ )\n* [[Universitas Bina Nusantara]] (jalaloka: http://www.binus.ac.id/ )\n* [[Universitas Tarumanagara]] (jalaloka: http://www.tarumanagara.ac.id/ )\n* [[Universitas Trisakti]] (jalaloka: http://www.trisakti.ac.id/ )\n\nPikeun daptar paguron luhur Indonésia nu leuwih lengkep, tempo [http://dikti.org/ Diréktorat Jéndral Perguruan Tinggi (Dikti)] (atawa tuturkeun tumbu di handap ieu),\n* [http://dikti.org/ban2003.htm List of accredited university departments in Indonesia (at dikti.org)]\n* [http://dikti.org/dirPTS Directory of private higher education institutions in Indonesia (at dikti.org)]\n\n[[Category:Daptar paguron jeung universitas]]','/* Universitas swasta */',3,'Kandar','20041202065301','',0,0,0,0,0.366355176254,'20041202065301','79958797934698'); INSERT INTO cur VALUES (988,0,'Daftar_paguron_luhur_di_Jepang','The following is a \'\'\'list of [[university|universities]] in [[Japan]]\'\'\':\n\n*[[Aichi University]]\n*[[Aoyama Gakuin University]]\n*[[Chiba University]]\n*[[Chubu University]]\n*[[Chuo University]]\n*[[Daito Bunka University]]\n*[[Dokkyo University]]\n*[[Doshisha University]]\n*[[Ferris University]]\n*[[Gakushuin University]]\n*[[Universitas Gifu - Gifu Daigaku]]\n*[[Hokkaido University]]\n*[[Hosei University]]\n*[[International Christian University]]\n*[[International University of Japan]]\n*[[Jichi Medical School]]\n*[[Kanto Gakuin University]]\n*[[Kobe University]]\n*[[Kokugakuin University]]\n*[[Kwansei Gakuin University]]\n*[[Kyoto University]]\n*[[Kyushu University]]\n*[[Keio University]]\n*[[Kansai University]]\n*[[Kansai Gaidai University]]\n*[[Mabie Memorial School]]\n*[[Meiji University]]\n*[[Meiji Gakuin University]]\n*[[Musashi University]]\n*[[Nagoya Institute of Technology]]\n*[[Nagoya University]]\n*[[Niigata University]]\n*[[Osaka University]]\n*[[Osaka City University]]\n*[[Rikkyo University]] ([[St. Paul\'s University]])\n*[[Ritsumeikan University]]\n*[[Sophia University]]\n*[[Teikyo University]]\n*[[Tohoku University]]\n*[[Tokyo Institute of Technology]]\n*[[Tokyo Metropolitan University]]\n*[[Tsukuba University]]\n*[[University of Tokyo]]\n*[[Waseda University]]\n*[[Yokohama National University]]\n\n==Tempo ogé==\n* [[Education in Japan]]\n* [[List of colleges and universities by country]]\n* [[List of colleges and universities]]\n\n[[Category:Japanese society]]\n[[Category:Lists of colleges and universities]]\n[[ja:日本の大学一覧]]\n[[zh:日本大学列表]]','',0,'219.49.2.53','20050213082425','',0,0,0,0,0.356705920937,'20050213082425','79949786917574'); INSERT INTO cur VALUES (989,0,'Universitas_Gifu_-_Gifu_Daigaku','==External link==\n\n*[http://www.gifu-u.ac.jp/index.shtml Gifu University official site]','',13,'Budhi','20040722122616','',0,0,0,1,0.83375342881,'20040722122616','79959277877383'); INSERT INTO cur VALUES (990,0,'Abad_ka-20','([[19th century]] - \'\'\'20th century\'\'\' - [[21st century]] - [[Centuries|more centuries]])\n\n[[Decades]]: [[1900s]] [[1910s]] [[1920s]] [[1930s]] [[1940s]] [[1950s]] [[1960s]] [[1970s]] [[1980s]] [[1990s]]\n\n----\nAs a means of recording the passage of [[time]], the \'\'\'20th century\'\'\' was that [[century]] which lasted from [[1901]]-[[2000]]. Colloquially, this is often known as the \'\'\'nineteen hundreds\'\'\' ([[1900s]]), referring to the years [[1900]] to [[1999]].\n\nThe twentieth century was a remarkable shift in the very existence of humanity due to the technological, medical, social, ideological, and international innovations. Terms like [[genocide]], [[holocaust]], [[nuclear war]], and [[terrorism]] rose to common language and an influence on the lives of everyday people. The trends of mechanization of goods and services and networks of global communication, which were begun in the [[19th century]], continued at an ever-increasing pace in the 20th. In spite of the terror and chaos, the 20th century saw many attempts at world peace. As the 35th United States President [[John F. Kennedy]] said:\n\n\"What kind of peace do we seek? I am talking about a genuine peace, the kind of peace that makes life on earth worth living. Not merely peace in our time, but peace in all time. Our problems are man-made, therefore they can be solved by man. For in the final analysis, our most basic common length is that we all inhabit this small planet, we all breath the same air, we all cherish our children\'s future, and we are all mortal.\"\n\nVirtually every aspect of life in virtually every human society changed in some fundamental way or another during the twentieth century.\n\n*[[20th_century/Death rates|Death rates]]\n*[[20th_century/Infant mortality|Infant mortality]]\n*[[20th_century/Infectious disease|Infectious disease]]\n*[[20th_century/Life expectancy|Life expectancy]]\n*[[20th_century/Maternal death rates|Maternal death rates]]\n*[[List of battles 1901-forward|Battles]]\n\n==Important developments, events and achievements==\n=== Science and technology ===\n* The [[assembly line]] and [[mass production]] of motor vehicles and other goods allowed manufacturers to produce more and cheaper products. This allowed the [[automobile]] to become the most important means of transportation.\n* The invention of [[Airplane|heavier-than-air flying machines]] and the [[jet engine]] allowed for the world to become \"smaller\". [[Space science|Space flight]] increased knowledge of the rest of the universe and allowed for global real-time communications via [[geosynchronous satellite]]s.\n* [[Mass media]] technologies such as [[film]], [[radio]], and [[television]] allow the communication of political messages and entertainment with unprecedented impact\n* Mass availability of the [[telephone]] and later, the [[computer]], especially through the [[Internet]], provides people with new opportunities for near-instantaneous communication\n* Applied [[electronics]], notably in its miniaturized form as [[integrated circuit]]s, made possible the above mentioned rise of [[mass media]], telecommunications, ubiquitous [[Computer|computing]], and all kinds of \"intelligent\" appliances; as well as many advances in natural sciences such as physics, by the use of [[Moore\'s Law|exponentially growing]] calculation power (see [[supercomputer]]).\n* The development of [[Nitrogen]] fertilizer, [[pesticide]]s and [[herbicide]]s resulted in significantly higher agricultural yield.\n* Advances in fundamental [[physics]] through the [[theory of relativity]] and [[quantum mechanics]] led to the development of [[nuclear weapon]]s, the [[nuclear reactor]], and the [[laser]]. [[Fusion power]] was studied extensively but remained an experimental technology at the end of the century.\n* The [[big bang]] model of [[cosmology]] was developed.\n* Inventions such as the [[washing machine]] and [[air conditioning]] led to an increase in both the quantity and quality of [[leisure time]] for the [[middle class]] in Western societies.\n* Most influencing inventions in the 20th century: [[Antibiotics]], [[Internet]]\n* [[Timeline_of_invention#1900-1999|More...]]\n\n=== Wars and politics ===\n* Rising [[nationalism]] and increasing national awareness were among the causes of [[World War I]], the first of two wars to involve all the major world powers including [[Germany]], [[France]], [[Italy]], [[Japan]], the [[United States]] and the [[British Commonwealth]]. World War I led to the creation of many new countries, especially in [[Eastern Europe]].\n* The economic and political aftermath of World War I led to the rise of [[Fascism]] and [[Nazism]] in Europe, and shortly to [[World War II]]. This war also involved Asia and the Pacific, in the form of [[Japan|Japanese]] aggression against [[China]] and the United States. While the First World War mainly cost lives among soldiers, civilians suffered greatly in the Second -- from the bombing of cities on both sides, and in the unprecedented German [[genocide]] of the [[Jew]]s and others, known as the [[Holocaust]].\n* Unhappiness in [[Russia]] led to the rise of [[Communism]] and the [[Russian Revolution]]. After the [[Soviet Union]]\'s involvement in World War II, Communism became a major force in global politics, spreading all over the world: notably, to Eastern [[Europe]], [[China]], [[Indochina]] and [[Cuba]]. This led to the [[Cold War]] with [[The West|the western world]], led by the [[United States]].\n* The \"fall of Communism\" in the late [[1980s]] left the [[United States]] as the world\'s only [[superpower]]. It also led to the dissolution of the [[Soviet Union]] and [[Socialist Federal Republic of Yugoslavia|Yugoslavia]] into successor states, many rife with [[ethnic nationalism]].\n* Through the [[League of Nations]] and, after [[World War II]], the [[United Nations]], international cooperation increased. Other efforts included the formation of the [[European Union]], leading to a common currency in much of [[Western Europe]], the [[euro]].\n* The end of [[colonialism]] led to the independence of many [[Africa]]n and [[Asia]]n countries. During the Cold War, many of these aligned with the USA, the USSR, or China for defense.\n* The creation of [[Israel]], a [[Jew]]ish state in a mostly [[Arab]] region of the world, fueled many conflicts in the region, which were also influenced by the vast [[oil]] fields in many of the [[Arab]] countries.\n\n=== Five overall largest mass killings of the 20th century ===\n(measured in numbers of people killed; also see [http://www-sul.stanford.edu/depts/ssrg/misc/misery.html])\n* [[World War II]] and regime of [[Adolf Hitler]] (1937-1945), over 50 million dead, including the [[Holocaust]], killing two-thirds of the [[Judaism|Jewish]] population of Europe (6 million).\n* Regime of [[Mao Zedong]] and [[People\'s Republic of China|Chinese]] famine (1949-1976), over 28 million dead.\n* Regime of [[Joseph Stalin]] (1924-1953), over 20 million dead.\n* [[World War I]] (1914-1918), over 15 million dead.\n* [[Russian Civil War]] (1918-1921), over 8.5 million dead.\n\n=== Culture and entertainment ===\n* [[Cinema|Movies]], [[music]] and the [[medium|media]] had a major influence on [[fashion]] and trends in all aspects of life. As many movies and music originate from the [[United States]], American culture spread rapidly over the world.\n* After gaining political rights in the [[United States]] and much of [[Europe]] in the first part of the century, women became more independent throughout the century.\n* Modern art developed new styles such as [[expressionism]], [[cubism]], and [[surrealism]].\n* The [[automobile]] provided vastly increased transportation capabilities for the average member of Western societies in the early to mid-century, spreading even further later on. City design throughout most of the West became focused on transport via car. The car became a leading symbol of modern society, with styles of car suited to and symbolic of particular lifestyles.\n* [[Sport]]s became an important part of society, becoming an activity not only for the privileged. Watching sports, later also on [[television]], became a popular activity.\n\n==== Highest grossing films of the 20th century ====\n# [[Titanic (1997 movie)|Titanic]] (1997)\n# [[Star Wars]] (1977)\n# [[Star Wars Episode I: The Phantom Menace]] (1999)\n# [[E.T. the Extra-Terrestrial]] (1982)\n# [[Jurassic Park]] (1993)\n\n==== Most critically acclaimed films ====\n* [[Battleship Potemkin]] (1925)\n* [[Citizen Kane]] (1941)\n* [[Psycho]] (1960)\n* [[The Wizard of Oz (1939 movie)|The Wizard of Oz]] (1939)\n* [[2001: A Space Odyssey]] (1968)\n* [[The Godfather]] (1972)\n* [[It\'s a Wonderful Life]] (1946)\n\n=== Disease and medicine ===\n* Though modern medicine is better than ever, an [[influenza]] pandemic kills 25 million in [[1918]]-[[1919]] (the [[Spanish Flu]]), while [[AIDS]], killing many remains incurable and treatments remain too expensive for wide use in [[developing countries]].\n* Advances in [[medicine]], such as the invention of [[antibiotic]]s, decreased the number of people dying from diseases. [[Contraceptive]] drugs and [[organ transplantation]] were developed. The discovery of [[DNA]] molecules and the advent of [[molecular biology]] allowed for [[cloning]] and [[genetic engineering]].\n\n=== Natural resources and the environment ===\n* The widespread use of [[petroleum]] in industry -- both as a chemical precursor to [[plastic]]s and as a fuel for the [[automobile]] and [[airplane]] -- led to the vital geopolitical importance of petroleum resources. The [[Middle East]], home to many of the world\'s oil deposits, became a center of geopolitical and military tension throughout the latter half of the century.\n* A vast increase in [[fossil fuel]] consumption leads to depletion of natural resources, while [[air pollution]] possibly leads to [[global warming]] and the [[ozone hole]]. The problem is increased by world-wide [[deforestation]], also causing a loss of [[biodiversity]]. The problem of a depletion of natural resources is decreased by advances in drilling technology which led to a net increase in the amount of fossil fuel that is readily obtainable at the end of the century, as compared with the amount considered obtainable at the beginning of the century.\n\n==Significant people==\n===World leaders===\n* [[Africa]]\n** [[Gnassingbe Eyadema]], [[Togo]]\n** [[Félix Houphouët-Boigny]], [[Côte d\'Ivoire]]\n** [[Kenneth Kaunda]], [[Zambia]]\n** [[Jomo Kenyatta]], [[Kenya]]\n** [[Idi Amin]], [[Uganda]]\n** [[Nelson Mandela]], [[South Africa]]\n** [[Robert Mugabe]], [[Zimbabwe]]\n** [[Gamal Abdal Nasser|Gamal Abdel Nasser]], [[Egypt]]\n** [[Kwame Nkrumah]], [[Ghana]]\n** [[Julius Nyerere]], [[Tanzania]]\n** [[Habib Bourguiba]], [[Tunisia]]\n** Colonel [[Moammar Al Qadhafi|Muammar Gaddafi]], [[Libya]]\n** [[Cecil Rhodes]], [[South Africa]]\n** [[Haile Selassie]], [[Ethiopia]]\n** [[Léopold Sédar Senghor]], [[Senegal]]\n** [[Ahmed Sékou Touré]], [[Guinea]]\n\n* [[Americas]]\n** [[Theodore Roosevelt]], [[United States|USA]]\n** [[Franklin Delano Roosevelt]], [[United States|USA]]\n** [[Dwight Eisenhower]], [[United States|USA]]\n** [[John F. Kennedy]], [[United States|USA]]\n** [[Richard Nixon]], [[United States|USA]]\n** [[Ronald Reagan]], [[United States|USA]]\n** [[Bill Clinton]], [[United States|USA]]\n** [[George H. W. Bush]], [[United States|USA]]\n** [[George W. Bush]], [[United States|USA]]\n** [[Wilfrid Laurier]], [[Canada]]\n** [[William Lyon Mackenzie King]], [[Canada]]\n** [[Pierre Trudeau]], [[Canada]]\n** [[Che Guevara|Ernesto \'Che\' Guevara]], [[Cuba]]\n** [[Fidel Castro]], [[Cuba]]\n** [[Juan Peron|Juan Perón]], [[Argentina]]\n** [[Salvador Allende]], [[Chile]]\n** [[Augusto Pinochet]], [[Chile]]\n** [[Emiliano Zápata]], [[Mexico]]\n** [[Pancho Villa]], [[Mexico]]\n\n* [[Asia]]\n** [[Mao Zedong]], [[People\'s Republic of China]]\n** [[Deng Xiaoping]], [[People\'s Republic of China]]\n** [[Pol Pot]], [[Cambodia]]\n** [[Mahatma Gandhi]], [[India]]\n** [[Indira Gandhi]], [[India]]\n** [[Muhammad Ali Jinnah]], [[Pakistan]]\n** [[Mahathir Mohamad]], [[Malaysia]]\n** [[Jawaharlal Nehru]], [[India]]\n** [[Emperor Hirohito of Japan|Emperor Hirohito]], [[Japan]]\n** [[Ho Chi Minh]], [[Vietnam]]\n** [[Sun Yat-sen]], [[Republic of China]]\n** [[Chiang Kai-shek]], [[Republic of China]]\n** Achmad [[Sukarno]], [[Indonesia]]\n** [[Lee Kuan Yew]], [[Singapore]]\n\n* [[Europe]]\n** [[Kemal Atatürk]], [[Turkey]]\n** [[Neville Chamberlain]], [[United Kingdom]]\n** [[Winston Churchill]], [[United Kingdom]]\n** [[Margaret Thatcher]], [[United Kingdom]]\n** [[Charles de Gaulle]], [[France]]\n** [[Eamon de Valera]], [[Republic of Ireland|Ireland]]\n** [[Franz Ferdinand, Archduke of Austria]], [[Austria-Hungary]]\n** Kaiser [[Wilhelm II]], [[Germany]]\n** [[Václav Havel]], [[Czech Republic]]\n** [[Adolf Hitler]], [[Germany]]\n** [[Helmut Schmidt]], [[Germany]]\n** [[Helmut Kohl]], [[Germany]]\n** [[Gerhard Schröder]], [[Germany]]\n** [[Benito Mussolini]], [[Italy]]\n** [[Francisco Franco]], [[Spain]]\n** [[Jozef Pilsudski]], [[Poland]]\n** [[Josip Broz Tito|Josip Broz \'Tito\']], [[Socialist Federal Republic of Yugoslavia|Yugoslavia]]\n** [[Milan Kucan|Milan Kučan]], [[Slovenia]]\n** [[Olof Palme]], [[Sweden]]\n** [[Nicolae Ceausescu]], [[Romania]]\n** [[Lech Walesa]], [[Poland]]\n** [[John Paul II]], [[World]]\n\n\n* [[Middle East]]\n** [[Abdul Nasser]], [[Egypt]] or [[United Arab Republic]]\n** [[Anwar Sadat]], [[Egypt]] or [[United Arab Republic]]\n** [[David Ben-Gurion]], [[Israel]]\n** [[Golda Meir]], [[Israel]]\n** [[Menachem Begin]], [[Israel]]\n** [[Hafez el Assad]], [[Syria]]\n** [[Saddam Hussein]], [[Iraq]]\n** [[King Hussein]], [[Jordan]]\n\n* [[Russia]] and [[Soviet Union]]\n** [[Czar Nicholas II]]\n** [[Vladimir Lenin]]\n** [[Joseph Stalin]]\n** [[Leon Trotsky]]\n** [[Nikita Khrushchev]]\n** [[Leonid Brezhnev]]\n** [[Mikhail Gorbachev]]\n** [[Boris Yeltsin]]\n** [[Vladimir Vladimirovich Putin]]\n\n===Scientists===\n\n* [[Niels Bohr]]\n* [[Albert Einstein]]\n* [[Enrico Fermi]]\n* [[Howard Walter Florey]]\n* [[Sigmund Freud]]\n* [[Kurt Gödel]]\n* [[Fritz Haber]]\n* [[Werner Karl Heisenberg]]\n* [[Andrey Nikolaevich Kolmogorov]]\n* [[Linus Pauling]]\n* [[Erwin Schrödinger]]\n* [[John von Neumann]]\n* [[Alan Turing]]\n\n===Economics and business===\n\n* [[John Maynard Keynes]]\n* [[John Kenneth Galbraith]]\n* [[Milton Friedman]]\n* [[Henry Ford]]\n* [[Thomas J. Watson]]\n* [[Bill Gates]]\n\n===Aerospace pioneers===\n\n* [[Robert Goddard (scientist)|Robert Goddard]]\n* [[Wernher Von Braun]]\n* [[Neil Armstrong]]\n* [[Louis Bleriot]]\n* [[Yuri Gagarin]]\n* [[Vladimir Mikhailovich Komarov]]\n* [[Freddie Laker]]\n* [[Charles Lindbergh]]\n* [[Ronald E. McNair|Ron McNair]]\n* [[Ellison S. Onizuka|Ellison Onizuka]]\n* [[Herman Potocnik|Herman Potočnik Noordung]]\n* [[Alan Shepard]]\n* [[Valentina Tereshkova]]\n* [[Wright Brothers]]\n\n===Military leaders===\n* [[Charles de Gaulle]]\n* [[Dwight Eisenhower]]\n* Sir [[Bernard Freyberg]]\n* [[Douglas Haig]]\n* [[Douglas MacArthur]]\n* [[Rudolf Maister]]\n* [[Bernard Montgomery]]\n* [[Chester Nimitz]] \n* [[George Patton]]\n* [[Erwin Rommel]]\n* [[Franc Rozman Stane]]\n* [[Leon Trotsky]]\n* [[Mao Zedong]]\n* [[Georgy Zhukov]]\n\n===Religious figures===\n* [[Grigori Rasputin]]\n* [[Pope John XXIII]]\n* [[Pope John Paul II]]\n* [[Mother Theresa]] of [[Calcutta]]\n* The 13th [[Dalai Lama]] of [[Tibet]], [[Thubten Gyatso]]\n* The 14th [[Dalai Lama]] of [[Tibet]], [[Tenzin Gyatso]]\n* The Rev. [[Martin Luther King Jr.]]\n* The Rev. [[Billy Graham]]\n* [[Mohandas Gandhi|Mahatma Gandhi]]\n* [[Prabhupada A.C. Bhaktivedanta]]\n\n===Artists===\n* [[Constatin Brancusi]]\n* [[George Braque]]\n* [[Salvador Dalí]]\n* [[Marcel Duchamp]]\n* [[Jacob Epstein]]\n* [[Juan Gris]]\n* [[Wassily Kandinsky]]\n* [[Henri Matisse]]\n* [[Joan Miró]]\n* [[Amedeo Modigliani]]\n* [[Piet Mondrian]]\n* [[Henry Moore]]\n* [[Pablo Picasso]]\n* [[Jackson Pollock]]\n* [[Andy Warhol]]\n\n===Entertainers===\n* [[The Beatles]]\n* [[Bob Dylan]]\n* [[Bob Marley]]\n* [[Charlie Chaplin]]\n* [[Charlie Parker]]\n* [[Elvis Presley]]\n* [[Frank Sinatra]]\n* [[Groucho Marx]]\n* [[Jimi Hendrix]]\n* [[Kraftwerk]]\n* [[Louis Armstrong]]\n* [[Lucille Ball]]\n* [[Marilyn Monroe]]\n* [[Michael Jackson]]\n* [[Miles Davis]]\n* [[Pink Floyd]]\n* [[Queen (band)]]\n* [[Spike Jones]]\n* [[Spike Milligan]]\n* [[The Velvet Underground]]\n\n===Writers and poets===\n* [[Louis Aragon]]\n* [[Samuel Beckett]]\n* [[Jorge Luis Borges]]\n* [[André Breton]]\n* [[Basil Bunting]]\n* [[Albert Camus]]\n* [[Noam Chomsky]]\n* [[Cid Corman]]\n* [[Hart Crane]]\n* [[Robert Creeley ]]\n* [[e. e. cummings]]\n* [[T. S. Eliot]]\n* [[Paul Eluard]]\n* [[William Faulkner]]\n* [[Gabriel García Márquez]]\n* [[Allen Ginsberg]]\n* [[Alamgir Hashmi]]\n* [[Seamus Heaney]]\n* [[Ernest Hemingway]]\n* [[H.D.]]\n* [[Orrick Johns]]\n* [[James Joyce]]\n* [[Franz Kafka]]\n* [[Jack Kerouac]]\n* [[Philip Larkin]]\n* [[Mina Loy]]\n* [[Hugh MacDiarmid]]\n* [[Antonio Machado]]\n* [[Andre Malraux]]\n* [[Marianne Moore]]\n* [[Sean O\'Casey]]\n* [[Charles Olson]]\n* [[George Oppen]]\n* [[George Orwell]]\n* [[Ezra Pound]]\n* [[Marcel Proust]]\n* [[Thomas Pynchon]]\n* [[Ayn Rand]]\n* [[Charles Reznikoff]]\n* [[Dorothy Richardson]]\n* [[Jean-Paul Sartre]]\n* [[Antoine de Saint-Exupéry]]\n* [[Gary Snyder]]\n* [[Gertrude Stein ]]\n* [[Wallace Stevens]]\n* [[John Millington Synge]]\n* [[J.R.R. Tolkien]]\n* [[William Carlos Williams]]\n* [[Virginia Woolf]]\n* [[W. B. Yeats]]\n* [[Louis Zukofsky]]\n\n===Sports figures===\n* [[Babe Ruth]]\n* [[Muhammad Ali]]\n* [[Wilfred Benitez]]\n* [[Larry Bird]]\n* Sir [[Donald Bradman]]\n* [[Roberto Clemente]]\n* [[Fausto Coppi]]\n* [[Angel Cordero]]\n* [[Wilfredo Gomez]]\n* [[Wayne Gretzky]]\n* Sir [[Edmund Hillary]]\n* [[Magic Johnson]]\n* [[Michael Jordan]]\n* [[Martina Navratilova]]\n* [[Diego Maradona]]\n* [[Jack Nicklaus]]\n* [[Pelé]]\n* [[Jackie Robinson]]\n* [[Martin Strel]]\n* [[Mark Todd (NZ)|Mark Todd]]\n* [[Mike Tyson]]\n* [[Ted Williams]]\n\n===Notorious figures===\n* [[Adolf Hitler]]\n* [[Saddam Hussein]]\n* [[Joseph Goebbels]]\n* [[Osama bin Laden]]\n* [[Timothy McVeigh]]\n* [[Charles Manson]]\n* [[Harold Shipman]]\n* [[Josef Stalin]]\n* [[Jeffrey Dahmer]]\n\n==Decades and years==\n{| border=\"0\" cellpadding=\"5\"\n|style=\"background: #eeeeee\"|\'\'\'[[1890s]]\'\'\'\n|[[1890]]\n|[[1891]]\n|[[1892]]\n|[[1893]]\n|[[1894]]\n|[[1895]]\n|[[1896]]\n|[[1897]]\n|[[1898]]\n|[[1899]]\n|-\n|style=\"background: #ffddcc\"|\'\'\'[[1900s]]\'\'\'\n|[[1900]]\n|style=\"background: #ffeedd\"|[[1901]]\n|style=\"background: #ffeedd\"|[[1902]]\n|style=\"background: #ffeedd\"|[[1903]]\n|style=\"background: #ffeedd\"|[[1904]]\n|style=\"background: #ffeedd\"|[[1905]]\n|style=\"background: #ffeedd\"|[[1906]]\n|style=\"background: #ffeedd\"|[[1907]]\n|style=\"background: #ffeedd\"|[[1908]]\n|style=\"background: #ffeedd\"|[[1909]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1910s]]\'\'\'\n|[[1910]]\n|[[1911]]\n|[[1912]]\n|[[1913]]\n|[[1914]]\n|[[1915]]\n|[[1916]]\n|[[1917]]\n|[[1918]]\n|[[1919]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1920s]]\'\'\'\n|[[1920]]\n|[[1921]]\n|[[1922]]\n|[[1923]]\n|[[1924]]\n|[[1925]]\n|[[1926]]\n|[[1927]]\n|[[1928]]\n|[[1929]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1930s]]\'\'\'\n|[[1930]]\n|[[1931]]\n|[[1932]]\n|[[1933]]\n|[[1934]]\n|[[1935]]\n|[[1936]]\n|[[1937]]\n|[[1938]]\n|[[1939]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1940s]]\'\'\'\n|[[1940]]\n|[[1941]]\n|[[1942]]\n|[[1943]]\n|[[1944]]\n|[[1945]]\n|[[1946]]\n|[[1947]]\n|[[1948]]\n|[[1949]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1950s]]\'\'\'\n|[[1950]]\n|[[1951]]\n|[[1952]]\n|[[1953]]\n|[[1954]]\n|[[1955]]\n|[[1956]]\n|[[1957]]\n|[[1958]]\n|[[1959]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1960s]]\'\'\'\n|[[1960]]\n|[[1961]]\n|[[1962]]\n|[[1963]]\n|[[1964]]\n|[[1965]]\n|[[1966]]\n|[[1967]]\n|[[1968]]\n|[[1969]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1970s]]\'\'\'\n|[[1970]]\n|[[1971]]\n|[[1972]]\n|[[1973]]\n|[[1974]]\n|[[1975]]\n|[[1976]]\n|[[1977]]\n|[[1978]]\n|[[1979]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1980s]]\'\'\'\n|[[1980]]\n|[[1981]]\n|[[1982]]\n|[[1983]]\n|[[1984]]\n|[[1985]]\n|[[1986]]\n|[[1987]]\n|[[1988]]\n|[[1989]]\n|- style=\"background: #ffeedd\"\n|style=\"background: #ffddcc\"|\'\'\'[[1990s]]\'\'\'\n|[[1990]]\n|[[1991]]\n|[[1992]]\n|[[1993]]\n|[[1994]]\n|[[1995]]\n|[[1996]]\n|[[1997]]\n|[[1998]]\n|[[1999]]\n|-\n|style=\"background: #ffddcc\"|\'\'\'[[2000s]]\'\'\'\n|style=\"background: #ffeedd\"|[[2000]]\n|[[2001]]\n|[[2002]]\n|[[2003]]\n|[[2004]]\n|[[2005]]\n|[[2006]]\n|[[2007]]\n|[[2008]]\n|[[2009]]\n|}\n\n[[af:20ste eeu]]\n[[bg:XX век]]\n[[ca:Segle XX]]\n[[cs:20. století]]\n[[da:20. århundrede]]\n[[de:20. Jahrhundert]]\n[[et:20. sajand]]\n[[el:20ός αιώνας]]\n[[es:Siglo XX]]\n[[eo:20-a jarcento]]\n[[fr:XXe siècle]]\n[[fy:20e ieu]]\n[[ko:20세기]]\n[[hi:बीसवी शताब्दी]]\n[[io:20-esma yar-cento]]\n[[it:XX secolo]]\n[[he:המאה ה-20]]\n[[la:20. saeculum]]\n[[nl:20e eeuw]]\n[[ja:20世紀]]\n[[no:20. århundre]]\n[[pl:XX wiek]]\n[[pt:Século XX]]\n[[ro:Secolul XX]]\n[[ru:XX век]]\n[[simple:20th century]]\n[[sl:20. stoletje]]\n[[fi:1900-luku]]\n[[sv:1900-talet]]\n[[tr:20. yüzyıl]]\n[[uk:20 століття]]\n[[zh:20世纪]]\n[[wa:20inme sieke]]','',0,'220.31.240.165','20040722234708','',0,0,0,1,0.475331729965,'20050208191941','79959277765291'); INSERT INTO cur VALUES (991,0,'Sukarno','\'\'\'Sukarno\'\'\' ([[June 6]], [[1901]] - [[June 21]], [[1970]]) teh [[Presiden Indonesia]] mimiti. Anjeunna anu \"memproklamirkan\" Indonesia merdeka ti jajahan [[Netherlands|the Netherlands]] sarta jadi Presiden ti taun 1945 nepi ka 1967, presiding over mixed success in the country\'s turbulent transition to independence. Sukarno was forced from power by one of his Generals, [[Suharto]], who was granted the formal title of President in March 1967.\n\n\'\'Sukarno oge biasa disebut Ahmed Sukarno atawa Soekarno. Masyakarat Indonesia nyebut ngaranna Bung Karno\'\'\n\n==Background==\nThe son of a [[Java (island)|Java]]nese nobleman and his [[Bali]]nese wife from Buleleng regency, Sukarno was born in [[Surabaya]] (although several sources said he was born in Blitar, East Java) in the [[Dutch East Indies]] (now Indonesia). He was admitted into a [[Netherlands|Dutch]]-run school as a child. When his father sent him to Surabaya in 1916 to attend a secondary school, he met [[Tjokroaminoto]], a future nationalist. 1921 he begun to study at the Technische Hoogeschool in [[Bandung]]. \n\nSukarno was fluent in several languages, especially Dutch. He once remarked that when he was studying in Surabaya, he often sat behind the screen in movie theaters reading the Dutch subtitles in reverse, because he could not afford the regular front seating\'s price.\n\n==Independence Struggle==\nSukarno became a leader of a Indonesian independence movement party, \'\'Partai Nasional Indonesia\'\' when it was founded in 1927. He was arrested in 1929 by Dutch colonial authorities and sentenced for two years in prison. By the time he was released, he had become a popular hero. In the 1930s he was again arrested several times. \n\n==WWII - Japanese Occupation==\nDuring the [[World War II]], Sukarno co-operated with [[Japan]]ese occupation forces but also continued to agitate for Indonesian independence. He accepted the role of a Indonesian head of state under Japanese military supervision in July 1942 and in 1943 became the head of Putera, a political auxiliary organization. \nHe also became head of Badan Penyelidik Usaha Persiapan Kemerdekaan Indonesia (BPUPKI), a Japanese-organized committee for Indonesian independence\n\n==Early Independence, the Panca Sila==\nAfter the Japanese defeat, Sukarno and [[Mohammed Hatta]] declared the Republic of Indonesia in August 17, 1945.\n\nSukarno\'s vision for the 1945 Indonesian constitution comprised the \'\'Panca Sila\'\'. ([[Sanskrit]] - \'\'five pillars\'\'). Sukarno\'s political philosophy was guided by (in no particular order) elements of [[Marxism]], [[Democracy]] and [[Islam]]. This is reflected in the Panca Sila, in the order in which he originally espoused them in a speech on June 1, 19451:\n\n#Nationalism (national unity, not ultranationalist supremacy)\n#Internationalism (one nation sovereign amongst equals)\n#Representative Democracy (all significant groups represented)\n#Social Justice (informed by Marxist philosophy)\n#Belief in God (however state remained secular)\n\nThe Indonesian parliament, founded on the basis of this original (and subsequent revised) constitutions, proved all but ungovernable. This was due to irreconcilable differences between varios social, political, religious and ethnic factions2.\n\nIn the ensuing chaos between various factions and Dutch attempts to re-establish colonial control, Dutch troops captured Sukarno in December 1948, but were forced to release him after the ceasefire. He returned to [[Jakarta]] in December 28 1949.\n\nThere were further attempts of military coups against Sukarno in 1956.\n\nIn an effort to restore order, Sukarno established what he called \'\'guided democracy\'\', in which he wielded progressively more executive powers, whilst maintaining a multiparty parliament.\n\n\n==\'Guided Democracy\', and Increasing Autocracy==\nDuring this later part of his presidency, Sukarno came to increasingly rely on the army and the support of the \'\'PKI\'\' - the [[Communist Party of Indonesia]].\n\nOn [[November 30]], [[1957]], there was a grenade attack against Sukarno when he was visiting a school in [[Jakarta]]. Six children were killed but Sukarno did not suffer any serious wounds. In December he ordered nationalization of 246 Dutch businesses. In February he began a breakdown of PRRI ([[Pemerintah Revolusioner Republik Indonesia]]) rebels at [[Bukittingi]].\n\nOver the following years he established government control over media and book publishing and purge against [[Ethnic Chinese]] residents. In July 5 1959 he reestablished 1945 constitution, dissolved the parliament, molded it to his liking and assumed full personal power as a prime minister. He called the system as government-by-decree \'\'\'Manifesto Politik\'\'\' or Manipol. He sent his opponents to internal exile.\n\nIn the 1950s he increased his ties to [[Peoples Republic of China|Communist China]] and admitted more [[Communist]]s to his government. Thus he also received [[Soviet]] military aid. \n\nIn 1962 Sukarno ordered raids to [[West Irian]] ([[Dutch New Guinea]]). There were more assassination attempts when he visited [[Sulawesi]] in 1962. West Irian was brought under Indonesian authority in May 1963 under the [[Bunker Plan]]. In the same year in July Sukarno had himself proclaimed [[President for Life]]. \n\nSukarno also opposed the British-supported Federation of [[Malaysia]], claiming that it was a \"neo-colonial plot\" to advance British interests. In spite of his political overtures, Malaysia was proclaimed in September 1963. This led to [[Indonesian Confrontation]] and the end of remaining US military aid to Indonesia. Sukarno withdrew Indonesia from the [[UN Security Council]] in 1965 and Malaysia took the seat. Sukarno also became increasingly ill and collapsed in public in August 9, 1965. He was secretly diagnosed with a kidney disease. \n\n==Removal from Power==\nOn the morning of October 1, 1965, some of Sukarno\'s closest guards kidnapped and murdered six anti-communist generals. One survivor, who was not targetted in the suspected coup attempt, was Lieutenant-General [[Suharto]]. \n\nThis crisis sparked a crackdown on the communist party and a nation-wide purge of suspected communists (mostly peasants). The murders were concentrated in Sumatra, East Java and Bali. By the time they petered out in 1966, an estimated half a million Indonesians have been slaughtered by soldiers, police and pro-Suharto vigilantes. Ethnic Chinese were also targetted, primarily for economic and racial reasons. An official CIA report called the purge \"one of the worst mass murders of the 20th century.\"2 \n\nSukarno\'s grip on power was weakened in the crisis, and eventually, pro-American Lieutenant-General [[Suharto]] forced Sukarno to hand over [[executive branch|executive power]]s on March 11, 1966.\n\nThere is much speculation about who triggered the crisis that led to Sukarno\'s removal from power. While the official version claims the Indonesian Communist Party (PKI) ordered the murders of the six generals, others say Sukarno himself, and some think Suharto orchestrated the assassinations to remove potential rivals for the presidency3.\n\nThere are also claims that Sukarno was toppled by the [[United States]] because of his [[nationalism]] and policy of [[Non-Aligned Movement|non-alignment]].\n\nSukarno was stripped of his presidential title by Indonesia\'s provisional parliament on March 12, 1967 and he remained under [[house arrest]] until his death at age 69 in Jakarta in 1970.\n\n[[Megawati Sukarnoputri]], the current Indonesian president, is his daughter.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n[[List of Presidents of Indonesia|Presidents of Indonesia]]
\n\'\'\'Preceded by\'\'\':
\n(first President)
\n(N/A)\n
\n\'\'\'Sukarno\'\'\'
\n([[1945]] - [[1967]])\n
\n\'\'\'Followed by\'\'\':
\n[[Suharto]]
\n([[1967]] - [[1998]])\n
\n[[Politics of Indonesia]]\n
\n\n==Quote==\nTo the US ambassador: \"Go to hell with your aid!\"\n\n==See also==\n* [[History of Indonesia]]\n\n==References==\n#Smith, Roger M (ed). \'\'Southeast Asia. Documents of Political Development and Change\'\', Ithaca and London, 1974, pp. 174-183.\n#U.S. Central Intelligence Agency, \'\'Research Study: Indonesia -- The Coup that Backfired,\'\' 1968, p. 71n.\n#Robert Cribb, ‘Nation: Making Indonesia’, in Donald K. Emmerson (ed.), Indonesia Beyond Suharto: Polity, Economy, Society, Transition. Armonk, New York: M.E. Sharpe, 1999, pp.3-38\n\n[[eo:Soekarno]]\n[[ja:スカルノ]]\n[[zh:苏加诺]]','+eo',0,'131.174.208.64','20041025110135','',0,0,0,0,0.175702297211,'20050208191941','79958974889864'); INSERT INTO cur VALUES (992,0,'Présidén_Indonésia','\'\'\'List of Presidents of Indonesia\'\'\'\n\n{|border=0 cellpadding=2 cellspacing=2 width=98%\n|-\n|\n|\'\'\'Name\'\'\'\n|\'\'\'Took Office\'\'\'\n|\'\'\'Left Office\'\'\'\n|\'\'\'Party\'\'\'\n|- bgcolor=#DDEEFF\n|1\n|[[Sukarno]]\n|[[17 August]] [[1945]]\n|[[12 March]] [[1967]]\n|[[Indonesian National Party]]\n|- bgcolor=#FFFFDD\n|2\n|[[Suharto]]\n|[[12 March]] [[1967]]\n|[[21 May]] [[1998]]\n|[[Golkar]]\n|- bgcolor=#FFFFDD\n|3\n|[[Jusuf Habibie|Baharuddin Jusuf Habibie]]\n|[[21 May]] [[1998]]\n|[[20 October]] [[1999]]\n|[[Golkar]]\n|- bgcolor=#DDFFDD\n|4\n|[[Abdurrahman Wahid]]\n|[[20 October]] [[1999]]\n|[[23 July]] [[2001]]\n|[[National Awakening Party]]\n|- bgcolor=#FFE8E8\n|5\n|[[Megawati Sukarnoputri]]\n|[[23 July]] [[2001]]\n|(present)\n|[[Indonesia Democracy Party - Struggle]]\n|}\n\n[[Category:Lists of office-holders|Indonesia, List of Presidents of]]\n[[id:Daftar Presiden Indonesia]]\n[[ms:Presiden-presiden Indonesia]]','',0,'220.31.240.165','20040722235521','',0,0,0,1,0.20300113652,'20050210184507','79959277764478'); INSERT INTO cur VALUES (993,0,'Abdurrahman_Wahid','\'\'\'Abdurrahman Wahid\'\'\' (biasa disebut ogé \'\'\'Gus Dur\'\'\') (lahir [[4 Agustus]], [[1940]]) ngajabat [[Présidén Indonésia]] ti taun [[1999]] nepi ka [[2001]], sarta pamingpin [[Partai Kebangkitan Bangsa]], nu diadegkeun sanggeus [[Suharto]] turun jabatan. Anjeunna ngarupakeun inohong ti [[Nahdlatul Ulama]]. Ku alatan kasakit jeung masalah korupsi, anjeunna diturunkeun tina jabatan présidén bulan Juli 2001.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n[[Daptar Présidén Indonésia|Présidén Indonésia]]
\n\'\'\'Saméméhna\'\'\':
\n[[B. J. Habibie]]
\n([[1998]] - [[1999]])\n
\n\'\'\'Abdurrahman Wahid\'\'\'
\n([[1999]] - [[2001]])\n
\n\'\'\'Diganti ku\'\'\':
\n[[Megawati Sukarnoputri]]
\n([[2001]]-)\n
\n[[Pulitik Indonésia]]\n
\n\n\n{{pondok}}\n\n[[de:Abdurrahman Wahid]] [[ja:ワヒド]]','',3,'Kandar','20041122082434','',0,0,0,0,0.786393774574,'20050303211247','79958877917565'); INSERT INTO cur VALUES (994,0,'Likelihood','Dina [[statistik]], \'\'\'fungsi likelihood\'\'\' ngarupakeun fungsi conditional probabilitas dumasar kana \"pertimbangan\" fungsi alesan \'\'kadua\'\' numana fungsi mimiti dianggap angger, ahirna:\n\n:B\\mapsto P(A|B),\n\nsalian ti eta fungsi sejen proporsional saperti halna fungsi likelihood. \nKusabab kitu, fungsi likelihood keur \'\'B\'\' ngarupakeun [[equivalence class]] tina fungsi \n\n:L(b) = \\alpha \\; P(A|B=b)\n\nfor any constant of proportionality α > 0. Thus the numerical value \'\'L\'\'(\'\'b\'\') is immaterial; all that matters are ratios of the form \n\'\'L\'\'(\'\'b\'\'2)/\'\'L\'\'(\'\'b\'\'1),\nsince these are invariant with respect to the constant of proportionality.\n\n\'\'\'\'\'Likelihood\'\'\'\'\' as a solitary term is a shorthand for \'\'\'\'\'likelihood function\'\'\'\'\'. In the colloquial language, \"likelihood\" is one of several informal synomyms for \"probability\", but throughout this article we use only the technical definition. \n\nIn a sense, likelihood works backwards from probability: given \'\'B\'\', we use the conditional probability P(\'\'A\'\' | \'\'B\'\') to reason about \'\'A\'\', and, given \'\'A\'\', we use the likelihood function P(\'\'A\'\' | \'\'B\'\') to reason about \'\'B\'\'.\nThis mode of reasoning is formalized in [[Bayes\' theorem]]; \nnote the appearance of a likelihood function for \'\'B\'\' given \'\'A\'\' in:\n:P(B|A) = \\frac{P(A|B)\\;P(B)}{P(A)}\nsince, as functions of \'\'B\'\', both P(\'\'A\'\'|\'\'B\'\') and P(\'\'A\'\'|\'\'B\'\')/P(\'\'A\'\') are likelihood functions for \'\'B\'\' given \'\'A\'\'.\n\nFor more about making inferences via likelihood functions, see also\nthe method of [[maximum likelihood]], and [[likelihood-ratio test]]ing.\n\n\n==Likelihood function of a parametrized model==\n\nAmong many applications, we consider here one of broad theoretical and practical importance.\nGiven a parametrized family of [[probability density function]]s\n\n:x\\mapsto f(x\\mid\\theta),\n\nwhere θ is the parameter (in the case of discrete distributions, the probability density functions are probability \"mass\" functions) the \'\'\'likelihood function\'\'\' is\n\n:L(\\theta)=f(x\\mid\\theta),\n\nwhere \'\'x\'\' is the observed outcome of an experiment. In other words, when \'\'f\'\'(\'\'x\'\' | θ) is viewed as a function of \'\'x\'\' with θ fixed, it is a probability density function, and when viewed as a function of θ with \'\'x\'\' fixed, it is a likelihood function.\n\n\'\'Note:\'\' This is \'\'not\'\' the same as the probability that those parameters are the right ones, given the observed sample. Attempting to interpret the likelihood of a hypothesis given observed evidence as the probability of the hypothesis is a common error, with potentially disastrous real-world consequences in medicine, engineering or jurisprudence. See [[prosecutor\'s fallacy]] for an example of this.\n\n== Example ==\n\nFor example, if I toss a coin, with a probability \'\'pH\'\' of landing heads up (\'H\'), the probability of getting two heads in two trials (\'HH\') is \'\'pH2\'\'. If \'\'pH\'\' = 0.5, then the probability of seeing two heads is 0.25. \n\nIn symbols, we can say the above as \n\n:P(\\mbox{HH} \\mid p_H = 0.5) = 0.25\n\nAnother way of saying this is to reverse it and say that \"the likelihood of \'\'pH\'\' = 0.5 given the observation \'HH\' is 0.25\", i.e., \n\n:L(p_H=0.5 \\mid \\mbox{HH}) = P(\\mbox{HH}\\mid p_H=0.5) =0.25.\n\nBut this is not the same as saying that the \'\'probability\'\' of \'\'pH\'\' = 0.5 given the observation is 0.25.\n\nTo take an extreme case, on this basis we can say \"the likelihood of \'\'pH\'\' = 1 given the observation \'HH\' is 1\". But it is clearly not the case that the \'\'probability\'\' of \'\'pH\'\' = 1 given the observation is 1: the event \'HH\' can occur for any \'\'pH\'\' > 0 (and often does, in reality, for \'\'pH\'\' roughly 0.5).\n\nThe likelihood function does not in general follow all the [[axioms of probability]]: for example, the integral of a likelihood function is not in general 1. This is because integration of the likelihood density function \'\'L\'\' is performed over all possible values of the model parameters (in this case, \'\'p\'\'\'\'H\'\'), while integration of a probability density function \'\'f\'\' is performed over the random variables (which in this case take on the four pairs of values \'TT\', \'TH\', \'HT\' and \'HH\'). In this example, the integral of the likelihood density over the interval [0, 1] in \'\'pH\'\' is 1/3, demonstrating again that the likelihood density function cannot be interpreted as a probability density function for \'\'pH\'\'. On the other hand, given any particular value of pH, e.g. pH=0.5, the integral of the probability density function over the domain of the [[random variable]]s \'\'\'is\'\'\' 1.\n\nSee also:\n* [[Bayesian inference]]\n* [[Likelihood principle]]\n* [[Likelihood-ratio test]]\n* [[Maximum likelihood method]]\n* The [[principle of maximum entropy]] is also related to the maximum likelihood method\n* [[Minimum entropy method]]\n* [[score (statistics)]]','',13,'Budhi','20040723001939','',0,0,0,0,0.970024064635,'20040904061007','79959276998060'); INSERT INTO cur VALUES (995,0,'Estimator','Dina [[statistik]], \'\'\'estimator\'\'\' nyaeta fungsi data \"diketahui\" numana digunakeun keur nga-\"estimasi\" [[parameter]] anu teu \"diketahui\". Lobana estimators nu beda ngamungkinkuen keur unggal paramater anu \"diberikan\". Sabaraha kriteria digunakeun keur milih antar estimator. Geus ilahar lamun hiji kriteria teu jelas keur nangtukeun hiji \'\'estimator\'\' ka \'\'estimator\'\' sejenna.\n\nAya dua tipe \'\'estimator\'\' nyaeta: \'\'point estimators\'\', jeung \'\'interval estimators\'\'.\n\n== Point estimators ==\n\nPoint estimator \'\'\'θ\'\'\' tina parameter θ:\n\n# \'\'[[bias (statistics)|Bias]]\'\' ti \'\'\'θ\'\'\' diartikeun B(\'\'\'θ\'\'\') = E[\'\'\'θ\'\'\'] − θ\n# \'\'\'θ\'\'\' nyaeta \'\'[[bias (statistics)|unbiased estimator]]\'\' ti θ \"jika dan hanya jika\" B(\'\'\'θ\'\'\') = 0 keur sakabeh θ\n# \'\'Mean square error\'\' ti \'\'\'θ\'\'\' diartikeun MSE(\'\'\'θ\'\'\') = E[(\'\'\'θ\'\'\' − θ)2]\n# MSE(\'\'\'θ\'\'\') = V(\'\'\'θ\'\'\') + (B(\'\'\'θ\'\'\'))2\n# [[Simpangan baku]] \'\'\'θ\'\'\' oge disebut \'\'standard error\'\' ti \'\'\'θ\'\'\'.\n\nnumana V(X) nyaeta [[varian]] ti X jeung E nyaeta operator [[nilai ekspektasi]].\n\nKadangkala pamilihan \'\'unbiased estimator\'\' ngagunakeun variance panghandapna. Kadangkala oge leuwih dipilih tanpa wates ka \'\'unbiased estimators\'\'; tingali [[Bias (statistics)]]. Ngeunaan \"best unbiased estimators\", tempo oge [[Gauss-Markov theorem]], [[téoréma Lehmann-Scheffé]], [[Rao-Blackwell theorem]].\n\nTempo oge [[Maximum likelihood]].','/* Point estimators */',13,'Budhi','20041225233307','',0,0,1,0,0.373948603111,'20041225233307','79958774766692'); INSERT INTO cur VALUES (996,0,'Gauss-Markov_theorem','\'\'Artikel di dieu \'\'\'lain\'\'\' ngeunaan [[Gauss-Markov process]]es.\'\'\n\n----\n\nDina [[statistik]], the \'\'\'[[Gauss-Markov]] theorem\'\'\', named after [[Carl Friedrich Gauss]] and [[Andrey Markov]], states that in a [[linear model]] in which the errors have expectation zero and are [[uncorrelated]] and have equal variances, the best linear unbiased estimators of the coefficients are the least-squares estimators. More generally, the best linear unbiased estimator of any linear combination of the coefficients is its least-squares estimator. The errors are \'\'\'not\'\'\' assumed to be [[normal distribution|normally distributed]], nor are they assumed to be independent (but only [[uncorrelated]] --- a weaker condition), nor are they assumed to be identically distributed (but only [[homoscedasticity|homoscedastic]] --- a weaker condition, defined below).\n\nMore explicitly, and more concretely, suppose we have\n\n:Y_i=\\beta_0+\\beta_1 x_i+\\varepsilon_i\n\nfor \'\'i\'\' = 1, . . . , \'\'n\'\', where β0 and β1 are non-random but \'\'\'un\'\'\'observable parameters, \'\'xi\'\' are non-random and observable, εi are random, and so \'\'Y\'\'i are random. (We set \'\'x\'\' in lower-case because it is not random, and \'\'Y\'\' in capital because it is random.) The random variables εi are called the \"[[errors and residuals in statistics|errors]]\" (not to be confused with \"residuals\"; see [[errors and residuals in statistics]]). The \'\'\'Gauss-Markov\'\'\' assumptions state that\n\n*{\\rm E}\\left(\\varepsilon_i\\right)=0,\n*{\\rm var}\\left(\\varepsilon_i\\right)=\\sigma^2<\\infty,\n(i.e., all errors have the same variance; that is \"homoscedasticity\"), and\n*{\\rm cov}\\left(\\varepsilon_i,\\varepsilon_j\\right)=0\n\nfor i\\not=j; that is \"uncorrelatedness.\"\nA \'\'\'linear unbiased estimator\'\'\' of β1 is a linear combination\n\n:c_1Y_1+\\cdots+c_nY_n\n\nin which the coefficients \'\'ci\'\' are not allowed depend on the earlier coefficients β\'\'i\'\', since those are not observable, but are allowed to depend on \'\'xi\'\', since those are observable, and whose expected value remains β1 even if the values of β\'\'i\'\' change. (The dependence of the coefficients on the \'\'xi\'\' is typically nonlinear; the estimator is linear in that which is random; that is why this is [[linear regression|\"linear\" regression]].) The \'\'\'[[mean kuadrat kasalahan]]\'\'\' of such an estimator is\n\n:E\\left((c_1Y_1+\\cdots+c_nY_n-\\beta_1)^2\\right),\n\ni.e., it is the expectation of the square of the difference between the estimator and the parameter to be estimated. (The mean squared error of an estimator coincides with the estimator\'s variance if the estimator is unbiased; for biased estimators the mean squared error is the sum of the variance and the square of the bias.) The \'\'\'best linear unbiased estimator\'\'\' is the one with the smallest mean squared error. The \"least-squares estimators\" of β0 and β1 are the functions \\widehat{\\beta}_0 and \\widehat{\\beta}_1 of the \'\'Y\'\'s and the \'\'x\'\'s that make the \'\'\'sum of squares of [[errors and residuals in statistics|residuals]]\'\'\'\n\n:\\sum_{i=1}^n\\left(Y_i-\\widehat{Y}_i\\right)^2=\\sum_{i=1}^n\\left(Y_i-\\left(\\widehat{\\beta}_0+\\widehat{\\beta}_1 x_i\\right)\\right)^2\n\nas small as possible. (It is easy to confuse the concept of \'\'error\'\' introduced early in this article, with this concept of \'\'residual\'\'. For an account of the differences and the relationship between them, see [[errors and residuals in statistics]].)\n\nThe main idea of the proof is that the least-squares estimators are uncorrelated with every \'\'\'linear unbiased estimator of zero\'\'\', i.e., with every linear combination\n\n:a_1Y_1+\\cdots+a_nY_n\n\nwhose coefficients do not depend upon the unobservable β\'\'i\'\' but\nwhose expected value remains zero regardless of how the values of β1 and β2 change.\n\n* See also [[linear regression]].\n\nIn terms of the matrix algebra formulation, the Gauss-Markov theorem shows that the difference between the parameter covariance matrix of an arbirary linear unbiased estimator and OLS is positive semi definite (see also proof in external link).\n\n==Tumbu kaluar==\n*[http://members.aol.com/jeff570/g.html Earliest Known Uses of Some of the Words of Mathematics: G] (brief history and explanation of its name)\n*[http://www.xycoon.com/ols1.htm Proof of the Gauss Markov theorem for multiple linear regression] (makes use of matrix algebra)\n\n[[Category:Statistics]]\n[[Category:Theorems]]','',13,'Budhi','20041224113530','',0,0,1,0,0.74643944844,'20041224113530','79958775886469'); INSERT INTO cur VALUES (997,0,'Gauss-Markov','Frase \'\'\'Gauss-Markov\'\'\' dipake dina dua hal anu beda. Tempo\n*[[Gauss-Markov process]]es dina [[probability theory]].\n*[[Gauss-Markov theorem]] dina [[statistik]] matematik.\nA major point of the latter theorem is that one does \'\'\'not\'\'\' assume the probability distributions are [[sebaran normal|Gaussian]].\n\nThe second sense of \"Gauss-Markov\" is far more widely known than the first because it is well-known to all statisticians, and generally not known to probabilists, whereas the first is known only to probabilists and some statisticians.\n\n{{disambig}}','',13,'Budhi','20040723051755','',0,0,0,0,0.007827921308,'20040723051755','79959276948244'); INSERT INTO cur VALUES (998,0,'Gauss-Markov_process','\'\'This article is \'\'\'not\'\'\' about the [[Gauss-Markov theorem]] of mathematical [[statistics]].\'\'\n\n----\n\nAs one would expect, \'\'\'[[Gauss-Markov]] stochastic processes\'\'\' (named after [[Carl Friedrich Gauss]] and [[Andrey Markov]]) are [[stochastic process]]es that satisfy the requirements for both [[Gaussian process]]es and [[Markov process]]es. \n\nEvery Gauss-Markov process \'\'X\'\'(\'\'t\'\') possesses the three following properties:\n\n# If \'\'h\'\'(\'\'t\'\') is a non-zero scalar function of \'\'t\'\', then \'\'Z\'\'(\'\'t\'\') = \'\'h\'\'(\'\'t\'\')\'\'X\'\'(\'\'t\'\') is also a Gauss-Markov process\n# If \'\'f\'\'(\'\'t\'\') is a non-decreasing scalar function of \'\'t\'\', then \'\'Z\'\'(\'\'t\'\') = \'\'X\'\'(\'\'f\'\'(\'\'t\'\')) is also a Gauss-Markov process\n# There exists a non-zero scalar function \'\'h\'\'(\'\'t\'\') and a non-decreasing scalar function \'\'f\'\'(\'\'t\'\') such that \'\'X\'\'(\'\'t\'\') = \'\'h\'\'(\'\'t\'\')\'\'W\'\'(\'\'f\'\'(\'\'t\'\')), where \'\'W\'\'(\'\'t\'\') is the [[Brownian motion|standard Wiener process]].\n\nProperty (3) means that every Gauss-Markov process can be synthesized from the standard Wiener process (SWP).\n\n[[Category:Stochastic processes]]','',13,'Budhi','20040723003735','',0,0,0,1,0.075281184202,'20040817120900','79959276996264'); INSERT INTO cur VALUES (999,0,'Maximum_likelihood','Dina [[statistik]], metoda \'\'\'maximum likelihood\'\'\', dimimitian ku [[geneticist|ahli genetika]]/[[statistician|ahli statistik]] [[Ronald Fisher|Sir Ronald A. Fisher]], ngarupakeun metoda [[titik estimasi]], nu digunakeun keur nga-estimasi anggota populasi nu teu ka-observasi tina parameter ruang nu di-maksimal-keun ku [[likelihood|fungsi likelihood]].\nTingali p ngalambangkeun parameter populasi teu ka-observasi nu bakal di-estimasi. Tingali X ngalambangkeun random variable nu di-observasi (which in general will not be [[scalar]]-valued, but often will be a vector of probabilistically [[statistical independence|independent]] scalar-valued random variables. The probability of an observed outcome X=x (this is case-sensitive notation!), or the value at (lower-case) x of the probability density function of the random variable (Capital) X, \'\'\'as a function of p with x held fixed\'\'\' is the \'\'\'likelihood function\'\'\'\n:L(p)=P(X=x\\mid p).\nFor example, in a large population of voters, the proportion p who will vote \"yes\" is unobservable, and is to be estimated based on a political opinion poll. A sample of n voters is chosen randomly, and it is observed that x of those n voters will vote \"yes\". Then the likelihood function is\n:L(p)={n \\choose x}p^x(1-p)^{n-x}.\nThe value of p that maximizes L(p) is the \'\'\'maximum-likelihood estimate\'\'\' of p. By finding the root of the first derivative one will obtain x/n as the maximum-likelihood estimate. In this case, as in many other cases, it is much easier to take \nthe logarithm of the likelihood function before finding the root of the derivative:\n:\\frac{x}{p}-\\frac{n-x}{1-p}=0\nTaking the logarithm of the likelihood is so common that the term \'\'\'log-likelihood\'\'\' is commonplace among statisticians. The log-likelihood is closely related to [[information entropy]].\n\nIf we replace the lower-case x with capital X then we have, not the observed value in a particular case, but rather a [[random variable]], which, like all random variables, has a [[probability distribution]]. The value (lower-case) x/n observed in a particular case is an \'\'\'estimate\'\'\'; the random variable (Capital) X/n is an \'\'\'[[estimator]]\'\'\'. The statistician may take the nature of the probability distribution of the \'\'\'estimator\'\'\' to indicate how good the estimator is; in particular it is desirable that the probability that the estimator is far from the parameter p be small. Maximum-likelihood estimators are sometimes better than [[bias (statistics)|unbiased estimator]]s. They also have a property called \"functional invariance\" that unbiased estimators lack: for any function f, the maximum-likelihood estimator of f(p) is f(T), where T is the maximum-likelihood estimator of p.\n\nHowever, the bias of maximum-likelihood estimators can be substantial. Consider a case where \'\'n\'\' tickets numbered from 1 through to \'\'n\'\' are placed in a box and one is selected at random, giving a value \'\'X\'\'. If \'\'n\'\' is unknown, then the maximum-likelihood estimator of \'\'n\'\' is \'\'X\'\', even though the expectation of \'\'X\'\' is only \'\'n\'\'/2; we can only be certain that \'\'n\'\' is at least \'\'X\'\' and is probably more.\n\n[[Category:Statistics]]','',13,'Budhi','20041224044704','',0,0,1,0,0.817083103497,'20041225235727','79958775955295'); INSERT INTO cur VALUES (1000,0,'Information_entropy','[[de:Entropie (Informationstheorie)]] [[nl:entropie (informatietheorie)]][[pl:Entropia (teoria informacji)]][[da:Entropi]]\n[[zh:熵 (信息论)]]\n\n\'\'\'Entropy\'\'\' is a concept in [[thermodynamics]] (see [[thermodynamic entropy]]), [[statistical mechanics]] and [[information theory]]. The two concepts do actually have something in common, although it takes a thorough understanding of both fields for this to become apparent.\n\n[[Claude E. Shannon]] defined a measure of entropy (\'\'H\'\' = − \'\'p1\'\' log2 \'\'p1\'\' − ... − \'\'pn\'\' log2 \'\'pn\'\') that, when applied to an information source, could determine the minimum channel capacity required to reliably transmit the source as encoded binary digits. Shannon\'s formula can be derived by calculating the mathematical expectation of the \'\'amount of information\'\' contained in a digit from the information source. Shannon\'s entropy measure came to be taken as a measure of the uncertainty about the realization of a random variable. It thus served as a proxy capturing the concept of information contained in a message as opposed to the portion of the message that is strictly determined (hence predictable) by inherent structures. For example, redundancy in language structure or statistical properties relating to the occurrence frequencies of letter or word pairs, triplets etc. See [[Markov chain]].\n\nShannon\'s definition of entropy is closely related to [[thermodynamic entropy]] as defined by physicists and many chemists. [[Ludwig Boltzmann|Boltzmann]] and [[Willard Gibbs|Gibbs]] did considerable work on statistical thermodynamics, which became the inspiration for adopting the word \'\'entropy\'\' in information theory. There are relationships between thermodynamic and informational entropy. For example, [[Maxwell\'s demon]] reverses thermodynamic entropy with information but getting that information exactly balances out the thermodynamic gain the demon would otherwise achieve.\n\nIt is important to remember that entropy is a quantity defined in the context of a probabilistic model for a data source. Independent fair coin flips have an entropy of 1 bit per flip. A source that always generates a long string of A\'s has an entropy of 0, since the next character will always be an \'A\'. Empirically, it seems that entropy of English text is about 1.5 bits per character (try compressing it with the [[PPM compression algorithm]]!), though clearly that will vary from text source to text source. The entropy rate of a data source means the average number of [[bit]]s per symbol needed to encode it.\n\n# Many data bits may not convey information. For example, data structures often store information redundantly, or have identical sections regardless of the information in the data structure.\n# The amount of entropy is not always an integer number of bits.\n\nEntropy effectively bounds the performance of the strongest non-lossy (or nearly non-lossy) compression possible, which can be realized in theory by using the [[typical set]] or in practice using [[Huffman coding| Huffman]], [[LZW|Lempel-Ziv]] or [[arithmetic coding]]. \n\nA common way to define entropy for text is based on the [[Markov model]] of text. For an order-0 source (each character is selected independent of the last characters), the binary entropy is:\n\n:\nH(\\mathcal{S}) = - \\sum p_i \\log_2 p_i\n\n\nWhere \'\'p\'\'\'\'i\'\' is the probability of \'\'i\'\'. For a first-order [[Markov chain|Markov source]] (one in which probabilities are dependent on the immediately preceding character but not on older history except through the immediately preceding character), the \'\'\'entropy rate\'\'\' is:\n\n:\nH(\\mathcal{S}) = - \\sum_i p_i \\sum_j \\ p_i (j) \\log_2 p_i (j)\n\n\nWhere \'\'i\'\' is a state (certain preceding characters) and p_i(j) is the probability of j given i as the previous character (s).\n\nIn general the \'\'\'b-ary entropy\'\'\' of a source \\mathcal{S} = (\'\'S\'\',\'\'P\'\') with [[source alphabet]] \'\'S\'\' = {\'\'a\'\'1, ..., \'\'an\'\'} and [[discrete probability distribution]] \'\'P\'\' = {\'\'p\'\'1, ..., \'\'pn\'\'} where \'\'pi\'\' is the probability of \'\'ai\'\' (say \'\'pi\'\' = \'\'p\'\'(\'\'ai\'\')) is defined by:\n\n:\nH_b(\\mathcal{S}) = - \\sum_{i=1}^n p_i \\log_b p_i\n\n\nAnother way to define the entropy function \'\'H\'\' (not using the [[Markov model]]) is by proving that \'\'H\'\' is uniquely defined (as earlier mentioned) [[iff]] \'\'H\'\' satisfies 1) - 3):\n\n1) \'\'H\'\'(\'\'p\'\'1, ..., \'\'pn\'\') is [[defined]] and [[continuous]] [[for all]] \'\'p\'\'1, ..., \'\'pn\'\' where \'\'pi\'\' \\in[0,1] [[for all]] \'\'i\'\' = 1, ..., \'\'n\'\' and \'\'p\'\'1 + ... + \'\'pn\'\' = 1. (Remark that the function solely depends on the probability distribution, not the alphabet.)\n\n2) [[For all]] [[positive integers]] \'\'n\'\', \'\'H\'\' satisfies\n\n:\nH\\left(\\frac{1}{n}, \\ldots, \\frac{1}{n}\\right) < H\\left(\\frac{1}{n+1}, \\ldots, \\frac{1}{n+1}\\right).\n\n\n3) For [[positive integers]] \'\'bi\'\' where \'\'b\'\'1 + ... + \'\'bn\'\' = \'\'n\'\', \'\'H\'\' satisfies\n\n:\nH\\left(\\frac{1}{n}, \\ldots, \\frac{1}{n}\\right) = H\\left(\\frac{b_1}{n}, \\ldots, \\frac{b_k}{n}\\right) + \\sum_{i=1}^k \\frac{b_i}{n} H\\left(\\frac{1}{b_i}, \\ldots, \\frac{1}{b_i}\\right).\n','',13,'Budhi','20040723004846','',0,0,0,1,0.078531945626,'20050120003736','79959276995153'); INSERT INTO cur VALUES (1001,0,'Ranté_Markov','Dina [[matematik]], \'\'\'ranté Markov\'\'\' nyaéta [[prosés stokastik]] nu ngagunakeun [[Markov property]]. \nSalaku prosés, jarak ti heula taya hubunganana jeung jarak ayeuna di dipikanyaho.\n\nDina kasus discrete-time, proses ngabogaan sekuen X1, X2, X3, ... tina [[variabel acak]].\nDomain tina variabel ieu disebut \'\'tetapan ruang\'\', nu mibanda nilai Xn salila dina waktu nu ditangtukeun n.\nLamun conditional distribution \'\'X\'\'\'\'n\'\'+1 dina tetapan ti heula salaku fungsi \'\'X\'\'\'\'n\'\' sorangan,\n\n: P(X_{n+1}|X_0, X_1, X_2, \\ldots, X_n) = P(X_{n+1}|X_n) \n\nsaterusna prosés ieu disebut mibanda \'\'\'sipat Markov\'\'\'.\n\nRanté Markov aya sanggeus [[Andrei Andreevich Markov|A.A. Markov]], nu mimiti ngahasilkeun ieu proses dina taun (1906). Dijadikeun bisa diitung keur tetapan dina ruang anu \"tidak tebatas\" ku [[Andrey Nikolaevich Kolmogorov|Kolmogorov]] (1936).\nRanté Markov patali jeung [[Brownian motion|gerak Brown]] sarta [[ergodic hypothesis|hipotesa ergodik]], dua topik penting dina widang fisik di awal [[twentieth century|abad kaduapuluh]],\ntapi Markov digunakeun oge di luar widang matematika, saperti [[law of large numbers|hukum wilangan gede]] dina kajadian anu pakait.\n\n== Sifat ranté Markov == \n\nRanté Markov dicirikeun ku conditional distribution\n\n: P(X_{n+1}| X_n)\\, \n\nnu disebut prosés \'\'transition probability\'\'.\nKadangkala disebut oge \"one-step\" transition probability.\n\'\'Transition probability\'\' dua tahap, tilu tahap atawa leuwih dijentrekeun tina \'\'transition probability\'\' satahap sarta sifat Markov:\n\n: P(X_{n+2}|X_n) = \\int P(X_{n+2},X_{n+1}|X_n)\\,dX_{n+1} \n = \\int P(X_{n+2}|X_{n+1}) \\, P(X_{n+1}|X_n) \\, dX_{n+1}\n\nSaperti,\n\n: P(X_{n+3}|X_n) = \\int P(X_{n+3}|X_{n+2}) \\int P(X_{n+2}|X_{n+1}) \\, P(X_{n+1}|X_n) \\, dX_{n+1} \\, dX_{n+2}\n\nRumus ieu nyaruakeun keur kayaan waktu nu teu \'\'teratur\'\' di mangsa datang \'\'n\'\'+\'\'k\'\' ku cara ngalikeun transition probabilities sarta nga-\'\'integral\'\'-keun waktu \'\'k\'\'.\n\n[[Marginal distribution]] \'\'P\'\'(\'\'X\'\'\'\'n\'\') nyaeta distribusi nu ditangtukeun dina waktu \'\'n\'\'.\nDistiribusi awal nyaeta \'\'P\'\'(\'\'X\'\'0).\nEvolusi proses ngaliwatan sakali tahap waktu nu dijentrekeun ku \n\n: P(X_{n+1}) = \\int P(X_{n+1}|X_n)\\,P(X_n)\\,dX_n \n\nIeu ngarupakeun versi [[Frobenius-Perron equation]].\nDidinya aya hiji atawa leuwih \'\'tetapan\'\' distribusi π saperti\n\n: \\pi(X) = \\int P(X|Y)\\,\\pi(Y)\\,dY\n\nnumana \'\'Y\'\' ngan sakadar ngaran variabel integrasi.\nSaperti distribution π disebut \'\'stationary distribution\'\' atawa \'\'steady-state distribution\'\'.\nStationary distribution nyaeta [[eigenfunction]] tina fungsi \'\'conditional distribution\'\', nu \'\'berhubungan\'\' jeung [[eigenvalue]] 1.\n\nWhether or not there is a stationary distribution,\nand whether or not it is unique if it does exist,\nare determined by certain properties of the process.\n\'\'Irreducible\'\' means that every state is accessible from every other state.\n\'\'Aperiodic\'\' means that there exists at least one state for which the transition from that state to itself is possible. \'\'Positive recurrent\'\' means that the expected return time is finite for every state.\nSometimes the terms \'\'indecomposable\'\', \'\'acyclic\'\', and \'\'persistent\'\' are used as synonyms for \"irreducible\", \"aperiodic\", and \"recurrent\", respectively.\n\nIf the Markov chain is positive recurrent,\nthere exists a stationary distribution.\nIf it is positive recurrent and irreducible,\nthere exists a unique stationary distribution,\nand furthermore the process constructed by taking the stationary distribution as the initial distribution is [[ergodic theory|ergodic]].\nThen the average of a function \'\'f\'\' over samples of the Markov chain is equal to the average with respect to the stationary distribution,\n\n: \\lim_{n\\rightarrow\\infty}\\; \\frac{1}{n} \\; \\sum_{k=0}^{n-1} f(X_k)\n = \\int f(X)\\,\\pi(X)\\,dX \n\nIn particular,\nthis holds for \'\'f\'\' equal to the identity function.\nMangka nilai average sampel dina waktu nyaeta sarua jeung [[nilai ekspektasi]] tina sebaran \'\'stationary\'\'.\n\nFurthermore,\nthe equivalence of averages also holds if \'\'f\'\' is the [[indicator function]] on some subset \'\'A\'\' of the state space.\n\n: \\lim_{n\\rightarrow\\infty}\\; \\frac{1}{n} \\; \\sum_{k=0}^{n-1} \\chi_A(X_k)\n = \\int_A \\pi(X)\\,dX = \\mu_{\\pi}(A) \n\nwhere μπ is the measure induced by π.\nThis makes it possible to approximate the stationary distribution by a [[histogram]] or other density estimate of a sequence of samples.\n\n== Markov chains dina ruang diskrit state ==\n\nIf the state space is [[finite]],\nthe transition probability distribution can be represented as a matrix,\ncalled the \'\'transition matrix\'\',\nwith the (\'\'i\'\', \'\'j\'\')\'th element equal to \n\n:P(X_{n+1}=i\\mid X_n=j)\n\n(In this formulation, element (\'\'i\'\', \'\'j\'\') is the probability of a transition from \'\'j\'\' to \'\'i\'\'.\nAn equivalent formulation is sometimes given with element (\'\'i\'\', \'\'j\'\') equal to the probability of a transition from \'\'i\'\' to \'\'j\'\'.\nIn that case the transition matrix is just the [[transpose]] of the one given here.)\n\nFor a discrete state space,\nthe integrations in the \'\'k\'\'-step transition probability are summations,\nand can be computed as the \'\'k\'\'\'th power of the transition matrix.\nThat is, if \'\'P\'\' is the one-step transition matrix, then\n\'\'P\'\'\'\'k\'\' is the transition matrix for the \'\'k\'\'-step transition.\n\nWriting \'\'P\'\' for the transition matrix,\na stationary distribution is a vector which satisfies the equation\n\n: P\\pi = \\pi\\,\n\nIn this case, the stationary distribution is an [[eigenvector]] of the transition matrix,\nassociated with the [[eigenvalue]] 1.\nIf the transition matrix \'\'P\'\' is positive recurrent, irreducible, and aperiodic,\nthen \'\'P\'\'\'\'k\'\' converges elementwise to a matrix in which each column is the unique stationary distribution.\n\nA transition matrix which is positive (that is, every element of the matrix is positive)\nis irreducible, aperiodic, and positive recurrent.\nA matrix is a [[stochastic matrix]] if and only if it is the matrix of transition probabilities of some Markov chain.\n\n==Scientific applications==\n\nMarkov chains are used to model various processes in [[queueing theory]] and [[statistics]], and can also be used as a signal model in [[entropy coding]] techniques such as [[arithmetic coding]]. Markov chains also have many biological applications, particularly [[population process]]es, which are useful in modelling processes that are (at least) analogous to biological populations. Markov chains have been used in [[bioinformatics]] as well. An example is the [[genemark algorithm]] for coding region/gene prediction.\n\nMarkov processes can also be used to generate superficially \"real-looking\" text given a sample document: they are used in various pieces of recreational \"parody generator\" software (see [[Jeff Harrison]]).\n\n==Tempo oge==\n\n* [[Hidden Markov model]]\n* [[Examples of Markov chains]]\n* [[Mark V Shaney]]\n\n== Rujukan ==\n\n* A.A. Markov. \"Rasprostranenie zakona bol\'shih chisel na velichiny, zavisyaschie drug ot druga\". \'\'Izvestiya Fiziko-matematicheskogo obschestva pri Kazanskom universitete\'\', 2-ya seriya, tom 15, pp 135-156, 1906. \n\n* A.A. Markov. \"Extension of the limit theorems of probability theory to a sum of variables connected in a chain\". reprinted in Appendix B of: R. Howard. \'\'Dynamic Probabilistic Systems, volume 1: Markov Chains\'\'. John Wiley and Sons, 1971. \n\n* Leo Breiman. \'\'Probability\'\'. Original edition published by Addison-Wesley, 1968; reprinted by Society for Industrial and Applied Mathematics, 1992. ISBN 0-89871-296-3. \'\'(See Chapter 7.)\'\'\n\n* J.L. Doob. \'\'Stochastic Processes\'\'. New York: John Wiley and Sons, 1953. ISBN 0-471-52369-0.\n\n==Tumbu kaluar==\n\n* [http://crypto.mat.sbg.ac.at/~ste/diss/node6.html Markov Chains]\n\n* [http://www.cs.bell-labs.com/cm/cs/pearls/sec153.html Generating Text] \'\'(About generating random text using a Markov chain.)\'\'\n\n* [http://www.mathworks.com/company/newsletters/news_notes/clevescorner/oct02_cleve.html The World\'s Largest Matrix Computation] \'\'(Google\'s PageRank as the stationary distribution of a random walk through the Web.)\'\'\n\n* [http://www.gnu.org/software/emacs/manual/html_node/emacs_473.html Disassociated Press] in [[Emacs]] approximates a Markov process\n\n[[Category:Téori kamungkinan]]\n[[Category:Prosés stokastik]]\n\n[[de:Markow-Kette]]\n[[en:Markov chain]]\n[[it:Processo markoviano]]','',13,'Budhi','20041224030017','',0,0,1,0,0.742154574367,'20041224030017','79958775969982'); INSERT INTO cur VALUES (1002,0,'Independent_identically-distributed_random_variables','Hiji sekuen atawa kumpulan [[variabel acak]] disebut \'\'\'independent and identically distributed (i.i.d.)\'\'\' lamun satuan anu ngabogaan [[probability distribution]] sarua dina satiap distribusi sejenna jeung sakabehna mutually [[statistical independence|independent]]. Tina sudut pandang [[sample space]] \'\'X\'\', hartina yen \'\'n\'\' percobaan berhubungan dina \'\'X\'\'\'\'n\'\' ka \'\'n\'\'-fold dihasilkeun tina [[probability measure]] keur sakali percobaan.\n\n{{msg:stub','',13,'Budhi','20041224210917','',0,0,1,0,0.436898175365,'20041224210917','79958775789082'); INSERT INTO cur VALUES (1004,1,'Main_Page','#redirect [[Talk:Tepas]]\n','Talk:Main Page dipindahkeun ka Talk:Tepas',3,'Kandar','20040728113716','',0,1,0,1,0.868958660279362,'20040806062717','79959271886283'); INSERT INTO cur VALUES (1005,0,'Wikipédia:Artikel_téh_naon?',': \'\'Tempo ogé: [[Wikipédia:NLD]]\'\'\n\n\'\'\'Artikel Wikipédia\'\'\' hartina kaca nu mibanda béja kawas [[énsiklopédi]] atawa [[almenak]] (\"kawas almenak\" nyaéta daptar, \'\'timelines\'\', tabel, atawa grafik).\n\nTempo [[Special:Allpages]] pikeun daptar sadaya artikel Wikipédia sarta [[Wikipedia:Statistics]] pikeun statistik na Wikipédia jeung pertumbuhanana. \n\n\"Artikel\" teu kaasup kaca naon baé nu \'\'[[wikipedia:namespace|namespace]]\'\'na geus ditangtukeun pikeun tujuan tinangtu, kayaning:\n* \'\'namecspace Wikipédia\'\' pikeun bahan ngeunaan subjék meta nu patali jeung Wikipédia (misalna, [[Wikipedia:Statistics]] jeung kaca omonganana, [[Wikipedia talk:Statistics]]);\n* \'\'namespace talk\'\' pikeun nyawalakeun nu merenah ngeunaan eusi kaca (misalna, [[Talk:Matematik]])\n* \'\'namespace special\'\' nu kacana dijieun ku software dumasar paménta (tempo [[Wikipedia:Special pages]]);\n* \'\'namespace user\'\' pikeun kaca-kaca nu dipaké ku individu kontributor Wikipédia (misal, [[User:Budhi]]).\n* \'\'namespace image\'\' nu dipaké pikeun ngajéntrékeun jeung nandaan gambar (misalna, [[:Image:Anatomi otot.jpg]])\n* \'\'namespace MediaWiki\'\' nu dipaké keur nangtukeun \'\'shortcuts\'\' sarta \'\'string\'\' téks séjén nu dipaké sabudeureun Wikipédia (misal, [[MediaWiki:Disclaimers]])\n\nIn the Monobook (default) skin, the type of page is shown in the currently selected tab and non-article pages have a light blue background. In the Classic skin, pages from these namespaces are displayed on a yellow background to distinguish them from pages in the article namespace.\n\nBut not all pages in the article namespace are considered to be articles; most notably:\n* the [[Main Page]];\n* thousands of \"[[wikipedia:find or fix a stub|stub]]\" pages that may not be considered real articles yet; \n* thousands of [[Wikipedia:Disambiguation|disambiguation pages]] which are used to resolve naming conflicts;\n* thousands of \"[[Wikipedia:redirect|redirect]]\" pages which are used to re-route one page to another page;\n\nThe automatic definition used by the software at [[Special:Statistics]] is: any page that is in the article namespace, is not a [[Wikipedia:Redirect|redirect page]] and contains at least one wiki link. \'\'\'\'\'The statistics software currently has no method of detecting disambiguation pages, however; nor does it disregard Stubs and Stublists (lists templates with little or no content)\'\'\'\'\'.\n\nSee [[Wikipedia:Naming conventions]] to learn how we title articles and [[Wikipedia:protected pages]] for a list of pages that have been made read-only to non-[[Wikipedia:Administrators|Wikipedia Administrators]].\n\n==Tempo ogé==\n\n* [http://www.wikipedia.org/wikistats/EN/TablesArticlesTotal.htm Jumlah artikel kiwari]\n* [[Wikipedia:Artikel minggu ieu|Artikel minggu ieu]]\n\n[[bg:Уикипедия:Статия]] [[cy:Wicipedia:Beth ydy erthygl]] [[da:Wikipedia:Hvad er en artikel]] [[de:Wikipedia:Was ist ein Artikel]] [[el:Wikipedia:Τι είναι ένα άρθρο]] [[en:Wikipedia:What is an article]]\n[[eo:Vikipedio:Kio estas artikolo]] [[it:Wikipedia:Articolo]] [[vi:Wikipedia:Bài bách khoa là cái gi?]] [[ja:Wikipedia:記事とは何か]] [[zh-cn:Wikipedia:什么是条目]] [[zh-tw:Wikipedia:什麽是條目]]','',3,'Kandar','20040723100845','',0,0,0,1,0.291790961424,'20040808225710','79959276899154'); INSERT INTO cur VALUES (1007,0,'Megawati_Sukarnoputri','[[Image:ac.megawati.jpg|frame|Megawati Sukarnoputri]]\n\n\'\'\'Diah Permata Megawati Setiawati Sukarnoputri\'\'\' (born [[23 Januari]] [[1947]]), became the fifth [[President of Indonesia]] on [[23 Juli]] [[2001]]. Early returns from the [[5 Juli]] [[2004]] [[Indonesian presidential election, 2004|Indonesian presidential election]] indicate that she is likely to be defeated in her bid to win a second term.\n\nSome Indonesian sources spell her name Soekarnoputri or Soekarno Putri. Note that Sukarnoputri means \"daughter of Sukarno\" and is not the President\'s surname: [[Java (island)|Javanese]] do not have surnames. She should be referred to as President Megawati.\n\n===Early life===\n\nMegawati was born in [[Jakarta]], the second child and eldest daughter of [[Sukarno]], then the president of Indonesia, which had declared its independence from the [[Netherlands]] in [[1945]]. Her mother Fatmawati was one of Sukarno\'s nine wives. Megawati grew up in luxury in her father\'s Merdeka Palace. \n\nMegawati went to Padjadjaran University in [[Bandung]] to study agriculture, but dropped out in [[1967]] to be with her father following his fall from power. Megawati was 19 when Sukarno was succeeded by a military regime led by [[Suharto]]. Sukarno\'s family was not molested by the new regime provided they stayed out of politics. \n\nIn [[1970]], the year Sukarno died, Megawati went to the University of Indonesia to study psychology but dropped out after two years. Even her warmest admirers would not claim that Megawati is an intellectual, and she has little knowledge of the world outside Indonesia. She is a pious [[Muslim]] but also follows traditional Javanese beliefs and has great faith in [[astrology]]. \n\nMegawati\'s first husband, First Lieutenant Surindo Supjarso, was killed in a plane crash in [[Irian Jaya]] in [[1970]]. In [[1972]], she married Hassan Gamal Ahmad Hasan, an Egyptian diplomat. The marriage was annulled shortly after. She married Taufik Kiemas, her present husband, in [[1973]]. They have three children, M. Rizki Pramata, M. Pranada Prabowo and Puan Maharani, now in their 30s.\n\n===Political career===\n\nMegawati avoided politics for nearly 20 years, describing herself as a simple housewife, although her father\'s followers continued to see her as his political heir. In [[1987]], however, Megawati and her husband joined the [[Indonesian Democracy Party]] (PDI), a government-sanctioned party which provided a facade of democratic choice in Suharto\'s \"New Order\" regime. As a reward for her apparent acceptance of the regime, Megawati was elected to the rubber-stamp Indonesian Parliament.\n\nIn [[1993]] Megawati became the leader of PDI. By this time Suharto was 72 and his regime was weakening. Megawati apparently decided to take up an openly oppositional position. She immediately became hugely popular, despite her lack of experience, mainly because of her name, but also because she was seen as free of corruption and having admirable personal qualities. \n\nBy [[1996]] the regime realised it had made a mistake in allowing Megawati to enter politics, and forced her removal from the leadership of the PDI. This triggered rioting in Jakarta. Megawati was banned from contesting the May [[1997]] general election. This only increased her popularity. She formed her own party, [[Indonesia Democracy Party - Struggle|PDI-Perjuangan]] (PDI-P) (\'\'Perjuangan\'\' means \"Struggle.\") During this period Megawiti displayed great courage in opposing the regime and became a symbol of hope for democratic reform.\n\nThe [[Asian economic crisis]] which began in [[1997]], as well as increasing public anger at pervasive corruption, brought about the end of Suharto’s long rule, and he resigned in May [[1998]]. His successor, [[B. J. Habibie]], promised free elections in [[1999]], and the PDI-P rapidly became the main rival to the government party, [[Golkar]].\n\nAt the June [[1999]] elections, the PDI-P emerged as the largest party, but did not win an absolute majority of votes, or a majority of seats in the Parliament. Under Indonesia\'s new constitution, the President was chosen by the legislature, and Megawati appeared to have the strongest claim to the presidency. But the other parties united to block her, partly because of Muslim opposition to a woman president. Her erstwhile friend and ally, [[Abdurrahman Wahid]], was chosen instead. Megawati agreed to become Vice President. \n\nWahid, however, had suffered several strokes and soon proved to be unable to carry out the role of President. He was also accused of tolerating corruption in the administration. In July [[2001]] the parties in the legislature united to force his resignation. On [[23 Juli]] [[2001]], Megawati was duly installed as the new President of the Republic of Indonesia. \n\nUnder Megawati, the process of democratic reform begun under Habibie and Wahid continued, albeit slowly and erratically. Megawati appeared to see her role mainly as a symbol of national unity, and she rarely actively intervened in government business. The military, disgraced at the time of Suharto\'s fall, regained much of its influence. Corruption continued to be pervasive, though Megawati herself was seldom blamed for this.\n\nSome Indonesian scholars explained Megawati\'s apparent passivity in office by reference to Javanese mythology. Megawati, they said, saw her father, Sukarno, as a \"Good King\" of Javanese legend. Suharto was the \"Bad Prince\" who had usurped the Good King\'s throne. Megawati was the Avenging Daughter who overthrew the Bad Prince and regained the Good King\'s throne. Once this had been achieved, they said, Megawati was content to reign as the Good Queen and leave the business of government to others.\n\n===Future===\n\nAlthough Indonesia\'s economy has partly recovered from the [[1997]] crisis, unemployment and poverty remain high, and there is considerable disappointment at Megawati\'s presidency. The Indonesian Constitution has been amended to provide for the direct election of the President, and Megawati\'s term will expire in [[2004]]. \n\nIn [[2004]] Megawati ran for a second term. She consistently trailed in the opinion polls, due in part to the strong preference for male candidates among Muslim voters, and in part due to her mediocre performance in office. See [[Indonesian presidential election, 2004]] for more details.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n[[List of Presidents of Indonesia|Presidents of Indonesia]]
\n\'\'\'Preceded by\'\'\':
\n[[Abdurrahman Wahid]]
\n([[1999]] - [[2001]])\n
\n\'\'\'Megawati Sukarnoputri\'\'\'
\n([[2001]]-)\n
\n\'\'\'Followed by\'\'\':
\n\'\'\'Current Incumbent\'\'\'
\n([[2001]]-)\n
\n[[Politics of Indonesia]]\n
\n\n[[de:Megawati Sukarnoputri]]\n[[id:Megawati Soekarnoputri]]\n[[ja:メガワティ・スティアワティ・スカルノプトゥリ]]\n[[ms:Megawati Sukarnoputri]]','translating dates',38,'Robin Patterson','20050208235249','',0,0,1,0,0.737671005417,'20050208235249','79949791764750'); INSERT INTO cur VALUES (1008,0,'Téori_kamungkinan','#REDIRECT [[Tiori kamungkinan]]\n','Téori kamungkinan moved to Tiori kamungkinan',3,'Kandar','20040724024003','',0,1,0,1,0.745745833726363,'20040724024003','79959275975996'); INSERT INTO cur VALUES (1009,0,'Téori_kaputusan','#REDIRECT [[Tiori kaputusan]]\n','Téori kaputusan moved to Tiori kaputusan',3,'Kandar','20040724024204','',0,1,0,1,0.121853218527374,'20040724024204','79959275975795'); INSERT INTO cur VALUES (1011,6,'Parabot_lalaki.png','','',3,'Kandar','20040724034133','',0,0,0,1,0.372028622191426,'20050303144037','79959275965866'); INSERT INTO cur VALUES (1012,0,'Sirit','[[image:Parabot lalaki.png|thumb|350px|Anatomi \"Parabot\" Lalaki]]\n\n\'\'\'Sirit\'\'\' ngarupakeun [[organ (anatomi)|organ]] [[sapatemon]] [[jalu]] jeung, pikeun [[mamalia]], organ jalu pikeun [[kiih]]. Sirit [[homolog]] jeung [[itil]] awéwé, sabab tumuwuh tina struktur émbrionik nu sarua. Sirit [[mangkreng]] pikeun pungsina nalika sapetemon.\n\n=== Sirit sato ===\n\nKalolobaan [[marsupial]], iwal dua spésiés [[kangguru]] pangbadagna, mibanda sirit \'\'bifurcated\'\': kabagi jadi dua kolom nu misah, sahingga tungtung siritna nyagak. [[Lumba-lumba]] mibanda kontrol \'\'[[prehensile]]\'\' kana siritna, sahingga kadang dipaké salaku [[sénsor]] pikeun mariksa dasar sagara. [[Kéong]] mibanda sirit pangpanjangna saluyu jeung panjang awakna: nepi ka dua puluh kalieun panjang awakna.\n\n[[Icelandic Phallological Museum]] di [[Reykjavik]] ngahususkeun diri kana ngulik sirit sasatoan.\n\n== Sirit manusa ==\n\nSirit manusa béda ti sirit sababaraha mamalia séjén sabab teu mibanda \'\'tulang mangkreng\'\' \'\'[[erectile bone]]\'\', sagemblengna ngandelkeun aliran getih sangkan mangkreng, teu bisa ngelok kana palangkakan, sarta leuwih badag batan rata-rata dibandingkeun jeung beurat awak.\n\n=== Struktur ===\n\nSirit manusa diwangun ku tilu kolom [[jaringan biologis|jaringan]] pamangkreng:\n* dua [[corpora cavernosa]] jeung\n* hiji [[corpus spongiosum]] di handapeunana.\n\nTungtung corpus spongiosum ngabadagan sarta ngurucut ngabentuk [[hulu sirit]] (\'\'glans penis\'\'). The glans supports the [[foreskin]] or [[prepuce]], a loose fold of skin that in adults can retract to expose the glans. It aids in sexual insertion, keeps the glans moist and provides a gliding action which is said to increase sexual pleasure for the man and his partner as well. For various cultural, religious, and more rarely medical reasons, the foreskin is sometimes partly or completely removed (usually during infancy); this is called [[circumcision]] and is considered by some to be a form of [[mutilation]]. Removal of the same tissue in females is considered by far more people to be mutilation and is outlawed in many countries. The area on the underside of the penis, where the foreskin attaches, is called the [[frenum]] (or frenulum). The inner portion of the foreskin near the sulcus is a highly innervated area known as the [[ridged band]]. Removal of the foreskin by circumcision also usually removes the ridged band and injures or removes the frenulum.\n\nThe [[urethra]], which is the last part of the [[urinary tract]], traverses the corpus spongiosum and its end lies on the tip of the [[glans penis]]. It is both a passage for [[urine]] and for the [[ejaculation]] of [[semen]]. Sperm is produced in the testes and stored in the attached [[epididymis]]. During ejaculation, sperm are propelled up the [[vas deferens]], two ducts that pass over and behind the bladder. Fluids are added by the [[seminal vesicle]]s and the vas deferens turns into the [[ejaculatory duct]]s which join the urethra inside the [[prostate gland]]. The prostate as well as the [[bulbourethral gland]]s add further secretions, and the semen is expelled through the penis.\n\nThe [[raphe]] is the ridge between the lateral halves of the penis, found on the ventral or under side of the penis, running from the anus to the meatus.\n\n=== Celegeng ===\n[[Celegeng]] hartina jadi heurasna sirit nu lumangsung nalika jalu [[rangsangan séx|karangsang]]. Mangkrengna sirit ngabisakeun sapatemon, sanajan teu kudu, sarta sababaraha [[kagiatan séxual]] séjénna.\n\nAlthough the average erect penis points approximately horizontally, it is common and normal for an erect penis to have a wide range of vertical angles, from nearly vertically upward to nearly vertically downward, depending on the tension of the suspensory ligament which holds it in position.\n\n=== Ukuran ===\n\nDibandingkeun jeung ukuran awak, sirit manusa mangrupa di antara nu pangbadagna di [[primata]] mah. Rata-rata sirit manusa panjangna 5 [[inci]] (13 [[cm]]) dina kaayaan mangkreng, bébédaanana teu pati jauh ti sakitu. Ukuran nalika leuleus mah komo deui, rupa-rupa pisan sarta teu bisa nunjukkeun ukuran nalika mangkrengna.\n\nTempo [[ukuran sirit]] pikeun leuwih jéntré ngeunaan jejer ieu.\n\n== Variasi normal sirit ==\nDepending on temperature, a flaccid (not erect) penis of normal size can withdraw almost completely within the body. Such a penis will be of normal size when erect - not unusually small.\n\nOther variations: \n* \'\'Pearly penile papules\'\' are raised bumps of somewhat paler color around the base of the glans and are normal. [http://www.studenthealth.co.uk/leaflets/NormalVariantsInAnogenitalSkin.htm (Picture of them on a human penis)]\n* [[Fordyce\'s spots]] are small, raised, yellowish-white spots 1-2mm in diameter which may appear on the penis, as well as the inner surface and [[vermilion border]] of the lips of the face, and are normal. See \'\'Pearly penile papules\'\' for a picture.\n* \'\'Sebaceous prominences\'\' are similar raised bumps on the shaft of the penis, located at the [[sebaceous gland]]s and are normal.\n* [[Phimosis]], an inability to retract the foreskin fully, is common and harmless in infants and pre-pubescent males, with only about 44 percent of boys having a fully retractable foreskin by age 10. Minimal treatment in the teenage years involves waiting, stretching as in normal masturbation (by emulating thrusting with hand movements, so the foreskin moves over the glans and is gently stretched over time - the [http://www.cirp.org/library/treatment/phimosis/beauge2/ Beaugé method]) or application of steroids. This normal situation is sometimes called \'\'preputial adhesions\'\' or \'\'physiological phimosis\'\'. \'\'True phimosis\'\' involves irritation, [[dysuria]], bleeding, acute or chronic urinary retention and non-retractability. It affects about 1.5% of uncircumcised males by age 17. [http://www.familymedicine.co.uk/features/circum.htm]\n\n== Kelainan nu mangaruhan sirit ==\n\n[[Oedema]] (swelling) of the foreskin can result from sexual activity, including masturbation. It appears worrying but so long as the foreskin is in its normal position and blood flow is present it\'s harmless. See \'\'paraphimosis\'\' for situations where the foreskin can\'t be moved to its normal position or the swelling persists. If the condition recurrs regularly, medical advice should be obtained, since it can be a symptom of conditions such as chronic heart disease. (\'\'[http://www.links.net/vita/corp/catdick/ description of a case resulting from sexual activity, with pictures]\'\')\n\n[[Paraphimosis]] is an inability to move the foreskin forward over the glans. It can result from fluid trapped in a foreskin which is left retracted, perhaps following a medical procedure, or accumulation of fluid in the foreskin because of friction during vigorous sexual activity. Applying pressure to compress the glans, then moving the foreskin to its normal position is the initial procedure to follow, perhaps with the assistance of a lubricant. Placing the penis in normal granulated sugar can reduce the swelling via osmosis. If the condition persists for more than several hours or there\'s a sign of lack of blood flow, a hard glans with no erection or an inability to urinate, it should be treated as a medical emergency.\n\nIn [[Peyronie\'s disease]], anomalous scar tissue grows in the soft tissue of the penis.\n\n[[Pudendal nerve entrapment]] is a condition characterized by pain on sitting and loss of penis (or clitoris) sensation and orgasm. In fact, sometimes there is a total loss of sensation and orgasm. The [[pudendal nerve]] can be damaged by narrow hard cycle seats and accidents. In females it commonly occurs as a result of childbirth. It is treated in France (the leaders in this area), America and Egypt.\n\n[[Penile fracture]] can occur if the erect penis is bent excessively. A pop or cracking sound and pain is normally associated with this event. Emergency medical assistance should be obtained, after which long term consequences are usually prevented. In one study [http://www.blackwell-synergy.com/links/doi/10.1046/j.1464-410X.1996.86420.x/abs/], the few patients suffering permanent penile curvature were the ones who had waited longest before seeking treatment.\n\nIn [[diabetes]], [[peripheral neuropathy]] can cause tingling in the penile skin and possibly reduced or completely absent sensation. The reduced sensations can lead to injuries for either partner and their absence can make it impossible to have sexual pleasure through stimulation of the penis. Since the problems are caused by permanent nerve damage, preventative treatment through good control of the diabetes is the primary treatment. Some limited recovery may be possible through improved diabetes control. \n\n[[Impotence]], sometimes called erectile disfunction or \'\'ED\'\', can reduce the ability to have and maintain a sufficiently firm erection for some activities. A wide variety of generally effective treatments are available. Diabetes is a leading cause, as is normal aging.\n\n=== Kelainan perkembangan sirit ===\n\n[[Hypospadias]] is a [[developmental disorder]] of the penis, where the [[meatus]] is positioned wrongly at birth. It is usually corrected by surgery.\n\nA [[micropenis]] is a very small penis caused by developmental problems.\n\n=== Kelainan psikologis nu patali jeung sirit ===\n\n*[[koro]] - [[delusion]] of shrinkage of the penis and retraction into the body \n*[[penis envy]] - the contested [[Freud]]ian belief of a woman [[envy]]ing men for having a penis\n\n== Body modification ==\n\nThe most common form of penile body modification is the common but controversial \npractice of [[circumcision]].\n\nLess commonly, the penis is sometimes [[body piercing|pierced]] and modified by other [[body art]]. Piercings of the penis include the [[Prince Albert piercing]], the [[Apadravya piercing]], the [[Ampallang piercing]], the [[dydoe piercing]], the [[frenum piercing]] and others.\n\nOther physical modifications to the penis are also performed by some people, although they are considered very extreme. Apart from a [[penectomy]], perhaps the most radical of these is [[subincision]], in which the urethra is bifurcated along the underside of the penis. This modification was originally done among [[Australian Aborigine]]s, although it is now done by some in the U.S. and Europe.\n\nA small number of men who are circumcised attempt to restore their foreskin through various means, including surgical. This is called [[foreskin restoration]].\n\n== Fears and reassurance ==\n\nPossibly due to shame incolcated in regard to genitalia, some people suffer from misunderstandings and resultant fear. \n\n[[Penis panic]] is a kind of hysteria that appears to be culturally conditioned and largely limited to China, Japan, and South-east Asia. \n\nThe \'\'\'normal\'\'\' human penis has what appears to be a scar leading from the foreskin (or from the scar that remains after circumcision) to the scrotum along the underside of the penis. This \"scar\" is actually the \'\'\'biological zipper\'\'\' that closes the urethra during the normal course of fetal development. When the urethra does not close normally, the resulting condition is called [[hypospadias]]. In order to close the urethra all the way to the tip of the penis, surgery must be used. Treatment may involve multiple surgeries, attending pain, and an air of mystery about the entire procedure if the adults involved feel shame about the \"abnormal\" condition of the infant. The reconstructive surgery may sometimes leave scars. The pain, fear, memory of visits to the hospital perhaps accompanied by an air of mystery, and (possibly) the scarring may cause the individual to believe that something terrible happened to him during his early childhood. \n\nAdolescent males trying to masturbate successfully for the first time, and ignorant of the utility of lubricants, may chafe themselves and become fearful due to having learned \"myths\" about penile cancer. Other such beliefs involve the idea that masturbation can cause insanity or blindness.\n\n== Penis size myths and legends ==\n(see also the more detailed article on \'\'[[penis size]]\'\')\n\nMany people are highly concerned with penis size. \nSome men seek [[penis enlargement]], as they perceive that their penis is \"too small\". Studies have shown that most men seeking penis enlargement have normal-sized penises. \n\nMany cultures have a persistent urban legend that the penis size of some minority groups is larger than the norm (about 6 inches, according to most sources). In the United States, the minority group chosen are African-Americans. This appears not to be supported by anything other than anecdote. \nFanon covers this subject in some detail in \"Black Skin, White Masks\", and tends to agree that this is a myth (which he backs up with statistics). \n\nThe only reliable penis-size studies commonly quoted in the literature are the Kinsey study, the UCSF study, and an Italian study, none of which even attempted to correlate with race. There is an ongoing government study in India as well (commissioned with the goal of helping reduce the high condom failure rate there), but it too is unlikely to answer the question. There have been many other studies and claims of varying rigor--for example, the LifeStyles condoms study, but they are generally flawed by selection bias.\n\n==Tempo ogé==\n\n[[impotence]], [[lingam]], [[penis envy]], [[priapism]], [[list of severed penises]], [[circumcision]], [[sexual intercourse]], [[sexual slang]], [[sheath|penis sheath]], and the movie \'\'[[Percy (1970 movie)|Percy]]\'\'.\n\n==Tumbu kaluar==\n*[http://www.cirp.org/pages/anat/ Anatomi Sirit, Mékanik Sapatemon]\n*[http://www.afraidtoask.com/members/index.html Tungtunan \"Parabot\" Lalaki AfraidToAsk.com]\n*[http://www.circumstitions.com/Glossary.html Glosarium Sirit]\n\n{{reproductive_system}}\n\n[[Category:sistim réproduktif]]\n[[Category:andrologi]]\n\n[[af:Penis]]\n[[ca:Penis]]\n[[da:Penis]]\n[[de:Penis]]\n[[en:Penis]]\n[[eo:Peniso]]\n[[es:Pene]]\n[[fi:Siitin]]\n[[fr:Pénis]]\n[[it:Pene]]\n[[ja:陰茎]]\n[[lt:Varpa (lytinis organas)]]\n[[ms:Zakar]]\n[[nl:Penis]]\n[[no:Penis]]\n[[pl:Prącie]]\n[[pt:Pênis]]\n[[simple:Penis]]\n[[sv:Penis]]\n[[zh:阴茎]]','warnfile Adding:lt,af,simple,ms,fi,eo,pt Modifying:pl',42,'Shizhao','20050303144030','',0,0,1,0,0.364315172361,'20050303144030','79949696855969'); INSERT INTO cur VALUES (1013,0,'Nagara','#REDIRECT [[Daptar nagara]]\n','Nagara moved to Daptar nagara',3,'Kandar','20040724044457','',0,1,0,1,0.494583486108653,'20040724044457','79959275955542'); INSERT INTO cur VALUES (1014,0,'Jawa_Kulon','[[Image:IndonesiaWestJava.png|right|Peta nu némbongkeun Jawa Barat di Indonésia]]\n\n\'\'\'Jawa Barat\'\'\' (Jawa Kulon) nyaéta salasahiji [[Propinsi di Indonésia|propinsi]] di [[Indonésia]], ayana di [[Jawa (pulo)|Pulo Jawa]] nu ibukotana di [[Bandung]].\n\n==Sajarah==\n\nSajarah nunjukkeun yén Jawa Barat ngarupakeun propinsi munggaran Indonésia, dumasar kana statement ti Staatblad nomer 378. Dina [[1950]], [[propinsi]] Jawa Barat jadi salah sahiji propinsi di Indonésia.\n\nTanggal [[17 Oktober]] [[2000]], [[Banten]] misah ti Jawa Barat jadi propinsi anyar.\n\n== Géografi jeung Démogarfi ==\n\nJawa Barat (sanggeus Banten misah) populasina 35.500.611 (perkiraan taun 2000) jeung luasna 34736 Km2.\n\nJawa Barat diwatesan ku [[Jakarta]] jeung propinsi [[Banten]] di beulah kulon, jeung [[Central Java]] di beulah wetan. Di beulah kaler [[Java Sea]]. Di beulah kidul [[Indian Ocean]]. Teu saperti umumna propinsi di Indonesia nu ibukotana di daerah pantai, ibukota [[Jawa Barat]] [[Bandung]] ayana di daerah pagunungan sarta daerahna di lingkung ku gunung.\n\nBasa resmi anu digunakeun nyaéta [[Basa Indonesia]], basa séjénna anu populér nyaéta [[basa Sunda]]. Di sababaraha daeérah pakidulan anu deukeut ka wates [[Jawa tengah]], migunakeun [[basa Jawa]]. Di wewengkon [[Cirebon]] jeung sabudeureunana ([[Majalengka]], [[Indramayu]], [[Sumber]], dipaké dua rupa basa nu nyoko ka basa Sunda jeung basa Jawa\n\n== Pamaréntahan ==\n\nDaptar [[kabupatén]] di Jawa Barat:\n\n* Kabupatén [[Bogor]]\n* Kabupatén [[Sukabumi]]\n* Kabupatén [[Cianjur]]\n* Kabupatén [[Bandung]]\n* Kabupatén [[Garut]]\n* Kabupatén [[Tasikmalaya]]\n* Kabupatén [[Ciamis]]\n* Kabupatén [[Kuningan]]\n* Kabupatén [[Cirebon]]\n* Kabupatén [[Majaléngka]]\n* Kabupatén [[Sumedang]]\n* Kabupatén [[Indramayu]]\n* Kabupatén [[Subang]]\n* Kabupatén [[Purwakarta]]\n* Kabupatén [[Karawang]]\n* Kabupatén [[Bekasi]]\n\nDaptar kotamadya jeung kota di Jawa Barat:\n\n* Bogor\n* Sukabumi\n* Bandung\n* Cirebon\n* Bekasi\n* [[Dépok]]\n* [[Cimahi]]\n* Tasikmalaya\n* [[Banjar]]\n\n== Sumber Daya Alam ==\n\nBahan baku alami:\n\n* Kapur ([[Padalarang]])\n* Sababaraha lapangan minyak lepas pantai di [[Java Sea]]\n* Lumber\n\nDaerah perkebunan:\n\n* [[Subang]]\n* [[Puncak]]\n\nSababaraha bendungan keur kaperluan pembangkit listrik.\n\n* [[Jatiluhur]]\n* [[Saguling]]\n* [[Cirata]]\n\n== Pariwisata ==\n\n* [[Ciater]] deukeut [[Subang]]\n* [[Maribaya]] di [[Lembang]]\n* Gunung [[Tangkuban Parahu]]\n* [[Puncak]] \n* Waduk [[Jatiluhur]] \n* [[Taman Safari]] di [[Cipanas]]\n* [[Kebun Raya Bogor]] di [[Bogor]]\n* Basisir [[Pangandaran]]\n* [[Selabintana]] di [[Sukabumi]]\n\n== Tumbu kaluar ==\n\n* [http://www.jabar.go.id Loka resmi Pamaréntah Jawa Barat]\n\n\n{{Indonésia}}\n\n[[id:Jawa Barat]]\n[[en:West Java]]','links',38,'Robin Patterson','20050208234655','',0,0,1,0,0.007571130063,'20050315084342','79949791765344'); INSERT INTO cur VALUES (1015,0,'Jawa_(pulo)','#Redirect [[Java (island)]]','',0,'220.31.240.165','20040724050030','',0,1,0,1,0.290064114281,'20050208040526','79959275949969'); INSERT INTO cur VALUES (1016,0,'Propinsi','\'\'\'Propinsi\'\'\' (Ing: \'\'province\'\') ngarupakeun sebutan pikeun pamaréntahan [[éntitas subnasional]] nu biasana sahambalan handapeun hambalan nasional. Di sababaraha nagara dipaké istilah séjén, misalna nagara bagian (\'\'[[state]]\'\') atawa \'\'[[departemén]]\'\'.\n\nKecap ieu diwanohkeun ku [[Rumawi kuna|urang Rumawi]], nu ngabagi kakaisaranana kana \'\'[[Propinsi Rumawi|provinciae]]\'\'. Sigana kecap ieu asalna tina kecap [[Latin]] \'\'provincia\'\' (wewengkon nu kapangaruhan/dikawasa).\n\n== Kiwari ==\n(Babagian-babagian disebut atawa ditarjamahkeun salaku: Propinsi)\n\n*[[Propinsi di Afghanistan]]\n*[[Propinsi di Argéntina]]\n*[[Propinsi di Bélgia]]\n*[[Daptar propinsi jeung wilayah Kanada|Propinsi di Canada]]\n*[[Propinsi di Cina]]\n*[[Propinsi di Kuba]]\n*[[Propinsi di Ékuador]]\n*[[Propinsi di Finlandia]]\n*[[Propinsi di Indonésia]]\n*[[Propinsi di Iran]]\n*[[Propinsi di Iraq]]\n*[[Propinsi di Irlandia]]\n*[[Propinsi di Itali]]\n*[[Propinsi di Koréa]]\n*[[Propinsi di Walanda]]\n*[[Propinsi di Pakistan]]\n*[[Propinsi di Filipin]]\n*[[Propinsi di Afrika Kidul]]\n*[[Propinsi di Spanyol]]\n*[[Propinsi di Muangtai]]\n*[[Propinsi di Turki]]\n\nPropinsi nu pangpadetna nyaéta [[Henan]], Cina, populasina 93,000,000 urang, dituturkeun ku sababaraha propinsi di CIna kénéh, ogé [[Punjab]], [[Pakistan]], nu pangeusina 85,000,000 urang.\n\nPropinsi panglegana nyaéta [[Xinjiang]], Cina (1,600,000 km2) jeung [[Quebec]], [[Canada]] (1,500,000 km2).\n\n== Sajarah ==\n*[[Propinsi Rumawi#Propinsi Rumawi mangsa 14 M|Propinsi-propinsi Rumawi]]\n*The former [[Provinces of France]]\n*The former [[Provinces of Ireland]]\n*The former [[Provinces of Japan]]\n*The former [[Provinces of Sweden]]\n*The former [[Republic of the Seven United Provinces]] (The Netherlands)\n\n[[en:Province]] [[es:Provincia]] [[ca:Provincia]] [[fr:province]] [[id:Provinsi]] [[it:Provincia]] [[nl:provincie]] [[sv:Provins]] [[zh:省]]','',3,'Kandar','20041125042119','',0,0,0,0,0.530618068544,'20041125042119','79958874957880'); INSERT INTO cur VALUES (1017,0,'Propinsi_di_Indonesia','The number of \'\'\'provinces of [[Indonésia]]\'\'\' has tended to increase as new provinces have been split from existing territories. As of January [[2003]] there appear to be 28 provinces (\'\'propinsi-propinsi\'\', singular - \'\'propinsi\'\'), 2 special regions* (\'\'daerah-daerah istimewa\'\', singular - \'\'daerah istimewa\'\'), and 1 special capital city district** (\'\'daerah khusus ibukota\'\').\n\n*[[New Guinea]]\n**[[Irian Jaya Barat]]\n**[[Papua (Indonesia)|Papua]] (formerly Irian Jaya). A proposal to split this into Papua Barat (West Papua), Papua Tengah (Central Papua) and Papua Timur (East Papua) has not been fully implemented.\n\n*[[Java (island)|Java]]\n**[[Banten]]\n**[[Central Java]] (Jawa Tengah)\n**[[East Java]] (Jawa Timur)\n**[[Jakarta]]**\n**[[Jawa Barat]] \n**[[Yogyakarta]]*\n\n*[[Kalimantan]], the Indonesian part of [[Borneo]]\n**[[Central Kalimantan]] (Kalimantan Tengah)\n**[[East Kalimantan]] (Kalimantan Timur)\n**[[South Kalimantan]] (Kalimantan Selatan)\n**[[West Kalimantan]] (Kalimantan Barat)\n\n*Maluku\n**[[Maluku]]\n**[[North Maluku]] (Maluku Utara)\n\n*Bali and [[Nusa Tenggara]]\n**[[Bali]]\n**[[East Nusa Tenggara]] (Nusa Tenggara Timur)\n**[[West Nusa Tenggara]] (Nusa Tenggara Barat)\n\n*[[Sulawesi]]\n**[[Central Sulawesi]] (Sulawesi Tengah)\n**[[Gorontalo]]\n**[[North Sulawesi]] (Sulawesi Utara)\n**[[South East Sulawesi]] (Sulawesi Tenggara)\n**[[South Sulawesi]] (Sulawesi Selatan)\n\n*[[Sumatra]]\n**[[Aceh]]*\n**[[Bangka-Belitung]]\n**[[Bengkulu]]\n**[[Jambi]]\n**[[Lampung]]\n**[[North Sumatra]] (Sumatera Utara)\n**[[Riau]]\n**[[Riau Islands]] (Kepulauan Riau)\n**[[South Sumatra]] (Sumatera Selatan)\n**[[West Sumatra]] (Sumatera Barat)\n\n==External link==\n\n*[http://www.world-gazetteer.com/s/s_id.htm Map]\n\n[[Category:Lists of subnational entities|Indonesia, Provinces of]] [[Category:Indonesia]]','',3,'Kandar','20041122093542','',0,0,0,0,0.413680865156,'20050208111611','79958877906457'); INSERT INTO cur VALUES (1018,0,'Basa_Sunda','\'\'\'Basa Sunda\'\'\' ngarupakeun [[basa]] nu dipaké ku kurang leuwih 27,000,000 jalma di wewengkon kulon pulo [[Jawa (pulo)|Jawa]], atawa 13,6% ti populasi [[Indonésia]].\n\nBasa Sunda digolongkeun kana famili basa [[Austronésia]] - [[Malayo-Polinésia]] - [[Malayo Kulon-Polinésia]] - Sundik nu mibanda sababaraha dialék/logat dumasar padumukan jalmana: \n*[[Banten]],\n*[[Bogor]],\n*[[Parahyangan]], jeung\n*[[Cirebon]].\n\n[[Parahiangan]], nu ngawengku sabagian badag Tatar Sunda, mangrupa dialék utama (basa lulugu) basa Sunda nu diajarkeun ti mimiti sakola dasar (SD) nepi ka sakola panengah (SLTP).\n\n==Fonologi==\nKiwari, sakumaha di sakabéh wewengkon Indonésia, basa Sunda ditulis dina [[aksara Latin]]. Aya tujuh sora vokal: a, e (pepet), é, i, o, u, jeung eu; tanpa diftong. Foném konsonan kawakilan ku aksara b, c, d, g, h, j, k, l, m, n, p, r, s, t, w, y, ny, jeung ng. Konsonan séjén nu datang ti basa deungeun (misalna Arab jeung Inggris) lolobana dialihbasakeun kana konsonan utama tadi: f -> p, v -> p, sy -> s, sh -> s, z -> j, jeung kh -> h.\n\n==Tata basa dasar==\n(to be written).\n===Kecap asal===\n(to be written).\n===Bentuk aktip===\n(to be written).\n===Négasi===\n(to be written).\n===Pananya===\n(to be written).\n===Bentuk pasif===\n(to be written).\n===Ajéktif===\n(to be written).\n===Préposisis===\n\n====Tempat====\n\n\n\n\n\n\n\n\n
Basa InggrisBasa Sunda
(loma)
Basa Sunda
(lemes)
above ..di luhureun ..di luhureun ..
behind ..di tukangeun ..di pengkereun ..
under ..di handapeun ..di handapeun ..
inside ..di jero ..di lebet ..
outside ..di luar ..di luar ..
between ..
and ..
di antara ..
jeung ..
di antawis ..
sareng ..
\n====Waktu====\n\n\n\n\n\n
Basa InggrisBasa Sunda
(loma)
Basa Sunda
(lemes)
beforesaacansateuacan
aftersanggeussaparantos
duringbasanalika
\n====Rupa-rupa====\n\n\n\n
Basa InggrisBasa Sunda
(loma)
Basa Sunda
(lemes)
fromtinatina
\n\n===Konjungtif===\n(to be written).\n\n==Sajarah==\n===Mangsa I (saméméh abad ka-16 M)===\n\nNepi ka taun 1600 [[Maséhi]], basa Sunda téh mangrupa basa nagara di karajaan [[Salakanagara]], [[Galuh]], [[Kawali]], [[Sunda]], jeung [[Pajajaran]]. Dina ieu mangsa, basa Sunda kaasupan ku basa [[Sansakerta]] saperti anu katémbong dina prasasti titinggal [[Purnawarman]], malah aksarana ogé maké aksara [[Pallawa]].\n\nBasa sunda alam harita dipaké dina widang kanagaraan, kasenian, jeung kahirupan sapopoé, loba kitab ageman anu ditulis dina basa Sunda sarta ngagunakeun aksara Sunda (kuna) saperti \'\'[[Siksa Kanda ng Karesian]]\'\', \'\'[[Carita Parahyangan]]\'\', \'\'[[Darmasiksa]]\'\', jeung \'\'[[Guru Talapakan]]\'\'. Geura titénan basa Sunda nu dipaké alam harita, boh nu aya dina prasasti atawa nu aya dina karya sastrana:\n\n*Transkripsi [[prasasti Ciaruteun]] titinggal Purnawarman\n\n:\'\'\'\'\'Jayaviclasya tarumendrasya hastinah airavabhasya vibhatidam padadavayam\'\'\'\'\'\n\nnu hartina: \'\'ieu (tapak) dua sampéan airawata anu gagah perkasa, gajah inguan pangawasa taruma nu mawa kadigjayaan.\'\'\n\n\n*Transkripsi [[prasasti Pasirmuara]] di [[Cibungbulang]], titinggal karajaan Sunda\n\n:\'\'\'\'\'ini sabdakalanda rakryan juru pengambat I kawihadji panca pasagi marsandeca barpulihkan hadji sunda\'\'\'\'\'\n\nnu hartina: \'\'ieu téh ucapan Rakeyan Juru Pengambat dina taun saka 458 nu nétélakeun yén pamaréntahan daérah dipulihkeun ku Raja Sunda.\'\'\n\n\n*Transkripsi [[prasasti Astana Gede]] titinggal karajaan Sunda di [[Kawali]]\n\n:\'\'\'\'\'nihan tapa kawali nu sanghiyang mulia tapa bhagya parebu raja wastu mangadeg dikuta kawali nu mahayuna kadatuan surawisesa nu marigi sakuriling dayeuh nu najur sgala desa. Aya ma nu pandeuri pakena gawe rahayu pakeun heubeul\'\'\'\'\'\n\nnu hartina: \'\'ieu nu tapa di Kawali téh nyaéta tapana nu mulya lir déwa. Gusti nu bagja, Raja Wastu nu ngéréh di kota Kawali, nu parantos mapaés Karaton Surawisésa nu ngadamel kakalén sakuriling dayeuh, nu nyantosa sakuliah wewengkon, muga-muga kapayunna aya nu kersa midamel kasaéan sangkan punjul sajagat.\'\'\n\n===Mangsa II (1600-1800 Maséhi)===\n\nBasa Sunda dina mangsa ieu geus kapangaruhan ku basa Arab jeung basa Jawa, basa Arab asupna kana basa Sunda ngaliwatan [[pasantrén]], ari basa Jawa asupna kana basa Sunda ngaliwatan padaleman (pamaréntahan). Harita di tatar Sunda geus jlug jleg pasantrén, umumna ajengan nu ngadegkeun pasantrén di urang kungsi masantrén di wétan, jadi salian ngasupkeun basa arab kana basa Sunda pasantrén ogé milu ngasupkeun basa Jawa deuih. Nya di antarana ngaliwatan pasantrén deuih asupna wawacan jeung sarupaning upacarana téh. Kitu deui widang pamaréntahan, harita tatar Sunda kaéréh ku Mataram, para gegedén Sunda (dalem) sataun sakali kudu séba ka dayeuh Mataram, tara sakeudeung di dituna téh, balikna mawa adat cara kadaleman Jawa, nya mangsa harita mimiti asupna \"undak usuk basa\" kana basa Sunda téh, nu mangrupa pangaruh tina basa Jawa (contono dina naskah [[Wawacan Sulanjana]]).\n\n===Mangsa III (1800-1900 M)===\n\nDina ieu mangsa, basa Sunda mimiti kaasupan ku basa [[Walanda]], ngaliwatan para [[bupati]] jeung pagawé Walanda. Mémang harita mah wewengkon Sunda téh geus aya dina genggeman pamaréntah Hindia Walanda, nya harita medalna buku basa Sunda anu ditulis ku [[aksara Latén]] téh. Basa Sunda mimiti dijadikeun ulikan bangsa deungeun utamana bangsa Walanda, salian ti éta basa Sunda ogé mimiti kaasupan basa Malayu deuih. Harita aya katangtuan ti bangsa Walanda sangkan bangsa pribumi, kaasup urang Sunda kudu ngagunakeun basa Malayu minangka \'\'lingua franca\'\'-na (contona aya dina [[Wawacan Panji Wulung]] taun 1876).\n\n===Mangsa IV (1900-1945 M)===\n\nDina ieu mangsa, sakola-sakola beuki réa, basa Sunda terus digunakeun sarta diajarkeun di sakola-sakola. Para panalungtik basa Sunda beuki loba deuih, boh bangsa deungeun atawa urang Sundana sorangan, beuki témbong baé pangaruh basa Walanda kana basa Sunda téh, nepi ka harita mah teu saeutik urang Sunda nu nyaritana direumbeuy ku basa Walanda, utamana kaom palajar. Basa Sunda pacampur jeung basa Arab, Jawa, Malayu, jeung Walanda dipaké dina widang atikan jeung kabudayaan, pikeun nuliskeunana geus prah maké aksara Latén. Dina ieu mangsa, medal [[pustakamangsa]] jeung [[kalawarta]] dina basa Sunda saperti \'\'[[Papaés Nonoman]]\'\' (1915), \'\'[[Pasoendan]]\'\' (1917), \'\'[[Poesaka Soenda]]\'\' (1923), jeung \'\'[[Sipatahoenan]]\'\' (1923).\n\n===Mangsa V (1945-kiwari)===\n\nMangsa ti taun 1945 nepi ka kiwari sok disebut ogé mangsa sabada perang, basa Sunda dipaké dina kahirupan sapopoé, pustakamangsa, sastra, kabudayaan, jeung buku-buku atawa kapustakaan. Mangsa ieu basa Sunda loba kapangaruhan ku basa Indonésia. Dina istilah-istilah basa kosta méméh asup kana basa Sunda téh umumna ngaliwatan heula basa Indonesia, utamana nu dipaké ku masarakat kota, nepi ka aya istilah \"Sunda kamalayon\" geuning, nyaéta basa Sunda anu reumbeuy kapangaruhan ku basa Malayu (Indonesia).\n\n==Tumbu kaluar==\n*http://www.ethnologue.com/show_iso639.asp?code=sun Laporan ngeunaan basa Sunda ti Ethnologue.com\n\n[[Category:Linguistik]]\n[[Category:Sunda]]\n[[Category:Basa]]\n\n[[en:Sundanese language]]','',3,'Kandar','20050309114447','',0,0,0,0,0.219916379182,'20050315075432','79949690885552'); INSERT INTO cur VALUES (1019,0,'Ciamis','== Tumbu kaluar ==\n\n* [http://www.ciamis.go.id Pamarentah Kabupaten Ciamis]\n\n{{Indonesia}}\n[[id:Jawa Barat]]','/* Tumbu kaluar */',13,'Budhi','20040724054731','',0,0,0,0,0.066795059977,'20040724054731','79959275945268'); INSERT INTO cur VALUES (1020,6,'Wiki.png','Lambang Wikipédia Basa Sunda','Lambang Wikipédia Basa Sunda',3,'Kandar','20040724060736','sysop',0,0,0,1,0.356831594702631,'20041130103413','79959275939263'); INSERT INTO cur VALUES (1021,4,'Protection_log','','protected [[Tepas]]: Bilih aya jurig nyiliwuri nu ngareksak eusi kaca',3,'Kandar','20040804064251','sysop',0,0,0,0,0.300407545920841,'20040804064251','79959195935748'); INSERT INTO cur VALUES (1022,0,'Matematik_terapan','\'\'\'Matematik terapan\'\'\' mangrupakeun cabang [[matematik]] that concerns itself with the application of mathematical knowledge to other domains. Such applications include [[analisis numeris]], mathematics of engineering, [[linear programming]], [[optimization]] and [[operations research]], [[continuous modelling]], [[mathematical biology]] and [[bioinformatics]], [[information theory]], [[game theory]], [[probability]] and [[statistics]], [[financial mathematics]], [[actuarial science]], [[cryptography]] and hence [[combinatorics]] and even [[finite geometry]] to some extent, [[graph theory]] as applied to network analysis, and a great deal of what is called [[computer science]]. \n\nThe question of what is applied mathematics does not answer to logical classification so much as to the sociology of professionals who use math. The mathematical methods are usually applied to the specific problem field by means of a [[mathematical model]] of the system.\n\nEngineering math describes physical processes, and so is often indistinguishable from [[theoretical physics]]. Important subdivisions include:\n* [[Fluid dynamics]]\n* [[Acoustic theory]]\n* [[Maxwell\'s equations]] that govern [[electromagnetism]]\n* [[Mechanics]]\n* [[Numerical relativity]]\n\n[[de:Angewandte Mathematik]]\n[[eo:Aplika matematiko]]\n[[fr:Mathématiques appliquées]]\n\n==External links==\n* The [http://www.siam.org/ Society for Industrial and Applied Mathematics] is a professional society dedicated to promoting the interaction between mathematics and other scientific and technical communities.\n* The [http://www.ima.umn.edu/index.html Institute for Mathematics and its Applications] (IMA) was founded by and receives major support from the National Science Foundation Division of Mathematical Sciences to carry out a crucial interdisciplinary mission. It also receives support and direction from its Participating Institutions and Participating Corporations.','',13,'Budhi','20040724064738','',0,0,0,0,0.113073611219,'20040724064738','79959275935261'); INSERT INTO cur VALUES (1023,0,'Sajarah_matematik','[[de:Geschichte der Mathematik]] [[fr:Histoire des mathématiques]] [[pt:História da matemática]] [[sv:Matematikens historia]] [[zh:数学史]]\n\n:\'\'See [[Timeline of mathematics]] for a timeline of events in mathematics. See [[mathematician]] for a list of biographies of mathematicians.\'\'\n\n:\'\'Also see [[The Nine Chapters on the Mathematical Art]] for information about the development of mathematics in China.\'\'\n\nKecap \"[[matematik]]\" asalna tina basa [[Greek language|Greek]] μάθημα (\'\'máthema\'\') hartina \"elmu, pangaweruh, awtawa diajar\"; μαθηματικός (\'\'mathematikós\'\') hartina \"resep diajar\".\n\nSacara sajarah, widang utama dina matematik ningkat kacida keur digunakeun dina widang \"perdagangan\", ngukur taneuh jeung keur \"prediksi\" kajadian astronomi. Hal ieu merlukan tilu hal anu raket pakuat pakaitna nu ngarupakeun \"pembagian dina widang matematik, nyaeta struktur, ruang jeung parobahan.\n\nPangajaran struktur dimimitian ku [[number]]s, firstly the familiar [[natural number]]s and [[integer]]s and their [[arithmetic]]al operations, which are recorded in [[elementary algebra]]. The deeper properties of whole numbers are studied in [[number theory]]. The investigation of methods to solve equations leads to the field of [[abstract algebra]], which, among other things, studies [[ring (mathematics)|rings]] and [[field (mathematics)|field]]s, structures that generalize the properties possessed by the familiar numbers. The physically important concept of [[vector (spatial)|vector]], generalized to [[vector space]]s and studied in [[linear algebra]], belongs to the two branches of structure and space.\n\nThe study of space originates with [[geometry]], first the [[Euclidean geometry]] and [[trigonometry]] of familiar three-dimensional space, but later also generalized to [[Non-euclidean geometry|non-Euclidean geometries]] which play a central role in [[general relativity]]. Several long standing questions about [[ruler and compass constructions]] were finally settled by [[Galois theory]]. The modern fields of [[differential geometry]] and [[algebraic geometry]] generalize geometry in different directions: differential geometry emphasizes the concepts of coordinate system, smoothness and direction, while in algebraic geometry geometrical objects are described as solution sets of [[polynomial]] equations. [[group (mathematics)|Group theory]] investigates the concept of symmetry abstractly and provides a link between the studies of space and structure. [[Topology]] connects the study of space and the study of change by focusing on the concept of [[continuous|continuity]]. \n\nUnderstanding and describing change in measurable quantities is the common theme of the natural sciences, and [[calculus]] was developed as a most useful tool for doing just that. The central concept used to describe a changing variable is that of a [[Fungsi (matematik)|function]]. Many problems lead quite naturally to relations between a quantity and its rate of change, and the methods to solve these are studied in the field of [[differential equations]]. The numbers used to represent continuous quantities are the [[real numbers]], and the detailed study of their properties and the properties of real-valued functions is known as [[real analysis]]. For several reasons, it is convenient to generalise to the [[complex number]]s which are studied in [[complex analysis]]. [[Functional analysis]] focuses attention on (typically infinite-dimensional) spaces of functions, laying the groundwork for [[quantum mechanics]] among many other things. Many phenomena in nature can be described by [[dynamical system]]s and [[chaos theory]] deals with the fact that many of these systems exhibit unpredictable yet deterministic behavior.\n\nIn order to clarify and investigate the foundations of mathematics, the fields of [[set theory]], [[mathematical logic]] and [[model theory]] were developed. \n\nWhen [[computers]] were first conceived, several essential theoretical concepts were shaped by mathematicians, leading to the fields of [[computability theory]], [[computational complexity theory]], [[information theory]] and [[algorithmic information theory]]. Many of these questions are now investigated in theoretical [[computer science]]. \n[[Discrete mathematics]] is the common name for those fields of mathematics useful in computer science.\n\n== Tumbu kaluar ==\n*John J O\'Connor and Edmund F Robertson: \'\'MacTutor History of Mathematics\'\', http://www-groups.dcs.st-andrews.ac.uk/~history/. Contains biographies, timelines and historical articles about mathematical concepts.\n*Jeff Miller: \'\'Earliest uses of various mathematical symbols\'\', http://members.aol.com/jeff570/mathsym.html\n*Jeff Miller: \'\'Earliest known uses of some of the words of mathematics\'\', http://members.aol.com/jeff570/mathword.html\n*Ian Pearce: \'\'History of Indian mathematics\'\', http://www-history.mcs.st-andrews.ac.uk/history/Projects/Pearce/index.html\n* [http://www.jewishencyclopedia.com/view.jsp?artid=259&letter=M&search=mathematics History of Mathematics, public domain article]\n* [[List of important publications in mathematics#Early manuscripts| Important publications in history of mathematics]]\n*Fred Rickey: \'\'History of calculus\'\', http://www.dean.usma.edu/math/people/rickey/hm/default.htm','',13,'Budhi','20041224212641','',0,0,1,0,0.585170568705,'20041224212641','79958775787358'); INSERT INTO cur VALUES (1025,6,'Bandera_indonesia.png','','',13,'Budhi','20040724070441','',0,0,0,1,0.431542976229957,'20050223153616','79959275929558'); INSERT INTO cur VALUES (1026,6,'IndonesiaWestJava.png','','',13,'Budhi','20040724071011','',0,0,0,1,0.256492274120908,'20050208234657','79959275928988'); INSERT INTO cur VALUES (1027,6,'Gaussian-pdf.png','[[Probability density function]] of [[Gaussian distribution]]. Created by Claus Wilke on 07/17/2004 and donated to public domain.\n\nImage was created with program \'\'Grace\'\'.\n\n{{PD}}','',0,'220.31.240.165','20040724073405','',0,0,0,0,0.987832472648316,'20041224031917','79959275926594'); INSERT INTO cur VALUES (1028,6,'Id-map.png','map of Indonesia, converted directly from CIA World Factbook GIF','',13,'Budhi','20040724072635','',0,0,0,0,0.169685571612497,'20050223153616','79959275927364'); INSERT INTO cur VALUES (1029,6,'Rorongkong.jpg','Salinan ti gambar di Wikipedia basa Inggris','Salinan ti gambar di Wikipedia basa Inggris',3,'Kandar','20040724073806','',0,0,0,1,0.884930470851185,'20041124073326','79959275926193'); INSERT INTO cur VALUES (1030,6,'Cumulative_normal_distribution.png','fungsi kumulative distribusi ti wikipedia english','fungsi kumulative distribusi ti wikipedia english',13,'Budhi','20040724110307','',0,0,0,1,0.915595670152079,'20041224031917','79959275889692'); INSERT INTO cur VALUES (1031,6,'Indonesiacoatofarms.jpg','lambang garuda ti wikipedia english','lambang garuda ti wikipedia english',13,'Budhi','20040724112337','',0,0,0,1,0.923186968940484,'20050223153616','79959275887662'); INSERT INTO cur VALUES (1032,0,'Bandéra_Indonésia','[[Image:Indonesia_flag_large.png|thumb|right|250px|Flag ratio: 2:3]]\nBandéra nasional \'\'\'bandéra [[Indonésia]]\'\'\' nyaéta bandéra basajan dua warna (katelah \"dwiwarna\") nu dibagi sacara horizontal, [[beureum]] (luhur) jeung [[bodas]]. Warna ieu dicokot ti Karajaan [[Majapahit]] [[abad la-14]]. Katelah \'\'Sang Saka\'\' (\"dwiwarna nu luhung\") \'\'Merah Putih\'\' (\"beureum bodas\") di [[basa Indonésia|Indonésia]], munggaran dipaké ku para siswa jeung nasionalis mangsa awal [[abad ka-20]] nalika dijajah kénéh ku [[Walanda]]. Nuturkeun [[Perang Dunya II]], para nasionalis Indonésia mroklamirkeun kamerdikaanana [[17 Agustus]] [[1945]], bari ngibarkeun bandéra ieu.\n\n== Tempo ogé == \n* [[Daptar bandéra]]\n* [[Bandéra Monako]], [[Bandéra Solothurn]]: béda ukuran\n* [[Bandéra Polandia]]: warna sarua, tibalik\n\n{{bandéranasional}}\n[[Category:Indonésia]]\n[[Category:Bandéra nasional]]\n[[de:Flagge Indonesiens]]\n[[en:Flag of Indonesia]]\n[[fr:Drapeau de l\'Indonésie]]\n[[he:דגל אינדונזיה]]\n[[ja:インドネシアの国旗]]\n[[sv:Indonesiens flagga]]','/* Tempo ogé */',3,'Kandar','20050316085729','',0,0,0,0,0.022725179336,'20050316085729','79949683914270'); INSERT INTO cur VALUES (1033,6,'LocationIndonesia.png','lokasi indonesia ti wikipedia english','lokasi indonesia ti wikipedia english',13,'Budhi','20040724113302','',0,0,0,1,0.86914786497983,'20050223153616','79959275886697'); INSERT INTO cur VALUES (1034,0,'Provinces_of_Indonesia','#REDIRECT [[Propinsi di Indonesia]]\n','Provinces of Indonesia moved to Propinsi di Indonesia',13,'Budhi','20040724113446','',0,1,0,1,0.57617844881134,'20040724113446','79959275886553'); INSERT INTO cur VALUES (1035,0,'Bandung','\'\'\'Bandung\'\'\' (Ejaan Basa Indonesian heubeul: \'\'Bandoeng\'\') ngarupakeun [[ibukota propinsi]] [[Jawa Barat]], [[Indonésia]]. Aya di dataran luhur [[plateau]] 768 meters di saluhureun laut, lobana jumlah penduduk kurang leuwih 2.1 million. [[Kabupaten Bandung]] ngarupakeun daerah \"suburban\" sakuriling Kota Bandung.\n\n== Sajarah ==\n\nIn [[1488]], the area now named Bandung was the capital of Kingdom of [[Pajajaran]]. During the colonial times, the governing [[Dutch East Indies]] built a supply road connecting [[Batavia]] (now [[Jakarta]]), [[Bogor]], [[Cianjur]], Bandung, [[Sumedang]] and [[Cirebon]]. This event was very important for growth of Bandung. Eventually the Dutch East Indies government planned Bandung to become the capital of the [[Dutch East Indies]] until [[World War II]] disrupted these plans.\n\nIt is not known how long the city of Bandung was built. However, the city was not originally built by the orders of [[Daendels]] (the Dutch East Indies general governor), but it was built by the orders of [[Bupati]] [[R.A. Wiranatakusumah II]]. So [[R.A. Wiranatakusumah II]] is named as the founding father of Bandung.\n\nSanggeus Indonesia merdeka, Bandung jadi [[ibukota propinsi]] [[Jawa Barat]].\n\nThe list of Bandung\'s head of city ([[Walikota]]):\n\n* E.A. Maurenbrecher (1906-1907)\n* R.E. Krijboom (1907-1908)\n* J.A. van Der Ent (1909-1910)\n* J.J. Verwijk (1910-1912)\n* C.C.B. van Vlenier (1912-1913) and B. van Bijveld (1913-1920)\n* B. Coops (1920-1921)\n* S.A. Reitsma (1921-1928)\n* B. Coops (1928-1934)\n* Ir. J.E.A. van Volsogen Kuhr (1934-1936)\n* Mr. J.M. Wesselink (1936-1942)\n* N. Beets (1942-1945)\n* R.A. Atmadinata (1945-1946)\n* R. Siamsurizal\n* Ir. Ukar Bratakusumah (1946-1949)\n* R. Enoch (1949-1956)\n* R. Priatna Kusumah (1956-1966)\n* R. Didi Jukardi (1966-1968)\n* Hidayat Sukarmadijaya (1968-1971)\n* R. Otje Djundjunan (1971-1976)\n* H. Ucu Junaedi (1976-1978)\n* R. Husein Wangsaatnaja (1978-1983)\n* H. Ateng Wahyudi (1983-1993)\n* Wahyu Hamidjaja (1993-1998)\n* Aa Tarmana (1998-2004)\n* H. Dada Rosada, SH,MSi (2004-now)\n\n== Motto ==\n\nThe motto of Bandung is \"Gemah Ripah Wibawa Mukti\" as shown in City of Bandung\'s logo. It means \'rich soil prosperous people\'.\n\n== Government ==\n\nThe City of Bandung is divided into 26 district of [[Kecamatan]]: [[Sukasari]], [[Cidadap]], [[Coblong]], [[Cibeunying Kaler]], [[Cibeunying Kidul]], [[Sukajadi]], [[Cicendo]], [[Andir]], [[Bandung Kulon]], [[Babakan Ciparay]], [[Astana Anyar]], [[Bojongloa Kaler]], [[Bojongloa Kidul]], [[Bandung Kidul]], [[Regol]], [[Lengkong]], [[Sumur Bandung]], [[Bandung Wetan]], [[Kiara Condong]], [[Batununggal]], [[Cicadas]], [[Margacinta]], [[Rancasari]], [[Arcamanik]], [[Ujungberung]], [[Cibiru]].\n\n== Landmarks ==\n\nBandung is known for its large number of old buildings in Dutch architecture: \n\n* [[Gedung Sate]], now functioning as the office of [[West Java]] government.\n* Hotel [[Savoy Homann]] in Jalan Asia-Afrika\n* [[Gedung Dwi Warna]]\n* [[Gedung Merdeka]], a historic building where the [[1955]] [[Conference of Asia and Africa]] took place\n* [[Gedung Pakuan]], now the official residence of Governor of [[West Java]]\n* [[Gedung Yayasan Pusat Kebudayaan]]\n* [[Museum Geologi Bandung]] (Geological Museum of Bandung)\n* There are several old buildings along the street of [[Braga]]\n\nOther landmarks:\n\n* Mesjid Agung Bandung (the great mosque of Bandung), located in the city square (alun-alun)\n* Babakan Siliwangi\n* The unfinished 2.8 Km bridge of [[Pasupati]]. The huge bridge (compared to the relative size of Bandung) is now unfinished, but it will surely be a major landmark once it finished\n\n== Transportation ==\n\nThe primary means of transportation is public transportation cars (in local language: Angkot, or angkutan kota) which serve certain route. There are also not particularly large number of taxis, but they are not popular since a large number of Bandung\'s resident couldn\'t afford them. Buses serve transportation route in big roads and relatively long routes.\n\nA railroad track connects Bandung to [[Jakarta]] and [[Cianjur]] to the west, and [[Tasikmalaya]] and [[Cilacap]] to the east. It is also the major means of transportation for people in neighboring areas of [[Cimahi]], [[Padalarang]], [[Rancaekek]] and [[Cileunyi]] who need to commute to Bandung everyday.\n\nThe major airport of Bandung is [[Husein Sastranegara]], serving flights to other major cities in Indonesia.\n\nThe bridge of Pasupati is being constructed at the time of this writing. It connects the eastern and northern part of Bandung through the valley of [[Cikapundung]]. It is 2.8 Km long and 30-60 meter wide. It is expected to be finished in mid 2005.\n\nTollroad of Padaleunyi connects [[Padalarang]], [[Cimahi]], southern part of Bandung and [[Cileunyi]]. A tollroad that connects Padalarang and [[Purwakarta]] is being constructed, in turn it will connect Bandung and [[Jakarta]]. [[Cileunyi]]-[[Sumedang]] tollroad is also being considered.\n\n== Education ==\n\nA lot of [[Indonesia]]\'s major University is located in Bandung, earning Bandung the name of \'city of education\' or \'city of students\'.\n\n* [[Institut Teknologi Bandung]]\n* [[Universitas Padjajaran]]\n* [[Universitas Katolik Parahyangan]]\n* [[Universitas Maranatha]]\n* [[Institut Teknologi Nasional]]\n\nSome of the best high schools in Indonesia also located in Bandung:\n\n* SMU Negeri 3 Bandung\n* SMU Negeri 5 Bandung\n* SMU St. Aloysius Bandung\n\n== Tourism and Economy ==\n\nBandung and its surrounding area have a lot of tourist attraction:\n\n* Gunung [[Tangkuban Parahu]] to the north of the city.\n* Maribaya\n* Lembang\n* Waduk Jatiluhur\n* Saung Pak Udjo\n\nBandung also known for its wealth of clothing outlet, attacting a huge number of visitors from surrounding cities (particularly from [[Jakarta]]), especially during weekends and holidays:\n\n* Denim clothing industry outlets along the street of [[Cihampelas]]\n* Now, know as \"Kota Wisata Belanja\" - Shopping Tourist City, because so many Factory Outlet which sells ex-export garment products.\n* Bandung also known for its garment industry, some of its product that didn\'t get exported is sold at cheaper price in outlets (in local speak: \'factory outlet\') in Bandung, particularly in Jalan Ir. H. Juanda (Dago) and Jalan R.E. Martadinata (Riau)\n* There are also flourishing shoe industry in [[Cibaduyut]] in southern Bandung\n\nAnybody can find any kind of food in Bandung. However Bandung is also known for its own characteristic food, such as [[peuyeum]].\n\nBandung attracts a lot of visitors from [[Jakarta]], sometimes resulting in severe traffic jam. Most notable is when all Jakarta was being put on holiday because of the [[APEC]] Convention, traffic in Bandung came into halt for more than 8 hours.\n\n== Sports ==\n\nBandung is the home town of [[soccer]] team [[Persib Bandung]]. The soccer team [[Persikab Bandung]] is actually based in neighboring city of [[Cimahi]] although it has the name \'Bandung\' in it. There are also soccer team with less fans such as [[Bandung Raya]]. The most popular stadium is [[Stadion Siliwangi]].\n\nOther popular sports in Bandung include [[Badminton]] and [[Basketball]].\n\n== Tempo ogé ==\n* [[Bandung purba]]\n\n== Tumbu kaluar ==\n\n* [http://www.sundanet.com Sundanet]\n* [http://www.urang-sunda.or.id/index.htm KUSNET - Sundanese Comunity in Internet]\n* [http://www.bandung.go.id The government of Bandung]\n\n----\n\n\'\'\'Bandung\'\'\' is also a [[Malaysia|Malay]]/[[Indonesia]]n drink consisting\nof [[milk]] flavored with [[rosewater]], usually dyed pink.\n\n\n\n[[de:Bandung]]\n[[en:Bandung]]\n[[id:Bandung]]\n[[nl:Bandung]]\n[[zh-cn:万隆]]\n\n== Tumbu kaluar ==\n\n* [http://www.sundanet.com Sundanet]\n* [http://www.urang-sunda.or.id/index.htm KUSNET - Sundanese Comunity in Internet]\n* [http://www.bandung.go.id The government of Bandung]\n\n----\n\n\'\'\'Bandung\'\'\' is also a [[Malaysia|Malay]]/[[Indonesia]]n drink consisting\nof [[milk]] flavored with [[rosewater]], usually dyed pink.\n\n\n\n[[de:Bandung]]\n[[id:Bandung]]\n[[nl:Bandung]]\n[[zh-cn:万隆]]','/* External links */',3,'Kandar','20041123084930','',0,0,0,0,0.878207352887,'20050313153115','79958876915069'); INSERT INTO cur VALUES (1036,0,'Ibukota_propinsi','#REDIRECT [[List of capitals of subnational entities]]','',13,'Budhi','20040724113909','',0,1,0,1,0.986256767058,'20040724114007','79959275886090'); INSERT INTO cur VALUES (1037,0,'Provincial_capital','#REDIRECT [[Ibukota propinsi]]\n','Provincial capital moved to Ibukota propinsi',13,'Budhi','20040724114007','',0,1,0,1,0.273448679850855,'20040724114007','79959275885992'); INSERT INTO cur VALUES (1038,0,'Infrastruktur','[[de:Infrastruktur]] [[en:Infrastructure]] [[fr:infrastructure]]\n\n\'\'\'Infrastruktur\'\'\' nyaéta sakumpulan [[unsur]]-unsur struktural nu silisambung nu nyadiakeun \'\'[[framework]]\'\' pikeun ngarojong [[struktur]] sacara gembleng. Istilah ieu mindeng ogé dipaké sacara abstrak. \n\n== Definition disputes ==\n\nIn [[national security]], the term \"[[critical infrastructure]]\" is also extremely broad (although it should be less inclusive as not all infrastructure should be considered critical) and includes support, e.g. for [[banking]], and other such processes of questionable merit. One issue is the necessity of [[means of protection]], and of [[accounting]], in increasing [[value of life]]. Advocates of a broad definition usually argue that without these \"critical\" systems, the rest of the infrastructure is looted, burned, or not safe to use.\n\nAnother issue is whether [[means of persuasion]], like [[computer]] or [[radio]] or [[television]] [[technology]], can qualify as infrastructure in any sense, as it is more belief-sustaining than life-sustaining. The arguments parallel those for means of protection, with conservatives generally asserting that belief in a common view of reality, especially in [[emergency response]], is critical to survival.\n\n== Urban planning usage ==\n\nThe term is used most often in an [[urban planning]] context to denote the facilities that support specific [[land use]]s and [[built environment]]. \'\'This article focuses on those, to avoid the more political issues above.\'\'\n\nTypically, infrastructure in this context denotes two general groups of support systems: [[transport]]ation modalities ([[road]]s, [[rail]], etc.) and [[utilities]]. These typically compose both public and private systems, and some ambiguously held in common.\n\nInfrastructure may also refer to necessary [[municipal services]], whether provided by the government or by private companies. If provided by [[nature]], e.g. the flow of a [[river]], they are called [[nature\'s services]] and are distincted (at least in economics) as the product of [[natural capital]]. This may be augmented or directed by [[infrastructural capital]], e.g. a dam or canal or irrigation ditch. In general what is called \'\'\'infrastructure\'\'\' tends to be very embedded in the natural [[landscape]] and cannot be moved from place to [[place]]. Even municipal services rely necessarily on fixed [[location]]s, e.g. fire stations in central [[position]]s in a [[city]], [[transmission tower]]s on tall buildings, etc..\n\nInfrastructure (in the civic sense) includes:\n*[[Angkutan]]\n**[[Jalan]]\n**[[Jalanraya]]s\n**[[Jalur karéta]]\n**[[Angkutan umum]]\n**[[Bandara]]\n**[[River freight]]\n**[[Bike path]]s\n**[[Trotoar]]\n*[[Utility|Utilities]]\n**[[Listrik]]\n**[[Gas alam]]\n**[[Coal]] delivery\n**[[cai|Water]] [[water resources|supply]]\n**[[Sewer]]s\n**[[Telephone]] service\n**[[Radio]] and [[television]] [[bandwidth]] allocation\n**[[Cable]] service\n*[[Municipal services]]\n**[[Trash collection]]\n**[[Police]] [[means of protection|protection]]\n**[[Fire]] [[means of protection|protection]]\n**[[Flood protection]]\n**[[Postal system]]\n**[[Mint (coin)|Mint]]ing and backing [[currency]]\n\n*\'\'\'Soft Infrastructure\'\'\' is a term that denotes institutions that maintain the health and cultural standards of the population. Principally, this refers to\n**Public [[Education]]\n**[[Public Health]] Systems \'\'including\'\' Public [[Hospitals]]','',3,'Kandar','20041201072238','',0,0,0,0,0.720078241881,'20041231121518','79958798927761'); INSERT INTO cur VALUES (1039,0,'Pindah','Watesan \'\'\'pindah\'\'\' ngabogaan sabaraha harti anu beda:\n\n*Physical movement between points in space (\"A to B\"). The amount of movement is called [[distance]]. Together with a direction you have a [[displacement]]. The rate of movement is the [[speed]]. Again, with the direction, you get the [[velocity]]. Active movement is called [[locomotion]]. See also under [[transport]].\n\n*In [[music]], a \'\'\'[[movement (music)|movement]]\'\'\' is a large division of a larger [[Musical composition|composition]]. [[Symphonies]] are typically divided into four movements, for example, and [[concerto]]s into three. Each movement has a distinct [[tempo]] and structure.\n*In computergames, a movement is a special way the player can lead his alter ego through the virtual reality.\n*\'\'\'[[Movement (poetry)|Movement]]\'\'\' can also refer to the [[Metre (poetry)|metrical]] or [[Rhythm|rhythmical]] properties of [[poetry]].\n\n*\'\'\'Movement\'\'\' is the term commonly used to refer to a trend in various fields.\n**\'\'\'[[Art movement]]\'\'\'\n**\'\'\'[[Cultural movement]]\'\'\'\n**\'\'\'[[New religious movement]]\n**[[The Movement]] in [[British poetry]].\n\n{{disambig}}\n\n[[de:Bewegung]] [[de:Satz]] [[ja:楽章]] [[simple:Movement]]','',13,'Budhi','20040724131453','',0,0,0,1,0.723283974791,'20040813090305','79959275868546'); INSERT INTO cur VALUES (1040,0,'Arkéologi','\'\'\'Arkéologi\'\'\' nyaéta élmu ngeunaan [[budaya]] manusa ngaliwatan \"penemuan kembali\", dokumentasi jeung analisis \"material sisa\", kaasup [[arsitéktur]], [[artifak]], [[biofak]], sésa-sésa manusa, jeung \'\'[[landscape]]\'\'. Subbab séjén ti [[antropologi]] ngalengkepan papanggihan arkéologi, hususna [[antropologi budaya]] (nu ngulik diménsi budaya paripolah sarta perlambang) jeung [[antropologi fisik]] (nu ngawengku ulikan évolusi manusa jeung ostéologi). Disiplin séjén ogé ngalengkepan arkéologi, kayaning [[paléontologi]] (ulikan kahirupan prasajarah), kaasup [[paléozoologi]] jeung [[paléobotani]], [[géografi]], [[géologi]], [[sajarah]], [[sajarah seni]], jeung \'\'[[classics]]\'\'. \n\nArchaeology is an approach to understanding lost cultures and the mute aspects of human history, without a cutoff date: in England, archaeologists have uncovered the long-lost layouts of medieval villages abandoned after the [[Black Death]] in the 14th century and the equally lost layouts of 17th century parterre gardens swept away by a change in fashion. In downtown [[New York City|New York]] archaeologists have exhumed the 18th century remains of the Black burial ground. \n\nIn the study of relatively recent cultures which have been observed and studied by Western scholars, archaeology is closely allied with [[ethnography]]. This is the case in large parts of [[North America]], the [[South Pacific]], [[Siberia]], and other places. In the study of cultures that were literate or had literate neighbors, [[history]] and archaeology supplement one another for broader understanding of the complete cultural context, as at [[Hadrian\'s Wall]].\n\n==Importance and applicability==\n\nMost of human history is not described by any written records. [[Writing]] did not exist anywhere in the world until about 5000 years ago, and only spread among a relatively small number of technologically advanced [[civilization]]s. These civilizations are, not coincidentally, the best-known; they have been open to the inquiry of historians for centuries, while archaeology has arisen only recently. Even within a civilization that is literate at some levels, many important human practices are not officially recorded. Any knowledge of the formative early years of human civilization - the development of [[agriculture]], cult practices of folk religion, the rise of the first [[city|cities]] - must come from archaeology.\n\nEven where written records do exist, they are invariably incomplete or biased to some extent. In many societies, literacy was restricted to the elite classes, such as the [[clergy]] or the [[bureaucracy]] of court or temple. The literacy even of an [[aristocracy]] has sometimes been restricted to deeds and contracts. The interests and world-view of elites are often quite different from the lives and interests of the masses. Any writings that were produced by people more representative of the general population were unlikely to find their way into [[library|libraries]] and be preserved there for posterity. Thus, written records tend to reflect the biases of the literate classes, and cannot be trusted as a sole source. The material record is nearer to a fair representation of society, though it is subject to its own inaccuracies, such as [[sampling bias]] and [[differential preservation]].\n\nIn addition to their scientific importance, archaeological remains sometimes have political significance to descendants of the people who produced them, monetary value to collectors, or simply strong [[aesthetic]] appeal. Many people identify archaeology with the recovery of such religious, political or economic treasures rather than the reconstruction of past societies. \n\nThis view is often espoused in works of popular fiction, such as \'\'[[Raiders of the Lost Ark]]\'\', \'\'[[The Mummy (1999 movie)|The Mummy]]\'\', and \'\'[[King Solomon\'s Mines]]\'\' where the field has become profitable fodder for entertainment. When such unrealistic subjects are treated more seriously, accusations of [[pseudoscience]] are invariably levelled at their proponents. Examples of discredited [[pseudoarchaeology|pseudoarchaeologists]] include [[Erich von Däniken]] and [[Graham Hancock]].\n\nPseudoarchaeology is indeed an accurate description of much of the amateur archaeology conducted in the [[19th century]], but the field has changed much since then. These endeavors, real and fictional, are not representative of the modern state of archaeology.\n\n==Nu ditujul==\n\nThere is still a tremendous emphasis in the practice of archaeology on field techniques and methodologies. These include the tasks of surveying areas in order to find new sites, and digging sites in order to unearth the cultural remains therein, and classification and preservation techniques in order to analyze and keep these remains. Every phase of this process can be a source of information.\n\nThe goals of archaeology are not always the same. There are at least three broad, distinct theories of exactly what archaeological research should do. (These are beyond the scope of the present discussion, and are discussed at length below.) Nevertheless, there is much common ground.\n\n===Subdisiplin akademis===\n\nArchaeological research is sometimes categorized according to the time period which it studies. Certain civilizations have attracted so much attention that their study has been specifically named. These subdisciplines include \'\'[[Assyriology]]\'\' (the [[ancient Near East]]), \'\'[[Classical archaeology]]\'\' ([[ancient Greece|Greece]] and [[ancient Rome|Rome]]), and \'\'[[Egyptology]]\'\' ([[ancient Egypt|Egypt]]). In the United States, all branches concerned with civilizations that left behind written records are called \'\'[[historical archaeology]]\'\'.\n\n\'\'[[Prehistoric archaeology]]\'\' concerns itself with societies that did not have writing systems. The term is generally valid only in Europe and Asia where literate societies emerged without colonial influence. In areas where literacy arrived relatively late, it more convenient to use other terms to divide up the archaeological record. In areas of semi-literacy the term \'\'[[protohistoric archaeology]]\'\' can be adopted to cover the study of societies with very limited written records. One example of a protohistoric site is [[Fort Ross]] on the northern [[California]] coast, which included settlements of literate [[Russia]]ns and non-literate [[American Indian]]s and [[Native American|Alaska native]]s.\n\n\'\'[[Ethnoarchaeology]]\'\' is the study of modern societies resembling extinct ones of archaeological interest, for archaeological purposes. It is often difficult to infer solid conclusions about the structure and values of ancient societies from their material remains, not only because objects are mute and say little about those who crafted and used them, but also because not all objects survive to be uncovered by scholars of a later age. Ethnoarchaeology seeks to determine, for instance, what kinds of objects used in a living settlement are deposited in [[midden]]s or other places where they may be preserved, and how likely an object is to be discarded near to the place where it was used.\n\n\'\'[[Taphonomy]]\'\' is the study of how objects decay and degrade over time. This information is critical to interpretation of artifacts and other objects, so that the work of ancient people can be differentiated from the later work of living creatures and elemental forces.\n\nA selective list of subdisciplines distinguished by time period or region of study is given below.\n\n*[[African archaeology]]\n*[[Archaeology of the Americas]]\n*[[Australian archaeology]]\n*[[European archaeology]]\n*[[Industrial archaeology]] focuses on the preservation of material relics of the [[Industrial Revolution]].\n*[[Landscape archaeology]] involves identifying and studying sites as components in a wider geographical area.\n*[[Maritime archaeology]] is the study of submerged archaeological sites, including [[shipwreck]]s as well as settlements that have been engulfed by bodies of water.\n*[[Middle-Eastern archaeology]]\n*[[Medieval archaeology]] is the study of post-Roman European archaeology until the sixteenth century.\n*[[Post-medieval archaeology]] is the study of material culture in Europe from the sixteenth century onwards.\n*[[Modern archaeology]] is the study of modern society using archaeological methods, eg the [[Tucson Garbage Project]].\n\nThe following is a list of other subdisciplines. Some of these are not areas of study in their own right, and are only methods to be used in larger projects.\n\n*[[Archaeoastronomy]] is the interpretation of ancient sites (such as [[Stonehenge]]) as temples or monuments of an [[astronomical]] nature.\n*[[Archaeometry]] or [[Archaeological Science]] is the application of \'hard\' scientific methods to archaeology such as [[carbon dating]], [[statistics]] and [[remote sensing]].\n*[[Computational archaeology]] is the application of computers, particularly [[GIS]], to archaeology\n*[[Experimental archaeology]] involves attempting to re-enact past processes to test theories about ancient manufacturing, engineering and the effects of time on sites and objects.\n*[[Lithic analysis]] is the analysis of [[stone tool]]s, a diverse and abundant type of artifact.\n*[[Museum studies]] display and interpretation of past remains for the public\n*[[Paleobotany]] is the analysis of [[plant]] remains (often [[pollen]], a relatively durable carrier of [[DNA]]) recovered from archaeological sites.\n*[[Zooarchaeology]] is the analysis of [[animal]] remains.\n*[[Aerial archaeology]] studying sites from air photos, especially by identifying [[cropmarks]]\n\n===Cultural resources management===\n\'\'[[Cultural resources management]]\'\' (CRM) (also called \'\'heritage management\'\' in Britain) is a branch of archaeology that accounts for most research done in the [[United States]] and much of that in [[western Europe]] as well. In the United States, CRM archaeology has been a growing concern since the passage of the [[National Historic Preservation Act]] of [[1966]] and most of the archaeology done in that country today proceeds from either direct or related requirements of that measure. In the United States, the vast majority of taxpayers, scholars, and politicians believe that CRM has helped to preserve much of that nation\'s history and prehistory that would have otherwise been lost in the expansion of cities, dams, and highways. Along with other statutes, this mandates that no construction project on public land or involving public funds may damage an unstudied archaeological site. \n\nThe application of CRM in the United Kingdom is not limited to government-funded projects. Since 1990 [[PPG 16]] has required planners to consider archaeology as a [[material consideration]] in determining applications for new development. As a result, numerous archaeological organisations undertake mitigation work in advance of (or during) construction work in archaeologically sensitive areas, at the developer\'s expense.\n\nAmong the goals of CRM are the identification, preservation, and maintenance of [[cultural]] sites on public and private lands, and the removal of culturally valuable materials from areas where they would otherwise be destroyed by human activity, such as proposed construction. This study involves at least a cursory examination to determine whether or not any significant archaeological sites are present in the area affected by the proposed construction. If these do exist, time and money must be allotted for their excavation. If initial survey and/or test excavation indicates the presence of an extraordinarily valuable site, the construction may be prohibited entirely. CRM is a thriving entity, especially in the United States and Europe where archaeologists from private companies and all levels of government engage in the practice of their discipline.\n\nCultural resources management has doubtless mitigated the destruction of the archaeological record by the ever-sprawling works of Western civilization, but it leaves something to be desired. CRM is conducted by private companies that bid for projects by submitting proposals outlining the work to be done and an expected budget. It is not unheard-of for the agency responsible for the construction to simply choose the proposal that asks for the least funding. CRM archaeologists face considerable time pressure, often being forced to complete their work in a fraction of the time that might be allotted for a purely scholarly endeavor.\n\n==Sajarah arkéologi==\n\n===Asal-usul===\n\nThe exact origins of archaeology as a discipline are uncertain. Excavations of ancient monuments and the collection of antiquities have been taking place for thousands of years. It was only in the [[19th century]], however, that the systematic study of the past through its physical remains began to be carried out in a manner recognisable to modern students of archaeology. Prior to this, excavation had tended to be haphazard; the importance of concepts such as [[stratification]] and [[context]] was completely overlooked. In [[1803]], there was widespread criticism of [[Thomas Bruce, 7th Earl of Elgin]] for removing the \"[[Elgin Marbles]]\" from their rightful place on the [[Parthenon]] in [[Athens]]; but the marble sculptures themselves were valued by his critics only for their aesthetic qualities, not for the information they might supply about Greek civilisation.\n\nBritain was one of the first countries to develop a systematic approach to archaeology and to recognise it as a discipline in its own right (though the debate over whether it is an \"art\" or a \"science\" continues). The first individuals to take a serious interest in the subject were clergymen. Many vicars recorded local landmarks within their parishes, and these might include details of the landscape, as well as ancient monuments such as [[standing stone]]s -- even where they did not recognise the significance of what they were seeing. It is thanks to them that we know about many archaeological features which have since disappeared or been moved. In the sixteenth and seventeenth centuries [[antiquarian|antiquarians]] such as [[John Leland]], [[John Aubrey]] and [[William Stukeley]] conducted surveys of the country, drawing, describing and interpreting the monuments they encountered.\n\nIn America, [[Thomas Jefferson]], possibly inspired by his experiences in Europe, supervised the systematic excavation of an Indian burial mound on his land in [[Virginia]] in [[1784]]. Although Jefferson\'s investigative methods were ahead of his time (and have earned him the nickname from some of the \"father of archaeology\"), they were primitive by today\'s standards. He did not simply dig down into the mound in the hope of \"finding something\"; he cut a wedge out of it in order to examine the stratigraphy. The results did not inspire his contemporaries to do likewise, and they generally continued to hack away indiscriminately at [[tell]] sites in the [[Middle East]], [[barrow|barrows]] in Europe and mounds in North America, destroying valuable archaeological material in the process.\n\nA little later, [[Napoleon Bonaparte|Napoleon]]\'s army carried out excavations during its Egyptian campaign. The emperor had taken with him a force of five hundred civilian scientists, specialists in fields such as biology, chemistry and languages, in order to carry out a full study of the ancient civilisation. The work of [[Jean-François Champollion]] in deciphering the [[Rosetta stone]] to discover the hidden meaning of [[hieroglyphics]] proved the key to the study of [[Egyptology]]. \n\nA major figure in the development of archaeological method was the Victorian [[Augustus Pitt Rivers]]. Archaeology was still an amateur pastime, but Britain\'s colonial period had provided the opportunity to study antiquities in many other countries. Pitt-Rivers himself, having caught the bug during his military career, brought many artefacts back from overseas and, having inherited a large estate with numerous prehistoric features, collected more artefacts off his own land. From his personal collection (the nucleus of the [[museum]] named after him, in [[Oxford]]), he developed a [[typology]], something few had thought of doing but which would be of enormous significance for dating purposes.\n\n[[William Flinders Petrie]] is another man who may legitimately be called the Father of Archaeology, His work in Egypt developed the concept of [[seriation]] which permitted accurate dating long before scientific methods were available to corroborate his chronologies. He was also a meticulous excavator and scrupulous record keeper and laid down many of the ideas behind modern archaeological recording.\n\n===Development of archaeological method===\n\nThe next major figure in the development of archaeology in the UK was [[Mortimer Wheeler]], whose highly disciplined approach to excavation and systematic coverage of much of the country in the [[1920s]] and [[1930s]] brought the science on swiftly. It was not until the introduction of modern technology, from the [[1950s]] onwards that a similar leap forward would be made in field archaeology. Wheeler\'s method of excavation, laying out the site on a grid pattern, though gradually abandoned in favour of the open-area method, still forms the basis of excavation technique.\n\nMeanwhile, the work of Sir [[Arthur Evans]] at [[Knossos]] in [[Crete]] had shed light on the [[Minoan]] civilisation. Many of the finds from this site were catalogued and brought to the [[Ashmolean Museum]] in [[Oxford]], where they could be studied by classicists, whilst an attempt was made to reconstruct much of the original site. Although this was done in a manner that would be considered inappropriate today, it helped raise the profile of archaeology considerably.\n\nThe bomb damage and subsequent rebuilding caused by the [[Second World War]] gave archaeologists the opportunity to meaningfully examine inhabited cities for the first time. Bomb damaged sites provided windows onto the development of European cities whose pasts had been buried beneath working buildings. [[Urban archaeology]] necessitated a new approach as centuries of human occupation had created deep layers of stratigraphy which could often only be seen through the keyholes of individual building plots. In Britain post-war archaeologists such as [[W. F. Grimes]] and [[Martin Biddle]] took the initiative in studying this previously unexamined area and developed the archaeological methods now employed in much CRM and [[Rescue Archaeology| Rescue]] archaeology.\n\nArchaeology was increasingly becoming a professional activity. Although the bulk of an excavation\'s workforce would still consist of volunteers, it would normally be led by a professional. It was now possible to study archaeology as a subject in universities and even schools, and by the end of the [[20th century]] nearly all professional archaeologists, at least in developed countries, were graduates.\n\n===Introduction of technology===\n\nUndoubtedly the major technological development in 20th century archaeology was the introduction of [[radiocarbon dating]], based on a theory first developed by American scientist [[Willard Libby]] in [[1949]]. Despite its many limitations (compared to later methods it is inaccurate; it can only be used on organic matter; it is reliant on a dataset to corroborate it; and it only works with remains from the last 10,000 years), the technique brought about a revolution in archaeological understanding. For the first time, it was possible to put reasonably accurate dates on discoveries such as bones. This in some cases led to a complete reassessment of the significance of past finds. Classic cases included the [[Red Lady of Paviland]]. It was not until [[1989]] that the Catholic church allowed the technique to be used on the [[Turin Shroud]], indicating that the linen fibres were of medieval origin. \n\n[[Lead]], [[strontium]] and [[oxygen]] [[isotope analysis]] can also be applied to human remains to estimate the diet and the even birthplace of study subjects.\n\nRadiocarbon dating was developed almost in tandem with [[dendrochronology]], another valuable archaeological technique. In the western United States dates could be calibrated by reference to the [[bristlecone pine]] of [[California]], which can live for four thousand years or more. Elsewhere, tree ring chronologies are created by aligning shorter sequences that overlap in time.\n\nInorganic items can now also be dated using a variety of techniques adopted from [[physics]] and [[chemistry]]. [[Thermoluminescence dating]] can provide information on the age of ceramics and [[potassium-argon dating]] can provide dates for fossilised [[hominid]] remains.\n\nOther developments, often spin-offs from wartime technology, led to other scientific advances. For field archaeologists, the most significant of these was the introduction of the [[geophysical survey]], enabling an advance picture to be built up of what lies beneath the soil, before excavation even commences. The entire Roman city of [[Viroconium]], modern day [[Wroxeter]], has been surveyed by these methods, though only a small portion has actually been excavated.\n\n===The development of archaeological theory===\n\nThere is no single theory of archaeology, and even definitions are disputed. Until the mid-20th century and the introduction of technology, there was a general consensus that archaeology was closely related to both history and anthropology. Since then, elements of other disciplines such as [[physics]], [[chemistry]], [[biology]], [[metallurgy]], [[engineering]], [[medicine]], etc, have found an overlap, resulting in a need to revisit the fundamental ideas behind archaeology.\n\nThe first major phase in the history of archaeological theory is commonly referred to as \'\'\'[[Cultural-history archaeology|cultural, or culture history]]\'\'\'. The product of cultural history was to group sites into distinct \"cultures\", to determine the geographic spread and timespan of these cultures, and to reconstruct the interactions and flow of ideas between them. Cultural history, as the name suggests, was closely allied with the science of [[history]]. Cultural historians employed the \'\'[[normative model of culture]]\'\', the principle that each culture is a set of norms governing human behavior. Thus, cultures can be distinguished by patterns of craftsmanship; for instance, if one excavated [[sherd]] of pottery is decorated with a triangular pattern, and another sherd with a checkered pattern, they likely belong to different cultures. Such an approach naturally leads to a view of the past as a collection of different populations, classified by their differences and by their influences on each other. Changes in behaviour could be explained by [[Diffusion (anthropology)|diffusion]] whereby new ideas moved, through social and economic ties, from one culture to another. \n\nThe Australian archaeologist [[Vere Gordon Childe]] was one of the first to explore and expand this concept of the relationships between cultures especially in the context of prehistoric Europe. By the 1920s sufficient archaeological material had been excavated and studied to suggest that diffusionism was not the only mechanism through which change occurred. Influenced by the political upheaval of the inter-war period Childe then argued that [[revolution]]s had wrought major changes in past societies. He conjectured a [[Neolithic Revolution]] which inspired people to settle and farm rather than hunt nomadically. This would have led to considerable changes in social organisation which Childe argued led to a second [[Urban Revolution]] which created the first [[city|cities]]. Such macro-scale thinking was in itself revolutionary and Childe\'s ideas are still widely admired and respected. \n\nIn the [[1960s]], a number of young, primarily American archaeologists, such as [[Lewis Binford]], rebelled against the paradigms of cultural history. They proposed a \"New Archaeology\", which would be more \"scientific\" and \"anthropological\". They came to see culture as a set of behavioral processes and traditions. (In time, this view gave rise to the term \'\'\'[[processual archaeology]]\'\'\'). Processualists borrowed from the exact sciences the idea of [[hypothesis]] testing and the [[scientific method]]. They believed that an archaeologist should develop one or more hypotheses about a culture under study, and conduct excavations with the intention of testing these hypotheses against fresh evidence. They had also become frustrated with the older generation\'s teachings through which [[culture]]s had taken precedence over the people being studied themselves. It was becoming clear, largely through the evidence of anthropology, that ethnic groups and their development were not always entirely congruent with the cultures in the archaeological record.\n\nIn the [[1980s]], a new movement arose led by the British archaeologists [[Michael Shanks_(archaeologist)|Michael Shanks]], [[Christopher Tilley]] and [[Ian Hodder]]. It questioned processualism\'s appeals to science and impartiality by claiming that every archaeologist is in fact biased by his or her personal experience and background, and thus truly scientific archaeological work is difficult or impossible. This is especially true in archaeology where experiments (excavations) cannot possibly be repeatable by others as the [[scientific method]] dictates. Exponents of this relativistic method, called \'\'\'[[post-processual archaeology]]\'\'\', analyzed not only the material remains they excavated, but also themselves, their attitudes and opinions. The different approaches to archaeological evidence which every person brings to his or her interpretation result in different [[constructs]] of the past for each individual. The benefit of this approach has been recognised in such fields as visitor interpretation, cultural resource management and ethics in archaeology as well as fieldwork. It has also been seen to have parallels with culture history. \n\nPost-processualism provided an umbrella for all those who decried the processual model of culture, which many feminist and neo-Marxist archaeologists for example believed treated people as mindless automatons and ignored their individuality. \n\nThis divergence of archaeological theory has not progressed identically in all parts of the world where archaeology is conducted. Australian archaeologists have embraced post-processualism, while those in the United States freely combine it with older approaches and methods.\n\n===Idéologi===\nMuch of the early history of professional archaeology was motivated by an attempt to distance itself from pseudo-archeologists and dilettantes, and to establish itself as a science. While this battle has been won, archaeology has been and remains a cultural, gender and political battlefield. Many groups have tried to use archaeology to prove some current cultural or political point. [[Marxism|Marxist]] or Marxist-influenced archaeologists in the [[Soviet Union|USSR]] and the [[United Kingdom|UK]] (among others) often try to prove the truth of [[dialectical materialism]] or to highlight the past (and present) role of conflict between interest groups (e.g. male vs. female, elders vs. juniors, workers vs. owners) in generating social change. Some contemporary cultural groups have tried, with varying degrees of success, to use archaeology to prove their historic right to ownership of an area of land. Many schools of archaeology have been patriarchal, assuming that in prehistory men produced most of the food by hunting, and women produced little nutrition by gathering; more recent studies have exposed the inadequacy of many of these theories. Some used the \"Great Ages\" theory implicit in the [[Three-age system|three-age system]] to argue continuous upwards progress by Western civilization. Much contemporary archaeology is influenced by neo-Darwinian evolutionary thought, phenomenology, post-modernism, agency theory, and cognitive science.\n\n===Schools of theoretical archaeology===\nThese include:\n*[[Functionalism (sociology)|Functionalism]]\n*[[Processualism]] - a systematic approach to culture.\n*[[Post-processualism]] - a relativistic approach to culture.\n*[[Cognitive archaeology]]\n*[[Gender/feminist archaeology]]\n\n==Relations with the public==\n\nEarly archaeology was largely an attempt to uncover spectacular artefacts and features, or to explore vast and mysterious abandoned cities. Such pursuits continue to fascinate the public, portrayed in books (such as \'\'[[King Solomon\'s Mines]]\'\') and films (viz. \'\'[[The Mummy (1999 movie)|The Mummy]]\'\', \'\'[[Raiders of the Lost Ark]]\'\').\n\nMuch thorough and productive research has indeed been conducted in dramatic locales such as [[Copán]] and the [[Valley of the Kings]], but the stuff of modern archaeology is not so reliably sensational. In addition, archaeological adventure stories tend to ignore the painstaking work involved in modern [[archaeological survey|survey]], [[excavation]] and [[archaeological data processing|data processing]] techniques. Some archaeologists refer to such portrayals as \'[[pseudoarchaeology]]\'.\n\nNevertheless, archaeology has profited from its portrayal in the mainstream media. Many practitioners point to the childhood excitement of [[Indiana Jones]] films and [[Tomb Raider]] games as the inspiration for them to enter the field. Archaeologists are also very much reliant on public support, the question of exactly who they are doing their work for is often discussed. Without a strong public interest in the subject, often sparked by significant finds and celebrity archaeologists, it would be a great deal harder for archaeologists to gain the political and financial support they require.\n\nWhere possible, archaeologists now make more provision for public involvement and outreach in larger projects than they once did. However, the move towards professionalisation has meant that volunteer places are now relegated to unskilled labor, and even this is less freely available than before. Developer-funded excavation necessitates a well-trained staff that can work quickly and accurately, observing the necessary [[Health and Safety]] and indemnity insurance issues involved in working on a modern building site to tight deadlines. Certain charities and local government bodies sometimes offer places on research projects either as part of academic work or as a defined community project. There is also a flourishing industry selling places on commercial [[training excavations]] and archaeological holiday tours.\n\nArchaeologists prize local knowledge and often liaise with local historical and archaeological societies. Anyone looking to get involved in the field without having to pay for the privilege should contact a local group.\n\n===Pseudoarkéologi===\n\n\'\'Pseudoarchaeology\'\' is an umbrella term for all activities that claim to be archaeological but in fact violate commonly accepted archaeological practices. It includes much fictional archaeological work (discussed above), as well as some actual activity. Many nonfiction authors have ignored the scientific methods of [[processual archaeology]]. ([[Post-processual archaeology|Postprocessualism]] is a valid branch of archaeology that looks skeptically on claims to scientific impartiality, but it does not conclude that these methods should be entirely dispensed with and forgotten. \"Pseudoarchaeology\" does not address the issues raised by postprocessualists.)\n\nAn example of this type is the author, [[Erich von Däniken]]. His \'\'[[Chariots of the Gods]]\'\' ([[1968]]), together with many subsequent, lesser-known works, expounds a theory of ancient contacts between human civilization on Earth and more technologically advanced extraterrestrial civilizations. (This theory, known as [[palaeocontact theory]], is not exclusively Däniken\'s.) Works of this nature are usually marked by the renunciation of well-established theories on the basis of limited evidence, and the interpretation of evidence with a preconceived theory in mind.\n\n[[Michael Cremo]]\'s work would also be regarded by many as pseudoarchaeology.\n\n===Looting===\nLooting of buried treasure is an ancient problem; for instance, many of the tombs of the Egyptian [[pharaoh]]s were looted in antiquity. The advent of archaeology has made ancient sites objects of great scientific interest, but it has also attracted public attention to the works of past peoples. A brisk commercial demand for artifacts has accelerated the pace of looting and the [[antiquities trade]].\n\nThe popular consciousness may associate looting with Third World countries, former homes to some of the less well-known ancient civilizations and lacking the financial resources to protect even the most fabulous sites. In fact, looting has left a significant mark in places as \"civilized\" and seemingly uninteresting as the United States. Abandoned towns of the ancient [[Sinagua]] people of [[Arizona]], clearly visible in the desert landscape, have been destroyed in large numbers. Sites in more densely populated areas farther east have also been looted.\n\n===Public outreach===\nMotivated by a desire to halt looting, to curb pseudoarchaeology, and to secure greater public funding for their research, archaeologists are mounting public-outreach campaigns. They seek to stop looting by informing prospective artifact collectors of the provenance of these goods, and by alerting people who live near archaeological sites of the threat of looting and the danger that it poses to science. Common methods of public outreach include press releases and the encouragement of school field trips to sites under excavation.\n\n===Descendant peoples===\nIn the United States, American Indians tend to mistrust archaeology. This mistrust is well-founded. For years, American archaeologists have been digging up Indian burial grounds and other places considered sacred, and carting away any artifacts and human remains to storage facilities for further study. Adding insult to injury, many skeletons were not even thoroughly studied. Furthermore, Western archaeologists\' views of the past are different from those of tribal peoples. The West views time as linear; for natives, it is cyclic. From a Western perspective, the past is long-gone; from a native perspective, disturbing the past can have dire consequences in the present. To an archaeologist, the past is long-gone and must be reconstructed; to a native, it is yet alive.\n\nAs a consequence of this misunderstanding, American Indians have often attempted to prevent archaeological excavation of sites inhabited by their ancestors, while American archaeologists have paid them little heed. This situation is beginning to change. The [[Native American Graves Protection and Repatriation Act]] (NAGPRA, [[1990]]), limits the right of research institutions to possess human remains. Due in part to the spirit of postprocessualism, some archaeologists have begun to actively enlist the assistance of native peoples likely to be descended from those under study.\n\nArchaeologists have also been obliged to re-examine what constitutes an archaeological site in view of what native peoples believe to constitute sacred space. To many native peoples, natural features such as lakes, mountains or even individual trees have cultural significance. Australian archaeologists especially have explored this issue and attempted to survey these sites in order to give them some protection them from being developed. Such work requires close links and trust between archaeologists and the people they are trying to help and at the same time study.\n\nWhile this cooperation presents a new set of challenges and hurdles to fieldwork, it has benefits for all parties involved. Tribal elders cooperating with archaeologists can prevent the excavation of areas of sites that they consider sacred, while the archaeologists gain the elders\' aid in interpreting their finds. There have also been active efforts to recruit aboriginal peoples directly into the archaeological profession.\n\n==Métode lapangan==\n\n===Survéy===\nA modern archaeological project often begins with [[archaeological survey|survey]]. \'\'Regional survey\'\' is the attempt to systematically locate previously unknown sites in a region. \'\'Site survey\'\' is the attempt to systematically locate features of interest, such as houses and [[midden]]s, within a site. Each of these two goals may be accomplished with largely the same methods.\n\nSurvey was not widely practiced in the early days of archaeology. Cultural historians and prior researchers were usually content with discovering the locations of monumental sites from the local populace, and excavating only the plainly visible features there. [[Gordon Willey]] pioneered the technique of regional settlement pattern survey in [[1949]] in the [[Viru Valley]] of coastal [[Peru]], and survey of all levels became prominent with the rise of processual archaeology some years later.\n\nSurvey work has many benefits if performed as a preliminary exercise to, or even in place of, excavation. It is requires relatively little time and expense, because it does not require processing large volumes of soil to search out artifacts. (Nevertheless, surveying a large region or site can be expensive, so archaeologists often employ [[sampling (statistics)|sampling]] methods.) It avoids ethical issues (of particular concern to descendant peoples) associated with destroying a site through excavation. It is the only way to gather some forms of information, such as [[settlement pattern]]s and settlement structure. Survey data are commonly assembled into [[map]]s, which may show surface features and/or artifact distribution.\n\nThe simplest survey technique is \'\'[[surface survey]]\'\'. It involves combing an area, usually on foot but sometimes with the use of mechanized transport, to search for features or artifacts visible on the surface. Surface survey cannot detect sites or features that are completely buried under earth, or overgrown with vegetation. Surface survey may also include mini-excavation techniques such as [[auger]]s, [[corer]]s, and [[shovel test]] pits.\n\n\'\'[[Aerial survey]]\'\' is conducted using [[camera]]s attached to [[airplane]]s, [[balloon]]s or even [[kite]]s. A bird\'s-eye view is useful for quick mapping of large or complex sites. Aerial imaging can also detect many things not visible from the surface. [[Plant]]s growing above a stone structure, such as a wall, will develop more slowly, while those above other types of features (such as [[midden]]s) may develop more rapidly. Photographs of ripening [[grain]], which changes color rapidly at maturation, have revealed buried structures with great precision. Aerial survey also employs [[infrared]], ground-penetrating [[radar]] wavelengths, and [[thermography]].\n\n\'\'[[Geophysical survey]]\'\' is the most effective way to see beneath the ground. [[Magnetometer]]s detect minute deviations in the [[planetary magnetic field]] caused by [[iron]] artifacts, [[kiln]]s, some types of stone structures, and even ditches and middens. Devices that measure the [[electrical resistivity]] of the soil are also widely used. Most soils are [[moisture|moist]] below the surface, this gives them a relatively low resistivity. Features such as hard-packed floors or concentrations of stone have a higher resistivity.\n\nRegional survey in maritime archaeology uses [[side-scan sonar]].\n\n===Ékskavasi===\n\n[[Excavation|Archaeological excavation]] existed when the field was still the domain of amateurs, and it remains the source of the majority of data recovered in most field projects. It can reveal several types of information usually not accessible to survey, such as stratigraphy, three-dimensional structure, and verifiably primary context.\n\nModern excavation techniques require that the precise locations of objects and features, known as their [[provenance]] or provenience, be recorded. This always involves determining their horizontal locations, and sometimes vertical position as well. Similarly their [[association]], or relationship with nearby objects and features, needs to be recorded for later analysis. This allows the archaeologist to deduce what artifacts and features were likely used together and which may be from different phases of activity. For example, excavation of a site reveals its [[stratigraphy]]; if a site was occupied by a succession of distinct [[culture]]s, artifacts from more recent cultures will lie above those from more ancient cultures.\n\nExcavation is the most expensive phase of archaeological research. Also, as a destructive process, it carries [[ethics|ethical]] concerns. As a result, very few sites are excavated in their entirety. [[Sampling]] is even more important in excavation than in survey. It is common for large mechanical equipment, such as [[backhoe]]s ([[JCB]]s), to be used in excavation, especially to remove the [[topsoil]] ([[overburden]]), though this method is increasingly used with great caution. Following this it is usual to hand-clean the exposed area with trowels or hoes to ensure that all features are apparent.\n\nThe next task is to produce a site plan and then use it to help decide the method of excavation. Features dug into the natural [[subsoil]] are normally excavated in portions in order to produce a visible [[archaeological section]] for recording. Scaled plans and sections of individual features are all drawn on site, black and white and colour photographs of them are taken and recording sheets are filled in describing the [[context]] of each. All this information serves as a permanent record of the now-destroyed archaeology and is used in describing and interpreting the site.\n\n==Téhnik laboratorium arkéologis==\n\n* [[Déndrokronologi]] - tree ring dating\n* [[Decipherment]]\n* [[Palinologi]] - pollen analysis\n* [[Radiometric dating]]\n* [[Arkéologi rékonstruksi]]\n\n==Jejer nu patali==\n*[[Daptar papanggihan arkéologis nu kawentar]] \n*[[Daptar situs arkéologis nu kawentar]] \n*[[Daptar ahli arkéologi]]\n*[[Tiori sistem na arkéologi]]\n*[[Sajarah nu leungit]]\n\n==Tumbu kaluar==\n* [http://www.eculturalresources.com/ eCulturalResources] - Cultural Resource Management Jobs, News, Consultants, and Resources.\n* [http://www.shovelbums.org/ Shovelbums.org] - Archaeological opportunities mailing list.\n* [http://wasteflake.com/tiki-index.php?page=PopularArchaeology Archaeology in Popular Culture]\n* \'\'[http://www.hallofmaat.com/maat/index.php Hall of Maat]\'\' : Weighing evidence for Alternative History, pseudohistory, and pseudoarchaeology.\n* [http://www.anthropologie.net/ Anthropology Resources on the Internet] - Anthropology Resources on the Internet : a web directory with over 3000 links grouped in specialized topics.\n* [http://www.ericdigests.org/2001-1/archaeology.html Teaching Archaeology. ERIC Digest.]\n* [http://www.african-archaeology.net/ African Archaeology] - African Archaeology : a web directory on Africa.\n* Kristin, \"\'\'[http://www.wasteflake.com/tiki-index.php?page=ArchaeologyFilms Archaeology Films]\'\'\". Wasteflake.com. (List of archaeology films.)\n\n==Bacaan salajengna==\n* Ashmore, W. and Sharer, R. J., \'\'Discovering Our Past: A Brief Introduction to Archaeology\'\' Mountain View: Mayfield Publishing Company. ISBN 076741196X. This has also been used as a source.\n* Neumann, Thomas W. and Robert M. Sanford, \'\'Practicing Archaeology: A Training Manual for Cultural Resources Archaeology\'\' [http://www.rowmanlittlefield.com/ Rowman and Littlefield Pub Inc], August, 2001, hardcover, 450 pages, ISBN 0759100942\n* Sanford, Robert M. and Thomas W. Neumann, \'\'Cultural Resources Archaeology: An Introduction\'\', [http://www.rowmanlittlefield.com/ Rowman and Littlefield Pub Inc], December, 2001, trade paperback, 256 pages, ISBN 0759100950\n* Trigger, Bruce. 1990. \"A History of Archaeological Thought\". Cambridge: Cambridge University Press. ISBN 0521338182\n\n[[Category:Antropologi]]\n[[Category:Arkéologi]]\n\n[[bg:Археология]] [[bs:Arheologija]] [[da:Arkæologi]] [[de:Archäologie]] [[en:Archaeology]] [[es:Arqueología]] [[eo:Arkeologio]] [[fr:Archéologie]] [[gl:Arqueoloxía]] [[ko:고고학]] [[hr:Arheologija]] [[ia:Archeologia]] [[it:Archeologia]] [[he:ארכיאולוגיה]] [[la:Archaeologia]] [[lv:Arheologija]] [[lt:Archeologija]] [[nl:Archeologie]] [[ja:考古学]] [[no:Arkeologi]] [[pl:Archeologia]] [[pt:Arqueologia]] [[ro:Arheologie]] [[simple:Archaeology]] [[sl:Arheologija]] [[sr:Археологија]] [[sv:Arkeologi]] [[ta:தொல்பொருளியல்]] [[th:โบราณคดี]] [[tr:Arkeoloji]] [[uk:Археологія]]\n[[vo:Vönotav]] [[zh:考古学]]','/* Field methods */',3,'Kandar','20040818051907','',0,0,0,0,0.851240200387,'20050316081936','79959181948092'); INSERT INTO cur VALUES (1041,0,'Marcapada','\n{| border=\"1\" cellspacing=\"0\" cellpadding=\"2\"align=\"right\" style=\"margin: 0 0 0.5em 1em\" width=\"300px\"\n|+\'\'\'Marcapada\'\'\'\n|-\n! align=\"center\" bgcolor=\"#000000\" colspan=\"2\" | [[Image:earth-apollo17.jpg|250px|Gambar warna Marcapada sakumaha nu katempo ti Apollo 17]]
\nKlik gambar pikeun dadaranana\n|-\n! bgcolor=\"#ffc0c0\" colspan=\"2\" | Ciri fisik\n|-\n! align=\"left\" | [[Equator]]ial [[radius]]\n| 6,378.14 [[Kilometre|km]]\n|-\n!align=\"left\" | [[Polar]] radius\n| 6,356.78 km\n|-\n!align=\"left\" | Mean [[Earth radius|radius]]\n| 6,371.3 km\n|-\n! align=\"left\" | Equatorial [[circumference]]\n| 40,075 km\n|-\n! align=\"left\" | [[Volume]]\n| 1.0832×1012 km³\n|-\n! align=\"left\" | [[Mass]]\n| 5.9737×1024 kg\n|-\n! align=\"left\" | [[Density]]\n| 5.515 [[Gram (unit)|g]]/[[cubic centimetre|cm³]]\n|-\n! align=\"left\" | Surface [[area]]\n| 510,065,700 km²\n|-\n! align=\"left\" | Equatorial surface [[gravity]]\n| 9.766 [[Metre per second squared|m/s²]], or 1 [[gee]]\n|-\n! align=\"left\" | [[Escape velocity]]\n| 11,180 [[Metre per second|m/s]]\n|-\n! align=\"left\" | [[Sidereal day|Sidereal rotation period]]\n| 23.934 hours\n|-\n! align=\"left\" | [[Axial tilt|Equatorial inclination to orbit]]\n| [[degree|23.45°]]\n|-\n! align=\"left\" | Surface [[Kelvin|temperature]]\n|\n{| cellspacing=\"0\" cellpadding=\"2\" align =\"center\" border=\"0\" width=\"100%\"\n|-\n! min\n! mean\n! max\n|- align =\"center\"\n| 185 K\n| [[1 E2 K|287 K]]\n| 331 K\n|}\n|-\n! align=\"left\" | Surface [[Atmospheric pressure|Pressure]]\n| 1 [[Bar (unit)|bar]]\n|-\n! bgcolor=\"#ffc0c0\" colspan=\"2\" | [[Orbit]]al characteristics\n|-\n! align=\"left\" | Average distance from the [[Sun]]\n| 149,597,890 km (1.000 [[astronomical unit|A.U.]])\n|-\n! align=\"left\" | [[Perihelion]] (closest)\n| 147,100,000 km\n|-\n! align=\"left\" | [[Aphelion]] (farthest)\n| 152,100,000 km\n|-\n! align=\"left\" | [[Sidereal year|Sidereal orbit period]]\n| 365.25636 days (1.0000174 [[Julian year]]s)\n|-\n! align=\"left\" | [[Avg. Orbital Speed|Mean Orbit Velocity]]\n| 29,785.9 m/s\n|-\n! align=\"left\" | [[Eccentricity|Orbital eccentricity]]\n| 0.01671022\n|-\n! align=\"left\" | [[Inclination|Orbital inclination to Ecliptic]]\n| 0.00005°\n|-\n! align=\"left\" | Orbital [[circumference]]\n| 924,375,700 km\n|-\n! align=\"left\" | [[natural satellite|Satellite]]s\n| 1 (the [[Moon]]), but see also [[3753 Cruithne]]\n|-\n! align=\"left\" | [[natural satellite|Satellite]] of\n| [[Sun]]\n|-\n! bgcolor=\"#ffc0c0\" colspan=\"2\" | Atmospheric constituents\n|-\n| [[nitrogen]] || 77%\n|-\n| [[oxygen]] || 21%\n|-\n| [[argon]] || 1%\n|-\n| [[carbon dioxide]]
\nuap [[cai]]\n| trace\n|}\n\n\'\'\'Marcapada\'\'\', ogé disebut \'\'\'Bumi\'\'\', (Ing. \'\'earth\'\', atawa \'\'Terra\'\'), ngarupakeun [[planét]] tempat manusa hirup, planét katilu luareun [[Panonpoé]]. Marcapada ngarupakeun hiji-hijina [[planét terestrial]] di [[Tatasurya]], sarta hiji-hijina planét nu mibanda [[hirup|kahirupan]], sahanteuna kitu nu dipikanyaho [[élmu modérn]]. Planét ieu mibanda hiji [[satelit alam]], [[bulan]], nu kabentuk kira 4,5 milyar [[taun]] ka tukang.\n\n== Ciri fisik ==\n\'\'Artikel utama\'\': [[Géofisik]]\n\n=== Struktur ===\n\nThe interior of Earth, like that of the other [[terrestrial planets]], is chemically divided into an outer [[silicon|siliceous]] solid crust, a highly viscous [[earth\'s mantle|mantle]], a liquid outer core that is much less viscous than the mantle, and a solid inner core. The liquid outer core gives rise to a weak [[magnetosphere|magnetic field]] due to the convection of its electrically conductive material. \n\nNew material constantly finds its way to the surface through volcanoes and cracks in the ocean floors (see [[seafloor spreading]]). Much of Earth\'s surface is less than 100 million years old; the very oldest parts of the crust are as much as 4.4 billion years old [http://spaceflightnow.com/news/n0101/14earthwater/].\n\nTaken as a whole, Earth\'s composition by mass is:\n\n*34.6% Iron\n*29.5% Oxygen\n*15.2% Silicon\n*12.7% Magnesium\n*2.4% Nickel\n*1.9% Sulfur\n*0.05% Titanium\n\n===Interior ===\n\nThe interior of Earth reaches temperatures of 5270 [[Kelvin|K]]. The planet\'s internal heat was originally released during its accretion (see [[gravitational binding energy]]), and since then additional heat has continued to be generated by the decay of [[radioactive]] elements such as [[uranium]], [[thorium]], and [[potassium]]. The heat flow from the interior to the surface is only 1/20,000 as great as the energy received from the Sun. \n\n*0-60 km - [[Lithosphere]]\n**0-30/35 km - [[Crust]]\n*30/35-2900 km - [[earth\'s mantle|Mantle]]\n**100-700 km - [[Asthenosphere]]\n*2900-5100 km - Outer Core\n*5100-~6375 km - Inner Core\n\n===The core===\n\nThe average density of Earth is 5,515 [[kilogram|kg]]/[[metre|m3]], making it the densest planet in the Solar system. Since the average density of surface material is only around 3000 kg/m3, we must conclude that denser materials exist within the core of the Earth. In its earliest stages, about 4.5 billion years ago, the Earth was mostly molten, and as a result gravity would have caused denser substances to sink towards the center in a process called [[planetary differentiation]], while less dense materials would have migrated to the crust. As a result, the core is largely composed of iron (80%), along with [[nickel]] and [[silicon]]; while other dense elements, such as lead and uranium, are either too rare to be significant or tend to bind to lighter elements and thus remain in the crust (see: [[felsic|felsic materials]]). \n\nThe core is divided into two parts, a solid inner core with a [[radius]] of ~1250 km and a liquid outer core extending beyond it to a radius of ~3500 km. The inner core is generally believed to be solid and composed primarily of iron and some nickel. Some have argued that the inner core may be in the form of a single iron [[crystal]]. The outer core surrounds the inner core and is believed to be composed of liquid iron mixed with liquid nickel and trace amounts of lighter elements. It is generally believed that convection in the outer core, combined with stirring caused by the Earth\'s rotation (see: [[Coriolis force]]s), gives rise to the [[Earth\'s magnetic field]] through a process known as the [[dynamo theory]]. The solid inner core is too hot to hold a permanent magnetic field (see: [[Curie temperature]]) but probably acts to stabilise the magnetic field generated by the liquid outer core.\n\nRecent evidence has suggested that the inner core of Earth may rotate slightly faster than the rest of the planet, by ~2° per [[year]] (\'\'[[Neil F. Comins|Comins]] DEU-p.82\'\').\n\n===Mantle===\n\nEarth\'s [[earth\'s mantle|mantle]] extends to a depth of 2,900 km. The [[pressure]], at the bottom of the mantle, is ~1.4 M[[atmospheric pressure|atm]] (140 [[pascal|GPa]]). It is largely composed of substances rich in [[iron]] and [[magnesium]]. The melting point of a substance depends on the pressure it is under. As there is intense and increasing pressure as one travels deeper into the mantle, the lower part of this region is thought solid while the upper mantle is [[Thermoplasticity|plastic]] (semi-molten). The viscosity of the upper mantle ranges between 1021 and 1024 Pa·s, depending on depth [http://www2.uni-jena.de/chemie/geowiss/geodyn/poster2.html]. Thus, the upper mantle can only flow very slowly.\n\nWhy is the inner core thought solid, the outer core thought liquid, and the mantle solid/plastic? The melting point of iron rich substances are higher than pure iron. The core is composed almost entirely of pure iron, while iron rich substances are more common outside the core. So, surface iron-substances are solid, upper mantle iron-substances are semi-molten (as it is hot and they are under relatively little pressure), lower mantle iron-substances are solid (as they are under tremendous pressure), outer core pure iron is liquid as it has a very low melting point (despite enormous pressure), and the inner core is solid due to the overwhelming pressure found at the center of the planet.\n\n===Crust===\n\nThe crust ranges from 5 to 35 km in depth. It is composed of silicon-based [[Rock (geology)|rock]]s. The crust-mantle boundary occurs as two physically different events. Firstly, there is a discontinuity in the [[seismic wave|seismic]] velocity which is known as the [[Mohorovicic discontinuity]] or Moho. The cause of the Moho is thought to be a change in rock composition from rocks containing [[feldspar|plagioclase feldspar]] (above) to rocks that contain none (below). The second event is a [[chemistry|chemical]] discontinuity between ultramafic cumulates and tectonized hartzburgites which has been observed from parts of the oceanic crust that have been [[obduction|obducted]].\n\n=== Biosfir ===\n\'\'Main Article:\'\' [[Life]]\n\nEarth is the only place where [[life]] is known to exist. The planet\'s lifeforms are sometimes said to form a \"[[biosphere]]\". This biosphere is generally believed to have begun [[evolution|evolving]] about 3.5 billion years ago. The biosphere is divided into a number of [[biome]]s, inhabited by broadly similar [[flora (plants)|flora]] and [[fauna (animals)|fauna]]. On land, biomes are separated primarily by [[latitude]]. Terrestrial biomes lying within the [[Arctic Circle|Arctic]] and [[Antarctic Circle]]s are relatively barren of [[plant]] and [[animal]] life, while most of the more populous biomes lie near the [[Equator]].\n\n=== Atmosfir ===\n\'\'Artikel utama\'\': [[Atmosfir Marcapada]]\n\nEarth has a relatively thick [[Earth atmosphere|atmosphere]] composed of 78% [[nitrogen]], 21% [[oxygen]], and 1% [[argon]], plus traces of other gases including [[carbon dioxide]] and [[cai]]. The atmosphere acts as a buffer between Earth and the Sun. The layers, [[troposphere]], [[stratosphere]], [[mesosphere]], [[thermosphere]], and the [[exosphere]], vary around the globe and in response to seasonal changes. This is sometimes described as the \"third atmosphere\" to distinguish it from earlier atmospheric compositions.\n\n===Hidrosfir===\n\'\'Artikel utama:\'\' [[Sagara]]\n\n[[Image:Full earth.jpg|thumb|right|197px|\"Marcapada\" hasil [[Clementine mission|Clementine]]. Langit teu biasana béngras luhureun [[Afrika]] jeung sagara sabudeureunana]]\n\nEarth is the only planet in our [[solar system]] whose surface has liquid [[cai|water]]. Water covers 71% of Earth\'s surface (97% of it being sea water and 3% fresh water [http://earthobservatory.nasa.gov/Library/Water/]) and divides it into five [[ocean]]s and seven [[continent]]s. Earth\'s [[orbit|solar orbit]], [[vulcanism]], [[gravity]], [[greenhouse effect]], [[magnetic field]] and oxygen-rich atmosphere seem to combine to make Earth a water planet. \n\nEarth is actually beyond the outer edge of the orbits which would be warm enough to form liquid water. Without some form of a [[greenhouse effect]], Earth\'s water would freeze. Paleontological evidence indicates that at one point after blue-green bacteria (Archaea) had colonized the oceans, the greenhouse effect failed, and Earth froze solid for 10 to 100 million years in what is called a [[snowball Earth]] event.\n\nOn other planets, such as [[Venus (planet)|Venus]], gaseous water is cracked by solar [[ultraviolet]], and the [[hydrogen]] is [[ion]]ized and blown away by the [[solar wind]]. This effect is slow, but inexorable. It is believed that this is the reason why Venus has no water. Without hydrogen, the oxygen interacts with the surface and is bound up in solid [[mineral]]s.\n\nOn Earth, a shield of [[ozone]] absorbs most of this energetic ultraviolet high in the atmosphere, reducing the [[cracking effect]]. The [[magnetosphere]] also shields the [[ionosphere]] from direct scouring by the solar wind. \n\nFinally, [[volcano|vulcanism]], aided by the Moon\'s tidal effects, continuously emits water [[vapor]] from the interior. Earth\'s [[plate tectonics]] recycle [[carbon]] and water as limestone fields are subducted into [[magma]] and volcanically emitted as gaseous carbon dioxide and steam. It is estimated that the minerals in the mantle may contain as much as 10 times the water as in all of the current oceans, though most of this trapped water will never be released.\n\nEarth also suffers from the [[Chandler wobble]].\n\n== Marcapada dina sistim Tatasurya ==\n\nIt takes Earth 23 hours, 56 minutes and 4.09 seconds ([[sidereal day|1 sidereal day]]) to rotate around the axis connecting the [[North Pole]] and the [[South Pole]]. It orbits the [[Sun]] every 365.2564 mean solar days ([[sidereal year|1 sidereal year]]). Earth has one [[natural satellite]], \"the [[Moon]]\", which orbits around Earth every [[month|27 1/3 days]]. Viewed from Earth\'s North Pole, the motion of Earth, its moon and their axial rotations are all [[counterclockwise]].\n\nThe orbital and axial planes are not precisely aligned: Earth\'s [[axial tilt|axis is tilted]] some 23.5 degrees against the Earth-Sun plane (which causes the [[season]]s), and the Earth-Moon plane is tilted about 5 degrees against the Earth-Sun plane (otherwise there would be an eclipse every month).\n\nThe [[Hill sphere]] (sphere of influence) of the earth is about 1.5 Gm (930 thousand miles) in radius, within which one natural satellite (the Moon) comfortably orbits.\n\n=== Bulan ===\n\'\'Artikel utama\'\': [[Bulan]]\n\n{| border=\"1\" cellspacing=\"0\" cellpadding=\"2\"\n!style=\"background:#efefef;\"|Ngaran\n!style=\"background:#efefef;\"|Diaméter (km)\n!style=\"background:#efefef;\"|Beurat (kg)\n!style=\"background:#efefef;\"|Radius orbital rata-rata (km)\n!style=\"background:#efefef;\"|Periode Orbital\n|-\n|[[Bulan]]\n|3,474.8\n|7.349 × 1022\n|384,400\n|27 Poé, 7 jam, 43.7 menit\n|}\n\nThe [[Moon]] is a relatively large terrestrial planet-like satellite, about one quarter of Earth\'s diameter. The [[natural satellite]]s orbiting other planets are called \"moons\", after Earth\'s Moon.\n\nThe Moon\'s gravity causes the [[tides]] on Earth. The same effect has led to its [[tidal locking]]: its rotation period is the same as the time it takes to orbit the Earth. As a result it always presents the same face to the planet.\n\nAs the Moon orbits Earth, different parts of its face are illuminated by the Sun, leading to the [[lunar phase|lunar phases]]: the dark part of the face is separated from the light part by the [[solar terminator line]]. \n\nThe Moon may enable life by moderating the weather. [[Paleontology|Paleontological]] evidence and computer simulations show that Earth\'s [[axial tilt]] is stabilised by tidal interactions with the Moon. Without this stabilization, the rotational axis might be chaotically unstable, as it is with a sphere, and appears to be with Mars. If Earth\'s axis of rotation were to approach the [[ecliptic|plane of the ecliptic]], extremely severe [[weather]] could result as one pole was continually heated and the other cooled. [[Planetology|Planetologists]] who have studied the effect claim that this might kill all large animal and higher plant life. This remains a controversial subject, however, and further studies of Mars - which shares Earth\'s [[sidereal day|rotation period]] and [[axial tilt]], but not its large moon or liquid core - may provide additional information.\n\nThe Moon is just far enough away to have, when seen from Earth, the same apparent angular size as the Sun. This allows a total [[eclipse]] to occur on Earth. (The Sun is 400 times larger, but the Moon is 400 times closer.)\n\nThe Moon\'s origin is unknown, but one popular theory is that it was formed from the collision of a [[Mars (planet)|Mars]]-sized [[protoplanet]] with the early Earth. This theory explains (among other things) the Moon\'s relative lack of [[iron]] and [[volatile element]]s. See [[Giant impact theory]].\n\nEarth also has at least one known co-orbital [[asteroid]], [[3753 Cruithne]].\n\n== Géografi ==\n\'\'Artikel utama\'\': [[Géografi]]\n\n[[Image:Physical_world.jpg|thumb|333px|right|Atlas fisik Marcapada ([[:Image:Physical_world.jpg|Medium]]) ([[:Image:World-map-2004-cia-factbook-large-2m.jpg|Large 2 MB)]]]]\n\n\'\'\'Map references:\'\'\'\n\n[[Time Zone]]s, [[Coordinate]]s.\n\n\'\'\'Biggest geographic subdivision\'\'\'\n\n[[Buana]], [[Sagara]]\n\n\'\'\'Area:\'\'\'\n*\'\'total:\'\' [[1 E14 m2|510.072 million]] [[square kilometre|km2]]\n*\'\'land:\'\' 148.94 million km2\n*\'\'water:\'\' 361.132 million km2\n*\'\'note:\'\' 70.8% of the world\'s surface is covered by water, 29.2% is exposed land\n\n\'\'\'Land boundaries:\'\'\'\nthe land boundaries in the world total 251,480.24 km (not counting shared boundaries twice)\n\n\'\'\'Coastline:\'\'\'\n356,000 km\n\n\'\'\'Maritime claims:\'\'\' see [[United Nations Convention on the Law of the Sea]]\n*\'\'contiguous zone:\'\' 24 [[nautical mile|nautical miles (NM)]] claimed by most, but can vary\n*\'\'continental shelf:\'\' 200 m depth claimed by most or to depth of exploitation; others claim 200 NM or to the edge of the continental margin\n*\'\'exclusive fishing zone:\'\' 200 NM claimed by most, but can vary\n*\'\'exclusive economic zone:\'\' 200 NM claimed by most, but can vary\n*\'\'territorial sea:\'\' 12 NM claimed by most, but can vary\n*\'\'Note:\'\' boundary situations with neighboring states prevent many countries from extending their fishing or economic zones to a full 200 NM; 43 nations and other areas that are landlocked include [[Afghanistan]], [[Andorra]], [[Armenia]], [[Austria]], [[Azerbaijan]], [[Belarus]], [[Bhutan]], [[Bolivia]], [[Botswana]], [[Burkina Faso]], [[Burundi]], [[Central African Republic]], [[Chad]], [[Czech Republic]], [[Ethiopia]], [[Holy See]] (Vatican City), [[Hungary]], [[Kazakhstan]], [[Kyrgyzstan]], [[Laos]], [[Lesotho]], [[Liechtenstein]], [[Luxembourg]], [[Malawi]], [[Mali]], [[Moldova]], [[Mongolia (country)|Mongolia]], [[Nepal]], [[Niger]], [[Paraguay]], [[Rwanda]], [[San Marino]], [[Slovakia]], [[Swaziland]], [[Switzerland]], [[Tajikistan]], [[Republic of Macedonia|The Republic of Macedonia]], [[Turkmenistan]], [[Uganda]], [[Uzbekistan]], [[West Bank]], [[Zambia]], [[Zimbabwe]]\n\n== Iklim ==\n\'\'Artikel utama\'\': [[Modél iklim]]\n\nTwo large areas of polar [[climate]]s separated by two rather narrow [[temperate]] zones from a wide [[equator]]ial band of [[tropical]] to [[subtropical]] [[climate]]s. [[precipitation (meteorology)|Precipitation]] patterns vary widely, ranging from several metres of water per year to less than a millimetre.\n\n== Terrain ==\n\n\'\'\'Elevation extremes:\'\'\' (measured relative to [[sea level]])\n*Lowest point on land: [[Dead Sea]] [[1 E2 m| −408]] m\n*Lowest point overall: [[Mariana Trench]] in the [[Pacific Ocean]] [[1 E4 m| −10,924]] m\n*Highest point: [[Mount Everest]] [[1 E3 m|8,850]] m ([[1999]] est.)\n\n== Natural resources ==\n\'\'Main article\'\': [[Natural resource]]s\n\n*Earth\'s crust contains large deposits of [[fossil fuel]]s: ([[coal]], [[oil]], [[natural gas]], [[methane clathrate]]). These deposits are used by humans both for energy production and as feedstock for chemical production.\n*[[Mineral]] [[ore]] bodies have been formed in Earth\'s crust by the action of [[erosion]] and [[plate tectonics]]. These [[ore]] bodies form concentrated sources for many [[metal]]s and other useful [[chemical element|element]]s.\n*Earth\'s [[biosphere]] produces many useful biological products, including (but far from limited to) [[food]], [[wood]], [[pharmaceutical]]s, [[oxygen]], and the recycling of many organic wastes. The land-based [[ecosystem]] depends upon [[topsoil]] and fresh [[cai|water]], and the [[ocean]]ic [[ecosystem]] depends upon dissolved nutrients washed down from the land.\n\nSome of these resources, such as [[fossil fuel]]s, are difficult to replenish on a short time scale, called [[non-renewable resources]]. The exploitation of non-renewable resources by human [[civilization]] has become a subject of significant controversy in modern [[environmentalism]] movements.\n\n== Land use ==\n\n*\'\'arable land:\'\' 10%\n*\'\'permanent crops:\'\' 1%\n*\'\'permanent pastures:\'\' 26%\n*\'\'forests and woodland:\'\' 32%\n*\'\'urban areas:\'\' 1.5%\n*\'\'other:\'\' 30% (1993 est.)\n\n\'\'\'Irrigated land:\'\'\'\n2,481,250 km2 ([[1993]] est.)\n\n\n== Natural hazards ==\n\nLarge areas are subject to extreme [[weather]] such as (tropical [[cyclone]]s), [[hurricane]]s,or [[typhoon]]s that dominate life in those areas. Many places are subject to [[earthquake]]s, [[landslide]]s, [[tsunami]]s, [[volcano|volcanic eruptions]], [[tornado]]es, [[sinkhole]]s, [[flood]]s, [[drought]]s, and other calamities and [[disaster]]s.\n\n== [[Lingkungan]] - isu kiwari ==\n\'\'Artikel utama\'\': [[Énvironmentalisme]]\n\nLarge areas are subject to [[overpopulation]], industrial disasters such as [[pollution]] of the air and water, [[acid rain]] and toxic substances, loss of vegetation ([[overgrazing]], [[deforestation]], [[desertification]]), loss of [[wildlife]], [[soils retrogression and degradation|soil degradation]], soil depletion, [[erosion]], and \nintroduction of [[invasive species]].\n\n== Populasi manusa ==\n\n[[Image:Earthlights_dmsp.jpg|333px|thumb|right|Earth at night, composite of pictures taken between October 1994 and March 1995.]]\n\nNearly all [[human]]s currently reside on Earth: 6,327,152,352 [[inhabitant]]s ([[November 1]] [[2003]] est.)\n\nA few humans are in orbit around Earth on board the [[International Space Station]], with others traveling briefly above the [[atmosphere]]. In total, about 400 people ([[astronaut]]s, [[cosmonaut]]s and [[taikonaut]]s) have been outside Earth (in space) as of [[2004]]. Most of them have reported a heightened understanding of its value and importance, reverence for human life and amazement at its beauty, not usually achieved by those living on the surface.\n\nSee also [[space colonization]].\n\nThe northernmost settlement in the world is [[Alert, Nunavut|Alert]], [[Ellesmere Island]], [[Canada]]. The southernmost is the [[Amundsen-Scott South Pole Station]], in [[Antarctica]], almost exactly at the [[South Pole]].\n\n\'\'\'Age structure:\'\'\'\n*\'\'0-14 years:\'\' 1,818,803,078 (29.92%)\n**\'\'male:\'\' 932,832,913 (15.35%)\n**\'\'female:\'\' 885,970,165 (14.57%)\n*\'\'15-64 years:\'\' 3,840,881,326 (63.19%)\n**\'\'male:\'\' 1,942,402,264 (31.95%)\n**\'\'female:\'\' 1,898,479,062 (31.23%)\n*\'\'65 years and over:\'\' 419,090,130 (6.89%)\n**\'\'male:\'\' 184,072,470 (3.03%)\n**\'\'female:\'\' 235,017,660 (3.87%) ([[2000]] est.)\n\n\'\'\' [[Population growth rate]]:\'\'\'\n1.3% ([[2000]] est.)\n\n\'\'\'[[Birth rate]]:\'\'\'\n22 births/1,000 population ([[2000]] est.)\n\n\'\'\'[[Death rate]]:\'\'\'\n9 deaths/1,000 population ([[2000]] est.)\n\n\'\'\'[[Sex ratio]]:\'\'\'\n*\'\'at birth:\'\' 1.05 male(s)/female\n*\'\'under 15 years:\'\' 1.05 male(s)/female\n*\'\'15-64 years:\'\' 1.02 male(s)/female\n*\'\'65 years and over:\'\' 0.78 male(s)/female\n*\'\'total population:\'\' 1.01 male(s)/female ([[2000]] est.)\n\n\'\'\'[[Infant mortality rate]]:\'\'\'\n54 deaths/1,000 live births ([[2000]] est.)\n\n\'\'\'[[Life expectancy]] at birth:\'\'\'\n*\'\'total population:\'\' 64 years\n\n*\'\'male:\'\' 62 years\n*\'\'female:\'\' 65 years ([[2000]] est.)\n\n\'\'\'Total [[fertility rate]]:\'\'\'\n2.8 children born/woman ([[2000]] est.)\n\n== [[Government]] ==\n\nThe worldwide general [[international organization]] is the [[United Nations]]. The United Nations is primarily an international discussion forum with only limited ability to pass and enforce [[law]]s.\n\n\'\'\'Administrative divisions:\'\'\'\n267 nations, dependent areas, other, and miscellaneous entries\n\n== Descriptions of Earth ==\n\nEarth has often been personified as a [[deity]], in particular a [[goddess]]. See [[Gaea]] and [[Mother Earth]]. In [[Norse mythology]], \'\'\'Earth\'\'\' was the son of [[Nott]] and [[Annar]].\n\nEarth has also been described as a massive [[spaceship]], with a [[life support (environment)|life support system]] that requires maintenance. See [[Spaceship Earth]].\n\nSince Earth is rather large, it is not immediately obvious to the naked eye that it is spherical. Because of this, in the past it was sometimes thought that Earth was in fact flat. See [[flat Earth]].\n\nIn [[science fiction]] the Earth is frequently the [[capital]] or a major administrative center of a hypothetical [[galactic]] [[government]] (especially when that galactic government is postulated to be [[human]]-dominated), often a representative [[federal republic]], though [[empire]]s and [[dictatorship]]s are definitely not unseen. Notable are [[Star Trek]] and [[Babylon 5]].\n\n== Tempo ogé ==\n\n* \'\'\'Sistim hukum:\'\'\' [[Hukum internasional]]\n* \'\'\'Ékonomi:\'\'\' [[ékonomi dunya]]\n* \'\'\'Sajarah:\'\'\' [[Sajarah dunya]]\n*[[Lini]]\n*[[Earth\'s magnetic field]]\n*[[Equatorial bulge]]\n*[[Earth in fiction]]\n*[[Daftar nagara]]\n*[[Géologi]]\n*[[Geologic timescale]]\n\n==Rujukan==\n* \'\'[[Discovering the Essential Universe]]\'\' (Second Edition) by [[Neil F. Comins|Comins]] ([[2001]])\n\n{{Footer_SolarSystem}}\n\n[[Category:Tatasurya]][[Category:Planét]] [[Category:Marcapada]]\n\n[[af:Aarde]]\n[[ar:ارض]]\n[[ast:Tierra]]\n[[bg:Земя]]\n[[ca:Terra]]\n[[cs:Země]]\n[[cy:Daear]]\n[[da:Jorden]]\n[[de:Erde]]\n[[el:Γη]]\n[[en:Earth]]\n[[eo:Tero]]\n[[es:Tierra]]\n[[et:Maa (planeet)]]\n[[eu:Lurra]]\n[[fi:Maa]]\n[[fr:Terre]]\n[[fy:Ierde]]\n[[he:כדור הארץ]]\n[[hi:पृथ्वी]]\n[[hr:Zemlja]]\n[[hu:Föld]]\n[[ia:Terra]]\n[[id:Bumi]]\n[[is:Jörðin]]\n[[it:Terra]]\n[[ja:地球]]\n[[jbo:Terdi]]\n[[ko:지구]]\n[[la:Terra]]\n[[lv:Zeme]]\n[[minnan:Tē-kiû]]\n[[ms:Bumi]]\n[[nds:Eer]]\n[[nl:Aarde]]\n[[no:Jorden]]\n[[pl:Ziemia]]\n[[pt:Terra]]\n[[ro:Pământ]]\n[[ru:Земля (планета)]]\n[[simple:Earth]]\n[[sl:Zemlja]]\n[[sr:Земља]]\n[[sv:Jorden]]\n[[uk:Земля (планета)]]\n[[zh:地球]]','',3,'Kandar','20041210102028','',0,0,0,0,0.040213285033,'20050208111611','79958789897971'); INSERT INTO cur VALUES (1043,6,'Earth-apollo17.jpg','bumi ti wikipedia english','bumi ti wikipedia english',13,'Budhi','20040724134542','',0,0,0,1,0.638708083553899,'20041210102040','79959275865457'); INSERT INTO cur VALUES (1044,6,'Full_earth.jpg','','',13,'Budhi','20040724135138','',0,0,0,1,0.373194408950577,'20041210102040','79959275864861'); INSERT INTO cur VALUES (1045,0,'Optimisasi_(matematik)','Dina [[matematik]], watesan \'\'\'optimisasi\'\'\' nujul kana pangajaran ngeunaan masalah nu ngabogaan bentuk \n:\'\'\'Given:\'\'\' a [[fungsi (matematik)|fungsi]] \'\'f\'\' : \'\'A\'\' -> \'\'\'R\'\'\' from some [[set]] \'\'A\'\' to the [[real number]]s\n:\'\'\'Sought:\'\'\' an element \'\'x\'\'0 in \'\'A\'\' such that \'\'f\'\'(\'\'x\'\'0) ≥ \'\'f\'\'(\'\'x\'\') for all \'\'x\'\' in \'\'A\'\' (\"maximization\") or such that \'\'f\'\'(\'\'x\'\'0) ≤ \'\'f\'\'(\'\'x\'\') for all \'\'x\'\' in \'\'A\'\' (\"minimization\").\n\nSuch a formulation is sometimes called a \'\'mathematical program\'\' (a term not directly related to [[computer programming]], but still in use for example for [[linear programming]] - see history below). Many real-world and theoretical problems may be modeled in this general framework.\n\nTypically, \'\'A\'\' is some [[subset]] of [[Euclidean space]] \'\'\'R\'\'\'\'\'n\'\', often specified by a set of \'\'[[constraint]]s\'\', equalities or inequalities that the members of \'\'A\'\' have to satisfy.\nThe elements of \'\'A\'\' are called the \'\'feasible solutions\'\' and the function \'\'f\'\' is called the objective function. A feasible solution that maximizes (or minimizes, if that is the goal) the objective function is called an optimal solution.\n\nIn general there will be several local maxima and minima, where a local minimum x* is defined as a point such that for some δ > 0 and all x such that ||x - x* || ≤ δ the formula f(x) ≥ f(x*) holds; that is to say on some ball around x* all of the function values are greater than the value at that point. Local maxima are defined similarly. In general, it is easy to find local minima, however additional facts about the problem (e.g. the function being convex) are required to ensure that the solution found is a global minimum.\n\n== Notasi ==\n\nMasalah optimization biasa dilambangkeun ku notasi husus. Here are some examples:\n\n:min\'\'x\'\' in \'\'\'R\'\'\' \'\'x\'\'2+1 \n\nKeur nyebutkeun nilai minimum dina rumus \'\'x2\'\'+1, numana \'\'x\'\' aya dina \"rentang\" [[real number]]s \'\'\'R\'\'\'. Nilai minimum dina kasus ieu nyaeta 1, dina waktu x=0.\n\n:max\'\'x\'\' in \'\'\'R\'\'\' 2x\n\nThis asks for the maximum value for the expression 2\'\'x\'\', where \'\'x\'\' ranges over the reals. In this case, there is no such maximum as the expression is unbounded, so the answer is \"[[infinity]]\" or \"undefined\".\n\n:arg min\'\'x\'\' in [-∞,-1]   \'\'x\'\'2+1\n\nThis asks for the value(s) of \'\'x\'\' in the [[interval (mathematics)|interval]] [-∞,-1] which minimizes the expression \'\'x\'\'2+1. (The actual minimum value of that expression does not matter.) In this case, the answer is \'\'x\'\' = -1.\n\n:arg max\'\'x\'\' in [-∞,5], \'\'y\'\' in \'\'\'R\'\'\'   \'\'x\'\' · cos(\'\'y\'\')\n\nThis asks for the (\'\'x\'\',\'\'y\'\') pair(s) that maximize the value of the expression \'\'x\'\'·cos(\'\'y\'\'), with the added constraint that \'\'x\'\' cannot exceed 5. (Again, the actual maximum value of the expression does not matter.) In this case, the solutions are the pairs of the form (5,2[[pi|π]]\'\'k\'\') and (-5,(2\'\'k\'\'+1)π), where \'\'k\'\' ranges over all [[integer]]s.\n\n== Teknik ==\n\nTeknik keur ngarengsekeun program matematik gumantung kana kondisi alami fungsi obyektif fungsi jeung constraint set. The following major subfields exist:\n\n* [[linear programming]] studies the case in which the objective function f is linear and the set A is specified using only linear equalities and inequalities\n* [[integer programming]] studies linear programs in which some or all variables are constrained to take on [[integer]] values\n* [[quadratic programming]] allows the objective function to have quadratic terms, while the set A must be specified with linear equalities and inequalities\n* [[nonlinear programming]] studies the general case in which the objective or constraints or both contain nonlinear parts\n* [[stochastic programming|program stokastik]] nalungtik kasus nu gumantung kana [[variabel acak]]\n* [[dynamic programming]] studies the case which has optimal substructure and overlapping subproblems.\n\nFor twice-differentiable functions, unconstrained problems can be solved by finding the places where the [[gradient]] of the function is 0 (i.e. the stationary points) and using the [[Hessian matrix]] to classify the type of point. If the hessian is positive definite, the point is a local minimum, if negative definite, a local maximum, and if indefinite it is some kind of saddle point.\n\nShould a function be convex over a region of interest (as defined by constraints) then any local minimum will also be a global minimum. Robust, fast numerical techniques exist for optimizing doubly differentiable convex functions. Outside of these functions, less ideal techniques must be used.\n\nConstrained problems can often be transformed into unconstrained problems with the help of the [[Lagrange multiplier]].\n\nSeveral techniques exist for find a good local minimum in nonlinear optimization problems with many poor local minima:\n* [[simulated annealing]]\n* [[particle swarm optimization]]\n* [[stochastic tunneling]]\n* [[random-restart hill climbing]]\n\n== Pamakean ==\n\nAdditionally, problems in [[rigid body]] [[dynamics (mechanics)|dynamics]] (in particular articulated rigid body dynamics) often require mathematical programming techniques, since you can view rigid body dynamics as attempting to solve an [[ordinary differential equation]] on a constraint manifold; the constraints are various nonlinear geometric constraints such as \"these two points must always coincide\", \"this surface must not penetrate any other\", or \"this point must always lie somewhere on this curve\". Also, the problem of computing contact forces can be done by solving a [[linear complementarity problem]], which can also be viewed as a QP (quadratic programming problem).\n\nMany design problems can also be expressed as optimization programs. This application is called design optimization. One recent and growing subset of this field is [[multidisciplinary design optimization]], which, while useful in many problems, has in particular been applied to [[aerospace engineering]] problems.\n\nAnother field that uses optimization techniques extensively is [[operations research]].\n\n== Sajarah ==\n\nHistorically, the first term to be introduced was [[linear programming]], which was invented by [[George Dantzig]] in the 1940s. The term programming in this context does not refer to [[computer programming]] (although computers are nowadays used extensively to solve mathematical programs). Instead, the term comes from the use of program by the United States military to refer to proposed training and [[logistics]] schedules, which were the problems that Dantzig was studying at the time. (Additionally, later on, the use of the term \"programming\" was apparently important for receiving government funding, as it was associated with high-technology research areas that were considered important.)\n\n\n\n==Tempo oge==\n*[[arg max]]\n*[[game theory]]\n*[[compiler]]s for [[programming language]]s\n*[[operations research]]\n*[[fuzzy logic]]\n*[[random optimization]]\n*[[genetic algorithm]]\n*[[variational inequality]]\n*[[mixed complementarity]]\n*[[simplex algorithm]]\n\n==Tumbu kaluar==\n\n*[http://www-fp.mcs.anl.gov/otc/Guide/index.html NEOS Guide]\n\n*[http://zunzun.com Online curve and surface fitting]\n\n[[en:Optimization (mathematics)]]\n[[ja:最適化問題]]\n[[fr:Optimisation (mathématiques)]]\n[[Category:Optimisasi]]','/* Tumbu kaluar */',3,'Kandar','20050203102229','',0,0,0,0,0.042805783936,'20050203102229','79949796897770'); INSERT INTO cur VALUES (1046,0,'Kulawarga',':\'\'This article is about the domestic group. For other uses, see [[Family (disambiguation)]].\'\'\n\nA \'\'\'family\'\'\' is a domestic [[group (sociology)|group]] of people, or a number of domestic groups linked through descent (demonstrated or stipulated) from a common ancestor, [[marriage]], or [[adoption]]. Families have some [[degree]] of [[kinship]]. \n\nIn Western culture, a family is defined specifically as a group of people affiliated by blood or by legal ties such as marriage or adoption. Many [[cultural anthropology|anthropologists]] argue that the notion of \"blood\" must be understood metaphorically; some argue that there are many non-Western societies where family is understood through other concepts rather than \"blood.\"\n\n== Family cross-culturally ==\n\nAccording to [[sociology]] and [[anthropology]], the primary function of the family is to reproduce society, either biologically, socially, or both. Thus, one\'s experience of one\'s family shifts over time. From the perspective of children, the family is a \'\'\'family of orientation\'\'\': the family serves to locate children socially, and plays a major role in their enculturation and socialization. From the point of view of the parent(s), the family is a \'\'\'family of procreation\'\'\' the goal of which is to produce and enculturate and socialize children. However, producing children is not the only function of the family. In societies with a sexual division of labor, [[marriage]], and the resulting relationship between a husband and wife, is necessary for the formation of an economically productive household. In modern societies marriage entails particular rights and privilege that encourage the formation of new families even when there is no intention of having children.\n\nThe structure of families traditionally hinges on relations between parents and children, between spouses, or both. Consequently, there are three major types of family: matrifocal, consanguineal, and conjugal. (Note: these are ideal families. In all societies there are acceptable deviations from the ideal or statistical norm, owing either to incidental circumstances, such as the death of a member of the family or infertility, or personal preferences).\n\nA \'\'\'matrifocal\'\'\' family consists of a mother and her children. Generally, these children are her biological offspring, although adoption of children is a practice in nearly every society. This kind of family is common where women have the resources to rear their children by themselves, or where men are more mobile than women.\n\nA \'\'\'consanguineal\'\'\' family consists of a mother and her children, and other people -- usually the family of the mother. This kind of family is common where mothers do not have the resources to rear their children on their own, and especially where property is inherited. When important property is owned by men, consanguineal families commonly consist of a husband and wife, their children, and other members of the husband\'s family.\n\nA \'\'\'conjugal\'\'\' family consists of one or more mothers and their children, and/or one or more spouses (usually husbands). This kind of family is common where men desire to assert control over children, or where there is a sexual division of labor requiring the participation of both men and women, and where families are relatively mobile.\n\n== Family in the West ==\nThe preceding types of families are found in a wide variety of settings, and their specific functions and meanings depend largely on their relationship to other social institutions. [[Sociology|Sociologists]] are especially interested in the function and status of these forms in stratified, especially capitalist, societies.\n\nNon-scholars, especially in the United States and Europe, use the term \"[[nuclear family]]\" to refer to conjugal families. Sociologists distinguish between conjugal families that are relatively independent of the kindreds of the parents, and of other families in general, and nuclear families which maintain relatively close ties with their kindreds.\n\nNon-scholars, especially in the United States and Europe, also use the term \'\'\'extended family\'\'\'. This term has two distinct meanings. First, it is used synonymously with consanguinal family. Second, in societies dominated by the conjugal family, it is used to refer to \'\'\'kindred\'\'\' (an egocentric network of relatives that extends beyond the domestic group) who do not belong to the conjugal family.\n\nThese types refer to ideal or normative structures found in particular societies. In any society there is some variation in the actual composition and conception of families. Much sociological, [[history|historical]], and [[cultural anthropology|anthropological]] research is dedicated to understanding this variation, and changes over time in the family form. Thus, some speak of the \'\'\'bourgeois family\'\'\', a family structure arising out of 16th and 17th century European households, in which the center of the family is a marriage between a man and woman, with strictly defined gender roles. The man typically is responsible for income and support, the woman for home and family matters. In contemporary Europe and the United States, people in both the academy, politics, and civil society have called attention to single-father-headed households, and families headed by [[gay|same-sex]] couples, although academics point out that these forms exist in other societies.\n\n==Economic Role of the Family==\nIn traditional society the family is an economic unit. This role has gradually diminished in modern times and in societies like the [[United States]] is much smaller except for certain sectors such as agriculture and a few [[upper class]] families. In [[Chinese culture]] the family as an economic unit still plays a strong if somewhat diminished role.\n\n==Kinship terminology==\nA \'\'\'kinship terminology\'\'\' is a specific system of familial relationships. The anthropologist [[Louis Henry Morgan]] argued that kinship terminologies reflect different sets of distinctions. For example, most kinship terminologies distinguish between \'\'\'genders\'\'\' (this is the difference between a brother and a sister) and between \'\'\'generation\'\'\' (this is the difference between a sister and a mother). Moreover, he argued, kinship terminologies distinguish between relatives by \'\'\'blood\'\'\' and \'\'\'marriage\'\'\' (although recently some anthropologists have argued that many societies define kinship in terms other than \"blood\").\n\nBut Morgan also observed that different languages (and thus, societies) organize these distinctions differently. He thus proposed to describe kin terms and terminologies as either \'\'\'descriptive\'\'\' or \'\'\'classificatory\'\'\'. \"Descriptive\" terms refer to only one type of relationship, while \"classificatory\" terms refer to many types of relationships. Most kinship terminologies include both descriptive and classificatory terms. For example, in Western societies there is only one way to be related to one\'s brother (brother = parents\' son); thus, in Western society, brother is a descriptive term. But there are many ways to be related to one\'s cousin (cousin = mother\'s brother\'s son, mother\'s sister\'s son, father\'s brother\'s son, father\'s sister\'s son, and so on); thus, in Western society, \"cousin\" is a classificatory term.\n\nMorgan discovered that what may be a descriptive term in one society can be a classificatory term in another society. For example, in some societies there are many different people that one would call \"mother\" (the woman of whom one was born, as well as her sister and husband\'s sister, and also one\'s father\'s sister). Moreover, some societies do not lump together relatives that the West classifies together (in other words, in some languages there is no word for cousin because mother\'s sister\'s children and father\'s sister\'s children are referred to in different terms).\n\nArmed with these different terms, Morgan identified six basic patterns of kinship terminologies:\n\n*\'\'\'[[Hawaiian kinship|Hawaiian]]\'\'\': the most classificatory; only distinguishes between gender and generation.\n*\'\'\'[[Sudanese kinship|Sudanese]]\'\'\': the most descriptive; no two relatives are referred to by the same term.\n*\'\'\'[[Eskimo kinship|Eskimo]]\'\'\': has both classificatory and descriptive terms; in addition to gender and generation, also distinguishes between lineal relatives (who are related directly by a line of decent) and collateral relatives (who are related by blood, but not directly in the line of descent). Lineal relatives have highly descriptive terms, collateral relatives have highly classificatory terms.\n*\'\'\'[[Iroquois kinship|Iroquois]]\'\'\': has both classificatory and descriptive terms; in addition to gender and generation, also distinguishes between siblings of opposite sexes in the parental generation. Siblings of the same sex are considered blood relatives, but siblings of the opposite sex are considered relatives by marriage. Thus, one\'s mother\'s sister is also called mother, and one\'s father\'s brother is also called father; however, one\'s mother\'s brother is called father-in-law, and one\'s father\'s sister is called mother-in-law.\n*\'\'\'[[Crow kinship|Crow]]\'\'\': like Iroquois, but further distinguishes between mother\'s side and father\'s side. Relatives on the mother\'s side of the family have more descriptive terms, and relatives on the father\'s side have more classificatory terms.\n*\'\'\'[[Omaha kinship|Omaha]]\'\'\': like Iroquois, but further distinguishes between mother\'s side and father\'s side. Relatives on the mother\'s side of the family have more classificatory terms, and relatives on the father\'s side have more descriptive terms.\n\nSocieties in different parts of the world and using different languages may share the same basic terminology; in such cases it is very easy to translate the kinship terms of one language into another. But it is usually impossible to translate directly the kinship terms of a society that uses one system into the language of a society that uses a different system.\n\nSome languages, such as [[Japanese language|Japanese]], add another dimension to some relations: relative age. There are different words for \"older brother\" and \"younger brother.\"\n\n==Western kinship terminology==\nMost Western societies employ Eskimo Kinship terminology. This kinship terminology is common in societies based on conjugal (or nuclear) families, where nuclear families must be relatively mobile.\n\nMembers of the nuclear family use descriptive kinship terms:\n*\'\'\'[[Mother]]\'\'\': the female parent\n*\'\'\'[[Father]]\'\'\': the male parent\n*\'\'\'[[Son]]\'\'\': the males born of the mother\n*\'\'\'[[Daughter]]\'\'\': the females born of the mother\n*\'\'\'[[Brother]]\'\'\': a male born of the same mother\n*\'\'\'[[Sister]]\'\'\': a female born of the same mother\n\nIt is generally assumed that the mother\'s husband is also the genitor. In some families, a woman may have children with more than one man or a man may have children with more than one woman. Children who share one parent but not another are called \"half-brothers\" or \"half-sisters.\" Children who do not share parents, but whose parents are married, are called \"step-brothers\" or \"step-sisters.\" \nIf a person is married to the parent of a child, but is not the parent of the child themselves, then they are the \"step-parent\" of the child, either the \"stepmother\" or \"stepfather\". Children who are adopted into a family are generally called by the same terms as children born into the family.\n\nTypically, societies with conjugal families also favor neolocal residence; thus upon marriage a person separates from the nuclear family of their childhood (family of orientation) and forms a new nuclear family (family of procreation). This practice means that members of one\'s own nuclear family were once members of another nuclear family, or may one day become members of another nuclear family.\n\nMembers of the nuclear families of members of one\'s own nuclear family may be lineal or collateral. When they are lineal, they are referred to in terms that build on the terms used within the nuclear family:\n*\'\'\'Grandfather\'\'\': a parent\'s father\n*\'\'\'Grandmother\'\'\': a parent\'s mother\n*\'\'\'Grandson\'\'\': a child\'s son\n*\'\'\'Granddaughter\'\'\': a child\'s daughter\n\nWhen they are collateral, they are referred to in more classificatory terms that do not build on the terms used within the nuclear family:\n*\'\'\'Uncle\'\'\': father\'s brother, father\'s sister\'s husband, mother\'s brother, mother\'s sister\'s husband\n*\'\'\'Aunt\'\'\': father\'s sister, father\'s brother\'s wife, mother\'s sister, mother\'s brother\'s wife\n*\'\'\'Nephew\'\'\': sister\'s sons, brother\'s sons\n*\'\'\'Niece\'\'\': sister\'s daughters, brother\'s daughters\nWhen separated by additional generations (in other words, when one\'s collateral relatives belong to the same generation as one\'s grandparents or grandchildren), these terms are modified by the prefix \"great\".\n\nMost collateral relatives were never members of the nuclear family of the members of one\'s own nuclear family.\n*\'\'\'Cousin\'\'\': the most classificatory term; the children of aunts or uncles. Cousins may be further distinguished by degree of collaterality and generation. Two persons of the same generation who share a grandparent are \"first cousins\" (one degree of collaterality); if they share a great-grandparent they are \"second cousins\" (two degrees of collaterality) and so on. If the shared ancestor is the grandparent of one individual and the great-grandparent of the other, the individuals are said to be \"first cousins once removed\" (removed by one generation); if the shared ancestor is the grandparent of one individual and the great-great-grandparent of the other, the individuals are said to be \"first cousins twice removed\" (removed by two generation), and so on. \n\nDistant cousins of an older generation (in other words, one\'s parents\' first cousins) are technically first cousins once removed, but are often classified with \"aunts\" and \"uncles\".\n\nSimilarly, a person may refer to close friends of one\'s parents as \"aunt\" or \"uncle,\" or may refer to close friends as \"brother\" or \"sister\". This practice is called \'\'\'fictive kinship\'\'\'.\n\nRelationships by marriage, except for wife/husband, are qualified by the term \"-in-law\". The mother and father of one\'s spouse are one\'s mother-in-law and father-in-law; the spouse of one\'s son or daughter is one\'s son-in-law or daughter-in-law.\n\nThe term \"sister-in-law\" refers to three essentially different relationships, either the wife of one\'s brother, of the sister of one\'s spouse, or the wife of one\'s spouse\'s sibling. \"Brother-in-law\" is similarly ambiguous. There are no special terms for the rest of one\'s spouse\'s family.\n\n==See also==\n*[[ancestor]]\n*[[marriage]] \n*[[household]]\n*[[genealogy]]\n*[[family life in literature]]\n*[[family law]]\n*[[family name]]: exists only in some cultures\n*[[family relationship]]\n*[[family/State paradigm]]\n\n==References==\n* \'\'American Kinship\'\', David Schneider\n\n==External links==\n* \'\'Online Dictionary of the Social Sciences\'\': http://bitbucket.icaap.org/\n* \'\'Cousins\'\': http://www.tedpack.org/cousins.html\n\n[[Category:Kinship and descent]]\n\n[[de:Familie]]\n[[ms:Keluarga]]\n[[da:Familie]]\n[[eo:Familio]]\n[[fr:Famille]]\n[[no:Familie]]\n[[sv:Familj]]','',13,'Budhi','20040724141046','',0,0,0,1,0.659478940377,'20040724141046','79959275858953'); INSERT INTO cur VALUES (1047,0,'Pangan','[[Image:Foods.jpg|thumbnail|right|Pangan tina tutuwuhan]]\n\n\'\'\'Pangan\'\'\' nyaéta [[zat]] naon baé nu ilahar di[[dahar]] atawa diinum ku [[hirup|mahluk hirup]]. Istilah \'\'pangan\'\' ogé ngawengku inuman [[cair]]. Pangan ngarupakeun sumber utama [[énergi]] sarta ngarupakeun [[gizi]] pikeun sato, nu biasana sumberna ti [[sato]] ogé atawa ti [[tutuwuhan]].\n\nUlikan ngeunaan pangan disebut [[élmu pangan]] (\'\'food science\'\').\n\n==Harti formal==\nHukum pangan di [[Dunya Kulon|Kulon]] ngabédakeun pangan kana opat kategori:\n*zat atawa produk naon baé, boh nu diolah, diolah sawaréh, atawa nu teu diolah, nu dimaksudkeun pikeun kadaharan manusa tanpa nempo ajén gizina;\n*[[cai]] jeung [[nginum|inuman]] séjénna;\n*[[permén karét]];\n*zat naon baé nu dipaké salaku \'\'[[ingredient]]\'\' atawa [[komponén]] dina nyiapkeun pangan.\n\n**[http://www.fda.gov/opacom/laws/fdcact/fdcact1.htm Dadaran Pamaréntah Féderal AS ngeunaan pangan]\n**[http://www.legislation.hmso.gov.uk/acts/acts1990/Ukpga_19900016_en_2.htm#mdiv1 Dadaran Inggris ngeunaan pangan]\n**[http://europa.eu.int/smartapi/cgi/sga_doc?smartapi!celexapi!prod!CELEXnumdoc&lg=EN&numdoc=32002R0178&model=guichett Dadaran Uni Éropa ngeunaan pangan]\n\n==Kabiasaan dahar manusa==\n\n===Historical development===\n\n[[Manusa]] ngarupakeun [[omnivora]] nu ngadahar boh hasil tutuwuhan (nabati) atawa sato (héwani). We changed from \'\'gatherers\'\' to \'\'[[Hunter-gatherer|hunter gatherers]]\'\'. After the experience of the [[Ice Age]] it is probable that humans wanted to create some feeling of security by controlling what plants were growing and which animals were available. This led to [[agriculture]], which has [[Timeline of agriculture and food technology|continually improved]] and altered the way in which food is obtained.\n\n===Meals===\nA selection of different complementary foods eaten together comprises a [[meal]]. People often choose to eat meals together with other [[family]] members or [[friend]]s and this is seen as an important [[social]] occasion. Food eaten in smaller quantities between meals is regarded as [[snack food]].\n\nThe number of meals in a [[day]], their [[size]], [[composition]], when and how they are prepared and eaten vary greatly around the world. This is greatly dependent on the local [[climate]], [[ecology]], [[Economics|economy]], [[culture|cultural]] [[tradition|traditions]] and [[industrialisation]]. Meals also plays an important role in the celebration of many key [[culture|cultural]] and [[religion|religious]] [[festival]]s.\n\nIn societies where the availability of food has risen above [[subsistence]] levels and beyond [[staple food]]s, food is also [[sell|sold]] pre-prepared for immediate consumption in [[restaurant]]s and other similar [[retail]] premises. In industrial societies, meals often contain a higher proportion of food of animal origin.\n\n:\'\'See also: [[Appetite]], [[Buddhist cuisine]], [[Eucharist]], [[Fast food]], [[Fasting]], [[Gault Millau|Gault Millau restaurant guide]], [[Halaal]], [[I-tal]], [[Kashrut]], [[Michelin|Michelin restaurant guide]], [[Muslim dietary laws]], [[Potluck]], [[Totemism]]\'\'.\n\n==Food production or acquisition==\nFood is traditionally obtained through [[farming]], [[ranching]], and [[fishing]], with [[hunting]], [[foraging]] and other [[List of subsistence techniques|methods of subsistence]] locally important for some populations, but minor for others.\n\nIn the modern era, in [[developed nations]], food supply is increasingly dependent upon [[agriculture]], [[factory farming|industrial farming]], [[aquaculture]] and [[fish farming]] techniques which aim to maximise the amount of food produced, whilst minimising the [[cost]]. These include a reliance on mechanised tools which have been developed, from the [[threshing machine]], [[seed drill]], through to the [[tractor]] and [[Combine|combine harvester]], etc. These have been combined with the use of [[pesticide]]s to promote high [[crop]] [[yield]]s and combat those [[insect]]s or mammals which reduce yield.\n\nMore recently, there has been a growing trend towards more [[sustainable agriculture|Sustainable agricultural]] practices. This approach - which is partly fuelled by [[consumer]] [[demand]] - encourages [[biodiversity]], local self-reliance and [[Organic farming]] methods.\n\nMajor influences on food production are international policy, \'\'e.g. the [[World Trade Organization]] and [[Common Agricultural Policy]]\'\', national government policy or [[law]] and [[war]].\n\nFood for [[livestock]] is [[fodder]] and traditionally comprises [[hay]] or [[grain]]. \n\n:\'\'See also: [[mariculture]], [[horticulture]], [[agribusiness]], [[gardening]].\'\'\n\n===Tina [[tutuwuhan]]===\n*[[Poaceae|Jujukutan]] katut sisikianana (\'\'[[grains]]\'\'), kayaning \'\'[[barley]]\'\', [[séréal]], \'\'[[couscous]]\'\', [[jagong]], \'\'[[oats]]\'\', [[béas]], \'\'[[rye]]\'\', \'\'[[sugarcane]]\'\', [[gandum]]\n* [[Buah|Bubuahan]], tempo ogé [[daptar bubuahan]]\n* [[Herb]]s, see also [[list of herbs and spices]]\n* [[Legume]]s, including [[bean]]s, [[pea]]s, [[lentil]]s, [[jicama]]\n* [[Nut (fruit)|Nut]]s\n* [[Seed]]s\n* [[Spice]]s, see also [[list of herbs and spices]]\n* [[Sayur]], tempo ogé [[daptar sayuran]]\n\n===Tina sasatoan=== \n* [[Dairy product]], kaasup [[susu]]\n* [[Endog]]\n* [[Lauk]]\n* [[Sarangga]], kaasup [[madu]]\n* [[Daging]]\n* [[Offal]], kaasup [[getih]]\n* [[Peternakan]], kaasup [[hayam]], [[kalkum]], [[éntog]], [[meri]], [[soang]], [[japati]], [[ostrich]], [[emu]], [[guinea fowl]], [[pheasant]], [[quail]]\n* [[Seafood]], kaasup [[molluska]] jeung [[crustacea]], which are collectively known as [[shellfish]]\n* [[Game (food)|Game]], this includes all animals hunted for food.\n\n===Boh ti sato atawa tutuwuhan===\n* [[Cai]], kaasup [[cai mineral]] jeung [[cai gunung]]\n\n==Food preparation==\nWhilst some food can be eaten without preparation, many foods undergo some form of preparation for reasons of safety, palatability, or [[Flavor|flavour]]. At the simplest level this may involve [[washing]], [[cutting]], trimming or adding other foods or ingredients, such as [[spice]]s. It may also involve mixing, heating or cooling, [[Pressure cooking]], [[fermentation]], or combination with other food. Most food preparation takes place in a [[kitchen]].\n\nThe preparation of animal-based food will usually involve [[slaughter]], [[evisceration]], hanging, [[portion]]ing and [[rendering]].\n\n:\'\'See also:\'\' [[Barbecue]], [[List of eating utensils|Eating utensils]], [[Frankfurt kitchen]], [[Hangi]], [[Oven]], [[Microwave oven]], [[Refrigeration]], [[:Category:Food preparation utensils|Food preparation utensils]].\n\n===Recipes===\nHuman knowledge of [[cooking]] and preparation methods is often taught by [[parenting|parents]] to their [[child]]ren, largely based on the [[cuisine]] within their cultural traditions. Since the development, of mass-produced printing, this has been supplemented by written [[recipe]]s. Early examples of influential recipe books include [[De re coquinaria]], [[Le Repertoire De La Cuisine]], [[Larousse Gastronomique]] and [[Mrs Beeton\'s Book of Household Management]].\n\n:\'\'See also: \'\'[http://wikibooks.org/wiki/Cookbook Wikipedia cookbook].\n\n===Food manufacture===\nFood manufacturing, or food processing, arose during the industrialisation era in the [[19th century]]. This development took advantage of new [[Mass-marketing|mass markets]] and emerging new technology, such as [[milling]], [[food preservation]], [[packaging and labelling]] and [[transport|transportation]]. It brought the advantages of pre-prepared time saving food to the bulk of ordinary people who did not employ [[domestic servant]]s.\n\nAt the start of the [[21st century]], a two-tier structure has arisen, with a few international food processing giants controlling a wide range of well known food [[brand]]s; with a populous number of small local or national food processing companies.\n\n:\'\'See also: [[Best before]], [[Canning]], [[Food coloring|Coloring]], [[Food quality]], [[Cook/chill]], [[Food additive|Additive]]s, [[Flavoring]], [[Enzyme]]s, [[Genetically modified food]], [[Packaging and labelling]], [[Pasteurization]], [[Food preservation|Preservation]], [[Shelf-life]], [[Ultra-high temperature processing]].\'\'\n\n====Types of manufactured food==== \n* [[Drink]]s: [[beer]], [[juice]], [[soft drink]], [[Squash (drink)|squash]], liquids.\n* [[Bread]] is a staple food for many nations, being made of risen dough.\n* [[Cheese]] is a curdled milk product, of which many varieties exist.\n* [[Dessert]] is a course, usually sweet, and generally served after the main course, e.g. [[Ice cream]].\n* [[French fries]]\n* [[Jelly]] and [[Jam]]\n* [[Pasta]]\n* [[Pizza]]\n* [[Sandwich]]\n* [[Salad]]\n* [[Sauce]]\n* [[Sausage]]\n* [[Snack food]]: [[Confectionery]], [[Potato chips]], [[Chocolate]], [[Cracker (biscuit)]], [[Hardtack]]\n* [[Soup]]\n* [[Sugar]]\n\n==Food trade==\nFood is now [[trade]]d on a global basis. The [[Variety (biology)|variety]] and availability of food is no longer restricted by the diversity of locally grown food or the limitations of the local growing [[season]]. Between [[1961]] and [[1999]] there has been a 400% increase in worldwide food [[export]]s. Some countries are now economically dependant on food exports, which in some cases account for over 80% of all exports.\n\nIn [[1994]] trade liberalisation began when over 100 countries became signatories to the [[Uruguay Round]] of the [[General Agreement on Tariffs and Trade]] which included an agreement to reduce subsidies paid to farmers. This is underpinned by the WTO enforcement of [[Agricultural policy|agricultural subsidy]], [[Tax, tariff and trade|tariffs]], import [[quota]]s and settlement of trade disputes that cannot be bilaterally resolved. Where trade barriers are raised on the disputed grounds of public health and safety, the WTO refer the dispute to the [[Codex Alimentarius]] Commission, which was founded in [[1962]] by the [[United Nations]] [[Food and Agriculture Organization]] and the [[World Health Organization]].\n\n===Food retailing===\n[[Image:Beer and wine aisle.jpg|thumb|right|Supermarket goods]]\nThe sale of surplus food traditionally took place once a week when farmers took their wares on market day, into the local [[village]] [[market place]]. Here food was sold to [[grocer]]s for sale in their local shops for purchase by local people.\n\nWith the onset of industrialisation, and the development of the food processing industry, a wider range of food could be sold and distributed in distant locations. Typically early grocery shops would be [[counter]]-based shops, in which purchasers told the shop-keeper what they wanted, so that the shop-keeper could get it for them.\n\nIn the [[20th century]] supermarkets were born. Supermarkets brought with them a [[self-service]] approach to shopping using [[shopping cart]]s (or Trollies in [[British English]]) and were able to offer quality food at lower cost, through [[economies of scale]] and reduced staffing costs. This was sometimes known as \'[[pile it high]]\' In the latter part of the [[20th century]], this has been further revolutionised by the development of vast [[warehouse]] sized out-of-town supermarkets, selling an extraordinarily wide range of food from around the world.\n\nAlike with food processors, food retailing is a two-tier market in which a small number of very large [[Corporation|companies]] control a large proportion of supermarkets. The supermarket giants wield great purchasing power over farmers and processors, and strong influence over consumers. Nevertheless, in [[2000]] only 19% of all US consumer expenditure spent on food went to farmers.\n\nRecent technological innovations such as [[point of sale]] technology - [[barcode]]s. This allows ordering of goods and food to be driven by actual sales.\n\n:\'\'See also: [[Farmers\' market]]\'\'\n\n==Pangan jeung kaséhatan==\n===Kacukupan pangan===\nDeprivasi pangan ngakibatkeun [[malnutrisi]] nu antukna jadi [[kalaparan]] (Ing. \'\'starvation\'\'). Ieu biasana patali jeung \'\'[[famine]]\'\', kakurangan pangan di masarakat, nu mawa balukar kana kaséhatan jeung mortalitas manusa. [[Taun]] [[2003]] sataunna aya kira 40 yuta urang nu maotr alatan [[kalaparan]]. [[Rationing]] is sometimes used to fairly the equal distribution of food in times of shortage, most notably during times of war.\n\nFood deprivation is regarded as a deficit need in [[Maslow\'s hierarchy of needs]].\n\n====Bantuan pangan====\nBantuan pangan bisa ngabantuan jalma-jalma nu kakurangan pangan. Sabalikna, bantuan pangan nu dikokolakeun sacara teu bener bisa ngaruksak pasar lokal, neken harga [[crop]] sarta ngalemahkeun produksi pangan. Its provision, or threatened withdrawal, is sometimes used as a political tool to influence the [[politics]] of the destination country. International efforts to distribute food to the neediest countries are co-ordinated by the [[World Food Program]].\n\n:\'\'Tempo ogé: [[Fair trade]], [[food security]]\'\'.\n\n===Kasalametan pangan===\n[[Kasakit alatan pangan]] (Ing. \'\'foodborne illness\'\') atawa [[karacunan pangan]], disababkeun ku [[baktéri]], [[toxin]], [[virus]], jeung [[prion]]. Karacunan pangan geus kasebutkeun ti jaman [[Hipokratés]]. Nelasan ku jalan ngaracun dahareun geus aya ti jaman [[Karajaan Romawi]]. In the [[Middle Ages]] all [[Noble court|Royal Court]]s had food tasters.\n\nThe sale of [[Rancidity|rancid]], contaminated or adulterated food was commonplace until introduction of [[hygiene]] and [[vermin]] controls in the [[19th century]]. Discovery of techniques for killing [[bacterium|bacteria]] using [[heat]] and other [[microbiology|microbiological ]] by scientists such as [[Louis Pasteur]] contributed to the modern standards that we enjoy today. This was further underpinned by the work of [[Justus von Liebig]] whose work led to the development of modern [[food storage]] and [[food preservation]] methods.\n\nUnderstanding of the causes of food-borne-illnesses and more systematic techniques for their elimination has led to the development of commercial systems such as [[HACCP]] which can, if properly implemented, identify and can eliminate all possible risks.\n\n===Dietary habits===\n[[Diet (nutrition)|Dietary habits]] play a significant role in the [[health]] and [[mortality]] of all humans. For example:\n\n*[[Eating disorder]]s are a group of mental disorders that interfere with normal food consumption. They often affect people with a negative [[body image]];\n*13[[%]] of the world\'s population suffer from [[Iodine]] deficiency;\n*In 2003 it was estimated that [[vitamin A]] deficiency causes [[blindness]] in up to 500,000 children each year;\n*[[Vitamin C]] deficiency results in [[scurvy]];\n*[[Kwashiorkor]] and [[marasmus]] are childhood disorders caused by lack of dietary [[protein]].\n*Certain foods contain [[allergen]]s which can safely be consumed by the majority by people. However, these can trigger severe illness in small proportion of susceptible people. Rarely this can trigger [[anaphylaxis]] which can be fatal.\n\nConcerns about foodborne illness have long influenced diet. Traditionally humans have leant to avoid foods that induce [[acute]] illness. Some believe that this is the underlying rationale behind some traditional religious dietary requirements. Additionally, many people choose to forgo food from animal sources to varying degrees; see [[vegetarianism]], [[veganism]], [[fructarianism]] , [[living foods diet]], and [[Raw foodist|raw foodism]].\n\nThe nutrient content of diets in industrialised countries contain more [[animal fat]], sugar, [[energy]], [[alcohol]] and less [[dietary fiber]], [[carbohydrate]]s and [[antidioxidant]]s. Contemporary changes to [[work]], [[family]] and [[exercise]] patterns, together with concerns about the effect of [[nutrition]] and [[obesity]] on human [[health]] and mortality are all having an effect on traditional eating habits. [[Physician]]s and [[alternative medicine]] practitioners may recommend changes to diet as part of their recommendations for treatment.\n\nMore recently, dietary habits have been influenced by the concerns that some people have about the [[chronic]] impact on health that arise through the consumption of [[genetically modified food]] or beef infected with [[Bovine spongiform encephalopathy]]. Further concerns about the impact of indudtrial farming on [[animal welfare]], human health and the [[Ecology|environment]] are also having an effect on contemporary human dietary habits. This has led to the emergence of a [[counterculture]] with a preference for [[organic food|organic]] and [[local food]].\n\n:\'\'See also: [[Food faddism]], [[Health claims on food labels]], [[list of diets]], [[Slow Food]].\'\'\n\n===[[Gizi]] dina pangan===\n* [[Kalsium]]\n* [[Karbohidrat]]\n* [[Asam amino ésénsil]]\n* [[Lemak]]\n* [[Beusi]]\n* [[Mineral]]\n* [[Zat Fitokimia]], kaasup antioksidan, [[énzim]], bio-flavonoid\n* [[Kalium]]\n* [[Protéin]]\n* [[Natrium]]\n* [[Aci]]\n* [[Vitamin]]\n* [[Cai]]\n\nKanyaho ngeunaan kandungan gizi jeung interaksi antarkomponén na [[métabolisme]] manusa pikeun asupan/diet idéal kiwari jadi ladang kaweruh nu terus tumuwuh.\n\n==Tempo ogé== \n* [[Daptar jejer pangan]]\n\n==Tumbu kaluar==\n*[http://www.dmoz.org/Recreation/Food/ Food Directory]\n*[http://www.foodinfonet.com Food Info Net: A leading internet portal for the global food industry].\n*[http://www.foodlexicon.net/ Food Lexicon: English, French, German, Danish, Dutch, Spanish]\n*[http://www2.gol.com/users/pbw/dicta.htm Patto\'s Gourmet Dictionary: English, French, German, Italian, Spanish, Nihongo].\n* [http://www.gti.net/mocolib1/kid/food.html Food Timeline]\n* [http://www.nutritiondata.com Nutritiondata.com]\n* [http://www.talkwellness.org/dietary-guidelines.html Dietary Guidelines] \n* [http://www.ichef.com Recipes]\n\n\n[[Category:Dahareun jeung inuman]]\n\n[[cy:Bwyd]]\n[[da:Mad]]\n[[de:Nahrungsmittel]]\n[[en:Food]]\n[[es:Alimento]]\n[[eo:Manĝaĵo]]\n[[fr:Nourriture]]\n[[he:מזון]]\n[[nah:Tlacualli]]\n[[nl:Voeding]]\n[[ja:食品]]\n[[no:Mat]]\n[[nds:Eeten]]\n[[simple:Food]]\n[[zh:食品]]','/* Kasalametan pangan */',3,'Kandar','20041222033216','',0,0,0,0,0.02231170145,'20050316081936','79958777966783'); INSERT INTO cur VALUES (1048,6,'Foods.jpg','','',13,'Budhi','20040724141305','',0,0,0,1,0.949847824824832,'20041222033217','79959275858694'); INSERT INTO cur VALUES (1049,0,'Random_variable','#REDIRECT [[Variabel random]]\n','Random variable moved to Variabel random',13,'Budhi','20040725000210','',0,1,0,1,0.629655928006075,'20040725000210','79959274999789'); INSERT INTO cur VALUES (1050,0,'Mangsa_katukang','#REDIRECT [[sajarah]]','',13,'Budhi','20040725000814','',0,1,0,1,0.480330003649,'20040725000832','79959274999185'); INSERT INTO cur VALUES (1051,0,'Past','#REDIRECT [[Mangsa katukang]]\n','Past moved to Mangsa katukang',13,'Budhi','20040725000832','',0,1,0,1,0.298736196289525,'20040725000832','79959274999167'); INSERT INTO cur VALUES (1052,6,'Wiki-logo-su.png','Resized Wiki.png','Resized Wiki.png',15,'Fire','20040725003118','',0,0,0,1,0.604713228163042,'20040725003118','79959274996881'); INSERT INTO cur VALUES (1053,0,'Likelihood_function','#REDIRECT [[Likelihood]]','',13,'Budhi','20040725005428','',0,1,0,1,0.948033634549,'20040725005428','79959274994571'); INSERT INTO cur VALUES (1054,0,'Likelihood_principle','#REDIRECT [[Prinsip likelihood]]\n','Likelihood principle moved to Prinsip likelihood',13,'Budhi','20040725005621','',0,1,0,1,0.127357582680283,'20040725005621','79959274994378'); INSERT INTO cur VALUES (1055,6,'Physical_world.jpg','From public domain http://www.odci.gov/cia/publications/factbook/reference_maps/physical_world.html','From public domain http://www.odci.gov/cia/publications/factbook/reference_maps/physical_world.html',13,'Budhi','20040725012840','',0,0,0,1,0.822648259645932,'20041210102040','79959274987159'); INSERT INTO cur VALUES (1056,6,'Japan_coa.png','Japanese Imperial coat of arms','Japanese Imperial coat of arms',13,'Budhi','20040725022105','',0,0,0,1,0.731168580922455,'20040725022105','79959274977894'); INSERT INTO cur VALUES (1057,6,'LocationJapan.png','Lokasi Jepang ti Wikipedia English','Lokasi Jepang ti Wikipedia English',13,'Budhi','20040725022233','',0,0,0,1,0.187898156408126,'20040725022233','79959274977766'); INSERT INTO cur VALUES (1058,6,'Ja-map.png','','',13,'Budhi','20040725022340','',0,0,0,1,0.745985070006908,'20040725022340','79959274977659'); INSERT INTO cur VALUES (1059,6,'PrefSymbol-Gifu.png','Gifu prefectural symbol (source: ja.wikipedia.org)','Gifu prefectural symbol (source: ja.wikipedia.org)',13,'Budhi','20040725022453','',0,0,0,1,0.166230911543808,'20050303143846','79959274977546'); INSERT INTO cur VALUES (1060,6,'Japan_gifu_map_small.png','Small map of Gifu prefecture','Small map of Gifu prefecture',13,'Budhi','20040725022630','',0,0,0,1,0.59319937843196,'20050303143846','79959274977369'); INSERT INTO cur VALUES (1061,0,'Kaséhatan','Organisasi Kasehatan Dunya ([[World Health Organization]]) ngartikeun \'\'\'kaséhatan\'\'\' nyaeta:\n\n:\"A state of complete physical, mental and social well-being, and does not consist only of the absence of disease or infirmity.\"\n\nIn any [[organism]], health is a form of [[homeostasis]]. This is a of balance, with inputs and outputs of energy and mass in approximate equilibrium (allowing for growth). Health also implies positive prospects for continued survival. \n\nIn [[human]]s, with the capacity to analyze and anticipate, health is more than immediate homeostasis. That is, not only must everything be all right at the moment, but there should be subjective understanding that the \"healthful\" balance will continue. This understanding comes from [[somatic]] perception, including [[pain]] and discomfort, as well as [[cognitive]] perception. In order to feel health, people need to feel that they look well, are functioning as well as they always have, and that no external or internal risk imminently endangers their healthful state.\n\nThe study of health of humans and animals is [[health science]]. \n\n\'\'See also\'\': [[wellness]] [[disease]] [[health professional]]\n\n[[bg:Здраве]]\n[[de:Gesundheit]] [[eo:Sansciencoj]] [[es:Salud]] [[fr:Santé]] [[ja:健康]] [[nl:Gezondheidszorg]] [[pl:Medycyna]] [[simple:Health]][[ms:kesihatan]][[no:Helse]]\n\n\n\n[[Category:Hirup-hurip]]\n[[Category:Kaséhatan]]\n[[Category:Manusa]]','kategori manusa',20,'DiN','20050303201931','',0,0,0,0,0.75487353781,'20050303201931','79949696798068'); INSERT INTO cur VALUES (1062,0,'Imah','[[Image:St-albans-fishpool-st.jpg|right|Houses in Fishpool Street, St Albans, England]]\n\n\'\'Harti lain tina imah tempo di [[House (disambiguation)]]\'\'.\n\n\'\'\'Imah\'\'\' dina rasa nu geus umum ngarupakeun struktur bangunan meunang [[manusa]] nu dihalangan ku [[tembok]] jeung [[hateup]]. Imah hiji tempat keur ngahindar tina [[precipitation (meteorology)|precipitation]], kaanginan, kapanasan, katiisan, gangguan manusa sareng satoa. When occupied as a routine dwelling for humans, a house is called a [[home]]. Masarakat kadang indit ti imah dina sababaraha poe keur kaperluan [[employment|work]] jeung [[recreation]], tapi imah boga fungsi utama keur [[sleeping]].\n\nSacara umum imah ngabogaan hiji jalan asup, nu ilaharna mangrupa [[panto]] atawa [[gapura]], jeung mungkin ngabogaan sababaraha [[jandéla]] atawa leuwih.\n\n==Sajarah==\nImah geus dipake tempat cicing ku manusa ti zaman pra-sajarah, mimiti dipake salaku alternatif tina cicing dina [[cave]], and construction materials, styles and methods of construction have varied wildly over time.\n\nEarly European houses were mere single-roomed shacks without windows in which entire families and their [[cattle]] lived, keeping the house and each other relatively warm during winter.\n\nAmong the first examples (according to the estimated age of archaeological retrievals), notable are the [[palafitte]]s.\n\n==Bentuk sejen==\n\nAn alternative form of housing is an [[apartment]] (or flat), which is one of several individual units on different levels separated by floors, walls and doors but combined to form a larger [[building]] under a shared roof. A house containing only two apartments is called a [[duplex]]. In England a flat on two floors is often called a [[maisonette]]. A \'\'\'[[mansion]]\'\'\' is a very large house, often very ornate and expensive.\n\n==Pangiuhan==\nBentuk \'\'\'pangiuhan\'\'\' (\'\'shelter\'\') nu leuwih basajan batan imah di antarana [[dugout (shelter)|dugout]]s, [[ténda]] (tempo ogé [[camp]]), [[camper]]s, [[hut]]s, [[roof]]s without [[wall]]s, or a structure with roof and partial walls, such as often at a [[bus stop]] (see picture there), and a [[gazebo]].\n\n==Construction==\nPopular modern house construction techniques include [[light-frame construction]] in areas with access to supplies of wood, and [[adobe]] or sometimes [[rammed-earth construction]] in arid regions with scarce wood resources.\n\nAlternative building structures have recently gain (or regained) popularity in recent years. Examples of these are [[cordwood construction]], [[strawbale construction]], and [[geodesic dome|geodesic domes]].\n\n==Imah sato==\nHumans often build houses for domestic or wild animals, often resembling smaller versions of human domiciles. Familiar animal houses built by humans include \'\'\'[[bird house]]s\'\'\' and \'\'\'[[dog house]]s\'\'\' ([[kennel]]s), while domiciles for agricultural animals are more often called [[Barn (building)|barn]]s.\n\n==Usage in language==\nAs a verb, to \'\'house\'\' (pronounced \"howz\") is to provide a routine locale for an object, a person or an organization. Historic or artistic artifacts, for example, are said to be housed in museums. A business may be housed in a storefront, or a family may be housed in an apartment or a house. A collection of domiciles, either for persons, for organizations, for animals or for objects, is often called \'\'housing\'\'. An individual person or a single object might also find housing in an appropriate [[domicile]].\n\n==Community standards==\nCommunities often establish standards, either by formal process or by custom, for adequate housing. Concepts related to housing include:\n* \'\'\'housing shortages\'\'\', which is a disproportionate number of people needing houses compared to the availability of structures.\n* \'\'\'substandard housing\'\'\', which is the existence of housing structures that lack sufficient space, environmental protection, security or maintenance to conform to community standards.\n* \'\'\'[[homelessness]]\'\'\', which refers to the condition of humans who lack a regular abode.\n* \'\'\'billet\'\'\', which refers to the usually [[military]] act of ordering [[civilian]]s to share private homes or to surrender private homes to soldiers. \'\'Billet\'\' is sometimes used as a metaphor to describe any temporary housing situation.\n* [[council house]] or council flat, a house or flat which is provided by the state for the use of the poor.\n* [[mortgage]], a loan secured on a house.\n\n== Tempo ogé == \n===Artikel===\n*[[Bahan wangunan]]\n*\'\'[[Co-housing]]\'\'\n*\'\'[[Domotics]]\'\' jeung [[otomasi imah]].\n*[[Earth-sheltered home]]\n*[[Housing estate]]\n*[[Lustron]]\n*[[Mobile home]]\n*[[Parker Morris Committee]]\n*[[Penthouse]]\n*[[Trailer]]\n\n===Daptar===\n*[[Daptar tipe imah]]\n*[[Daptar gaya imah]]\n*[[Daptar jejer real estate]]\n\n== Tumbu kaluar ==\n*[http://y2u.co.uk/&002_Images/Downland_Museum%2001.htm Photos of rare houses at Singleton Wealdland and Downland Museum, Nr Chichester]\n\n\n[[da:Hus]] [[de:Haus]] [[en:House]] [[eo:Domo]] [[nah:Chantli]] [[ja:家屋]] [[pl:Dom]] [[sv:Hus]] [[pt:casa]]\n\n\n[[Category:Imah]]\n\n','/* Shelters */',3,'Kandar','20041206093020','',0,0,0,0,0.594162133333,'20041206093020','79958793906979'); INSERT INTO cur VALUES (1063,6,'St-albans-fishpool-st.jpg','Houses in Fishpool St, St Albans, 12 October 2003. The original can be found at [1] (http://arglist.com/photos/).','Houses in Fishpool St, St Albans, 12 October 2003. The original can be found at [1] (http://arglist.com/photos/).',13,'Budhi','20040725032136','',0,0,0,1,0.467304188262023,'20041206093024','79959274967863'); INSERT INTO cur VALUES (1064,0,'Linguistik','{{linguistics}}\n\nGeus ditarima sacara umum, \'\'\'Basa\'\'\' nyaeta elmu ngeunaan [[language]] manusa, and a \'\'\'linguist\'\'\' is someone who engages in this study. The study of linguistics can be thought of along three major axes, the endpoints of which are described below:\n\n* Synchronic and diachronic -- Synchronic study of a language is concerned with its form at a given moment; diachronic study covers the history of a language (group) and its structural changes over time. \n* Theoretical and applied -- Theoretical linguistics is concerned with frameworks for describing individual languages and theories about universal aspects of language; applied lingusitics applies these theories to other fields.\n* Contextual and independent -- Contextual linguistics is concerned with how language fits into the world: its social function, how it is acquired, how it is produced and perceived. \'\'Independent\'\' linguistics considers languages for their own sake, aside from the externalities related to a language. Terms for this dichotomy are not yet well established--the [[Encyclopædia Britannica]] uses \'\'macrolinguistics\'\' and \'\'microlinguistics\'\' instead. \n\nGiven these dichotomies, scholars who call themselves simply \'\'linguists\'\' or \'\'theoretical linguists\'\', with no further qualification, tend to be concerned with independent, theoretical synchronic linguistics, which is acknowledged as the core of the discipline. \n\nLinguistic [[research|inquiry]] is pursued by a wide variety of specialists, who may not all be in harmonious agreement; as [[Russ Rymer]] flamboyantly puts it:\n\n
\"Linguistics is arguably the most hotly contested property in the academic realm. It is soaked with the blood of [[poet]]s, [[theologian]]s, [[philosopher]]s, [[philologist]]s, [[psychologist]]s, [[biologist]]s, and [[neurologist]]s, along with whatever blood can be got out of [[grammarian]]s.\" [[Linguistics#References|1]]
\n\n==Areas of theoretical linguistics ==\nTheoretical linguistics is often divided into a number of separate areas, to be studied more or less independently. The following divisions are currently widely acknowledged:\n\n* [[phonetics]], the study of the different sounds that are employed across all human languages;\n* [[phonology]], the study of patterns of a language\'s basic sounds;\n* [[morphology (linguistics)|morphology]], the study of the internal structure of words;\n* [[syntax]], the study of how words combine to form grammatical sentences\n* [[semantics]], the study of the meaning of words ([[lexical semantics]]), and how these combine to form the meanings of sentences;\n* [[stylistics (linguistics)|stylistics]], the study of style in languages;\n* [[pragmatics]], the study of how utterances are used (literally, figuratively, or otherwise) in communicative acts;\n\nThe independent significance of each of these areas is not universally acknowledged, however, and nearly all linguists would agree that the divisions overlap considerably. Nevertheless, each subarea has core concepts that foster significant scholarly inquiry and research.\n\n==Diachronic linguistics==\nWhereas the core of theoretical linguistics is concerned with studying languages at a particular point in time (usually the present), diachronic linguistics examines how language changes through time, sometimes over centuries. Historical linguistics enjoys both a rich history (the study of linguistics grew out of historical linguistics) and a strong theoretical foundation for the study of language change.\n\nIn American universities, the non-historic perspective seems to have the upper hand. Many introductory linguistics classes, for example, cover historical linguistics only cursorily. The shift in focus to a non-historic perspective started with [[Ferdinand de Saussure|Saussure]] and became predominant with [[Noam Chomsky]].\n\nExplicitly historical perspectives include [[historical-comparative linguistics]] and [[etymology]].\n\n==[[Applied linguistics]]==\nWhereas theoretical linguistics is concerned with finding and describing generalities both within languages and among all languages, as a group, applied linguistics takes the results of those findings and \'\'applies\'\' them to other areas. Usually \'\'applied linguistics\'\' refers to the use of linguistic research in language teaching, but linguistics is used in other areas, as well. [[Speech synthesis]] and [[Speech recognition]], for example, use linguistic knowledge to provide voice interfaces to computers.\n\n==Contextual linguistics==\nContextual linguistics is that realm where linguistics interacts with other academic disciplines. Whereas core theoretical linguistics studies languages for their own sake, the inder-disciplinary areas of linguistic consider how language interacts with the rest of the world. But that rather depends upon their world-view.\n\n[[Sociolinguistics]], [[anthropological linguistics]], and [[linguistic anthropology]] are where the social sciences that consider societies as whole and linguistics interact.\n\n[[Critical discourse analysis]] is where [[rhetoric]] and [[philosophy]] interact with linguistics.\n\n[[Psycholinguistics]] and [[neurolinguistics]] is the where the [[medical science]]s meets linguistics. \n\nOther cross-disciplinary areas of linguistics include [[language acquisition]], [[evolutionary linguistics]], [[stratificational linguistics]], and [[cognitive science]].\n\n== Individual speakers, language communities, and linguistic universals ==\nLinguists also differ in how broad a group of language users they study. Some analyze a given speaker\'s language or [[language development]] in great detail. Some study language pertaining to a whole [[speech community]], such as the language of all those who speak [[Black English Vernacular]]. Others try to find linguistic universals that apply, at some abstract level, to all users of [[human language]] everywhere. This latter project has been most famously advocated by [[Noam Chomsky]], and it interests many people in [[psycholinguistics]] and [[cognitive science]]. It is thought that universals in human language may reveal important insight into universals about the [[human mind]].\n\n== Description and prescription ==\nMost work currently done under the name \"linguistics\" is purely descriptive; the linguists seek to clarify the nature of language without passing value judgments or trying to chart future language directions. Nonetheless, there are many professionals and amateurs who also [[prescriptive|prescribe]] rules of language, holding a particular standard out for all to follow.\n\nWhereas prescriptivists might want to stamp out what they perceive as \"incorrect usage\", descriptivists seek to find the root of such usage; they might describe it simply as \"[[idiosyncratic usage|idiosyncratic]]\", or they may discover a regularity that the prescriptivists don\'t like because it is perhaps too new or from a dialect they don\'t approve of.\n\n== Speech versus writing ==\nMost contemporary linguists work under the assumption that [[speech|spoken language]] is more fundamental, and thus more important to study, than [[writing]]. Reasons for this standpoint include:\n*Speech appears to be a human universal, whereas there are and have been many [[culture]]s that lack written communication;\n*People learn to speak and process [[oral language]] easier and earlier than writing; \n*A number of [[cognitive science|cognitive scientists]] argue that the [[brain]] has an innate \"[[language module]]\", [[knowledge]] of which is thought to come more from studying speech than writing.\n\nOf course, linguists agree that that the study of written language can be worthwhile and valuable. For linguistic research that uses the methods of [[corpus linguistics]] and [[computational linguistics]], written language is often much more convenient for processing large amounts of linguistic data. Large corpuses of spoken language are difficult to create and hard to find.\n\nFurthermore, the study of [[writing systems]] themselves falls under the aegis of linguistics.\n\n== Research areas of linguistics ==\n\n[[phonetics]], [[phonology]], [[syntax]], [[semantics]], [[pragmatics]], [[etymology]], [[lexicology]], [[lexicography]], [[theoretical linguistics]], [[historical-comparative linguistics]] and [[descriptive linguistics]], [[linguistic typology]], [[computational linguistics]], [[corpus linguistics]], [[semiotics]].\n\n== Interdisciplinary linguistic research ==\n\n[[applied linguistics]], [[historical linguistics]], [[orthography]], [[writing system]]s, [[historical linguistics|comparative linguistics]], [[cryptanalysis]], [[decipherment]], [[sociolinguistics]], [[critical discourse analysis]], [[psycholinguistics]], [[language acquisition]], [[evolutionary linguistics]], [[anthropological linguistics]], [[stratificational linguistics]], [[text linguistics]], [[cognitive science]], [[neurolinguistics]], and in [[Computational linguistics]] there is\n[[natural language understanding]], [[speech recognition]], [[speaker recognition]] (authentication), [[speech synthesis]], and more generally, [[speech processing]]\n\n== Important linguists and schools of thought ==\n\nEarly [[scholar]]s of linguistics include [[Jakob Grimm]], who devised the principle of consonantal shifts in pronunciation known as [[Grimm\'s Law]] in 1822, [[Karl Verner]], who discovered [[Verner\'s Law]], [[August Schleicher]] who created the \"Stammbaumtheorie\" and [[Johannes Schmidt (linguist)|Johannes Schmidt]] who developed the \"Wellentheorie\" (\"wave model\") in 1872. [[Ferdinand de Saussure]] was the founder of modern structural linguistics. [[Noam Chomsky|Noam Chomsky\'s]] formal model of language, [[transformational-generative grammar]], developed under the influence of his teacher [[Zellig Harris]], who was in turn strongly influenced by [[Leonard Bloomfield]], has been the dominant one from the [[1960s]].\n\nOther important linguists and [[school]]s include [[Michael Halliday]], whose [[systemic functional grammar]] is pursued widely in the [[United Kingdom|U.K.]], [[Canada]], [[Australia]], [[China]], and [[Japan]]; [[Dell Hymes]], who developed a pragmatic approach called The Ethnography of Speaking; [[George Lakoff]], [[Len Talmy]], and [[Ronald Langacker]], who were pioneers in [[cognitive linguistics]]; [[Charles Fillmore]] and [[Adele Goldberg (linguist)|Adele Goldberg]], who are associated with [[construction grammar]]; and linguists developing several varieties of what they call [[functionalism | functional grammar]], including [[Talmy Givon]] and [[Robert Van Valin, Jr.]].\n\n== Representation of speech ==\n\n* [[International Phonetic Alphabet]] (IPA), a system used to write down and reproduce the [[sound]]s of [[human speech]].\n* [[SAMPA]], an [[ASCII]]-only transcription for the IPA used by some authors. See also http://www.phon.ucl.ac.uk/home/sampa/home.htm\n\n== Narrower conceptions of \"linguistics\" ==\n\n\"Linguistics\" and \"[[linguist]]\" may not always be meant to apply as broadly as above. In some contexts, the best [[definition]]s may be \"what is studied in a typical university\'s department of linguistics\", and \"one who is a [[professor]] in such a department.\" Linguistics in this narrow sense usually does not refer to learning to speak foreign languages (except insofar as this helps to craft formal models of language.) It does not include [[literary analysis]]. Only sometimes does it include study of things such as [[metaphor]]. It probably does not apply to those engaged in such prescriptive efforts as found in Strunk and White\'s \'\'The Elements of Style\'\'; \"linguists\" usually seek to study what people do, not what they \'\'should\'\' do. One could probably argue for a long while about who is and who is not a \"linguist\".\n\n== See also ==\n* [[list of linguists]]\n* [[history of linguistics]]\n* [[linguistics basic topics]], a page designed to organize information about linguistics on Wikipedia\n* [[list of linguistic topics]]\n* [[philology]], the study of [[ancient text]]s and languages. \n* [[structuralism]]\n\n== References ==\n* [[Geoffrey Sampson]]: \'\'\"Schools of Linguistics.\"\'\', Hutchinson, London (1980), ISBN 0804710848 \n* Rymer, p. 48, quoted in Fauconnier and Turner, p. 353)\n* [[Gilles Fauconnier]] and [[Mark Turner]] (2002). \'\'The Way We Think: Conceptual Blending and the Mind\'s Hidden Complexities\'\'. Basic Books.\n* Rymer, Russ (1992). \"Annals of Science: A Silent Childhood-I\". \'\'New Yorker\'\', April 13.\n* [[Steven Pinker]], [[The Language Instinct]]\n\n== External links ==\n* [http://www.canoo.com/wmtrans/home/index.html Multilingual Morphology Software]\n* [http://www.englishpage.com/grammar/ Grammar Book]\n* [http://www.arcs.ac.at/dissdb/rn036488 Automated word analysis for the German language]\n* [http://www.sfs.nphil.uni-tuebingen.de/linguist/issues/6/6-1586.html Syllabification algorithm]\n* [http://www.tu-chemnitz.de/global-text/short-docs/html2ps.html#hyph The hyphenation block]\n\n[[ar:علم اللغة]]\n[[bg:Езикознание]]\n[[ca:Lingüística]]\n[[cs:Lingvistika]]\n[[cy:Ieithyddiaeth]]\n[[da:Lingvistik]]\n[[de:Sprachwissenschaft]]\n[[es:Lingüística]]\n[[eo:Lingvistiko]]\n[[fr:Linguistique]]\n[[ko:언어학]]\n[[ia:Linguistica]]\n[[it:Linguistica]]\n[[he:בלשנות]]\n[[sw:Maarifa_Ya_Lugha]]\n[[la:Linguistica]]\n[[nah:Tlahtomachiliztli]]\n[[nl:Taalkunde]]\n[[ja:言語学]]\n[[pl:Lingwistyka]]\n[[pt:Lingüística]]\n[[ro:Lingvistică]]\n[[sl:jezikoslovje]]\n[[sr:лингвистика]]\n[[fi:Kielitiede]]\n[[sv:Lingvistik]]\n[[ur:%D9%84%D8%B3%D8%A7%D9%86%D9%8A%D8%A7%D8%AA]]\n[[zh:语言学]]','',13,'Budhi','20040725032406','',0,0,0,0,0.445948707613,'20041226000117','79959274967593'); INSERT INTO cur VALUES (1065,0,'Tatamba',':\'\'See [[drug]]s, [[medication]], and [[pharmacology]] for substances that treat patients. This article is about medical practice.\'\'\n\n\'\'\'Tatamba\'\'\' mangrupakeun cabang tina elmu kasehatan nu musatkeun perhatian kana \"penyembuhan\" jeung perawatan [[health]] sarta [[wellness]]. Broadly, it is the practical [[science]] of preventing and curing [[diseases]]. However, \'\'medicine\'\' often refers more specifically to matters dealt with by [[physician]]s and [[surgery|surgeons]]. \n\nMedicine is both an area of knowledge (a [[science]]), and the application of that knowledge (the medical profession). The various specialized branches of the science of medicine correspond to equally specialized medical professions dealing with particular organs or diseases. The [[science]] of medicine is the body of knowledge about body systems and diseases, while the [[profession]] of medicine refers to the social structure of the group of people formally trained to apply that knowledge to treat disease.\n\nThere are traditional and schools of healing which are usually not considered to be part of (Western) medicine in a strict sense (see [[health science]] for an overview). The most highly developed systems of medicine outside of the Western or [[Hippocrates|Hippocratic]] tradition are the [[Ayurvedic medicine|Ayurvedic school]] (of [[India]]) and [[traditional Chinese medicine]]. The remainder of this article focuses on modern (Western) medicine.\n\n==History of medicine==\n\'\'See the main articles [[History of medicine]] and [[Timeline of medicine and medical technology]]\'\'\n\nMedicine as it is practiced now is rooted in various traditions, but developed mainly in the late [[18th century|18th]] and early [[19th century]] in [[Germany]] ([[Rudolf Virchow]]) and [[France]] ([[Jean-Martin Charcot]] and others). The new, \"scientific\" medicine replaced more traditional views based on the \"[[Four humours]]\". The development of clinical medicine shifted to the [[United Kingdom]] and the [[United States|USA]] during the early [[1900s]] ([[William Osler|Sir William Osler]], [[Harvey Cushing]]).\n\n[[Evidence-based medicine]] is the recent movement to link the practice and the science of medicine more closely through the use of the [[scientific method]] and modern [[information science]].\n\n[[Genomics]] is already having a large influence on medical practice, as most [[monogenic]] [[genetic disorder]]s have now been linked to causative [[gene]]s, and [[molecular biology|molecular biological]] techniques are influencing medical decision-making.\n\n== Medical sciences and health professions ==\nThe delivery of modern health care depends, not just on medical practitioners, but on an expanding group of highly trained [[profession|professionals]] coming together as an [[interdisciplinary team]]. A full list is given on the [[health profession]] page. Some examples include: [[nurse|nurses]], laboratory scientists, [[pharmacy|pharmacists]], [[physiotherapy|physiotherapists]], [[speech therapy|speech therapists]], [[occupational therapy|occupational therapists]], [[nutritionist|dieteticians]] and [[bioengineering|bioengineers]].\n\nThe scope and sciences underpinning human medicine overlap many other fields. [[Dentistry]] and [[clinical psychology|psychology]], while separate disciplines from medicine, are sometimes also considered medical fields. [[Physician assistant]]s, [[nurse practitioner]]s and [[midwives]] treat patients and prescribe medication in many legal jurisdictions. [[Veterinary medicine]] applies similar techniques to the care of animals.\n\nMedical doctors have many specializations and subspecializations which are listed below.\n\n=== Basic, supplementary, and related sciences ===\n*\'\'[[Anatomy]]\'\' is the study of the physical structure of organisms. In contrast to \'\'macroscopic\'\' or \'\'gross anatomy\'\', \'\'cytology\'\' and \'\'histology\'\' are concerned with microscopic structures.\n*\'\'[[Biochemistry]]\'\' is the study of the chemistry taking place in living organisms, especially the structure and function of their chemical components.\n*\'\'[[Bioethics]]\'\' is a field of study which concerns the relationship between biology, science, medicine and ethics, philosophy and theology.\n*\'\'[[Biostatistics]]\'\' is the application of statistics to biological fields in the broadest sense. A knowledge of biostatistics is essential in the planning, evaluation, and interpretation of medical research. It is also fundamental to [[epidemiology]] and evidence-based medicine.\n*\'\'[[Cytology]]\'\' is the microscopic study of individual [[cell (biology)|cells]].\n*\'\'[[Embryology]]\'\' is the study of the early development of organisms.\n*\'\'[[Epidemiology]]\'\' is the study of the demographics of disease processes, and includes, but is not limited to, the study of epidemics.\n*\'\'[[Genetics]]\'\' is the study of genes, and their role in [[biological inheritance]].\n*\'\'[[Histology]]\'\' is the study of the structures of [[biological tissue]]s by light microscopy, electron microscopy and histochemistry.\n*\'\'[[Immunology]]\'\' is the study of the [[immune system]], which includes the innate and adaptive immune system in human, for example. \n*\'\'[[Microbiology]]\'\' is the study of microorganisms, including protozoa, bacteria, fungi, and viruses.\n*\'\'[[Neuroscience]]\'\' is a comprehensive term for those disciplines of science that are related to the study of the nervous system. A main focus of neuroscience is the biology and physiology of the human brain.\n*\'\'[[Pathology]]\'\' is the study of disease - the causes, course, progression and resolution thereof.\n*\'\'[[Pharmacology]]\'\' is the study of [[drug]]s and their actions.\n*\'\'[[Physiology]]\'\' is the study of the normal functioning of the body and the underlying regulatory mechanisms.\n*\'\'[[Toxicology]]\'\' is the study of hazardous effects of drugs and [[poison]]s.\n\n===Diagnostic and imaging specialties===\n*\'\'[[Clinical laboratory sciences]]\'\' are the clinical diagnostic services which apply laboratory techniques to [[diagnosis]] and management of patients. In the United States these services are supervised by a Pathologist. The personnel that work in these departments are technically trained staff, each of whom usually hold a [[medical technology]] degree, who actually perform the tests, assays, and procedures needed for providing the specific services.\n**\'\'[[Transfusion medicine]]\'\' is concerned with the transfusion of blood and blood component, including the maintenance of a \"\'\'[[blood bank]]\'\'\".\n**\'\'[[Cellular pathology]]\'\' is concerned with diagnosis using samples from patients taken as tissues and cells using [[histology]] and [[cytology]].\n**\'\'[[Chemical pathology|Clinical chemistry]]\'\' is concerned with diagnosis by making biochemical analysis of blood, body fluids and tissues.\n**\'\'[[Hematology]]\'\' is concerned with diagnosis by looking at changes in the cellular composition of the [[blood]] and [[bone marrow]] as well as the [[coagulation system]] in the blood.\n**\'\'[[Clinical microbiology]]\'\' is concerned with the \'\'[[in vitro]]\'\' diagnosis of diseases caused by [[bacteria]], [[viruses]], [[fungi]], and [[parasites]]. \n**\'\'[[Clinical immunology]]\'\' is concerned with disorders of the [[immune system]] and related body defenses. It also deals with diagnosis of [[allergy]].\n*\'\'[[Radiology]]\'\' is concerned with imaging of the human body, e.g. by x-ray, x-ray [[computed tomography]], [[ultrasonography]], and [[nuclear magnetic resonance]] [[tomography]].\n**\'\'[[Interventional radiology]]\'\' is concerned with using imaging of the human body, usually from CT, ultrasound, or fluoroscopy, to do [[biopsy|biopsies]], place certain tubes, and perform intravascular procedures.\n**\'\'[[Nuclear Medicine]]\'\' uses [[radioactive]] substances for \'\'[[in vivo]]\'\' and \'\'[[in vitro]]\'\' diagnosis using either imaging of the location of radioactive substances placed into a patient, or using \'\'in vitro\'\' diagnostic tests utilizing radioactive substances.\n\n===Disciplines of clinical medicine===\n*\'\'[[Anesthesiology]]\'\' ([[American English|AE]]), \'\'Anaesthesia\'\' ([[British English|BE]]), is the clinical discipline concerned with providing [[anesthesia]]. [[Pain medicine]] is often practiced by specialised anesthesiologists.\n*\'\'[[Dermatology]]\'\' is concerned with the skin and its diseases.\n*\'\'[[Emergency medicine]]\'\' is concerned with the diagnosis and treatment of acute or life-threatening conditions, including trauma, surgical, medical, pediatric, and psychiatric emergencies.\n*\'\'[[General practice]]\'\' or \'\'family medicine\'\' or \'\'primary care\'\' is, in many countries, the first port-of-call for patients with non-emergency medical problems. Family doctors are usually able to treat over 90% of all complaints without referring to specialists.\n*\'\'[[Intensive care medicine]]\'\' is concerned with the therapy of patients with serious and life-threatening disease or injury. Intensive care medicine employs invasive diagnostic techniques and (temporary) replacement of organ functions by technical means.\n*\'\'[[Internal medicine]]\'\' is concerned with diseases of inner organs and systemic dieseases of adults, i.e. such that affect the body as a whole. There are several subdisciplines of internal medicine:\n**\'\'[[Cardiology]]\'\' is concerned with the heart and cardiovascular system and their diseases.\n**\'\'[[Clinical pharmacology]]\'\' is concerned with how systems of therapeutics interact with patients.\n**\'\'[[Gastroenterology]]\'\' is concerned with the organs of digestion. \n**\'\'[[Endocrinology]]\'\' is concerned with the endocrine system, i.e. endocrine glands and hormones.\n**\'\'[[Hematology]]\'\' (or \'\'haematology\'\') is concerned with the blood and its diseases.\n**\'\'[[Infectious disease]]s\'\' is concerned with the study, diagnosis and treatment of diseases caused by biological agents.\n**\'\'[[Nephrology]]\'\' is concerned with diseases of the kidneys.\n**\'\'[[Oncology]]\'\' is devoted to the study, diagnosis and treatment of [[cancer]] and other malignant diseases.\n**\'\'[[Pulmonology]]\'\' (or \'\'chest medicine\'\', \'\'respiratory medicine\'\' or \'\'lung medicine\'\') is concerned with diseases of the lungs and the respiratory system.\n**\'\'[[Rheumatology]]\'\' is devoted to the diagnosis and treatment of inflammatory diseases of the joints and other organ systems.\n*\'\'[[Neurology]]\'\' is concerned with the diagnosis and treatment of [[nervous system]] diseases.\n*\'\'[[Obstetrics]] and [[gynecology]]\'\' are concerned respectively with childbirth and the female reproductive and associated organs. [[Reproductive medicine]] and [[fertility medicine]] is generally practiced by gynecological specialists.\n*\'\'[[Palliative care]]\'\' is a relatively modern branch of clinical medicine that deals with pain and symptom relief and emotional support in patients with [[terminal]] disease ([[cancer]], [[heart failure]]).\n*\'\'[[Pediatrics]]\'\' (or \'\'paediatrics\'\') is devoted to the care of children, and adolescents. Like internal medicine, there are many pediatric supspecialities for specific age ranges, organ systems, disease classes and sites of care delivery. Most subspecialities of adult medicine have a pediatric equivalent such as [[pediatric cardiology]], [[pediatric endocrinology]], [[pediatric gastroenterology]], [[pediatric hematology]], and [[pediatric oncology]].\n*\'\'[[Physical medicine and rehabilitation]]\'\' (or \'\'physiatry\'\') is concerned with functional improvement after injury, illness, or congenital abnormality.\n*\'\'[[Preventive medicine]]\'\'\n**[[Community health care]] or [[public health]]\n**[[Occupational medicine]]\n*\'\'[[Psychiatry]]\'\' is a branch of medicine that studies and treats mental disorders. Related non-medical fields are [[psychotherapy]] and [[clinical psychology]].\n*\'\'[[Radiation therapy]]\'\' is concerned with the therapeutic use of ionizing radiation and high energy elementary particle beams in patient treatment.\n*\'\'Surgical specialties\'\' - there are many medical disciplines that employ operative treatment. Some of these are highly specialized and are often not considered subdisciplines of surgery, although their naming might suggest so.\n**\'\'[[General surgery]]\'\' is the specialty of surgery of the skin, locomotor system, and abdominal organs. In the past, it was deemed the pre-requisite training prior to progression to other sub-specialty training, but lately has evolved into its own sub-specialty.\n**\'\'[[Cardiovascular surgery]]\'\' is the surgical specialty that is concerned with the [[heart]] and major blood vessels of the chest.\n**\'\'[[Neurosurgery]]\'\' is concerned with the operative treatment of diseases of the nervous system.\n**\'\'[[Oromaxillofacial surgery]]\'\' (technically a subspeciality of [[dentistry]])\n**\'\'[[Ophthalmology]]\'\' deals with the diseases of the eye and their treatment.\n**\'\'[[Orthopedic surgery]]\'\', surgery of the locomotor system, is generally practiced together with [[trauma surgery]] and/or [[traumatology]].\n**\'\'[[Otolaryngology]]\'\' (or \'\'otorhinolaryngology\'\' or \'\'ENT\'\'/ear-nose-throat) is concerned with treatment of ear, nose and throat disorders.\n**\'\'[[Pediatric surgery]]\'\'\n**\'\'[[Plastic surgery]]\'\' includes aesthetic surgery (operations that are done for other than medical purposes) as well as reconstructive surgery (operations to restore function and/or appearance after traumatic or operative mutilation).\n**\'\'[[Surgical Oncology]]\'\' is concerned with ablative and palliative surgical approaches to [[cancer]] treatment\n**\'\'[[Urology]]\'\' focuses on the urinary tracts of males and females, and on the male reproductive system. It is often practiced together with [[andrology]] (\"men\'s health\").\n**\'\'[[Vascular surgery]]\'\' is surgery of the blood vessels, usually outside of the chest.\n\n== Interdisciplinary medical fields ==\nInterdisciplinary sub-specialties of medicine are:\n*\'\'[[Aerospace medicine]]\'\' deals with medical problems related to flying and [[space travel]].\n*\'\'[[Diving medicine]]\'\' (or \"hyperbaric medicine\") is the prevention and treatment of diving-related problems.\n*\'\'[[Forensic medicine]]\'\' deals with medical questions in [[legal]] context, such as determination of the time and cause of death.\n*\'\'[[Medical informatics]]\'\' and \'\'[[medical computer science]]\'\' are relatively recent fields that deal with the application of [[computer]]s and [[information technology]] to medicine.\n*\'\'[[Nosology]]\'\' is the classification of diseases for various purposes.\n\n==Settings where medical care is delivered==\n\'\'See also [[clinic]], [[hospital]], and [[hospice]]\'\'\n\nMedicine is a diverse field and the provision of medical care is therefore provided in a variety of locations. In addition to inpatient hospital settings, medical services are often provided in locations such as clinics, emergency departments, endoscopy departments, outpatients department, operating theaters, and birth suites. Modern medical care also depends on information - still delivered in many health care settings on paper records, but increasingly nowadays by electronic means.\n\n== Teaching of medicine ==\n\'\'See also the main articles [[Medical doctor]] ([[British English|BE]]) and [[Physician]] ([[American English|AE]])\'\'\n\nMedical training is involves several years of university study followed by several more years of residential practice at a hospital. Entry to a medical degree in some countries (such as the [[United States]]) requires the completion of another degree first, while in other countries (such as the [[United Kingdom]]) medical training can be commenced as an undergraduate degree immediately after [[secondary education]]. Once graduated from medical school most physicians begin their residency training, where skills in a speciality of medicine are learned, supervised by more experienced doctors. The first year of residency is known as the \"[[intern]]\" year. The duration of residency training depends on the speciality.\n\nIn the [[United States|USA]], physician training generally follows the following timeline (with age of completion):\n*Finish high school at 18\n*College/university, 4 years, graduate at 22\n*[[Medical school]], 4 years, graduate at 26 with [[M.D.]] degree\n*Residency (internship usually synonymous with first year of residency), 3 years, finish at 29. Physicians are generally eligible for independent licensure to practice primary care specialties at this point. Many surgical residencies are longer than 3 years.\n*Fellowship, 3 year, finish at 32. Fellowships are taken to become eligible for board certification in subspecialties.\n\nThe name of the medical [[academic degree|degree]] gained at the end varies: some countries (e.g. the US) call it \'Doctor of Medicine\' (abbreviated \'M.D.\'), while others (e.g. [[Australia]], [[Britain]], [[Pakistan]]) call it \"Bachelor of Medicine/Bachelor of Surgery\" ([[French language|French]]: \"\'\'Chirurgie\'\'\"); this is technically a double degree, frequently abbreviated \'M.B.B.S\' or \'M.B.B.Ch.\', dependent on the medical school. In either case graduates of a medical degree may call themselves physician. In the US and some other contries there is a parallel system of medicine called \"[[osteopathy]]\" which awards the degree [[D.O.]] (doctor of osteopathy). In many countries, a doctorate of medicine does not require original research as does, in distinction, a [[PhD]].\n\nA medical graduate can then enter [[general practice]] and become a [[general practitioner]] (or primary care [[internist]] in the [[United States|USA]]); training for these is generally shorter, while specialist training is typically longer.\n\n== Legal restrictions ==\nIn most countries, it is prohibited to practice medicine without a proper degree in that field and doctors must be licensed by a [[medical board]] or some other equivalent organization. This is meant as a safeguard against [[charlatan]]s. These laws are obstacles to those who would want to pretend to training and expertise they have not earned, such as practitioners of [[alternative medicine]] or [[faith healing]].\n\n==Criticism==\nCriticism against medicine has a long history. In the [[Middle Ages]], it was not considered a profession suitable for Christians, as disease was considered Godsent, and interfering with the process a form of [[blasphemy]]. Barber-surgeons generally had a bad reputation that was not to improve until the development of academic surgery as a specialism of medicine, rather than an accessory field.\n\nThrough the course of the twentieth century, doctors naturally focused increasingly on the technology that was enabling them to make dramatic improvements in patients\' health. This resulted in criticism for the loss of compassion and mechanistic, detached treatment. This issue started to reach collective professional consciousness in the 1970s and the profession had begun to respond by the 1980 and 1990s. \n\nPerhaps the most devastating criticism came from [[Ivan Illich]] in his [[1976]] work \'\'Medical Nemesis\'\'. In his view, modern medicine only \'\'medicalises\'\' disease, causing loss of health and [[wellness]], while generally failing to restore health by eliminating disease. The human being thus becomes a lifelong \'\'patient\'\'. Other less radical philosophers have voiced similar views, but none were as virulent as Illich. (Another example can be found in \'\'Technopoly: The Surrender of Culture to Technology\'\' by [[Neil Postman]], [[1992]], which criticises overreliance on technological means in medicine.)\n\nCriticism against modern medicine has led to some improvements in the curricula of medical schools, which now teach students systematically on [[medical ethics]], [[holistic medicine|holistic approaches]] to medicine, the [[biopsychosocial model]] and similar concepts.\n\nThe inability of modern medicine to properly address many common complaints continues to prompt many people to seek support from [[alternative medicine]]. Although a large number of alternative approaches to health await scientific validation, many report improvement of symptoms after obtaining alternative therapies.\n\n==See also==\n*[[Big killer]]s\n*[[Complementary and alternative medicine]]\n*[[Health profession]]\n*[[Healthcare system]]\n*[[Iatrogenesis]]\n*[[List of diseases]]\n*[[List of medical abbreviations]]\n*[[List of medical schools in the U.S.]]\n*[[Medical equipment]]\n*[[Rare disease]]s\n* [[List of publications in medicine|Important publications in medicine]]\n\n==External links==\n*[http://www.nlm.nih.gov The US National Library of Medicine]\n*[http://www.vh.org Virtual Hospital - digital library of health information]\n*[http://cancerweb.ncl.ac.uk/omd/index.html Online Medical Dictionary]\n\n{{msg:Medicine}}\n\n[[Category:Medicine]]\n\n[[af:Geneeskunde]]\n[[bg:Медицина]]\n[[ca:Medicina]] \n[[da:Lægevidenskab]] \n[[de:Medizin]]\n[[et:Meditsiin]]\n[[eo:Medicino]]\n[[es:Medicina]]\n[[fr:Médecine]]\n[[he:רפואה]]\n[[ia:Medicina]]\n[[ja:医学]]\n[[la:Medicina]]\n[[nds:Medizin]]\n[[no:Medisin]]\n[[nl:Geneeskunde]]\n[[pl:Medycyna]] \n[[ru:Медицина]]\n[[simple:Medicine]]\n[[sl:medicina]]\n[[sr:Медицина]]\n[[sv:Medicin]]\n[[zh-cn:医学]] \n[[zh-tw:%E9%86%AB%E5%AD%B8]]\n[[he:רפואה]]','',0,'61.5.60.252','20040902093929','',0,0,0,0,0.065138351203,'20041231121518','79959097906070'); INSERT INTO cur VALUES (1066,0,'Hirup-hurip',':\'\'Alternate uses: see [[Life (disambiguation)]]\'\'\n\n\'\'\'\'\'Life\'\'\'\'\' or \'\'\'\'\'personal life\'\'\'\'\' or \'\'\'\'\'human existence\'\'\'\'\' refers to the idea that each [[individual]] human runs a personal, private [[career]] (including, but not the same as their [[employment]] career), a common notion in modern existence. There are service industries designed to help people improve their personal lives via [[counselling]] or [[life coaching]].\n\nIn the past, before [[abundance]] and [[technology]], a person\'s life consisted almost entirely of [[survival]] of both self and community; food needed to be harvested and shelters needed to be maintained. There was little privacy in a community, and a person was identified by their job.\n\nIn modern times, many people have even come to think of their personal lives as if they are separate from their work. Work and recreation are distinct; one is either on the job or not, and the transition is abrupt. Employees have certain hours they are bound to work, and work during recreational time is rare. Many people think of their personal lives as separate from their work. This may be related to the continuing specialization of jobs and the demand for increased efficiency, both at work and at home. A common phrase demonstrating this is \"Work hard, play hard.\"\n\nA \"life\" as a whole may seem morally \"good\" or \"bad\", and become characterised as such. It (or part of it) may find literary reflection in a [[biography]], an [[autobiography]] or a [[memoir]]. Some outstanding lives merit [[hagiography]] or a [[vita]].\n\nThe career from [[childbirth|birth]] to [[death]] is not always a uniform \"daily life\". Many people separate their overall lives into individual strands: their \"[[intellectual]] lives\", their \"[[employment|work]]ing lives\", their \"[[family]] lives\" and (particularly) their \"[[human sexual behavior|sex lives]]\". The religiously inclined may have \"[[spirituality|spiritual]] lives\" or \"[[religion|religious]] lives\" intertwined with their everyday activities; they may also expect an [[afterlife]] (for some the most important thing). In the interim, those who can afford to pause and to do so may adopt a [[lifestyle]] or assess their [[quality of life]].\n\nSome doubts, however, may assail the would-be life-conductor. Acquaintances may encourage such to \"get a life\" - in the sense of promoting fuller participation in human (especially socially approved) activities - often outside one\'s own personally-defined life. Certain cultures, some defined by [[state]] or [[corporate]] agencies, encourage individuals to submerge themselves in [[collectivism | collective]] wholes: mass movements or [[team]]s - on the sportsfield or in the workplace.\n\n\n*[[human condition]]\n*[[human ecology]]\n*[[Maslow\'s hierarchy of needs]]\n*[[personal life index]]\n*[[physical quality-of-life index]]\n*[[purpose]]\n\n\n*[[human condition test]]\n*[[human condition]]\n*[[human ecology]]\n*[[Maslow\'s hierarchy of needs]]\n*[[personal life index]]\n*[[physical quality-of-life index]]\n*[[purpose]]\n\n\n[[Category:Main page]]\n[[Category:Person]]','',13,'Budhi','20040725032720','',0,0,0,1,0.698763921717,'20040725032720','79959274967279'); INSERT INTO cur VALUES (1067,0,'Psikologi','\'\'\'Psychology\'\'\' is the practice of studying, teaching or applying an understanding of the [[mind]], [[thought]] and [[behaviour]]. It is largely concerned with psychology of humans, although the behaviour and thought of non-human animals is also studied; either as a subject in its own right (see [[animal cognition]]), or more controversially, as a way of gaining an insight into human psychology by means of comparison (see [[comparative psychology]]). \n\nPsychology is conducted both scientifically and non-scientifically. Mainstream psychology is based largely on [[positivism]], using [[quantitative psychological research|quantitative]] studies and the [[scientific method]] to test and disprove [[hypothesis|hypotheses]], often in an [[experiment]]al context. Psychology tends to be eclectic, drawing on scientific knowledge from other fields to help explain and understand behavior. However, not all psychological [[research methods]] are scientific, and some may involve [[qualitative psychological research|qualitative]] or interpretive techniques more allied to the [[humanities]]. Some psychologists, particularly adherents to [[humanistic psychology]], may go as far as completely rejecting a scientific approach. However, mainstream psychology has a bias towards the [[scientific method]], which is reflected in the dominance of [[cognitivism (psychology)|cognitivism]] as the guiding [[theory|theoretical framework]] used by most psychologists to understand thought and behaviour.\n\nPsychology does not necessarily refer to the [[brain]] or [[nervous system]] and can be framed purely in terms of [[phenomenology|phenomenological]] or [[information processing]] theories of mind. Increasingly though, an understanding of brain function is being included in psychological theory and practice, particularly in areas such as [[artificial intelligence]], [[neuropsychology]] and [[cognitive neuroscience]].\n\nPsychology differs from [[sociology]], [[anthropology]], [[economics]], and [[political science]], in part, by studying the behavior of individuals (alone or in groups) rather than the behavior of the groups or aggregates themselves. While psychological questions were asked in antiquity (c.f., [[Aristotle]]\'s \'\'De Memoria et Reminiscentia\'\' or \'\'\"On Memory and Recollection\"\'\'), psychology emerged as a separate discipline only recently. The first person to call himself a \"psychologist\", [[Wilhelm Wundt]], opened the first psychological laboratory in [[1879]].\n\n==History==\n\nThe root of the word psychology (\'\'[[psyche]]\'\') means \"soul\" or \"spirit\" in Greek, and psychology was sometimes considered a study of the soul (in a religious sense of this term), though its emergence as a medical discipline can be seen in [[Thomas Willis]]\' reference to psychology (the \"Doctrine of the Soul\") in terms of brain function, as part of his 1672 anatomical treatise \"De Anima Brutorum\" (\"Two Discourses on the Souls of Brutes\"). \n\nUntil about the end of the [[19th century]], psychology was regarded as a branch of philosophy.\n\nIn [[1879]] [[Wilhelm Wundt]] founded a laboratory at the University in Germany in [[Leipzig]] specifically to focus on general and basic questions concerning behaviour and mental states. [[William James]] later published his [[1890]] book, \'\'[[Principles of Psychology]]\'\' which laid many of the foundations for the sorts of questions which psychologists would focus on for years to come. Crucially, the approach of Wundt and James did not involve [[metaphysics]] or religious explantions of human thought and behaviour, freeing it from the realms of philosophy and theology, and in many people\'s eyes, founding the modern science of psychology.\n\nMeanwhile, [[Sigmund Freud]] had invented and applied a method of [[psychotherapy]] known as [[psychoanalysis]]. Freud\'s understanding of the mind was largely based on interpretive methods and [[introspection]] (a technique also championed by Wundt), but was particularly focused on resolving mental distress and [[psychopathology]]. Freud\'s theories were wildly successful, not least because they aimed to be of practical benefit to individual patients, but also because they tackled subjects such as [[sexuality]] and [[repression]] as general aspects of psychological development. These were largely considered [[taboo]] subjects at the time, and Freud provided a catalyst for them to be openly discussed in polite society. Although it has become fashionable to discredit many of Freud\'s more outlandish theories, his application of psychology to clinical work and his more mainstream work has been massively influential.\n\nPartly as a reaction to the subjective and introspective nature of psychology at the time, [[behaviourism]] began to become popular as a guiding psychological theory. Championed by psychologists such as [[John B. Watson]], [[Edward Thorndike]] and [[B. F. Skinner]] it argued that psychology should be a science of behaviour, not the mind, and rejected the idea of internal mental states such as [[belief]]s, [[desire]]s or goals, believing all behaviour and learning to be a reaction to the environment. In his classic [[1913]] paper \'\'Psychology as the behaviourist views it\'\' Watson argued that psychology \"is a purely objective experimental branch of natural science\", \"introspection forms no essential part of its methods...\" and \"The behaviorist... recognizes no dividing line between man and brute\".\n\nBehaviourism was the dominant model in psychology for much of the early 20th century, largely due to the creation and successful application (not least of which in [[advertising]]) of [[conditioning]] theories as scientific models of human behaviour. \n\nHowever, it became increasingly clear that although behaviourism had made some important discoveries, it was deficient as a guiding theory of human behaviour. [[Noam Chomsky]]\'s review of Skinners book \'\'[[Verbal Behavior]]\'\' (that aimed to explain [[language acquisition]] in a behaviourist framework) is considered one of the major factors in the ending of behaviourism\'s reign. Chomsky demonstrated that language could not purely be learnt from conditioning, as people could produce sentences unique in structure and meaning that couldn\'t possibly of been generated solely through experience of natural language, implying that there must be internal states of mind that behaviourism rejected as illusory. Similarly, work by [[Albert Bandura]] showed that children could [[social learning theory|learn by social observation]], without any change in overt behaviour, and so must be accounted for by internal representations.\n\nThe rise of computer technology also promoted the metaphor of mental function as [[information processing]]. This, combined with a scientific approach to studying the mind, as well as a belief in internal mental states, led to the rise of [[cognitivism (psychology)|cognitivism]] as the dominant model of the mind.\n\nLinks between [[brain]] and [[nervous system]] function were also becoming common, partly due to the experimental work of people like [[Charles Sherrington]] and [[Donald Olding Hebb|Donald Hebb]], and partly due to studies of people with [[brain injury]] (see [[cognitive neuropsychology]]). With the development of technologies for accurately measuring brain function, [[neuropsychology]] and [[cognitive neuroscience]] have become some of the most active areas in contemporary psychology. \n\nWith the increasing involvement of other disciplines (such as [[philosophy]], [[computer science]] and [[neuroscience]]) in the quest to understand the mind, the umbrella discipline of [[cognitive science]] has been created as a means of focusing such efforts in a constructive way.\n\nHowever, not all psychologists have been happy with what they perceive as \'mechanical\' models of the mind and human nature. \n\n[[Carl Jung]], a one-time follower and contemporary of Freud, was instrumental in introducing notions of spirituality into Freudian psychoanalysis (Freud had rejected religion as a mass delusion).\n\n[[Humanistic psychology]] emerged in the 1950s and has continuted as a reaction to [[positivism|positivist]] and scientific approaches to the mind. It stresses a phenomenological view of human experience and seeks to understand human beings and their behavior by conducting [[qualitative psychological research|qualitative research]]. The humanistic approach has its roots in [[existentialism|existentialist]] and [[phenomenology|phenomenological]] philosophy and many humanist psychologists completely reject a scientific approach, arguing that trying to turn human experience into measurements, strips it of all meaning and relevance to lived existence.\n\nSome of the founding theorists behind this school of thought are [[Abraham Maslow]] who formulated a [[Maslow\'s hierarchy of needs|hierarchy of human needs]], [[Carl Rogers]] who created and developed client centered therapy, and [[Fritz Perls]] who helped create and develop [[gestalt therapy]].\n\n==Major nineteenth and twentieth century schools of thought ==\nVarious schools of thought have argued for a particular model to be used as a guiding theory by which all, or the majority, of human behaviour can be explained. The popularity of these has waxed and waned over time. Some psychologists may think of themselves as adherents to a particular school of thought and reject the others, although most consider each as an approach to understanding the mind, and not necessarily as mutually exclusive theories.\n\n* [[behaviorism]] (see also [[radical behaviorism]])\n* [[cognitivism (psychology)|cognitivism]]\n* [[functionalism (sociology)|functionalism]]\n* [[Gestalt psychology]]\n* [[humanistic psychology]] and [[phenomenology]]\n* [[psychoanalysis]]\n* [[structuralism]]\n\n==Modern psychology==\nThe majority of mainstream psychology is based on a framework derived from [[cognitive psychology]], although the popularity of this paradigm does not exclude others, which are often applied as necessary. Alternatively a psychologist may specialise in an area in which cognitive psychology is rarely used.\n\nA psychologist will often attempt to measure or [[psychological testing|test]] different aspects of psychological function, using [[psychometric]] and [[statistics|statistical]] methods, including well known standardised tests as well as those created as the situation requires.\n\nAcademic psychologists may focus purely on research, aiming to further psychological understanding in a particular area, while other psychologists may work in [[applied psychology]] to deploy such knowledge for immediate and practical benefit. However, these approaches are not mutually exclusive and most psychologists will be involved in both researching and applying psychology at some point during their work.\n\nContemporary psychology is a broad church and consists of a diverse set of approaches, subject areas and applications. A comprehensive list is given in the Topics and Divisions sections below. Where an area of interest is considered to need specific training and specialist knowledge (especially in applied areas), psychological societies will typically set up a governing body to manage training requirements. Similarly, requirements may be laid down for university degrees in psychology, so that students acquire an adequate knowledge in a number of areas. While the exact divisions may vary from country to country, the following areas are usually considered as \'core\' subjects or approaches by psychology societies and universities.\n\n===Cognitive psychology===\n[[Cognitive psychology]] is a framework in which to understand the mind more than a subject area, although it has traditionally focused on certain aspects of psychology. [[Perception]], [[learning]], [[problem solving]], [[memory]], [[attention]], [[language]] and [[emotion]] are all well researched areas. Cognitive psychology is based on a school of thought known as [[cognitivism (psychology)|cognitivism]], which argues for an [[information processing]] model of mental function, informed by [[positivism]] and [[experimental psychology]]. Techniques and models from cognitive psychology are widely applied and form the mainstay of psychological theories in many areas of both research and applied psychology.\n\n===Clinical and counselling psychology===\n[[Clinical psychology]] is the application of psychology to the understanding, treatment and assessment of [[psychopathology]], behavioural or mental health issues. It has traditionally been associated with [[counselling]] and [[psychotherapy]], although modern clinical psychology may take an eclectic approach, including a number of therapeutic approaches. Typically, although working with many of the same clients as [[psychiatry|psychiatrists]], clinical psychologists do not prescribe psychiatric drugs. Clinical psychologists largely work within the \'scientist-practictioner model\' where clinical problems are formulated as hypotheses to be tested as information is gathered about the patient and their mental state. Some clinical psychologists may focus on the clinical management of patients with [[brain injury]]. This is known as [[clinical neuropsychology]] and typically involves additional training in [[brain]] function.\n\nIn recent years and particularly in the United States, a major split has been developing between academic research psychologists in universities and some branches of clinical psychology. Many academic psychologists believe that these clinicians use therapies based on discredited theories and unsupported by empirical evidence of their effectiveness. From the other side, these clinicians believe that the academics are ignoring their experience in dealing with actual patients. The disagreement has resulted in the formation of the [[American Psychological Society]] by the research psychologists as a new body distinct from the [[American Psychological Association]].\n\n===Developmental and educational psychology===\nLargely focusing on the development of the human mind through childhood (although development through adulthood is also studied), [[developmental psychology]] seeks to understand how children come to perceive, understand and act within the world. This may focus on intellectual, cognitive, neural, social or moral development and involve a number of unique research methods to engage children in experimental tasks. These tasks often resemble specially designed games and activities which are both enjoyable for the child and scientifically useful. [[Educational psychology]] largely seeks to apply much of this knowledge and understand how learning can best take place in [[education]]al situations. Because of this, the work of child psychologists such as [[Lev Vygotsky]], [[Jean Piaget]] and [[Jerome Bruner]] has been influential in creating [[teaching]] methods and educational practices.\n\n===Forensic psychology===\n[[Forensic psychology]] is concerned with the psychology of [[crime]], [[criminals]] and [[law enforcement]]. A forensic psychologist may be involved in assessment of offenders or interventions to prevent offending behaviour, usually with people who have already come in contact with the [[legal system|legal]] or [[penal system]]. Often this involves working with offenders with mental health problems, or with people who act dangerously or in an antisocial manner (for example, [[psychopathy|psychopaths]]). Criminal profiling is another important role fulfilled by forensic psychologists and typically involves building psychological profiles of unknown or at-large offenders from the known evidence.\n\n===Health psychology===\nWhilst clinical psychology focuses on mental health and neurological illness, [[health psychology]] is concerned with the psychology of a much wider range of health related behaviour. For example, healthy eating, the doctor-patient relationship, a patient\'s understanding of health information and beliefs about illness. Health psychologists may be involved in public health campaigns, examining the impact of illness or health policy on [[quality of life]] or research into the psychological impact of health and social care.\n\n===Industrial and organisational psychology===\nInvolved with the application of psychology to the world of business, commerce and the function of organisations, [[industrial and organisational psychology]] focuses to varying degrees on the psychology of the workforce, customer and consumer, including issues such as the psychology of recruitment, training, appraisal, job satisfaction, [[stress]] at work and [[management]]. Psychologists may also work on product design, interaction with machines or software, [[advertising]], sales and [[marketing]], to aid functionality, safety and appeal.\n\n===Neuropsychology===\n[[Neuropsychology]] is a branch of psychology that aims to understand how the structure and function of the [[brain]] relates to specific psychological processes. Often neuropsychologists are employed as scientists to advance scientific or medical knowledge. [[Cognitive neuropsychology]] is particularly concerned with the understanding of [[brain injury]] in an attempt to work out normal psychological function. [[Clinical neuropsychology]] is the application of neuropsychology for the clinical managment of patients with [[neurocognitive deficit]]s.\n\n===Social psychology===\n[[Social psychology]] aims to understand how the mind makes sense of social situations. For example, this could involve the influence of others on an individual\'s behaviour (e.g. [[Conformity (psychology)|conformity]] or [[persuasion]]), the perception and understanding of social cues, or the formation of [[attitude (psychology)|attitudes]] or [[stereotype]]s about other people. [[Social cognition]] is a common approach and involves a mostly cognitive and scientific approach to understanding social behaviour.\n\n== Topics in psychology ==\nAlthough in principle, psychology aims to explain all aspects of thought and behaviour, some topics have generated particular interest, either due to their perceived importance, their ease of study or popularity. Many of the concepts studied by professional psychology stem from the day-to-day psychology used by most people and learnt through experience. This is known as [[folk psychology]] to distinguish it from psychological knowledge developed through formal study and investigation. The extent to which folk psychology should be used as a basis for understanding human experience is controversial, although theories which are based on everyday notions of the mind have been among some of the most successful.\n\nFor a comprehensive list of psychological topics on wikipedia, please see the [[list of psychological topics]].\n\n* [[addiction]]\n* [[attention]]\n* [[attitude (psychology)|attitude]]\n* [[brain]] and [[nervous system]] function\n* [[brain injury]]\n* [[child development]]\n* [[cognition]]\n* [[communication]]\n* [[conditioning]]\n* [[conformity (psychology)|conformity]]\n* [[consciousness]]\n* [[crime]]\n* [[Heuristic#Psychology|decision making]]\n* [[emotion]]\n* [[ergonomics]]\n* [[executive function]] \n* [[experimental analysis of behavior]]\n* [[face perception]]\n* [[group dynamics]]\n* [[human computer interaction]]\n* [[language]] and [[language acquisition]]\n* [[learning]]\n* [[memory]]\n* [[mental illness]]\n* [[motivation]]\n* [[perception]]\n* [[personality]]\n* [[problem solving]]\n* [[program evaluation]]\n* [[psychological testing]]\n* [[psychopathology]]\n* [[psychopharmacology]]\n* [[psychotherapy]]\n* [[reasoning]] and [[decision making]]\n* [[rehabilitation]]\n* [[reinforcement]]\n* [[psychological research methods|research methods]]\n* [[senses|sensory experience]]\n* [[sexuality]] and [[gender role]]\n* [[social cognition]]\n* [[social influence]]\n* [[vision]]\n\n== Divisions and approaches in psychology ==\nDifferent disciplines in psychology typically signify both a set of practices and an area of interest. The divisions are largely arbitrary and overlapping (although they may have been formalised into areas of interest by psychological societies or regulatory bodies) and most psychologists will use methods from each area as appropriate, even if they mostly focus on one area of interest in their work.\n\n* [[abnormal psychology]]\n* [[analytical psychology]]\n* [[applied psychology]]\n* [[behavioral medicine]]\n* [[behavioral psychology]]\n* [[biobehavioral health]]\n* [[biological psychology]]\n* [[cognitive neuropsychology]]\n* [[cognitive psychology]]\n* [[cognitive neuroscience]]\n* [[community psychology]]\n* [[comparative psychology]]\n* [[clinical psychology]] \n* [[counselling psychology]]\n* [[critical psychology]]\n* [[developmental psychology]]\n* [[educational psychology]]\n* [[emotional clearing]]\n* [[evolutionary psychology]]\n* [[experimental psychology]]\n* [[forensic psychology]]\n* [[health psychology]]\n* [[humanistic psychology]]\n* [[individual differences psychology]]\n* [[industrial and organizational psychology]]\n* [[medicinal psychology]]\n* [[medical psychology]]\n* [[neuropsychology]]\n* [[personality psychology]]\n* [[physiological psychology]]\n* [[popular psychology]], [[self-help]], and [[alternative therapy]]\n* [[positive psychology]]\n* [[pre- and perinatal psychology]]\n* [[problem solving]]\n* [[psychoanalysis]]\n* [[psychohistory]]\n* [[psychometrics]]\n* [[psychonomics]]\n* [[psychophysics]]\n* [[psychophysiology]]\n* [[psychotherapy]] a branch of [[psychiatry]] as well.\n* [[social psychology]]\n* [[traffic psychology]]\n* [[transpersonal psychology]]\n\n== Some related disciplines ==\n* [[artificial consciousness]] (see also [[simulated consciousness]])\n* [[cognitive science]]\n* [[complex system]]s\n* [[computer science]] and [[captology]]\n* [[economics]] and [[marketing]]\n* [[ethology]]\n* [[game theory]]\n* [[history]]\n* [[hypnotherapy]]\n* [[linguistics]] and especially [[psycholinguistics]]\n* [[literature]], [[literary theory]], and [[critical theory]]\n* [[neuroeconomics]]\n* [[neuro-linguistic programming]]\n* [[neuroscience]]\n* [[parapsychology]]\n* [[philosophy of mind]]\n* [[philosophy of psychology]]\n* [[psychometrics]]\n* [[psychophysics]]\n* [[simplicity theory]]\n* [[sociology]]\n* [[socionics]]\n* [[systems theory]]\n\n==Famous psychologists==\nSee [[List of psychologists]] for a full list of famous and influential psychologists.\n\n== External links ==\n\n===Psychology Resources===\n* [http://www.vanguard.edu/faculty/ddegelman/amoebaweb/ AmoebaWeb Psychology Resources]\n* [http://www.apa.org/monitor/dec99/toc.html A Century of Psychology (APA)]\n* [http://psychclassics.yorku.ca Classics in the History of Psychology]\n* [http://allpsych.com/dictionary/ Dictionary of Psychology]\n* [http://www.psychology.org/ Encyclopedia of Psychology]\n* [[New Scientist]] news on the [http://www.newscientist.com/hottopics/humannature/sectindex.jsp?sub=The%20mind mind] and [http://www.newscientist.com/hottopics/humannature/sectindex.jsp?sub=The%20brain brain]\n* [http://www.sonoma.edu/psychology/psychart.html Pictures of famous psychologists]\n* [http://www.conferencealerts.com/psychology.htm Psychology Conferences]\n* [http://www.perfectionnement.info/lo/agenda.php?i_pays=0&i_date=0&keywords=congr Psychology Congresses]\n* [http://www.sciencedaily.com/news/mind_brain.htm ScienceDaily Mind and Brain news]\n* [[List of publications in psychology| Important publications in psychology]]\n\n===Psychology Societies===\n* [http://www.apa.org American Psychological Association]\n* [http://www.psychologicalscience.org/ American Psychological Society]\n* [http://www.bps.org.uk British Psychological Society]\n* [http://www.cpa.ca Canadian Psychological Association]\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\n\n\n[[category:Psychology]]\n[[category:Person]]\n[[category:Dewey Decimal 100]]\n\n[[af:Sielkunde]]\n[[ar:علم نفس]]\n[[ast:Psicoloxía]]\n[[bg:Психология]]\n[[bs:Psihologija]]\n[[ca:Psicologia]]\n[[cs:Psychologie]]\n[[cy:Seicoleg]]\n[[da:Psykologi]]\n[[de:Psychologie]]\n[[el:Ψυχολογία]]\n[[en:Psychology]]\n[[eo:Psikologio]]\n[[es:Psicología]]\n[[et:Psühholoogia]]\n[[fa:روان‌شناسی]]\n[[fi:Psykologia]]\n[[fr:Psychologie]]\n[[gl:Psicoloxía]]\n[[he:פסיכולוגיה]]\n[[hi:मानस शास्त्र]]\n[[hr:Psihologija]]\n[[ia:Psychologia]]\n[[io:Psikologio]]\n[[is:Sálfræði]]\n[[it:Psicologia]]\n[[ja:心理学]]\n[[ko:심리학]]\n[[ku:Psîkolojî]]\n[[li:Psychologie]]\n[[lv:Psiholoģija]]\n[[ms:Psikologi]]\n[[nl:Psychologie]]\n[[no:Psykologi]]\n[[pl:Psychologia]]\n[[pt:Psicologia]]\n[[ro:Psihologie]]\n[[ru:Психология]]\n[[simple:Psychology]]\n[[sl:Psihologija]]\n[[sr:Психологија]]\n[[sv:Psykologi]]\n[[tr:Psikoloji]]\n[[uk:Психологія]]\n[[zh:心理学]]','warnfile Adding:li,ku,bs,is Modifying:lv',42,'Shizhao','20050303144001','',0,0,1,0,0.466901861349,'20050303144001','79949696855998'); INSERT INTO cur VALUES (1068,0,'Komunikasi','\'\'\'Komunikasi\'\'\' nyaeta [[process|proses]] tina [[exchange|parobahan]] [[information|inpormasi]] umumna ngaliwatan [[system|sistim]] tina [[symbol|simbol]] nu geus umum. \"[[Communications|Elmu Komunikasi]]\" nyaeta [[academic discipline|élmu akademik]] nu ngajarkeun ngeunaan komunikasi. \n\n==Bentuk Komunikasi==\n*[[Animal communication]]s\n*[[Interpersonal communication]]s\n**[[Marketing]]\n**[[Propaganda]]\n**[[Public affairs]]\n**[[Public relations]]\n*[[Intrapersonal communication]]s\n*[[Nonverbal communication]]s\n*[[Speech communication]]s\n*[[Telecommunication]]s\n**[[Computer-mediated communication]]s\n\n==Bentuk jeung komponen komunikasi [[manusa]] ==\n\'\'\'Humans\'\'\' communicate in order to share [[knowledge]] and [[experience]]s. Common forms of human communication include [[sign language]], [[speech|speaking]], [[writing]], [[gesture]]s, and [[broadcasting]]. Communication can be [[interaction|interactive]], [[transactive communication|transactive]], [[intentional communication|intentional]], or [[unintentional communication|unintentional]]; it can also be [[verbal communication|verbal]] or [[nonverbal communication|nonverbal]]. In addition, communication can be [[intrapersonal communication|intrapersonal]] or [[interpersonal communication|interpersonal]].\n\n== Téhnologi Komunikasi ==\nIn [[telecommunications]], the first transatlantic two-way \'\'\'[[radio]]\'\'\' broadcast occurred on [[July 25]]th [[1920]].\n
(see also: [[semaphore]], [[telegraphy]], [[telephony]], [[radioteletype]], [[global telephone network]] - also known as the Public Switched Telephone Network, [[communications satellite]]s, [[ethernet]], and the [[internet]] - a network of [[computer network]]s). \n\nAs the technology evolved, [[communication protocol]] also had to evolve; for example, [[Thomas Edison]] had to discover that \'\'hello\'\' was the least ambiguous greeting by voice over a distance; previous greetings such as \'\'hail\'\' tended to be lost or garbled in the transmission.\n\nAs regards human communication these diverse fields can be divided into those which cultivate a thoughtful exchange between a small number of people ([[debate]], [[talk radio]], [[e-mail]], [[personal letter]]s) on the one hand; and those which disseminate broadly a simple message ([[Public relations]], [[television]], [[cinema]]).\n\nOur indebtedness to the [[Roman]]s in the field of communication does not end with the Latin root \"communicare\". They devised what might be described as the first real mail or [[postal system]] in order to centralize control of the [[empire]] from [[Rome]]. This allowed Rome to gather knowledge about events in its many widespread provinces.\n\nAs the Romans well knew, communication is as much about taking in towards the centre as it is about putting out towards the extremes. Thus [[peace]] is a side-effect of communication, starting, for example, when the [[August 30]]th [[1963]] \'\'communication hotline\'\' between U.S. and Soviet leaders went into operation.\n\nIn [[virtual management]] an important issue is [[computer-mediated communication]].\n\nThe view people take toward communication is changing, as new technologies change the way they communicate and organize. In fact, it is the changing technology of communication that tends to make the most frequent and widespread changes in a society. The latest [[trend]] in communication, decentralized [[personal networking]], is termed [[smartmob]]bing.\n\n==Communication barriers==\n[[Anxiety]] associated with communication is known as \'\'\'communication apprehension\'\'\'. Such anxiety tends to be influenced by one\'s [[self-concept]]. Besides apprehension, communication can be impaired via [[bypassing]], [[indiscrimination]], and [[polarization (psychology)|polarization]]. Failing to share a common [[language]] is also a important barrier in many parts of the world.\n\n== References ==\n[1] Dance, Frank. \"The \'concept\' of communication. \'\'Journal of Communication, 20\'\', 201-210 (1970).\n\n==Jejer nu patali==\n* [[Tiori informasi]]\n* [[jurnalisme]]\n* [[linguistik]]\n* [[postal service]]\n* [[mass media]]\n* [[rhetorical criticism]]\n* [[social software]]\n* [[neuro-linguistic programming]]\n* [[communication basic topics]]\n* [[vocalization]]\n* [[media studies]]\n\n==Tumbu Kaluar==\n* [http://www.hains.net/communication/studying.html Studying Communication: An introduction to the field, by R.C. Hains]\n* [http://www.uiowa.edu/~commstud/resources/ University of Iowa - Communication Studies Resources]\n* [http://www.unm.edu/~emmons/communications.html UNM General Library Communication Studies]\n\n\n\n\n[[ca:Comunicació]] [[da:Kommunikation]] [[de:Kommunikation]] [[el:Επικοινωνία]] [[en:Communication]] [[es:Comunicación]] [[eo:Komunikadteĥnikoj]] [[fr:Communication]] [[he:תקשורת]] [[nl:Communicatie]] [[ja:通信]]\n[[no:Kommunikasjon]] [[simple:Communication]] [[zh:通信]] \n[[Category:Komunikasi]]','',13,'Budhi','20041224222012','',0,0,1,0,0.947946997335,'20041231124655','79958775777987'); INSERT INTO cur VALUES (1069,0,'Ékonomi','\'\'\'Ekonomi\'\'\' nyaéta [[élmu sosial]] nu ngulik produksi, distribusi, jeung konsumsi barang jeung jasa, in terms of the trade offs between competing alternatives as observed through measurable quantities such as input, price and output. The field of economics comprises a number of potentially irreconcilable theories about systems of production and distribution, but as a general rule economists study human behavior and welfare as a relationship between ends socially required and scarce means which have alternative uses ([[Lionel Robbins]], [[1935]]). \n\n[[Image:Market-Chichicastenango.jpg|thumb|250px|The bazaar in action: [[Chichicastenango]] Market, Guatemala]]\n\nUnderstanding choices by individuals and groups is central in economics. With scarcity, choosing one alternative implies forgoing another alternative; economists refer to the best alternative forgone by taking another choice as the [[opportunity cost]]. For instance, learning one skill implies time not spent learning another. In a market setting, the currently dominant theory is that scarcity is most often quantified by [[price]] relationships.\n\nEconomists believe that incentives and desires together play an important role in shaping [[decision making]]. Concepts from the [[utilitarianism|Utilitarian]] school of philosophy are used as analytical concepts within economics, though economists appreciate that society may not adopt utilitarian objectives. One example of this is the idea of a [[utility function]], which is assumed to be the means by which individual economic actors decide what makes them \"happy\" and what decisions they make in pursuit of that happiness.\n\nThe subject is said to be [[positive (social sciences)|positive]] when it attempts to explain the consequences of different choices given a set of assumptions and [[normative]] when it prescribes a certain route of action. \n\nAspects receiving particular attention in economics are resource allocation, production, distribution or [[trade]], and [[competition]].\n\nThe word \'\'economy\'\' comes from the Greek \'\'oikos-\'\' for \"house\" and \'\'nomos\'\' for \"laws\" or \"norms\". Originally, the term oikonomikos was used for different contexts: the house, a town, a city (the \"polis\" in Greek).\n\nThis last use originated the term \'\'[[political economy]]\'\', while the term \'\'economics\'\' was coined around [[1870]] and popularized by [[Alfred Marshall]]. Note that the word \'\'economist\'\' predated \'\'economics\'\'.\n\nAfter this \"change\", the term \"political economy\" has been used to denote the \"classical economy\" of the 19th century, with [[Adam Smith]], [[David Ricardo]] and [[Karl Marx]] as its main thinkers, in recent years the term has also been used to describe the study of production systems which are not viewed through the lens of price, but through descriptions of the network of relationships and requirements involved in a particular economy. There are also those who use the terms economics and political economy as interchangeable.\n\n== Widang-widang ulikan ékonomi ==\n\nÉkonomi biasana dibagi jadi dua cabang utama:\n\n* [[Microeconomics]], which examines the economic behaviour of individual actors such as firms, households, and individuals, with a view to understand decision making in the face of scarcity and the allocation consequences of these decisions.\n* [[Macroeconomics]], which examines an economy as a whole with a view to understanding the interaction between economic aggregates such as [[measures of national income and output|national income]], [[employment]] and [[inflation]]. Note that this is different from [[general equilibrium]] theory, which deals with aggregate problems from a strictly constructed microeconomic viewpoint.\n\nAttempts to join these two branches or to refute the distinction between them have been important motivators in much of recent economic thought, especially in the late [[1970s]] and early [[1980s]]. Today, the consensus view is arguably that good macroeconomics has solid microeconomic foundations; i.e. its premises have theoretical and evidential support in microeconomics.\n\nEconomics can also be divided into numerious subdisciplines that do not always fit neatly into the macro/micro categorization. Some of these subdisciplines include: international economics, labour economics, welfare economics, resource economics, environmental economics, managerial economics, financial economics, urban economics, and spatial economics. \n\nThere are also methodologies used by economists whose underlying theories are important. \n* The most significant example may be [[econometrics]], which applies statistical techniques to the study of [[economic data]]. Computational economics relies on mathematical methods, including econometrics. \n* Another trend which is more recent, and closer to microeconomics, is to use [[social psychology]] concepts ([[behavioral economics]]) and methods ([[experimental economics]])\n\nOther subdivisions are possible. [[Finance]] has traditionally been considered a part of economics – as its body of results emerges naturally from microeconomics – but has today effectively established itself as a separate, though closely related, discipline.\n\nThere has been an increasing trend for ideas and methods from economics to be applied in wider contexts. Since economics analysis focuses on decision making, it can be applied (with varying degrees of success) to any field where people are faced with alternatives – [[education]], [[marriage]], [[health]], etc. [[Public Choice Theory]] studies how economic analysis can apply to those fields traditionally considered outside of economics. The areas of investigation in Economics therefore overlap with other social sciences, including [[political science]] and [[sociology]]. See [[political economy]] for the study of economics in the context of political science. The most prevalent political economy is loosely called [[capitalism]].\n\n== Economic assumptions ==\n\n[[Image:Supply-demand-P.png|thumb|right|[[Supply and demand]] when the demand curve shifts]]\n\nMainstream economics does not assume [[a priori]] that markets are preferable to other forms of social organization. In fact, much analysis is devoted to cases where so-called [[market failure]]s lead to resource allocation that is suboptimal by some standard. In such cases, economists may attempt to find policies that will avoid waste; directly by government control, indirectly by regulation that induces market participants to act in a manner consistent with optimal welfare, or by creating \'missing\' markets to enable efficient trading where none had previously existed. This is studied in the field of [[collective action]].\n\nMainstream economics centers around the relationship between [[supply and demand]]. Supply can be said to be the amount of a given [[commodity]] available at a give price, and demand can be said to be the amount of a commodity that would be purchased at a given price. Mainstream economic theory centers on creating a series of supply and demand relationships, describing them as equations, and then adjusting for factors which produce \"stickiness\" between supply and demand. Analysis is then done to see what \"trade offs\" are made in the \"market\" which is the negotiation between sellers and buyers. Analysis is done as to what point the ability of sellers to sell becomes less useful than other opportunities. This is related to \"marginal\" costs - or the price to produce the last unit that can be sold profitably, versus the chance of using the same effort to engage in some other activity.\n\nDespite the extreme controversy surrounding larger economic issues, there is significant agreement among mainstream economists on the fundamentals of the subject, especially as reflected in [[microeconomics]] as opposed to [[macroeconomics]]. In particular the nature of money, supply and whether price reflects available information are areas of dispute. See below for further discussion.\n\nMuch contemporary theory assumes that economic agents act [[Rationality|rationally]] to optimize well-being given available information. This may sometimes be an acceptable approximation - for instance, if a given individual\'s irrationality is canceled out in the aggregate) and tends to produce tractable results. However, this framework (\"[[homo economicus]]\" - has for decades been understood as a handy approximation (e.g., see [[Herbert Simon]]\'s model for \"[[bounded rationality]]\", which was awarded a Nobel Prize in 1978). More recently, irrational behavior and imperfect information have increasingly been the subject of formal modelling, often referred to as behavioral economics, for which [[Daniel Kahneman]] won a Nobel Prize in 2002. An example is the growing field of [[behavioral finance]] which combines previous theory with [[cognitive psychology]].\n\n== Economic language and reasoning ==\n\nEconomics relies on rigorous styles of argument more than other social sciences. This is at least, the purported ideal of professionals in the field. Economic methodology has several interacting parts; \n\n* Collection of economic data. This data consists of collecting measurable values of price, and changes in price, for measurable commodities. For example the cost to hire a worker for a week, or the cost of a particular commodity, and how much is typically used. \n\n* Formulation of [[model (economics)|models]] of economic relationships, for example, the relationship between the general level of prices and the general level of employment. This includes observable forms of economic activity: money, consumption, preferences, buying, selling, prices etc. Some of the models are simple [[accounting]] models, while others postulate specific kinds of economic behavior, such as utility or profit maximization. An example of a model which illustrates both of these aspects, is the classical mathematical formulation of the [[Keynesian]] system involving the [[consumption function]] and the [[national income]] identity. In this article we will refer to such models as \'\'formal models\'\' although they are not formal in the sense of [[formal logic]].\n\n* Production of Economic statistics. Taking the data collected, and applying the model being used to produce a representation of economic activity. For example the \"general price level\" is theoretical idea common to macroeconomic models. The specific inflation rate involves taking measurable prices, and a model of how people consume, and calculating what the \"general price level\" is from the data within the model. For example suppose that gasoline costs 1 euro a liter, to calculate the price level would require a model of how much gasoline an average person uses, and what fraction of their income is devoted to this - but it also requires having a model of how people use gasoline, and what other goods they might substitute for it.\n\n* Reasoning within economic models. This process of reasoning (see the articles on [[informal logic]], [[logical argument]], [[fallacy]]) may or may not involve advanced mathematics. For instance, an established (though possibly unexamined) tradition among economists is to reason about economic variables in two-dimensional graphs in which curves representing relations between the axis variables are parametrized by various indices. A good example of this type of reasoning is exhibited by [[Paul Krugman]]\'s online essay, \'\'There\'s something about macro\'\'. See also the article [[IS/LM model]]. One critical analysis of economic reasoning is studied in [[Paul Samuelson]]\'s thesis, \'\'Foundations of Economic Analysis\'\': he identifies a class of assertions called \'\'operationally meaningful theorems\'\' which are those that can be meaningfully formulated within an economic model. As usual in science, the conclusions obtained by reasoning have a predictive as well as confirmative (or dismissive) value. An example of the predictive value of economic theory is a prediction as to the effect of current deficits on interest rates 10 years into the future; An example of the confirmative value of economic theory would be confirmation (or dismissal) of theories concerning the relation between marginal tax rates and the deficit.\n\nFormal modelling is motivated by general principles of consistency and completeness.\n\nFormal modelling has been adopted to some extent by all branches of economics. It is not the identical to what is often referred to as [[mathematical economics]]; this includes, but is not limited to, an attempt to set [[microeconomics]], in particular general equilibrium on solid mathematical foundation. Some reject mathematical economics: The [[Austrian School]] of economics believes that anything beyond simple logic is often unnecessary and inappropriate for economic analysis. In fact, the entire empirical-deductive framework sketched in this section may be rejected outright by this school. However, we believe the framework sketched here represents accurately the current predominant view of economics.\n\n== Development of economic thought ==\n\n
[[Image:David ricardo.jpg|thumb|133px|[[David Ricardo]], one of the most influential [[classical economists]], is often credited with systematising economics.]] [[Image:Adam Smith.jpg|133px|thumb|[[Adam Smith]] wrote \'\'[[The Wealth of Nations]]\'\'.]] [[Image:Kmarx.jpg|thumb|133px|[[Karl Marx]] analysed history in terms of [[class conflict]] and coined the term \"[[capitalism]].\"]] [[Image:keynes.gif|thumb|133px|[[John Maynard Keynes]] pioneered the modern study of [[macroeconomics]].]]\n
\n\nModern economic thought is usually considered to have begun with [[Adam Smith]] in the late [[18th century]], although earlier thinkers such as the Spanish [[Scholastics]] and the [[physiocrats]] made important contributions. For an overview of precursors to Smith as well as an overview of schools that have developed later, see [[History of Economic Thought|history of economic thought]]. Modern mainstream economics can be said to begin with Mills focusing of what was then called \"political economy\" on \"wealth\" which he defined exclusively in relation to the exchange value of objects, or what would now be called [[price]]. \"Classical Economics,\" as the economic work of the period is called, forms the foundation of [[micro-economics]].\n\nThe central idea promoted by Smith was that the competition between various suppliers and buyers would produce the best possible distribution of goods and services, because it would encourage individuals to specialize and improve their capital, so as to produce more value with the same labor. As with its contemporaneous idea of [[evolution]], it rests on the belief that large systems can be self-regulating by the activity of their parts, without specific direction. Smith\'s formulation is called the \"invisible hand\" and is still the centerpiece of [[market]] economics, and [[capitalism]] in particular. \n\nIn the 19th century, [[Karl Marx]] synthesized a variety of schools of thought involving the social distribution of resources, including the work of Adam Smith, as well as socialism and egalitarianism, and used the systematic approach to logic taken from philosopher [[Georg Wilhelm Friedrich Hegel|Hegel]] to produce \"Das Kapital\". His work was the most widely adhered-to critique of market economics during much of the 19th and 20th centuries. The Marxist paradigm of economics is not generally held in high regard by market economists, though some concepts from his work are occasionally used in mainstream contexts, particularly in [[labor economics]] and in [[political economy]]. The term [[Marxian]] is in some contexts used to describe work which accepts concepts from his work but does not necessarily subscribe to the political thrust of [[Marxist]] thought.\n\nIn the early 20th century, economics became increasingly statistical, and the study of [[econometrics]] became increasingly important. Statistical treatment of price, unemployment, money supply and other variables, as well as the compiling of these statistics, became more and more central to economic writing and disputes within the field of economics.\n\nMacroeconomics diverged from microeconomics with [[John Maynard Keynes|Keynes]] in the [[1920s]], and was codified in the [[1930s]] by Keynes and others, particularly [[John Hicks]]. It grew in popularity as a reaction to the [[Great Depression]]. Keynes had been an influential exponent of the importance of central banking and government involvement in economic affairs, as well as a critic of the political economy of the post [[World War I]] period. His \"General Theory\" encapsulated both criticisms of classical theory that had been levelled by [[Thorstein Veblen]] and others, as well a method for economic management of aggregate demand. For an overview of a number of competing schools, see [[macroeconomics]].\n\nMany economists use a combination of Neoclassical microeconomics and Keynesian macroeconomics. This combination, sometimes known as the \'\'Neoclassical synthesis\'\', was dominant in Western teaching and public policy in the years following [[World War II]] and up to the late 1970s. The neoclassical school was challenged by [[monetarism]], formulated in the late 1940\'s and early 1950\'s by [[Milton Friedman]] and associated with the [[University of Chicago]].\n\nIn principle, economics can be applied to any type of economic organization. However. the majority of economic theory centers around systems where goods are exchanged in the [[market]] - where buyers and sellers seek to maximize their results by trading. The dominant form of [[market]] economics focuses on societies where property is owned by individuals, money has a rational basis, and profit comes from utilizing labor and capital to produce goods to be sold in the market - or [[capitalism]]. However, economic theory is also applied to markets where the control of capital is in the hands of the state or society, which include [[socialism]] and [[mercantilism]], and to societies where the allocation of resources is not through the market, but through political mechanisms, generally referred to as command economies, which includes [[communism]] and other forms of [[totalitarianism]]. Many economists assert that it is impossible to avoid the \"Invisible Hand\" of the Market, and hence all societies can be modelled through market dynamics, though this viewpoint has vehement opponents across the political spectrum.\n\nThe development of economics as a field of study is closely related to the rise of capital as the primary determining factor of production and trading, hence its most detailed and precise work has dealt with the institutions belonging to market societies, and most specifically to capitalist and socialist societies. To what extent economics must be adjusted to be applied to earlier forms of social organization has been the source of discussion. Generally, mainstream economists mostly feel that the basic framework of economics is relevant and flexible enough to be applied to virtually any form of society. Marxist economics asserts that history is divided into eras which are determined by which two classes, which are struggling to control the means of production - that is slaves and masters, peasants and royalty, wage workers and capitalists - and that mainstream economics only applies to those societies which are \"objectively\" industrial, that is to say, societies which are capable of industrial production based on their own knowledge and resources. (See [[Marxism]], particularly \"The Hegelian Roots of Marxism\".) \n\nIn the late 20th Century three of the areas of study which are producing change in economic thinking are: risk based rather than price based models, imperfect economic actors, and treating economics as a biological science, based on evolutionary norms rather than abstract exchange. \n\nThe study of [[risk]] has been influential, which viewed variations in price over time as more important than actual price. This particularly applies to financial economics where risk-return tradeoffs are the crucial decisions to be made.\n\nThe most important area of growth has been in the study of information and decision. Examples of this school include the work of [[Joseph Stiglitz]]. Problems of asymmetric information and moral hazard, both based around information economics, profoundly affect modern economic dilemmas like executive stock options, insurance markets, and third-world debt relief.\n\nFinally, there are a series of economic ideas rooted in the conception of economics as a branch of biology, including the idea that energy relationships rather than price relationships determine economic structure, and the use of fractal geometry to create economic models. (See [[Energy Economics]])\n\nIn its infancy is the application of [[non-linear dynamics]] to economic theory, as well as the application of [[evolutionary psychology]]. So far the most visible work has been in the area of applying fractals to market analysis, particularly [[arbitrage]]. (See [[Complexity in Economics]])\n\nAnother infant branch of economics is [[neuroeconomics]]. This combines neuroscience, economics, and psychology to study how we make choices.\n\n== Economics in the context of Western thought ==\n\n=== Basic Scarcity in Economic Theory ===\n\nBecause scarcity and decision are central to economic theory, the question of what is the basic trade-off in economics is of central importance. In every economic theory, there is a basic exchange of two or more ultimately scarce commodities. For Adam Smith, it was defined as the trading of time, or convenience, for money. For example, a person could live near town, and pay more for rent or his domicile, or live farther away and pay less, \"paying the difference out of his convenience\". \n\n[[Image:NYSE-floor.jpg|thumb|right|240px|Trading floor of the [[New York Stock Exchange]] ]]\n\nThis view, that the primary trade-off involved in economics is between time and money, has several challengers. Each of these bases its view of scarcity on a different fundamental trade-off. A small number of economists prefer to define economics as the study of how and why people [[trade]]; this definition implies relative scarcity. \n\nIn economic theory, the price level is determined by the \"marginal\" cost and \"marginal\" utility. Marginalism became increasingly important in economic theory in the late 19th century, and is a tool which is used to analyze how economic systems will react. The marginal cost of a commodity is the cost to produce the last unit of it, the marginal utility is the happiness gained from buying the last unit. Economic theory uses marginalism to describe the \"diminishing returns\" from consumption - the 10th candy bar doesn\'t taste as good as the first, and so brings less \"marginal utility\". Marginal cost of production divides costs into \"fixed\" costs which must be paid regardless of how many of a commodity are produced, and \"variable costs\". The marginal cost is the variable cost of the last unit, plus the percentage of fixed costs. Marginalism states that when the profit from the next unit will be zero, that unit will not be produced.\n\n[[Information theory]] has been applied to economics since the work of [[Ronald Coase]] in the 1930\'s. However, with [[Herbert Simon]] and [[John von Neumann]] in the 1950\'s, it gathered a more specific [[formalism]] as part of [[game theory]]. This emphasises that the decision-making process itself is costly. \n\nMarxist economics generally denies the trade-off of time for money. In the Marxist view, concentrated control over the means of production is the basis for the allocation of resources among classes. Scarcity of any particular physical resource is subsidiary to the central question of power relationships embedded in the means of production.\n\nThe question of the environment is viewed, in the traditional economic framework, as being related to the externalization of costs. That is, market economics assumes that a good which is underpriced, is overconsumed. Externalization of cost, in this view, will be corrected by pricing the overconsumed resources which are being used, for example the work of [[Lester Thurow]] and also see [[social cost#Pigovian taxes|Pigovian taxes]]. Not all economics study accepts this paradigm, and, instead, there is a seven decade old tradition of viewing economic relationships as being based on the scarcity of energy, rather than price, as the central feature of economics.\n\n=== Value Theory ===\n\nIt could be argued that beneath an economic theory is a theory of [[value]]. Value can be defined as the underlying activity which economics describes and measures. It is what is \"really\" happening.\n\nAdam Smith defined \"labor\" as the underlying source of value, and \"the [[labor theory of value]]\" underlies the work of Karl Marx, [[David Ricardo]] and many other \"classical\" economists. The \"labor theory of value\" argues that a good or service is worth the labor that it takes to produce, and the abundance or scarcity of labor determines the price of a commodity. The labor theory of value and the closely related [[cost-of-production theory of value]] dominates the work of most classical economists, but they are far from the only accepted basis for \"value\". For example [[neoclassical economics|neoclassical]] economists and [[Austrian School]] economists prefer the [[marginal theory of value]].\n\n\"Market theory\" argues that there is no \"value\" separate from price, that the market incorporates all available information into price, and that so long as markets are open, that price and value are one and the same. This theory rests on the idea of the \"rational economic actor\". This was orginally asserted by Mill.\n\nAnother set of theories rest on the idea that there is a basic external scarcity, and that \"value\" represents the relationship to that basic scarcity. Theories based on economics being limited by energy or based on a \"gold standard\" are of this type.\n\nAll of these value theories are used in current economic work.\n\n=== Price ===\n\nPrice is the measurable quantities involved in an exchange. Price theory, therefore, charts the movement of measurable quantities over time, and the relationship between price and other measurable variables. In [[Adam Smith]]\'s \'\'Wealth of Nations\'\' this was the trade-off between price and convenience. A great deal of economic theory is based around prices and the theory of [[supply and demand]].\n\nSupply and demand assume that the factors affecting the agents who supply a particular commodity can be separated from those who wish to sell it. Sellers have a quantity they would wish to sell at every given price and a price for any quantity they wish to sell; buyers have a quantity they will demand at any given price and a price that they will pay to if they have to buy a particular quantity. \n\nThe market \'clears\' at the point where all the supply and demand at a given price balance. That is, the amount of a commodity available at a given price equals the amount that buyers are willing to purchase at that price. It is assumed that there is a process that will result in the market reaching this point, but exactly what the process is in a real situation is an ongoing subject of research. Markets which do not clear will react in some way, either by a change in price, or in the amount produced, or in the amount demanded. Graphically the situation can be represented by two curves; one showing the price-quantity combinations buyers will pay for, or the [[demand curve]], one showing the combinations sellers will sell for, or the [[supply curve]]. The market clears where the two are in equilibrium, that is where the curves intersect. In a [[general equilibrium]] model, all markets in all goods clear simultaneously and the \'price\' can be described entirely in terms of tradeoffs with other goods. For a century the [[Say\'s Law]] was believed in economic theory, which said that markets, as a whole, would always clear.\n\nIn many practical economic models, some form of \"price stickiness\" is incorporated to model the observed fact that in many markets prices do not move fluidly. Economic policy often revolves around arguments as to what is causing \"economic friction\", or price stickiness, and which is, therefore, preventing the supply and demand from reaching equilibrium.\n\nAnother area of economic controversy is on whether price measures value correctly. In mainstream market economics, where there are significant scarcities not factored into price, there is said to be an [[externality|externalization]] of cost. Market economics predicts that scarce goods which are under-priced are over-consumed (See [[social cost]]). This leads into [[public good]]s theory.\n\n=== Economics and other disciplines ===\n\nThere is some degree of tension between economics and [[ethics]], another of the most basic [[social sciences]], which tends to avoid quantification and emphasize balances of [[rights]]. Modern economics deals with this tension explicitly – according to some thinkers a theory of economics is also, or implies also, a theory of [[moral reasoning]]. One way economists deal with this is to qualify discussions of [[economic choice]] by noting that \"all else being equal...\" referring to moral or social factors that are supposedly held equivalent for all choices that one might make. \'\'For exploration of this issue, see the [[moral purchasing]] article.\'\'\n\nAnother premise is that economics fits within a finite ecosystem where there are at least some abundant resources – for instance, when fueling a fire one is usually concerned with finding the wood, and not so much with finding the air to burn it with. Economics explicitly does not deal with free abundant inputs – one criticism is that it often conflicts with [[ecology]]\'s view of what affects what. Human beings are, according to ecologists, merely one species participating in a vast [[energy economics|energy system]] on this planet – economy is a subset of ecology that deals with just one species\' habits and wants. \'\'See [[nature\'s services]] for the economic view of ecology and [[green economics]] for the view wherein economics is a subset of ecology.\'\'\n\nA third premise is that economics suggests [[market form]]s and other means of distribution of scarce goods that do not just affect \"desires and wants\" but also \"needs\" and \"habits\". Much of so-called economic \"choice\" is involuntary, certainly given the [[conditioning]] that people have to expect certain [[quality of life]]. This leads to one of the most hotly debated areas in economic policy: namely the effect and efficacy of welfare policies. This is viewed as a failure to respect economics reasoning by [[libertarians]], who argue that redistribution of wealth is morally and economically wrong. And viewed as a failure of economics to respect society by [[socialists]], who argue that disparities of wealth should not have been allowed in the first place. This led to both [[19th century]] [[labour economics]] and [[20th century]] [[welfare economics]] before being subsumed into [[human development theory]].\n\nThe debates above are all quite old. The term economics was coined in around 1870, and popularised by influential \"neoclassical\" economists such as [[Alfred Marshall]]. Prior to this the subject had been known as \'\'\'political economy\'\'\' and referred to \"the economy of polities\" – competing [[state]]s. The older term is still often used \'\'instead of\'\' \'\'\'economics\'\'\', especially by radical economists such as [[Marxists]] who strongly question assumptions of \"mainstream\" technical and quantitative economics. Use of this term often signals an a basic disagreement with the terminology or paradigm of market economics. Political economy explicitly brings political considerations into economic analysis and therefore tends to be more [[normative]]. Some mainstream universities (such as the [[University of Toronto]] and many in the [[United Kingdom]]) have a political economy department rather than an economics department.\n\n== See also ==\n\n:\'\'Microeconomics\'\'
\n:[[Microeconomics]] — [[supply and demand|Supply and Demand]] — [[Consumer theory|Consumer Theory]] — [[production, costs, and pricing|Production theory]] — [[Experimental economics]] — [[Behavioral economics]] — [[General equilibrium]] — [[Industrial organization]] — [[Financial economics]] — [[Managerial economics]] — [[International trade]] — [[Labor market|Labor economics]] — [[Development economics]] — [[Environmental economics]] — [[Welfare economics]] — [[Public choice theory]] — [[Public good]]s — [[Transport economics]] — [[Health economics]] — [[Marginal demand]]\n\n:\'\'Macroeconomics\'\'
\n:[[Macroeconomics]] — [[Stabilisation policy]] — [[Monetary policy]] — [[Fiscal policy]] — [[Economic growth]] — [[Purchasing power parity]] — [[Supply side economics]] — [[Keynesian economics]] — [[Gold standard]] \n\n:\'\'Methodology\'\'
\n:[[Cycles]] — [[Econometrics]] — [[Game Theory]] — [[Mathematical economics]] — [[Evolutionary economics]] \n\n:\'\'Related fields\'\'
\n:[[History of Economic Thought|History of economic thought]] — [[Economic history]] — [[Praxeology]] — [[Political economy]] — [[Political science]] — [[Economic geography]] — [[Finance]] — [[Operations research]] — [[Economic anthropology]] — [[Public finance]] — [[Home economics]] — [[Neuroeconomics]]\n\n:\'\'Critics\'\'
\n:[[Steve Keen|Steve_Keen]] \n\n:\'\'Selected topics\'\'
\n:[[Communism]] — [[Capitalism]] — [[Coordinatorism]] — [[Market economy]] — [[Informal economy]] — [[Freiwirtschaft]] — [[Synthetic economies]] — [[Participatory economics]] — [[Natural capitalism]] — [[Stock exchange]] — [[economic indicator]] — [[Regulation]] — [[Deregulation]] — [[Privatization]] — [[Network effect]]— [[Laissez-faire]]\n\n== Finding related topics ==\n*[[List of economics topics]]\n*[[List of economic geography topics]]\n*[[List of finance topics]]\n*[[List of economics consultancies and think tanks]]\n*[[List of economists]]\n*[[List of international trade topics]]\n*[[Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel]]\n*[[List of production topics]]\n*[[List of accounting topics]]\n*[[List of management topics]]\n*[[List of marketing topics]]\n*[[List of business ethics, political economy, and philosophy of business topics]]\n*[[List of information technology management topics]]\n*[[List of human resource management topics]]\n*[[List of business law topics]]\n* [[List of publications in economics| Important publications in economics]]\n\n==Tumbu kaluar==\n* [[wikibooks:Economics|Buku téks ékonomi]] na [[wikibooks:Main_Page|Bukuwiki]]\n* [http://www.tutor2u.net A source of free study notes on economics]\n* [http://www.oswego.edu/~economic/newbooks.htm A guide to several online economics textbooks]\n*[http://www.oecd.org/statistics/ OCED Statistics] Organization For Co-operation and Economic Development Statistical site.\n* [http://www.dmoz.org/Science/Social_Sciences/Economics/ Economics Directory]\n*[http://www.bls.gov Bureau of Labor Statistics] American Labor Department\'s statistical division.\n*[http://www.worldbank.org/data/ World Bank\'s Data Web Page]\n*[http://www.bea.doc.gov US Department of Commerce Economics Statistics]\n*[http://www.utexas.edu/world/lecture/eco/ World Lecture Hall] Economics Section\n*[http://william-king.www.drexel.edu/top/prin/txt/EcoToC.html Essential Principles of Economics] Text in Progress on Economics\n*[http://rfe.wustl.edu/EconFAQ.html Economics Resources on the Net]\n*[http://www.nber.org National Bureau of Economic Research] Economics material from the organization that declares Recessions and Recoveries.\n*[http://www.econlib.org/index.html The library of economics and liberty], a site with numerous articles and essays written by well-known economists\n*[http://www.stlouisfed.org/ St Louis Federal Reserve] Gateway to the Federal Reserve, including working papers, links to lectures and other material.\n*[http://www.daviddfriedman.com/Academic/Price_Theory/PThy_ToC.html David Friedman\'s Price Theory Text] Entire text on-line.\n*[http://web.mit.edu/krugman/www/islm.html Brief Introduction to Macroeconomics by Paul Krugman]\n*[http://www.wws.princeton.edu/~pkrugman/ Paul Krugman\'s Page,] including the essay \'\'There\'s something about macro\'\'.\n* [http://www.libertyforums.com/ LibertyForums] – Classical Liberal, Libertarian & Objectivist Discussion Board\n* [http://www.ericdigests.org/1999-4/economics.htm The National Voluntary Content. ERIC Digests.]\n* [http://www.ericdigests.org/1998-1/economic.htm Recent Trends in Economic Education. ERIC Digest.]\n* [http://www.uqac.uquebec.ca/zone30/Classiques_des_sciences_sociales/ Classiques des Sciences Sociales] More than 800 full text books and articles (in French)\n\n[[af:Ekonomie]]\n[[bg:Икономика]]\n[[bs:Ekonomija]]\n[[ca:Economia]]\n[[cs:Ekonomie]]\n[[cy:Economeg]]\n[[da:Økonomi]]\n[[de:Volkswirtschaftslehre]]\n[[en:Economics]]\n[[eo:Ekonomiko]]\n[[es:Economía]]\n[[el:Οικονομικά]]\n[[fr:Économie (science)]]\n[[fy:Ekonomy]]\n[[gl:Economía]]\n[[hr:Ekonomija]]\n[[hu:közgazdaságtan]]\n[[ia:Economia]]\n[[id:Ekonomi]]\n[[it:Economia]]\n[[ja:経済学]]\n[[ko:경제학]]\n[[lt:Ekonomika]]\n[[lv:Ekonomika]]\n[[nl:Economie]]\n[[no:Økonomi]]\n[[oc:Economia]]\n[[nds:Wertschap]]\n[[pl:Ekonomia]]\n[[pt:Economia]]\n[[ro:Economie]]\n[[ru:Экономика]]\n[[simple:Economics]]\n[[sl:ekonomija]]\n[[sr:Економија]]\n[[sv:Nationalekonomi]]\n[[zh-cn:经济学]]\n[[zh-tw:經濟學]]\n\n[[Category:Ékonomi]]\n[[Category:Élmu sosial]]','/* Tumbu kaluar */',3,'Kandar','20050202105809','',0,0,1,0,0.029277559383,'20050316081936','79949797894190'); INSERT INTO cur VALUES (1070,0,'Pamaréntah','\'\'\'Pamaréntah\'\'\' nyaeta hiji [[organisasi]] anu ngabogaan kakuatan keur nyieun jeung ngatur hukum di [[territory]] husus. Aya sababaraha harti ngeunaan hari sabenerna tina pamarentah.\n\nPamaréntah geus dihartikeun kakuatan \"pengambil keputusan\" anu dominan (elit pulitik) di hiji \'\'\'[[state]]\'\'\'. The latter has been defined (by the political economist [[Max Weber]] and later [[political philosophy]]) as the organization that holds a monopoly in legitimate use of violence within its territory. If seen in ethical terms, the definition of \"legitimate\" is open to discussion, and implies that an organisation may be considered a state by its supporters but not by its detractors. Some define \"legitimate\" as simply involving active and tacit support by the vast majority of the population, i.e., the absence of civil war. (An entity that shares military/police power with independent militias and bandits is not a state in this view. It may be a \"failed state.\") Democratic control over the government -- and thus the state -- would encourage the legitimacy of the state in this view. \n\nGovernment can also be defined as the [[pulitik|political]] means of creating and enforcing [[hukum|law]]s; typically via a [[bureaucracy|bureaucratic]] [[hierarchy]]. Under this definition, a purely [[despotism|despotic]] organisation which controls a territory without defining laws would not be considered a government.\n\nAn alternative is to define a government as an organisation that attempts to maintain control of a territory, where \"control\" involves activities such as collecting [[tax]]es, controlling entry and exit to the state, preventing encroachment of territory by neighbouring states and preventing the establishment of alternative governments within the country. \n\nGovernments concern themselves with many issues, such as [[economics]], [[education]], [[health]], [[science]], [[territory]], and [[war]].\n\nThe modern standard unit of territory comprises a [[country]]. In addition to the meaning used above, the word [[state]] can refer either to a government or to its territory. Within a territory, [[subnational entity|subnational entities]] may have [[local government]]s which do not have the full power of a national government. \n\nGovernments use a variety of methods to maintain control, such as [[police]] and [[military forces]], (particularly under [[despotism]], see also [[police state]]), making agreements with other states, and maintaining support within the state. Typical methods of maintaining support and legitimacy include providing [[infrastructure]] for [[justice]], [[administration]] , [[transport]], [[social welfare]] etc., claiming support of [[deity|deities]], providing benefits to influential groups, holding [[election]]s\nfor important posts within the state, limiting the power of the state through [[law]]s and [[constitution]]s and appealing to [[nationalism]]. Groups opposed to government control include [[libertarians]] and [[anarchists]].\n\nVarious [[form of government|forms of government]] have been implemented or proposed. A government in a developed state is likely to have various sub-organisations known as offices, departments, or agencies, which are headed by politically appointed officials, often called [[minister|ministers]] or secretaries. Ministers may in theory act as advisors to the [[head of state]], but in practice have a certain amount of direct power in specific areas. In most modern [[democracy|democracies]], the elected [[legislative assembly]] has the power to dismiss the government, though the [[head of state]] generally has great latitude in appointing a new one.\n\n===Sumangga tingali=== \n* [[system of government]]\n* [[head of government]]\n* [[pulitik]] \n* [[filosofi politis]] \n* [[élmu politis]] \n* [[kabinét (government)|kabinét]] \n* [[executive]] \n* [[legislature]] \n* [[egovernment]]\n* [[anarchism]]\n* [[federalism]]\n* [[governance]]\n* [[world government]]\n\n\n----\n\'\'\'Government\'\'\' is also a name given, in [[debate|debating]] [[event]]s and [[competition]]s, to the team which supports and tries to prove a [[Motion_(democracy)|motion]].\n\n[[ca:Govern]] [[da:Regering]] [[de:Regierung]] [[en:Government]] [[fr:Gouvernement]] [[nl:Regering]] [[simple:Government]] [[zh-cn:政府]]','',13,'Budhi','20041224145535','',0,0,1,0,0.858148060207,'20041224145535','79958775854464'); INSERT INTO cur VALUES (1071,0,'Planning_statistical_research','#REDIRECT [[Ngarencanakeun panalungtikan statistik]]\n','Planning statistical research moved to Ngarencanakeun panalungtikan statistik',13,'Budhi','20040725045144','',0,1,0,1,0.55692283674788,'20040725045144','79959274954855'); INSERT INTO cur VALUES (1072,0,'Atlas','\'\'\'Peta\'\'\' atawa \'\'\'atlas\'\'\' ngarupakeun gambaran dua-diménsi pikeun rohangan tilu diménsi. Élmu nyieun peta disebut [[kartografi]].\n\n==Bubuka==\nEarly maps were vague and there was often controversy as to where to centre the map - one world map, for instance, has [[Jerusalem]] at the centre. The purpose of such maps seem to not be intended as geographic, but rather to show a history with regards to that geography. The early ship navigation charts were quite similar to modern maps in accuracy with the exception of unknown areas.\n\nMany maps have a [[scale (measurement)|scale]], determining how large objects on the map are in relation to their actual size. A larger scale shows more detail, thus requiring a larger map to show the same area. Some, though, are not drawn to scale - a famous example being the [[Tube_map|London Underground map]]. \n\nIf the map covers a large area of the surface of a globe, such as [[Earth|the Earth]], it also has a [[map projection|projection]], a way of translating the three-dimensional real surface of the [[geoid]] to a two-dimensional picture. One commonly used for navigation is the [[Mercator Projection]]; other popular projections are polar and a variety of equal-area projections.\n\nThe features shown on a map vary according to its purpose. For example, a [[road]] map may or may not show [[railroad]]s, and if it does, it may show them less clearly than [[highway]]s. \n\nMaps can be political or geographical. The most important purpose of the political map is to show territorial borders; the purpose of the geographical is to show features of [[physical geography]] such as mountains, soil type or land use. Geological maps show not only the physical surface, but characteristics of the underlying rock, [[Geologic fault|fault]] lines, and subsurface structures.\n\nMany surveying projects have been carried out by the military. An example of this the [[British]] [[Ordnance Survey]] (which now is a civilian government agency).\n\nBecause maps are abstract representations of the world they are not neutral documents and must be carefully interpreted. It is, of course, this abstraction that makes them useful. [[Lewis Carroll]] made this point humorously in \'\'Sylvie and Bruno\'\' with his mention of a fictional map that had \"the scale of a mile to the mile.\" A character notes some practical difficulties with this map and states that \"we now use the country itself, as its own map, and I assure you it does nearly as well.\"\n\n==Peta éléktronik==\n\nFor maps on a computer display, e.g. from the web or locally stored on CD-ROM or harddisk, zooming in means enlarging the scale, either by showing a smaller area in the same viewing window or by showing the same area in a larger viewing window, and one of the following:\n*replace the map by a more detailed one\n*enlarge the same map without enlarging the [[pixel]]s, hence show more detail\n*enlarge the same map with the pixels enlarged (replaced by rectangles of pixels); no additional detail is shown, but, depending on the quality of one\'s vision, possibly more detail can be seen; if a computer display does not show adjacent pixels really separate, but overlapping instead (this does not apply for an [[LCD]] display, but may apply for a [[cathode ray tube|CRT]]), then replacing a pixel by a rectangle of pixels does show more detail.\n\nCombinations are possible, e.g. the second applying for text and the third for the outline of a map feature such as a forest, a building etc. Also the map may have layers which are partly [[raster graphics]] and partly [[vector graphics]].\n\nFor a single raster graphics image the second applies until the pixels in the image file correspond to the pixels of the display; on further zooming in, the third applies.\n\nFor a [[Portable Document Format|PDF]]-file typically the second applies. The increase in detail is, of course, limited to the information contained in the file: enlarging a curve it may eventually become a series of straight line segments, or other standard geometric figures such as arcs of circles.\n\nA variation of the third possibility is that interpolation is performed.\n\nText is not necessarily enlarged when zooming in. Similarly, a road represented by a double line may or may not become wider when one zooms in. A variation of the first possibility above is that more text is displayed (such as more town names), but that for the rest of the image the second applies.\n\nSee also [[Webpage#Graphics]], [[Portable Document Format#Layers]].\n\n==Other uses==\n\n*\'\'Road map\'\' is also used [[metaphor]]ically for a plan, for example \"[[Road map for peace]]\".\n* In [[computer game]]s, a \'\'map\'\' is synonymous to a [[level]]. In the context of [[modification]]s, especially for [[first person shooter]]s, the word \'\'map\'\' likewise refers to the full distribution-ready set of data for a map - for example, the map \"de_dust\" in [[Counter-Strike]] includes the [[brush]]es, textures, bomb sites, spawn points, and backgrounds.\n*[[Songline]]s as maps in [[Australian Aborigine]] culture.\n\n==Peta na Wikipédia==\n[[Daptar nagara|Unggal artikel nagara]] kudu nyadiakeun peta nagarana, ogé [[Daptar éntitas subnasional|bagian-bagian tina nagara éta]]. \'\'Tempo ogé [[Peta dunya]], [[Peta na Wikipédia]].\'\'\n\n== Tumbu jeung acuan ==\n\n===Acuan===\n*David Buisseret, ed., \'\'Monarchs, Ministers and Maps: The Emergence of Cartography as a Tool of Government in Early Modern Europe.\'\' Chicago: University of Chicago Press, 1992, [ISBN 0226079872]\n*Mark Monmorier, \'\'How to Lie with Maps\'\', [ISBN 0226534219]\n\n===Tempo ogé===\n*[[Atlas (kartografi)]]\n*[[Peta topografik]]\n*[[Peta géologis]]\n\n=== Tumbu kaluar ===\n*[http://www.multimap.com/ Multimap world atlas]: on UK, US, Canada, Australia and Western Europe more detailed than the rest of the world \n*[http://www.expedia.com/pub/agent.dll?qscr=mmfn] - [[Microsoft]]/[[Encarta]]/[[Expedia]] world atlas, for North America and Europe to street level. \n*[http://www.mapquest.com/maps MapQuest]: on US, Canada and Western Europe more detailed than the rest of the world \n*[http://maps.yahoo.com Yahoo Maps]: on US, Canada, Germany, France, Spain, Italy\n*[http://de.maps.yahoo.com/ Yahoo Germany]: on France, UK, Germany, Italy, Spain, Portugal, Austria, Switzerland, Benelux\n*[http://www.mapsouthpacific.com/ Map South Pacific]: on Polynesia, Melanesia, Micronesia\n*[http://mapapps.esri.com/routing/] - [[ESRI]] atlas of the US\n*[http://www.nationalatlas.gov/ National Atlas of the United States]\n*[http://www.infoplease.com/atlas/ Small country maps, conveniently linked from continent maps]\n*[http://www.lib.utexas.edu/maps UT scanned collection]: by the [[University of Texas at Austin]]\n*[http://www.citoplan.nl/citoplan/img/legenda_groot.gif Example of legend (Cito-Plan city maps)]\n*http://www.geocities.com/marcoschmidt.geo/geo-data.html\n*[http://nationalmap.usgs.gov/ USGS National Map]\n\n\n\n[[Category:Kartografi]]\n\n[[da:Kort (geografi)]] [[de:Karte (Kartographie)]] [[en:Map]] [[es:Mapa]] [[eo:Mapo]] [[et:Kaart]] [[fr:Carte]] [[ja:地図]] [[nl:Kaart (cartografie)]] [[pl:Mapa]] [[zh-cn:地图]]','/* Links and references */',3,'Kandar','20040826075926','',0,0,0,0,0.734589535154,'20040826075926','79959173924073'); INSERT INTO cur VALUES (1073,0,'Peta_géologis','A \'\'\'geologic map\'\'\' is a special-purpose [[map]] made for the purpose of showing subsurface geological features. In the [[United States]], geologic maps are usually based on [[topographic map]]s, with the addition of a color mask, stratigraphic contour lines, and various other selected symbols.\n\nThe color mask denotes the exposure of the immediate [[bedrock]], even if obscured by soil or other cover. Each area of color denotes a particular rock formation. However, in areas where the bedrock is overlain by a significantly thick unconsolidated burden of till, terrace deposits, loess deposits, or other important feature, these are shown instead.\n\nThe stratigraphic contour lines are drawn on the surface of a selected deep stratum, so that they can show the topographic trends of the strata under the ground. It is not always possible to properly show this when the strata are extremely fractured, mixed, in some discontinuities, or where they are otherwise disturbed.\n\nFault lines are also shown where known.\n\nWhereas topographic maps are produced by the [[United States Geological Survey]] in conjunction with the states, geologic maps are usually produced by the states. There are almost no geologic map resources for some states, while a few states, such as [[Kentucky]], are extensively mapped geologically.\n\n==Tempo ogé==\n*[[Géologi]]\n*[[Géografi fisik]]\n\n[[de:Geologische Karte]] [[en:Geologic map]]\n\n[[Category:Kartografi]]','',3,'Kandar','20040826080441','',0,0,0,0,0.50100754085,'20040826080441','79959173919558'); INSERT INTO cur VALUES (1074,0,'Random','#redirect [[randomness]]','',13,'Budhi','20040726221254','',0,1,0,1,0.062754489976,'20040726221254','79959273778745'); INSERT INTO cur VALUES (1075,0,'Kaulinan',':\'\'This article is about a recreational activity. For other meanings, see [[game (disambiguation)]].\'\'\n\n\'\'\'Kaulinan\'\'\' nyaeta kagiatan rekreasi nu digawekeun ku saurang pamaen atawa leuwih, dina hari a) usaha pamaen keur meunangkeun kaulinan jeung b) sababaraha aturan ngeunaan naon anu bisa dipigawe ku pamaenna. Kaulinan dimaenkeun utamana keur karesep atawa kasenangan.\n\nKaulinan bisa oge saurang pamaen ulin nyorangan, tapi leuwih ilahar ngarupakeun kompetisi antara dua urang atawa leuwih. Taking an action that falls outside the rules generally constitutes a foul or cheating.\n\nAll through [[human]] [[history]], people have played games to entertain themselves and others, and there is an enormous variety of games types; for specific information about any type, see links at the end of this article.\n\n[[philosophy|Philosopher]] [[David Kelley]], in his popular introductory reasoning text \'\'[[The Art of Reasoning]]\'\', defines the concept \"game\" as \"a form of recreation constituted by a set of rules that specify an object to be attained and the permissible means of attaining it.\" This covers most cases well, but does not quite fit with things like [[war game]]s and [[sport]]s that are often done not for [[entertainment]] but to build [[skill]]s for later use. In \'\'[[Philosophical Investigations]],\'\' philosopher [[Ludwig Wittgenstein]] argued that the concept \"game\" could not be contained by any single definition, but that games must be looked at as a series of definitions that share a \"family resemblance\" to one another. \n\nIn a different context, [[Stephen Linhart]] said, \"People say you have to choose between games and real life. I think this claim that there\'s a dichotomy is very dangerous.\"\n\nMany technical fields are often applied to the study of games, including [[probability]], [[statistik]], [[economics]], [[ethnomathematics]], and [[game theory]].\n\n==Tipe Kaulinan==\n*[[Alternate Reality Game]]\n*[[Board game]]s\n*[[Car game]]s\n*[[Card game]]s\n*[[Casino game]]s\n*[[List of traditional children\'s games|Children\'s games]]\n*[[Clapping game]]s\n*[[Computer game]]s or [[Dojin game]]s\n*[[Counting-out game]]s\n*[[Dice game]]s\n*[[Drinking game]]s\n*[[Educational game]]s\n*[[Game show]]s\n*[[Games of chance]]\n*[[Games of logic]]\n*[[Games of physical activity]]\n*[[Games of physical skill]]\n*[[Games of skill]]\n*[[Games of strategy]]\n*[[Simulation game|Games of status]]\n*[[Group-dynamic game]]s\n*[[Guessing game]]s\n*[[Internet game]]s\n*[[Letter game]]s\n*[[Mathematical game]]s\n*[[Online skill-based game]]s\n*[[Open gaming]]\n*[[Party game]]s\n*[[Pencil and paper game]]s\n*[[Play by mail game]]s\n*[[Political game]]s\n*[[Puzzle]]s\n*[[Quiz]]\n*[[Role-playing game]]s, [[MMORPG]]s\n*[[Singing game]]s\n*[[Spoken game]]s\n*[[String game]]s\n*[[Table-top game]]s\n*[[Tile-based game]]s\n*[[Traditional game]]s\n*[[Unclassified game]]s\n*[[Video game]]s\n*[[Word game]]s\n\n==See also==\n* [[List of game manufacturers]]\n* [[List of game topics]]\n* [[Game classification]]\n* [[Game semantics]]\n* [[Game theory]]\n* [[Play]]\n* [[Toy]]\n\n==External link==\n* [http://www.open-site.org/Games Open-Site Games] - Encyclopedia of games and game information, including video games and gambling\n\n[[bg:Игра]]\n[[ca:Joc]]\n[[da:Spil]]\n[[de:Spiel]]\n[[el:Παιχνίδι]]\n[[eo:Ludo]]\n[[es:Juego]]\n[[fi:Peli]]\n[[fr:Jeu]]\n[[hi:खेल]]\n[[hr:Igra]]\n[[is:Leikir]]\n[[it:Gioco]]\n[[ja:ゲーム]]\n[[he:משחק]]\n[[nl:Spel]]\n[[nds:Speel]]\n[[pl:Gra]]\n[[pt:Jogos]]\n[[ro:Joc]]\n[[simple:Game]]\n[[sl:igra]]\n[[sv:Spel]]\n[[zh-cn:游戏]]\n[[zh-tw:遊戲]]\n\n[[Category:Games]]','/* Types of Games */',13,'Budhi','20040901070925','',0,0,0,0,0.326143128018,'20041225124916','79959098929074'); INSERT INTO cur VALUES (1077,0,'Zat_kimia','\'\'\'Zat kimia\'\'\' bisa ngandung harti [[unsur kimia]] atawa bahan nu mibanda wangunan unsur-unsur nu tangtu: [[sanyawa kimia]]. Istilah ieu ogé nujul ka \'\'bulk material\'\' batan ka partikel mikroskopik/submikroskopik tunggal, nu hartina, \"\'\'zat kimia\'\' nyaéta kumpulan husus [[atom]]-atom/[[molekul]]-molekul.\"\n\n:\'\'Tempo ogé:\'\' [[kimia]], [[industri kimia]], [[campuran]].\n\n\n{{pondok}}\n\n[[ja:%E8%96%AC%E5%93%81]]\n[[en:Chemical]]','',3,'Kandar','20041125071226','',0,0,0,0,0.414624951973,'20050303211247','79958874928773'); INSERT INTO cur VALUES (1078,0,'Molekul','\'\'\'Molekul\'\'\' nyaéta bagéan pangleutikna tina [[unsur kimiawi|unsur]] atawa [[sanyawa kimiawi]] murni nu mibanda sakumpulan sipat-sipat kimiawi jeung fisik nu has. Molekul biasana disusun ku dua atawa leuwih [[atom]] nu [[beungkeut kimiawi|kabeungkeut]] jadi hiji, iwal [[gas mulya]] nu diwangun ku ukur hiji atom.\n\n
[[Image:Atisan.png|center|framed|\'\'Gambar 1.\'\' Gambaran [[modél géométris 3D|3D]] (kénca jeung tengah) jeung [[modél géométris 2D|2D]] (katuhu) [[terpenoid]], [[atisan]]. Dina modél 3D beulah kénca, atom [[karbon]] digambarkeun salaku buleudan abu-abu, buleudan bodas ngagambarkeun atom [[hidrogén]], sedengkeun silinder nunjukkeun beungkeutna. Modél ieu dibungkus ku \"jaring\" nu ngagambarkeun beungeut molekular, diwarnaan dumasar wewengkon [[muatan listrik]] positif (beureum) jeung négatif (bulao).]]
\n\nKalolobaan molekul leutik teuing mun hayang ditempo bungkeuleukanana ku mata taranjang, tapi aya iwal. Saguruntul [[natrium klorida|uyah]], atawa [[inten]] dina lélépén, ngarupakeun kisi [[kristal]] raksasa, molekul \'\'repetitif\'\' nu beungkeutan atomna (boh [[beungkeut ionik]] atawa [[beungkeut kovalén|kovalén]]) nyambungkeun sakabéh struktur. Conto séjén molekul makroskopis séjén nyaéta [[DNA]], hiji [[makromolekul]].\n\nSalasahiji sipat molekul nyéta [[nisbah]] [[integer|buleud]] unsur-unsur nu nyusun sanyawa, nyaéta [[rumus émpiris]]. Pikeun conto, dina wujud murnina, [[cai]] salawasna diwangun ku [[hidrogén]] jeung [[oksigén]] dina nisbah 2:1, sedengkeun étil [[alkohol]] atawa [[étanol]] salawasna diwangun ku [[karbon]], [[hidrogén]], jeung [[oksigén]] dina nisbah 2:6:1. Najan kitu, nisbah ieu teu nangtukeun jenis molekul sacara husus - [[dimétil éter]] mibanda nisbah nu sarua jeung étanol, misalna. Molekul nu mibanda atom nu sarua dina susunan nu béda disebut [[isomér]].\n\n[[Rumus kimia]] dina sisi séjén ngagambarkeun jumlah nu pasti atom-atom nu ngawangun hiji molekul. [[Beurat molekul]] diitung tina rumus kimia sarta diéksprésikeun dina unit konvénsional nu sarua jeung 1/12 beurat [[isotop]] atom 12[[karbon|C]].\n\n\'\'Tempo ogé:\'\' [[Molekul polar]] jeung [[molekul nonpolar|nonpolar]].\n\n[[ca:Molècula]] [[da:Molekyle]] [[de:Molekül]] [[en:Molecule]] [[eo:molekulo]] [[es:molécula]] [[et:Molekul]] [[fr:Molécule]] [[gl:molécula]] [[id:Molekul]] [[is:Sameind]] [[ja:分子]] [[nds:Molekül]] [[nl:molecuul]] [[simple:Molecule]] [[sl:molekula]] [[sv:Molekyl]] [[zh:分子 (化学)]] [[he:מולקולה]]\n\n[[Category:Kimia]]\n[[Category:Fisika]]','',3,'Kandar','20041218130433','',0,0,0,0,0.568313764207,'20041218130433','79958781869566'); INSERT INTO cur VALUES (1079,0,'Beungkeut_kimia','Dina [[kimia]], \'\'\'beungkeut kimia\'\'\' hartina gaya nu nahan [[atom]]-atom dina [[molekul]] atawa [[kristal]]. Dina molekul-molekul basajan, [[tiori beungkeut valénsi]] jeung konsép [[wilangan oksidasi]] bisa dipaké pikeun ngaduga struktur jeung wangunan molekular. Nya kitu ogé tiori [[fisika klasik]] bisa dipaké pikeun ngaduga struktur-struktur ionik. Pikeun sanyawa nu leuwih pajeulit kayaning [[kompléx]] logam, tiori beungkeut valénsi teu bisa dipaké sarta merlukeun pamahaman nu leuwih jero dumasar [[mékanik kuantum]].\n\nThe spatial characteristics and range of energies encompassed by chemical forces span a continuum, so the terms for the different types of chemical bond overlap in their applicability, but the types include\n\n*[[beungkeut ionik]]\n*[[beungkeut kovalén]]\n*[[beungkeut kovalén koordinat]]\n*[[beungkeut logam]]\n*[[beungkeut hidrogén]].\n\nSadaya beungkeutan kimiawi mucunghulna tina interaksi antar[[éléktron]] ti atom-atom nu béda nu sacara énergétik dipikaresep (nyaéta hémat [[énergi]]). The types of bonding are distinguished by the extent to which electron density is localized or delocalized among the atoms of the substance. \n\nDina kasus beungkeutan ionik, éléktron-éléktron utamana ngahiji jeung salasahiji atomna, sahingga muatan listrikna netep sacara diskrét. The nature of the interatomic (or in fact interionic) forces is largely characterized by [[isotropic]] continuum electrostatic potentials.\n\nSabalikna dina beungkeutan kovalén, sebaran dénsiti éléktron dina beungkeut teu netep di salasahiji atom, tapi didélokalisasi sapanjang molekul dina struktur nu digambarkeun ku tiori kontémporér umum salaku [[orbita molekul]]. Teu siga beungkeut ionik murni, hal ieu ngakibatkeun sipat [[anisotropik]]. Kaayaan panengah (\'\'intermediate\'\') tangtu aya, nalika beungkeutna nunjukkeun campuran antara ciri ionik polar jeung ciri délokalisasi éléktron kovalén.\n\nBeungkeut ionik sacara umum bisa digambarkeun ku [[fisika klasik]], sedengkeun pajeulitna beungkeut kovalén ngandelkeun pisan kana konsép-konsép [[mékanika kuantum]].\n\nSagigireun beungkeut intramolekul nu ngaheuyeuk hiji molekul sangkan ngahiji, [[gaya antarmolekul]] ogé meta dina interaksi antarmolekul hiji zat. \n\n:\'\'Tempo ogé:\'\' [[orbital atom]], [[beungkeut ganda]], [[tabel periodik]]\n\n[[Category:Kimia]]\n\n[[de:Chemische Bindung]]\n[[en:Chemical bond]]\n[[es:enlace químico]]\n[[eo:Kemia ligo]]\n[[fr:Liaison chimique]]\n[[ja:化学結合]]\n[[sl:kemijska vez]]','',3,'Kandar','20041125073038','',0,0,0,0,0.728716825474,'20041125073038','79958874926961'); INSERT INTO cur VALUES (1080,0,'Daptar_jejer_kimia','Kaca ieu ditujukeun pikeun ngadaptar artikel-artikel nu patali jeung [[kimia]]. Ieu ogé dimaksudkeun sangkan nu aya karesep dina subjék ieu bisa ngawaskeun parobahan-parobahan ku jalan ngaklik Parobahan nu Patali di lajursisi jeung handapeun kacana.\n\nIeu bisa jadi teu lengkep atawa mutahir - mun anjeun manggihan artikel nu sakuduna kadaptar di dieu tapi can asup (atawa nu sakuduna teu didaptar tapi aya), dihaturan pikeun ngalengkepan/ngalereskeun.\n\n{{compactTOC}}__NOTOC__\n\n== A ==\n[[Abisit]] — [[Asetaldehid]] — [[Asétaminofén]] — [[Asam asetat]] — [[Aseton]] — [[asetil]] — [[Asetilkolin]] — [[Asetilén]] — [[asam]] — [[Akrilamid]] — [[Aktinid]] — [[Aktinium]] — [[Aktinolit]] — [[Énergi aktivasi]] — [[Adolf Friedrich Johann Butenandt]] — [[Adolf Otto Reinhold Windaus]] — [[Adolph Wilhelm Hermann Kolbe]] — [[Agat]] — [[Ahmed H. Zewail]] — [[Alabaster]] — [[Alan G MacDiarmid]] — [[Alan J Heeger]] — [[Albertus Magnus]] — [[Albit]] — [[Lambang alkémi]] — [[Alkémis]] — [[Alkémi]] — [[alkohol]] — [[aldehid]] — [[Aléksandrit]] — [[Alfred Stock]] — [[Alfred Werner]] — [[sanyawa alisiklik]] — [[sanyawa alifatik]] — [[Alkali]] — [[Logam alkali]] — [[Alkali taneuh]] — [[alkana]] — [[alkéna]] — [[Allingite]] — [[alotrop]] — [[Alotropi]] — [[alloy]] — [[Alum]] — [[Aluminium]] — [[Aluminium gallium arsenida]] — [[Aluminium oksida]] — [[Alunite]] — [[Alvite]] — [[amalgam]] — [[Amazonit]] — [[Amber]] — [[Amblygonite]] — [[Amedeo Avogadro]] — [[Americium]] — [[Amethyst]] — [[amida]] — [[amina]] — [[asam amino]] — [[Amonia]] — [[amonium]] — [[Amonium nitrat]] — [[Amonium perklorat]] — [[Amfibol]] — [[Analcim]] — [[Analsit]] — [[Kimia analitis]] — [[Anatase]] — [[Andalusit]] — [[Andesit]] — [[Anglesit]] — [[Anortit]] — [[Anortosit]] — [[Anortoklas]] — [[Antimoni]] — [[Antoine Lavoisier]] — [[Apatit]] — [[Aquamarine]] — [[Aragonit]] — [[Archer John Porter Martin]] — [[hidrokarbon aromatik]] — [[argon]] — [[Arne Wilhelm Kaurin Tiselius]] — [[amina aromatik]] — [[sanyawa aromatik]] — [[persamaan Arrhenius]] — [[arsenik]] — [[Arthur Harden]] — [[Artturi Ilmari Virtanen]] — [[Arvedsonite]] — [[Asbestos]] — [[Astatin]] — [[atom]] — [[spéktroskopi serapan atom]] — [[massa atom]] — [[unit massa atom]] — [[inti atom]] — [[wilangan atom]] — [[orbital atom]] — [[RAdius atom]] — [[Atomic weight]] — [[Auger electron spectroscopy]] — [[Augite]] — [[Axinite]] — [[Azurite]] —\n\n== B ==\n[[Baddeleyite]] — [[Barit]] — [[Barium]] — [[barométer]] — [[Basalt]] — [[Basa]] — [[Bastnasit]] — [[Batré (listrik)|batré]] — [[Bauksit]] — [[Békerit]] — [[Bénzén]] — [[cingcin bénzén]] — [[Berkelium]] — [[Beril]] — [[Berilium]] — [[bikarbonat]] — [[bioaccumulate]] — [[biokimia]] — [[Bioinformatik]] — [[Biotit]] — [[Bismut]] — [[Boehmit]] — [[Bohrium]] — [[Titik golak]] — [[Boraks]] — [[Asam borat]] — [[Bornit]] — [[boron]] — [[Golongan Boron]] — [[Boron nitrid]] — [[brain]] — [[brass]] — [[bromin]] — [[Brusit]] — [[Leyuran dapar]] — [[Bunsen burner]] — [[Burét]] — [[Burmit]] — [[Butan]] — [[Bytownite]] —\n\n== C ==\n[[cadmium]] — [[Cai]] — [[Calamine]] — [[Calcflinta]] — [[Calcite]] — [[Kalsium|Calcium]] — [[Calcium carbonate]] — [[Calcium oxide]] — [[Californium]] — [[calomel]] — [[Calorimeter]] — [[Canfieldite]] — [[Carbohydrate]] — [[carbon]] — [[carbon dioxide]] — [[Carbon group]] — [[carbon monoxide]] — [[carbonate]] — [[carbonation]] — [[Carbonic acid]] — [[carbonyl]] — [[carboxylic acid]] — [[Carl Bosch]] — [[Carl Remigius Fresenius]] — [[Carl Wilhelm Scheele]] — [[Carnallite]] — [[Carnelian]] — [[Carnotite]] — [[CAS registry number]] — [[Cassiterite]] — [[catalyst]] — [[caustic soda]] — [[Celadonite]] — [[Celestite]] — [[Celsius]] — [[central nervous system]] — [[Cerium]] — [[Cerussite]] — [[Caesium]] — [[Chabasite]] — [[Chalcedony]] — [[Chalcogen]] — [[Chalcopyrite]] — [[Chalcosine]] — [[Chalk]] — [[Charles J. Pedersen]] — [[Chemical bond]] — [[chemical element]] — [[Chemical elements named after people]] — [[Chemical elements named after places]] — [[Chemical equilibrium]] — [[chemical formula]] — [[Chemical nomenclature]] — [[chemical property]] — [[Chemical reaction]] — [[Chemical series]] — [[chemical symbol]] — [[Chemical thermodynamics]] — [[Cheminformatics]] — [[chemist]] — [[chemistry]] — [[Chemistry basic topics]] — [[Chirality]] — [[Chloride]] — [[Chlorin]] — [[chlorine]] — [[Chlorite]] — [[chocolate]] — [[Christian B. Anfinsen]] — [[Chromatography]] — [[Chromite]] — [[Chromium]] — [[Chrysoberyl]] — [[Chrysolite]] — [[cinnabar]] — [[Cinnabarite]] — [[Citric acid]] — [[Citrine quartz]] — [[Clay]] — [[Cleveite]] — [[Coal]] — [[Cobalt]] — [[Coinage metal]] — [[Colemantite]] — [[colloid]] — [[color]] — [[Colorimeter]] — [[Coltan]] — [[Columbite]] — [[Combinatorial chemistry]] — [[Complex]] — [[Chemical compound|compound]] — [[computational chemistry]] — [[Concentration]] — [[condensation polymer]] — [[Condensation reaction]] — [[Cooperite]] — [[Copper]] — [[corderoite]] — [[Cordierite]] — [[Corrin]] — [[corrosion]] — [[Corundum]] — [[cosmetics]] — [[covalent bond]] — [[Covalent radius]] — [[Coveline]] — [[Crocidolite]] — [[Crooksite]] — [[Cryolite]] — [[crystal]] — [[Crystal structure]] — [[cubic metre per mole]] — [[Cumene process]] — [[Cuprite]] — [[Curium]] — [[cyanide]] — [[Cyclopentadiene]] — [[Cylindrite]] — [[Cymophane]] — [[Cytosine]] —\n\n== D ==\n[[d block]] — [[d-block]] — [[Darmstadtium]] — [[Datolite]] — [[decay energy]] — [[decay mode]] — [[decay product]] — [[decomposition temperature]] — [[Delessite]] — [[Density]] — [[Deposition (chemistry)|Deposition]] — [[Derek H. R. Barton]] —[[Deuterium]] — [[diamond]] — [[Diaspore]] — [[Diatomite]] — [[diffusion pump]] — [[Diopside]] — [[Diorite]] — [[Dipole]] — [[Discovery of the chemical elements]] — [[Distillation]] — [[Dmitri Ivanovich Mendeleev]] — [[Dmitrii Mendeleev]] — [[Dmitry Ivanovich Mendeleev]] — [[Dolomite]] — [[Donald J. Cram]] — [[Dorothy Crowfoot Hodgkin]] — [[Dubnium]] — [[Dudley R. Herschbach]] — [[Dysprosium]] —\n\n== E ==\n[[Eduard Buchner]] — [[Edwin Mattison McMillan]] — [[Einsteinium]] — [[Electrical conductivity]] — [[electricity]] — [[Electrochemical cell]] — [[Electrochemistry]] — [[electrode]] — [[Electrode potential]] — [[electrolysis]] — [[Electrolyte]] — [[Electrolytic cell]] — [[electromagnetic spectroscopy]] — [[electron]] — [[electron capture]] — [[Electron configuration]] — [[electron shell]] — [[electron volt]] — [[Electronegativity]] — [[Electrophile]] — [[Element]] — [[Elements song]] — [[Elias James Corey]] — [[Emerald]] — [[Emil Hermann Fischer]] — [[Emil Knoevenagel]] — [[emulsion]] — [[energy level]] — [[Enthalpy]] — [[Entropy]] — [[environmental chemistry]] — [[Enzyme]] — [[Epidiorite]] — [[Epinephrine]] — [[Epoxyethane]] — [[Epsom salt]] — [[Erbium]] — [[Ernest Rutherford]] — [[Ernst Otto Fischer]] — [[ester]] — [[Ethanol]] — [[ethene]] — [[ether]] — [[Europium]] — [[Euxenite]] — [[explosive]] —\n\n== F ==\n[[f block]] — [[f-orbital]] — [[F. Sherwood Rowland]] — [[Fahrenheit]] — [[Fat]] — [[Feldspar]] — [[Felsic]] — [[Ferberite]] — [[Fergusonite]] — [[Fermium]] — [[Ferrocene]] — [[Filtration]] — [[Flint]] — [[Fluorapatite]] — [[fluorescence spectroscopy]] — [[fluorine]] — [[Fluorite]] — [[Fluorspar]] — [[Formaldehyde]] — [[Formic acid]] — [[Fractional freezing]] — [[Francis William Aston]] — [[Francium]] — [[Francois Auguste Victor Grignard]] — [[Frankeite]] — [[Franklinite]] — [[Franz Joseph Emil Fischer]] — [[Frederick Sanger]] — [[Frederick Soddy]] — [[freezing point]] — [[Friedrich Bergius]] — [[Friedrich Woehler]] — [[Fritz Haber]] — [[Fritz Pregl]] — [[Frédéric Joliot]] — [[functional group]] — [[fur]] —\n\n== G ==\n[[Gabbro]] — [[Gadolinite]] — [[Gadolinium]] — [[Galena]] — [[gallium]] — [[Gallium arsenide]] — [[Garnet]] — [[gas]] — [[gaseous]] — [[Gedanite]] — [[Geoffrey Wilkinson]] — [[Georg Wittig]] — [[George A. Olah]] — [[George de Hevesy]] — [[George Porter]] — [[Gerhard Herzberg]] — [[Germanite]] — [[Germanium]] — [[Gibbsite]] — [[Gilbert Stork]] — [[Giulio Natta]] — [[Glauconite]] — [[Glenn T. Seaborg]] — [[Glessite]] — [[Glucose]] — [[Glycerine]] — [[Glycine]] — [[Gneiss]] — [[Goethite]] — [[gold]] — [[Granite]] — [[Graphite]] — [[Group 1 element]] — [[Group 10 element]] — [[group 12 element]] — [[Group 2 element]] — [[Group 3 element]] — [[Group 4 element]] — [[Group 5 element]] — [[Group 6 element]] — [[Group 7 element]] — [[Group 8 element]] — [[Group 9 element]] — [[Gypsum]] —\n\n== H ==\n[[H. M. Rouell]] — [[Hafnium]] — [[half-life]] — [[Halite]] — [[halogen]] — [[halogenoalkane]] — [[Hans Fischer]] — [[Hans Karl August Simon von Euler-Chelpin]] — [[Harold Clayton Urey]] — [[Harold Kroto]] — [[Hartmut Michel]] — [[Hassium]] — [[heat]] — [[Heat of fusion]] — [[Heat of vaporization]] — [[Heavy metal (chemistry)]] — [[Heinrich Otto Wieland]] — [[Helium]] — [[Hematite]] — [[Henri Louis le Chatelier]] — [[Henri Moissan]] — [[Henry Taube]] — [[Heptane]] — [[Herbert A. Hauptman]] — [[Herbert C. Brown]] — [[Hermann Emil Fischer]] — [[Hermann Staudinger]] — [[heterocyclic compound]] — [[Hexane]] — [[Hiddenite]] — [[Hideki Shirakawa]] — [[Histidine]] — [[Holmium]] — [[Hornblende]] — [[Huebnerite]] — [[Humphry Davy]] — [[Hund\'s rule]] — [[Hutchinsonite]] — [[Hyalite]] — [[Hydrazine]] — [[hydrocarbon]] — [[Hydrochloric acid]] — [[hydrogen]] — [[Hydrogen bond]] — [[Hydrogen cyanide]] — [[Hydrogen peroxide]] — [[Hydrogen sulfide]] — [[Hydrolysis]] — [[hydroxide]] — [[hydroxyl]] —\n\n== I ==\n[[ice]] — [[Idocrase]] — [[Illite]] — [[Ilmenite]] — [[Ilya Prigogine]] — [[Indium]] — [[infrared spectroscopy]] — [[Inorganic chemistry]] — [[Intermolecular force]] — [[International Temperature Scale]] — [[International Union of Pure and Applied Chemistry]] — [[Iodine]] — [[Ion]] — [[Ionic bond]] — [[ionization potential]] — [[Irene Joliot-Curie]] — [[Iridium]] — [[iron]] — [[Iron (III) oxide]] — [[Irving Langmuir]] — [[isocyanate]] — [[Isomer]] — [[isotope]] — [[Isotope table (complete)]] — [[Isotope table (divided)]] — [[Israel Shahak]] — [[IUPAC]] —\n\n== J ==\n[[J. H. van\'t Hoff]] — [[Jade]] — [[James Batcheller Sumner]] — [[James Dewar]] — [[Jaroslav Heyrovsky]] — [[Jasper]] — [[Jean-Marie Lehn]] — [[Jens C. Skou]] — [[Jerome Karle]] — [[Johann Deisenhofer]] — [[Johann Friedrich Wilhelm Adolf von Baeyer]] — [[Johann Wolfgang Döbereiner]] — [[Johannes Diderik van der Waals]] — [[John A. Pople]] — [[John Alexander Reina Newlands]] — [[John C. Polanyi]] — [[John Cowdery Kendrew]] — [[John Dalton]] — [[John E. Walker]] — [[John Ernest Walker]] — [[John Fenn]] — [[John Howard Northrop]] — [[John Pople]] — [[John Warcup Cornforth]] — [[Jons Jacob Berzelius]] — [[Joseph Priestley]] — [[joule per kilogram-kelvin]] — [[Justus von Liebig]] —\n\n== K ==\n[[K. Barry Sharpless]] — [[Kainit]] — [[Kalsilit]] — [[Kamasit]] — [[Kaolinit]] — [[Karl Ziegler]] — [[Kary Mullis]] — [[Keilhauite]] — [[Kelvin]] — [[Kenichi Fukui]] — [[Kernit]] — [[keton]] — [[kilogram per méter kubik]] — [[kilojoule per mol]] — [[Kimberlit]] — [[Kimia analitis]] — [[Kimia bahan padet]] — [[Kimia kuantum]] — [[Kimia organik]] — [[kinetika]] — [[Kobellit]] — [[Koichi Tanaka]] — [[Krantzit]] — [[kripton]] — [[Kunzit]] — [[Kurt Alder]] — [[Kurt Heinrich Meyer]] — [[Kurt Wüthrich]] — [[Kianit]] —\n\n== L ==\n[[Labradorite]] — [[Lactic acid]] — [[Lanthanide]] — [[Lanthanum]] — [[Lapis lazuli]] — [[Lars Onsager]] — [[Lawrencium]] — [[Lazurite]] — [[Le Chatelier\'s principle]] — [[Lead]] — [[Leopold Ruzicka]] — [[Lepidolite]] — [[Leucite]] — [[Ligand]] — [[Lignite]] — [[Limestone]] — [[Limonite]] — [[Linus Pauling]] — [[liquid]] — [[Lise Meitner]] — [[List of biochemistry topics]] — [[List of chemists]] — [[list of compounds]] — [[List of elements by name]] — [[List of elements by number]] — [[List of elements by symbol]] — [[Chemical elements named after people|List of elements named after people]] — [[Chemical elements named after places|List of elements named after places]] — [[Lithium]] — [[liver]] — [[livingstonite]] — [[Lodestone]] — [[Lonsdaleite]] — [[Lorandite bertrandite]] — [[Lord Alexander R. Todd]] — [[Lothar Meyer]] — [[Louis Pasteur]] — [[Luis F. Leloir]] — [[Lutetium]] —\n\n== M ==\n[[Magnesite]] — [[Magnesium]] — [[magnetic resonance]] — [[magnetism]] — [[Magnetite]] — [[Malachite]] — [[Malacolite]] — [[Manfred Eigen]] — [[Manganese]] — [[Marble]] — [[Marcasite]] — [[Marie Curie]] — [[Marie Sklodowska-Curie]] — [[Mario J. Molina]] — [[Marl]] — [[mass]] — [[mass spectrometer]] — [[materials science]] — [[Max Ferdinand Perutz]] — [[medicine]] — [[Meerschaum]] — [[mega]] — [[Meitnerium]] — [[Melting point]] — [[Melvin Calvin]] — [[Mendelevium]] — [[Mendozite]] — [[Menilite]] — [[Mercury (II) sulfide]] — [[Mercury (I) chloride]] — [[Mercury (element)]] — [[Mercury (II) chloride]] — [[mercury fulminate]] — [[mercury-vapor lamp]] — [[Metacinnabarite]] — [[metal]] — [[metal halide]] — [[Metallic bond]] — [[Metalloid]] — [[Methane]] — [[Methanol]] — [[methyl]] — [[Methyl isocyanate]] — [[Methyl mercury]] — [[methylene]] — [[metre per second]] — [[Mica]] — [[Michael Faraday]] — [[Michael Smith (chemist)]] — [[Microcline]] — [[Milk quartz]] — [[millinery]] — [[mineral]] — [[mineralogy]] — [[mixture]] — [[Mohs hardness scale]] — [[Molar volume]] — [[mole (unit)]] — [[Molecular dynamics]] — [[Molecular mechanics]] — [[Molecular modeling]] — [[Molecular orbital]] — [[molecule]] — [[Molybdenite]] — [[Molybdenum]] — [[Monazite]] — [[Morganite]] — [[Mossbauer spectroscopy]] — [[Muscovite]] — [[Mustard gas]] —\n\n== N ==\n[[Naphthalene]] — [[natural abundance]] — [[Neodymium]] — [[neon]] — [[Nephiline]] — [[Neptunium]] — [[Nernst equation]] — [[neutron]] — [[neutron activation analysis]] — [[Nickel]] — [[Nikolay Nikolaevich Semenov]] — [[Nils Gabriel Sefström]] — [[Niobite]] — [[Niobite-tantalite]] — [[Niobium]] — [[nitrate]] — [[Nitric acid]] — [[Nitric oxide]] — [[nitrogen]] — [[Nitroglycerine]] — [[Nitrous oxide]] — [[Nobel Prize in Chemistry]] — [[Nobelium]] — [[Noble gas]] — [[Nonmetal]] — [[nuclear magnetic resonance]] — [[Nucleic Acid]] — [[Nucleophile]] —\n\n== O ==\n[[Octane]] — [[octave]] — [[Odd Hassel]] — [[ohm]] — [[Olivine]] — [[Opal]] — [[Optical isomerism]] — [[Orbitals]] — [[Organic chemistry]] — [[organic compound]] — [[Organic nomenclature]] — [[Organic reaction]] — [[Orthoclase]] — [[Osmium]] — [[Osmium tetroxide]] — [[Otto Hahn]] — [[Otto Paul Hermann Diels]] — [[Otto Wallach]] — [[Oxidation]] — [[Oxidation number]] — [[oxidation state]] — [[oxide]] — [[oxygen]] —\n\n== P ==\n[[p block]] — [[paint]] — [[Palagonite]] — [[Palladium]] — [[Partial pressure]] — [[Pascal]] — [[Paul Berg]] — [[Paul D. Boyer]] — [[Paul J. Crutzen]] — [[Paul J. Flory]] — [[Paul Karrer]] — [[Paul Sabatier]] — [[Pauling scale]] — [[Pegmatite]] — [[Pentlandite]] — [[Peptide]] — [[perchlorate]] — [[Peridotite]] — [[Period 1 element]] — [[Period 2 element]] — [[Period 3 element]] — [[Period 4 element]] — [[Period 5 element]] — [[period 6 element]] — [[Period 7 element]] — [[periodic table]] — [[periodic table block]] — [[periodic table group]] — [[periodic table period]] — [[Periodic table series]] — [[Periodic table/Alternate Table]] — [[Periodic table/Big Table]] — [[Periodic table/Electron configurations]] — [[Extended periodic table]] — [[Periodic table/Huge Table]] — [[Periodic table/Metals and Non Metals]] — [[Periodic table/Standard Table]] — [[Periodic table/Wide Table]] — [[Periodicity]] — [[Perlite]] — [[pesticide]] — [[Petalite]] — [[Peter D. Mitchell]] — [[Peter Debye]] — [[pH]] — [[phases of matter]] — [[Phenacite]] — [[phenol]] — [[phenyl]] — [[Phlogopite]] — [[Phosphorite]] — [[Phosphorus]] — [[Phthalates]] — [[Phyllite]] — [[Physical chemistry]] — [[physics]] — [[physiologically active compound]] — [[picometre]] — [[Picric acid]] — [[Pitchblende]] — [[Plagioclase]] — [[Platinum]] — [[Plivine]] — [[Plutonium]] — [[Pnictogen]] — [[Pollucite]] — [[pollution]] — [[Polonium]] — [[polymer]] — [[Polymerization]] — [[Poor metal]] — [[Porphyrin]] — [[Potassium]] — [[Potassium nitrate]] — [[Praseodymium]] — [[Prehnite]] — [[Promethium]] — [[Propane]] — [[Protactinium]] — [[Protein]] — [[Proton]] — [[Pumice]] — [[Pumicite]] — [[Purine]] — [[Putrescine]] — [[Pyridine]] — [[Pyrimidine]] — [[Pyrite]] — [[Pyrochlore]] — [[Pyroxene]] — [[Pyrrole]] —\n\n== Q ==\n[[quantum chemistry]] — [[Quartz]] — [[Quartzite]] —\n\n== R ==\n[[Radioisotop]] — [[Radium]] — [[Radius atom]] — [[Radon]] — [[Radon florid]] — [[Raoult\'s law]] — [[Réaksi kimiawi]] — [[Rédoks]] — [[Réduksi]] — [[Reflux]] — [[Reversible reaction]] — [[Rhazes]] — [[Rhenium]] — [[Rhodium]] — [[Rhyolite]] — [[Rhyolitic]] — [[Richard Adolf Zsigmondy]] — [[Richard Kuhn]] — [[Richard Laurence Millington Synge]] — [[Richard Martin Willstätter]] — [[Richard R. Ernst]] — [[Richard Smalley]] — [[Riebeckite]] — [[Roald Hoffmann]] — [[Robert Bruce Merrifield]] — [[Robert Burns Woodward]] — [[Robert Curl]] — [[Robert G. Parr]] — [[Robert Huber]] — [[Robert S. Mulliken]] — [[Robert Wilhelm Bunsen]] — [[Rock crystal]] — [[Ronald George Wreyford Norrish]] — [[Rose quartz]] — [[Roumanite]] — [[Rubidium]] — [[Ruby (gemstone)]] — [[Rudolph A. Marcus]] — [[Rudolph Pariser]] — [[Ruthenium]] — [[Rutherfordium]] — [[Rutile]] — [[Ryoji Noyori]] —\n\n== S ==\n[[s block]] — [[s-orbital]] — [[S.P.L. Sørensen]] — [[salt]] — [[Saltpetre]] — [[Salvinorin-A]] — [[Samarium]] — [[Samarskite]] — [[Sand]] — [[Sapphire]] — [[Sard]] — [[Scandium]] — [[Scheelite]] — [[Schist]] — [[scientific notation]] — [[Seaborgium]] — [[Selenium]] — [[semikonduktor]] — [[Serpentin]] — [[SI]] — [[Sidney Altman]] — [[Silan]] — [[silikon]] — [[Silikon dioxida]] — [[Sillimanite]] — [[silver]] — [[Simetite]] — [[Sir Cyril Norman Hinshelwood]] — [[Sir Robert Robinson]] — [[Sir William Ramsay]] — [[skeletal formula]] — [[skin]] — [[Smectite]] — [[Smoky quartz]] — [[Soapstone]] — [[Soda niter]] — [[Natrium|sodium]] — [[Natrium bikarbonat|Sodium bikarbonat]] — [[Natrium karbonat|Sodium karbonat]] — [[Natrium klorida|Sodium klorida]] — [[Natrium sianida|Sodium sianida]] — [[Natrium hidroxida|Sodium hidroxida]] — [[Natrium hipoklorit|Sodium hipoklorit]] — [[solid]] — [[soluble]] — [[solution]] — [[solvation]] — [[solvent]] — [[Specific heat capacity]] — [[Spéktroskopi]] — [[Spéktroskopi Raman]] — [[Speed of sound]] — [[Sperrylite]] — [[Spinel]] — [[Spodumeme]] — [[stable isotope]] — [[standard temperature and pressure]] — [[Standard Ambient Temperature and Pressure]] — [[Stanford Moore]] — [[Stanite]] — [[Stantienite]] — [[State of matter]] — [[Staurolite]] — [[Steatite]] — [[Stereochemistry]] — [[Stoichiometry]] — [[Strontianite]] — [[Strontium]] — [[structural formula]] — [[Sublimation (chemistry)|Sublimation]] — [[sulfate]] — [[sulfur]] — [[Sulfur dioxide]] — [[Sulphuric acid]] — [[superconductor]] — [[surface chemistry]]— [[suspension (chemistry)]] — [[Svante Arrhenius]] — [[Syenite]] — [[Sylvite]] — [[synthetic radioisotope]] — [[systematic element name]] —\n\n== T ==\n[[Tabun]] — [[Talc]] — [[Talcum]] — [[Tantalite]] — [[Tantalum]] — [[Tanzanite]] — [[Teallite]] — [[Technetium]] — [[Telluride]] — [[Tellurium]] — [[Terbium]] — [[Tetryl]] — [[Thallium]] — [[Theodor Svedberg]] — [[Theodore William Richards]] — [[Thermal conductivity]] — [[Thermochemistry]] — [[thermometer]] — [[Thiamin]] — [[thioether]] — [[Thomas Graham]] — [[Thomas R. Cech]] — [[Thorium]] — [[Thortveitite]] — [[Thulium]] — [[Timeline of biology and organic chemistry]] — [[Tin]] — [[Titanite]] — [[Titanium]] — [[Titanium dioxide]] — [[Titration]] — [[Toluene]] — [[Topaz]] — [[Tourmaline]] — [[toxic]] — [[transition metal]] — [[Tremolite]] — [[Trinitrotoluene]] — [[triple point]] — [[Troctolite]] — [[Tuff]] — [[Tungsten]] — [[Turquoise]] — [[Tutty]] — [[Tyrosine]] —\n\n== U ==\n[[Ulexite]] — [[UN number]] — [[Ununbium]] — [[Ununhexium]] — [[Ununoctium]] — [[Ununpentium]] — [[Ununquadium]] — [[Ununseptium]] — [[Ununtrium]] — [[Unununium]] — [[Uralite]] — [[Uraninite]] — [[Uranium]] — [[Urea]] — [[Uric acid]] — [[UV/VIS spectroscopy]] —\n\n== V ==\n[[Valence]] — [[van der Waals radius]] — [[van der Waals\' force]] — [[Vanadium]] — [[Vapor pressure]] — [[Vapour pressure]] — [[vermilion]] — [[Victor Grignard]] — [[Viktor Meyer]] — [[Vincent du Vigneaud]] — [[Vinyl]] — [[Vladimir Prelog]] — [[Vladimir Vasilevich Markovnikov]] —\n\n== W ==\n[[Walter Gilbert]] — [[Walter Kohn]] — [[Walter Norman Haworth]] — [[Walther Hermann Nernst]] — [[watt per metre-kelvin]] — [[Wendell Meredith Stanley]] — [[Wilhelm Ostwald]] — [[Willard Frank Libby]] — [[Willemite]] — [[William Francis Giauque]] — [[William H. Stein]] — [[William Hardin Graham]] — [[William Hyde Wollaston]] — [[William Lipscomb]] — [[William S. Knowles]] — [[Wiserine]] — [[Wolframite]] — [[Wollastonite]] —\n\n== X ==\n[[X-ray photoelectron spectroscopy]] — [[xenon]] — [[Xenotine]] —\n\n== Y ==\n[[YBCO]] — [[Ytterbium]] — [[Yttria]] — [[Yttrium]] — [[Yuan T. Lee]] —\n\n== Z ==\n[[Zéolit]] — [[zinc]] — [[Zinnwaldite]] — [[Zircon]] — [[Zirconium]] — [[Zone melting]] — [[Zyklon B]] — [[Zymology]] —\n\n[[Category:Kimia]]\n[[Category:Daptar jejer]]\n\n[[en:List of chemistry topics]]\n[[fr:Liste des articles de chimie]]\n[[ja:化学に関する記事の一覧]]\n[[sl:Seznam kemijskih vsebin]]','/* K */',3,'Kandar','20050127061806','',0,0,0,0,0.294350976261,'20050127061806','79949872938193'); INSERT INTO cur VALUES (1081,0,'Apoptosis','\'\'\'Apoptosis\'\'\' ngarupakeun tipe utama [[program paéh sél]] (\'\'programmed cell death\'\', PCD), nyaéta hiji prosés [[maéhan manéh]] nu ngahaja ku sél nu teu dipikabutuh dina [[organisme]] multisélular. Sabalikna ti [[nékrosis]], nu sélna paéh alatan tatu jaringan akut, apoptosis lumangsung dina prosés nu teratur sahingga sacara umum nguntungkeun pikeun daur hirup organisme. Pikeun conto, diferensiasi [[ramo]] [[manusa]] na émbrio nu keur tumuwuh merlukeun apoptosis sél na sela-sela ramo sahingga ramo-ramona bisa misah. Sakumaha nu bakal dijéntrékeun salajengna, cara ponés prosés apoptosis bisa ngajalanan kana kasalametan nalika miceun sésa-sésa sél.\nTeu sadaya PCD mibanda bentuk ciri ([[morfologi]]) sarta runtuyan sarupa apoptosis, tapi sadaya tipe PCD pasti ngarupakeun prosés nu diatur. \n\n== Fungsi apoptosis ==\n\n=== Karuksakan sél atawa inféksi ===\nApoptosis bisa lumangsung, singgetna, nalika hiji sél ruksak satutasna diropéa, atawa kainféksi [[virus (biologi)|virus]]. \"Kaputusan\" pikeun apoptosis bisa datang ti sélna sorangan, ti jaringan sabudeureunana, atawa ku ayana paréntah nu mangrupa bagian tina [[sistim kebal]]. \n\nMun kamampuh apoptosis sél ruksak (misalna alatan [[mutasi]]), atawa inisiasi spoptosis dipeungpeuk (ku virus), sél nu ruksak bisa tetep meulah diri kalawan teu kapegung, nu ngakibatkeun [[kangker]]. Pikeun conto, sangkan [[papillomavirus manusa|papillomavirus]] bisa ngabajak sistim genetik sél (\'\'human papillomavirus\'\', HPV), hiji gén nu disebut \'\'E6\'\' diéksprésikeun jadi produk nu ngancurkeun protéin [[gén p53|p53]], nu ngarupakeun hiji bagian penting jalur apoptotik. Gangguan nu parah na kamampuhan apoptotik sél ieu maénkeun peran kritis sabab mun inféksi HPV onkogenik ieu kateterusan bisa ngakibatkeun kangker sérvik (tempo \"Integration of interferon-alpha/beta signaling to p53 responses in tumor suppression and antiviral defense\", ku Akinori Takaoka \'\'et al\'\'., \'\'\'Nature\'\'\' Vol. 424, nomer 6948, 31 Juli 2003, hal. 517).\n\n=== Ketak nyanghareupan strés atawa karuksakan DNA ===\nKaayaan stres --kayaning kalaparan-- sakumaha karuksakan DNA sél --alatan karacunan atawa paparan radiasi pangion, kayaning sinar-X atawa ultrabungur-- bisa micu sél pikeun ngamimitian prosés apoptotik. Salasahiji contona, nu dialatankeun ku ruksakna génom na inti sél, nyéta sél nu maéhan manéh nu dipicu ku énzim poli(ADP-ribosa) polimérase-1 inti, or PARP-1. Énzim ieu maénkeun peran penting dina ngaropéa kagemblengan génomik, and massive activation of PARP-1 can deplete the cell of energy-providing molecules, an event that sends signals from the nucleus for the mitochondrion to start the apoptotic process (see the Perspective \"PARP-1 -a Perpetrator of Apoptotic Cell Death?\", by Alberto Chiarugi and Michael A. Moskowitz, in \'\'[[Science (journal)|Science]]\'\', Vol. 297, No. 5579, p. 200, and the research report by Seong-Woon Yu, \'\'et al.\'\', in p. 259, in the same issue).\n\n=== Homeostasis ===\nIn the adult organism, the number of cells within an [[organ (anatomy)|organ]] or tissue has to be constant within a certain range. Blood and skin cells, for instance, are constantly renewed by their respective progenitor cells; but this proliferation has to be compensated by cell death. This balancing process is part of the \'\'[[homeostasis]]\'\' required by living organisms to maintain their internal states within certain limits. Some authors and researchers like Steven Rose and [[Antonio Damasio]] have suggested \'\'homeodynamics\'\' as a more accurate and elocuent term (see Damasio: \'\'The Feeling of What Happens\'\', Harcourt Brace & Co., New York, 1999, p. 141). \n\nFrom 50 to 70 billion cells die each day due to apoptosis in the average human adult. In a year, this amounts to the proliferation and subsequent destruction of a mass of cells equal to an individual\'s body weight (see \"Cell Proliferation, Differentiation, and Apoptosis\" by Michael Andreeff \'\'et al.\'\' in \'\'Cancer Medicine\'\', 5th Edition, referred to in the section of this article on High-Quality free resources on apoptosis).\n\nHomeostasis is achieved when the rate of [[mitosis]] (cell proliferation) in the tissue is balanced by cell death. If this equilibrium is disturbed, either of two things happen:\n* The cells are dividing faster than they die, effectively developing a [[tumor]].\n* The cells are dividing slower than they die, which results in a disorder of cell loss.\nBoth states can be fatal or highly damaging (see \"Apoptosis in the Pathogenesis and Treatment of Desease\", by Craig B. Thompson, in \'\'Science\'\', Vol. 267, p. 1456, Mar. 10, 1995). \n\nFor instance, misregulation of Hedgehog (Hgg) protein signalling (see subsection on Development, below) has been implicated in several forms of cancer. Hgg, which conveys an anti-apoptotic signal, has been found to be overexpressed in pancreatic adenocarcinoma tissues (see \"Hedgehog is an early and late mediator of pancreatic cancer tumorigenesis\" by Sarah P. Thayer \'\'et al.\'\', \'\'Nature\'\' Vol. 425, pgs. 851-856, Oct. 23, 2003).\n\n=== Development ===\nProgrammed cell death is an integral part of both plant and [[metazoa]] (multicellular animals) [[biological tissue|tissue]] [[developmental biology|development]], and it does not elicit the inflammatory response which is characteristic of [[necrosis]] (on metazoa, see \"Mechanisms and Genes of Cellular Suicide\", by Hermann Steller, \'\'Science\'\' Vol. 267, Mar. 10, 1995, p. 1445; on plants, see references in the section below on programmed cell death in plant tissue). In other words, apoptosis does not resemble the sort of reaction that comes as a result of tissue damage due to accident or [[pathogen]]ic infection. Instead of swelling and bursting --and, hence, spilling their possibly damaging internal contents into extracellular space--, apoptotic cells and their [[cell nucleus|nuclei]] shrink, and often fragment. In this way, they can be efficiently [[phagocytose]]d (and, as a consequence of this, their components reused) by [[macrophage]]s or by neighboring cells.\n\nResearch on chick embryos -- specifically on chick neural tube development -- has suggested how selective cell proliferation, combined with selective apoptosys, sculpts developing tissues in vertebrates. During vertebrate embryo development, structures called the notocord and the floor plate secrete a gradient of the signaling molecule [[Sonic hedgehog]] (Shh), and it is this gradient that directs cells to form patterns in the embryonic neural tube: cells that receive Shh in a receptor in their membranes called Patched1 (Ptc1) survive and proliferate; but, in the absence of Shh, one of the ends of this same Ptc1 receptor (the carboxyl-terminal, inside the membrane) is cleaved by caspase-3, an action that exposes an aptotosys-producing domain. (See the Perspective \"Longing for Ligand: Hedgehog, Patched, and Cell Death\", by Isabel Guerrero and Ariel Ruiz i Altaba, in \'\'Science\'\' Vol. 301, No. 5634, p. 774; and the research report \"Inhibition of Neuroepithelial Patched-Induced Apoptosis by Sonic Hedgehog\" by Chantal Thibert, \'\'et al.\'\', in p. 843 of that same issue, Aug. 8, 2003).\n\nResearch like the one carried out by Thibert and her colleagues has begun to clarify some of the fundamental aspects of [[morphogenesis]], or the development of organisms from fertilized eggs to fully-developed animals and plants. It has also suggested specific answers to why normal cells carry out apopotosis when they end up outside the places they should be in body tissues.\n\n=== Pangaturan sél kebal ===\n[[B cell]]s and [[T cell]]s are sophisticated –and very effective– front-line players in the body\'s defenses against infectious agents, as well as against local cells that have acquired or developed a malignancy. In order to carry out their job, B ant T cells must have the ability to discriminate \"self\" from \"nonself\", and \"healthy\" from \"unhealthy\" [[antigen]] (protein segments that make a good fit, like a key and a lock, with specialized receptors in B and T cell membranes). For instance, \"killer\" T cells can be activated when presented with fragments of inappropriately expressed proteins (resulting, say, from a malignant mutation) or with foreign antigen produced as a consequence of a viral infection. After becoming activated, they migrate out of the lymph nodes in which they reside, proliferate, recognize the affected cells and commit them to programmed cell death. \n\nThe receptors in immature B and T cell membranes are not tailored precisely to coincide with \"known\" antigen. Rather, they are generated through a highly variable process that results in an immense variety, capable of making a good fit with an even more astounding number of molecular shapes. This means that most of these immature cells can be either ineffective (because their almost random shapes do not engage any antigen of significance), or dangerous to their own organism, because their receptors could make a good molecular fit with healthy self antigen. If they would be let loose without any further processing, many could become \'\'autoreactive\'\' and attack healthy body cells. The way the immune system regulates this process is by \"deleting\" both the ineffective and the potentially damaging immature cells via apoptosis. \n\nAs has just been described in the previous section on development, all tissue in multicellular animals depends on continuous receipt of survival signals. In the case of T cells, as they develop and mature in the thymus, the survival signal depends on their capability to engage foreign antigen. Those that fail in this test, amounting to about 97% of the freshly produced T cells, are committed to programmed cell death. The survivors are tested as well for potentially damaging autoimmune reactions, and those that show high affinity to healthy self antigen are killed via apoptosis. (See \"Signaling Life and Death in the Thymus: Timing Is Everything\", a Perspective by Guy Werlen \'\'et al.\'\', \'\'Science\'\', Vol. 299, p. 1859, 21 March 2003.) \n\nBe aware that the above paragraphs present a highly simplified picture: the actual process in which B and T cells are driven to proliferation, differentiation or apoptosis comprises a complex interplay between positive and negative regulators (see \"Control of T Cell Function by Positive and Negative Regulators\", a Viewpoint by Andrew L. Singer and Gary A. Koretzky, \'\'Science\'\', Vol. 296, p. 1639 31 May 2002).\n\n== Prosés apoptotik ==\n\n=== Morfologi ===\nA cell undergoing apoptosis shows a characteristic morphology that can be seen under a [[microscope]]:\n# The cell becomes round (circular). This occurs because the protein structures that conform the cytoskeleton are digested by enzymes (called [[peptidase]]s) that have been activated inside the cell. \n# Its nucleus and the [[DNA]] inside it undergo condensation.\n# Its DNA is fragmented, the nucleus is broken into several discrete \'\'[[chromatin]] bodies\'\' due to the degradation of DNA between [[nucleosome]]s while preserving the DNA associated with them.\n# The cell is phagocytosed, \'\'or\'\',\n# The cell breaks apart into several [[vesicle]]s called \'\'apoptotic bodies\'\'.\n\n(See the afore-quoted article by Craig B. Thompson, in \'\'Science\'\' Vol. 267, 1995.)\n\n=== Sinyal biokimiawi pikeun \'\'safe disposal\'\' ===\nThe dying cells that have just been described display \"eat me\" signals, like phosphatidylserine (PS, a phospholipid from the inner cell-membrane). Phagocytic scavengers, such as macrophages, have specialized receptors that recognize PS and carry out their disposal job in an orderly manner without eliciting an inflammatory response. (See the Perspective \"Eat me or die\", by Savill \'\'et al.\'\', in \'\'Science\'\', Vol. 302, p. 1516, Nov. 28, 2003, and the corresponding research articles on new work by Li \'\'et al.\'\', and Wang \'\'et al.\'\' in the same issue of \'\'Science\'\'.)\n\nIn the studies on mouse embryos lacking PS receptors (\"PSR knockout mice\") \nconducted by Li and colleagues, un-ingested cells undergoing apoptosis accumulated in the brain and lungs, leading to neonatal lethality. These studies show how critical is the role of PS receptor (PSR) in the development of complex organisms such as mammals.\n\n=== Intrinsic and extrinsic inducers ===\nApoptotic messages from outside the cell (called \'\'extrinsic\'\' inducers) will be described in the next section, on biochemical execution of apoptosis. \n\nApoptotic messages from inside the cell (\'\'intrinsic\'\' inducers) are a response to stress, such as nutrient deprivation or DNA damage, as explained by Chiarugi and Moskowitz in their previously mentioned article on PARP-1.\n\nBoth extrinsic and intrinsic pathways have in common the activation of \'\'central effectors of apoptosis\'\', a group of cysteine proteases called \'\'[[caspase|caspases]]\'\', which carry out the cleaving of both structural and functional elements of the cell, resulting in the previously described morphological changes.\n\n=== Éksékusi biokimiawi ===\nCaspases are normally suppressed by [[inhibitor of apoptosis protein|IAP]] (inhibitor of apoptosis) proteins (see \"Controlling the Caspases\", by Stephen W. Fesik and Yigong Shi, in \'\'Science\'\', Vol. 294, No. 5546, p. 1477, November 16, 2001). When a cell receives an apoptotic stimulus, IAP activity is relieved after SMAC (Second Mitochondria-derived Activator of Caspases, or its mouse homolog, called DIABLO), a [[mitochondrion|mitochondrial]] protein, is released into the [[cytosol]]. SMAC binds to IAPs, and in doing so \"inhibits the inhibitors\", effectively preventing them from arresting the apoptotic process. \n\nBut before we go on to a short description of how SMAC is released, lets take a look at two well-studied extrinsically induced apoptotic processes: the TNF and the Fas pathways. Keep in mind, however, that both activating and inhibiting factors are present at each step of these pathways. \n\nTumor necrosis factor ([[TNF]]), a 157 amino acid inter-cellular signaling molecule ([[cytokine]]) produced mainly by activated macrophages, and is the major extrinsic mediator of apoptosis. The cell membrane has two specialized receptors for TNF: TNF-R1 and TNF-R2. The binding of TNF to TNF-R1 has been shown to fire-off the pathway that leads to activating the caspases (see \"TNF-R1 Signaling: A Beautiful Pathway\", by Guoqing Chen and David V. Goeddel, in \'\'Science\'\', Vol. 296, No. 5573, p. 1634). \n\nFas (\'\'a.k.a.\'\' Apo-1 or CD95), is another receptor of extrinsic apoptotic signals in the cell membrane, and belongs to the TNF receptor superfamily. (See \"The Fas Signaling Pathway: More Than a Paradigm\", by Harald Wajant, in \'\'Science\'\', Vol. 296, No. 5573, p. 1635, May 31, 2002). The Fas ligand (FasL, the protein that binds to Fas and activates the Fas pathway) is a transmembrane protein, and is part of the TNF family. The interaction between Fas and FasL results in the formation of the death-inducing signaling complex (DISC), which contains the Fas-associated death domain protein (FADD) and caspases 8 and 10. In some types of cells (type I), processed caspase-8 directly activates other members of the caspase family, and triggers the execution of apoptosis; while in other types of cells (type II), the Fas DISC starts a feed-back loop that spirals into increasing release of pro-apoptotic factors from mitochondria (see below), and the amplified activation of caspase-8.\n\nDownstream from TNF-R1 and Fas activation --at least in mammalian cells-- the proapoptotic molecules BAK and BAX are required in order to make the mitchondrial membrane permeable for the release of caspase activators. Just how BAX and BAK are controlled under the normal conditions of cells that are not undergoing apoptosis, is incompletely understood. But it has been found that a mitochondrial outer-membrane protein, VDAC2, interacts with BAK to keep this potentially lethal apoptotic effector under control. When the death signal is received, products of the activation cascade --such as tBID, BIM or BAD-- displace VDAC2: BAK and BAX are activated, and the mitochondrial outer-membrane becomes permeable. This results in the release of caspase activators, including cytochrome c (see \"[[Bcl-2]] inhibits Bax translocation from cytosol to mitochondria during drug-induced apoptosis of human tumor cells\", by Murphy, K.M., \'\'et al.\'\', in \'\'Nature Cell Death and Differentiation\'\', Vol. 7, No. 1, Jan. 2000, p. 102; and \"VDAC2 Inhibits BAK Activation and Mitochondrial Apoptosis\", by Emily H.-Y. Cheng, Tatiana V. Sheiko, \'\'et al.\'\', in \'\'Science\'\', Vol. 301, No. 5632, July 25, 2003, p. 513).\n\nRelease of citochrome c and SMAC from the mitochondrion result in the caspase-9 activating apoptosome, which in turn activates executioner caspase-3. \n\n([http://stke.sciencemag.org/cgi/cm/CMP_7966 The canonical Fas pathway]] is available in \'\'Science\'s\'\' Signal Transduction Knowledge Environment. [http://stke.sciencemag.org/cgi/cm/CMP_7107 The canonical TNF pathway] is also available; but be aware that access to STKE\'s items is restricted to subscribers.)\n\nThe whole process requires energy and a cell machinery not too damaged. If the cell damage is between certain levels, the cell can start the earliest events of apoptosis and then continue with a necrosis.\n\nReaders should be aware, however, that the apoptotic pathways that have been summarily described are subject to regulatory mechanisms, and that there is not a 1-to-1 relationship between the reception of TNF or FasL and the complete execution of an apoptotic pathway. Fas, for instance, has been implicated --in a seemingly ironic way-- in cell proliferation, through pathways that are not yet well understood (see the afore-quoted article by Wajant); and both Fas and TNF-R1 trigger events that activate the transcription factor nuclear factor kappa B (NF-κB), which induces the expression of genes that play an important role in diverse biological processes, including cell growth and death, development, and immune responses (see the afore-quoted paper by Chen and Goeddel). \n\nThe link between TNF and apoptosis shows why an abnormal production of TNF plays a fundamental role in several human diseases, especially (but not only) in autoimmune diseases, such as diabetes and multiple sclerosis.\n\n== Implikasi jeung peran apoptosis dina rupa-rupa patologi ==\n\n=== Apoptosis jeung peran interferon pikeun nyegah tumor ===\nIn their previously mentioned article on the \"Integration of interferon-alpha/beta signaling to p53 responses...\", Takaoka and co-worker describe their research on how interferon alpha and beta (IFN-alpha/beta)induce transcription of the [[p53 gene]], resulting in the increase of p53 protein level and enhancement of cancer cell-apoptosis. p53 is a tumor suppressor, and is considered as a negative-growth and anti-oncogenic factor. \n\nWork carried out by Takaoka and colleagues has contributed to clarify the role played by interferon in the treatment of some forms of human cancer, and has provided knowledge on the link between p53 and IFN alpha/beta. The p53 response not only contributes to tumor suppression, but is also important in eliciting an apoptotic response to viral infection and consequent damage to the cell\'s reproductive cycle.\n\n=== Beuki loba bukti numbukeun kangker ka karuksakan jalur apoptotik ===\nLiling Yang \'\'et al.\'\' reported in the Feb. 15, 2003, issue of \'\'Cancer Research\'\' the results of their work in the role played by a defective death signal in a type of lung cancer cells called NCI-H460 (human non-small cell lung cancer cells). They found that the X-linked inhibitor of apoptosis protein (XIAP) is overexpressed in H460 cells. XIAPs bind to the processed form of caspase-9, and suppress the activity of apoptotic activator cytochrome c (see previous section on biochemical execution). \n\nThe apoptotic pathway was found to be dramatically restored in H460 cells with a Smac peptide (SmacN7) that targets IAPs. Yang and her team successfully developed a SmacN7 peptide that selectively reversed apoptosis resistance --and, hence, tumor growth-- in H460 cells in mice.\n\n=== Peran produk apoptotik dina kakebalan tumor ===\nAn interesting case of re-use and feed-back of apoptotic products was presented by Matthew L. Albert in a research article that won him an Amersham Biosciences & Science Prize for Young Scientists in Molecular Biology, and published in \'\'Science Online\'\' in December, 2001. Albert described how dendritic Cells, a type of antigen-presenting cells, phagocytose (that is, engulf) apoptotic tumor cells. Upon maturation, these dendritic cells present antigen (derived from the apoptotic corpses) to killer T cells, which are then primed for the eradication of cells undergoing malignant transformation. This apoptosis-dependent pathway for T cell activation is not present during necrosis, and has opened exciting posibilities in tumor immunity research.\n\n== History and highlights in apoptosis research ==\n\n===Panalungtikan munggaran===\n\n[[Sydney Brenner]]\'s studies on animal development began in the late [[1950s]] in what was to become the [[Laboratory of Molecular Biology]] (LMB) in Cambridge, UK. During the [[1960s]], Brenner chose the roundworm \'\'[[Caenorhabditis elegans]]\'\' as a model, mainly because this 1 mm-long soil nematode is simple, is easy to grow in bulk populations, and turned out be quite convenient for genetic analysis. \n\nAn LMB team led by John White succeeded, after twenty years, in mapping the worm\'s entire nervous system. They described the results of their feat in 1986, in a 340-page paper published in the \'\'Philosophical Transactions\'\' of The Royal Society. Another team, led by [[John Sulston]], traced the nematode\'s entire embryonic cell lineage. (Sulston was to become also a central figure in both the \'\'C. elegans\'\' and human genome sequencing projects.) \n[[Robert Horvitz]], who would collaborate closely with Sulston, arrived from the US at the Cambridge LMB in 1974. He would go back to the US in 1978, in order to establish his own lab at the Massachusetts Institute of Technology.\n\nBrenner\'s original interests were centered in genetics and in the development of the nervous system, but cell lineage and differentiation inevitably led to the study of cell fate: \"One aspect of the cell lineage particularly caught my attention: in addition to the 959 cells generated during worm development and found in the adult, another 131 cells are generated but are not present in the adult. These cells are absent because they undergo programmed cell death\", as Horvitz narrated in his Nobel Lecture \"Worms, Life and Death\" (delivered on 8 Dec. 2002.)\n\nProgrammed cell death had been known long before \"the worm people\" began to publish their celebrated findings. In 1964 Richard A. Lockshin and Carroll Williams published their contribution on \"Endocrine potentiation of the breakdown of the intersegmental muscles of silkmoths\" in the \'\'Journal of insect physiology\'\' 10 p. 643, where they used the concept of \"programmed cell death\". Unfortulately, though, not much research was being carried out on this topic. John W. Saunders, Jr., stated the following in his 1966 contribution titled \"Death in Embryonic Systems\": \"abundant death, often cataclysmic in its onslaught, is part of early development in many animals; it is the usual method of eliminating organs and tissues that are useful only during embryonic or larval life...\" (\'\'[[Science (journal)|Science]]\'\' Vol. 154 p. 604, 4 Nov. 1966). A little further on, this author lamented that too little had been done to analyze the significance of this process. Saunders, it should be noted, recognized that he was building on earlier work by A. Glücksmann, and others.\n\nSaunders and Lockshin reciprocally acknowledged that they benefitted from each other\'s work, and both ponted out the possibility that cell death might be regulated. Their observations helped to lead later work toward the genetic pathways of programmed cell death.\n\n===1970an-1980an===\nIn a signal article published in 1972, John F. Kerr, Andrew H. Wyllie and A. R. Currie (\"Apoptosis: a basic biological phenomenon with wide-ranging implications in tissue kinetics\", \'\'British Journal of Cancer\'\' 26, pgs. 239–57), coined the term \"apoptosis\" in order to differentiate naturally occurring developmental cell death, from the necrosis that results from acute tissue injury. They also noted that the structural changes characteristic of apoptosis (see the section on Morphology, above) were present in cells that died in order to maintain an equilibrium between cell proliferation and death in a particular tissue (see Homeostasis, above).\n\n===1990an ka hareup===\nIn 1991, Ron Ellis, Junying Yuan and Horvitz released a rounded and up-to-date account of research on programmed cell death in their \"Mechanisms and Functions of Cell Death\" (\'\'Annual Review of Cell Biology\'\' Nov 1991, Vol. 7, p. 663-698). Among other important work at Horvitz\'s laboratory, graduate students Hilary Ellis and Chand Desai had made the first discovery of genes that encode apoptosis-inducing proteins: \'\'ced-3\'\' and \'\'ced-4\'\'. \n\nRon Ellis also identified a gene with an opposite effect: \'\'ced-9\'\'. The product of this gene, CED-9, protects cells from programmed cell death, so its expression (or lack of) conveys a life-or-death decision on individual cells. As part of the same research, and not long afterwards, on February 1992, Michael Hengartner found that \'\'ced-9\'\' had a human homolog: \'\'[[bcl-2]]\'\' (which is not, actually, a single gene but a whole family of mammalian genes). Indeed, around four years before, in landmark research by David L. Vaux and colleagues, the anti-apoptotic and tumorigenic (tumor-causing) role of \'\'bcl-2\'\' had been identified[http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=3262202] (Vaux \'\'et al.\'\': \"Bcl-2 gene promotes haemopoietic cell survival and cooperates with c-myc to immortalize pre-B cells\", [[Nature (journal)|Nature]] 335 p. 440, 29 Sep. 1988). Researchers had been hot in the track of [[oncogene]]s (genes that played a prominent role in causing cancer), and now more and more of the pieces were falling into place.\n\nHorvitz would recount in his Nobel Lecture: \"I believe that the fact that Bcl-2 proved to look like a worm protein that antagonized programmed cell death helped convince researchers that the function of Bcl-2 was to antagonize the cell death process. I also believe that this similarity made the worm cell-death pathway suddenly a topic of major interest in the biomedical community, as this pathway was no longer simply an abstract formalism derived from complicated genetic studies of a microscopic soil dwelling roundworm but rather a framework for a process fundamental to human biology and human disease.\"\n\nIn 1992, two independent teams working at pharmaceutical companies had identified and purified interleukin-1-beta converting enzyme (ICE) in human cells, and succeeded in cloning the DNA sequence of this cysteine protease. (See Nancy A. Thornberry \'\'et al.\'\', \'\'Nature\'\' 356 p. 768, 30 Apr. 1992; Douglas P. Cerretti \'\'et al.\'\', \'\'Science\'\' 256 p. 97, 3 Apr. 1992.) That same year, graduate student Shai Shaham working in Horvitz\'s laboratory identified ICE as the mammalian counterpart of CED-3 (that is, the product of the \'\'ced-3\'\' gene in \'\'C. elegans\'\'). \n\nIn 1997, a protein similar to CED-4 was identified, as well, at the laboratory of Xiaodong Wang (Department of Biochemistry, University of Texas Southwestern Medical Center at Dallas), which they called Apaf-1 (apoptotic protease activating factor). The team published their results in an article titled \"Apaf-1, a human protein homologous to C. elegans CED-4, participates in cytochrome c-dependent activation of caspase-3 (Zou \'\'et al.\'\', \'\'Cell\'\' 90(3) p. 405, 8 Aug. 1997).\n\nWang and his team identified and reconstituted the mitochondrial pathway to apoptosis (see Biochemical execution, above). Their published results illuminated whole new avenues of research on inflammatory diseases, cancer, and apoptosis in general. \n\nBy 1998, research on the topic had already picked a good deal of wind in its sails, as attested in the editorial \"Cell Death in Us and Others\", written by an important contributor to apoptosis research, Pierre Golstein, in \'\'Science\'\' 281 p. 1283, 28 Aug. 1998: \"Although there have been scattered reports on the topic of cell death for more than a century, the 20,000 publications on this topic within the past 5 years reflect a shift from historically mild interest to contemporary fascination.\"\n\n==Tempo ogé==\n*[[Imunologi]]\n*[[Biokimia]]\n\n==Pustaka==\n*\'\'Cancer Medicine\'\', 5th Edition (2000), Robert C. Bast Jr. et al., editors, published by B.C. Decker Inc ([http://www.ncbi.nlm.nih.gov/books/bv.fcgi?call=bv.View..ShowTOC&rid=cmed.TOC&depth=2]). \n*\'\'Molecular biology of the cell\'\', 3th edition (1994), by Bruce Alberts, Dennis Bray, Julian Lewis, Martin Raff, Keith Roberts, James D. Watson, published by Garland Publishing, Inc ([http://www.ncbi.nlm.nih.gov/books/bv.fcgi?call=bv.View..ShowTOC&rid=cell.TOC]).\n\n== Tumbu kaluar == \n*[[Entrez]] is a life sciences information search engine provided by the US National Center for Biotechnology Information ([http://www.ncbi.nih.gov/Entrez/index.html]).\n*\'\'Entrez books\'\' is a service provided by the NCBI in collaboration with book publishers ([http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=books)]. \n*freebooks4doctors promotes free access to medical books ([http://www.freebooks4doctors.com/])\n*[[PubMed]] Central (PMC), provided by the US National Library of Medicine, is a digital archive of life sciences journal literature ([http://www.pubmedcentral.nih.gov/]).\n\n[[Category:Biologi sél]]\n\n[[de:Apoptose]]\n[[en:Apoptosis]]\n[[es:Apoptosis]]\n[[fr:Apoptose]]\n[[ja:アポトーシス]]\n[[nl:Apoptose]]\n[[pl:Apoptoza]]','',3,'Kandar','20041231022645','',0,0,1,0,0.215496691976,'20041231022645','79958768977354'); INSERT INTO cur VALUES (1082,2,'Kandar','Nepangkeun! Simkuring [[sysop]] di Wikipédia Basa Sunda. Pami bade badami atawa tataros perkawis proyék ieu, mangga diantos [[surélék]]na. [[User:Kandar|Kandar]] 05:37, 28 Jul 2004 (UTC)','',3,'Kandar','20040728053710','',0,0,0,1,0.648649768275,'20040728053710','79959271946289'); INSERT INTO cur VALUES (1084,10,'CabangKimia','
\n{| style=\"margin:0 auto;\" align=center width=75% id=toc\n|align=center style=\"background:#ccccff\"| \n\'\'\'[[Kimia]]\'\'\'\n|-\n|align=center| [[Kimia analitis]] | [[Kimia organik]] | [[Kimia anorganik]] | [[Kimia fisik]] | [[Kimia polimér]] | [[Biokimia]] | [[Élmu bahan]] | [[Kimia lingkungan]] | [[Farmasi]] | [[Térmokimia]] | [[Éléktrokimia]] | [[Kimia inti]] | [[Kimia komputasi]]\n|-\n|align=center style=\"background:#ccccff\"| [[Tabel periodik]] | [[Daptar sanyawa]]\n|}','',3,'Kandar','20040803084210','',0,0,0,0,0.139805926541,'20040908064414','79959196915789'); INSERT INTO cur VALUES (1085,0,'Organisasi','[[da:Organisation]]\n[[de:Organisation]]\n[[es:organización]] [[fr:organisation]]\n[[he:%D7%90%D7%99%D7%A8%D7%92%D7%95%D7%9F]]\n:\'\'Alternative meaning: [[Organisation (band)]].\'\'\nAn \'\'\'organization\'\'\' (also \'\'\'organisation\'\'\' in many [[Commonwealth of Nations|Commonwealth]] countries) is a formal group of people with one or more shared goals. This topic is a broad one. \n\nAccording to [[management science]], most [[human]] organizations fall roughly into five types:\n*[[Pyramid]]s or [[hierarchy|hierarchies]]\n*[[Committee]]s or [[jury|juries]]\n*[[Matrix]] organisations\n*Ecologies\n*[[Composite]] organisations\n\n== Pyramids or Hierarchies ==\n\nA [[hierarchy]] exemplifies an arrangement with a [[leader]] who leads leaders. This is the classic [[bureaucracy]]. Usually one \"rises\" by [[seniority]], or by acquiring [[authority]] over more people.\n\n[[Pyramid]]s are an effective way to achieve repeatable results because they have the shortest path from the standard-setter to the worker.\n\nThey suffer from communication and supervisory faults because the organization is only as good as its weakest link. They lack creativity because they have poor communications (\"why\" is often lost).\n\nThe classic fix for the communication problem is a magazine that reviews the whole hierarchy\'s business, perhaps daily or weekly. One good scheme has each person send e-mail up each week, telling what he did, his plans, and problems. Each boss makes a summary and sends it up. Then all the bosses send their summary down, appended to the summary from their boss.\n\nAt [[Printronix]] this freed cash equal to a year\'s revenue, sped up engineering cycles six fold, reduced defects by two sigmas (tempo [[varian]]), increased inventory turns tenfold and doubled product service life. People found out what to fix, and where.\n\nHierarchies were [[satire|satirised]] in \'\'The [[Peter Principle]]\'\' ([[1969]]), a book that introduced the term \'\'hierarchiology\'\' and the saying that \"in a hierarchy every employee tends to rise to his level of incompetence\".\n\nAn extremely rigid, in terms of responsibilities, type of organization is exemplified by [[Führerprinzip]].\n\n== Committees or Juries ==\n\nThese consist of a group of peers who decide as a group, perhaps by voting. The difference between a [[jury]] and a [[committee]] is that the members of the committee are usually assigned to perform or lead further actions after the group comes to a decision, whereas members of a jury come to a decision. In [[common law]] countries legal juries render decisions of guilt, liability and quantify damages, juries are also used in athletic contests, book awards and similar activities. Sometimes a selection committee functions like a jury. In the middle ages juries in continental Europe were used to determine the law according to consensus amongst local notables. \n\nCommittees are often the most reliable way to make decisions. [[Condorcet method|Condorcet\'s jury theorem]] proved that if the average member votes better than a roll of dice, then adding more members increases the number of majorities that can come to a correct vote (however correctness is defined). The problem is that if the average member is \'\'worse\'\' than a roll of dice, the committee\'s decisions grow worse, not better! Staffing is crucial.\n\nFamously, unstructured committees can dither without making decisions. [[Parliament]]ary procedure, such as Robert\'s Rules of Order, helps prevent dithering.\n\n== Staff Organisation or Cross-functional Team ==\n\nA [[staff]] helps an [[expert]] get all his work done. To this end, a \"[[chief of staff]]\" decides whether an assignment is routine or not. If it\'s routine, he assigns it to a staff member, who is a sort of junior expert. The chief of staff schedules the routine problems, and checks that they are completed. \n\nIf a problem is not routine, the chief of staff notices. He passes it to the expert, who solves the problem, and educates the staff -- converting the problem into a routine problem.\n\nStaffs make decisions quickly, and carry out assignments efficiently, though less reliably than committees or matrices. For this reason [[business]]es often prefer to use this method.\n\nStaffs break down easily, usually from bad selection of people. [[Dilbert]]\'s boss is a non-expert trying to run a staff. In a \"cross functional team,\" like an executive committee, the boss \'\'has\'\' to be a non-expert, because so many kinds of expertise are required. Also: chiefs of staff can be disorganized, play favorites, or can\'t tell what should go to the expert.\n\nExecutive committees \'\'can\'\' be expert staffs: at choosing people. This is how [[General Electric]] succeeded under [[Jack Welch]]. You could do worse.\n\n== [[Matrix]] Organisation ==\n\nOn the face of it, this is the perfect organisation. One hierarchy is \"functional\" and assures that each type of expert in the organization is well-trained, and measured by a boss who is super-expert in the same field. The other direction is \"executive\" and tries to get projects completed using the experts.\n\nMatrices are the only known organizations that can consistently create complex technical products like airplanes and engines.\n\nThe problem is that going through channels takes too long. Getting approval to actually \'\'do\'\' anything often needs the approval of each type of expert, and both of each expert\'s bosses! The trick is to speed aprovals: make approval everybody\'s number one job, and simplify sign-offs.\n\n== Ecologies ==\n\nThis organization has intense [[competition]]. Bad parts of the organization starve. Good ones get more work. Everybody is paid for what they actually do, and runs a tiny business that has to show a [[profit]], or they get canned. For example: upper managers invest, and if they make bad investments, there\'s no profit. Engineers rent their designs out to manufacturing. Facilities people rent space, etc.\n\nThis is a really effective organization. But it\'s wasteful because all those dead pieces of organization have valuable training, and are very hard to recycle. They\'re bitter, and they will stop taking it after a while. Reorganization follows.\n\nThis may reflect a rather one-sided view of what goes on in [[ecology]]. It is also the case that a natural [[ecosystem]] has a natural border - [[ecoregion]]s do not in general compete with one another in any way, but are very autonomous.\n\n== Composite Organizations ==\n\nThese try to use each of the above types of organization in the right places. Very occasionally, a true organizational genius can make this work, for a while. \n\nDon\'t bet on it in the long term. Success outgrows the ability of the genius. There just get to be too many special cases.\n\nOne golden exception may be a hierarchy of staffs, where every staff above the first level works to find or make the right people. This is the G.E. model, of course.\n\n== \"Chaordic\" Organizations ==\n\nAn emerging model of organizing human endeavors, based on a blending of [[chaos]] and [[order]] (hence \"chaordic\"), comes out of the work of Dee Hock and the creation of the VISA financial network. Blending [[democracy]], [[complex system]], [[consensus decision making]], [[co-operation]] and [[competition]], the chaordic approach attempts to encourage organizations to evolve from the increasingly nonviable hierarchical, command-and-control models. Reference: http://www.chaordic.org.\n\nSimilarly, see [[Emergent organisation]]s, and the principle of [[self-organization]]. See also [[group entity]] for an [[anarchism|anarchist]] perspective on human organizations.\n\n== References ==\n\n* \'\'Organizations\'\' by Richard Scott: ISBN 0132663546 (not a recommendation, but a hearsay suggestion)\n* \'\'Understanding Organisations\'\' by Charles Handy.\n* \'\'The Peter Principle\'\', Dr. Laurence J. Peter and Raymond Hull, Pan Books 1970 ISBN 0-330-02519-8 \n* \'\'[[The Nature of the Firm]]\'\' by [[Ronald Coase]].\n\nOrganisations which are legal entities: [[government]], [[international organization]], [[non-governmental organization]], [[armed forces]], [[corporation]], [[charity]], [[not-for-profit corporation]].\n\n== See also == \n* [[List of organizations]]\n* [[service club]]\n* [[List of civic, fraternal, service, and professional organizations]]\n* [[project]]\n* [[Service organization]]\n* [[Charitable trust]]\n* [[Fraternal organization]]\n* [[Fraternities and sororities]]\n* [[List of trade unions]]\n* [[List of environmental organizations]]\n* [[Non-governmental organization]]\n* [[International organization]]\n* [[Voluntary association]]\n\n== Related concepts ==\n* [[bureaucracy]]\n* [[Meeting]]\n* [[Organizational Development]]\n* [[organized crime]]\n* [[Requisite organization]]\n* [[Virtual organization]]\n* [[Conversation organization]]','/* Pyramids or Hierarchies */',13,'Budhi','20040907105508','',0,0,0,0,0.879519857876,'20040907105508','79959092894491'); INSERT INTO cur VALUES (1086,0,'Organization','#REDIRECT [[Organisasi]]\n','Organization dipindahkeun ka Organisasi',13,'Budhi','20040729214122','',0,1,0,1,0.382701649686975,'20040729214122','79959270785877'); INSERT INTO cur VALUES (1087,0,'Territory','[[da:Territorium]]\n[[pl:Terytorium]]\n[[ru:Территория]]\n[[zh:领土]]\n\nA \'\'\'territory\'\'\' is a defined area (including land and waters), usually considered to be a possession of an animal, person, organization, or institution. \n*In [[biology]], an [[organism]] which defends an area against intrusion (usually from members of its own species) is said to be \'\'\'territorial\'\'\'. For further details see [[territory (animal)]]\n*In [[politics]], a \'\'\'territory\'\'\' is an area of land under the jurisdiction of a governmental authority. Territory can, though, include any geographical area under the jurisdiction of a sovereign and does not have a political division status. The remainder of this article deals with political territories.\n*In [[psychology]], Enviromentalists study Territorial Behaviour to understand which Territory an [[organism]] defends and why. Territorial Behaviour is defined as;\n\"The actions or reactions of a person or animal in responce to external threats towards the space that is defended by that person or animal.\"\n\nTypes of territories include:\n\n* A legally administered territory, which is a non-sovereign geographic area that has come under the authority of another government. For example, [[American Samoa]] is a territory of the government of the [[United States]]. With regard to [[Canadian provinces and territories]], the major difference between a Canadian province and a Canadian territory is that the federal government has more direct control over the territories, while the provinces are run by provincial governments. See also [[Australian States and Territories]].\n\n* An [[occupied territory]] which is a region that is under the military control of an outside power that has not annexed the region. An example of an [[occupied territory]] is Iraq after the American invasion of 2003 or Germany after World War II.\n\n* A [[disputed territory]], which is a geographic area claimed by two or more rival governments. For example, the territory of [[Kashmir]] is claimed by both the governments of [[India]] and [[Pakistan]].\n\n*A claimed part of [[Antarctica]].','',13,'Budhi','20040729214741','',0,0,0,1,0.210400296007,'20040729214741','79959270785258'); INSERT INTO cur VALUES (1088,3,'Meursault2004','Salam!\nBang Revo, saya lebih memilih istilah \"Tepas\" (artinya \"halaman depan\") daripada \"Kaca Utama\" untuk main page Wikipedia Sunda, karena saya menganggap istilah tepas sudah cukup cocok dalam hal ini.\nTrims. [[User:Kandar|Kandar]] 04:29, 30 Jul 2004 (UTC)\n----','',3,'Kandar','20040730042937','',0,0,0,1,0.765382795485,'20040730042937','79959269957062'); INSERT INTO cur VALUES (1089,0,'Wikipédia:Ngeunaan','\'\'\'Wikipédia\'\'\' ngarupakeun [[énsiklopédi]] [[nembrak]] (\'\'open-content\'\') nu ditulis sacara réréongan ku kontributor-kontributor ti sakuliah dunya. Loka (situs)-na mangrupa [[wiki]], nu hartina \'\'singsaha baé\'\' bisa ngédit/ngarobah artikel, cukup ku ngaklik tumbu \'\'édit kaca ieu\'\' nu katémbong di punclut unggal kaca. \n\n\'\'Wikipédia\'\' ngarupakeun mérk dagang [[Wikimédia|Yayasan Wikimedia, Inc.]]\n\nPatarosan Pérs kedah didugikeun ka Terry Foote di (USA) 310-474-3223. Anjeunna bakal neraskeun hal ieu ka [[user:Jimbo Wales|Jimmy Wales]], présidén Yayasan Wikimedia. Nomer éta husus kanggo pérs, patarosan nu sanésna mugi langsung baé didugikeun ka jwales@bomis.com. \n\nWikipédia dikawitan ti [[15 Januari]] [[2001]] ku [[User:Jimmy Wales|Jimmy Wales]], [[Larry Sanger]], sarta sababaraha urang kolaborator basa Inggris nu parinuh ku sumanget. Tilu taun ti harita, Maret [[2004]], tos aya 6000 kolaborator aktif nu midamel 600000-an artikel dina [http://www.wikipedia.org/wikistats/EN/TablesArticlesTotal.htm 50 basa]. Dinten ieu, tos aya langkung ti 300000 artikel na basa Inggris sarta {{NUMBEROFARTICLES}} artikel na [[basa Sunda]]; unggal dinten [http://www.wikipedia.org/wikistats/EN/TablesUsageVisits.htm ratusan rébu] urang ti sakuliah dunya ngadamel puluhan rébu édit sarta rébuan artikel anyar. \n\nSadaya seratan na Wikipédia, sarta kaseuseueuran gambar jeung eusi nu sanésna ditangtayungan ku \'\'[[Lisénsi Dokumén Bébas GNU]] (\'\'GNU Free Documentation License\'\', GFDL). Sagala sumbangsih tetep hak milik nu ngadamelna, sedengkeun lisénsi GFDL mastikeun yén eusina tetep bisa disebarkeun sarta dilobaan kalawan bébas (tingal [[Wikipédia:Hak cipta|béwara hak cipta]] lan [[Wikipédia:Bantahan eusi|bantahan eusi]] kanggo langkung paos).\n\n== Sajarah proyék jeung ihtisar == \n\n* [[Wikipédia|Sajarah jeung proyék]] Wikipédia sarta [[Wikipédia:NLD|NLD]] \n* [[Yayasan Wikimedia]], organisasi tanpabati indung Wikipédia \n* Wikipédia [[Wikipedia:Announcements|announcements]], [[Wikipedia:Press coverage|press coverage]], and a [[Wikipedia:Goings-on|weekly review]].\n\n== Ngalanglang Wikipédia == \n \n* [[Special:Recentchanges|Parobahan anyar]] -- artikel-artikel nu keur dipigawé. \n* [[Wikipedia:Featured articles|Featured articles]], [[Special:Newpages|artikel anyar]], [[requested articles]], atawa [[Special:Randompage|artikel acak]]. \n* \'\'[[Wikipedia:Reference desk|Reference desk]]\'\' lokal, pikeun ménta pitulung atawa béja panalungtikan.\n\n== Sumbangsih ka Wikipédia == \n\nKaca réferénsi: [[Wikipédia:kawijakan jeung tungtunan|kawijakan jeung tungtunan]] pikeun kontributor, [[Wikipédia:Wilujeng sumping|kaca pangbagéa]], [[Wikipédia:Tutorial|wawanohan pikeun nu anyaran datang]], jeung [[Wikipédia: Pitulung|\'\'\'pitulung\'\'\' umum]] pikeun ngédit sarta lalayaran di Wikipédia.\n\n== Cara nepungan anggota proyék == \n\nRohangan baku pikeun nanyakeun kawijakan jeung hal-hal nu patali jeung proyék nyaéta di [[Wikipedia:Village pump|village pump]] nu online, sarta [[Wikipedia:mailing lists|Wikipedia mailing lists]], ngaliwatan [[surélék]]. Anjeun ogé bisa nepungan [[Wikipedia:Wikipedians|Wikipédiawan]] séjén di [[Wikipedia:IRC channels|IRC]] jeung [[Wikipedia:Instant Messaging Wikipedians|instant messager]]. \n\nThere is also a [http://meta.wikipedia.com/ \'\'\'meta\'\'\'-Wikipedia], a site for coordinating the various Wikipedia projects (and abstract discussions of policy and direction), and there are a few different places for submitting [[Wikipedia:Bug reports|bug reports and feature requests]].\n\n== Pamendak jeung kaabotan == \n \n* Wikipédia [[Wikipedia:Why Wikipedia is so great|\'\'\'pros\'\'\']] and [[Wikipedia:Why Wikipedia is not so great|\'\'\'cons\'\'\']], and some [[Wikipedia:Replies to common objections|replies to common objections]].\n\n== Tumbu séjén == \n\n* [[Wikipedia:Statistics|statistik]], [[Wikipedia:Friends of Wikipedia|baraya]], sarta [[Wikipedia:Power structure|struktur kakuatan]] Wikipédia \n* [[Wikipedia:Other projects similar to Wikipedia|proyék nu sarupa]].\n\n== Vérsi basa séjén == \n\n{{Wikipedialang}}\n\n== Proyék sadulur == \n\n{{wikipediasister}} \n\nTempo ogé [[Wikipédia:Édisi citak]]\n\n[[ar:ويكيبيديا:حول]] \n[[da:Wikipedia:Om]] \n[[de:Wikipedia:Über Wikipedia]] \n[[es:Wikipedia:Acerca de]] \n[[et:Vikipeedia:Tiitelandmed]] \n[[fo:Wikipedia:Um]] \n[[fr:Wikipédia:À propos]] \n[[fy:Wikipedy:Wat is Wikipedia]] \n[[gl:Wikipedia:Sobre]] \n[[he:ויקיפדיה:אודות]] \n[[hi:विकिपीडिया:विकिपीडिया के बारे में]] \n[[hu:Wikipédia:Wikipédiáról]] \n[[ja:Wikipedia:ウィキペディアについて]] \n[[lb:Wikipedia:Iwwert Wikipedia]] \n[[ms:Wikipedia:Perihal]] \n[[pt:Wikipedia:Sobre]]\n[[ru:Википедия:Описание]] \n[[simple:Wikipedia:About]] \n[[sv:Wikipedia:Om]] \n[[tr:Wikipedia:Om]] \n[[vi:Wikipedia:Nói về]] \n[[zh:Wikipedia:关于]]','/* Proyék sadulur */',3,'Kandar','20050215050403','',0,0,0,0,0.993936535899,'20050215053251','79949784949596'); INSERT INTO cur VALUES (1091,10,'Wikipedialang','Wikipédia nu mibanda leuwih ti 10,000 artikel ditulis \'\'\'kandel\'\'\'.\n\n[http://en2.wikipedia.org/wiki/Wikipedia:Complete_list_of_language_wikis_available Daptar basa salengkepna] –\n[[:af:|Afrikaans]] –\n[[:sq:|Shqip ]] –\n[[:ar:|‮العربية ‬ ]] –\n[[:roa-rup:|Armâneashti]] –\n[[:eu:|Euskara ]] –\n[[:bs:|Bosanski ]] –\n[[:bg:|Български ]]  –\n[[:ca:|Català ]] –\n[[:chr:|ᏣᎳᎩ ]] –\n\'\'\'[[:zh:%E9%A6%96%E9%A1%B5|简体中文]] –\'\'\'\n\'\'\'[[:zh:%E9%A6%96%E9%A0%81|繁體中文]] –\'\'\'\n[[:hr:|Hrvatski ]] –\n[[:cs:|Čeština ]] –\n\'\'\'[[:da:|Dansk ]] –\'\'\'\n\'\'\'[[:nl:|Nederlands ]] –\'\'\'\n\'\'\'[[:en:|English]] –\'\'\'\n\'\'\'[[:eo:|Esperanto]] –\'\'\'\n[[:et:|Eesti ]] –\n[[:fi:|Suomeksi ]] –\n[[:fo:|Føroyskt ]] –\n\'\'\'[[:fr:|Français ]] –\'\'\'\n[[:fy:|Frysk ]] –\n[[:gl:|Galego ]] –\n\'\'\'[[:de:|Deutsch ]] –\'\'\'\n[[:el:|Ελληνικά ]] –\n[[:he:|עברית ]]  –\n[[:hi:|हिन्दी ]] –\n[[:hu:|Magyar ]] –\n[[:io:|Ido]] –\n[[:is:|Íslenska ]] –\n[[:id:|Bahasa Indonesia ]] –\n[[:ia:|Interlingua]] –\n[[:ga:|Gaeilge ]] –\n\'\'\'[[:it:|Italiano ]] –\'\'\'\n\'\'\'[[:ja:|日本語  ]] –\'\'\'\n[[:csb:|Kaszëbsczi ]] –\n[[:jv:|Basa Jawi ]] –\n[[:km:|ភាសាខ្មែរ]]  –\n[[:ko:|한국어 ]] –\n[[:ku:|Kurdî ]] –\n[[:la:|Latina ]] –\n[[:lv:|Latviešu ]] –\n[[:lt:|Lietuvių ]] –\n[[:lb:|Lëtzebuergesch]]   –\n[[:ms:|Bahasa Melayu ]] –\n[[:ml:|മലയാളം ]] –\n[[:mn:|Монгол ]] –\n[[:mi:|Maori]] –\n[[:nah:|Nahuatl]] –\n[[:no:|Norsk ]] –\n[[:oc:|Occitan]] –\n[[:fa:|فارسی ]] – \n[[:nds:|Plattdüütsch]] –\n\'\'\'[[:pl:|Polski ]] –\'\'\'\n\'\'\'[[:pt:|Português ]] –\'\'\'\n[[:ro:|Română ]] – \n[[:ru:|Русский ]] –\n[[:simple:|Simple English]] –\n[[:sk:|Slovenčina ]] –\n[[:sl:|Slovenščina ]] –\n[[:sr:|Српски ]] –\n\'\'\'[[:es:|Español ]] –\'\'\'\n[[:sw:|Kiswahili ]] –\n\'\'\'[[:sv:|Svenska ]]\'\'\' –\n[[:ta:|தமிழ் ]] –\n[[:tl:|Tagalog]] –\n[[:tt:|Tatarça ]] –\n[[:th:|ภาษาไทย ]] –\n[[:tokipona:|Toki Pona]] –\n[[:tpi:|Tok Pisin]] –\n[[:tr:|Türkçe ]] –\n[[:uk:|Українська]] –\n[[:ur:|اردو ]] –\n[[:vi:|Tiếng Việt ]] – \n[[:vo:|Volapük]] –\n[[:wa:|Walon ]] –\n[[:cy:|Cymraeg ]]\n\n
\n\'\'\'[[m:Complete list of language Wikipedias available|Daptar lengkep]]\'\'\' –\n\'\'\'[http://en.wikipedia.org/wiki/Wikipedia:Multilingual_coordination Koordinasi multibasa]\'\'\' – \'\'\'[[m:How to start a new wikipedia|Mimitian Wikipédia basa séjén]]\'\'\'\n
','',3,'Kandar','20050215053251','',0,0,0,0,0.109428670308,'20050215053251','79949784946748'); INSERT INTO cur VALUES (1092,10,'Wikipediasister','Wikipédia dijalankeun ku Yayasan [http://en.wikipedia.org/wiki/Wikimedia Wikimédia] tanpabati. Wikimédia ngajalankeun sababaraha proyék wiki [http://en.wikipedia.org/wiki/Wikipedia:Multilingual_coordination multibasa] nu [[Wikipédia:Hak cipta|nembrak]]:\n\n{| align=\"center\" cellpadding=\"2\"\n| valign=\"top\" align=\"center\" | [[Image:wiki-meta.png|80px|Meta-Wiki]]\n| valign=\"top\" align=\"center\" | [[Image:Wiktionary.png|80px|Wiktionary]]\n| valign=\"top\" align=\"center\" | [[Image:Wiki-textbook.png|80px|Wikibooks]]\n| valign=\"top\" align=\"center\" | [[Image:Wikiquote.png|80px|Wikiquote]]\n| valign=\"top\" align=\"center\" | [[Image:Sourceberg.jpg|80px|Wikisource]]\n|-\n| align=\"center\" | [[m:|\'\'\'Meta-Wiki\'\'\']]
\'\'Koordinasi sadaya proyék Wikimédia\'\'\n| align=\"center\" | [http://su.wiktionary.org \'\'\'Wiktionary\'\'\']
\'\'Kamus jeung tésaurus\'\'\n| align=\"center\" | [http://su.wikibooks.org \'\'\'BukuWiki\'\'\']
\'\'Buku téks jeung manual bébas\'\'\n| align=\"center\" | [http://su.wikiquote.org \'\'\'Wikiquote\'\'\']
\'\'Kumpulan kutipan\'\'\n| align=\"center\" | [[wikisource:Main Page:Basa Sunda|\'\'\'Wikisource\'\'\']]
\'\'Dokumén nu sumberna bébas\'\'\n|}','',3,'Kandar','20041231034902','',0,0,0,0,0.499164167558,'20041231034902','79958768965097'); INSERT INTO cur VALUES (1093,6,'Wiki-meta.png','Lambang meta wiki','Lambang meta wiki',3,'Kandar','20040730093101','',0,0,0,1,0.242739768924881,'20050313153637','79959269906898'); INSERT INTO cur VALUES (1094,6,'Wiktionary.png','Lambang Wiktionary vérsi Inggris','Lambang Wiktionary vérsi Inggris',3,'Kandar','20040730094257','',0,0,0,1,0.0655939262971225,'20050313153637','79959269905742'); INSERT INTO cur VALUES (1095,8,'Categoryarticlecount','Aya $1 artikel na kategori ieu.','',3,'Kandar','20040802075042','',0,0,0,1,0.307883572442,'20040802075042','79959197924957'); INSERT INTO cur VALUES (1097,8,'Infosubtitle','Iber pikeun kaca','',3,'Kandar','20050223043339','',0,0,1,0,0.988495140797,'20050223043339','79949776956660'); INSERT INTO cur VALUES (1098,8,'Timezonelegend','Wewengkon wanci','',3,'Kandar','20040803023152','',0,0,0,1,0.598859683424,'20040803023152','79959196976847'); INSERT INTO cur VALUES (1099,6,'Wiki-textbook.png','Salinan ti lambang Wikibooks.png','Salinan ti lambang Wikibooks.png',3,'Kandar','20040803033630','',0,0,0,1,0.599750355444616,'20050313153637','79959196966369'); INSERT INTO cur VALUES (1100,8,'Others','Séjénna','',3,'Kandar','20040803050849','',0,0,0,1,0.34713359007,'20040803050849','79959196949150'); INSERT INTO cur VALUES (1101,6,'Wikiquote.png','Salinan ti logo Wikiquote','Salinan ti logo Wikiquote',3,'Kandar','20040803065819','',0,0,0,1,0.801970029065358,'20050313153637','79959196934180'); INSERT INTO cur VALUES (1102,0,'Kimia_organologam','\'\'\'Kimia organologam\'\'\' ngarupakeun ulikan [[sanyawa kimia]] nu ngandung [[beungkeut kimia|beungkeut]] antara [[karbon]] jeung [[logam]]. \n\nIstilah \"logam\" dina jihat ieu dihartikeun sacara husus sarta bisa ngawengku unsur kayaning [[silikon]] atawa [[boron]], nu lain logam kawas beusi tapi dianggap [[métaloid]]. Kimia organologam ngagabungkeun aspék-aspék [[kimia anorganik]] jeung [[kimia organik]].\n\nSanyawa organologam mindeng dipaké salaku [[katalis]], misalna dina olahan produk [[pétroleum]] sarta produksi [[polimér]] organik.\n\nTempo ogé:\n\n*[[Katalis Ziegler-Natta]]\n*\'\'[[metallocene]]\'\'\n*\'\'[[electron counting]]\'\'\n*[[Réagen Grignard]]\n\n\n{{pondok}}\n\n{{CabangKimia}}\n\n[[Category:Kimia]]\n[[Category:Élmu alam]]\n\n[[en:Organometallic chemistry]]','',3,'Kandar','20041125073737','',0,0,0,0,0.677883266787,'20050303211247','79958874926262'); INSERT INTO cur VALUES (1103,0,'Kimia_kuantum','\'\'\'Kimia kuantum\'\'\' ngarupakeun larapan [[mékanik kuantum]] dina masalah-masalah widang [[kimia]].\n\nDadaran ngeunaan paripolah éléktronik [[atom]] jeung [[molekul]] patali jeung réaktivitina mangrupa hiji larapan kimia kuantum.\n\nKusabab ulikan mékanis-kuantum [[atom]] dianggap aya dina garis wates antara [[kimia]] jeung [[fisika]], and not always included in quantum chemistry, what is often considered the first true calculation in quantum chemistry was that of the [[Germany|German]] scientists [[Walter Heitler]] and [[Fritz London]] (though Heitler and London are generally classed as physicists) on the hydrogen (H2) molecule in [[1927]]. Heitler and London\'s method was extended by the [[United States|American]] chemists [[John C. Slater]] and [[Linus Pauling]] to become the \'\'\'Valence-Bond (VB)\'\'\' [or \'\'\'Heitler-London-Slater-Pauling (HLSP)\'\'\'] method. In this method, attention is primarily devoted to the pairwise interactions of atoms, and this method therefore correlates closely with classical chemists\' drawing of [[chemical bond|bonds]] between atoms.\n\nAn alternative approach was developed by [[Friedrich Hund]] and [[Robert S. Mulliken]], in which the [[electron]]s are described by mathematical functions delocalized over an entire molecule. The \'\'\'Hund-Mulliken\'\'\' approach [or \'\'\'[[molecular orbital]] (MO) method\'\'\'] is less intuitive to chemists, but since it turns out to be more capable of predicting properties than the VB method, it is virtually the only method used in recent years.\n\nIn [[1970s]] was created a Quantum-Mechanical Theory of the Elementary Act of Chemical, Electrochemical and Biochemical Reactions in Polar Liquids (by [[Revaz Dogonadze|R.R. Dogonadze]] and others). R.R. Dogonadze was a founder of the well-known scientific school of [[Quantum Electrochemistry]]. \n\nSababaraha jejer dina kimia kuantum kayaning:\n\n*the [[Born-Oppenheimer approximation]]\n*[[Hartree-Fock]] self consistent field ([[Self consistent field|SCF]]) theory \n* [[Density functional theory]]\n\n----\n\nSome people (other than those mentioned above) significant in the development of quantum chemistry:\n\n*[[Erich Hueckel|Erich Hückel]]\n*[[Rudolph Pariser]]\n*[[Robert G. Parr]]\n*[[John Pople]]\n*[[Henry Eyring]]\n*[[Revaz Dogonadze]]\n\n{{CabangKimia}}\n\n[[Category:Kimia]]\n\n[[bg:Квантова химия]]\n[[ca:Química quàntica]]\n[[da:Kvantekemi]]\n[[de:Quantenchemie]]\n[[en:Quantum chemistry]]\n[[es:Química cuántica]]\n[[fr:Chimie quantique]]\n[[ja:量子化学]]\n[[pl:Chemia kwantowa]]\n[[zh:量子化学]]','warnfile Adding:bg,de,zh,pl Modifying:ca',42,'Shizhao','20050303143850','',0,0,1,0,0.123852805292,'20050303143850','79949696856149'); INSERT INTO cur VALUES (1104,0,'Spéktroskopi','\'\'\'Spéktroskopi\'\'\' ngarupakeun ulikan ngeunaan [[Spéktrum|spéktra]].\n\nSpéktroskopi mindeng dipaké na [[kimia]] fisik sarta analitis pikeun idéntifikasi zat tina spéktrum nu mencar atawa nu diserepna. Parabot pikeun ngarékam spéktrum disebut [[spéktrométer]]. Spéktroskopi bisa digolongkeun dumasar kuantitas fisik nu diukur, diitung, atawa prosés ngukurna.\n\nSpéktroskopi ogé kapaké pisan dina [[astronomi]]. Tempo [[spéktroskopi astronomis]].\n\n==Kuantitas fisik nu diukur==\nTipe spéktroskopi gumantung kana kuantitas fisik nu rék diukur. Ilaharna, kuantitas nu diukur mangrupa jumlah atawa inténsitas. \n*Inténsitas [[radiasi éléktromagnetik]] nu dipencarkeun jeung jumlah nu diserep diulik ku [[spéktroskopi éléktromagnetik]].\n*Amplitudo geteran/vibrasi makroskopik diulik ku [[spéktroskopi akustik]] jeung [[spéktroskopi mékanis dinamik]].\n*Énergi kinetik partikel diulik ku \'\'[[electron energy loss spectroscopy]]\'\', \'\'[[spéktroskopi éléktron Auger]]\'\'\n*Nisbah massa ka muatan molekul jeung atom diulik dina [[spéktrométer massa|spéktrométri massa]]. Catet yén spéktrométer massa teu ngukur énergi kinetik partikel: sadaya partikel mibanda énergi kinetik nu sarua sarta geus kanyahoan (or an integer multiple thereof, depending on the charge). It is disputable whether this field strictly is a type of spectroscopy.\n*Jumlah molekul atawa atom atawa kuantum-mékanik nangtukeun kamana paraméter frékuénsi atawa énergi dilarapkeun.\n\n==Prosés ngukur==\nTipe spéktroskopi nu béda dipaké dina prosés ngukur nu béda:\n\n=== \'\'\'Dua tipe utama spéktroskopi\'\'\' ===\n\n\'\'\'Spéktroskopi Absorpsi\'\'\' uses the range of electromagnetic spectra in which a substance absorbs. It is more commonly used. The sample is vaporised and then light of a particular frequency is passed through the vapour. After calibration, the amount of absorption can be related to the concentrations of various metal ions. The method can be automated and is widely used to measure concentrations of ions such as sodium and calcium in blood. ( Atomic Absorption Spectroscopy )\n\n\'\'\'Spéktroskopi Émisi\'\'\' uses the range of electromagnetic spectra in which a substance radiates. It requires the substance to be vaporised at high temperatures by placing it in a spark gap.\n\n=== \'\'\'Tipe spéktroskopi nu ilahar\'\'\' ===\n\n\'\'\'X-ray spectroscopy\'\'\' and \'\'\'[[X-ray crystallography]]\'\'\'\nWhen X-rays of sufficient frequency (energy) interact with a substance, inner shell electrons in the atom are excited to outer empty orbitals, or they may be removed completely, ionizing the atom. The inner shell \"hole\" will then be filled by electrons from outer orbitals. The energy available in this de-excitation process is emitted as radiation (fluorescence) or will remove other less-bound electrons from the atom (Auger effect). The absorption or emission frequencies (energies) are characteristic of the specific atom. In addition, for a specific atom small frequency (energy) variations occur which are characteristic of the chemical bonding. With a suitable apparatus, these characteristic X-ray frequencies or Auger electron energies can be measured. X-ray absorption and emission spectroscopy is e.g. used in chemistry and material sciences to determine elemental composition and chemical bonding.\n\nX-ray crystallography is a process in which X-rays are shone onto crystals at a certain angle. The wavelength of the X-rays is known and so the distance apart of the crystal planes can be calculated. Combining all information enables crystal structure to be detected.\n\n\'\'\'Visible spectroscopy\'\'\'\n\nMany atoms emit or absorb visible light. In order to obtain a fine line spectrum, the atoms must be in a gas phase. This means that the substance has to be vaporised. Spectrum is studied in absorption or emission.\n\n\'\'\'UV spectroscopy\'\'\'\n\nAll atoms absorb in the UV region because photons are energetic enough to excite outer electrons. If the frequency is high enough, [[Photoionisation]] takes place.\n\n\'\'\'[[Photoemission spectroscopy]]\'\'\'\n\n===\'\'\'Less frequently used / combined spectroscopy\'\'\' ===\n*[[Fourier transform]] is an efficient method for collecting various spectra. The use of Fourier transform in spectroscopy is called [[Fourier transform spectroscopy]]. It is frequently applied to infrared spectroscopy (FTIR) and nuclear magnetic resonance ([[NMR]]) spectroscopy.\n*Spectroscopy of matter in situations where the properties are changing with time is called [[Time-resolved spectroscopy]].\n*Spectroscopy using an [[AFM]]-based analytical technique is called [[Force spectroscopy]].\n*[[Dielectric spectroscopy]]\n\n[[Category:Kimia analitis]]\n[[Category:Fisika]]\n[[Category:Spéktroskopi]]\n\n[[da:Spektroskopi]]\n[[de:Spektroskopie]]\n[[en:Spectroscopy]]\n[[it:Spettroscopia]]\n[[ja:%E5%88%86%E5%85%89%E6%B3%95]]','/* Prosés ngukur */',3,'Kandar','20050218080251','',0,0,1,0,0.354634454639,'20050218080251','79949781919748'); INSERT INTO cur VALUES (1105,8,'Subcategorycount','Aya $1 subkategori na kategori ieu.','',3,'Kandar','20040803083707','',0,0,0,1,0.196958609483,'20040803083707','79959196916292'); INSERT INTO cur VALUES (1106,0,'Wikipédia:Hak_cipta','Cita-cita [[Wikipédia]] nyaéta pikeun nyieun sumber béja dina hiji format [[énsiklopédi]] nu disadiakeun kalawan bébas (haratis). Lisénsi nu dipaké ngajamin aksés bébas ka sakabéh eusina sakumaha [[software bébas]] dilisénsikeun kalawan bébas. Prinsip ieu dipikawanoh salaku \'\'\'\'\'[[copyleft]]\'\'\'\'\'. Hartina, eusi Wikipédia bisa disalin, dirobah, sarta disebarkeun \'\'sapanjang\'\' vérsi anyarna ngajamin kabébasan nu sarua ka nu séjén sarta nganyahokeun \'\'penulis\'\' artikel Wikipédia nu dipaké (a direct link back to the article satisfies our author credit requirement). Artikel Wikipédia ku kituna bakal tetep bébas salawasna sarta bisa dipaké ku singsaha waé asal bisa tetep ngajamin kabébasanana.\n\nPikeun nedunan cita-cita éta, téks nu aya na Wikipédia dilisénsikeun dina panangtayungan [[Lisénsi Dokumén Bébas GNU]] (\'\'GNU Free Documentation License\'\', GFDL). Téks lengkep lisénsi ieu aya di [http://en.wikipedia.org/wiki/Wikipedia:Text_of_the_GNU_Free_Documentation_License Téks Lisénsi Dokumén Bébas GNU]. \n\n:Nyalin, nyebarkeun, sarta/atawa ngarubah dokumén ieu aya dina panangtayungan Lisénsi Dokumén Bébas GNU, Vérsi 1.2 atawa vérsi nu salajengna nu dikaluarkeun ku [http://en.wikipedia.org/wiki/Free_Software_Foundation Free Software Foundation]; with no Invariant Sections, with no Front-Cover Texts, and with no Back-Cover Texts.\n:Salinan lisénsina aya dina bagian nu judulna \"[http://en.wikipedia.org/wiki/Wikipedia:Text_of_the_GNU_Free_Documentation_License Lisénsi Dokumén Bébas GNU]\".\n:Eusi Wikipédia dipayungan ku [[Wikipédia:Bantahan umum|bantahan]].\n\n\nThe text of the GFDL is the only legally binding document; what follows is our interpretation of the GFDL: the rights and obligations of users and contributors.\n\nPENTING: Mun anjeun hayang migunakeun kandungan Wikipédia, baca heula bab [[Wikipédia:Hak cipta#Hak jeung kawajiban pamaké|Hak jeung kawajiban pamaké]]. Salajengna anjeun kudu maca [http://en.wikipedia.org/wiki/Wikipedia:Text_of_the_GNU_Free_Documentation_License Lisénsi Dokumén Bébas GNU].\n\n== Hak jeung kawajiban pamaké ==\n\nMun anjeun hayang maké bahan-bahan Wikipédia dina buku/artikel/jalaloka anjeun sorangan atawa publikasi séjénna, anjeun kudu nuturkeun bagéan 2 GFDL na \'\'nyalin verbatim\'\', sakumaha nu disawalakeun na [[Wikipédia:nyalin verbatim|nyalin verbatim]].\n\nMun anjeun nyieun vérsi turunan ku jalan ngarobah atawa nambahan eusina, ieu ngudukeun:\n* bahan-bahan anjeun saterusna kudu dilisénsikeun dina panangtayungan GFDL,\n* anjeun kudu nganyahokeun \'\'authorship\'\' artikelna (bagéan 4B), jeung\n* anjeun kudu nyadiakeun aksés ka \"salinan transparan\" bahanna (bagéan 4J). (\"Salinan transparan\" artikel Wikipédia nyaéta téks wiki-na.) \n\nYou may be able to partially fulfill the latter two obligations by providing a conspicuous direct link back to the Wikipedia article hosted on this website. You also need to provide access to a transparent copy of the new text. However, please note that the Wikimedia Foundation makes no guarantee to retain authorship information and a transparent copy of articles. Therefore, you are encouraged to provide this authorship information and a transparent copy with your derived works.\n\n=== Example notice ===\n\nAn example notice, for an article that uses the Wikipedia article [[Foo]] might read as follows:\n\n: This article is licensed under the
GNU Free Documentation License. It uses material from the Wikipedia article \"Foo\".\n\n(\"Foo\" and the Wikipedia URL must of course be substituted accordingly.)\n\nAlternatively you can distribute your copy of Foo along with a copy of the GFDL (as explained in the text) and list at least five (or all if fewer than five) principal authors on the title page (or top of the document).\n\n=== Fair use materials and special requirements ===\n\nAll original Wikipedia text is distributed under the [[GFDL]]. Occasionally, Wikipedia articles may include images, sounds, or text quotes used under the U.S. Copyright law \"[[fair use]]\" doctrine. It is preferred that these be obtained under the most free ([[libre]]) license (such as the GFDL or public domain) practical. In cases where no such images/sounds are currently available, then fair use images are acceptable (until such time as free images become available). \n\nIn such a case, the material should be identified as from an external source (on the image description page, or history page, \nas appropriate). As \"fair use\" is specific to the use that you contemplate it is best if your describe the fair use rationale for such specific use either in hidden text in the article or on the [[Wikipedia:Image_description_page#Fair_use_rationale|image description page]]. Remember what is fair use for Wikipedia may not be considered a fair use for your intended use of the content in another context.\n\nFor example, if we include an image under fair use, you must ensure that your\nuse of the article also qualifies for fair use (this might not be the case,\nfor example, if you were using a Wikipedia article for a commercial use that\nwould otherwise be allowed by the GFDL and the fair use would not be allowed under that commercial use).\n\nWikipedia does use some text under licenses that are compatible with the GFDL but may require additional terms that we do not require for original Wikipedia text (such as including Invariant Sections, Front-Cover Texts, or Back-Cover Texts). When using these materials, you have to include those invariant sections verbatim.\n\nAn approval process for fair use images at has been proposed at [[Wikipedia:Fair use]]. Images which have gone through that process carry the tag:\n\n
{{verifieduse}}{{verifieduse}}\n
\n\n== Tungtunan gambar ==\n\nGambar jeung fotograf, sakumaha karya tinulis séjénna ngarupakeun subjék tina [[hak cipta]]. Aya nu mibogana iwal mun ku manéhna geus sacara éksplisit ditempatkeun di [[domain umum]]. Gambar ti internét perlu dilisénsikeun sacara langsung ti nu nyepeng hak cipta atawa ti nu séjén nu bisa ngalisénsikeun ngawakilan nu hakna. Dina sababaraha kasus, tungtunan \'\'[[fair use]]\'\' bisa ngawenangkeun dipakéna hiji fotograf.\n\n=== Tagging ===\n\nImage description pages can be tagged with a special tag to indicate the legal status of the images, as described at [[wikipedia:image copyright tags]]. It is unclear what should happen if different images have been uploaded with different copyright statuses.\n\n=== Fotograf pamaréntah ===\n\nKarya-karya nu dihasilkeun ku pagawé pamaréntah féderal [[Amérika Sarikat]] dina cakupan gawéna aya dina domain umum nurutkeun undang-undang. However, note that, despite popular misconception, the US Federal Government can own copyrights that are assigned to it by others. As a general rule photographs on .mil and .gov sites are public domain. However there are some notable exceptions. Check the privacy and security notice of the website. It should also be noted that governments outside the US often do claim copyright over works produced by their employees (for example, [[Crown Copyright]] in the [[United Kingdom]]). Also, most state governments in the United States do not place their work into the public domain and do in fact own the copyright to their work. Please be careful to check ownership information before copying.\n\n=== Fotograf selebriti ===\n\nThis is based on the image guidelines at [[IMDB]], so it especially applies to celebrity photographs, but also can apply to other pictures. Legitimate photographs generally come from three different places \'\'\'with permission\'\'\'.\n\n# The studios, producers, magazine publisher, or media outlet that originally shot the photograph.\n# Agencies that represent the photographers who shot the photos or the photographer themself (the latter especially for amateur photographs)\n# Submissions from the celebrity themselves or a legal representatives of the celebrity.\n\n== Hak jeung kawajiban kontributor ==\n\nMun anjeun nyumbangkeun bahan ka Wikipédia, hartina anjeun ngalisénsikeun éta karya ka umum dina panangtayungan GFDL (with no invariant sections, front-cover texts, or back-cover texts).\nPikeun nyumbang, hartina anjeun kudu dina kaayaan ngajamin lisénsi ieu nu maksudna\n* anjeun ngapimilik hakcipta bahan nu dimaksud, misalna kusabab mémang anjeun nu nyiptakeunana, atawa\n* anjeun nyokot bahanna ti sumber nu ngawenangkeun ngalisénsi dina panangtayungan GFDL, misal kusabab bahanna aya dina [[domain umum]] atawa mémang geus ti dituna medal dina panangtayungan GFDL.\n\nIn the first case, you retain copyright to your materials. You can later republish and relicense them in any way you like. However, you can never retract the GFDL license for the versions you placed here: that material will remain under GFDL forever. In the second case, if you incorporate external GFDL materials, as a requirement of the GFDL, you need to acknowledge the authorship and provide a link back to the network location of the original copy. If the original copy required invariant sections, you have to incorporate those into the Wikipedia article; it is however very desirable to replace GFDL texts with invariant sections by original content without invariant sections whenever possible.\n\n=== Migunakeun karya hak cipta batur ===\n\nIf you use part of a copyrighted work under \"[[fair use]]\", or if you obtain special permission to use a copyrighted work from the copyright holder under the terms of our license, you must make a note of that fact (along with names and dates). It is our goal to be able to freely redistribute as much of Wikipedia\'s material as possible, so original images and sound files licensed under the GFDL or in the [[public domain]] are greatly preferred to copyrighted media files used under fair use. See [[Wikipedia:Boilerplate request for permission]] for a form letter asking a copyright holder to grant us a license to use their work under terms of the GFDL. \n\nNever use materials that infringe the copyrights of others.\nThis could create legal liabilities and seriously hurt the project.\nIf in doubt, write it yourself.\n\nNote that copyright law governs the \'\'creative expression\'\' of ideas, not the ideas or information themselves. Therefore, it is perfectly legal to read an encyclopedia article or other work, reformulate it in your own words, and submit it to Wikipedia. (See [[plagiarism]] and [[fair use]] for discussions of how much reformulation is necessary in a general context.)\n\n=== Numbukeun ka karya nu mibanda hak cipta ===\n\nNumbukeun ka karya nu mibanda hak cipta biasana mah teu masalah, salila anjeun yakin yén kaca nu ditujul teu ngarumpak hak cipta \'\'batur\'\'. Mun mémang kitu, \'\'ulah\'\' numbukeun ka kaca éta. Whether such a link is contributory infringement is currently being debated in the courts, but in any case, linking to a site that illegally distributes someone else\'s work sheds a bad light on us.\n\n=== If you find a copyright infringement ===\n\nIt is not the job of rank-and-file Wikipedians to police every article for possible copyright infringement, but if you suspect one, you should at the very least bring up the issue on that page\'s talk page. Others can then examine the situation and take action if needed. The most helpful piece of information you can provide is a URL or other reference to what you believe may be the source of the text.\n\nSome cases will be false alarms. For example, if the contributor was in fact the author of the text that is published elsewhere under different terms, that does not affect their right to post it here under the GFDL. Also, sometimes you will find text elsewhere on the Web that was copied from Wikipedia. In both of these cases, it is a good idea to make a note in the talk page to discourage such false alarms in the future.\n\nIf some of the content of a page really is an infringement, then the infringing content should be removed, and a note to that effect should be made on the talk page, along with the original source. If the author\'s permission is obtained later, the text can be restored.\n\nIf \'\'all\'\' of the content of a page is a suspected copyright infringement, then the page should be listed it on [[Wikipedia:Possible copyright infringements]] and the content of the article replaced by the standard notice which you can find there. If, after a week, the page still appears to be a copyright infringement, then it may be deleted following the procedures on the votes page.\n\nIn extreme cases of contributors continuing to post copyrighted material after appropriate warnings, such users may be blocked from editing to protect the project.\n\n==If you are the owner of Wikipedia-hosted content being used without your permission==\nIf you are the owner of content that is being used on Wikipedia without your permission, then you may request the page be immediately removed from Wikipedia by following [[Wikipedia:Request for immediate removal of copyright violation | this link]]. You can also contact our [[Wikipedia:Designated agent|Designated agent]] to have it permanently removed, but it may take up to a week for the page to be deleted that way (you may also blank the page but the text will still be in the page history). Either way, we will, of course, need some evidence to support your claim of ownership.\n\n== Tempo ogé ==\n* The [[Wikipedia:Contributing FAQ]] for questions on copyright.\n* Wikipedia\'s [[Wikipedia:designated agent|designated agent]] under [[OCILLA]]\n* [[Wikipedia:Sites that use Wikipedia as a source]]\n* [[Wikipedia:Standard GFDL violation letter]]\n* [[Wikipedia:Possible copyright infringements]]\n* [[Wikipedia:Spotting possible copyright violations]]\n\nSawala salajengna...\n* [[Wikipedia:Copyright issues]]\n* [[m:Wikipedia and copyright issues]]\n* [[m:Avoid Copyright Paranoia]]\n* [[m:Permission grant extent]]\n\n[[Category:Wikipédia:Hak cipta|Hak cipta]]\n\n[[ca:Viquipèdia:Copyrights]] [[de:Wikipedia:Lizenzbestimmungen]] [[da:Wikipedia:Ophavsret]] [[en:Wikipedia:Copyrights]] [[fr:Wikipédia:Copyright]] [[ja:Wikipedia:著作権]] [[hu:Wikipédia:Copyright]] [[nl:Wikipedia:Auteursrechten]] [[no:Wikipedia:Opphavsrett]][[simple:Wikipedia:Copyrights]][[sv:Wikipedia:Upphovsrätt]] [[zh-cn:Wikipedia:版权信息]]','/* Hak jeung kawajiban pamaké */',3,'Kandar','20041202065156','',0,0,0,0,0.025129747123,'20041202065156','79958797934843'); INSERT INTO cur VALUES (1107,6,'Sourceberg.jpg','Lambang Wikisource','Lambang Wikisource',3,'Kandar','20040803104120','',0,0,0,1,0.210599109726585,'20050313153637','79959196895879'); INSERT INTO cur VALUES (1108,2,'Suisui','[[ja:利用者:Suisui]][[m:User:Suisui]]','',8,'Suisui','20040803121300','',0,0,0,1,0.060491372859,'20040803121355','79959196878699'); INSERT INTO cur VALUES (1109,3,'Suisui','Hi. I\'m mainly active on ja.wikipedia.\n\nIf you have any msg for me, please write it [[m:User talk:Suisui]]. Thanx.','',8,'Suisui','20040803121355','',0,0,1,1,0.425061375101,'20040803121355','79959196878644'); INSERT INTO cur VALUES (1110,0,'Bahan_kimia','\'\'\'Bahan kimia\'\'\' bisa ngandung harti [[unsur kimia]] atawa bahan nu wangunan unsur-unsur kimiawina tangtu: [[sanyawa kimia]]. Istilah ieu ogé mindeng ditujulkeun ka bahan bungkeuleukan, teu ukur partikel mandiri nu mikroskopik atawa submikroskopik, yén, \"\'\'bahan kimia\'\' téh mangrupa guruntulan husus atom atawa molekul.\"\n\n:\'\'Tempo ogé:\'\' [[kimia]], [[industri kimia]], [[molekul]], [[campuran]].\n\n\n{{pondok}}\n[[en:Chemical]] [[ja:%E8%96%AC%E5%93%81]]','',3,'Kandar','20041125073303','',0,0,0,0,0.630561911795,'20050303211247','79958874926696'); INSERT INTO cur VALUES (1111,0,'Kimia_lingkungan','{{CabangKimia}}','',3,'Kandar','20040804044252','',0,0,0,1,0.888693957072,'20040804044356','79959195955747'); INSERT INTO cur VALUES (1113,0,'Tabel_periodik','\'\'\'Tabel periodik unsur kimiawi\'\'\' ngarupakeun pintonan tabular [[unsur kimiawi]] nu dipikanyaho. Unsur-unsur disusun dumasar struktur [[éléktron]] sahingga rupa-rupa [[sipat kimiawi]]na puguh susunanana sapanjang tabelna. Nu ditémbongkeun utamana [[wilangan atom]] sarta [[lambang kimiawi]]na. \n\n[[Tabel periodik#Tabel periodik baku|Tabel baku]] nyadiakeun dasar-dasar nu perlu. Aya ogé [[Tabel periodik#Métode séjén pikeun mintonkeun unsur-unsur kimiawi|Métode séjén pikeun mintonkeun unsur-unsur kimiawi]] pikeun leuwih rinci atawa sawangan séjénna.\n\n==Golongan==\n[[Golongan tabel periodik|Golongan]] mangrupa kolom vértikal dina tabel periodik. Aya 18 golongan dina tabel periodik baku. Unsur-unsur nu sagolongan mibanda konfigurasi éléktron [[cangkang valénsi|valénsi]] nu sarua/mirip, sahingga sipat-sipatna ogé mirip.\n\n===Nomer golongan===\nAya tilu sistim [[golongan tabel periodik#Nomer golongan|nomer golongan]]; hiji maké wilangan Arab, sedengkeun nu séjénna wilangan Romawi. Ngaran wilangan Romawi ngarupakeun ngaran tradisional asli golongan; ngaran wilangan Arab ngarupakeun skéma nu leuwih anyar nu dirékoméndasikeun ku [[International Union of Pure and Applied Chemistry]] (IUPAC). Skéma IUPAC dijieun pikeun ngaganti dua sistim wilangan Romawi nu heubeul sabab ngalieurkeun ku ayana ngaran nu sarua pikeun maksud nu béda.\n\n==Tabel periodik baku==\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
[[Golongan tabel periodik|\'\'\'Golongan\'\'\' →]][[Logam alkali|\'\'\'1\'\'\']][[Taneuh alkalin|\'\'\'2\'\'\']]
[[Unsur golongan 3|\'\'\'3\'\'\']][[Unsur golongan 4|\'\'\'4\'\'\']][[Unsur golongan 5|\'\'\'5\'\'\']][[Unsur golongan 6|\'\'\'6\'\'\']][[Unsur golongan 7|\'\'\'7\'\'\']][[Unsur golongan 8|\'\'\'8\'\'\']][[Unsur golongan 9|\'\'\'9\'\'\']][[Unsur golongan 10|\'\'\'10\'\'\']][[Coinage metal|\'\'\'11\'\'\']][[Unsur golongan 12|\'\'\'12\'\'\']][[Golongan boron|\'\'\'13\'\'\']][[Golongan karbon|\'\'\'14\'\'\']][[Pnictogen|\'\'\'15\'\'\']][[Chalcogen|\'\'\'16\'\'\']][[Halogén|\'\'\'17\'\'\']][[Gas mulya|\'\'\'18\'\'\']]
[[Periode tabel periodik|\'\'\'Periode\'\'\' ↓]]
[[Unsur periode 1|\'\'\'1\'\'\']]1
[[Hidrogén|H]]

2
[[Hélium|He]]
[[Unsur periode 2|\'\'\'2\'\'\']]3
[[Litium|Li]]
4
[[Berilium|Be]]


5
[[Boron|B]]
6
[[Karbon|C]]
7
[[Nitrogén|N]]
8
[[Oksigén|O]]
9
[[Florin|F]]
10
[[Néon|Ne]]
[[Unsur periode 3|\'\'\'3\'\'\']]11
[[Natrium|Na]]
12
[[Magnesium|Mg]]


13
[[Aluminium|Al]]
14
[[Silikon|Si]]
15
[[Fosfor|P]]
16
[[Walirang|S]]
17
[[Klorin|Cl]]
18
[[Argon|Ar]]
[[Unsur periode 4|\'\'\'4\'\'\']]19
[[Kalium|K]]
20
[[Kalsium|Ca]]

21
[[Skandium|Sc]]
22
[[Titanium|Ti]]
23
[[Vanadium|V]]
24
[[Kromium|Cr]]
25
[[Mangan|Mn]]
26
[[Beusi|Fe]]
27
[[Kobalt|Co]]
28
[[Nikel|Ni]]
29
[[Tambaga|Cu]]
30
[[Séng|Zn]]
31
[[Galium|Ga]]
32
[[Germanium|Ge]]
33
[[Arsén|As]]
34
[[Sélénium|Se]]
35
[[Bromin|Br]]
36
[[Kripton|Kr]]
[[Unsur periode 5|\'\'\'5\'\'\']]37
[[Rubidium|Rb]]
38
[[Stronsium|Sr]]

39
[[Itrium|Y]]
40
[[Zirkonium|Zr]]
41
[[Niobium|Nb]]
42
[[Molibdenum|Mo]]
43
[[Téhnetium|Tc]]
44
[[Rutenium|Ru]]
45
[[Rodium|Rh]]
46
[[Paladium|Pd]]
47
[[Pérak|Ag]]
48
[[Kadmium|Cd]]
49
[[Indium|In]]
50
[[Tin|Sn]]
51
[[Antimony|Sb]]
52
[[Telurium|Te]]
53
[[Iodin|I]]
54
[[Xenon|Xe]]
[[Unsur periode 6|\'\'\'6\'\'\']]55
[[Sesium|Cs]]
56
[[Barium|Ba]]
*
71
[[Lutetium|Lu]]
72
[[Hafnium|Hf]]
73
[[Tantalum|Ta]]
74
[[Tungsten|W]]
75
[[Rhenium|Re]]
76
[[Osmium|Os]]
77
[[Iridium|Ir]]
78
[[Platinum|Pt]]
79
[[Emas|Au]]
80
[[Raksa (unsur)|Hg]]
81
[[Thallium|Tl]]
82
[[Timbal|Pb]]
83
[[Bismut|Bi]]
84
[[Polonium|Po]]
85
[[Astatin|At]]
86
[[Radon|Rn]]
[[Unsur periode 7|\'\'\'7\'\'\']]87
 [[Francium|Fr]] 
88
[[Radium|Ra]]
**
103
[[Lawrencium|Lr]]
104
[[Rutherfordium|Rf]]
105
[[Dubnium|Db]]
106
[[Seaborgium|Sg]]
107
[[Bohrium|Bh]]
108
[[Hassium|Hs]]
109
[[Meitnerium|Mt]]
110
[[Darmstadtium|Ds]]
111
[[Roentgenium|Rg]]
112
[[Ununbium|Uub]]
113
[[Ununtrium|Uut]]
114
[[Ununquadium|Uuq]]
115
[[Ununpentium|Uup]]
116
[[Ununhexium|Uuh]]
117
[[Ununseptium|Uus]]
118
[[Ununoctium|Uuo]]

* \'\'\'[[Lantanida]]\'\'\'57
[[Lanthanum|La]]
58
[[Cerium|Ce]]
59
[[Praseodymium|Pr]]
60
[[Neodymium|Nd]]
61
[[Promethium|Pm]]
62
[[Samarium|Sm]]
63
[[Europium|Eu]]
64
[[Gadolinium|Gd]]
65
[[Terbium|Tb]]
66
[[Dysprosium|Dy]]
67
[[Holmium|Ho]]
68
[[Erbium|Er]]
69
[[Thulium|Tm]]
70
[[Ytterbium|Yb]]
** \'\'\'[[Aktinida]]\'\'\'89
[[Actinium|Ac]]
90
[[Thorium|Th]]
91
[[Protactinium|Pa]]
92
[[Uranium|U]]
93
[[Neptunium|Np]]
94
[[Plutonium|Pu]]
95
[[Americium|Am]]
96
[[Curium|Cm]]
97
[[Berkelium|Bk]]
98
[[Californium|Cf]]
99
[[Einsteinium|Es]]
100
[[Fermium|Fm]]
101
[[Mendelevium|Md]]
102
[[Nobelium|No]]
\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
[[Dérét tabel periodik|Dérét Kimiawi Tabel Periodik]]
[[Logam alkali]][[Taneuh alkalin]][[Lantanid]][[Aktinid]]s[[Logam transisi]]
[[Poor metal]][[Métaloid]][[Nonlogam]][[Halogén]][[Gas mulya]]es
\n\nSandi warna pikeun wilangan atom:\n* Unsur nu wilanganana biru mangrupa cair na [[temperatur jeung tekanan baku]] (standard temperature and pressure, STP);\n* nu héjo mangrupa gas na STP;\n* nu hideung mangrupa padet na STP;\n* nu beureum mangrupa [[Unsur sintétik|sintétik]] (sadayana padet na STP).\n* nu abu-abu can kapanggih (they also have muted fill colors indicating the likely chemical series they would fall under).\n\n==Métode séjén pikeun mintonkeun unsur-unsur kimiawi==\n*[[Tabel periodik (baku)|Tabel baku]] (sarua jeung di luhur) nyadiakeun dasar.\n*[[Tabel periodik (alternate)|Alternate Table]]\n*[[Tabel periodik (anti)|Anti table]]\n*[[Tabel periodik (badag)|Tabel badag]] nu nyadiakeun dadasar sarta ngaran unsur lengkep.\n*[[Tabel periodik (huge)|huge table]] provides the basics plus full element names and [[atomic mass]]es.\n*[[Periodic table (wide)|Wide Table]]\n*[[Periodic table (extended)|Extended Table]]\n*[[Tabel periodik (konfigurasi éléktron)|Konfigurasi Éléktron]]\n*[[Tabel periodik (logam jeung nonlogam)|Logam jeung Nonlogam]]\n*[[Tabel periodik (balok)|Tabel periodik eusi balok]]\n*[[Daptar unsur dumasar ngaran]]\n*[[Daptar unsur dumasar lambang]]\n*[[Daptar unsur dumasar wilangan atomik]] \n*[[Daptar unsur dumasar titik golak]]\n*[[Daptar unsur dumasar titik lééh]]\n*[[Daptar unsur dumasar dénsiti]]\n*[[Daptar unsur dumasar beurat atom]]\n\nJeung ieu [http://bic.beckman.uiuc.edu/mritab1/ tabel periodik] pikeun [[résonansi magnétik]].\n\n== Dadaran ngeunaan struktur tabel periodik ==\n\nJumlah [[cangkang éléktron]] hiji atom nangtukeun kaasup periode sabaraha. Unggal cangkang kabagi kana subcangkang nu béda-béda, di mana nambahna wilangan atom ngeusian nuturkeun urutan nu sacara kasar kawas kieu:\n\n 1s\n 2s 2p\n 3s 3p\n 4s 3d 4p\n 5s 4d 5p\n 6s 4f 5d 6p\n 7s 5f 6d 7p\n 8s 5g 6f 7d 8p\n ...\n\nHence the structure of the table. Since the outermost electrons determine chemical properties, those tend to be similar within groups. Elements adjacent to one another within a group have similar physical properties, despite their significant differences in [[mass]]. Elements adjacent to one another within a period have similar mass but different properties.\n\nFor example, very near to [[nitrogen]] (N) in the second period of the chart are [[carbon]] (C) and [[oxygen]] (O). \nDespite their similarities in mass (they differ by only a few [[atomic mass unit]]s), they have extremely different properties, as can be seen by looking at their [[allotrope|allotropes]]: diatomic oxygen is a [[gas]] that supports burning, diatomic nitrogen is a gas that does not support burning, and carbon is a [[solid]] which can be burnt (yes, [[diamond|diamonds]] can be burnt!).\n\nIn contrast, very near to [[chlorine]] (Cl) in the next-to-last group in the chart (the [[halogen|halogens]]) are [[fluorine]] (F) and [[bromine]] (Br).\nDespite their dramatic differences in mass within the group, their allotropes have very similar properties: \nThey are all highly [[corrosion|corrosive]] (meaning they combine readily with [[metal|metals]] to form [[metal halide]] [[salt|salts]]); chlorine and fluorine are gases, while bromine is a very low-boiling [[liquid]]; chlorine and bromine at least are highly colored.\n\n== Sajarah ==\n\'\'Artikel utama: [[Sajarah tabel periodik]]\'\'\n\nTabel asli dijieunna tanpa pangaweruh ngeunaan struktur jero [[atom]]: mun urang nyusun unsur-unsur dumasar [[massa atom]], lajeng ngaplot salasahiji sipat séjénna kana massa atomna, one sees an undulation or \'\'periodicity\'\' to these properties as a function of atomic mass. \nThe first to recognize these regularities was the German chemist [[Johann Wolfgang Döbereiner]] who, in [[1829]], noticed a number of \'\'triads\'\' of similar elements:\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Some triads
UnsurMassa atomikDénsitas
klorin35.50.00156 g/cm3
bromin79.90.00312 g/cm3
iodin126.90.00495 g/cm3
 
kalsium40.11.55 g/cm3
strontium87.62.6 g/cm3
barium1373.5 g/cm3
\n\nIeu salajengna dituturkeun ku kimiawan Inggris [[John Alexander Reina Newlands]], nu taun [[1865]] ngémbarkeun yén unsur-unsur nu tipena sarua kaulang unggal selang dalapan unsur, nu ceuk manéhna bet mirip [[oktaf|oktaf musik]], najan \'\'hukum oktaf\'\'na diseungseurikeun ku batur-baturna. Tungtungna, taun [[1869]] kimiawan Jérman [[Lothar Meyer]] jeung Rusia [[Dmitry Ivanovich Mendeleev]] ampir bareng ngembangkeun tabel periodik munggaran, nyusun unsur-unsur dumasar massa. Ngan, Mendeleev plotted a few elements out of strict mass sequence in order to make a better match to the properties of their neighbours in the table, corrected mistakes in the values of several atomic masses, and predicted the existence and properties of a few new elements in the empty cells of his table. Mendeleev was later vindicated by the discovery of the electronic structure of the elements in the late [[19th century|19th]] and early [[20th century]].\n\n==Sumberdaya séjén==\n* Mazurs, E.G., \"\'\'Graphical Representations of the Periodic System During One Hundred Years\'\'\". University of Alabama Press, Alabama. 1974.\n* Bouma, J., \"\'\'An Application-Oriented Periodic Table of the Elements\'\'\". J. Chem. Ed., 66 741 (1989).\n\n== Tempo ogé ==\n* [[Golongan tabel periodik]]\n* [[Periode tabel periodik]]\n* [[Dérét kimiawi]]\n* [[Periodic table block]]\n\n* [[Tabe isotop (lengkep)]]\n* [[Isotope table (divided)]]\n\n* [[Papanggihan unsur kimiawi]]\n* [[Abundance of the chemical elements]]\n* [[Elements song]]\n\n* [[IUPAC]]\'s [[systematic element name]]s.\n\n* [[Cosmochemical Periodic Table of the Elements in the Solar System]]\n\n== Tumbu kaluar ==\n\n* \"\'\'[http://www.wou.edu/las/physci/ch412/alttable.htm Presentation forms of the periodic table]\'\'\". Western Oregon University.\n* \"\'\'[http://www.wou.edu/las/physci/ch412/perhist.htm A Brief History of the Development of Periodic Table]\'\'\". Western Oregon University.\n* \"\'\'[http://www.chemsoc.org/viselements/pages/periodic_table.html Visual Periodic Table]\'\'\". ChemSoc.org.\n* Barbalace, Kenneth L., \"\'\'[http://environmentalchemistry.com/yogi/periodic/ Biochemical Periodic Tables]\'\'\". KLBProductions.com.\n* \"\'\'[http://www.webelements.com Periodic table] (professional edition)\'\'\". WebElements.\n* Counterman, Craig, \"\'\'Periodic Table of the Elements : [http://web.mit.edu/3.091/www/pt/ Atomic Number]\'\'\". MIT Course 3.091.\n* Holler, F. James, and John P. Selegue, \"\'\'[http://www.uky.edu/Projects/Chemcomics/ Periodic Table of Comic Books]\'\'\". Department of Chemistry, University of Kentucky. 1996-2002.\n* Heilman, Chris, \"\'\'[http://chemlab.pc.maricopa.edu/periodic/default.html The Pictorial Periodic Table]\'\'\". (Includes alternate styles: Stowe, Benfey, Zmaczynski, Giguere, Tarantola, Filling, Mendeleev)\n* \"\'\'[http://pearl1.lanl.gov/periodic/default.htm Periodic table]\'\'\". Los Alamos National Laboratory\'s Chemistry Division. \n* \"\'\'[http://www.phys.ufl.edu/fermisurface/periodic_table.html Periodic Table of the Fermi Surfaces of Elemental Solids]\'\'\". [http://www.phys.ufl.edu/fermisurface/ The Fermi Surface Database]\n* \"\'\'[http://www.nyu.edu/cgi-bin/cgiwrap/aj39/NMRmap.cgi Interactive NMR Frequency Map]\'\'\". Texas A&M.\n* \"\'\'[http://www.science.co.il/PTelements.asp Periodic Table Elements]\'\'\". Israel Science and Technology Directory. 1999-2004. (sorted by physical characteristics)\n* Barthelmy, David, \"\'\'[http://webmineral.com/chemical.shtml Periodic table]\"\'\' Mineralogy Database. (mineral emphasis)\n* Gray, Theodore, \"\'\'[http://www.theodoregray.com/PeriodicTable/ Wooden Periodic Table Table]\'\'\" (with samples)\n* \"\'\'[http://www.dartmouth.edu/~chemlab/info/resources/p_table/Periodic.html Periodic table applet]\'\'\". Dartmouth College. ([[Java programming language|Java]])\n* Jacobs, Bob, \"\'\'[http://www.chemistrycoach.com/periodic_tables.htm Periodic Tables] (in case you were thinking that the Internet needed one more)\'\'\". The Chemistry Coach.\n* \"\'\'[http://periodictable.com/ Periodic Table].Com\'\'\". \n\n[[af:Periodieke tabel]]\n[[bg:Периодична таблица]]\n[[ca:Taula periòdica]]\n[[cs:Periodická tabulka]]\n[[cy:Tabl Cyfnodol]]\n[[da:Det periodiske system]]\n[[de:Periodensystem]]\n[[en:Periodic table]]\n[[eo:Perioda tabelo]]\n[[es:Tabla periódica de los elementos]]\n[[et:Keemiliste elementide perioodilisussüsteem]]\n[[eu:Elementuen sailkapen periodiko]]\n[[fa:جدول تناوبی (استاندارد)]]\n[[fi:Alkuaineiden jaksollinen järjestelmä]]\n[[fo:Skeiðbundna skipanin]]\n[[fr:Tableau périodique des éléments]]\n[[ga:Tábla peiriadach]]\n[[he:הטבלה המחזורית]]\n[[hr:Periodni sustav elemenata]]\n[[hu:Periódusos rendszer]]\n[[id:Tabel periodik]]\n[[io:Periodala tabelo dil elementaro]]\n[[is:Lotukerfið]]\n[[it:Tavola periodica]]\n[[ja:周期表]]\n[[ko:원소 주기율표]]\n[[ku:Tabloya periyodîk a elementan]]\n[[la:Systema Periodica]]\n[[lb:Periodesystem vun den Elementer]]\n[[li:Periodiek systeem vaan elemente]]\n[[lt:Periodinė elementų lentelė]]\n[[lv:Elementu periodiskā tabula]]\n[[mi:Ripanga pūmotu]]\n[[mk:Периоден систем]]\n[[ms:Jadual berkala]]\n[[nds:Periodensysteem]]\n[[nl:Periodiek systeem]]\n[[nn:Periodesystemet]]\n[[no:Periodesystemet]]\n[[pl:Układ okresowy pierwiastków]]\n[[pt:Tabela Periódica]]\n[[ru:Периодическая система элементов]]\n[[simple:Periodic table]]\n[[sk:Periodická tabuľka]]\n[[sl:Periodni sistem elementov]]\n[[sr:Периодни систем елемената]]\n[[sv:Periodiska systemet]]\n[[ta:ஆவர்த்தன அட்டவணை]]\n[[th:ตารางธาตุ]]\n[[tr:Periyodik cetvel]]\n[[uk:Періодична система]]\n[[wa:Tåvlea periodike des elemints]]\n[[zh:元素周期表]]\n{{CabangKimia}}\n{{TabelPeriodik}}\n\n[[Category:Kimia]]','',0,'61.10.7.83','20050312122654','',0,0,0,0,0.998836122453,'20050316081936','79949687877345'); INSERT INTO cur VALUES (1114,0,'Wikipédia:Bantahan_umum','\'\'\'Bantahan umum\'\'\' - [[Wikipédia:Bantahan résiko|Migunakeun Wikipédia, résiko tanggung nyalira!]] - [[Wikipédia:Bantahan médis|Wikipédia teu méré naséhat médis]] - [[Wikipédia:Bantahan hukum|Wikipédia teu méré pamanggih hukum]] - [[Wikipédia:Bantahan eusi|Wikipédia ngandung bahan nu teu nyugemakeun]]\n\n
\nWIKIPÉDIA TEU NGAJAMIN EUSI NU SOHÉH\n
\n\n\'\'\'Wikipédia\'\'\' ngarupakeun énsiklopédi eusi-muka (\'\'open-content\'\') online, nu ngandung harti, hiji gempungan sukaréla nu ngembangkeun hiji sumberdaya umum pangaweruh urang. Strukturna ngabisakeun sing saha baé nu miboga sambungan Internét sarta panyaksrak \'\'World Wide Web\'\' pikeun ngarobah eusi nu kapanggih di dieu. Kusabab kitu, perlu kauninga yén nu aya di dieu teu merlukeun diulas ku para profésional husus nu mémang kaweruhna dipikabutuh pikeun nyadiakeun béja ngeunaan naon baé na \'\'Wikipédia\'\' kalawan lengkep, akurat, sarta bisa dipercaya.\n\nSadaya ieu teu ngandung harti yén anjeun moal manggih béja nu boga ajén sarta akurat na \'\'Wikipédia\'\', tapi ogé, mugia kauninga yén \'\'\'\'\'Wikipedia\'\' TEU BISA ngajamin, dina jalan naon baé, sohéhna béja nu kapanggih di dieu.\'\'\' Eusina bisa cikénéh pisan robah, diruksak, atawa diganggu ku jalma séjén nu pamanggihna teu saluyu jeung jihat pangaweruh dina widang husus nu kabeneran keur dipaluruh ku anjeun. Urang keur ngusahakeun cara pikeun milih sarta nyatujuan vérsi artikel nu bisa leuwih dipercaya, tapi tetep tanpa jaminan. 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You are being granted a limited license to copy anything from this site; it does not create or imply any contractual or extracontractual liability on the part of \'\'Wikipedia\'\' or any of its agents, members, organizers or other users.\n\nAny of the trademarks, service marks, collective marks, design rights, personality rights or similar rights that are mentioned, used or cited in the articles of the Wikipedia encyclopedia are the property of their respective owners. Their use here does not imply that you may use them for any other purpose other than for the same or a similar informational use as contemplated by the original authors of these Wikipedia articles under the GFDL licensing scheme. Unless otherwise stated Wikipedia and Wikimedia sites are neither endorsed nor affiliated with any of the holders of any such rights and as such Wikipedia can not grant any rights to use any otherwise protected materials. \'\'Your use of any such or similar incorporeal property is at your own risk.\'\'\n\nPlease note that that the information found here may be in violation of the laws of the country or jurisdiction from where you are viewing this information. \'\'Wikipedia\'\' does not encourage the violation of any laws, but as this information is stored on a server in the State of [[Florida]] in the [[United States of America]], it is being maintained in reference to the protections afforded to all under the [[United States Constitution]]\'s [[First Amendment]] and under the principles of the [[Universal Declaration of Human Rights]] of the [[United Nations]]. The laws in your country may not recognize as broad a protection of free speech as the laws of the United States or the principles under the UN Charter, and as such, \'\'Wikipedia\'\' cannot be responsible for any potential violations of such laws should you link to this domain or use any of the information contained herein in anyway whatsoever.\n\n:\'\'\'If you need specific advice (for example, medical, legal, financial, or risk management) please seek a professional who is licensed or knowledgeable in that area.\'\'\' Read [[Wikipedia:Risk disclaimer]], [[Wikipedia:Medical disclaimer]], and [[Wikipedia:Legal disclaimer]] for specific disclaimers.\n\n:\'\'\'Wikipedia is not uniformly peer reviewed; while readers may correct errors or remove erroneous suggestions they have no legal duty to do so and thus all information read here is without any implied warranty of fitness for any purpose or use whatsoever.\'\'\' \n\n\'\'\'No consequential damages can be sought against \'\'Wikipedia\'\'\'\'\', as it is a voluntary association of individuals developed freely to create various open source online educational, cultural and informational resources. \'\'\'This information is being given to you gratuitously\'\'\' and there is \'\'\'no agreement or understanding between you and \'\'Wikipedia\'\'\'\'\' regarding your use or modification of this information beyond the [[GNU Free Documentation License]]; neither is anyone at \'\'Wikipedia\'\' responsible should someone change, edit, modify or remove any information that you may post on \'\'Wikipedia\'\' or any of its associated projects.\n\nThank you for spending the time to read this page, and please enjoy your experience at \'\'Wikipedia\'\'. \n\n\n[[ca:Viquipèdia:Avís legal]]\n[[da:Wikipedia:Generelle forbehold]]\n[[en:Wikipedia:General disclaimer]]\n[[hu:Wikip%C3%A9dia:Jogi_nyilatkozat]]\n[[no:Wikipedia:Generelle forbehold]]\n[[pl:Wikipedia:Zrzeczenie się odpowiedzialności]]\n[[simple:Wikipedia:General disclaimer]]\n[[sv:Wikipedia:Allmänt förbehåll]]\n[[zh:Wikipedia:%E5%85%8D%E8%B4%A3%E5%A3%B0%E6%98%8E]]\n[[ro:Wikipedia:General disclaimer]]','',3,'Kandar','20040812041750','',0,0,0,0,0.688009218168,'20040812041750','79959187958249'); INSERT INTO cur VALUES (1115,0,'Ceuli','[[Image:ceuli.jpg|framed|100px|Ceuli katuhu [[manusa]].]]\n\'\'\'Ceuli\'\'\' atawa \'\'\'cepil\'\'\' mangrupakeun organ nu dipaké ku sato pikeun ngariksa [[sora]]. Istilah ieu bisa nujul ka sakabéh sistim pikeun ngumpulkeun sarta ngolah sora (mimiti [[sistim pangrungu]]), atawa sakadar bagéan luar nu katempo.\n\n== Organ pangrungu lian-mamalia ==\n\nLancah boga bulu na sukuna nu dipaké pikeun \"nyabak\" sora.\n\nCeuli réptil ngan boga hiji tulang - \'\'malleus\'\' (tempo di handap).\n\n== Ceuli mamalia ==\n[[Image:anatomi_ceuli_manusa.png|thumb|250px|Anatomi ceuli manusa.]]\n[[Mamalia]], kaasup [[manusa]], boga dua ceuli, hiji di unggal sisi sirah.\n\n\'\'\'Ceuli luar\'\'\' nyaéta bagéan luar ceuli. Bagéan nu ketempo disebut [[pinna]], atawa [[auricle]], n fungsina pikeun ngumpulkeun sarta mokuskeun gelombang sora. Loba mamalia nu bisa ngagerakkeun pinna sangkan bisa mokuskeun sarta ngarahkeun pangdéngéna, sakumaha maranéhna bisa ngagilerkeun [[panon]]na. Manusa sacara umum geus leungiteun kabisa ieu. Ti pinna, [[gelombang]] [[tekenan sora]] p ([[Pascal]]) mepay ka [[liang ceuli]], solobong basajan nu nujul ka [[ceuli tengah]].\n\n\'\'\'Ceuli tengah\'\'\' ngawengku [[kendang ceuli]] ([[tympanum]] atawa [[mémbran tympanik]]) jeung [[osikel]], tilu tulang leutik na ceuli tengah.\n\n== Kasakit jeung kaayaan médis ceuli sarta sistim pangrungu ==\n\nKagangguna ceuli atawa sistim olah pangrungu na [[otak]] bisa ngakibatkeun [[torék]].\n\n* [[Acoustic neurinoma]]\n* [[Balance disorder]]s\n* [[Barotrauma]]\n* [[Benign Paroxysmal Positional Vertigo]]\n* [[Cholesteatoma]]\n* [[Ear infection]]s\n* [[Conductive hearing impairment]]\n* [[Labyrinthine hydrops]]\n* [[Labyrinthitis]]\n* [[Ménière\'s disease]]\n* [[Meningitis]]\n* [[Neurofibromatosis Type 1]]\n* [[Neurofibromatosis Type 2]]\n* [[Noise-induced hearing loss]]\n* [[Nonsyndromic hereditary hearing impairment]]\n* [[Otitis externa]]\n* [[Otitis media]]\n* [[Otosclerosis]]\n* [[Perilymph fistula]]\n* [[Presbycusis]]\n* [[Sensorineural hearing loss]]\n* [[Sudden deafness]]\n* [[Tinnitus]]\n* [[Usher syndrome]]\n* [[Vestibular neuronitis]]\n\n== Tempo ogé ==\n\n* [[Glosarium istilah médis nu patali jeung kalainan komunikasi]]\n* [[Sistim vestibular]]\n* [[Cerumen]]\n\n{{pondok}}\n[[Category:Sistim pangrungu]]\n[[Category:Sistim sénsor]]\n[[Category:Sistim saraf]]\n\n[[ca:Oïda]] [[cs:Ucho]] [[cy:Clust]] [[da:Øre (legemsdel)]] [[de:Ohr]] [[en:Ear]] [[es:Oído]] [[fr:Oreille]] [[he:אוזן]] [[id:Telinga]] [[is:Eyra]] [[it:Orecchio]] [[ja:耳]] [[nl:Oor]] [[pl:Ucho]]','',3,'Kandar','20050228064740','',0,0,1,0,0.51738515986,'20050303211247','79949771935259'); INSERT INTO cur VALUES (1116,0,'Panon',': \'\'Artikel ieu nujul ka organ panempo. Tempo [[Eye (disambiguation)]] pikeun guna séjénna.\'\'\n\n\'\'\'Panon\'\'\' ngarupakeun hiji [[organ (anatomi)|organ]] nu boga tujuan pikeun ngariksa [[cahya]]. Panon nu pangbasajanna teu migawé lian ti ngariksa naha sakuriling téh caang atawa poék. Panon nu leuwih kompléks dipaké pikeun nyadiakeun rasa [[daya téwak visual|sawangan]]. \n\n[[Panon majemuk]] dipimilik ku [[arthropod]] (serangga jeung sabangsana), nu disusun ku fasét-fasét basajan nu ngahasilkeun \'\'pixelated image\'\' (lain sababaraha gambar sakumaha nu disangka). \n\n\n\n\n\n
\n[[image:Human eye cross-sectional view grayscale.png]]
\n\'\'Diagram panon manusa. Catet yén teu sadaya panon mibanda anatomi nu sarua jeung panon manusa.\'\'







\n
[[Image:Focus in an eye.png]]
\'\'Cahya ti hiji titik tunggal nu jauh jeung cahya ti hiji titik tunggal séjén nu deukeut dibawa kana fokus\'\'







\n\n[[Image:Cheche.JPG|Panon]]
\n\'\'Panon manusa cenah mangrupa jandéla jiwa\'\'\n
[[Image:Eye.png|thumb|right|Eye, png & svg image]]\n
\n\nPikeun kalolobaan [[vertebrata]] jeung sababaraha [[molluska]], fungsi panon nyaéta pikeun ngeunteungkeun (proyéksi) gambar kana [[rétina]] nu peka ku cahya, where the light is detected and transmitted to the [[brain]] via the [[optic nerve]]. The eye is typically roughly spherical, filled with a [[transparency (optics)|transparent]] gel-like substance called the [[vitreous humour]], with a focusing [[Lens (vision)|lens]] and often a muscle called the [[iris of the eye|iris]] that controls how much light enters.\n\n==Mokuskeun==\nIn order for light rays to be brought to a [[focus]] they must be [[refraction|refracted]]. The amount of refraction required depends on the distance of the object which is being viewed. A distant object will require less bending of light than a nearer one. Most of the refraction occurs at the [[cornea]] which has a fixed curvature. The remainder of the required refraction occurs at the lens. The lens can be pulled flatter or rounder by muscles, which adjust the power of the lens. As we age we lose this ability to adjust the focus. Such a condition is known as [[presbyopia]]. There are other [[refraction error]]s arising from the shape of the cornea and lens, and from the length of the eyeball. These include [[myopia]], [[hyperopia]], and [[astigmatism]].\n\n----\n\nTempo \'\'site\'\' ieu pikeun diagram panon nu hadé [http://webvision.med.utah.edu/anatomy.html]\n\n==Bagéan-bagéan panon==\n* [[Kornéa]]\n* [[Iris panon|Iris]]\n* [[Pupil]]\n* [[Aqueous humour]]\n* [[Lénsa (vision)|Lénsa]]\n* [[Vitreous humour]]\n* [[Rétina]]\n* [[Macula]]\n* [[Optic fovea|Fovea]]\n* [[Blind spot (anatomy)|Blind spot]]\n* [[Sclera]]\n* [[Tapetum lucidum]] (lain di manusa)\n\n==Gangguan==\n*[[Achromatopsia]]\n*[[Age-related macular degeneration]]\n*[[Aniridia]]\n*[[Amblyopia]]\n*[[Anisometropia]]\n*[[Arc eye]]\n*[[Astigmatism]]\n*[[Lolong]]\n*[[Katarak]]\n*[[Lolong warna]]\n*[[Conjunctivitis]]\n*[[Corrective lens]]es\n*[[Floater|Floaters]]\n*[[Glaukoma]]\n*[[Hypermetropia]]\n*[[Myopia]]\n*[[Nyctalopia]]\n*[[Presbyopia]]\n*[[Retinopathy]]\n*[[Scotoma]]\n*[[Snow blindness]]\n*[[Strabismus]]\n*[[Uveitis]]\n\n==Tempo ogé==\n*[[Visual perception]]\n*[[Saccade]]\n*[[Persistence of vision]]\n*[[Macropsia]]\n*[[Micropsia]]\n*[[Optometry]]\n*[[Opthamologist|Opthamology]]\n*[[Eyeglass prescription]]\n*[[Crystallin]]\n*[[Nictating membrane]]\n*[[Adaptation]]\n*[[Tears]]\n*[[Visual acuity]]\n*[[Snellen chart]]\n\n==Tumbu kaluar==\n*[http://www.pbs.org/wgbh/evolution/library/01/1/l_011_01.html Évolusi Panon]\n\n[[cs:Oko]]\n[[cy:Llygad]]\n[[da:Øje]]\n[[de:Auge]]\n[[en:Eye]]\n[[eo:Okulo]]\n[[es:Ojo]]\n[[fr:Œil]]\n[[he:עין]]\n[[id:Mata]]\n[[is:Auga]]\n[[it:Occhio]]\n[[ja:目]]\n[[ms:Mata]]\n[[nl:Oog]]\n[[pl:Oko]]\n[[pt:Olho]]\n[[sv:Öga]]\n[[tokipona:oko]]\n[[zh:眼睛]]\n\n{{Panon}}\n{{Visual_system}}\n[[Category:Visual system]]\n[[Category:Optik]]\n[[Category:Computer vision]]\n[[Category:Oftalmologi]]','',0,'63.249.97.119','20041222031808','',0,0,0,0,0.168961940412,'20041222031808','79958777968191'); INSERT INTO cur VALUES (1117,0,'Baham','{|cellpadding=\"0\" cellspacing=\"0\" style=\"float:right;\"\n|-\n|[[image:bahamsagital.png|right|thumb|Potongan sagital irung, baham, faring, jeung laring.]]\n|-\n|} \n\n\'\'\'Baham\'\'\' nyaéta lawang asup pikeun [[sato]] [[meal|ngasupkeun]] [[dahareun]]. Biasana aya na [[hulu]], tapi teu salawasna; baham [[planaria]] aya na beuteungna.\n\nKalolobaan sato mibanda [[sistim digéstif]] nu lengkep: baham di hiji tungtung sarta [[bool]] di tungtung séjén. Tungtung mana nu kabentuk tiheula na [[ontogeni]] ngarupakeun kriteria nu dipaké pikeun nangtukeun kelas sasatoan kana [[protostom]] jeung [[deutérostom]].\n\nSababaraha sato, kayaning [[cnidarian]] jeung planaria, teu boga bool. Maranéhna miceun ngaliwatan sungutna, atawa sarua jeung [[brachiopod]], nu boga sistim digéstif nu éfisién pisan, digiling na [[beuteung]] nepi ka réngsé.\n\nSababaraha rupa satu, kawas [[cacing pita]], teu boga sungut-sungut acan. Cacing pita hirup jero peujit, sahingga teu butuh sistim pencernaan.\n\nDi kalolobaan sato, sungutna boga babagian pikeun nyapék dahareun, ngabeuweung dahareun, atawa pikeun nyuntikkeun peurah/racun. Dina [[artropod]], aya suku nu dimodifikasi di luareun sungutna; sedengkeun di [[vertebrata]] gnatostome aya di jero.\n\nDina manuk, sungutna ditutup ku [[pamatuk]].\n\nBaham manusa ditutupan ku \'\'\'biwir\'\'\' luhur jeung handap. Biwir ieu penting pikeun [[nyarita]], [[paroman beungeut]], [[nginum]] (utamana mun maké panyerot), [[udud|ngaroko]]. [[Orok]] lahir mawa réfléks [[neureuy]], hal ieu [[naluri]]an pikeun ngalatih biwir jeung [[sihung|huntuna]]. \'\'\'Ruruncang\'\'\' (\'\'philtrum\'\') kabentuk alatan tepungna prosés nasomedial jeung maksilar nalika [[émbrio]] tumuwuh. Mun prosés ieu gagal ngahiji sacara sampurna, balukarna jadi [[suing]].\n\nTempo ogé\n*[[Létah]]\n*[[Huntu]].\n\n[[zh-min-nan:Chhùi]][[de:Mund]] [[en:Mouth]] [[es:Boca]] [[fr:Bouche]] [[it:Bocca (anatomia)]] [[ja:口]] [[nl:Mond]] [[pt:Boca]][[sv:Mun]] \n\n{{SistimDigéstif}}\n\n[[Category:Sistim digéstif]]','',3,'Kandar','20050315050829','',0,0,1,0,0.850958629908,'20050315050829','79949684949170'); INSERT INTO cur VALUES (1118,0,'Ginjal','[[Image:Ginjal_ti_tukang.jpg|thumb|250px|Ginjal ditémbongkeun ti tukang, tanpa tulang tonggong]]\n\n\'\'\'Ginjal\'\'\' nyaéta [[organ (anatomi)]] [[éxkrési]] nu bentukna kawas [[kacang]] na [[vertebrata]]. Bagéan tina [[sistim urin]], ginjal nyaring runtah (utamana [[uréa]]) tina [[getih]] sarta miceun babarengan jeung [[cai]] salaku [[urin]]. Widang médis nu ngulik ginjal sarta kasakit nu mangaruhan ginjal disebut [[nefrologi]].\n\n== [[Anatomi]] dasar ==\n===Lokasi===\nDi [[manusa]], ginjal mangrupa dua organ nu aya di bagéan [[posterior]] [[abdomén]], on either side of the [[spine (anatomy)|spine]] just below the [[liver]] and [[spleen]] on the right and left sides of the body respectively. [[Superior]] to each kidney is an [[adrenal gland]] (also called the \'\'suprarenal gland\'\').\n\nThe kidneys are retroperitoneal, which means they lie behind the [[peritoneum]], the lining of the [[abdominal cavity]]. They are approximately at the [[vertebra]]l level T12 to L3, and the right kidney usually lies slightly lower than the left, due to the size of the [[liver]].\n\nThe upper parts of the kidneys are protected somewhat by the eleventh and twelfth [[rib]]s, and each whole kidney is surrounded by two layers of fat, the perirenal fat and the pararenal fat, which help to cushion it.\n\n[[Image:Kidney_section.jpg|thumb|Section of a kidney]]\n\n===Structural details===\nIn a normal human adult, each kidney is about 11 cm long and about 5 cm thick, weighing 150 [[1 E-1 kg|grams]]. The kidneys are \"bean-shaped\" organs, and have a concave side facing inwards (medially). On this medial aspect of each kidney is an opening, called the hilus, which admits the renal [[artery]], the renal [[vein]], [[nerve]]s, and the [[ureter]]. \n\n===Organization===\nThe outer portion of the kidney is called the [[renal cortex]], the next portion is called the [[renal medulla]], at the center of the kidney is the [[renal pelvis|pelvis]]. The outside is covered by the [[renal capsule]], which is made of [[loose connective tissue]].\n\nThe basic functional unit of the kidney is the [[nephron]], of which there are more than a million in each normal adult kidney. Nephrons regulate water and soluble substances (especially [[electrolyte]]s) in the body by filtering it all out first, reabsorbing what should be kept and converting the rest into [[urine]] for excretion. They use [[countercurrent exchange]] mechanisms.\n\nA nephron consists of an initial filtering component called the [[renal corpuscle]] (or [[Malpighian corpuscle]]), and a [[renal tubule]] that extends from the renal corpuscle.\n\nEach renal corpuscle contains a compact bunch of interconnected capillaries called the \"[[glomerulus (kidney)|glomerulus]]\", which protrudes into the [[Bowman\'s capsule]]. Each glomerulus is supplied with blood by an \'\'afferent\'\' (in-coming) [[arteriole]]. Blood leaves the glomerulus through an \'\'efferent\'\' (out-going) arteriole.\n\nThe Bowman\'s capsule contains a fluid-filled space called \"Bowman\'s space\", which is separated from blood in the glomerulus by three layers:\n# a single-cell capillary [[endothelium]] in the glomerulus\n# a proteinaceous layer of basement membrane\n# a single-cell epithelial lining of Bowman\'s capsule (these cells are called [[podocyte]]s)\n\nDue to pressure, fluid in the blood is forced out of the glomerulus, through these three layers and into the Bowman\'s space to form \"glomerular filtrate\". Measuring the [[glomerular filtration rate]] is a [[Renal_physiology#Tests|diagnostic test of kidney function]].\n\n\n[[Image:Kidney tubules.png|thumb|Kidney tissue]]\n\nThe renal tubule is continuous with Bowman\'s capsule. The segment that drains glomerular filtrate from the Bowman\'s capsule is the [[proximal convoluted tubule]]. The next portion of the tubule is the [[loop of Henle]], which leads to the [[distal convoluted tubule]]. The loop of Henle was named after [[Friedrich Gustav Jakob Henle]] who described it in the early 1860s. The loop of Henle maintains an [[osmotic]] gradient set up as a [[countercurrent exchange]] to filter and concentrate glomerular filtrate. Fluid flows from the distal convoluted tubule into the [[collecting duct system]], which consists of: \n* the [[connecting tubule]] \n* the [[cortical collecting duct]] \n* the [[medullary collecting duct]]. \n\n\nThe site where the ascending loop of Henle touches the afferent arteriole, is called the [[juxtaglomerular apparatus]]. It contains [[macula densa]] and [[juxtaglomerular cell]]s. Juxtaglomerular cells are the site of [[renin]] synthesis and secretion. \n\n\nFluids become more concentrated along the tubules and ducts to form [[urine]], which is then drained into the [[urinary bladder | bladder]] via the [[ureter]].\n\n===Istilah===\n*\'\'\'[[kapsul rénal]]\'\'\' (Ing. \'\'renal capsule\'\'): bungkus ginjal nu mibanda lapisan mémbran.\n*\'\'\'[[kortéx]] (Ing. \'\'cortex\'\'): lapisan luar médulla internal, ngandung saluran getih, glomeruli (nyaéta \"saringan\" ginjal), jeung solobong [[urin]] nu dirojong ku matrix serat.\n*\'\'\'[[hilus]]\'\'\': The opening in the middle of the concave medial border for nerves and blood vessels to pass into the renal sinus.\n*\'\'\'[[kolom rénal]]\'\'\' (Ing. \'\'renal column\'\'): struktur nu ngarojong kortéx, disusun ku pirang-pirang saluran getih jeung solobong urin sarta bahan serat. \n*\'\'\'[[renal sinus]]\'\'\': The cavity which houses the renal pyramid.\n*\'\'\'[[calyce]]s\'\'\': The recesses in the internal medulla which hold the pyramids. They are used to subdivide the sections of the kidney. (singular - \'\'calyx\'\')\n*\'\'\'[[papillae]]\'\'\': The small conical projections along the wall of the renal sinus. They have openings through which urine passes into the calyces. (singular - [[papilla]])\n*\'\'\'pyramids\'\'\': The conical segments within the internal medulla. They contain the secreting apparatus and tubules and are also called \'\'[[malpighian pyramid]]s\'\'.\n*\'\'\'[[renal artery]]\'\'\': Two renal arteries come from the [[aorta]], each connecting to a kidney. The artery divides into five branches, each of which leads to a ball of capillaries. The arteries supply (unfiltered) blood to the kidneys. The left kidney receives about 60% of the renal bloodflow.\n*\'\'\'[[renal vein]]\'\'\': The filtered blood returns to circulation through the renal veins which join into the [[inferior vena cava]]. \n*\'\'\'[[renal pelvis]]\'\'\': Basically just a [[funnel]], the renal pelvis accepts the urine and channels it out of the hilus into the [[ureter]].\n*\'\'\'[[ureter]]\'\'\': A narrow tube 40 cm long and 4 mm in diameter. Passing from the renal pelvis out of the hilus and down to the [[urinary bladder|bladder]]. The ureter carries urine from the kidneys to the [[urinary bladder|bladder]].\n\n==Fungsi rénal==\nFungsi rénal ngawengku [[éxkrési]] runtah tina saluran getih, sékrési hormon - hususna [[éritropoiétin]] jeung [[rénin]] sarta ngajaga éléktrolit sérum, kadar asam-basa, jeung osmolality.\n\nPikeun leuwih lengkep tempo [[fisiologi rénal]].\n\n==Kasakit jeung kalainan==\n\n===Kasakit kongenital ginjal===\n* [[Congenital hydronephrosis]]\n* [[renal dysplasia]]\n* [[Congenital obstruction of urinary tract]]\n* [[horseshoe kidney]]\n* [[duplicated ureter]]\n\n===Acquired diseases of the kidneys===\n* [[Batu ginjal]] are a relatively common and particularly painful disorder.\n* [[Pyelonephritis]] is infection of the kidneys and is frequently caused by complication of a [[urinary tract infection]].\n* [[Azotemia]] is a toxic condition characterized by abnormal and dangerously high levels of urea, creatinine, various body waste compounds, and other nitrogen-rich compounds in the blood.\n* [[Hydronephrosis]] is the enlargement of one or both of the kidneys caused by obstruction of the flow of urine.\n* In [[nephrotic syndrome]], the [[glomerulus (kidney)|glomerulus]] has been damaged so that a large amount of [[protein]] in the blood enters the [[urine]]. Other frequent features of the nephrotic syndrome include swelling, low serum albumin, and high cholesterol.\n* kidney tumors\n** [[Wilms tumor]]\n** [[Renal cell carcinoma]]\n* [[Renal failure]] (acute and chronic)\n* [[Glomerulonephritis]]\n* [[Diabetic nephropathy]]\n* [[Lupus nephritis]]\n\n==Dialisis jeung cangkok ginjal==\nSacara umum, urang bisa hirup ku boga hiji ginjal. Mun duanana geus teu bener fungsina, kudu ngalakukeun [[dialysis]], nyaéta nyaring getih di luar awak. [[Cangkok organ|Cangkok]] ginjal ayeuna geus kaitung biasa. Cangkok ginjal munggaran nu hasil diumumkeun [[4 Maret]] [[1954]] ku [[Peter Bent Brigham Hospital]] di [[Boston]]. Bedahna dilaksanakeun ku Dr. Joseph E. Murray, nu taun [[1990]] dileler [[Hadiah Nobel]] widang Médis.\n\n== Informasi séjén ==\nIstilah médis nu patali jeung ginjal biasana maké émbohan \'\'rénal\'\' atawa \'\'néfro-\'\'.\n\n== Tempo ogé ==\n* [[Urologi]]\n* [[Nefrologi]]\n* [[Anatomi manusa]]\n\n{{sistim urin}}\n{{sistim éndokrin}}\n[[Category:Sistim urin]]\n[[Category:Sistim éndokrin]]\n\n[[cy:Aren]]\n[[de:Niere]]\n[[en:Kidney]]\n[[es:Riñón]]\n[[fr:Rein]]\n[[it:Rene]]\n[[ja:腎臓]]\n[[nl:Nier]]\n[[no:Nyre]]\n[[pt:Rim]]','/* Terms */',3,'Kandar','20050131050157','',0,0,0,0,0.911104496527,'20050131050157','79949868949842'); INSERT INTO cur VALUES (1119,0,'Palawangan','Organ séks luar awewe sacara umum disebut \'\'\'palawangan\'\'\' (aya ogé sebutan \'\'\'pudendum\'\'\').\n\nDi [[manusa]] ngawengku \'\'labia mayora\'\' jeung \'\'labia minora\'\' (ngaran ieu ditarjamahkeun ka biwir \"badag\" jeung biwir \"leutik\", mindeng ogé \"minora\" leuwih badag sarta nonjol luareun \"mayora\"), [[itil]], lawang [[urétra]] ([[meatus]]), sarta [[heunceut]].\nFungsi utama nu ngalibetkeun palawangan nyaéta [[urinasi|kiih]], [[paripolah séksual]], [[kareseban]], sarta [[babar]].\n\n== Dadaran ==\n\nNu cendewok lebah hareup palawangan nyaéta \'\'[[mons pubis]]\'\', atawa nu husus keur jelema, \'\'mons veneris\'\' atawa \"gunung [[Afrodit|Vénus]]\" nu sanggeus [[puber]] katutupan ku [[baok]] (\'\'pubic hair\'\'), nu jumlahna gumantung kana faktor turunan. Labia mayora atawa biwir badag manteng di dua sisi heunceut, nu ogé bisa katutupan ku baok. Labia mayora sagemblengna atawa sawaréh nyumputkeun bagian séjén palawangan.\n\nLabia minora nyaéta dua tilep kulit lemes di antara labia mayora jeung dua sisi lawang heunceut. [[Itil]] ayana di lebah hareup heunceut tempat labia minora tepung. Tungtung itil nu katémbong, \'\'hulu itil\'\' (\'\'clitoral glans\'\') sagemblengna atawa sawaréh katutupan ku \'tiung\' jaringan ([[tiung itil]]). \n\nLawang [[heunceut]] ayana deukeut bagian tukang (atawa na bagian handap) palawangan; lawang [[urétra]] nu leuwih leutik aya di antara itil jeung heunceut. In young girls, the opening of the vagina is partially covered by a piece of skin, the [[hymen]]. \"Opening of the vagina\" is somewhat of a misnomer, as the vagina is normally not open but collapsed and the walls of the vagina touch.\n\nSlightly below and to the left and right of the vaginal opening are two [[Bartholin glands]]; when the woman is sexually aroused, they produce a [[lubrication|lubricating]] substance that makes [[sexual penetration]] easier (the [[vagina]] also exudes [[vaginal lubrication]]). If this lubrication is insufficient, artificial lubrication may be used to facilitate sexual intercourse.\n\nWewengkon antara heunceut jeung [[kérod salawé]] disebutna [[perineum]].\n\n== Patalina jeung sirit ==\n\nAnatomi palawangan patali jeung anatomi [[sirit]] ku ayana \'\'common developmental biology\'\'. Bagéan-bagéan nu babagi \'\'common developmental ancestry\'\' dina hal ieu disebutna [[homolog]].\n\nHulu itil (\'\'clitoral glans\'\') homolog jeung [[hulu sirit]] (\'\'glans penis\'\') lalaki, sedengkeun \'\'tiung itil\'\' homologna jeung [[kulup]] sirit. Awak itil homolog jeung [[corpora cavernosa]], hiji bagian tina sirit. Labia mayora homolog jeung kanjut (\'\'[[scrotum]]\'\'), sedengkeun \'\'vestibular bulb\'\' handapeun kulit labia minora homolog jeung [[corpus spongiosum]], jaringan sirit sabudeureun urétra. Kalenjar Bartholin homolog jeung [[Kalenjar Cowper]] di lalaki.\n\n== \'\'Pembuahan\'\' ==\n\nPasangan [[hétéroséksual]] nu teu miharep [[kakandungan]] perlu nyatet yén \'\'[[pembuahan]]\'\' bisa lumangsung mun [[mani]] keuna kana palawangan (malah nembus pakéan jero) sabab [[spérma]] bisa asup kana heunceut ku ayana [[peta kapilér]]. Sayaktosna, najan nalika [[sapatemon]] teu kungsi [[éjakulasi|bucat]], tetep waé tiasa ngakibatkeun kakandungan.\n\n== Isu budaya ==\n\nIn many cultures, including modern Western culture, some women have [[shaving|shaved]] or otherwise depilated part or all of the vulva.\n\nWestern cultures have commonly viewed the vulva as something shameful that should be hidden; the term \'\'pudendum\'\' literally means \"shameful thing.\" However, in some other cultures it has been celebrated and even worshipped. In some [[Hindu]] sects the vulva is revered under the name \'\'[[yoni]]\'\', and texts seem to indicate a similar attitude in some ancient [[Middle East|Middle Eastern]] religions. As an aspect of [[Goddess Worship|Goddess worship]] such reverence may be part of modern [[Neopaganism|Neopagan]] or [[Wicca|Wiccan]] beliefs, and may be indicated in [[paleolithic]] [[art|artworks]]. Some cultures consider the vulva to be \"unclean\" and go as far as to advocate [[female circumcision]].\n\n== Tempo ogé ==\n* [[Itil]]\n* [[Urétra]]\n* [[Heunceut]]\n* [[Perineum]]\n* [[Kérod salawé]]\n* [[Orgasme]]\n* [[Vulvovaginal health]]\n* [[Clitoridectomy]]\n\n== Tumbu kaluar ==\n\n[[de:Vulva]] [[en:Vulva]] [[es:vulva]] [[fr:Vulve]] [[nl:Schaamlip]]\n\n[[Category:Sistim baranahan]]\n[[Category:Ginekologi]]','/* Dadaran */',3,'Kandar','20041030030826','',0,0,0,0,0.508196269399,'20050301090443','79958969969173'); INSERT INTO cur VALUES (1120,3,'Webkid','Thanks for adding interlanguage link. [[User:Kandar|Kandar]] 02:44, 5 Aug 2004 (UTC)','',3,'Kandar','20040805024420','',0,0,0,1,0.745366802321,'20040805024420','79959194975579'); INSERT INTO cur VALUES (1121,0,'Pangleyur','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n\'\'\'Pangleyur\'\'\' (\'\'solvent\'\', \'\'pelarut\'\') nyaéta cairan nu ngaleyurkeun [[solut]]. The solvent is the component of a solution that is present in greater amount. See [[solution]].\n\nPerhaps the most common solvent in everyday life is [[cai|water]]. Many other solvents are organic compounds, such as [[benzene]], [[tetrachloroethylene]] or [[turpentine]].\n\nSolvents can be broadly classified into polar and non-polar solvents. Common polar solvents include water and ethanol. Generally polar or ionic compounds will only dissolve in polar solvents. A test for the polarity of a liquid solvent is to rub a plastic rod, to induce static electricity. Then hold this charged rod close to a running stream of the solvent. If the path of the solvent deviates when the rod is held close to it, it is a polar solvent.\n\nIn chemistry, a common rule for determining if a solvent will dissolve a given solute is \"like dissolves like.\" Solvents composed of polar molecules, such as water, dissolve other polar molecules, such as [[table salt]], while nonpolar solvents, such as [[gasoline]], dissolve nonpolar substances such as [[wax]]. The degree that a solvent dissolves a given solute is known as its \'\'\'solubility\'\'\'. Ethyl alcohol is highly soluble in water, for example. Vinegar is very insoluble in oil, and the two substances will quickly separate into two layers even after being shaken well. \n\n[[en:Solvent]] [[ja:溶媒]]\n\n[[Category:Zat kimia]]','',3,'Kandar','20040818082622','',0,0,0,0,0.984945551485,'20040818082622','79959181917377'); INSERT INTO cur VALUES (1122,0,'Éléktron','\'\'(Salinan ti vérsi basa Inggris)\'\'\n\n{{alternateuses}}\n\n\n\n\n\n\n
Electron
[[Image:HAtomOrbitals.png|center|200px|Hydrogen atom electron orbitals]]
The first few [[hydrogen atom]] electron orbitals
shown as cross-sections with color-coded probability density
Classification
\n\n\n\n\n\n\n
[[Elementary particle]]
[[Fermion]]
[[Lepton]]
First Generation
\'\'Electron\'\'
\n
\n\n
Properties
\n
\n\n\n\n\n\n\n
Mass: 9.10 × 10-31 [[Kilogram|kg]]
Electric Charge: -1.6 × 10-19[[Coulomb|C]]
Spin: 1/2
Color Charge: none
Interaction: [[Gravity]], [[Electromagnetic interaction|Electromagnetic]],[[Weak interaction|Weak]]
\n
\n\n\'\'\'Éléktron\'\'\' (ogé disebut \'\'\'négatron\'\'\', biasa dilambangkeun ku \'\'\'e\'\'\') ngarupakeun partikel subatomik. Dina [[atom]], éléktron ngurilingan [[inti atomik|inti]] [[proton]] jeung [[neutron]] dina sarupaning [[konfigurasi éléktron]]. \n\nÉléktron mangrupa salasahiji golongan partikel subatomik nu disebut [[lepton]] nu dipercaya ngarupakeun [[fisika partikel|partikel fundaméntal]] (nyaéta teu bisa dibeulah deui jadi bagéan nu leuwih leutik).\n\nÉléktron mibanda [[spin (fisika)|spin]] 1/2, nu nunjukkeun yén éléktron téh hiji [[fermion]], hartina, nuturkeun [[statistik Fermi-Dirac]].\n\nDina [[mékanik kuantum]], éléktron digambarkeun ku \'\'[[Dirac Equation]]\'\'. Dina [[Modél Baku]] [[fisika partikel]], éléktron ngabentuk hiji doblét dina SU(2) jeung [[electron neutrino]], as they interact through the [[weak interaction]]. The electron has two more massive partners, with the same charge but different masses: the [[muon]] and the [[tauon]].\n\nThe [[antimatter]] counterpart of the electron is its antiparticle, the [[positron]]. The positron has the same amount of electrical charge as the electron, except that the charge is positive. It has the same mass and spin as the electron. When an electron and a positron meet, they may [[Annihilation|annihilate]] each other, giving rise to two [[Gamma ray|gamma-ray]] photons, each having an energy of 0.511 [[MeV]] (511 [[keV]]). See also [[Electron-positron annihilation]]. \n\nSome theorists believe the electron may be a very small black hole. \n\n==Sipat ganda==\nÉléktron bisa némbongkeun boh sipat partikel jeung gelombang. Éléktron nu kabeungkeut na inti polahna salaku \'\'[[standing wave]]\'\'.\n\n==Details==\nThe electron has a negative [[electric charge]] of -1.6 × 10-19 [[coulomb]]s, and a mass of about [[1 E-31 kg|9.10 × 10-31 kg]] (0.51 MeV/c2), which is 1/1800 of the [[proton]] mass. \n\nIt is believed that the number of electrons that would fit in the known [[universe]] is 10 followed by 130 zeros. \n\n==Listrik==\nWhen electrons move, free of the nuclei of atoms, and there is a net flow, this flow is called [[electricity]], or an [[electric current]]. This might be compared to a flock of sheep moving north together, while the shepherds do not. Electric charge can be directly measured with an [[electrometer]]. Electric current can be directly measured with a [[galvanometer]].\n\nSo-called \"static electricity\" is not a flow of electrons at all. More correctly called a \"static charge\", it refers to a body that has more or fewer electrons than are required to balance the positive charge of the nuclei. When there is an excess of electrons, the object is said to be \"negatively charged\". When there are fewer electrons than [[proton]]s, the object is said to be \"positively charged\". When the number of electrons and the number of protons are equal, the object is said to be electrically \"neutral\".\n\n==Sajarah==\nThe electron had been posited by [[G. Johnstone Stoney]], as a unit of charge in electrochemistry, but Thompson realised that it was also a [[subatomic particle]]. \n\nThe electron was [[discovery (observation)|discover]]ed by [[J.J. Thomson]] in [[1897]] at the [[Cavendish Laboratory]] at [[Cambridge University]], while studying \"[[cathode rays]].\" Influenced by the work of [[James Clerk Maxwell]], and the discovery of the [[X-ray]], he deduced that [[cathode ray tube|cathode ray]]s existed and were negatively charged \"\'\'particles\'\'\", which he called \"\'\'corpuscles\'\'\".\n\n==Tempo ogé==\n* [[Modél baku]]\n* [[Partikel subatomik]]\n* [[Proton]]\n* [[Neutron]]\n* [[Éfék fotolistrik]]\n* [[Gelap]]\n* [[Daptar partikel]]\n* [[Sinar katoda]]\n\n==Tumbu kaluar==\n* [http://pdg.lbl.gov/ Particle Data Group]\n* Stoney, G. Johnstone, \"\'\'[http://dbhs.wvusd.k12.ca.us/webdocs/Chem-History/Stoney-1894.html Of the \'Electron,\' or Atom of Electricity]\'\'\". Philosophical Magazine. Series 5, Volume 38, p. 418-420 October 1894.\n\n[[Category:Kimia]]\n[[Category:Leptons]]\n\n[[ca:Electró]] [[da:Elektron]] [[de:Elektron]] [[en:Electron]] [[es:Electrón]] [[eo:Elektrono]] [[et:Elektron]] [[fr:Électron]] [[hu:Elektron]] [[ia:Electron]] [[id:Elektron]] [[it:Elettrone]] [[nl:Elektron]] [[ja:電子]] [[nds:Elektron]] [[pl:Elektron]] [[simple:Electron]] [[sl:Elektron]] [[fi:Elektroni]] [[sv:Elektron]] [[zh-cn:电子]]','',3,'Kandar','20040805055024','',0,0,0,0,0.345570419145,'20050126082014','79959194944975'); INSERT INTO cur VALUES (1123,0,'Wikipédia:_Panglawungan','[http://en.wikipedia.org Wikipédia] téh mangrupa [[énsiklopédi]] \'\'\'sakaligus\'\'\' mangrupa masarakat [[wiki]]. Anjeun bisa [[Wikipédia: Cara ngédit kaca|ngédit]] artikel dina Wikipédia ayeuna kénéh ogé. Cobi lenyepan kumaha carana sumbangsih dina kaca [[Wikipédia: Tutorial|tutorial]] (atawa sakadar uulinan dina [[Wikipédia:Kotrétan|kotrétan]]). Pikeun wawaran nu leuwih lengkep, kirimkeun koméntar anjeun dina \'\'\'[[Wikipédia: Padungdengan| Padungdengan]]\'\'\', baca diréktori [[Pitulung: Eusi|pitulung]] sarta kaca ngeunaan [[Wikipédia: Kawijakan jeung tungtunan|kawijakan]], atawa bisa ogé badami jeung para [[Wikipédia: Wikipédiawan| Wikipédiawan]] (\'\'[http://en.wikipedia.org/wiki/Wikipedia:Wikipedians Wikipedians]\'\') séjén. Mangga, tong asa-asa ngadamel [[Special:Userlogin|rekening]]. ([[Wikipédia: Keur naon rekening?|Keur naon ari rekening?]]). \n\n==Garapeun ayeuna==\n{{browsergarapeun}}\n\nKang [[User:Budhi|Budhi]] parantos naratas artikel-artikel ngeunaan [[statistik]] ku jalan narjamahkeun artikel-artikel ti Wikipédia Inggris, mung seueur di antarana nu teu acan lengkep ditarjamahkeun. Ka sadérék nu gaduh minat dina widang ieu, dianti-anti pisan bantosanana pikeun ngeureuyeuh artikel-artikel dimaksad.\n\n==Kamarana urang Sunda téh?==\nButuh pisan pitulung yeuh, nu aub di Wikipédia Sunda kiwari ngan saeutik pisan. Nu jadi udagan ayeuna utamana ngumpulkeun artikel-artikel anu aya patula-patalina jeung [[:Category:Sunda|Kasundaan]].\n\nOgé dihaturan muka kaca [[daptar istilah]] pikeun istilah-istilah Sunda/Inggris nu can pati dipikawanoh.\n\n==Nepangan kuncén==\nPami aya hal nu peryogi didugikeun ka [[Special:Listadmins|para kuncén]], mangga sindang ka [[Wikipédia:Kuncén|rohangan kuncén]].\n\n[[ar:ويكيبيديا:بوابة المجتمع]]\n[[bg:Уикипедия:Портал]]\n[[cs:Wikipedie:Portál Wikipedie]]\n[[da:Wikipedia:Forside]]\n[[de:Wikipedia:Portal]]\n[[en:Wikipedia:Community portal]]\n[[eo:Vikipedio:Redakta_subportalo]]\n[[fo:Wikipedia:Forsíða]]\n[[ku:Wikipedia:Portala komê]]\n\n[[nl:Wikipedia:Gebruikersportaal]]\n[[fr:Wikipédia:Accueil]]\n[[is:Wikipedia:Samfélagsgátt]]\n[[it:Wikipedia:Portale Comunità]]\n[[ja:Wikipedia:コミュニティ・ポータル]]\n[[mi:Wikipedia:Community portal]]\n[[ms:Wikipedia:Portal masyarakat]]\n[[pl:Wikipedia:Portal wikipedystów]]\n[[pt:Wikipedia:Portal comunitário]]\n[[ro:Portal comunitate]]\n[[simple:Wikipedia:Community Portal]]\n[[ur:%D8%A7%D8%B1%DA%A9%D8%A7%D9%86]]\n[[vi:Wikipedia:Trang Cộng Đồng]]\n[[zh:Wikipedia:首页]]\n[[sv:Wikipedia:Portalen]]','/* Panglawungan */',3,'Kandar','20050308090910','',0,0,1,0,0.414354780882,'20050308090910','79949691909089'); INSERT INTO cur VALUES (1124,0,'Téhnik_sipil','#REDIRECT [[Rékayasa sipil]]\n','Téhnik sipil dipindahkeun ka Rékayasa sipil',3,'Kandar','20040806034026','',0,1,0,1,0.647085492170495,'20040806034026','79959193965973'); INSERT INTO cur VALUES (1126,0,'Biografi','== Headline text ==\nsajarah bangsa yahudi\nBangsa yahudi kiwari jadi bangsa anu paling rame diomongkeun ku balerea jalema di sabudeureun dunya sababna nyaeta bangsa yahudi teh jadi bangsa anu dianggap paling sarakah jeung paling bengal tapi oge paling pinter.\nPikeun urang islam atawa nasrani bangsa yahudi geus aya ti jaman bareto mula, eta aya kabuktian dina injil jeung al quran. Dina dua kitab suci eta disebutkeun yen bangsa yahudi teh geus aya ti jamanna nabi yusuf.\nNurut kan al quran jeung injil bangsa yahudi teh katurunan nabi yaqub keneh nyaeta ti pamajikanna nu kadua anu anakna ngan dua nyaeta yusuf jeung benyamin, tah ari cikal bakal na bangsa yahudi mah mimitina pisan mah ti nabi ibrahim/abraham. Ibrahim teh boga pamajikan dua nyaeta sarah/sara jeung hajar. Ti hajar lahir ismail/ismael anu jadi moyangna bangsa arab, ti sara lahir ishak/isaac nu jadi moyangna bangsa yahudi. Jadi sabenerna bangsa arab jeung yahudi teh padudulur keneh terus ti ishak turun bondoroyotna nepi ka yaqub terus ka yusuf.\nDi zaman nabi Yusuf bangsa yahudi teh jadi budak bangsa mesir terus disalamtkeun tina perbudakan ku musa/moses, jeung ku pangeranna dijangjikeun tanah di palestina. Kusabab orang yahudi loba nu ingkar tuluyna mah dihukum ku pangeranna sasab salila 40 th teu bisa asup kapalestina nepi ka maotna musa, terus wae jaman nabi daud/david karak bisa asup ka palestina. Samaotna daud yahudi dipingpin ku sulaiman/solomon, tah di zaman ieu diadegkeun kanisah kahiji, sabada maotna sulaiman bangsa yahudi diusir ti palestina ku bangsa babilonia jeung kanisah kahiji diancurkeun.\nBangsa yahudi bisa deui ka palestina basa keur palestina aya dina kakawasaanna bangsa persia.\nWanci eta diadegkeun kanisah kadua diurut kanisah sulaiman, ngan hanjakalna palestina tuluy dikuasai ku bangsa romawi tah ieu nu jadi cikalna kunaon bangsa yahudi papencar pencar, ku bangsa romawi bangsa yahudi diusir jeung diudag udag kurang leuwih dina th 70 M. Papencarna bangsa yahudi ieu disebut diaspora.\nBangsa Yahudi bisa asup deui ka palestina sarengsena perang dunia ka dua th 1948, di Palestina ngadeg nagara israel nu jadi nagarana bangsa yahudi nagan nu jadi masalah nepi ka ayeuna palestina teh geus mang abad abad di kawasaan ku bangsa arab. Matkna nepi ka ayuena yahudi jeung arab terus wae paguntren padahal mah arab jeung yahudi teh sadudulur keneh nyaeta turunanana ibrahim/abraham.','',0,'203.130.204.6','20040808054541','',0,0,0,0,0.983064939726,'20040808054541','79959191945458'); INSERT INTO cur VALUES (1127,0,'Gedung_Dwi_Warna','Gedung dwi warna telah direbut oleh Kanwil X DJA dari PPDIA','',0,'202.155.73.41','20040810033258','',0,0,0,1,0.411954052472,'20040810033258','79959189966741'); INSERT INTO cur VALUES (1128,0,'Null_hypothesis','Dina [[statistik]], \'\'\'null hypothesis\'\'\' nyaeta hipotesis nu mibanda anggapan awal bener lamun kajadian statistik dina bentuk tes hipotesis nunjukkeun sabalikna. It is a hypothesis that you are interested in showing to be false! Often it is a statement about a [[parameter]] that is a property of a population, the whole population being unobservable, and the test being based on a random sample from the population. Such a parameter is often a mean or a standard deviation.\n\nNot unusually, such a hypothesis states that the [[parameter]]s, or mathematical characteristics, of two or more [[populasi statistik|populasi]] are identical. For example, if we want to compare the test scores of two random [[statistical sample|sample]]s of men and women, the null hypothesis would be that the mean score in the male population from which the first sample was drawn was the same as the mean score in the female population from which the second sample was drawn:\n\n:H_0: \\mu_1 = \\mu_2\n\nwhere:\n:\'\'H\'\'0 = the null hypothesis\n:μ1 = the mean of population 1, and\n:μ2 = the mean of population 2.\n\nAlternatively, the null hypothesis can postulate that the two samples are drawn from the same population:\n\n:H_0: \\mu_1 - \\mu_2 = 0\n\nFormulation of the null hypothesis is a vital step in [[statistical significance]] testing. Having formulated such a hypothesis, we can then proceed to establish the probability of observing the data we have actually obtained, or data more different from the prediction of the null hypothesis, if the null hypothesis is true. That probability is what is commonly called the \"significance level\" of the results. \n\nIn formulating a particular null hypothesis, we are always also formulating an \'\'\'alternative hypothesis\'\'\', which we will accept if the observed data values are sufficiently improbable under the null hypothesis. The precise formulation of the null hypothesis has implications for the alternative. For example, if the null hypothesis is that sample A is drawn from a population with the same mean as sample B, the alternative hypothesis is that they come from populations with \'\'different\'\' means (and we shall proceed to a [[two-tailed test]] of significance). But if the null hypothesis is that sample A is drawn from a population whose mean is no lower than the mean of the population from which sample B is drawn, the alternative hypothesis is that sample A comes from a population with a \'\'larger\'\' mean than the population from which sample B is drawn, and we will proceed to a one-tailed test.\n\nA null hypothesis is only useful if it is possible to calculate the probability of observing a data set with particular parameters from it. In general it is much harder to be precise about how probable the data would be if the alternative hypothesis is true.\n\nIf experimental observations contradict the prediction of the null hypothesis, it means that either the null hypothesis is false, or we have observed an event with very low probability. This gives us high confidence in the falsehood of the null hypothesis, which can be improved by increasing the number of trials. However, accepting the alternative hypothesis only commits us to a difference in observed parameters; it does not prove that the theory or principles that predicted such a difference is true, since it is always possible that the difference could be due to additional factors not recognised by the theory. \n\nFor example, rejection of a null hypothesis (that, say, rates of symptom relief in a sample of patients who received a [[placebo]] and a sample who received a medicinal drug will be equal) allows us to make a non-null statement (that the rates differed); it does not prove that the drug relieved the symptoms, though it gives us more confidence in that hypothesis.\n\nThe formulation, testing, and rejection of null hypotheses is methodologically consistent with the [[falsificationism|falsificationist]] model of [[Science|scientific discovery]] formulated by [[Karl Popper]] and widely believed to apply to most kinds of [[empirical research]]. However, concerns regarding the high [[Statistical power|power]] of [[tes hipotesa statistik|statistical tests]] to detect differences in large samples have led to suggestions for re-defining the null hypothesis, for example as a hypothesis that an effect falls within a range considered negligible.\n\nIn [[2002]], a group of psychologists launched a new journal dedicated to experimental studies in [[psychology]] which support the null hypothesis. The \'\'Journal of Articles in Support of the Null Hypothesis\'\' (JASNH) was founded to address a scientific publishing bias against such articles. [http://www.jasnh.com/] According to the editors,\n\n:\"other journals and reviewers have exhibited a bias against articles that did not reject the null hypothesis. We plan to change that by offering an outlet for experiments that do not reach the traditional significance levels (p < 0.05). Thus, reducing the file drawer problem, and reducing the bias in psychological literature. Without such a resource researchers could be wasting their time examining empirical questions that have already been examined. We collect these articles and provide them to the scientific community free of cost.\"\n\nFor example, if you want to see if there is greater divorce avoidance from Thomas Theory than from Edgar Theory, so your Null Hypothesis would be, \"Thomas Theory is no more effective than Edgar Theory.\" If the probability of the observed results is under the null hypothesis is sufficiently low, you can accept the alternative hypothesis that Thomas Theory is indeed more effective.\n\nTempo oge: [[tes hipotesa statistik]].','',13,'Budhi','20050104040359','',0,0,1,0,0.717962540089,'20050104040359','79949895959640'); INSERT INTO cur VALUES (1129,0,'Heunceut','[[Image:Organ_kelamin_wanoja.png|right|thumb|300px|Anatomi réproduktif internal awéwé]]\n\n\'\'\'Heunceut\'\'\' ([[Basa Latin]]na \'\'vagina\'\', hartina \"[[sarangka]]\"), nyaéta jalan nyolobong ti mimiti [[uterus]] nepi ka bagian luar awak bikang [[mamalia]], atawa nepi ka [[kloaka]] na [[manuk]] bikang sarta sababaraha [[réptil]]. [[Serangga]] bikang jeung [[invertebrata]] séjénna ogé boga heunceut, nu mangrupa bagian tungtung [[oviduk]].\n\nPikeun tujuan [[anatomi]], vagina bisa ngandung harti struktur naon waé salaku sarangka (atawa [[theca]]), saperti dina heunceut [[véna portal]]. Conto séjén nyaéta sarangka serat sabudeureun [[téndon]], disebutna [[vagina fibrosa]] nalika padet atawa [[vagina mucosa]] nalika ngandung rongga nu pinuh ku cairan sabudeureun téndon.\n\nDina [[basa Sunda]], kecap heunceut ogé dilarapkeun pikeun nuduhkeun bagian nu liangan dina hiji barang. Misalna, \'\'heunceut jarum\'\', nu maksudna liang nu aya na jarum kaput. \n\n== Heunceut manusa ==\nHeunceut ngarupakeun solobong otot nu élastis nu panjangna kira 4 inci (100 mm) nu nyambungkeun [[heunceut]] di bagian luar, ka [[sérvix]] [[uterus]] di bagian jero. Mun wanoja ngadeg ajeg, solobong heunceut nangtung déngdék ka tukang ngabentuk [[juru]] saeutik leuwih ti 90 darajat jeung uterus. Liang heunceut aya di bagian tukang palawangan (\'\'vulva\'\'), tukangeun [[urétra|liang kahampangan]]. \n\n[[Image:Female_anatomy_frontal.png|right|Sawangan frontal skématik anatomi wanoja]]\n\nSacara biologis, heunceut ngajalankeun sababaraha fungsi:\n* ngasupkeun [[sirit]] nalika [[sapatemon|rarasmi]] dina raraga nepungkeun [[gamét]] ([[spérma]]) na mani pikeun fértilisasi [[ovum|sél endog]]. \n* jalan pikeun [[ngalahirkeun]] [[utun inji]] tina uterus.\n* jalan pikeun ngaluarkeun cairan [[ménstruasi|héd]]. \n\nNalika rarasmi, heunceut ngalegaan sarta manjangan; [[leuleueur heunceut]] kaluar tina [[kalenjar]] deukeut lawang heunceut jeung sérvix. \n\n[[Selaput dara]]—[[mémbran]] nu aya tukangeun lawang urétra—sabagian nutupan heunceut sababaraha organisme, kaasup [[manusa]] (wanoja), ti babar nepi ka ditembus nalika munggaran sapatemon, atawa bisa ogé alatan kagiatan séjén kaasup papariksaan médis, kacilakaan, sababaraha rupa latihan, jsb.\n\n\'\'\'Tempo ogé\'\'\' [[kalainan heunceut]], [[kaséhatan heunceut]], [[kalenjar Skene]], jeung \'\'[[G-spot]]\'\'.\n\n==Tumbu kaluar==\n*[http://www.myvag.net/ Sadaya ngeunaan heunceut]\n\n{{SistimBaranahan}}\n[[Category:Sistim baranahan]]\n[[da:Skede (kønsorgan)]] [[de:Vagina]] [[en:Vagina]] [[fr:Vagin]] [[es:vagina]] [[it:Vagina]] [[nl:vagina]] [[sv:Vagina]] [[pl:Pochwa (anatomia)]] [[ja:膣]]','/* Heunceut manusa */',3,'Kandar','20050316115816','',0,0,1,0,0.603630162406368,'20050316120503','79949683884183'); INSERT INTO cur VALUES (1130,0,'Bumi','#REDIRECT [[Marcapada]]\n','Bumi dipindahkeun ka Marcapada',3,'Kandar','20040812030628','',0,1,0,1,0.0768943662540003,'20040812030628','79959187969371'); INSERT INTO cur VALUES (1131,0,'DNA','{{otheruses}}\n\n[[image:dna-split.png|frame|Réplikasi DNA]]\n\'\'\'Asam déoksiribonukléat\'\'\' (\'\'Deoxyribonucleic acid\'\', \'\'\'DNA\'\'\') ngarupakeun [[asam nukléat]] nu mawa [[paréntah]] [[genetik]] pikeun [[biologi pertumbuhan|pertumbuhan biologis]] sadaya bentuk [[mahluk hirup|kahirupan]] jeung rupa-rupa [[virus]]. DNA kadang disebut salaku [[molekul]] [[warisan]] sabab [[warisan biologis|diwariskeun]] sarta digunakeun pikeun ngabaranahkeun [[sifat]]. Nalika [[réproduksi]], DNA [[Réplikasi DNA|disalin]] sarta diteruskeun ka turunan.\n\nDina [[baktéri]] jeung organisme [[sél biologis|sél]] [[prokariot|basajan]] séjénna, DNA nyebar kurang leuwih ampir di sapanjang jero sél. Na sél [[yukariot|kompléks]] nu nyusun ta[[tangkal]]an, [[sato]], sarta [[organisme]] multisél séjén, lolobana DNA kapanggih na [[kromosom]] nu aya na [[inti sél]]. [[Organél]] nu ngahasilkeun énergi nu katelah salaku [[kloroplas]] jeung [[mitokondria]] ogé mawa DNA, nya kitu ogé rupa-rupa [[virus]].\n\n== Ihtisar struktur molekular ==\n\nNajan kadang disebut \"molekul warisan\", lambaran DNA teu mangrupa molekul tunggal. DNA mangrupa pasangan molekul, nu murilit kawas tambang nu ngawujud jadi hiji \'\'\'[[héliks]] ganda\'\'\' (bagéan luhur na gambar katuhu). \n\nUnggal lambar molekul ngarupakeun salambar DNA: hiji ranté [[nukléotida]] nu numbu kimiawi nu masing-masing ngandung hiji [[gula]], hiji [[fosfat]], jeung salasahiji ti opat \"[[basa nirogénan|basa]]\" [[hidrokarbon aromatik|aromatik]]. Kusabab lambaran DNA diwangun ku subunit-subunit nukléotida ieu, mangga kaasup [[polimér]]. \n\nKabinékaan basa ieu ngandung harti yén aya opat rupa nukléotida, nu biasa ditujul dumasar basana, nyaéta [[adénin]] (A), [[timin]] (T), [[sitosin]] (C), jeung [[guanin]] (G). \n\nDina héliks ganda, dua lambar polinukléotida ngahiji dina [[pasangan basa|papasangan kompleméntér]] basa-basana ku ayana [[beungkeut hidrogén]]. Unggal basa nyieun beungkeut hidrogén ukur jeung pasangan nu tinangtu -- A ka T jeung C ka G -- sahingga idéntitas basa na hiji lambar nangtukeun basa naon nu aya na lambar lawanna. Thus the entire nucleotide [[primary structure|sequence]] of each strand is complementary to that of the other, and when separated, each may act as a template with which to [[replication|replicate]] the other (middle and lower half of the illustration at the right). \n\nBecause pairing causes the nucleotide bases to face the helical axis, the sugar and phosphate groups of the nucleotides run along the outside, and the two chains they form are sometimes called the \"\'\'\'backbones\'\'\'\" of the helix. In fact, it is chemical bonds between the phosphates and the sugars that link one nucleotide to the next in the DNA strand.\n\n==Pentingna runtuyan==\n\nDina hiji gén, runtuyan nukléotida sapanjang lambar DNA nangtukeun hiji [[protéin]], nu perlu dijieun ku hiji [[organisme]] atawa \"[[éksprési gén|diéksprésikeun]]\" sakali atawa sababaraha kali nalika hirupna migunakeun béja runtuyanana. Hubungan antara runtuyan nukléotida jeung runtuyan [[asam amino]] protéinna ditangtukeun ku aturan [[Tarjamah (biologi)|tarjamah]] sélular basajan, nu sacara koléktif katelah salaku [[sandi genetik]]. Maca sapanjang runtuyan \"panyandi protéin\" hiji gén, unggal tilu runtuy nukléotida (disebut [[kodon]]) nangtukeun atawa \"nyandi\" hiji asam amino. \n\nDi loba [[spésiés]], jigana ukur sabagéan leutik tina sakabéh runtuyan [[génom]] nu nyandi protéin. Fungsi nu sésana nepi ka kiwari can dipikanyaho. Geus dipikanyaho yén aya runtuyan nukléotida nu nangtukeun \'\'affinity\'\' pikeun [[protéin pamengkeut DNA]] (\'\'DNA binding protein\'\') nu boga rupa-rupa peran penting, hususna dina ngatur réplikasi jeung transkripsi. Runtuyan ieu mindengna disebut [[runtuyan pangatur]] (\'\'regulatory sequence\'\'), bari panalungtik nganggap yén sajauh ieu mah aranjeunna bisa manggihan ngan saeutik ti antarana. \"[[DNA runtah]]\" (\'\'junk DNA\'\') nunjukkeun runtuyan nu can kapanggih mibanda gén atawa fungsi.\n\nRuntuyan ogé nangtukeun karentanan hiji bagéan DNA tina beulah alatan [[énzim]] [[énzim réstriksi|réstriksi]], alat penting pisan dina [[rékayasa genetik]]. Lebah mana meulahna dina sapanjang génom individu nangtukeun \"[[sidik DNA]]na\".\n\n==Réplikasi DNA==\n\'\'Artikel utama:\'\' [[Réplikasi DNA]]\n\n\nRéplikasi DNA atawa sintésis DNA ngarupakeun prosés nyalin DNA lambar-ganda nuturkeun ayana \'\'[[pembelahan sél]]\'\'. Lambaran ganda nu dihasilkeun sacara umum ampir sarua samasakali, ngan kasalahan dina réplikasi bisa ngakibatkeun salinan nu teu sampurna (tempo [[mutasi]]). Unggal lambar ganda nu dihasilkeun ngandung salambar nu asli sarta salambar nu anyar disintésis. Ieu disebutna \'\'[[réplikasi semikonservatif]]\'\'. Prosés réplikasi ngawengku tilu hambalan: \'\'inisiasi\'\', \'\'réplikasi\'\', jeung \'\'terminasi\'\'.\n\n==Sifat mékanis nu patali jeung biologi==\n\n[[Image:Dna-helix.png|frame|Modél \'\'ngeusi rohangan\'\' (\'\'space-filling\'\') potongan molekul DNA]]\n\nBeungkeut hidrogén antara lambaran héliks ganda cukup lemah sahingga bisa leupas kalawan gampang ku ayana [[énzim]]. Énzim nu katelah [[hélikase]] ngudar lambaran pikeun ngajalanan majuna énzim nu maca runtuyan kayaning [[polimérase DNA]]. The unwinding requires that helicases chemically cleave the phosphate backbone of one of the strands so that it can swivel around the other. The stands can also be separated by gentle heating, as used in [[PCR]], provided they have fewer than about 10,000 \'\'\'base pairs\'\'\' (10 kilobase pairs, or 10 kbp). The intertwining of the DNA strands makes long segments difficult to separate. \n\nWhen the ends of a piece of double-helical DNA are joined so that it forms a circle, as in [[plasmid]] DNA, the strands are [[knot theory|topologically]] knotted. This means they cannot be separated by gentle heating or by any process that does not involve breaking a strand. The task of unknotting topologically linked strands of DNA falls to enzymes known as [[topoisomerase]]s. Some of these enzymes unknot circular DNA by cleaving two strands so that another double-stranded segment can pass through. Unknotting is required for the replication of circular DNA as well as for various types of [[recombination]] in linear DNA.\n\nThe DNA helix can assume one of three slightly different geometries, of which the \"B\" form described by [[James D. Watson]] and [[Francis Crick]] is believed to predominate in cells. It is 2 [[nanometer]]s wide and extends 3.4 nanometers per 10 bp of sequence. This is also the approximate length of sequence in which the helix makes one complete turn about its axis. This frequency of twist (known as the helical \'\'pitch\'\') depends largely on stacking forces that each base exerts on its neighbors in the chain. \n\nThe narrow breadth of the double helix makes it impossible to detect by conventional [[transmission electron microscope|electron microscopy]], except by heavy staining. At the same time, the DNA found in many cells can be macroscopic in length -- approximately 5 [[centimetre|centimeters]] long for strands in a human chromosome. Consequently, cells must compact or \"package\" DNA to carry it within them. This is one of the functions of the chromosomes, which contain spool-like [[protein]]s known as [[histone]]s, around which DNA winds. \n\nThe B form of the DNA helix twists 360° per 10.6 bp in the absence of strain. But many molecular biological processes can induce strain. A DNA segment with excess or insufficient helical twisting is referred to, respectively, as positively or negatively \"[[supercoil|supercoiled]]\". DNA in vivo is typically negatively supercoiled, which facilitates the unwinding of the double-helix required for [[transcription|RNA transcription]].\n\nThe two other known double-helical forms of DNA, called A and Z, differ modestly in their geometry and dimensions. The A form appears likely to occur only in dehydrated samples of DNA, such those used in [[crystallography]] experiments, and possibly in hybrid pairings of DNA and [[RNA]] strands. Segments of DNA that cells have [[methylation|methylated]] for regulatory purposes may adopt the Z geometry, in which the strands turn about the helical axis like a mirror image of the B form.\n\n==Maca runtuyan DNA==\n\nThe asymmetric shape and linkage of nucleotides means that a DNA strand always has a discernable orientation or directionality. Because of this directionality, close inspection of a double helix reveals that, although the nucleotides along one strand are heading one way (e.g. the \"\'\'ascending strand\'\'\") the others are heading the other (e.g. the \"\'\'descending strand\'\'\"). This arrangement of the strands is called \'\'\'antiparallel\'\'\'. \n\nFor reasons of chemical nomenclature, people who work with DNA refer to the asymmetric termini of each strand as the \'\'\'5\'\'\'\' and \'\'\'3\'\'\'\' ends (pronounced \"five prime\" and \"three prime\"). DNA workers and enzymes alike always read nucleotide sequences in the \"\'\'\'5\' to 3\' direction\'\'\'\". In a vertically oriented double helix, the 3\' strand is said to be ascending while the 5\' strand is said to be descending. \n\nAs a result of their antiparallel arrangement and the sequence-reading preferences of enzymes, even if both strands carried identical instead of complementary sequences, cells could properly translate only one of them. The other strand a cell can only read backwards. [[molecular biology|Molecular biologists]] call a sequence \"\'\'\'sense\'\'\'\" if it is translated or translatable, and they call its complement \"\'\'\'antisense\'\'\'\". It follows then, somewhat paradoxically, that the template for transcription is the \'\'antisense\'\' strand. The resulting transcript is an RNA replica of the \'\'sense\'\' strand and is itself \'\'sense.\'\'\n\nSome viruses blur the distinction between sense and antisense, because certain sequences of their [[genome|genomes]] do double duty, encoding one protein when read 5\' to 3\' along one strand, and a second protein when read in the opposite direction along the other strand. As a result, the genomes of these viruses are unusually compact for the number of genes they contain, which biologists view as an [[adaptation]]. \n\nTopologists like to note that the juxtaposition of the 3\' end of one DNA strand beside the 5\' end of the other at both termini of a double-helical segment makes the arrangement a \"[[crab canon]]\".\n\n==Single-stranded DNA (ssDNA) and repair of mutations==\n\nIn some [[Virus|viruses]] DNA appears in a non-helical, single-stranded form. Because many of the [[DNA repair]] mechanisms of cells work only on paired bases, viruses that carry single-stranded DNA [[genome]]s [[mutation|mutate]] more frequently than they would otherwise. As a result, such species may adapt more rapidly to avoid extinction. The result would not be so favorable in more complicated and more slowly replicating organisms, however, which may explain why only viruses carry single-stranded DNA. These viruses presumably also benefit from the lower cost of replicating one strand versus two.\n\n==Kapanggihna DNA jeung ulir ganda==\n\nWorking in the 19th century, biochemists initially isolated DNA and RNA (mixed together) from cell nuclei. They were relatively quick to appreciate the polymeric nature of their \"nucleic acid\" isolates, but realized only later that nucleotides were of two types--one containing ribose and the other deoxyribose. It was this subsequent discovery that led to the identification and naming of DNA as a substance distinct from RNA. \n\n[[Friederich Miescher]] (1844-1895) discovered a substance he called \"nuclein\" in 1869. Somewhat later he isolated a pure sample of the material now known as DNA from the sperm of salmon, and in 1889 his pupil, [[Richard Altmann]], named it \"nucleic acid\". This substance was found to exist only in the chromosomes.\n\n[[Max Delbrück]], [[Nikolai V. Timofeeff-Ressovsky]], and [[Karl G. Zimmer]] published results in 1935 suggesting that chromosomes are very large molecules the structure of which can be changed by treatment with X-rays, and that by so changing their structure it was possible to change the heritable characteristics governed by those chromosomes. (Delbrück and [[Salvador Luria]] were awarded the Nobel Prize in 1969 for their work on the genetic structure of viruses.) In 1943, [[Oswald Theodore Avery]] discovered that traits proper to the \"smooth\" form of the \'\'Pneumococcus\'\' could be transferred to the \"rough\" form of the same bacteria merely by making the killed \"smooth\" (S) form available to the live \"rough\" (R) form. Quite unexpectedly, the living R \'\'Pneumococcus\'\' bacteria were transformed into a new strain of the S form, and the transferred S characteristics turned out to be heritable. \n\nIn 1944, the renowned physicist, [[Erwin Schrödinger]], published a brief book entitled \'\'What is Life?\'\', in which he maintained that chromosomes contained what he called the \"hereditary code-script\" of life. He added: \"But the term code-script is, of course, too narrow. The chromosome structures are at the same time instrumental in bringing about the development they foreshadow. They are law-code and executive power -- or, to use another simile, they are architect\'s plan and builder\'s craft -- in one.\" He conceived of these dual functional elements as being woven into the molecular structure of chromosomes. By understanding the exact molecular structure of the chromosomes one could hope to understand both the \"architect\'s plan\" and also how that plan was carried out through the \"builder\'s craft.\" [[Francis Crick]], [[James D. Watson]], [[Maurice Wilkins]], [[Rosalind Franklin]], [[Seymour Benzer]], et al., took up the physicist\'s challenge to work out the structure of the chromosomes and the question of how the segments of the chromosomes that were conceived to relate to specific traits could possibly do their jobs. \n\nJust how the presence of specific features in the molecular structure of chromosomes could produce traits and behaviors in living organisms was unimaginable at the time. Because chemical dissection of DNA samples always yielded the same four nucleotides, the chemical composition of DNA appeared simple, perhaps even uniform. Organisms, on the other hand, are fantastically complex individually and widely diverse collectively. Geneticists did not speak of genes as conveyors of \"information\" in such words, but if they had, they would not have hesitated to quantify the amount of information that genes need to convey as vast. The idea that information might reside in a chemical in the same way that it exists in text--as a finite alphabet of letters arranged in a sequence of unlimited length--had not yet been conceived. It would emerge upon the discovery of DNA\'s structure, but few researchers imagined that DNA\'s structure had much to say about genetics. \n\nIn the 1950s, only a few groups made it their goal to determine the structure of DNA. These included an American group led by [[Linus Pauling]], and two groups in Britain. At [[Cambridge University]], Crick and Watson were building physical models using metal rods and balls, in which they incorporated the known chemical structures of the nucleotides, as well as the known position of the linkages joining one nucleotide to the next along the polymer. At [[King\'s College, London]], Maurice Wilkins and Rosalind Franklin were examining [[crystallography|x-ray diffraction]] patterns of DNA fibers. \n\nA key inspiration in the work of all of these teams was the discovery in [[1948]] by Pauling that many proteins included helical (see [[alpha helix]]) shapes. Pauling had deduced this structure from x-ray patterns. Even in the initial crude diffraction data from DNA, it was evident that the structure involved helices. But this insight was only a beginning. There remained the questions of how many strands came together, whether this number was the same for every helix, whether the bases pointed toward the helical axis or away, and ultimately what were the explicit angles and coordinates of all the bonds and atoms. Such questions motivated the modeling efforts of Watson and Crick. \n\nIn their modeling, Watson and Crick restricted themselves to what they saw as chemically and biologically reasonable. Still, the breadth of possibilities was very wide. A breakthrough occurred in [[1952]], when [[Erwin Chargaff]] visited Cambridge and inspired Crick with a description of experiments Chargaff had published in 1947. Chargaff had observed that the proportions of the four nucleotides vary between one DNA sample and the next, but that for particular pairs of nucleotides -- adenine and thymine, guanine and cytosine -- the two nucleotides are always present in equal proportions. \n\nWatson and Crick had begun to contemplate double helical arrangements, and they saw that by reversing the directionality of one strand with respect to the other, they could provide an explanation for Chargaff\'s puzzling finding. This explanation was the complementary pairing of the bases, which also had the effect of ensuring that the distance between the phosphate chains did not vary along a sequence. Watson and Crick were able to discern that this distance was constant and to measure its exact value of 2 nanometers from an X-ray pattern obtained by Franklin. The same pattern also gave them the 3.4 nanometer-per-10 bp \"pitch\" of the helix. The pair quickly converged upon a model, which they announced before Franklin herself published any of her work. \n\nThe great assistance Watson and Crick derived from Franklin\'s data has become a subject of controversy, and it has angered people who believe Franklin has not received the credit due to her. The most controversial aspect is that Franklin\'s critical X-ray pattern was shown to Watson and Crick without Franklin\'s knowledge or permission. Wilkins showed it to them at his lab while Franklin was away.\n\nWatson and Crick\'s model attracted great interest immediately upon its presentation. Arriving at their conclusion on [[February 21]] [[1953]], Watson and Crick made their first announcement on [[February 28]]. Their paper [http://www.nature.com/genomics/human/watson-crick/ \'A Structure for Deoxyribose Nucleic Acid\'] was published on [[April 25]]. In an influential presentation in [[1957]], Crick laid out the \"[[Central Dogma]]\", which foretold the relationship between DNA, RNA, and proteins, and articulated the \"sequence hypothesis.\" A critical confirmation of the replication mechanism that was implied by the double-helical structure followed in [[1958]] in the form of the [[Meselson-Stahl experiment]]. Work by Crick and coworkers deciphered the [[genetic code]] not long afterward. These findings represent the birth of [[molecular biology]]. \n\n[[James D. Watson|Watson]], [[Francis Crick|Crick]], and [[Maurice Wilkins|Wilkins]] were awarded the [[1962]] [[Nobel Prize for Medicine]] for discovering the molecular structure of DNA, by which time [[Rosalind Franklin|Franklin]] had died.\n\n==Pustaka==\n\n* \'\'DNA: The Secret of Life\'\', by James D. Watson. ISBN 0-375-41546-7\n\n==Tumbu kaluar==\n*[http://nist.rcsb.org/pdb/molecules/pdb23_1.html DNA: PDB molecule of the month]\n*Google: [http://directory.google.com/Top/Science/Biology/Biochemistry_and_Molecular_Biology/Biomolecules/Nucleic_Acids/ Nucleic Acids]\n*[http://news.bbc.co.uk/1/hi/sci/tech/2949629.stm 17 April, 2003, BBC News: Most ancient DNA ever?]\n*[http://www.myfirstbookaboutdna.com My First Book About DNA]\n* Watson, James, and Francis Crick, \"\'\'[http://biocrs.biomed.brown.edu/Books/Chapters/Ch%208/DH-Paper.html Molecular structure of nucleic acids], A structure for Deoxyribose Nucleic Acid\'\'\". April 2, 1953. (paper on the structure of DNA)\n*[http://www.dnai.org DNA Interactive] (requires [[Macromedia Flash]])\n*[http://www.indigo.com/models/dna-models.html DNA model] - sometimes a solid three-dimensional model, rather than an in silico model, is the best for demonstrating the structure of DNA (viz. Watson and Crick!)\n\n[[cy:DNA]] [[da:DNA]] [[de:Desoxyribonukleinsäure]] [[en:DNA]] [[es:ADN]] [[eo:DNA]] [[fi:DNA]] [[fr:Acide désoxyribo-nucléique]][[gl:ADN]] [[id:Asam deoksiribosanukleat]] [[it:DNA]] [[la:Acidum deoxyribonucleinicum]] [[nl:DNA]] [[ja:デオキシリボ核酸]] [[no:DNA]] [[pl:DNA]] [[pt:DNA]] [[zh:脱氧核糖核酸]]\n\n[[Category:Asam nukléat]] [[Category:Genetik]]','it:',36,'Renato Caniatti','20050210143558','',0,0,1,0,0.926202064346,'20050210143558','79949789856441'); INSERT INTO cur VALUES (1132,6,'Wikipedia.png','Wikipédia (aksara Sunda)','Wikipédia (aksara Sunda)',3,'Kandar','20040813035900','',0,0,0,1,0.573581374784542,'20050306113334','79959186964099'); INSERT INTO cur VALUES (1134,0,'Pindahna','#REDIRECT [[Pindah]]\n','Pindahna dipindahkeun ka Pindah',3,'Kandar','20040813090305','',0,1,0,1,0.637223805894352,'20040813090305','79959186909694'); INSERT INTO cur VALUES (1135,0,'Hipotesa_ergodik','Dina [[physics|fisika]] jeung [[thermodynamics|termodinamika]], \'\'\'hipotesa ergodic\'\'\' nyebutkeun yen, dina periode waktu nu lila, waktu nu dipake dina daerah nu sarua tina [[phase space]] [[Microstate (thermodynamics)|microstates]] mibanda energi nu sarua jeung volume di eta daerah, contona keur sakabeh microstates nu bisa diakses mibanda kamungkinan nu sarua dina periode waktu nu lila. Kasaruaan ieu, bisa disebutkeun yen waktu average sarta average dina [[statistical ensemble|susunan statistik]] mibanda nilai nu sarua.\n\n[[Ergodic theory|Teori ergodik]] ngarupakeun cabang tina [[matematik]] nu pakait jeung [[dynamical system|dinamika sistim]] nu salaras jeung versi ieu hipotesis, dina bahasa [[measure theory|teori ukuran]].','',13,'Budhi','20041204015346','',0,0,1,0,0.65353876569,'20041204015414','79958795984653'); INSERT INTO cur VALUES (1136,0,'Markov_property','Sacara informal, [[prosés stokastik]] mibanda \'\'\'sipat Markov\'\'\' if the conditional [[probability distribution]] of future states of the process, given the present state, depends only upon the current state, and [[conditional independence|conditionally independent]] of the past states (the \'\'path\'\' of the process) given the present state. A process with the Markov property is usually called a \'\'\'Markov process\'\'\', and may be described as \'\'Markovian\'\'.\n\nMathematically, if \'\'X\'\'(\'\'t\'\'), \'\'t\'\' > 0, is a stochastic process, the Markov property states that\n:\\mathrm{Pr}\\big[X(t+h) = y \\,|\\, X(s) = x(s), s \\leq t\\big] = \\mathrm{Pr}\\big[X(t+h) = y \\,|\\, X(t) = x(t)\\big], \\quad \\forall h > 0.\n\nMarkov processes are typically termed \'\'(time-) homogeneous\'\' if\n:\\mathrm{Pr}\\big[X(t+h) = y \\,|\\, X(t) = x(t)\\big] = \\mathrm{Pr}\\big[X(h) = y \\,|\\, X(0) = x(0)\\big], \\quad \\forall t, h > 0,\nand otherwise are termed \'\'(time-) inhomogeneous\'\' (or \'\'(time-) nonhomogeneous\'\'). Homogeneous Markov processes, usually being simpler than inhomogeneous ones, form the most important class of Markov processes. \n\nIn some cases, apparently non-Markovian processes may still have Markovian representations, constructed by expanding the concept of the \'current\' and \'future\' states. Let \'\'X\'\' be a non-Markovian process. Then we define a process \'\'Y\'\', such that each state of \'\'Y\'\' represents a time-interval of states of \'\'X\'\', i.e. mathematically\n:Y(t) = \\big\\{ X(s) : s \\in [a(t), b(t)] \\, \\big\\}.\nIf \'\'Y\'\' has the Markov property, then it is a Markovian representation of \'\'X\'\'. In this case, \'\'X\'\' is also called a \'\'\'second-order Markov process\'\'\'. \'\'\'Higher-order Markov processes\'\'\' are defined analogously. \n\nAn example of an non-Markovian process with a Markovian representation is a [[moving average]] [[deret waktu]].\n\nProsés Markov nu pangkawentarna nyaéta [[ranté Markov]], ngan prosés-prosés séjénna ogé, kaasup [[gerak Brown]] (Ing. \'\'Brownian motion\'\'), Markovian kénéh.\n\n==Tempo ogé==\n\n* [[Conto ranté Markov]], [[memorylessness]], [[prosés semi Markov]]\n\n[[Category:Prosés stokastik]]','',3,'Kandar','20041222034548','',0,0,0,0,0.736267262016,'20041222035517','79958777965451'); INSERT INTO cur VALUES (1137,0,'Gerak_Brown','Aya dua harti ngeunaan watesan \'\'\'\'\'gerak Brown\'\'\'\'\': hiji, dina fénoména fisik salaku gerak partikel dina fluida nu ngarupakeun gerak acak, sarta nu séjénna dina modél [[matematik]] nu dipaké pikeun ngajelaskeun hal éta.\n\nModél matematik bisa ogé digunakeun keur ngajelaskeun lobana fénoména séjén anu teu kasusun (ku matematik séjénna) ku gerak acak partikel. Nu biasa dipaké conto séjénna nyaéta turun unggahna [[pasar stok]] (Ing. \'\'stock market\'\'), sarta conto penting sejenna evolusi karakter fisik dina rekaman fosil. \n\nGerak Brown mangrupa [[prosés stokastik]] pangbasajanna dina domain kontinyu, and it is a [[limit (mathematics)|limit]] of both simpler (see [[random walk]]) and more complicated stochastic processes. This [[universality]] is closely related to the universality of the [[normal distribution]]. In both cases, it is often mathematical convenience rather than actual accuracy as models that dictates their use. All three quoted examples of Brownian motion are cases of this: it has been argued that [[Lévy flight]]s are a more accurate, if still imperfect, model of stock-market fluctuations; the physical Brownian motion can be modelled more accurately by more general [[diffusion|diffusion process]]; and the dust hasn\'t settled yet on what the best model for the fossil \nrecord is, even after correcting for non-[[normal distribution|Gaussian]] data.\n\n== Sajarah gerak Brown ==\n\nGerak Brown kapanggih ku ahli biologi [[Robert Brown (ahli biologi)|Robert Brown]] taun 1827. The story goes that Brown was studying pollen particles floating in water under the \nmicroscope, and he observed minute particles within vacuoles in the pollen grains executing the jittery motion that now bears his name. By doing the same with particles of dust, he was able to rule out that the motion was due to pollen being \"alive\", but it remained to explain the origin of the motion. Nu pangheulana méré téori ngeunaan gerak Brown taya lian ti [[Albert Einstein]] taun 1905. \n\nAt that time the atomic nature of matter was still a controversial idea. Einstein observed that, if the [[kinetic theory]] of \nfluids was right, then the molecules of water would move at random and so a small particle would receive a random \nnumber of impacts of random strength and from random directions in any short period of time. This random bombardment by \nthe molecules of the fluid would cause a sufficiently small particle to move in exactly the way described by Brown.\n\n== Dadaran modél matematis ==\n\nSacara matematik, gerak Brown ngarupakeun [[prosés Wiener]] numana sebaran kondisional probailiti tina posisi partikel dina waktu \'\'t\'\'+d\'\'t\'\', nu dina posisi waktu \'\'t\'\' nyaeta \'\'p\'\', ngarupakeun [[sebaran normal]] mibanda [[mean]] \'\'p\'\'+μ dt sarta [[varian]] σ2 d\'\'t\'\'; parameter μ ngarupakeun simpangan \'\'kecepatan\'\', sarta parameter σ2 ngarupakeun \'\'power noise\'\'. These properties clearly establish that Brownian motion is Markovian (i.e. it satisfies the [[Markov property]]). Brownian motion is related to the [[random walk]] problem and it is generic in the sense that many different stochastic processes reduce to Brownian motion in suitable limits.\n\nIn fact, the Wiener process is the only time-[[homogeneous]] [[stochastic process]] with [[independent increments]] and which is [[continuous in probability]]. These are all reasonable approximations to the physical properties of Brownian motion. \n\nThe mathematical theory of Brownian motion has been applied in contexts ranging far beyond the movement of particles in fluids. For example, in the modern theory of [[Black-Scholes|option pricing]], asset classes are sometimes modeled as if they move according to a Brownian motion with drift.\n\nIt turns out that the Wiener process is not a physically realistic model of the motion of Brownian particles. More sophisticated formulations of the problem have led to the mathematical theory of [[diffusion|diffusion processes]]. The accompanying equation of motion is called the [[Langevin equation]] or the [[Fokker-Planck equation]] depending on whether it is formulated in terms of random trajectories or probability densities.\n\n==Tempo ogé== \n\n[[osmosis]], [[tangkal brown]] (Ing. \'\'brownian tree\'\'), [[ultramikroskop]], [[Brownian ratchet]]\n\n==Tumbu kaluar==\n*[http://www.math.princeton.edu/~nelson/books.html Edward Nelson, \'\'Dynamical Theories of Brownian Motion\'\' (1967)] PDF of this out of print book available on the author\'s webpage.\n\n[[de:Brownsche Molekularbewegung]] [[fr:Mouvement brownien]] [[ja:ブラウン運動]] [[nl:Brownse beweging]] [[pt:Movimento browniano]] [[sl:Brownovo gibanje]]\n\n[[Category:Prosés stokastik]]','/* External link */',3,'Kandar','20041222040439','',0,0,0,0,0.653579002551,'20041222040439','79958777959560'); INSERT INTO cur VALUES (1138,0,'Hukum',':\'\'Artikel ieu ngeunaan hukum dina [[masarakat]]. Harti mungkin sejenna bisa ditempo di [[law (disambiguation)]].\'\'\n\nArtikel ieu mokuskeun kana \'\'\'hukum\'\'\' [[pulitik]] sarta [[yurisprudénsi]]: \nrules of conduct which mandate and/or proscribe specified [[relationship]]s among [[human|people]] and [[organization]]s; as well as punishments for those who do not follow the established rules of conduct. \n\nIn [[ethics]] and moral [[philosophy]] this type of law is often called a \"human [[legal code]]\" to distinguish it from more fundamental laws applicable to all beings ([[metaphysics]], [[ontology]]). \nSuch a body of laws can be seen as a legally-enforced [[ethical code]] or as a \"secular [[moral code]]\" (to the degree that political leaders replace religious leaders as [[moral example]]s). \nBecause lawyers and jurists more than other professions are self-regulating, almost by definition, they are often held to higher standards of behaviour or at least a stricter [[etiquette]]. \nThese concerns are not part of this article, because those expectations and disciplines are specific to each [[legal code]].\nThis article takes an English-speaking point of view and deals with other legal traditions and codes by way of comparison only.\n\n==Yurisprudénsi==\nJurisprudence refers to two different things. First, in [[common law]] jurisdictions, it means simply \"[[case law]]\", i.e. the law that is established through the decisions of the courts and other officials. Second, it means the [[philosophy of law]], or [[legal theory]], which studies not what the law is in a particular jurisdiction (say, Turkey or the United States) but law in general--i.e. those attributes common to all legal systems.\n\nJurisprudence in the second sense is conventionally divided into two parts: descriptive, or analytic, jurisprudence, and [[normative jurisprudence]]. [[Analytic jurisprudence]] studies what law \'is\', normative jurisprudence studies what law \'ought to be\'. \n\nAmong the most important questions of analytic jurisprudence are these: What is a law? What is a [[legal system]]? What is the relationship between [[law]] and [[power (sociology)|power]]? What is the relationship between law and [[justice]] or [[morality]]? Does every society have a legal system? How should we understand [[concept]]s like [[legal right]]s and [[legal duty|legal obligations or duties]]? The most influential works of analytic jurisprudence include: [[Jeremy Bentham]], \'\'[[Of Laws in General]]\'\'; [[Hans Kelsen]], \'\'[[The Pure Theory of Law]],\'\' [[H.L.A. Hart]], \'\'[[The Concept of Law]]\'\', and [[Ronald Dworkin]], \'\'[[Law\'s Empire]]\'\'.\n\nAmong the most important questions of normative jurisprudence are these: What is the [[proper function of law]]? What sorts of acts should be subject to [[sanction|punishment]], and what sorts of punishment should be permitted? What is [[justice]]? What [[legal right|rights]] do we have? Is there a duty to obey the law? What value has the [[rule of law]]? The most influential works of normative jurisprudence include all the [[classics of political philosophy]]. Among contemporary writers, the following have been particularly influential: [[John Rawls]], \'\'[[A Theory of Justice]]\'\' [[H.L.A. Hart]], \'\'[[Punishment and Responsibility]]\'\'; [[Joel Feinberg]], \'\'[[The Moral Limits of the Criminal Law]]\'\'; [[Joseph Raz]], \'\'[[The Morality of Freedom]]\'\'; [[Ronald Dworkin]], \'\'[[A Matter of Principle]]\'\'\n\n==Codification of law==\nLaw is the formal [[codification]] of [[custom]]s which have achieved such acceptance as become the enforced norm. The process of acceptance is accelerated by the existence of [[legislature|legislative]] bodies which seek to impose laws. \n\nLaw codification involves the [[legislation]] and [[regulation]] of [[statute]]s; as well as the [[dispute resolution|resolution of disputes]]. \nIn the [[civil law|civil law system]] codification is also an attempt to structure the law according to fundamental [[ethics|ethical]] principles to create a sense of order and simplicity that all members of society can comprehend, not merely university trained [[jurist]]s. \nStating the law in simple, precise terms, understandable to the lay person without a specialized legal education, is the only way they can reasonably obey it or be fairly sanctioned for not obeying it. \n\nThis overlaps with the idea of a formal social [[legal code]] as understood in [[ethics]]. \nThis may be understandable to the educated lay person but perhaps not to the ordinary lay person. \nFor example, one can explain the idea of [[precedent]] more easily than that of the [[reasonable man]], but it may be much harder to explain why precedent is \"[[fairness|fair]]\" to one without \"[[higher education]]\". \nThe following are examples of such lay explanations of different branches of law, and theories of law. \n\n\n== Law as academic discipline and profession ==\n\nIn addition to being part of the societal framework law is also an academic discipline and a [[profession]]. [[Lawyer]]s are sometimes called by other names, as in [[English law|England]] where the profession is divided between [[solicitor|solicitors]] and [[barrister|barristers]] or [[solicitor]] and [[advocate]] in [[Scotland]]. \nSometimes they are also called [[civil law notary|notaries]]. (Do not confuse this term with \'\'[[notary public]]\'\' which is an individual who is licensed to act as a witness to certain transactions, take oaths and authenticate signatures.)\nThey are professionally trained in the United States at [[graduate]] [[law school|schools of law]] leading to the [[J.D.]] degree (Juris Doctor). \nIn other countries legal education is considered to start at the [[undergraduate]] stage taught in [[faculty of law]] leading to the [[LL.B.]] or [[B.C.L.]] degrees. NOTE: In Canada at least, the LL.B. requires a previous undergraduate degree to study. Law is an undergraduate degree mainly in civil law countries.\nMost of these schools also have advanced legal degrees such as the [[LL.M.]] and the [[J.S.D.]] degrees. Many persons who attend law school never practice law but use their knowledge of law in another profession. \nSee [[Law (academic)]] and [[jurisprudence]] For law as a profession, see [[lawyer]], [[jurist]] and [[practice of law]].\n\n== Further discussion ==\n\nMost laws and legal systems—at least in the Western world—are quite similar in their essential themes, arising from similar values and similar social, economic, and political conditions, and they typically differ less in their substantive content than in their [[technical terminology|jargon]] and procedures. Communication between legal systems is the focus of [[legal translation]] and [[legal lexicography]], which deals with the principles of producing a [[law dictionary]].\n\nOne of the fundamental similarities across different legal systems is that, to be of general approval and observation, a law has to appear to be public, effective, and legitimate, in the sense that it has to be available to the knowledge of the [[citizen]] in common places or means, it needs to contain instruments to grant its application, and it has to be issued under given formal procedures from a recognized authority.\n\nIn the context of most legal systems, laws are enacted through the processes of [[constitutional charter]], [[constitutional amendment]], [[legislation]], [[executive order]], [[rulemaking]], and [[adjudication]]; within [[Common law]] jurisdictions, rulings by judges are an important additional source of legal rules.\n\nHowever, \'\'de facto\'\' laws also come into existence through custom and tradition. (See generally [[consuetudinary|Consuetudinary law]]; [[Anarchist law]].)\n\nLaw has an [[anthropology|anthropological]] dimension. In order to have a [[culture]] of law, people must dwell in a society where a government exists whose authority is hard to evade and generally recognised as legitimate. People forego personal [[revenge]] or [[self-help]] and choose instead to take their grievances before the government and its agents, who arbitrate disputes and enforce penalties. \n\nThis behaviour is contrasted with the culture of [[honor]], where respect for persons and groups stems from fear of the disproportionate revenge they may exact if their person, property, or prerogatives are not respected. Cultures of law must be maintained. They can be eroded by declining respect for the law, achieved either by weak government unable to wield its authority, or by burdensome restrictions that attempt to forbid behaviour prevalent in the culture or in some [[subculture]] of the society. When a culture of law declines, there is a possibility that an undesirable culture of honor will arise in its place. \n\nA particular [[society]] or community adopts a specific set of laws to regulate the behavior of its own members, to order life in its political [[territory]], to grant or acknowledge the [[right]]s and privileges of its citizens and other people who may come under the jurisdiction of its [[Court (judicial)|courts]], and to resolve disputes.\n\nThere are several distinct laws and legal traditions, and each [[jurisdiction]] has its own set of laws and its own legal system. Individually codified laws are known as [[statute]]s, and the collective body of laws relating to one subject or emanating from one source are usually identified by specific reference. (E.g., [[Roman law]], [[Common law]], and [[Criminal law]].) \n\nMoreover, the several different levels of [[government]] each produce their own laws, though the extent to which law is centralized varies. Thus, at any one place there can be conflicting laws in force at the local, regional, state, national, or international levels.\n(See [[conflict of laws]], [[Preemption of State and Local Laws]].)\n\n==Bodies of law, a sampling==\n\n\'\'This list is not comprehensive.\'\'\n\n*[[Administrative law]] refers to the body of law which regulates bureaucratic managerial procedures and is administered by the [[executive branch]] of a [[government]]; rather than the [[judicial branch|judicial]] or [[legislative branch|legislative]] branches (if they are different in that particular jurisdiction). This body of law regulates [[international trade]], [[manufacturing]], [[pollution]], [[tax|taxation]], and the like. This is sometimes seen as a subcategory of [[civil law]] and sometimes called [[public law]] as it deals with regulation and public institutions.\n\n*[[Canon law]] refers to laws of the [[Anglican Communion|Anglican]], [[Eastern Orthodoxy|Eastern Orthodox]], [[Roman Catholic]] [[church]]es. \n\n*[[Case law]] (precedental law) regulates, via [[precedent]]s, how laws are to be understood. Case law, also called [[common law]] or [[judge]]-made law, is derived from the body of rulings made by a country\'s courts. In the United States, the primary source of case law relating to federal and [[constitution]]al questions is the [[Supreme Court of the United States]]. The states, each with its own final [[court of appeals]], generate case law that is only binding [[precedent]] in that state. In countries that were once part of the [[British Empire]] the [[Judicial Committee of the Privy Council]] and the [[Judicial functions of the House of Lords|House of Lords]] are primary sources of case law, though not necessarily binding precedent, as each country has its own [[court of last resort]].\n\n*[[Civil law]], not to be confused with the civil legal system, has several meanings:\n**[[civil law|Secular law]] is the legal system of a [[non-theocratic]] [[government]], such as that which developed in [[England]], especially during the reign of [[Henry II of England|Henry II]] \n**[[civil law|Private law]] regulates relationships between persons and organizations including contracts and responsible behaviour such as through liability through [[negligence]]. This body of law enforces statutes or the [[common law]] by allowing a party, whose rights have been violated, to collect [[damages]] from a [[defendant]]. Where [[money|monetary]] damages are deemed insufficient, civil court may offer other remedies in [[equity]]; such as forbidding someone to do an act (eg; an [[injunction]]) or formally changing someone\'s legal status (eg; [[divorce]]). This body of law includes the [[tort|law of torts]] in common law systems, or in civilian systems, the [[Law of Obligations]].\n\n*[[Commercial law]], often considered to be part of [[civil law]], covers [[business]] and [[commerce]] relations including [[sales]] and [[business entity|business entities]]. \n\n*[[Common law]] is derived from [[Anglo-Saxon]] [[custom|customary law]], also referred to as judge-made law, as it developed over the course of many centuries in the English courts. \n\n*[[Criminal law]] (penal law) is the body of laws which regulate [[government]]al [[sanction]]s (such as [[prison|imprisonment]] and/or fines) as retaliation for [[crime]]s against the [[social control|social order]]. \n\n* [[International law]] governs the relations between [[states]], or between [[citizens]] of different states, or [[international organizations]]. Its two primary sources are [[custom (law)|customary law]] and [[treaty|treaties]].\n\n*[[Procedural Law]] are rules and regulations found in an legal system that regulate access to legal institutions such as the courts, including the filing of private [[lawsuit]]s and regulating the treatment of [[defendant]]s and [[convict]]s by the public [[criminal justice]] system. Within this field are laws regulating [[arrest]]s and [[evidence]], [[injunction]]s and [[pleading]]s. Procedural law defines the procedure by which law is to be enforced. See [[criminal procedure]] and [[civil procedure]].\n\n*[[Space law]] regulates events occurring outside Earth\'s atmosphere. At present this is limited to several treaties against atomic testing in space.\n\n== Legal subject areas ==\n[[Administrative law]] - [[Admiralty law|Admiralty]] - [[Alternative dispute resolution]] - [[Appellate review]] - [[Brehon Laws]] - [[Civil procedure]] - [[Civil rights]] - [[Commercial law]] - [[Comparative law]] - [[Consuetudinary|Consuetudinary law]] - [[Contract]]s - [[Constitutional law]] - [[Courts of England and Wales]] - [[Corporations law]] - [[Criminal law]] - [[Criminal procedure]] - [[Election law]] - [[Environmental law]] - [[Equity]] - [[Evidence]] - [[Family law]] - [[Human rights law|Human rights]] - [[Immigration]] - [[Intellectual Property law|Intellectual property]] - [[Jurisprudence]] - [[Law and economics]] - [[agency (law)|Agency]] - [[Law of Obligations]] - [[Labor law]] - [[Land use]] - [[List of items for which possession is restricted]] - [[Military law]] - [[Philosophy of law]] - [[Practice of law]] - [[Private law]] - [[Procedural law]] - [[Property law]] - [[Public Health law]] - [[Religious law]] - [[Statutory law]] - [[Tax law]] - [[Technology law]] - [[Torts]] - [[Trusts and Estates]] - [[Cyber law]] - [[Water law]]\n\n== Subjects auxiliary to law ==\n[[Government]] - [[Legal history]] - [[Law and literature]] - [[Political science]]\n\n==Terms, case law, legislation and other resources==\n* [[Law topics overview]]\n* [[List of jurists]]\n* [[List of legal topics]]\n* [[List of basic criminal justice topics]]\n* [[List of international public law topics]]\n\n* [[List of Supreme Court of Canada cases]]\n* [[List of Judicial Committees of the Privy Council & House of Lords cases]]\n* [[List of United States Supreme Court cases]]\n* [[List of leading legal cases in copyright law]]\n\n* [[List of treaties]]\n* [[List of Uniform Acts (United States)]]\n* [[List of United States federal legislation]]\n* [[Québec Highway Safety Code]]\n\n== Legal books ==\n* [[Black\'s Law Dictionary]]\n* [[Halsbury\'s Laws of England]]\n* [[Corpus Juris Secundum]]\n* [[American Law Reports]]\n* [[Recueil Dalloz]]\n\n==Further reading==\n* Cheyenne Way: Conflict & Case Law in Primitive Jurisprudence, Karl N. Llewellyn and E. Adamson Hoebel, University of Oklahoma Press, 1983, trade paperback, 374 pages, ISBN 0806118555\n*\'\'The Bilingual LSP Dictionary. Principles and Practice for Legal language\'\', Sandro Nielsen, Gunter Narr Verlag 1994.\n* [http://browse.addall.com/Browse/Author/2088479-1 Other books by Karl N. Llewellyn]\n\n== See also ==\n* [[Law (principle)]]\n* [[List of legal abbreviations]]\n* [[Legal code]]\n* [[Letter versus Spirit]]\n* [[Natural law]]\n* [[Religious law]]\n* [[Witness intimidation]]\n\n== External links ==\n*[http://www.HavenWorks.com/law Law & Legal News & Reference]\n*[http://www.ericdigests.org/1996-3/law.htm Essentials of Law-Related Education. ERIC Digest.]\n*[http://www.worldlii.org WorldLII - The World Legal Information Institute]\n\n[[Category:Law]] [[Category:Core issues in ethics]]\n[[cs:Právo]]\n[[de:Recht]]\n[[eo:Juro]]\n[[es:Derecho]]\n[[fi:Laki]]\n[[fr:Droit]]\n[[he:משפטים]]\n[[is:Lög]]\n[[ja:法律]]\n[[nl:Recht]]\n[[pl:Prawo]]\n[[pt:Direito]]\n[[simple:Law]]\n[[sl:pravo]]\n[[sv:Lag]]\n[[sv:Juridik]]\n[[uk:%D0%9F%D1%80%D0%B0%D0%B2%D0%BE]]\n[[ur:قانون]]\n[[zh-tw:%E6%B3%95%E5%AD%B8]]\n[[zh-cn:法学]]','',3,'Kandar','20041125033939','',0,0,0,0,0.522884101385,'20041229235111','79958874966060'); INSERT INTO cur VALUES (1139,0,'Algoritma_keur_ngitung_varian','[[Rumus]] pikeun ngitung populasi [[varian]]:\n:\\mathit{Variance} = \\frac {n\\sum_{i=1}^{n} x_i^2 - (\\sum_{i=1}^{n} x_i)^2}{n^2}\n\nRumus pikeun ngitung unbiased estimasi populasi [[varian]] tina sampel \"terhingga\" nyaéta:\n:\\mathit{Variance} = \\frac {n\\sum_{i=1}^{n} x_i^2 - (\\sum_{i=1}^{n} x_i)^2}{n(n-1)}\n\nCara ngitung bakal leuwih gampang kaharti dina tabel di handap ieu \ndimana nilai mean = 8.\n\n
\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
i xi xi-mean (xi-mean)2
(index) (datum) (deviation) (squared deviation)
1 5 -3 9
2 7 -1 1
3 8 0 0
4 10 2 4
5 10 2 4
n=5 sum=40 0 18
\n
\n\n\n\n\n

Catetan: Ngitung varian sacara lengkep:

\n

338 = [52 + 72 + 82 + 102 + 102]
\n40 = [5 + 7 + 8 + 10 + 10]

\n\n\n

Algoritma

\n

Algoritma sederhana keur ngitung varian saperti di handap ieu:

\n
double sum;\ndouble sum_sqr;\ndouble variance;\nlong n = data.length; // the number of elements in the data array (the actual syntax is language-specific)\n\nfor i = 0 to n\n sum += data[i];\n sum_sqr += ( data[i] * data[i] );\nend for\n\nvariance = ((n * sum_sqr) - (sum * sum))/(n*(n-1));\n
\n\n

Algoritma

\n

Algoritma sejen keur jumlah angka anu loba

\n
double avg;\ndouble var;\nlong n = data.length; // number of elements\n\nfor i = 0 to n\n avg = (avg*i + data[i]) / (i + 1);\n if (i > 0) var += (var * (i - 1) + (x - avg)*(x - avg)) / i;\nend for\n\nreturn var; // resulting variance\n
','',3,'Kandar','20041203175142','',0,0,0,0,0.379504348328,'20041203175142','79958796824857'); INSERT INTO cur VALUES (1140,0,'Rumus','\'\'\'Rumus\'\'\' (Ing. \'\'formula\'\') nyaéta jalan ringkes keur méré gambaran informasi (saperti dina [[matematik]] atawa [[rumus kimia]]) atawa \"hubungan umum antar kuantitas\". Salah sahiji nu kawentar nyaéta rumus [[Albert Einstein]] \'\'\'E = m × c 2\'\'\' (tempo [[Special relativity]]).\n\n==Tempo ogé==\n*[[Wikipedia:WikiProject_Mathematics|WikiMath: how to write mathematical formulae in wikipedia]].\n\n==Harti séjén==\n*[[Formula hiji]] ([[balap mobil]]).\n*[[Formula Language]] ([[Lotus Notes]] programming language)\n\n\n{{pondok}}\n[[en:Formula]] [[sv:formel]][[de:Formel]] [[es:fórmula]] [[ja:公式]] [[zh:数学公式]]','',3,'Kandar','20041125094626','',0,0,0,0,0.249929064536,'20050303211247','79958874905373'); INSERT INTO cur VALUES (1141,0,'Lognormal_distribution','#redirect [[log-normal distribution]]','',13,'Budhi','20040816230901','',0,1,0,1,0.531875359142,'20040816230949','79959183769098'); INSERT INTO cur VALUES (1142,0,'Sebaran_Log-normal','Dina [[kamungkinan]] jeung [[statistik]], \'\'\'sebaran log-normal\'\'\' nyaeta [[probability distribution]] nu raket hubunganna jeung [[sebaran normal]]: lamun \'\'X\'\' ngarupakeun [[random variable]] dina sebaran normal, maka [[exponential function|exp]](\'\'X\'\') ngabogaan sebaran log-normal. Dina basa sejen: variabel [[natural logarithm]] sebaran log-normal ngabogaan sebaran normal.\n\n\"Log-normal\" oge disebut \"log normal\" atawa \"lognormal\".\n\nVariable bisa dimodelkeun salaku log-normal lamun mangrupakeun [[mathematical product|product]] hasil kali tina sababaraha faktor bebas. Conto tipena nyaeta angka ti \'\'return rate\'\' bursa efek dina waktu nu lila: bisa dianggap salalu produk harian \'\'return rate\'\'.\n\nSebaran log-normal mibanda [[probability density function]]\n\n:f(x) = \\frac{1}{x \\sigma \\sqrt{2 \\pi}} e^{-(\\ln x - \\mu)^2/2\\sigma^2}\n\nkeur \'\'x\'\' > 0, numana μ and σ nyaeta [[mean]] jeung [[simpangan baku]] tina variabel logaritma. [[Nilai ekspektasi]] nyaeta \n\n:\\mathrm{E}(X) = e^{\\mu + \\sigma^2/2}\n\njeung [[varian]] nyaeta \n\n:\\mathrm{var}(X) = (e^{\\sigma^2} - 1) e^{2\\mu + \\sigma^2}.\n\n\n==Hubungan geometrik mean jeung geometrik simpangan baku==\n\nSebaran log-normal, [[geometric mean]], jeung [[geometri simpangan baku]] ngarupakeun hal nu pakait. Dina kasus , geometric mean sarua jeung \\exp(\\mu) sarta geometric simpangan baku sarua jeung \\exp(\\sigma).\n\nLamun sampel data nu ditangtukeun asalna ti populasi sebaran log-normal, geometric mean jeung geometric simpangan baku bisa dipake keur nga-estimasi confidence interval ku jalan arithmetic mean jeung simpangan baku nu digunakeun keur nga-estimasi confidence interval dina sebaran normal.\n\n{| border=\"1\" cellpadding=\"2\"\n!Confidence interval bounds\n!log space\n!geometric\n|-\n|3σ lower bound\n|\\mu - 3\\sigma\n|\\mu_{geo} / \\sigma_{geo}^3\n|-\n|2σ lower bound\n|\\mu - 2\\sigma\n|\\mu_{geo} / \\sigma_{geo}^2\n|-\n|1σ lower bound\n|\\mu - \\sigma\n|\\mu_{geo} / \\sigma_{geo}\n|-\n|1σ upper bound\n|\\mu + \\sigma\n|\\mu_{geo} \\sigma_{geo}\n|-\n|2σ upper bound\n|\\mu + 2\\sigma\n|\\mu_{geo} \\sigma_{geo}^2\n|-\n|3σ upper bound\n|\\mu + 3\\sigma\n|\\mu_{geo} \\sigma_{geo}^3\n|}\n\nNumana geometric mean \\mu_{geo} = \\exp(\\mu) jeung geometri simpangan baku \\sigma_{geo} = \\exp(\\sigma)\n\n==See also==\n\n[[geometric mean]], [[geometri simpangan baku]]\n\n[[Category:Probability distributions]]\n[[de:logarithmische Normalverteilung]]','',13,'Budhi','20040917025757','',0,0,0,0,0.797891023475,'20040917025757','79959082974242'); INSERT INTO cur VALUES (1143,0,'Statistical_power','[[de:Power]]\n\'\'\'Power\'\'\' [[tes hipotesa statistik|uji statistik]] nyaeta tes probabilitas nu nolak [[null hypothesis]] salah, atawa dina basa sejen moal make [[Type II error]]. The higher the power, the greater the chance of obtaining a [[statistical significance|statistically significant]] result when the null hypothesis is false.\n\nStatistical tests attempt to use data from [[Sampling (statistics)|sample]]s to determine if differences or similarities exist in a [[populasi statistik|populasi]]. For example, to test the null hypothesis that the [[mean]] [[score]]s of men and women on a test do not differ, samples of men and women will be drawn, the test administered to them, and the mean score in each group compared with a statistical test. If the populations of men and women have different mean scores but the test of the sample data concludes that there is no such difference, a Type II error has been made.\n\nStatistical power depends on the significance criterion, the size of the difference or the strength of the similarity (that is, the [[efek ukuran]]) in the population, and the sensitivity of the data. \n\nA significance criterion is a statement of how unlikely a difference must be, if the null hypothesis is true, to be considered significant. The most commonly used criteria are probabilities of 0.05, 0.01, and 0.001. If the criterion is 0.05, the probability of the difference must be less than 0.05, and so on.\nThe greater the effect size, the greater the power. Calculation of power requires that researchers determine the effect size they want to detect.\n\n[[Sensitivity (tests)|Sensitivity]] can be increased by using [[statistical control]]s, by increasing the reliability of measures (as in [[Reliability (psychometric)|psychometric reliability]]), and by increasing the size of the sample. Increasing sample size is the most commonly used method for increasing statistical power.\n\nAlthough there are no formal standards for power, most researchers who assess the power of their tests use 0.80 as a standard for adequacy.\n\nOne way of increasing the power of a test is to weaken the significance level by increasing it. This would also reduce the risk of a Type II error and increase the chance of obtaining a statistically significant result when the null hypothesis is false, but it would also increase the risk of obtaining a statistically significant result and rejecting the null hypothesis when it is in fact is true, i.e. increase the risk of a [[Type I error]].','',13,'Budhi','20050104061514','',0,0,1,0,0.881820017883,'20050104061514','79949895938485'); INSERT INTO cur VALUES (1144,0,'Tes_hipotesa_statistik','Salah sahiji hal nu pakait jeung meupeuskeun masalah nyaeta nyieun kaputusan nu hade dumasar kana hipotesa nu teu pasti ngaliwatan panalungtikan.\n\'\'\'Tes hipotesa statistik\'\'\', atawa leuwih ilahar disingkat, \'\'tes hipotesa\'\', nyaeta algoritma keur nangtukeun alternatip (keur atawa lawan hipotesa) nu ngaminimalkeun resiko kasalahan.\n\nKaca ieu ngajentrekeun nu [[frequentist|remen]] digunakeun dina tes hipotesa.\nTina panempo [[Bayesian probability|Bayesian]],\nngarupakeun hal nu pas keur make tes hipotesa dina kasus [[decision theory|teori kaputusan normatip]] (hususna dina [[model selection problem|masalah pamilihan model]]) sarta mungkin keur ngumpulkeun [[evidence|bukti]] pitulung hipotesa saperti make konsep rasio [[likelihood]] nu disebut [[Bayes factors]].\n\nAya sababaraha hal nu perlu disiapkeun samemeh nalungtik data. \n#Hipotesa kudu ditangtukeun dina watesan matematika/statistik sangkan mungkin ngitung probabiliti hipoetsa sample bener. Conto: \'\'Respon mean kana \"perlakuan\" salila uji sarua jeung respon mean kana \"placebo\" dina grup kontrol. Respon duanana mibanda [[sebaran normal]] nu nilai mean teu dipikanyaho sarta nilai [[simpangan baku]] nu sarua tur dipikanyaho.\'\'\n#Hiji tes [[statistik]] kudu dipilih nu bakal nyimpulkeun informasi dina sampel nu pakait jeung hipotesa. Saperti statistik nu dipikanyaho salaku [[sufficient statistic|statistik kacukupan]]. Statistik kacukupan keur hiji parameter tina sebaran, aya lamun jeung lamun bentuk sebaran-na kaasup kana [[exponential family|kulawarga eksponensial]]. Dina conto diberekeun di luhur, mungkin bakal aya beda numeris antara dua sampel mean, m1 − m2.\n#Sebaran tes statistik dipake keur ngitung susunan probabiliti nilai nu mungkin (ilaharna hiji interval atawa gabungan intervals). Dina conto ieu, beda antara means sampel bakal mibanda sebaran normal nu simpangan baku-na sarua jeung faktor waktu simpangan baku nu ilahar \\sqrt{\\frac{1}{n_1} + \\frac{1}{n_2}} where n1 jeung n2 nyaeta ukuran sampel.\n#Antara sakabeh susunan nilai mungkin, kudu dipilih hiji nilai nu dianggap ngawakilan kajadian ekstri \'\'\'tinimbang\'\'\' hipotesa. Ieu disebut \'\'\'daerah kritis\'\'\' uji statistik. Sebaran uji statistik aya dina daerah kritis lamun hipotesa bener sarta disebut nilai \'\'\'alpha\'\'\' (atawa \'\'\'ukuran\'\'\') tina uji statistik. \n\nSanggeus data aya, uji statistik diitung sarta ditangtukeun dina jero daerah kritis. \n\nLamun uji statistik aya dina jero daerah kritis, maka kasimpulanna nyaeta\n#Hipotesa salah \'\'atawa\'\'\n#Kajadian probibilti kurang atawa sarua jeung \'\'alpha\'\' geus kajadian.\nPanaliti geus milih antara dua logika alternatif ieu.\nDina conto bisa disebutkeun: respon observasi kana perlakuan [[Statistical significance|signifikan sacara statistik]]. \n\nLamun tes statistik di luar daerah kritis, ngan hiji kasimpulan nyaeta \n*\'\'Teu cukup kajadian keur nolak hipotesa.\'\' \nIeu \'\'\'teu\'\'\' sarua salaku kajadian keur hipotesa. Hal ieu teu bisa dipake salaku alesan, sabab kurangna kajadian tinimbang hipotesa. Dumasar kana hal ieu, kamajuan pananglutikan sacara statistik ku ngurangan kasalahan, lain ku \'\'manggihkeun bebeneran\'\'.\n\n\n==Tempo ogé==\n\n[[falsifiability]] -- [[tiori statistik]] -- [[statistik terapan]] -- [[null hypothesis]]','',13,'Budhi','20050104012019','',0,0,0,0,0.774219740543,'20050104012539','79949895987980'); INSERT INTO cur VALUES (1145,0,'Type_II_error','Dina [[tes hipotesa statistik]], \'\'\'Type II error\'\'\' miboga gagalna keur nolak [[null hypothesis]] nu salah (contona. kasalahan narima hypothesis nu salah).\n\nSimbol keur probabiliti Type II error nyaeta \\beta ([[beta (letter)|beta]]). [[statistical power|Power]] tes statistik dihartikeun salaku 1 - \\beta. Tes nu mibanda [[sensitivity (tests)|sensitivity]] luhur bakal miboga Type II errors saeutik.\n\nTempo oge [[Type I error]].\n\n[[de:Fehler 2. Art]]','',0,'220.31.240.165','20050104061658','',0,0,0,0,0.056587555006,'20050104061658','79949895938341'); INSERT INTO cur VALUES (1146,0,'Type_I_error','Dina [[tes hipotesa statistik]], \'\'\'Type I error\'\'\' nyaeta ditolakna [[null hypothesis]] lamun bener, dina basa sejen manggihkeun hasil nu miboga [[statistical significance]] dina waktu bener-bener kajadian. Hiji tes nu mibanda [[specificity]] luhur bakal saeutik ngabogaan \'\'Type I errors\'\'. Simbol keur probabiliti Type I error nyaeta α ([[alpha]]) sarta kadang-kadang dipake salaku \"ukuran\" tes. \n\nTempo [[Type II error]].\n\n[[de:Fehler 1. Art]]','',13,'Budhi','20050104061731','',0,0,0,0,0.690116586019,'20050104061731','79949895938268'); INSERT INTO cur VALUES (1147,0,'Statistical_significance','Dina [[statistik]], a result is \'\'\'significant\'\'\' if it is unlikely to have occurred by chance.\n\nMore precisely, in traditional [[frequentist]] [[tes hipotesa statistik|statistical hypothesis testing]], the \'\'\'significance level\'\'\' of a test is the maximum [[probability]] of accidentally rejecting a \'\'true\'\' [[null hypothesis]] (a decision known as a [[Type I error]]). The significance of a result is also called its [[p-value]].\n\nFor example, one may choose a significance level of, say, 5%, and calculate a \'\'critical value\'\' of a [[statistic]] (such as the mean) so that the [[probability]] of it exceeding that value, given the truth of the [[null hypothesis]], would be 5%. If the actual, calculated statistic value exceeds the critical value, then it is \'\'\'significant\'\'\' \"at the 5% level\".\n\nIf the significance level is smaller, a value will be less likely to be more extreme than the critical value. So a result which is \"significant at the 1% level\" is more significant than a result which is \"significant at the 5% level\". However a test at the 1% level is more likely to have a [[Type II error]] than a test at the 5% level, and so will have less [[statistical power]]. In devising a hypothesis test, the tester will aim to maximize power for a given significance, but ultimately have to recognise that the best which can be achieved is likely to be a balance between significance and power, in other words between the risks of Type I and Type II errors.\n\n[[Category:Statistik]]\n[[de:Statistische Signifikanz]]\n[[nl:significantie]]','',13,'Budhi','20050104062231','',0,0,0,0,0.546444046566,'20050104062231','79949895937768'); INSERT INTO cur VALUES (1148,0,'Sensitivity_(tests)','The \'\'\'sensitivity\'\'\' of a [[binary classification]] test or [[algorithm]], such as a blood test to determine if a person has a certain disease, or an automated system to detect faulty products in a factory, is a parameter that expresses something about the test\'s performance. The sensitivity of such a test is the proportion of those cases having a positive test result of all positive cases (eg, people with the disease, faulty products) tested. \n\n:{\\rm sensitivity}=\\frac{\\rm number\\ of\\ true\\ positives}{{\\rm number\\ of\\ true\\ positives}+{\\rm number\\ of\\ false\\ negatives}}.\n\nA sensitivity of 100% means that all sick people or faulty products were recognized as such, but it alone doesn\'t tell us all about the test, as a 100% sensitivity can be trivially achieved by labeling all test cases positive, despite their true status. For more information see [[binary classification]]. See also [[specificity]].\n\nDina basa tradisional [[tes hipotesa statistik]], the sensitivity of a test is called the [[statistical power]] of the test, although the word \'\'power\'\' in that context has a more general usage that is not applicable in the present context. A sensitive test will have fewer [[Type II error]]s.\n\nIn the context of [[information retrieval]], the concept of sensitivity is also known as \'\'\'recall\'\'\'.\n\n[[de:Sensitivität]]','',13,'Budhi','20050104065449','',0,0,0,0,0.837323326076,'20050104065449','79949895934550'); INSERT INTO cur VALUES (1149,0,'Média','#REDIRECT [[mass media]]','',13,'Budhi','20040816234522','',0,1,0,1,0.339361228207,'20040816234522','79959183765477'); INSERT INTO cur VALUES (1150,0,'Pulitik','\'\'\'Pulitik\'\'\' nyaéta prosés sarta cara kelompok pikeun [[nyieun kaputusan]]. Sanajan ilahar dipaké keur pamaréntah, sifat pulitik ogé ditalungtik di pausahaan, akademik, agama sarta institusi séjén. \'\'\'[[Élmu pulitik]]\'\'\' nyaéta élmu ngeunaan paripolah politik, uji akurasi sarta pamakéan kakuatan, contona kamampuan keur ngaruntagkeun lawan.\n\n==Sajarah pulitik==\n===The biological genesis of politics===\nPolitics predates human society.\n\nMost primates live in groups and form \"dominance hierarchies.\" Individuals with greater hierarchical status tend to displace those ranked lower from space, from food, and from mating opportunities. Thus higher status individuals tend to have greater reproductive success by mating more often and having more resources to invest in the survival of offspring.\n\nThese hierarchies are not fixed and depend on any number of changing factors, among them are age, gender, intelligence, and aggressiveness.\nStatus may also be affected by the ability to marshal the support of others. Indeed, the need to maintain social position and social knowledge may be an impetus for the evolution of larger brains in humans.\n\nEarly human polities organized groups include families, clans, and tribes.\n\n===Urban revolution===\n[[V.G. Childe]] describes the transformation of human society that took place around [[6th millennium BCE|6000 BCE]] as an Urban Revolution. Among the features of this new type of civilization are: institutional social stratification(dominance hierarchy), non-agricultural specialised crafts (including priests and lawyers), taxation, and writing. All of which require densely populated settlements - cities.\n\nWhile the word, \"Politics\" is derived from the Greek word for city, \"Polis\", it should be remembered that politics happens in every group undertaking. Corporate, religious, academic and every other polity, especially those constrained by limited resources, contain dominance hierarchies and therefore politics.Politics is most often studied in the public administrative context.\n\n===The evolution of government: a Eurocentric perspective===\nThe oldest form of government grew out of tribal organization. Rule by elders was supplanted by monarchy, an arrangement where a single family dominated the political affairs of a polity. Monarchies have existed in one form or another throughout human history.\n\n[[Greeks]] developed democracy as a means of governance. Athenian direct democracy limited citizenship to free, male, landholders but demonstrated the viability of government by the governed, albeit an educated leisure class.\n\nThe [[Roman Republic]] is credited with significant innovation in forms of government. It was the first [[bicameral]] legislative system, which divided power between the [[patrician]] [[aristocracy]] and [[plebian]] general [[citizens]]. It also contained the beginnings of [[representative democracy]], having various officers selected for fixed terms by popular [[election]].\n\nFollowing the collapse of the Roman Empire, Europe reverted to feudal monarchy where the mailed fist ruled.\n\nThe [[Renaissance]], the [[Enlightenment]], and the [[Industrial Revolution]] each increased the availability of education and leisure to otherwise disenfranchised classes along with a desire to participate in governance.\n\n[[Karl Marx]] argued that this process of political progress will not be complete until classes no longer exist and every person is the master of his own fate. Marx never imagined the juggernaut democratic capitalism.\n\nThis analysis argues that progress, i.e. democratization, increases with the rise of an educated population that has time to devote to activities beyond simple survival.\n\n==Sababaraha konsép nu mangpaat==\n===Kakawasaan===\nAs noted power is the ability to impose ones will on another. It implies a capacity for force, i.e violence. \nMore generally, it can be considered the ability to change the liklihood of outcomes. The ability to impose one\'s will on others is very often not a totally dependable policy option. It comes in degrees, thus we can speak of the degree to which we can change the liklihood of outcomes. In politics one of the most subtle and effective kinds of \"power\" does not involve overt violence. Instead , it is the control of the agenda for deliberation. If you control what is considered proper for political discourse, what our options are for policy choice, you are indeed exercising real power.\n\n===Authority===\nAuthority is the ability to wield the instruments of power. Its legitimacy is measured by the extent to which it receives support from the governed.\n===Legitimacy===\nLegitimacy is an attribute of government gained through the application of power in accordance with recognized or accepted standards or principles.\n===Government===\nA government is a body that has the ability to make and enforces rules or laws. A government\'s power is influenced by authority and legitimacy.\n\n==Sources of authority==\n\n\"Politics\" may have a [[pejorative]] sense, particularly when applied to the internal workings of institutions. Saying that a decision was reached for \"political\" reasons may hint that those reasons were more motivated by petty interests or [[influence peddling]] than by objective reasons or the common good.\n\nAt whatever scale, politics is the rather imperfect way that people coordinate individual actions for mutual (or strictly personal) gain. What distinguishes the \'\'\'political\'\'\' from the [[ethical]] or merely [[social]] is a much-debated question. Most theorists would acknowledge that to be political, a process has to involve at least some potential for use of force or violence - politics is about conflict that is about much more than theory and fashion. To win a political conflict always implies that one has taken power away from one [[group-entity|group or faction]] to give it to another. Most would also acknowledge that political conflict can easily degrade to [[zero-sum game]]s, with little learned or settled by conflict other than \"who won and who lost\":\n\n[[Lenin]] said politics was about \"who could do what to whom\" ([[Russian language|Russian]] \"[[Kto-Kogo]]\" for \"Who-Whom\"). As political scientist [[Harold Lasswell]] said, politics is \"who gets what, when and how.\" It also concerns how we resolve moral conflicts that are sufficiently serious that they constitute a risk of social disruption - in which case commitment to a common process of [[arbitration]] or [[diplomacy]] tends to reduce [[violence]] - usually viewed as a key goal of [[civilization]]. [[Bernard Crick]] is a major theorist of this view and also of the idea that politics is itself simply \"[[ethics]] done in public\", where public institutions can agree, disagree, or intervene to achieve a desirable culmination or comprehensive (process) result. \n\nIn addition to [[government]], [[journalism|journalists]],\n[[religion|religious groups]], [[special interest]] groups, and [[economics|economic]] systems and conditions may all have influence on decisions. Therefore, politics touches on all these subjects. \n\nThe word itself is coined from the Greek word for city, \"Polis\", hence the term \'Politics\'. The first expression of what Politics means is found in [[Hesoid]] where it is quoted, \"How would men best dwell in cities, and with what observances?\". (1) Paraphrased, it would read, \"How shall man order his ways?\". For the Greeks, it was the application of reason to life. Politics is an ordering of society by reason of attainment to some goal; such as harmony among the social classes as in [[Athens]] under [[Solon]], or business and commerce, or for war such as the Doric Communities of [[Crete]] and [[Sparta]]. \n\n[[Authors]] of studies of politics have both reflected and influenced the political systems of the world. [[Niccolo Machiavelli]] wrote [[The Prince]], an analysis of politics in a [[monarchy]], in 1513, while living in a monarchy. [[Karl Marx]] and [[Friedrich Engels]] published \"[[The Communist Manifesto]]\" in [[1848]], a widely-read and highly influential pamphlet that formed the basis for Socialism and Communism throughout the 19th and 20th centuries. \n\nToday, much study of politics focuses on [[democracy|democracies]], and how their form affects the decisions they make.\n\nOther lines of political inquiry attempt to answer \n[[political philosophy|philosophical]] questions such as;\n*is there a moral [[The justification of the state|justification]] for government?\n*what is [[the purpose of government]]? \n*is there any possible empirical or more [[formal method for evaluating and quantifying ethicality and morality of human actions]] that could augment or replace [[religion]] or [[authority]] or political contention in deciding what political leaders \"should\" do? \n*is there an objective way to evaluate the quality of a decision, policy, leader or [[political party|party]]? \n\nThese are ongoing debates that are millennia old.\n\nAs well as being influenced by these weighty matters, politics is also a [[social]] activity, and as such it is subject to the whims of [[fashion]] as any other.\n\n== References ==\n\n(1) Hesoid, Loeb Classical Library, pg 581\n\n== Élmu pulitik ==\n\n[[Élmu pulitik|Élmuwan pulitik]] nyaéta akademisi nu nalungtik paripolah/kagiatan pulitik. Aranjeunna nengetkeun [[pamilihan umum|pamilu]], pamanggih umum (\'\'public opinion\'\'), kagiatan kalembagaan (cara peta législatur, the relative importance of various sources of political power etc), idéologi satukangeun rupa-rupa pulitikus jeung organisasi pulitik, cara pulitikus achieve and wield their influence, jeung saterusna.\n\n== Sistim pulitik jeung idéologi ==\n\n[[Anarkisme]] | [[Anarko-kapitalisme]] | [[Anarko-komunisme]] | [[Anti-komunisme]] | [[Otoritarianisme]] | [[Kapitalisme]] | [[Républik: definisi klasik]] | [[Liberalisme klasik]] | [[Komunisme]] | [[Konservatisme]] | [[Korporatokrasi]] | [[Démokrasi]] | [[Sosialisme démokratis]] | [[pulitik héjo|Héjo]] | [[Fasisme]] | [[Féderalisme]] | \'\'[[Leftism]]\'\' | [[Liberalisme pulitik|Liberalisme]] | [[Libertarianisme]] | [[Sosialisme libertarian]] | [[Marxisme]] | [[Meritokrasi]] | [[Minarkisme]] | [[Monarki]] | [[Nasionalisme]] | [[Nazisme|Sosialisme nasional]] | [[Oligarki]] | [[Post-Communism]] | [[Radical centrism]] | [[Républikanisme]] | [[Sosialisme]] | [[Stalinisme]] | [[Totalitarianisme]] | [[Téokrasi]]\n\n== Éntitas pulitik ==\n\n[[Dayeuh]] | [[Nagara-dayeuh]] | [[Konféderasi]] | [[Nagara]] | [[Kakaisaran]] | [[Féderasi]] | [[Pamaréntah]] | [[Nagara-bangsa]] | [[police state]] | \'\'[[Prefecture]]\'\' | [[Principality]] | [[Provinsi]] | [[Républik]] | [[state]] | [[Pamaréntahan dunya]]\n\n== Major topics in [[political philosophy]] ==\n\n== Classical political theorists ==\n\n[[Plato]] | [[Aristotle]] | [[Thucydides]] | [[Cicero]] | [[Saint Augustine]] | [[Thomas Aquinas]]\n\n== Modern political theorists == \n\n[[Nicolo Machiavelli]] | [[John Calvin]] | [[Martin Luther]] | [[Baruch Spinoza]] | [[Jean Bodin]] | [[Thomas Hobbes]] | [[John Locke]] | [[David Hume]] | [[Adam Smith]] | [[Jeremy Bentham]] | [[the Federalist Papers]] | [[Jean-Jacques Rousseau]] | [[Immanuel Kant]] | [[G.W.F. Hegel]] | [[Johann Gottfried von Herder]] | [[Alexis deTocqueville]] | [[John Stuart Mill]] | [[Karl Marx]] | [[Friedrich Engels]] | [[Max Weber]] | [[Lenin]]\n\n== Contemporary political theorists ==\n\n[[David Friedman]] | [[Noam Chomsky]] | [[John Rawls]] | [[Jan Narveson]] | [[David Gauthier]] | [[Amartya Sen]] | [[Jürgen Habermas]] | [[James M. Buchanan]] | [[Bernard Crick]] | [[Michel Foucault]] | [[Jane Jacobs]] | [[Carol Moore]] | [[Antonio Negri]] | [[Robert Nozick]] | [[Hannah Arendt]] | [[Mohandas Gandhi]] | [[Ayn Rand]]\n\n== Miscellaneous ==\n\n[[International organization]] | [[Corporate police state]] | [[Crony capitalism]] | [[European Union]] | [[Police]] | [[Propaganda]] | [[U.S. Politics]] | [[Political spectrum]] | [[Political party]] | [[Political economy]] | [[Political parties of the world]] | [[E-democracy]] | [[Terrorism]] | [[Political Compass]] | [[Divide and conquer (politics)|Divide and conquer]] | [[Political sociology]] | [[Political education]] | [[Civic education]] | [[List of years in politics]]\n\n== Tempo ogé ==\n\n*Pikeun politik nu husus hiji nagara, mangga sindang ka [[Daptar politik dumasar artikel nagara]]\n*[[Apolitis]]\n\n[[Category:Étik]]\n[[Category:Daptar jejer]]\n\n[[bg:Политика]]\n[[ca:Política]]\n[[cs:Politika]]\n[[da:Politik]]\n[[de:Politik]]\n[[en:Politics]]\n[[et:Politoloogia]]\n[[es:Política]]\n[[eo:Politiko]]\n[[fr:Politique]]\n[[gl:Política]]\n[[ia:Politica]]\n[[it:Politica]]\n[[he:פוליטיקה]]\n[[sw:Siasa]]\n[[la:Politica]]\n[[ms:politik]]\n[[nl:Politiek]]\n[[ja:政治]]\n[[no:Politikk]]\n[[nds:Politik]]\n[[pl:Polityka]]\n[[pt:Política]]\n[[fi:Politiikka]]\n[[sv:Politik]]\n[[th:การเมือง]]\n[[tr:Politika]]\n[[uk:Політика]]\n[[zh-cn:政治学]]\n[[zh-tw:政治學]]\n[[simple:Politics]]','/* Some useful concepts */',3,'Kandar','20041222043210','',0,0,0,0,0.581307463619,'20041229235111','79958777956789'); INSERT INTO cur VALUES (1151,6,'','sebaran-t','sebaran-t',13,'Budhi','20040817020957','',0,0,0,1,0.465374935851782,'20040817020957','79959182979042'); INSERT INTO cur VALUES (1152,6,'T_distribution_1df.png','sebaran-t','sebaran-t',13,'Budhi','20040817021102','',0,0,0,1,0.415203292309496,'20041225044457','79959182978897'); INSERT INTO cur VALUES (1153,6,'T_distribution_2df.png','sebaran-t ti wikipedia english','sebaran-t ti wikipedia english',13,'Budhi','20040817021911','',0,0,0,1,0.67989168472578,'20041225044457','79959182978088'); INSERT INTO cur VALUES (1154,6,'T_distribution_3df.png','','',13,'Budhi','20040817022436','',0,0,0,1,0.153848577434056,'20041225044457','79959182977563'); INSERT INTO cur VALUES (1155,6,'T_distribution_5df.png','','',13,'Budhi','20040817022516','',0,0,0,1,0.729567863726586,'20041225044457','79959182977483'); INSERT INTO cur VALUES (1156,6,'T_distribution_30df.png','sebaran-t ti wikipedia english','sebaran-t ti wikipedia english',13,'Budhi','20040817022554','',0,0,0,1,0.186293617064407,'20041225044457','79959182977445'); INSERT INTO cur VALUES (1157,6,'T_distribution_10df.png','sebaran-t ti wikipedia english','sebaran-t ti wikipedia english',13,'Budhi','20040817022626','',0,0,0,1,0.742764524875921,'20041225044457','79959182977373'); INSERT INTO cur VALUES (1158,0,'Student\'s_t-test','\'\'\'Test\'\'\'-\'\'\'\'\'t\'\'\'\'\' nyaeta unggal [[tes hipotesa statistik]] numana tes statistik ngabogaan [[Sebaran-t student]] lamun [[null hypothesis]] bener.\n\n\n{{pondok}}','',13,'Budhi','20050104065556','',0,0,0,0,0.778961606686,'20050303211247','79949895934443'); INSERT INTO cur VALUES (1159,0,'William_Sealey_Gosset','\'\'\'William Sealy Gosset\'\'\' ([[June 13]], [[1867]] – [[October 16]], [[1937]]) was a [[chemist]] and [[statistician]], better known by his pen name \'\'Student\'\'. Born [[Canterbury, England|Canterbury]], [[England]] to Agnes Sealy Vidal and Colonel Frederic Gosset , Gosset attended [[Winchester College]], the famous private school, before reading [[chemistry]] and [[mathematics]] at [[New College, Oxford]]. On graduating in [[1899]], he joined the [[Dublin]] brewery of Arthur [[Guinness]] & Son.\n\n[[Guinness]] was a progressive agro-chemical business and Gosset would apply his statistical knowledge both in the brewery and on the farm—to the selection of the best yielding varieties of [[barley]]. Gosset acquired that knowledge by study, trial and error and by spending two terms in 1906/7 in the biometric laboratory of [[Karl Pearson]]. Gosset and [[Karl Pearson|Pearson]] had a good relationship and Pearson helped Gosset with the mathematics of his papers. [[Karl Pearson|Pearson]] helped with the 1908 papers but he had little appreciation of their importance. The papers addressed the brewer\'s concern with small samples but the biometrician typically had hundreds of observations and saw no urgency in developing small-sample methods.\n\nAnother researcher at Guinness had previously published a paper containing trade secrets of the Guinness brewery. To prevent further disclosure of confidential information, Guinness prohibited its employees from publishing any papers regardless of the contained information. This means that Gosset was unable to publish his works under his own name. Therefore he used the pseudonym \'\'Student\'\' for his publications to avoid detection of his publications by his employer. Therefore his most famous achievement is now referred to as the [[sebaran-t student]], which may otherwise have been the Gosset t-distribution. \n\nUsing this pseudonym [[Karl Pearson|Pearson]] published \'\'The probable error of a mean\'\' and almost all of Gosset\'s papers in his journal \'\'Biometrika\'\'. However, it was [[Ronald Fisher]] who appreciated the importance of Gosset\'s small-sample work, after Gosset had written to him to say \'\'I am sending you a copy of Student\'s Tables as you are the only man that\'s ever likely to use them!\'\'. [[Ronald Fisher|Fisher]] believed that Gosset had effected a “logical revolution”. Ironically the \'\'t\'\'-statistic for which Gosset is famous was actually [[Ronald Fisher|Fisher]]\'s creation. Gosset\'s statistic was \'\'z\'\' = \'\'t\'\'/√(\'\'n\'\' - 1). [[Ronald Fisher|Fisher]] introduced the \'\'t\'\'-form because it fitted in with his theory of [[degrees of freedom]]. [[Ronald Fisher|Fisher]] was also responsible for the applications of the \'\'t\'\'-distribution to regression.\n\nAlthough introduced by others, [[Studentized residual]]s are named in Student\'s honor because, like the problem that led to Student\'s t-distribution, the idea of adjusting for estimated standard deviations is central to that concept.\n\nGosset\'s interest in [[barley]] cultivation led him to speculate that [[desain percobaan]] should aim, not only at improving the average yield, but also at breeding varieties whose yield was insensitive (robust) to variation in soil and climate. This principle only occurs in the later thought of [[Ronald Fisher|Fisher]] and then in the work of [[Genichi Taguchi]] in the [[1950s]].\n\nIn [[1935]], he left [[Dublin]] to take up the position of Head Brewer, in charge of the scientific side of production, at a new [[Guinness]] brewery in London. He died in [[Beaconsfield]], [[England]].\n\nGosset was a friend of both [[Karl Pearson|Pearson]] and [[Ronald Fisher|Fisher]], an achievement for each had a massive ego and a loathing for the other. Gosset was a modest man who cut short an admirer with the comment that “Fisher would have discovered it all anyway.”\n----\n\n===Bibliography===\n* \'\'The application of the law of error to the work of the Brewery\'\' ([[1904]], nota interna presso \'\'Guinness\'\')\n* \'\'On the error of counting with hæmacytometer,\'\' Biometrika, Vol. 5, No. 3. (Feb.), pp. 351-360 ([[1907]])\n* [http://www.york.ac.uk/depts/maths/histstat/student.pdf \'\'The probable error of a mean,\'\' Biometrika, Vol. 6, No. 1. (Mar.), pp. 1-25] ([[1908]])\n* \'\'Probable error of a correlation coefficient,\'\' Biometrika, Vol. 6, No. 2/3. (Sep.), pp. 302-310.([[1908]])\n* \'\'The distribution of the means of samples which are not drawn at random,\'\' Biometrika, Vol. 7, No. 1/2. (Jul. - Oct.), pp. 210-214 ([[1909]])\n* \'\'An experimental determination of the probable error of Dr Spearman\'s correlation coefficients,\'\' Biometrika, Vol. 13, No. 2/3. (Jul.), pp. 263-282. ([[1921]])\n*[http://www.economics.soton.ac.uk/staff/aldrich/fisherguide/student.htm \'\'Review of Statistical Methods for Research Workers (R. A. Fisher)\'\'] ([[1926]])\n* \'\'‘Student’s’ Collected Papers\'\' (edited by E.S. Pearson and John Wishart, with a foreword by Launce McMullen. London: Biometrika Office. ([[1942]])\n\n===Biography of Gosset===\n*E. S. Pearson (1990) \'\'‘Student’, A Statistical Biography of William Sealy Gosset,\'\' Edited and Augmented by R. L. Plackett with the Assistance of G. A. Barnard, Oxford: University Press.\n\n==External links==\n*[http://www.swlearning.com/quant/kohler/stat/biographical_sketches/bio12.1.html Biography by Heinz Kohler]\n*[http://www.umass.edu/wsp/statistics/tales/gosset.html Tales of Statisticians by E. Bruce Brooks]\n*[http://www-stat.stanford.edu/~naras/jsm/TDensity/TDensity.html Student\'s T Distribution]\nFor a brief account of how Student\'s \'\'z\'\' became \'\'t\'\' see the entry on Student\'s \'\'t\'\'-distribution in\n*[http://members.aol.com/jeff570/s.html Earliest known uses of some of the words of mathematics: S]\n\n[[Category:Statisticians|Gosset, William Sealey]]\n[[Category:Chemists|Gosset, William Sealey]]\n\n[[de:William Gosset]]\n[[it:William Sealy Gosset]]','',13,'Budhi','20041224104316','',0,0,1,0,0.971311691669,'20041225235727','79958775895683'); INSERT INTO cur VALUES (1160,0,'Student\'s_t-distribution','#REDIRECT [[sebaran-t student]]','',13,'Budhi','20040817024057','',0,1,0,1,0.374342673632,'20040817024057','79959182975942'); INSERT INTO cur VALUES (1161,0,'Ronald_A._Fisher','#redirect [[Ronald Fisher]]','',13,'Budhi','20040817030517','',0,1,0,1,0.144820020602,'20040817030626','79959182969482'); INSERT INTO cur VALUES (1162,0,'Ronald_Fisher','[[image:Ronald_Fisher.jpg|thumb|right|220px|Sir Ronald Fisher]]\n\nSir \'\'\'Ronald Aylmer Fisher\'\'\', [[Fellow of the Royal Society|FRS]] ([[February 17]], [[1890]] - [[July 29]], [[1962]]) was an extraordinarily talented [[evolution]]ary biologist, [[genetics|geneticist]] and [[statistician]]. He has been described by [[Richard Dawkins]] as \"The greatest of [[Charles Darwin|Darwin’s]] successors,\" and the historian of statistics [[Anders Hald]] said \"Fisher was a genius who almost single-handedly created the foundations for modern statistical science.\"\n\n==Contributions to statistics==\n\nFisher nu manggihkeun teknik [[maximum likelihood]] sarta [[analisa varian]], nu ngamimitian dina [[desain percobaan]], and originated the concepts of [[sufficiency (statistics)|sufficiency]], [[ancillary statistic|ancillarity]], and [[Fisher information]], making him a major figure in [[20th century]] statistics. His article \"On a distribution yielding the error functions of several well known statistics\" presented [[Karl Pearson|Karl Pearson\'s]] [[Uji kuadrat-chi Pearson|chi-square]]d and [[William Sealey Gosset|Student\'s]] [[Student\'s t-distribution|t]] in the same framework as the normal distribution and his own analysis of variance distribution z. Fisher\'s book \'\'Statistical methods for research workers\'\' showed how to use these distributions. His work on the theory of [[population genetics]] also made him one of the three great figures of that field, together with [[Sewall Wright]] and [[J. B. S. Haldane]], and as such one of the founders of the neodarwinian [[modern synthesis]]. See also [[Fisher\'s linear discriminator]].\n\nFisher\'s important contributions to both genetics and statistics are emphasized by the remark of [[Leonard Jimmie Savage|L.J. Savage]],\n“I occasionally meet geneticists who ask me whether it is true that the great geneticist R.A. Fisher was also an important statistician” (\'\'Annals of Statistics\'\', 1976).\n\n==Fisher information==\nHe introduced the concept of [[Fisher information]] in [[1925]], many years before [[Shannon]]\'s notion of entropy. Fisher information has been the subject of renewed interest in the last few years, both due to the growth of [[Bayesian inference]] in [[AI]], and due to [[B. R. Frieden]]\'s book \'\'Physics from Fisher Information\'\', which attempts to derive the laws of physics from a Fisherian starting point.\n\n==Brief biography==\n\nHe was born in [[East Finchley]], [[London]] and obtained a B.A. degree in [[mathematics]], not astronomy as is often said, from [[Cambridge University]] in [[1912]]. In [[1911]] he was involved in the formation of the Cambridge University Eugenics Society. His studies of errors in astronomical calculations, together with his interests in [[genetics]] and [[natural selection]], led to involvement in statistics.\n\nFrom [[1919]] he worked at [[Rothamsted Experimental Station]] making contributions in statistics and [[genetics]]. In [[1933]] he became a professor of [[eugenics]] at [[University College London]] moving in 1943 to the Balfour chair of [[genetics]] at Cambridge.\n\nHe received various awards for his work and was made a [[Knight Bachelor]] by [[Elizabeth II of the United Kingdom|Queen Elizabeth II]] in [[1952]]. He had a long running feud with [[Karl Pearson]] (he declined a post at the University of London), and later with Pearson\'s son E.S. Pearson. After retiring from Cambridge he spent some time as a research fellow at the [[CSIRO]] in [[Adelaide]], [[Australia]] where he died in [[1962]].\n\n==Bibliography==\n\n=== A selection from Fisher\'s 395 articles===\n(The following are all available on the University of Adelaide website)\n* \"Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population.\" \'\'Biometrika\'\', \'\'\'10\'\'\': 507-521.([[1915]])\n* \"[[The Correlation Between Relatives on the Supposition of Mendelian Inheritance|The correlation between relatives on the supposition of Mendelian inheritance]]\" \'\'Trans. Roy. Soc. Edinb.\'\', \'\'\'52\'\'\': 399-433.([[1918]])\n* \"On the mathematical foundations of theoretical statistics\" \'\'Philosophical Transactions of the Royal Society, A\'\', \'\'\'222\'\'\': 309-368.([[1922]])\n* \"On the dominance ratio. \'\'Proc. Roy. Soc. Edinb.\'\', \'\'\'42\'\'\': 321-341.([[1922]])\n* \"On a distribution yielding the error functions of several well known statistics\" \'\'Proc. Int. Cong. Math.\'\', Toronto, \'\'\'2\'\'\': 805-813. ([[1924]])\n* \"Theory of statistical estimation\" Proceedings of the Cambridge \'\'Philosophical Society\'\', \'\'\'22\'\'\': 700-725 ([[1925]])\n* \"Applications of Student\'s distribution\" \'\'Metron\'\', \'\'\'5\'\'\': 90-104 ([[1925]])\n* \"The arrangement of field experiments\" \'\'J. Min. Agric. G. Br.\'\', \'\'\'33\'\'\': 503-513.([[1926]])\n* \"The general sampling distribution of the multiple correlation coefficient\" \'\'Proceedings of Royal Society, A\'\', \'\'\'121\'\'\': 654-673 ([[1928]])\n* \"Two new properties of mathematical likelihood\" \'\'Proceedings of Royal Society, A\'\', \'\'\'144\'\'\': 285-307([[1934]])\n\n===Books by Fisher===\n(Full publication details are available on the University of Adelaide website)\n*\'\'Statistical methods for research workers\'\' ([[1925]])\n*\'\'[[The Genetical Theory of Natural Selection]]\'\' ([[1930]])\n*\'\'The design of experiments\'\' ([[1935]])\n*\'\'Statistical tables for biological, agricultural and medical research\'\' ([[1938]], coauthor:[[Frank Yates]])\n*\'\'The theory of inbreeding\'\' ([[1949]])\n*\'\'Contributions to mathematical statistics\'\' ([[1950]]) \n*\'\'Statistical methods and statistical inference\'\' ([[1956]])\n\n===Biographies of Fisher===\n* Fisher Box J ([[1978]]) \'\'R. A. Fisher: The Life of a Scientist\'\', New York: Wiley.\n* Yates F & Mather K ([[1963]]) Ronald Aylmer Fisher. \'\'Biographical Memoirs of Fellows of the Royal Society of London\'\' 9:91-120 [http://www.library.adelaide.edu.au/digitised/fisher/raf.pdf Available on University of Adelaide website]\n\n==External links==\n*[http://www-groups.dcs.st-and.ac.uk/~history/Mathematicians/Fisher.html Biography at MacTutor]\n*[http://www.hbcollege.com/business_stats/kohler/biographical_sketches/bio13.1.html Biography by Heinz Kohler]\n*[http://www.economics.soton.ac.uk/staff/aldrich/fisherguide/rafreader.htm A Guide to R. A. Fisher by John Aldrich]\n*[http://members.aol.com/jeff570/mathword.html Earliest Known Uses of Some of the Words of Mathematics for Fisher’s contribution to the language of statistics]\n*[http://www.library.adelaide.edu.au/digitised/fisher/index.html University of Adelaide Library for bibliography, biography, 2 volumes of correspondence and many articles]\n*[http://psychclassics.yorku.ca/Fisher/Methods/ Classics in the History of Psychology for the first edition of \'\'Statistical Methods for Research Workers\'\']\n\n{{popgen}}\n[[Category:Statisticians|Fisher, Ronald]]\n[[category:Evolutionary biologists|Fisher, Ronald]]\n[[Category:Population geneticists|Fisher, Ronald]]\n[[category:Fellows of the Royal Society|Fisher, Ronald]]\n[[it:Ronald Fisher]]','/* Contributions to statistics */',13,'Budhi','20041224204434','',0,0,1,0,0.344212070733,'20050316081936','79958775795565'); INSERT INTO cur VALUES (1163,6,'Ronald_Fisher.jpg','Ronald Fisher ti Wikipedia English','Ronald Fisher ti Wikipedia English',13,'Budhi','20040817030815','',0,0,0,1,0.154941803920029,'20041224204434','79959182969184'); INSERT INTO cur VALUES (1164,0,'Thomas_Bayes','[[image:thomasbayes.jpg|right|Thomas Bayes]]\n\n\'\'\'Thomas Bayes\'\'\' (c. [[1702]]-[[April 17]],[[1761]]) was a [[United Kingdom|British]] [[mathematician]] and [[Presbyterian]] minister, known for having formulated a special case of [[Bayes\' theorem]].\nBayes was elected Fellow of the [[Royal Society]] in 1742.\n\nBorn in [[London, England]], Bayes died in [[Tunbridge Wells]], [[Kent]]. He is interred in [[Bunhill Fields]] Cemetery in London,\nwhere many [[Nonconformist]]s are buried.\n\n== Works by Thomas Bayes ==\n\nBayes is known to have published two works in his lifetime: \'\'Divine Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of His Creatures\'\' ([[1731]]), and \'\'An Introduction to the Doctrine of Fluxions, and a Defence of the Mathematicians Against the Objections of the Author of the Analyst\'\' (published anonymously in [[1736]]), in which he defended the logical foundation of [[Isaac Newton]]\'s [[calculus]] against the criticism of [[George Berkeley]], author of \'\'[[The Analyst]]\'\'.\nIt is speculated that Bayes was elected to the Royal Society on the strength of the \'\'Introduction to the Doctrine of Fluxions\'\', \nas he is not known to have published any other mathematical works during his lifetime.\n\nBayes\' solution to a problem of \"inverse probability\" was presented in the \'\'Essay Towards Solving a Problem in [[the Doctrine of Chances]]\'\' ([[1763]]), published posthumously by his friend [[Richard Price]] in the \'\'Philosophical Transactions of the Royal Society of London.\'\'\nThis essay contains a statement of a special case of [[Bayes\' theorem]].\n\nIn the first decades of the [[eighteenth century]],\nmany problems concerning the probability of certain events,\ngiven specified conditions, were solved.\nFor example, given a specified number of white and black balls in an urn,\nwhat is the probability of drawing a black ball?\nThese are sometimes called \"forward probability\" problems.\nAttention soon turned to the converse of such a problem:\ngiven that one or more balls has been drawn,\nwhat can be said about the number of white and black balls in the urn?\nThe \'\'Essay\'\' of Bayes contains his solution to a similar problem,\nposed by [[Abraham de Moivre]], author of \'\'[[The Doctrine of Chances]]\'\' (1733).\n\nIn addition to the \'\'Essay Towards Solving a Problem\'\',\na paper on asymptotic series was published posthumously.\n\n== Was Bayes a Bayesian? ==\n\n[[Bayesian probability]] is the name given to several related interpretations of [[probability]],\nwhich have in common the application of probability to any kind of statement,\nnot just those involving [[random variable]]s.\n\"Bayesian\" has been used in this sense since about 1950.\n\nIt is not at all clear that Bayes himself would have embraced the very broad interpretation now called Bayesian.\nIt is difficult to assess Bayes\' philosophical views on probability,\nas the only direct evidence is his essay,which does not go into questions of interpretation. In the essay, Bayes defines \'\'probability\'\' as follows (Definition 5).\n\n:The probability of any event is the ratio between the value at which an expectation depending on the happening of the event ought to be computed, and the chance of the thing expected upon it\'s happening.\n\nIn modern [[utility theory]] we would say that expected utility is the probability of an event times the payoff received in case of that event.\nRearranging that to solve for the probability, we obtain Bayes\' definition.\nAs Stigler (citation below) points out, this is a subjective definition, and does not require repeated events; however, it does require that the event in question be observable, for otherwise it could never be said to have \"happened\".\n\nThus it can be argued, as Stigler does,\nthat Bayes intended his results in a rather more limited way than modern Bayesians; given Bayes\' definition of probability, his result concerning the parameter of a binomial distribution makes sense only to the extent that one can bet on its observable consequences.\n\n==Bayesian inference and spam==\n\nAs a particular application of statistical [[classification]],\n[[Bayesian inference]] has been used in recent years to develop a number of algorithms for identifying unsolicited bulk e-mail ([[Spam (e-mail)|spam]]). \nThis has introduced [[Bayesian probability]] to a wider audience.\nSpam classification is treated in more detail in the article on [[naive Bayesian classification]].\n\n==References== \n\n* Andrew I. Dale. \"Most Honourable Remembrance: The Life and Work of Thomas Bayes\". ISBN: 0-387-00499-8. Springer, 2003.\n\n* Stephen M. Stigler. \"Thomas Bayes\' Bayesian Inference,\" \'\'Journal of the Royal Statistical Society\'\', Series A, 145:250-258, 1982.\n\n* Stephen M. Stigler. \"Who Discovered Bayes\'s Theorem?\" \'\'The American Statistician\'\', 37(4):290-296, 1983.\n\n==Tumbu kaluar==\n\n* [http://www.bayesian.org/bayesian/bayes.html Who was The Rev. Thomas Bayes?]\n\n* [http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Bayes.html Biographical sketch of Thomas Bayes]\n\n* Thomas Bayes. [http://www.stat.ucla.edu/history/essay.pdf \"An essay towards solving a Problem in the Doctrine of Chances\"] \'\'(Bayes\'s essay in the original notation)\'\'\n\n* D.R. Bellhouse. [http://www.stats.uwo.ca/faculty/bellhouse/bayesmss.pdf \"On Some Recently Discovered Manuscripts of Thomas Bayes\"]\n\n* Daniel Covarrubias. [http://www.stat.rice.edu/~blairc/seminar/Files/danTalk.pdf \"An Essay Towards Solving a Problem in the Doctrine of Chances\"] \'\'(an outline and exposition of Bayes\'s essay)\'\'\n\n* Paul Graham. [http://www.paulgraham.com/spam.html \"A Plan for Spam\"] \'\'(exposition of a popular approach for spam classification)\'\'\n\n[[Category:Mathematicians|Bayes, Thomas]]\n[[Category:Statisticians|Bayes, Thomas]]\n\n[[de:Thomas Bayes]]\n[[it:Thomas Bayes]]\n[[nl:Thomas Bayes]]','/* External links */',13,'Budhi','20040818000300','',0,0,0,0,0.8165620979,'20041231122709','79959181999699'); INSERT INTO cur VALUES (1165,6,'Thomasbayes.jpg','Thomas Bayes ti Wikipedia English','Thomas Bayes ti Wikipedia English',13,'Budhi','20040817031241','',0,0,0,1,0.546415475706025,'20040818000305','79959182968758'); INSERT INTO cur VALUES (1166,0,'Daptar_statistikawan','#REDIRECT [[Daptar Statistikawan]]','',13,'Budhi','20040817031623','',0,1,0,1,0.739305083984,'20040817031623','79959182968376'); INSERT INTO cur VALUES (1167,0,'Statistikawan','#REDIRECT [[statistik]]','',13,'Budhi','20040817032000','',0,1,0,1,0.592420602959,'20040817032000','79959182967999'); INSERT INTO cur VALUES (1168,0,'Probability_density_function','[[da:sandsynlighedstæthedsfunktion]] [[sv:Täthetsfunktion]]\n\nDina [[matematik]], \'\'\'probability density function\'\'\' dipake keur ngagambarkeun [[probability distribution]] di watesan [[integral]]s. Lamun probability distribution ngabogaan densiti \'\'f\'\'(\'\'x\'\'), saterusna [[interval (mathematics)|interval]] tak terhingga [\'\'x\'\', \'\'x\'\' + d\'\'x\'\'] ngabogaan probabiliti \'\'f\'\'(\'\'x\'\') d\'\'x\'\'. Probability density function bisa oge ditempo tina versi \"smoothed out\" [[histogram]]: if one empirically measures values of a [[random variable]] repeatedly and produces a histogram depicting relative frequencies of output ranges, then this histogram will resemble the random variable\'s probability density (assuming that the variable is sampled sufficiently often and the output ranges are sufficiently narrow).\n\nFormally, a probability distribution has density \'\'f\'\'(\'\'x\'\') if \'\'f\'\'(\'\'x\'\') is a non-negative [[Lebesgue integration|Lebesgue-integrable]] function \'\'\'R\'\'\' → \'\'\'R\'\'\' such that the probability of the interval [\'\'a\'\', \'\'b\'\'] is given by \n\n:\\int_a^b f(x)\\,dx\n\nfor any two numbers \'\'a\'\' and \'\'b\'\'. This implies that the total integral of \'\'f\'\' must be 1. Conversely, any non-negative Lebesgue-integrable function with total integral 1 is the probability density of a suitably defined probability distribution.\n\nContona, sebaran seragam dina interval [0,1] ngabogaan probabiliti densiti \'\'f\'\'(\'\'x\'\') = 1 keur 0 ≤ \'\'x\'\' ≤ 1 jeung nol dimamana. Standar [[sebaran normal]] ngabogaan probabiliti densiti\n\n:f(x)={e^{-{x^2/2}}\\over \\sqrt{2\\pi}}.\n\nLamun [[variabel random]] \'\'X\'\' diberekeun sarta distribusina kaasup kana fungsi probabiliti densiti \'\'f\'\'(\'\'x\'\'), mangka [[nilai ekspektasi]] \'\'X\'\' (lamun eta aya) bisa diitung ku\n\n:\\operatorname{E}(X)=\\int_{-\\infty}^\\infty x\\,f(x)\\,dx\n\nNot every probability distribution has a density function: the distributions of [[discrete random variable]]s do not; nor does the [[Cantor distribution]], even though it has no discrete component, i.e., does not assign positive probability to any individual point.\n\nA distribution has a density function if and only if its [[cumulative distribution function]] \'\'F\'\'(\'\'x\'\') is [[absolute continuity|absolutely continuous]]. In this case, \'\'F\'\' is [[almost everywhere]] [[derivative|differentiable]], and its derivative can be used as probability density. If a probability distribution admits a density, then the probability of every one-point set {\'\'a\'\'} is zero. \n\nIt is a common mistake to think of \'\'f\'\'(\'\'a\'\') as the probability of {\'\'a\'\'}, but this is incorrect; in fact, \'\'f\'\'(\'\'a\'\') will often be bigger than 1 - consider a random variable with a [[sebaran seragam|uniform distribution]] between 0 and 1/2.\n\nDua densiti \'\'f\'\' jeung \'\'g\'\' for the same distribution can only differ on a set of [[Lebesgue measure]] zero.\n\n\nTempo oge:\n* [[likelihood]]\n* [[probability mass function]]\n* [[exponential family]]','',13,'Budhi','20041224032611','',0,0,1,0,0.389272848325,'20041224032611','79958775967388'); INSERT INTO cur VALUES (1169,0,'Spearman\'s_rank_correlation_coefficient','[[de:Korrelationskoeffizient]]\n[[lv:Spirmena rangu korelacijas koefficients]]\n\nDina [[statistik]], \'\'\'Spearman\'s rank correlation coefficient\'\'\', often denoted by the Greek letter [[rho|ρ]], is a [[statistik non-parametrik|non-parametrik]] measure of [[correlation]] – that is, it assesses how well an arbitrary [[monotonic]] function could describe the relationship between two [[variable]]s, without making any assumptions about the [[sebaran frekuensi]] of the variables. Unlike the [[Pearson product-moment correlation coefficient]], it does not require the assumption that the relationship between the variables is [[linear equation|linear]], nor does it require the variables to be measured on [[interval measurement|interval scales]]; it can be used for variables measured at the [[ordinal measurement|ordinal]] level. \n\nIn principle, ρ is simply a special case of the Pearson product-moment coefficient in which the data are converted to ranks before calculating the coefficient. In practice, however, a simpler procedure is normally used to calculate ρ. The [[raw score]]s are converted to ranks, and the differences \'\'D\'\' between the ranks of each observation on the two variables are calculated. ρ is then given by:\n\n: \\rho = 1- {\\frac {6 \\sum D^2}{N(N^2 - 1)}}\n\nwhere: \n\n:\'\'D\'\' = the difference between the ranks of corresponding values of \'\'X\'\' and \'\'Y\'\', and\n\n:\'\'N\'\' = the number of pairs of values.\n\nThe formula becomes more complicated in the presence of [[tied ranks]], but unless the tie bands are large, the effect of ignoring them is small.\n\nTo test whether an observed value of ρ is significantly different from zero, the observed value can be compared with published tables for various levels of significance. A reference to such a table is given below. For sample sizes above about 20, ρ has a [[sebaran-t student]] in the null case (zero correlation). In the non-null case (i.e. to test whether an observed ρ is significantly different from a theoretical value, or whether two observed ρs differ significantly) tests are much less powerful, though the \'\'t\'\'-distribution can again be used.\n\nA generalisation of the Spearman coefficient is useful in the situation where there are three or more conditions, a number of subjects are all observed in each of them, and we predict that the observations will have a particular order. For example, a number of subjects might each be given three trials at the same task, and we predict that performance will improve from trial to trial. A test of the significance of the trend between conditions in this situation was developed by E. B. Page and is usually referred to as [[Page\'s trend test]] for ordered alternatives.\n\n==Tumbu kaluar==\n*[http://www.sussex.ac.uk/Users/grahamh/RM1web/Rhotable.htm Table of critical values of ρ for significance with small samples]','',13,'Budhi','20050105000158','',0,0,0,0,0.237065165414,'20050105000158','79949894999841'); INSERT INTO cur VALUES (1170,0,'Prediksi_interval','Dina [[statistik]], \'\'\'prediksi interval\'\'\' ngahasilkeun hubungan nu sarua dina observasi nu bakal datang yen [[interval kapercayaan]] ngalahirkeun parameter populasi nu teu ka-observasi.\n\n==Conto==\n\nAnggap sampel dicokot tina populasi [[sebaran normal]]. Populasi [[mean]] jeung [[simpangan baku]] teu dipikanyaho sajaba duanana bisa di-estimasi dumasar kana sampel. Hal ieu diperlukeun keur prediksi observasi saterusna. Anggap \'\'n\'\' jadi ukuran sampel; anggap μ jeung σ populasi mean jeung simpangan baku nu teu katalungtik. Anggap \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\', jadi sampel; anggap \'\'X\'\'\'\'n\'\'+1 observasi saterusna nu bakal diprediksi. Maka\n\n:\\overline{X}_n=(X_1+\\cdots+X_n)/n\n\njeung\n\n:S_n^2={1 \\over n-1}\\sum_{i=1}^n (X_i-\\overline{X}_n)^2.\n\nSaterusna geus ilahar ditunjukkeun ku\n\n:{X_{n+1}-\\overline{X}_n \\over S_n\\sqrt{1+(1/n)}}\n\nngabogaan [[sebaran-t student]] nu mibanda \'\'n\'\' − 1 tingkat kabebasan. Akibatna\n\n:P\\left(\\overline{X}_n-A S_n\\sqrt{1+(1/n)}\\leq X_{n+1} \\leq\\overline{X}_n+A S_n\\sqrt{1+(1/n)}\\,\\right)=p\n\nnumana \'\'A\'\' nyaeta percentil 100(1 − (p/2))th ti [[sebaran-t student]] nu mibanda \'\'n\'\' − 1 tingkat kabebasan. Numana angka\n\n:\\overline{X}_n\\pm A S_n\\sqrt{1+(1/n)}\n\nnyaeta the titiktungtung tina 100p% \'\'\'prediksi interval\'\'\' keur \'\'X\'\'\'\'n\'\'+1.\n\n==Tempo oge==\n\n[[Seymour Geisser]]','',13,'Budhi','20041225044724','',0,0,1,0,0.685827163367,'20041225044724','79958774955275'); INSERT INTO cur VALUES (1171,0,'Sebaran_chi-kuadrat','Keur satiap positip integer k, \'\'\'sebaran chi-kuadrat\'\'\' nu mibanda \'\'k\'\' [[tingkat kabebasan]] nyaeta [[probability distribution]] [[random variable]]\n: X=Z_1^2 + \\cdots + Z_k^2\nnumana \'\'Z\'\'1, ..., \'\'Z\'\'\'\'k\'\' ngarupakeun [[sebaran normal|variabel normal]] [[statistical independence|bebas]], masing-masing [[nilai ekspektasi]] 0 jeung [[varian]] 1. Sebaran ieu biasa ditulis\n:\nX\\sim\\chi^2_k\n\n\nLamun p watesan linier homogen bebas ditumpukeun dina ieu variabel, kayaan sebaran X dina watesan ieu nyaeta \\chi^2_{k-p}, dipastikeun salaku watesan \"tingkat kabebasan\". [[Characteristic function]] sebaran Chi-kuadrat nyaeta\n:\n\\phi(t)=(1-2it)^{k/2}.\n\nSebaran chi-kuadrat ngabogaan aplikasi numeris dina kaputusan [[statistik]], contona dina [[tes chi-kuadrat]] jeung estimasi [[varian]]. Ieu bisa diasupkeun kana masalah estimasi mean dina populasi sebaran normal jeung masalah estimasi slope dina garis [[linear regression|regression]] ku aturan dina [[sebaran-t student]]. Ieu diasupkeun kana sakabeh masalah [[analisa varian]] ku aturan dina [[sebaran-F]], nu ngarupakeun sebaran perbandingan dua chi-kuadrat [[variabel acak]].\n\nRumus [[probability density function]] nyaeta \n:\np_k(x) = \\frac{(1/2)^{k/2}}{\\Gamma(k/2)} x^{k/2 - 1} e^{-x/2} \\quad \\mbox{ for }x > 0\n\njeung \'\'p\'\'\'\'k\'\'(\'\'x\'\') = 0 keur \'\'x\'\'≤0. Di dieu Γ ngalambangkeun [[fungsi gamma]].\n\n====Pendekatan normal====\n\nLamun X\\sim\\chi^2_k, saterusna k nuju ka takterhingga, sebaran X nuju ka normal. Sanajan kitu, kacenderunganna lalaunan (skewness nyaeta 8/k jeung kurtosis nyaeta 12/k) sarta dua transpormasi umumna diperhatoskeun, unggal pendekatan normal leuwih gancang tinimbang X sorangan:\n\nFisher nembongkeun yen \\sqrt{2X} ngadeukeutan sebaran normal nu mibanda mean \\sqrt{2k-1} jeung unit varian.\n\nWilson and Hilferty dina taun [[1931]] nembongkeun yen \\sqrt[3]{X/k} nyaeta pendekatan sebaran normal nu mibanda mean 1-2/(9k) jeung varian 2/(9k).\n\n\n[[Nilai ekspektasi]] tina variabel random ngabogaan sebaran chi-kuadrat nu mibanda \'\'k\'\' tingkat kabebasan \'\'k\'\' jeung [[varian]] nyaeta 2\'\'k\'\'. Median dina ieu kaayaan dideukeutan ku\n:\nk-\\frac{2}{3}+\\frac{4}{27k}-\\frac{8}{729k^2}.\n\n\n\nCatetan yen 2 tingkat kabebasan nuju kana [[sebaran eksponensial]].\n\nSebaran chi-kuadrat dina kasus husus nyaéta [[sebaran gamma]].\n\nTempo [[Teorema Cochran]].\n\n[[Category:Probability distributions]]\n\n[[en:Chi-square distribution]] [[sv:chitvåfördelning]] [[it:variabile casuale Chi Quadrato]][[de:Chi-Quadrat-Verteilung]]','',13,'Budhi','20041224211203','',0,0,1,0,0.41027767696,'20041224211203','79958775788796'); INSERT INTO cur VALUES (1172,0,'Teorema_Cochran','[[Category:Statistics]]\n[[Category:Theorems]]\nDina [[statistik]], \'\'\'teorema Cochran\'\'\' digunakeun dina [[analisa varian]].\n\nAnggap \'\'U\'\'1, ..., \'\'U\'\'\'\'n\'\' ngarupakeun standar [[variabel random]] [[statistical independence|bebas]] nu [[sebaran normal|kasebar normal]], sarta dina bentuk identitas\n\n:\n\\sum_{i=1}^n U_i^2=Q_1+\\cdots + Q_k\n\n\nbisa dituliskeun yen unggal \'\'Q\'\'\'\'i\'\' nyaeta jumlah kuadrat kombinasi liniér tina \'\'U\'\'. Mangka lamun\n\n:\nr_i+\\cdots +r_k=n\n\n\nnumana \'\'r\'\'\'\'i\'\' ngarupakeun [[rank|rangking]] tina \'\'Q\'\'\'\'i\'\', teorema Cochran nangtukeun yen \'\'Q\'\'\'\'i\'\' bebas sarta \'\'Q\'\'\'\'i\'\' ngabogaan [[sebaran chi-kuadrat]] nu mibanda [[tingkat kabebasan]] \'\'r\'\'\'\'i\'\'.\n\nTeorema Cochran ngarupakeun konversi [[Fisher\'s theorem|teorema Fisher]].\n\n===Conto===\n \nLamun \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun variabel random bebas nu kasebar normal mibanda mean μ sarta simpangan baku σ mangka\n\n:U_i=(X_i-\\mu)/\\sigma\n\nngarupakeun standar normal keur unggal \'\'i\'\'.\n\nIeu mungkin keur nulis\n\n:\n\\sum U_i^2=\\sum\\left(\\frac{X_i-\\overline{X}}{\\sigma}\\right)^2\n+ n\\left(\\frac{\\overline{X}-\\mu}{\\sigma}\\right)^2\n\n\n(didieu, jumlahna ti 1 nepi ka \'\'n\'\', dumasar kana observasi).\nKeur nempo ieu identitas, kalikeun ku \\sigma sarta catet yen\n\n:\n\\sum(X_i-\\mu)^2=\n\\sum(X_i-\\overline{X}+\\overline{X}-\\mu)^2\n\n\nsarta legaan keur manggihkeun \n\n:\n\\sum(X_i-\\overline{X})^2+\\sum(\\overline{X}-\\mu)^2+\n2\\sum(X_i-\\overline{X})(\\overline{X}-\\mu).\n\n\nWatesan katilu sarua jeung nol sabab ieu angger kana waktu\n\n:\\sum(\\overline{X}-X_i),\n\nsarta watesan kadua ngan watesan \'\'n\'\' identik nu ditambahkeun babarengan.\n\nKombinasi di luhur ngahasilkeun (sarta dibagi ku σ2), urang mibanda:\n\n:\n\\sum\\left(\\frac{X_i-\\mu}{\\sigma}\\right)^2=\n\\sum\\left(\\frac{X_i-\\overline{X}}{\\sigma}\\right)^2\n+n\\left(\\frac{\\overline{X}-\\mu}{\\sigma}\\right)^2\n=Q_1+Q_2.\n\n\nAyeuna rengking \'\'Q\'\'2 ngan 1 (ieu ngarupakeun kuadrat tina hiji kombinasi linier variabel normal standar). Rengking \'\'Q\'\'1 bisa ditembongkuen jadi \'\'n\'\' − 1, sarta kondisi teorema Cochran kapanggih.\n\nTeorema Cochran netepkeun yen \'\'Q\'\'1 and \'\'Q\'\'2 ngarupakeun bebas, mibanda sebaran chi-kuadrat \'\'n\'\' − 1 sarta 1 tingkat kabebasan.\n\nIeu nembongkeun yen sampel mean sarta sampel varian bebas; sarta\n\n:\n(\\overline{X}-\\mu)^2\\sim \\frac{\\sigma^2}{n}\\chi^2_1.\n\nKeur \'\'estimasi\'\' varian &sigma2, hiji estimator nu biasa digunakeun nyaeta \n\n:\n\\hat{\\sigma^2}=\n\\frac{1}{n}\\sum\\left(\nX_i-\\overline{X}\\right)^2 .\n\nTeorema Cochran nembongkeun yen\n\n:\n\\hat{\\sigma^2}\\sim\n\\frac{\\sigma^2}{n}\\chi^2_{n-1}\n\n\nnu nembongkeun yen nilai ekspektasi \\hat{\\sigma}^2 nyaeta σ2\'\'n\'\'/(\'\'n\'\' − 1).\n\nDua sebaran ieu ngarupakeun \'\'proporsi\'\' kana varian sabenerne tapi teu dipikanyaho σ2; mangka ieu rasio ngarupakeun σ2 bebas sabab duana bebas, mangka urang miboga\n\n:\n\\frac{\\left(\\overline{X}-\\mu\\right)^2}\n{\\frac{1}{n}\\sum\\left(X_i-\\overline{X}\\right)^2}\\sim\nF_{1,n}\n\n\nnumana \'\'F\'\'1,\'\'n\'\' ngarupakeun [[sebaran-F]] nu mibanda 1 sarta \'\'n\'\' tingkat kabebasan (tempo oge [[sebaran-t student]]).','/* Conto */',13,'Budhi','20040917063942','',0,0,0,0,0.940819234094,'20040917064007','79959082936057'); INSERT INTO cur VALUES (1173,0,'Skewness','Dina [[probability theory]] jeung [[statistik]], \'\'\'skewness\'\'\' nyaeta ukuran kateu-simetrian [[probability distribution]] tina nilai-[[real number|real]] [[random variable]]. Sacara kasar bisa disebutkeun, sebaran mibanda \'\'skew\'\' positip lamun nilai panjang \'\'tail\'\' positip sarta skew negatip lamun nilai panjang \'\'tail\'\' negatip.\n\nSkewness, [[standardized moment]] nu katilu, diartikeun ku μ3 / σ3, numana μ3 ngarupakeun [[moment about the mean]] nu katilu sarta σ ngarupakeun [[simpangan baku]]. \'\'Skewness\'\' tina random variable \'\'X\'\' kadangkala ngalambangkeun \'\'Skew\'\'[\'\'X\'\'].\n\nKeur nilai sampel \'\'N\'\' sampel \'\'skewness\'\' nyaeta Σ\'\'i\'\'(\'\'x\'\'\'\'i\'\' − μ)3 / \'\'N\'\'σ3, where \'\'x\'\'\'\'i\'\' ngarupakeun nilai \'\'i\'\'th jeung μ ngarupakeun [[mean]].\n\nLamun \'\'Y\'\' nyaeta jumlah \'\'n\'\' [[statistical independence|independent]] variabel random, dina distribusi nu sarua salaku \'\'X\'\', saterusna ditempokeun yen \'\'Skew\'\' [\'\'Y\'\'] = Skew[\'\'X\'\'] / √\'\'n\'\'.\n\nSampel nu asalna tina populasi, persamaan keur populasi \'\'skewness\'\' nyaeta [[biased estimator]] tina populasi \'\'skewness\'\'. [[Unbiased estimator]] \'\'skewness\'\' nyaeta \n\n: \\mbox{Skew} = \\frac{n}{(n-1)(n-2)}\n\\sum_{i=1}^N \\left( \\frac{x_i - \\bar{x}}{\\sigma} \\right)^3\n\n\nnumana σ ngarupakeun sample simpangan baku sarta μ ngarupakeun sampel mean.\n\nTempo oge: [[mean]], [[varian]], [[kurtosis]], [[cumulant]].\n\n[[de:Schiefe]]','',13,'Budhi','20040907111445','',0,0,0,0,0.317191886398,'20040907111445','79959092888554'); INSERT INTO cur VALUES (1174,0,'Kurtosis','Dina [[probability theory]] jeung [[statistik]], \'\'\'kurtosis\'\'\' nyaeta ukuran \'\'posisi puncak\'\' tina [[probability distribution]] nilai-[[real number|real]] [[random variable]]. \n\n[[Standardized moment]] kaopat diartikeun salaku μ4 / σ4, numana μ4 ngarupakeun [[momen mean]] kaopat jeung σ nyaeta [[simpangan baku]]. Hal ieu kadangkala dipake keur ngartikeun kurtosis dina pagawean samemehna, tapi teu dipake dina definisi di dieu.\n\nKurtosis leuwih ilahar diartikeun ku μ4 / σ4 − 3. Minus 3 di tungtung persamaan eta nerangkeun yen koreksi dijieun keur ngajadikeun kurtosis sebaran normal sarua jeung nol. Alesan sejenna nembongkeun yen kurtosis ngarupakeun jumlah tina variabel random. Lamun \'\'Y\'\' jumlah tina \'\'n\'\' [[statistical independence|independent]] variabel random, sakabeh sebaranna sarua nyaeta \'\'X\'\', saterusna Kurt[\'\'Y\'\'] = Kurt[\'\'X\'\'] / \'\'n\'\', sabalikna ieu rumus bakal leuwih pajuriwet lamun kurtosis dihartikeun ku μ4 / σ4.\n\n[[Sebaran normal]] ngabogaan kurtosis sarua jeung nol (sebaran nu mibanda nilai kurtosis sarua jeung nol disebut \'\'mesokurtic\'\'). Sebaran nu mibanda kurtosis positip disebut \'\'leptokurtic\'\', sarta lamun negatif disebut \'\'platykurtic\'\'.\n\nKeur nilai sampel \'\'N\'\', \'\'\'sampel kurtosis\'\'\' nyaeta Σ\'\'i\'\'(\'\'x\'\'\'\'i\'\'  −  μ)4 / \'\'N\'\'σ4 − 3, numana \'\'x\'\'\'\'i\'\' nyaeta nilai \'\'i\'\'th jeung μ nyaeta [[mean]].\n\nDina kaayaan bagean-susunan sampel tina populasi, sampel kurtosis di luhur ngarupakeun [[biased estimator]] ti populasi kurtosis. [[Unbiased estimator]] tina populasi kurtosis nyaeta\n\n:\n\\mbox{Kurt} = \\frac{n(n+1)}{(n-1)(n-2)(n-3)}\n\\sum_{i=1}^N \\left( \\frac{x_i - \\bar{x}}{\\sigma} \\right)^4\n- \\frac{3(n-1)^2}{(n-2)(n-3)}\n\n\nnumana σ nyaeta simpangan baku sampel jeung μ nyaeta sampel mean.\n\nTempo oge: [[mean]], [[varian]], [[skewness]].\n\n[[de:Wölbung]]','',13,'Budhi','20040907111607','',0,0,0,0,0.266427014613,'20040907111607','79959092888392'); INSERT INTO cur VALUES (1175,0,'Cumulative_distribution_function','[[pl:dystrybuanta]]\n\nDina [[matematik]], \'\'\'fungsi distribusi kumulatip\'\'\' (disingkat \'\'\'cdf\'\'\') ngajelaskeun probability distribution ti sakabeh nilai-[[Real_number|real]] [[variabel acak]], \'\'X\'\'. Keur satiap real number \'\'x\'\', cdf dirumuskeun ku\n\n:F(x) = \\operatorname{P}(X\\leq x),\n\nthe [[probability]] that the variable \'\'X\'\' takes on a value less than or equal to \'\'x\'\'.\nThe probability that \'\'X\'\' lies in the [[interval (mathematics)|interval]] (\'\'a\'\', \'\'b\'\') is therefore \'\'F\'\'(\'\'b\'\') − \'\'F\'\'(\'\'a\'\') if \'\'a\'\' ≤ \'\'b\'\'. It is conventional to use a capital \'\'F\'\' for a cumulative distribution function, in contrast to the lower-case \'\'f\'\' used for [[probability density function]]s and probability mass functions.\n\nNote that in the definition above, the \"less or equal\" sign, \'≤\' could be replaced with \"strictly less\" \'<\'. This would yield a different function, but either of the two functions can be readily derived from the other. One could even use \"greater\" sign there (changing cdf properties even more). The only thing to remember is to stick to either definition as mixing them will lead to incorrect results. In English-speaking countries the convention that uses the weak inequality (≤) rather than the strict inequality (<) is nearly always used.\n\n== Conto ==\n\nSalaku conto, anggap \'\'X\'\' kasebar seragam dina [[unit interval]] [0, 1].\nMangka cdf nyaeta\n\n:\'\'F\'\'(\'\'x\'\') = 0, lamun \'\'x\'\' < 0;\n:\'\'F\'\'(\'\'x\'\') = \'\'x\'\', lamun 0 ≤ \'\'x\'\' ≤ 1;\n:\'\'F\'\'(\'\'x\'\') = 1, lamun \'\'x\'\' > 1.\n\nContona sejenna, anggap \'\'X\'\' ngan nilai 0 jeung 1, proababiliti sarua.\nMangka cdf nyaeta\n\n:\'\'F\'\'(\'\'x\'\') = 0, lamun \'\'x\'\' < 0;\n:\'\'F\'\'(\'\'x\'\') = 1/2, lamun 0 ≤ \'\'x\'\' < 1;\n:\'\'F\'\'(\'\'x\'\') = 1, lamun \'\'x\'\' ≥ 1.\n\n== Sipat ==\n\nEvery cumulative distribution function \'\'F\'\' is [[monotone increasing]] and [[continuous]] from the right. Furthermore, we have [[limit (mathematics)|lim]]\'\'x\'\' → −∞ \'\'F\'\'(\'\'x\'\') = 0 and lim\'\'x\'\' → +∞ \'\'F\'\'(\'\'x\'\') = 1. Every function with these four properties is a cdf.\n\nIf \'\'X\'\' is a [[discrete random variable]], then it attains values \'\'x\'\'1, \'\'x\'\'2, ... with probability \'\'p\'\'1, \'\'p\'\'2 etc., and the cdf of \'\'X\'\' will be discontinuous at the points \'\'x\'\'\'\'i\'\' and constant in between.\n\nIf the cdf \'\'F\'\' of \'\'X\'\' is [[continuous]], then \'\'X\'\' is a [[continuous random variable]]; if furthermore \'\'F\'\' is [[absolute continuity|absolutely continuous]], then there exists a [[Lebesgue integral|Lebesgue-integrable]] function \'\'f\'\'(\'\'x\'\') such that \n\n:F(b)-F(a) = \\operatorname{P}(a\\leq X\\leq b) = \\int_a^b f(x)\\,dx\n\nfor all real numbers \'\'a\'\' and \'\'b\'\'. (The first of the two equalities displayed above would not be correct in general if we had not said that the distribution is continuous. Continuity of the distribution implies that P(\'\'X\'\' = \'\'a\'\') = P(\'\'X\'\' = \'\'b\'\') = 0, so the difference between \"<\" and \"\\leq\" ceases to be important in this context.) The function \'\'f\'\' is equal to the [[derivative]] of \'\'F\'\' [[almost everywhere]], and it is called the [[probability density function]] of the distribution of \'\'X\'\'.\n\nThe [[Kolmogorov-Smirnov test]] is based on cumulative distribution functions and can be used to test to see whether two empirical distributions are different or whether an empirical distribution is different from an ideal distribution. The closely related [[Kuiper\'s test]] (pronounced in Dutch the way an Cowper might be pronounced in English) is useful if the domain of the distribution is cyclic as in day of the week. For instance we might use Kuiper\'s test to see if the number of tornadoes varies during the year or if sales of a product vary by day of the week or day of the month.\n\n==Tempo oge==\n\n[[Statistik deskriptif]], [[Probability distribution]]','/* Tempo oge */',13,'Budhi','20041225132013','',0,0,1,0,0.059205166557,'20041225132013','79958774867986'); INSERT INTO cur VALUES (1176,0,'Fungsi_béta_teu_lengkep','[[Category:Analisis matematik]]\nDina [[matematik]], \'\'\'fungsi béta teu lengkep\'\'\' dihartikeun dina bentuk integral,\n\n: I_x(a,b) = \\frac{B_x(a,b)}{B(a,b)} \n = \\frac{1}{B(a,b)} \\int_0^x t^{a-1}\\,(1-t)^{b-1}\\,dt \n\nmibanda \'\'a\'\' > 0 jeung \'\'b\'\' > 0.\n\n==Sifat==\n\n: I_0(a,b) = 0 \\, \n: I_1(a,b) = 1 \\, \n\n\'\'(Loba sifat séjénna nu bisa dituliskeun di dieu).\'\'\n\n==Sumber séjén==\n\n* \'\'\'M. Abramowitz and I. A. Stegun\'\'\', eds. (1972) \'\'Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables\'\'. New York: Dover. (Tempo bab 6.6 jeung 26.5)\n\n* \'\'\'W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling\'\'\'. (1988) \'\'Numerical Recipes in C. Cambridge\'\', UK: Cambridge University Press. (Tempo bab 6.3)','',3,'Kandar','20041221111907','',0,0,0,0,0.672175180946,'20041221111907','79958778888092'); INSERT INTO cur VALUES (1177,0,'Sebaran-F','Dina [[statistik]], \'\'\'sebaran\'\'\'-\'\'F\'\' nyaeta [[probability distribution]] tina variabel random dina bentuk\n\n:\\frac{U_1/d_1}{U_2/d_2}\n\nnumana\n\n*\'\'U\'\'\'\'1\'\' jeung \'\'U\'\'2 ngabogaan [[sebaran chi-kuadrat]] nu mibanda \'\'d\'\'\'\'1\'\' jeung \'\'d\'\'2 tingkat kapercayaan sarta\n\n*\'\'U\'\'1 jeung \'\'U\'\'2 variabel ngarupakeun [[statistical independence|bebas]] (tempo [[teorema Cochran]] keur conto pamakeanna).\n\nSebaran-\'\'F\'\' sering dipake salaku sebaran null dina tes statistik, husuna dina [[likelihood-ratio test]], diharapkeun leuwih hade dina [[analisa varian]]; tempo [[F-test]].\n\nLamun \'\'d\'\'\'\'2\'\' > 2, saterusna mean \'\'d\'\'2/(\'\'d\'\'2 − 2) jeung lamun \'\'d\'\'\'\'2\'\' > 4 maka varian dirumuskeun ku\n:\n\\frac{2d_2^2(d_1+d_2-2)}{d_1(d_2-2)^2(d_2-4)}.\n\n\nSebaran-F salawasna aya dina rentang nol nepi ka \"takterhingga\"; lamun \'\'d\'\'\'\'1\'\' > 2, ngarupakeun [[unimodal]] mibanda [[mode]]\n\n:\n\\frac{d_1-2}{d_1}\\cdot\\frac{d_2}{d_2+1}\n\n\n==Tumbu kaluar==\n*[http://www.itl.nist.gov/div898/handbook/eda/section3/eda3673.htm Table of critical values of the \'\'F\'\'-distribution]\n*[http://home.clara.net/sisa/signhlp.htm Online significance testing with the F-distribution]\n\n[[Category:Probability distributions]]','',13,'Budhi','20040917064443','',0,0,0,0,0.183045055337,'20040917064443','79959082935556'); INSERT INTO cur VALUES (1178,0,'Real_number','#REDIRECT [[Real Number]]','',13,'Budhi','20040817043638','',0,1,0,1,0.137032430217,'20040817043638','79959182956361'); INSERT INTO cur VALUES (1179,0,'Standardized_moment','Dina [[probability theory]] jeung [[statistik]], \'\'k\'\'th\n\'\'\'standardized moment\'\'\' tina [[probability distribution]] nyaeta μkk, numana μk ngarupakeun \'\'k\'\'th [[momen mean]] jeung σ ngarupakeun [[simpangan baku]].\n\nStandardized moments katilu jeung kaopat digunakeun keur ngartikeun [[skewness]] jeung [[kurtosis]].\n\nInformasi saterusna ngeunaan \"momen\", bisa konsultasi ka Wolfram Research\'s [[http://mathworld.wolfram.com/topics/Moments.html mathworld website]].\n\n[[de:Moment (Statistik)]]','',13,'Budhi','20040817071630','',0,0,0,0,0.834616846328,'20040817071630','79959182928369'); INSERT INTO cur VALUES (1180,0,'Momen_mean','\'\'\'Momen mean\'\'\' \'\'k\'\'th (atawa \'\'k\'\'th \'\'\'central moment\'\'\') nilai-real [[random variable]] \'\'X\'\' nyaeta kuantitas E[(\'\'X\'\' − E[\'\'X\'\'])\'\'k\'\'], numana E ngarupakeun [[nilai ekspektasi|operator ekspektasi]]. Sababaraha variabel random teu ngabogaan [[mean]], dina kasus momen mean teu bisa diartikeun. Momen mean \'\'k\'\'th salawasna dilambangkeun ku μ\'\'k\'\'. Keur continuous univariate [[probability distribution]] nu mibanda [[probability density function]] \'\'f\'\'(\'\'x\'\') momen mean μ nyaeta\n\n:\n\\mu_k\n= \\left\\langle ( x - \\langle x \\rangle )^k \\right\\rangle\n= \\int_{-\\infty}^{+\\infty} (x - \\mu)^k f(x)\\,dx.\n\n\nKadangkala kacida gampangna keur koversi momen asli ka momen mean. Persamaan umum keur konversi momen asli orde-nth ka momen mean nyaeta \n\n:\n\\mu_n = \\sum_{j=0}^n {n \\choose j} (-1) ^{n-j} \\mu\'_j m^{n-j},\n\n\nnumana m ngarupakeun mean sebaran, sarta momen asli dirumuskeun ku \n\n:\n\\mu\'_j = \\int_{-\\infty}^{+\\infty} x^n f(x)\\,dx.\n\n\nMomen mean kahiji nyaeta nol. Momen mean kadua disebut [[varian]], biasa dilambangkeun ku σ2, numana σ ngawakilan [[simpangan baku]]. Momen mean katilu jeung kaopat ngartikeun [[standardized moment]] sacara \"berurutan\" dipake keur ngartikeun [[skewness]] jeung [[kurtosis]].\n\n==Tempo oge==\n\n[[moment (matematik)]], [[cumulant]]','',13,'Budhi','20040917030320','',0,0,0,0,0.271597601134,'20040917030320','79959082969679'); INSERT INTO cur VALUES (1181,0,'Biased_estimator','#REDIRECT [[Bias (statistics)]]','',13,'Budhi','20040817045223','',0,1,0,1,0.208975169439,'20040817045223','79959182954776'); INSERT INTO cur VALUES (1182,0,'Cumulant','== Cumulants sebaran probabiliti ==\n\nDina [[probability theory]] jeung [[statistik]], \'\'\'cumulants\'\'\' κ\'\'n\'\' ti[[probability distribution]] dirumuskeun ku\n\n:E\\left(e^{tX}\\right)=\\exp\\left(\\sum_{n=1}^\\infty\\kappa_n t^n/n!\\right)\n\nnumana \'\'X\'\' nyaeta unggal [[variabel random]] sebaran probabiliti is the one whose cumulants are taken. In other words, κ\'\'n\'\'/\'\'n\'\'! is the \'\'n\'\'th coefficient in the [[power series]] representation of the [[logarithm]] of the [[moment-generating function]]. The logarithm of the moment-generating function is therefore called the \'\'\'cumulant-generating function\'\'\'.\n\nThe \"problem of cumulants\" attempts to recover a probability distribution from its sequence of cumulants. In some cases no solution exists; in some cases a unique solution exists; in some cases more than one solution exists.\n\n==Some properties of cumulants==\n\n===Invariance and equivariance===\n\nThe first cumulant is shift-equivariant; all of the others are shift-invariant. To state this less tersely, denote by κ\'\'n\'\'(\'\'X\'\') the \'\'n\'\'th cumulant of the probability distribution of the random variable \'\'X\'\'. The statement is that if \'\'c\'\' is constant then κ1(\'\'X\'\' + \'\'c\'\') = κ1(\'\'X\'\') + \'\'c\'\' and κ\'\'n\'\'(\'\'X\'\' + \'\'c\'\') = κ\'\'n\'\'(\'\'X\'\') for \'\'n\'\'≥ 2, i.e., \'\'c\'\' is added to the first cumulant, but all higher cumulants are unchanged.\n\n===Homogeneity===\n\nThe \'\'n\'\'th cumulant is homogeneous of degree \'\'n\'\', i.e. if \'\'c\'\' is any constant, then\n\n:\\kappa_n(cX)=c^n\\kappa_n(X).\n\n===Additivity===\n\nIf \'\'X\'\' and \'\'Y\'\' are [[statistical independence | independent]] random variables then κ\'\'n\'\'(\'\'X\'\' + \'\'Y\'\') = κ\'\'n\'\'(\'\'X\'\') + κ\'\'n\'\'(\'\'Y\'\').\n\n===Cumulants and moments===\n\nThe cumulants are related to the [[moment (mathematics)|moments]] by the following recursion formula:\n\n:\\kappa_n=\\mu\'_n-\\sum_{k=1}^{n-1}{n-1 \\choose k-1}\\kappa_k \\mu_{n-k}\'.\n\nThe \'\'n\'\'th [[moment (mathematics)|moment]] μ′\'\'n\'\' is an \'\'n\'\'th-degree polynomial in the first \'\'n\'\' cumulants, thus:\n\n:\\mu\'_1=\\kappa_1\n:\\mu\'_2=\\kappa_2+\\kappa_1^2\n:\\mu\'_3=\\kappa_3+3\\kappa_2\\kappa_1+\\kappa_1^3\n:\\mu\'_4\n=\\kappa_4+4\\kappa_3\\kappa_1+3\\kappa_2^2+6\\kappa_2\\kappa_1^2+\\kappa_1^4\n:\\mu\'_5=\\kappa_5+5\\kappa_4\\kappa_1+10\\kappa_3\\kappa_2\n+10\\kappa_3\\kappa_1^2+15\\kappa_2^2\\kappa_1\n+10\\kappa_2\\kappa_1^3+\\kappa_1^5\n:\\mu\'_6=\\kappa_6+6\\kappa_5\\kappa_1+15\\kappa_4\\kappa_2+15\\kappa_4\\kappa_1^2\n+10\\kappa_3^2+60\\kappa_3\\kappa_2\\kappa_1+20\\kappa_3\\kappa_1^3+15\\kappa_2^3\n+45\\kappa_2^2\\kappa_1^2+15\\kappa_2\\kappa_1^4+\\kappa_1^6\n\nThe \"prime\" distinguishes the moments μ′\'\'n\'\' from the [[moment about the mean|central moments]] μ\'\'n\'\'. To express the \'\'central\'\' moments as functions of the cumulants, just drop from these polynomials all terms in which κ1 appears as a factor.\n\nThe coefficients are precisely those that occur in [[Faà di Bruno\'s formula]].\n\n===Cumulants and set-partitions===\n\nThese polynomials have a remarkable [[combinatorics|combinatorial]] interpretation: the coefficients count certain partitions of sets. A general form of these polynomials is\n\n:\\mu\'_n=\\sum_{\\pi}\\prod_{B\\in\\pi}\\kappa_{\\left|B\\right|}\n\nwhere\n\n*π runs through the list of all partitions of a set of size \'\'n\'\';\n\n*\"\'\'B\'\' ∈ π\" means \'\'B\'\' is one of the \"blocks\" into which the set is partitioned; and\n\n*|\'\'B\'\'| is the size of the set \'\'B\'\'.\n\nThus each monomial is a constant times a product of cumulants in which the sum of the indices is \'\'n\'\' (e.g., in the term κ3 κ22 κ1, the sum of the indices is 3 + 2 + 2 + 1 = 8; this appears in the polynomial that expresses the 8th moment as a function of the first eight cumulants). A partition of the integer \'\'n\'\' corresponds to each term. The \'\'coefficient\'\' in each term is the number of partitions of a set of \'\'n\'\' members that collapse to that partition of the integer \'\'n\'\' when the members of the set become indistinguishable.\n\n==Cumulants of particular probability distributions==\n\nCumulant [[sebaran normal]] mibanda [[nilai ekspektasi]] μ sarta [[varian]] σ2 ngarupakeun κ1 = μ, κ2 = σ2, sarta κ\'\'n\'\' = 0 keur \'\'n\'\' > 2.\n\nSakabeh cumulant [[sebaran Poisson]] sarua jeung nilai ekspektasi.\n\nA distribution with arbitrary given cumulants κ\'\'n\'\' can be approximated through the [[Gram-Charlier series|Gram-Charlier]] or [[Edgeworth series]].\n\n==Joint cumulants==\n\nThe \'\'\'joint cumulant\'\'\' of several random variables \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' is\n\n:\\kappa(X_1,\\dots,X_n)\n=\\sum_\\pi\\prod_{B\\in\\pi}(|B|-1)!(-1)^{|B|-1}E\\left(\\prod_{i\\in B}X_i\\right)\n\nwhere π runs through the list of all partitions of { 1, ..., \'\'n\'\' }, and \'\'B\'\' runs through the list of all block of the partition π. For example,\n\n:\\kappa(X,Y,Z)=E(XYZ)-E(XY)E(Z)-E(XZ)E(Y)-E(YZ)E(X)+2E(X)E(Y)E(Z).\n\nThe joint cumulant of just one random variable is its expected value, and that of two random variables is their [[kovarian]]. If some of the random variables are idependent of all of the others, then the joint cumulant is zero. If all \'\'n\'\' random variables are the same, then the joint cumulant is the \'\'n\'\'th ordinary cumulant.\n\nThe combinatorial meaning of the expression of moments in terms of cumulants is easier to understand than that of cumulants in terms of moments:\n\n:E(X_1\\cdots X_n)=\\sum_\\pi\\prod_{B\\in\\pi}\\kappa(X_B)\n\nwhere κ(\'\'X\'\'\'\'B\'\') is the joint cumulant of those among the random variables \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' whose indices are included in the block \'\'B\'\'. For example:\n\n:E(XYZ)=\\kappa(X,Y,Z)+\\kappa(X,Y)\\kappa(Z)+\\kappa(X,Z)\\kappa(Y)\n+\\kappa(Y,Z)\\kappa(X)+\\kappa(X)\\kappa(Y)\\kappa(Z).\n\n===Conditional cumulants===\n\nThe [[law of total expectation]] and the [[law of total variance]] generalize naturally to conditional cumulants. The case \'\'n\'\' = 3, expressed in the language of (central) [[moment (mathematics)|moments]] rather than that of cumulants, says\n\n:\\mu_3(X)=E(\\mu_3(X\\mid Y))+\\mu_3(E(X\\mid Y))\n+3\\,\\operatorname{cov}(E(X\\mid Y),\\operatorname{var}(X\\mid Y)).\n\nThe general result stated below first appeared in 1969 in \'\'The Calculation of Cumulants via Conditioning\'\' by David R. Brillinger in volume 21 of \'\'Annals of the Institute of Statistical Mathematics\'\', pages 215-218.\n\nIn general, we have\n\n:\\kappa(X_1,\\dots,X_n)=\\sum_\\pi \\kappa(\\kappa(X_{\\pi_1}\\mid Y),\\dots,\\kappa(X_{\\pi_b}\\mid Y))\n\nwhere\n\n* the sum is over all [[partition of a set|partitions]] π of the set { 1, ..., \'\'n\'\' } of indices, and\n\n* π1, ..., πb are all of the \"blocks\" of the partition π; the expression κ(\'\'X\'\'π\'\'k\'\') indicates that the joint cumulant of the random variables whose indices are in that block of the partition.\n\n==History==\n\nCumulants were first introduced by the Danish astronomer, actuary, mathematician, and statistician Thorvald N. Thiele (1838 - 1910) in 1889. Thiele called them \'\'half-invariants\'\'. They were first called \'\'cumulants\'\' in a 1931 paper, \'\'The derivation of the pattern formulae of two-way partitions from those of simpler patterns\'\', Proceedings of the London Mathematical Society, Series 2, v. 33, pp. 195-208, by the great statistical geneticist Sir [[Ronald Fisher]] and the statistician [[John Wishart]], eponym of the [[Sebaran Wishart]]. The historian Stephen Stigler has said that the name \'\'cumulant\'\' was suggested to Fisher in a letter from [[Harold Hotelling]]. In another paper published in 1929, Fisher had called them \'\'cumulative moment functions\'\'.\n\n== \"Formal\" cumulants ==\n\nMore generally, the cumulants of a sequence { \'\'m\'\'\'\'n\'\' : \'\'n\'\' = 1, 2, 3, ... }, not necessarily the moments of any probability distribution, are given by\n\n:1+\\sum_{n=1}^\\infty m_n t^n/n!=\\exp\\left(\\sum_{n=1}^\\infty\\kappa_n t^n/n!\\right)\n\nwhere the values of κ\'\'n\'\' for \'\'n\'\' = 1, 2, 3, ... are found \"formally\", i.e., by algebra alone, in disregard of questions of whether any series converges. All of the difficulties of the \"problem of cumulants\" are absent when one works \"formally\". The simplest example is that the second cumulant of a probability distribution must always be nonnegative, and is zero only if all of the higher cumulants are zero. \"Formal\" cumulants are subject to no such constraints.\n\n== One well-known example ==\n\nIn [[combinatorics]], the \'\'n\'\'th [[Bell numbers | Bell number]] is the number of partitions of a set of size \'\'n\'\'. All of the cumulants of the sequence of Bell numbers are equal to 1. The Bell numbers are the moments of the Poisson distribution with [[nilai ekspektasi]] 1.\n\n== Cumulants of a polynomial sequence of binomial type ==\n\nFor any sequence { κ\'\'n\'\' : \'\'n\'\' = 1, 2, 3, ... } of [[scalar]]s in a [[field (mathematics)|field]] of characteristic zero, being considered formal cumulants, there is a corresponding sequence { μ ′ : \'\'n\'\' = 1, 2, 3, ... } of formal moments, given by the polynomials above. For those polynomials, construct a [[polynomial sequence]] in the following way. Out the polynomial\n\n:\\begin{matrix}\\mu\'_6= &\n\\kappa_6+6\\kappa_5\\kappa_1+15\\kappa_4\\kappa_2+15\\kappa_4\\kappa_1^2\n+10\\kappa_3^2+60\\kappa_3\\kappa_2\\kappa_1 \\\\ \\\\\n& +20\\kappa_3\\kappa_1^3+15\\kappa_2^3\n+45\\kappa_2^2\\kappa_1^2+15\\kappa_2\\kappa_1^4+\\kappa_1^6\\end{matrix}\n\nmake a new polynomial in these plus one additional variable \'\'x\'\':\n\n:\\begin{matrix}p_6(x)= &\n(\\kappa_6)\\,x+(6\\kappa_5\\kappa_1+15\\kappa_4\\kappa_2+10\\kappa_3^2)\\,x^2\n+(15\\kappa_4\\kappa_1^2+60\\kappa_3\\kappa_2\\kappa_1+15\\kappa_2^3)\\,x^3 \\\\ \\\\\n& +(45\\kappa_2^2\\kappa_1^2)\\,x^4+(15\\kappa_2\\kappa_1^4)\\,x^5 +(\\kappa_1^6)\\,x^6\\end{matrix}\n\n... and generalize the pattern. The pattern is that the numbers of blocks in the aforementioned partitions are the exponents on \'\'x\'\'. Each coefficient is a polynomial in the cumulants; these are the [[Bell polynomials]], named after [[Eric Temple Bell]].\n\nThis sequence of polynomials is of [[binomial type]]. In fact, no other sequences of binomial type exist; every polynomial sequence of binomial type is completely determined by its sequence of formal cumulants.\n\n[[Category:Probability theory]]\n[[Category:Statistics]]','/* History */',13,'Budhi','20040918222451','',0,0,0,0,0.786146653251,'20040918222451','79959081777548'); INSERT INTO cur VALUES (1183,0,'Moment_about_the_mean','#REDIRECT [[Momen mean]]\n','Moment about the mean dipindahkeun ka Momen mean',13,'Budhi','20040817051352','',0,1,0,1,0.267251997503687,'20040817051352','79959182948647'); INSERT INTO cur VALUES (1184,0,'Tingkat_kabebasan','Frase \"tingkat kebebasan\" digunakeun dina 3 cabang elmu anu beda nyaeta: dina [[physics]] jeung [[physical chemistry]], dina [[mechanical engineering|mechanical]] jeung [[aeronautical engineering]], sarta dina [[statistik]]. Tiluannana dihubungkeun sacara sajarah jeung ngaliwatan [[matematik]] nyaeta konsep [[dimensionality]], sanajan tiluanana teu identik.\n\n==Physics and chemistry==\n\nIn physics and chemistry, each independent mode in which a particle or system may move or be oriented is one \'\'\'degree of freedom.\'\'\' For a roughly dumbell-shaped hydrogen molecule, three such modes would be rotation (twirling), translation (hurtling through space) and vibration (the two dumbbell \"balls\" bouncing together and apart). According to the [[Equipartition Theorem]] of [[thermodynamic]]s, in case of [[thermal equilibrium]] each degree of freedom in every particle of a system will contain the same energy on average (equal to kT, the [[temperature]] of the system multiplied by the fundamental [[Ludwig Boltzmann|Boltzmann]] constant). \nHowever, thermal equilibrium can only be reached among interacting particles, a process called [[thermalization]]. According to [[quantum mechanics]] and more specifically [[Werner Heisenberg|Heisenberg\'s]] [[uncertainty principle]], the amount of energy within any degree of freedom is never zero, but is always at least equal to the [[zero-point energy]] for that mode.\n\n==Engineering==\n\nIn mechanical and aeronautical engineering, \'\'\'degrees of freedom\'\'\' (DOF) describes flexibility of motion. A mechanism that has complete freedom of motion (even if only in a limited area, or envelope) has six degrees of freedom. Three modes are translation - the ability to move in each of three dimensions. Three are rotation, or the ability to change angle around three perpendicular axes.\n\nTo put it in simpler terms, each of the following is one degree of freedom: \n#Moving up and down ([[heave|heaving]]);\n#moving left and right ([[sway|swaying]]);\n#moving forward and back ([[surge|surging]]);\n#tilting up and down ([[flight dynamics|pitch]]ing);\n#turning left and right ([[flight dynamics|yaw]]ing);\n#tilting side to side ([[flight dynamics|roll]]ing).\n\nSee also: [[Euler angles]].\n\nA mechanism that can (for instance) be raised and lowered, which has a pivoting head that can tilt forward or back, left or right, can be described as having 3 degrees of freedom (colloquially, 3DOF).\n\n==Statistik==\n\nDina statistik, \'\'\'tingkat kabebasan\'\'\' nyaeta [[statistical parameter]] anu penting dina [[probability distribution]]. Contona dipake dina [[sebaran chi-kuadrat]], [[sebaran-F]], [[sebaran-t student]], jeung [[sebaran beta]]. Tempo [[Uji kuadrat-chi Pearson]] jeung [[analisa varian]] keur informasi saterusna.\n\nDina sebaran anu geus ilahar dipake, tingkat kabebasan ngan nyokot [[integer]] (umumna kurang ti hiji). Sacara matematik diidinan keur ngabagi-bagi tingkat kabebasan, sahingga meunang hasil itungan nu nyugemakeun. \n\n[[de:Freiheitsgrad]] [[ja:自由度]][[sl:prostostna stopnja]] [[sv:Frihetsgrader]]','/* Statistik */',13,'Budhi','20041224204349','',0,0,1,0,0.014458078432,'20041224204349','79958775795650'); INSERT INTO cur VALUES (1185,0,'F-distribution','#REDIRECT [[Sebaran-F]]\n','F-distribution dipindahkeun ka Sebaran-F',13,'Budhi','20040817052606','',0,1,0,1,0.697013591134002,'20040817052606','79959182947393'); INSERT INTO cur VALUES (1186,0,'Chi-square_distribution','#REDIRECT [[Sebaran chi-kuadrat]]','',13,'Budhi','20040908011220','',0,1,0,0,0.683311993892595,'20040908011220','79959091988779'); INSERT INTO cur VALUES (1187,0,'Algoritma','[[image:flowchart.png|frame|right|[[Flowchart|Diagram alir]] mindeng dipaké pikeun ngagambarkeun algoritma.]]\n\n\'\'\'Algoritma\'\'\' nyaéta susunan paréntah, nu jumlahna kawates, pikeun ngolah sababaraha paréntah nu, sakumpulan data asupanana, bakal ngahasilkeun sarupaning bentuk ahir nu bisa dipikawanoh; sabalikna ti [[heuristik]]. Konsép algoritma mindeng digambarkeun ku conto hiji [[recipe|resép]], although many algorithms are much more complex; algorithms often have steps that repeat ([[iteration|iterate]]) or require decisions (such as [[Boolean logic|logic]] or [[inequality|comparison]]) until the task is completed.\n\nDifferent algorithms may complete the same task with a different set of instructions in more or less time, space, or effort than others. For example, given two different recipes for making potato salad, one may have \'\'peel the potato\'\' before \'\'boil the potato\'\' while the other presents the steps in the reverse order, yet they both call for these steps to be repeated for all potatoes and end when the potato salad is ready to be eaten. \n\nCorrectly performing an algorithm will not solve a problem if the algorithm is flawed or not appropriate to the problem. For example, performing the potato salad algorithm will fail if there are no potatoes present, even if all the motions of preparing the salad are performed as if the potatoes were there.\n\nIn some countries, such as the USA, some algorithms can effectively be [[Patent|patented]] if an embodiment is possible (for example, a multiplication algorithm embodied in the arithmetic unit of a microprocessor). \n\n== Formalized algorithms ==\nAlgorithms are essential to the way [[computer]]s process information, because a [[computer program]] is essentially an algorithm that tells the computer what specific steps to perform (in what specific order) in order to carry out a\nspecified task, such as calculating employees’ paychecks or printing students’ report cards. Thus, an algorithm can be considered to be any sequence of operations which can be performed by a [[Turing-complete]] system.\n\nTypically, when an algorithm is associated with processing information, data is read from an input source or device, written to an output sink or device, and/or stored for further use. Stored data is regarded as part of the [[internal state]] of the entity performing the algorithm.\n\nFor any such computational process, the algorithm must be rigorously defined: specified in the way it applies in all possible circumstances that could arise. That is, any conditional steps must be systematically dealt with, case-by-case; the criteria for each case must be clear (and computable).\n\nBecause an algorithm is a precise list of precise steps, the order of computation will almost always be critical to the functioning of the algorithm. Instructions are usually assumed to be listed explicitly, and are described as starting \'from the top\' and going \'down to the bottom\', an idea that is described more formally by \'\'[[control flow|flow of control]]\'\'.\n\nSo far, this discussion of the formalisation of an algorithm has assumed the premises of [[imperative programming]]. This is the most common conception, and it attempts to describe a task in discrete, \'mechanical\' means. Unique to this conception of formalized algorithms is the [[assignment operation]], setting the value of a variable. It derives from the intuition of \'memory\' as a scratchpad. There is an example below of such an assignment. \n\nSee [[functional programming]] and [[logic programming]] for alternate conceptions of what constitutes an algorithm.\n\n== Ngalarapkeun algoritma ==\nAn \'\'\'algorithm\'\'\' is a method or procedure for carrying out a task (such as solving a problem in [[mathematics]], finding the freshest produce in a supermarket, or manipulating [[information]] in general).\n\nAlgorithms are sometimes implemented as [[computer program]]s but are more often implemented by other means, such as in a biological neural network (for example, the human brain implementing [[arithmetic]] or an insect relocating food), or in [[electric circuit]]s or in a mechanical device. \n\nThe [[analysis of algorithms|analysis and study of algorithms]] is one discipline of [[computer science]], and is often practiced abstractly (without the use of a specific [[programming language]] or other implementation). In this sense, it resembles other mathematical disciplines in that the analysis focuses on the underlying principles of the algorithm, and not on any particular implementation. One way to embody (or sometimes \'\'codify\'\') an algorithm is the writing of [[pseudocode]]. \n\nSome writers restrict the definition of \'\'algorithm\'\' to procedures that eventually finish. Others include procedures that could run forever without stopping, arguing that some entity may be required to carry out such permanent tasks. In the latter case, success can no longer be defined in terms of halting with a meaningful output. Instead, terms of success that allow for unbounded output sequences must be defined. For example, an algorithm that verifies if there are more zeros than ones in an infinite random binary sequence must run forever to be effective. If it is implemented correctly, however, the algorithm\'s output will be useful: for as long as it examines the sequence, the algorithm will give a positive response while the number of examined zeros outnumber the ones, and a negative response otherwise. Success for this algorithm could then be defined as eventually outputting only positive responses if there are actually more zeros than ones in the sequence, and in any other case outputting any mixture of positive and negative responses.\n\n== Conto ==\nDi dieu aya conto sederhana dina algoritma.\n\nBayangkeun anjeun mibanda wilangan random dina daptar nu teu kasortir. Tujuan ahirna keur manggihkeun wilangan panggedena tina eta daptar. Lengkah mimiti nyaeta kudu nempo kana sakabeh nilai nu aya dina deret. Lengkah saterusna nyaeta nempo kana eta nilai ngan sakali. Asupkeun kana itungan, algoritma basajan ngeunaan hal eta saperti di handap ieu:\n# Pretend the first number in the list is the largest number. \n# Look at the next number, and compare it with this largest number.\n# Only if this next number is larger, then keep that as the new largest number.\n# Repeat steps 2 and 3 until you have gone through the whole list.\n\nAnd here is a more formal coding of the algorithm in a [[pseudocode]] that is similar to most [[programming language]]s:\n Given: a list \"List\" \n \n largest = List[1]\n counter = 2\n while counter <= length(List):\n if List[counter] > largest:\n largest = List[counter]\n counter = counter + 1\n print largest\n \nNotes on notation:\n*= as used here indicates assignment. That is, the value on the right-hand side of the expression is assigned to the container (or variable) on the left-hand side of the expression.\n*List[counter] as used here indicates the counterth element of the list. For example: if the value of counter is 5, then List[counter] refers to the 5th element of the list.\n*<= as used here indicates \'less than or equal to\'\n\nNote also the algorithm assumes that the list contains at least one number. It will fail when presented an empty list.\nMost algorithms have similar assumptions on their inputs, called [[precondition|pre-conditions]].\n\nAs it happens, most people who implement algorithms want to know how much of a particular resource (such as time or storage) a given algorithm requires. Methods have been developed for the [[analysis of algorithms]] to obtain such quantitative answers; for example, the algorithm above has a time requirement of O(\'\'n\'\'), using the [[big O notation]] with \'\'n\'\' representing for the length of the list.\n\n== Sajarah ==\n[[Image:Abu Abdullah Muhammad bin Musa al-Khwarizmi.jpg|thumb|A tribute to the originator and namesake of algorithms]]\n\nKecap \'\'algoritma\'\' comes ultimately from the name of the [[9th century|9th-century]] mathematician [[al-Khwarizmi|Abu Abdullah Muhammad bin Musa al-Khwarizmi]]. The word \'\'[[algorism]]\'\' originally referred only to the rules of performing [[arithmetic]] using [[Arabic numerals]] but evolved into \'\'algorithm\'\' by the [[18th century]]. The word has now evolved to include all definite procedures for solving problems or performing tasks. \n\nThe first case of an algorithm written for a [[computer]] was [[Ada Lovelace|Ada Byron]]\'s [[Ada Byron\'s notes on the analytical engine|notes on the analytical engine]] written in [[1842]], for which she is considered by many to be the world\'s first [[programmer]]. However, since [[Charles Babbage]] never completed his [[analytical engine]] the algorithm was never implemented on it.\n\nThe lack of [[mathematical rigor]] in the \"well-defined procedure\" definition of algorithms posed some difficulties for mathematicians and [[logic]]ians of the [[19th century|19th]] and early [[20th century|20th centuries]]. This problem was largely solved with the description of the [[Turing machine]], an abstract model of a [[computer]] formulated by [[Alan Turing]], and the demonstration that every method yet found for describing \"well-defined procedures\" advanced by other mathematicians could be emulated on a Turing machine (a statement known as the [[Church-Turing thesis]]). \n\nNowadays, a formal criterion for an algorithm is that it is a procedure that can be implemented on a completely-specified Turing machine or one of the equivalent [[formalism]]s. Turing\'s initial interest was in the [[halting problem]]: deciding when an algorithm describes a terminating procedure. In practical terms [[computational complexity theory]] matters more: it includes the puzzling problem of the algorithms called [[NP-complete]], which are generally presumed to take more than polynomial time.\n\n== Kelas algoritma ==\nAya sababaraha cara keur nyieun kelas algoritma, and the merits of each classification have been the subject of ongoing debate.\n\nOne way of classifying algorithms is by their design methodology or paradigm. There is a certain number of paradigms, each different from the other. Furthermore, each of these categories will include many different types of algorithm. Some commonly found paradigms include:\n* Divide and conquer. A [[divide-and-conquer algorithm]] reduces an instance of a problem to one or more smaller instances of the same problem (usually [[recursion|recursively]]), until the instances are small enough to be directly expressible in the [[programming language]] employed (what is \'direct\' is often discretionary). \n* Dynamic programming. When a problem shows optimal substructure, i.e when the optimal solution to a problem consists of optimal solutions to subproblems (for instance the shortest path between two vertices on a weighted [[Graph (mathematics)|graph]] consists of the shortest path between all the vertices in between.) You solve such a problem bottom-up by solving the simplest problems first and then procceding to increasingly difficult problems until you have solved the original problem. This is called a [[Dynamic programming|dynamic programming algorithm]].\n* The greedy method. A [[greedy algorithm]] is similar to a [[Dynamic programming|dynamic programming algorithm]], but the difference is that at each stage you don\'t have to have the solutions to the subproblems, you can make a \"greedy\" choice of what looks best for the moment.\n* Linear programming. When you solve a problem using [[linear programming]] you put the program into a number of [[Linear algebra|linear]] [[Inequality|inequalities]] and then try to maximize (or minimize) the inputs. Many problems (such as the [[maximum flow]] for directed [[Graph (mathematics)|graphs]]) can be stated in a linear programming way, and then be solved by a \'generic\' algorithm such as the [[Simplex algorithm]]. \n* Search and enumeration. Many problems (such as playing [[chess]]) can be modelled as problems on [[graph theory|graphs]]. A [[graph exploration algorithm]] specifies rules for moving around a graph and is useful for such problems. This category also includes the [[search algorithm]]s and [[backtracking]].\n* The probabilistic and heuristic paradigm. Algorithms belonging to this class fit the definition of an algorithm more loosely. [[Probabilistic algorithm]]s are those that make some choices randomly (or pseudo-randomly); for some problems, it can in fact be proved that the fastest solutions must involve some randomness. [[Genetic algorithm]]s attempt to find solutions to problems by mimicking biological [[evolution]]ary processes, with a cycle of random mutations yielding successive generations of \'solutions\'. Thus, they emulate reproduction and \"survival of the fittest\". In [[genetic programming]], this approach is extended to algorithms, by regarding the algorithm itself as a \'solution\' to a problem. Also there are [[heuristic]] algorithms, whose general purpose is not to find a final solution, but an approximate solution where the time or resources to find a perfect solution are not practical. An example of this would be [[simulated annealing]] algorithms, a class of [[heuristic]] [[probabilistic algorithm]]s that vary the solution of a problem by a random amount. The name \'simulated annealing\' alludes to the metallurgic term meaning the heating and cooling of metal to achieve freedom from defects. The purpose of the random variance is to find close to globally optimal solutions rather than simply locally optimal ones, the idea being that the random element will be decreased as the algorithm settles down to a solution.\n\nAnother way to classify algorithms is by implementation. A [[recursive algorithm]] is one that invokes (makes reference to) itself repeatedly until a certain condition matches, which is a method common to [[functional programming]]. Algorithms are usually discussed with the assumption that computers execute one instruction of an algorithm at a time. Those computers are sometimes called serial computers. An algorithm designed for such an environment is called a serial algorithm, as opposed to [[parallel algorithm]]s, which take advantage of computer architectures where several processors can work on a problem at the same time. The various heuristic algorithm would probably also fall into this category, as their name (e.g. a genetic algorithm) describes its implementation.\n\nA [[list of algorithms]] discussed in Wikipedia is available.\n\n==Tempo ogé==\n*[[Algorism]]\n*[[Bulletproof algorithm]]s\n*[[Numerical analysis]]\n*[[Cryptography|Cryptographic algorithms]]\n*[[Sort algorithm]]s\n*[[Search algorithm]]s\n*[[Merge algorithm]]s\n*[[String algorithms]]\n*[[List of algorithms]]\n*[[Timeline of algorithms]]\n*[[Struktur data]]\n*[[Genetic Algorithm]]s\n*[[Randomised algorithm]]s\n*[[Computability logic]]\n\n==Sumber sejen==\n* [[Donald E Knuth]]: \'\'[[The Art of Computer Programming]]\'\', Vol 1–3, Addison Wesley 1998. Widely held as a definitive reference. ISBN 0201485419.\n* [[List of important publications in computer science#Algorithms|Important algorithm-related publications]]\n\n==Tumbu kaluar==\n* Gaston H. Gonnet and Ricardo Baeza-Yates: Example programs from [http://www.dcc.uchile.cl/~rbaeza/handbook/ \'\'Handbook of Algorithms and Data Structures.\'\'] Free source code for lots of important algorithms.\n* [http://www.nist.gov/dads/ Dictionary of Algorithms and Data Structures]. \"This is a dictionary of algorithms, algorithmic techniques, data structures, archetypical problems, and related definitions.\"\n* [http://www.nr.com Numerical Recipes]\n\n[[Category:Aljabar]]\n[[Category:Algoritma]]\n[[Category:Élmu komputer]] \n[[Category:Matematik]]\n\n[[ca:Algorisme]]\n[[cs:Algoritmus]]\n[[de:Algorithmus]]\n[[et:Algoritm]]\n[[es:Algoritmo]]\n[[eo:Algoritmo]]\n[[fr:Algorithmique]]\n[[ko:알고리즘]]\n[[it:Algoritmo]]\n[[he:אלגוריתם]]\n[[lt:Algoritmas]]\n[[hu:Algoritmus]]\n[[nl:Algoritme]]\n[[ja:アルゴリズム]]\n[[pl:Algorytm]]\n[[pt:Algoritmo]]\n[[ru:Алгоритм]]\n[[fi:Algoritmi]]\n[[sv:Algoritm]]\n[[th:อัลกอริธึม]]\n[[zh:算法]]','kategori',20,'DiN','20050303205238','',0,0,0,0,0.41376107345,'20050316081936','79949696794761'); INSERT INTO cur VALUES (1188,6,'Flowchart.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040817055410','',0,0,0,1,0.325519226794615,'20050303205258','79959182944589'); INSERT INTO cur VALUES (1189,0,'Monte_Carlo_method','#REDIRECT [[Metoda Monte Carlo]]\n','Monte Carlo method dipindahkeun ka Metoda Monte Carlo',13,'Budhi','20040817055749','',0,1,0,1,0.577660183028933,'20040817055749','79959182944250'); INSERT INTO cur VALUES (1190,0,'Algorithm','#REDIRECT [[Algoritma]]\n','Algorithm dipindahkeun ka Algoritma',13,'Budhi','20040817055830','',0,1,0,1,0.911743265494465,'20040817055830','79959182944169'); INSERT INTO cur VALUES (1191,0,'Diménsi','\'\'\'Dimension\'\'\' (tina [[Latin]] \"measured out\") is, in essence, the number of [[degrees of freedom]] available for movement in a space. (In common usage, the dimensions of an object are the [[measurement]]s that define its [[shape]] and size. That usage is related to, but different from, what this article is about.)\n\n==Physical dimensions==\n\nFor example, the space in which we live appears to be 3-dimensional. We can move up-or-down, north-or-south, or east-or-west, and movement in any other direction can be expressed in terms of just these three. Moving down is the same as moving up a negative amount. Moving northwest is merely a combination of moving north and moving west.\n\nSome theories predict that the space we live in has in fact many more dimensions (frequently 10, 11 or 26) but that the universe measured along these additional dimensions is subatomic in size. See also [[string theory]].\n\nTime is frequently referred to as the \"fourth dimension\"; time is not the fourth dimension of space, but rather of [[spacetime]].\nThis does not have a Euclidean geometry, so temporal directions are not entirely equivalent to spatial dimensions.\nA [[tesseract]] is an example of a four-dimensional object. \n\n===Related topics:===\n* [[2D geometric model]]s\n* [[3D geometric model]]s\n* [[Stereoscopy]] (3-D imaging)\n* [[2D computer graphics]]\n* [[3D computer graphics]]\n* [[3-D]] films and video\n\n==Dimensi matematik==\n\nDina [[matematik]], no definition of dimension adequately captures the concept in all situations where we would like to make use of it. Consequently, mathematicians have devised numerous definitions of dimension for different types of spaces. All, however, are ultimately based on the concept of the dimension of [[Euclidean space|Euclidean n-space]] \'\'E\'\' \'\'n\'\'. The point \'\'E\'\' 0 is 0-dimensional. The line \'\'E\'\' 1 is 1-dimensional. The plane \'\'E\'\' 2 is 2-dimensional. And in general \'\'E\'\' \'\'n\'\' is \'\'n\'\'-dimensional.\n\nIn the rest of this article we examine some of the more important mathematical definitions of dimension.\n\n=== Hamel dimension ===\n\nFor [[vector space|vector spaces]], there is a natural concept of dimension, namely the cardinality of a basis.\nSee [[Hamel dimension]] for details.\n\n=== Manifolds ===\n\nA [[connectedness|connected]] topological [[manifold]] is locally [[homeomorphic]] to Euclidean \'\'n\'\'-space, and the number \'\'n\'\' is called the manifold\'s dimension. One can show that this yields a uniquely defined dimension for every connected topological manifold.\n\nThe theory of manifolds, in the field of [[geometric topology]], is characterised by the way dimensions 1 and 2 are relatively elementary, the \'\'\'high-dimensional\'\'\' cases \'\'n\'\' > 4 are simplified by having extra space in which to \'work\'; and the cases \'\'n\'\' = 3 and 4 are in some senses the most difficult. This state of affairs was highly marked in the various cases of the [[Poincaré conjecture]], where four different proof methods are applied.\n\n=== Lebesgue covering dimension ===\n\nFor any [[topological space]], the [[Lebesgue covering dimension]] is defined to be \'\'n\'\' if \'\'n\'\' is the smallest integer for which the following holds: any open cover has a refinement (a second cover where each element is a subset of an element in the first cover) such that no point is included in more than \'\'n+1\'\' elements. For manifolds, this coincides with the dimension mentioned above. If no such n exists, then the dimension is infinite.\n\n=== Hausdorff dimension ===\n\nFor sets which are of a complicated structure, especially [[fractal|fractals]], the [[Hausdorff dimension]] is useful. The Hausdorff dimension is defined for all [[metric space|metric spaces]] and, unlike the Hamel dimension, can also attain non-integer real values.\n\n=== Hilbert spaces ===\n\nEvery [[Hilbert space]] admits an orthonormal basis, and any two such bases have the same [[cardinality]]. This cardinality is called the dimension of the Hilbert space. This dimension is finite if and only if the space\'s Hamel dimension is finite, and in this case the two dimensions coincide.\n\n=== Krull dimension of commutative rings ===\n\nThe [[Krull dimension]] of a commutative [[ring (algebra)|ring]] is defined to be the maximal number of strict inclusions in an increasing chain of [[prime ideal|prime ideals]] in the ring.\n\n=== More dimensions ===\n\n* [[Box-counting dimension]]\n* [[Dimension of an algebraic variety]]\n* [[Topological dimension]]\n* [[Poset dimension]]\n* [[Pointwise dimension]]\n* [[Lyapunov dimension]]\n* [[Kaplan-Yorke dimension]]\n* [[Minkowski-Bouligand dimension]]\n* [[Exterior dimension]] \n* [[Hurst exponent]]\n* [[q-dimension]]; especially:\n** [[Information dimension]] (corresponding to q=1)\n** [[Correlation dimension]] (corresponding to q=2)\n\n=== Bacaan salajengna ===\n\n* Thomas Banchoff, (1996) Beyond the Third Dimension: Geometry, Computer Graphics, and Higher Dimensions, Second Edition, Freeman\n\n* [[Clifford A. Pickover]], (1999) Surfing through Hyperspace: Understanding Higher Universes in Six Easy Lessons, Oxford University Press\n\n* [[Rudy Rucker]] (1984), The Fourth Dimension, Houghton-Mifflin\n\n* Edwin A. Abbott, (1884) [http://sources.wikipedia.org/wiki/Flatland Flatland]\n\n[[Category:Aljabar abstrak]] [[Category:Aljabar]] [[Category:Aljabar linear]]\n\n[[da:Dimension]] [[de:Dimension (Physik)]] [[en:Dimension]] [[fr:Dimension]] [[nl:Dimensie]] [[ja:次元]] [[simple:Dimension]] [[zh:维数]]','kategori',20,'DiN','20050303205517','',0,0,1,0,0.679393011927,'20050303205517','79949696794482'); INSERT INTO cur VALUES (1192,0,'Computation','[[Category:Computation]]\n\'\'\'Komputasi\'\'\' bisa dihartikeun salaku cara meupeuskeun masalah tina [[input]] nu dibere ngagunakeun [[algoritma]]. Ieu oge nu disebut salaku \'\'téori komputasi\'\', bagean tina [[computer science|élmu komputer]] sarta [[matematik]], oge nu pakait. For thousands of years, computing was done with pen and paper, or chalk and slate, or mentally, sometimes with the aid of tables.\n\n\'\'The \'\'\'theory\'\'\' of [[computation]]\'\' began early in the twentieth century, before modern [[electronic computers]] had been invented. \n\nAt that time, [[mathematician]]s were trying to find which math problems can be solved by simple methods and which cannot. The first step was to define what they meant by a \"simple method\" for solving a problem. In other words, they needed a formal model of computation.\n\nSeveral different computational models were devised by these early researchers. One model, the [[Turing machine]], stores characters on an infinitely long tape, with one square at any given time being scanned by a read/write head. Another model, [[recursive function|recursive functions]], uses functions and function composition to operate on numbers. The [[lambda calculus]] uses a similar approach. Still others, including [[Markov algorithm]]s and [[Post system]]s, use grammar-like rules to operate on strings. All of these formalisms were shown to be equivalent in computational power -- that is, any computation that can be performed with one can be performed with any of the others. They are also equivalent in power to the familiar electronic\ncomputer, if one pretends that electronic computers have infinite memory. Indeed, it is widely believed that all \"proper\" formalizations of the concept of algorithm will be equivalent in power to Turing machines; this is known as the [[Church-Turing thesis]]. In general, questions of what can be computed by various machines are investigated in [[computability theory]].\n\nThe theory of computation studies these models of general computation, along with the limits of computing: Which problems are (provably) unsolvable by a computer? (See the [[Halting Problem|halting problem]] and the [[Post correspondence problem]].) Which problems are solvable by a computer, but require such an enormously long time to compute that the solution is impractical? (See [[Presburger arithmetic]].) Can it be harder to solve a problem than to check a given solution? (See [[complexity classes P and NP]]). In general, questions concerning the time or space requirements of given problems are investigated in [[Computational complexity theory| complexity theory]].\n\nIn addition to the general computational models, some simpler computational models are useful for special, restricted applications. [[Regular expressions]], for example, are used to specify string patterns in [[UNIX]] and in some programming languages such as [[Perl]]. Another formalism mathematically equivalent to regular expressions, [[finite state machines|Finite automata]] are used in circuit design and in some kinds of problem-solving. [[Context-free grammar|Context-free grammars]] are used to specify programming language syntax. Non-deterministic [[pushdown automaton|pushdown automata]] are another formalism equivalent to context-free grammars. [[primitive recursive function|Primitive recursive functions]] are a defined subclass of the recursive functions.\n\nDifferent models of computation have the ability to do different tasks. One way to measure the power of a computational model is to study the class of\n[[formal language|formal languages]] that the model can generate; this leads to the [[Chomsky hierarchy]] of languages.\n\nThe following table shows some of the classes of problems (or languages, or \ngrammars) that are considered in computability theory (blue) and complexity theory (green). If class \'\'\'X\'\'\' is a strict subset of \'\'\'Y\'\'\', then \'\'\'X\'\'\' is shown below \'\'\'Y\'\'\', with a dark line connecting them. If \'\'\'X\'\'\' is a subset, but it is unknown whether they are equal sets, then the line is lighter and is dotted.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
[[decision problem|Decision Problem]]
[[image:solidLine.png]][[image:solidLine.png]]
[[recursively enumerable language|Type 0 (Recursively enumerable)]]
[[Undecidable]]
[[image:solidLine.png]]
[[Decidable language|Decidable]]
[[image:solidLine.png]]
[[EXPSPACE]]
[[image:dottedLine.png]]
[[EXPTIME]]
[[image:dottedLine.png]]
[[PSPACE]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[context-sensitive grammar|Type 1 (Context Sensitive)]]
[[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[PSPACE-Complete]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[image:solidLine.png]][[image:solidLine.png]]
[[Co-NP]]
[[image:dottedLine.png]]
[[NP (complexity)|NP]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]]
[[BPP]]
[[BQP]]
[[NP-Complete]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[image:solidLine.png]][[image:solidLine.png]]
[[P]]
[[image:solidLine.png]][[image:solidLine.png]][[image:dottedLine.png]][[image:dottedLine.png]]
[[image:solidLine.png]]
[[NC (complexity)|NC]]
[[P-Complete]]
[[image:solidLine.png]][[image:solidLine.png]]
[[context-free grammar|Type 2 (Context Free)]]
[[image:solidLine.png]]
[[regular grammar|Type 3 (Regular)]]
\n\n==For further reading==\n\n*Garey, Michael R., and David S. Johnson: \'\'Computers and Intractability: A Guide to the Theory of NP-Completeness.\'\' New York: W. H. Freeman & Co., 1979. The standard reference on NP-Complete problems - an important category of problems whose solutions appear to require an impractically long time to compute.\n*Hein, James L: \'\'Theory of Computation.\'\' Sudbury, MA: Jones & Bartlett, 1996. A gentle introduction to the field, appropriate for second-year undergraduate computer science students.\n*Hopcroft, John E., and Jeffrey D. Ullman: \'\'Introduction to Automata Theory, Languages, and Computation.\'\' Reading, MA: Addison-Wesley, 1979. One of the standard references in the field.\n*Taylor, R. Gregory: \'\'Models of Computation.\'\' New York: Oxford University Press, 1998. An unusually readable textbook, appropriate for upper-level undergraduates or beginning graduate students.\n*[http://www.cs.berkeley.edu/~aaronson/zoo.html The Complexity Zoo]: A huger list of complexity classes, as reference for experts.\n*[http://www.cis.upenn.edu/~giorgi/cl.html Computability Logic]: A theory of interactive computation. The main web source on this new subject.\n\n==Tempo oge==\n*[[Computability logic]]\n*[[Interactive computation]]\n*[[List of important publications in computer science#Computability| Important publications in computability]]\n*[[Calculation]]\n\n----\nThis article contains some content from an [http://www.nupedia.com/article/567/ article by Nancy Tinkham], originally posted on [[Nupedia]]. This article is [[open content]].\n\n\n\n[[de:Theoretische Informatik]]\n[[fr:Calculabilité]]\n[[ja:計算理論]]\n[[pl:Teoria oblicze%C5%84]]\n[[th:การคณนา]]','',13,'Budhi','20041224121439','',0,0,1,0,0.366917228031,'20041224121439','79958775878560'); INSERT INTO cur VALUES (1193,0,'Hydrogeology','\'\'\'Hydrogeology\'\'\' or \'\'\'geohydrology\'\'\' is the part of [[hydrology]] that deals with the occurrence and movement of water beneath the earth\'s surface ([[groundwater]]).\n\nHydrogeology is a complex subject, as the chemical and physical interactions between [[soil]] and water are intricate and difficult to quantify. Although the basic principles of hydrogeology are not complex or difficult to understand, the quantification of some of the most important aspects of this science are very complex, multi-component systems that are difficult to determine through direct measurement, and are therefore determined through groundwater [[modeling]] which presents questions as to the accuracy of these techniques.\n\nFor example, it may be desirable to determine the conditions of flow for a chemical plume from a spill or leak, such as produced by a leaking storage tank. If the contaminant reaches the groundwater then the contaminant may be dissolved in and carried with it. It is possible to determine the concentration in the water by [[sampling]] of [[well]]s. It is also possible to determine the direction and speed of the groundwater flow by measuring the water table elevation in several wells and using \'\'[[Henry Darcy|Darcy]]\'s law\'\':
\n

v = k /n x (Ha - Hb)/D

\nwhere v = velocity,
\nk = permeability factor, depending on soil type,
\nn = porosity, depending on soil type,
\nHa, Hb = Hydraulic head (groundwater level) in wells A and B,
\nD = horizontal distance between wells A and B
\n((Ha-Hb)/D is called the \'hydraulic gradient\').\n\nHowever, the speed of the contaminant is not likely to be the same as the speed of the groundwater due to [[adsorption]] and [[organic matter]] content of the soil, [[dilution]] and [[attenuation]], all depending on the nature of the contaminant.\nSo, to determine where that plume may be headed, and where it will be in the future, requires mathematical groundwater [[model]]ing. Simple models may be two dimensional (in a horizontal plane) only. Other, more complex three dimensional models based on extensive field data, may require considerable computing time. These models are then usually set up using a [[finite element method]] (FEM). \n\nHydrogeology has particular importance with regards to [[remediation]] issues such as a \'simple\' thing as an urban groundwater contamination caused by a [[dry cleaning|dry cleaner]] using \'[[trichloroethylene|tri]]\' and \'[[tetrachloroethylene|tetra]]\' or a complex case as burial of [[hazardous waste]] and finding out where that waste went when it escaped from such facilities as the [[Hanford Nuclear Waste Dump]] and other [[Department of Energy]] facilities, such as [[Los Alamos National Lab]] and [[Sandia National Labs]]. \n\nAs an example, an understanding of the hydrogeology surrounding the [[Waste Isolation Pilot Plant]] or \'\'\'WIPP\'\'\' where tons of [[low level radioactive waste]] will be interred in salt mines is of utmost importance to help determine the chances of [[radioactive contamination|leakage or escape of material]] over hundreds or thousands of years. The hydrogeology of the [[Yucca Mountain]], [[Nevada]] nuclear waste site, for storage of [[high level radioactive waste]] has been studied intensely in anticipation of receiving tens of thousands of [[glass log]] or similar canisters of extremely radioactive waste less than 80 miles from [[Las Vegas]].\n\nAlso see: [[Environmental Engineering]]\n\n==Tumbu kaluar==\n* [http://www.epa.gov/seahome/groundwater/src/geo.htm Hydrogeology basics]\n* [http://www.uwsp.edu/water/portage/undrstnd/gwmove2.htm Groundwater movement]\n* [http://www.microfem.com/ Groundwater modeling with Microfem]\n\n[[Category:Geology]]','/* External links */',13,'Budhi','20040901002427','',0,0,0,0,0.510422009747,'20040901002427','79959098997572'); INSERT INTO cur VALUES (1194,0,'Geohydrology','#REDIRECT [[hydrogeology]]','',13,'Budhi','20040817061311','',0,1,0,1,0.699635970732,'20040817061311','79959182938688'); INSERT INTO cur VALUES (1195,0,'Hidrologi','[[de:Hydrologie]] [[es:Hidrología]] [[fr:Hydrologie]] [[pl:Hydrologia]] [[zh:水文学]]\n\n\'\'\'Hidrologi\'\'\' nyaeta elmu ngeunaan kajadian, distribusi, sarta pindahna cai dina, di jero jeung di luhur bumi. Saperti, dina [[earth science]]. Siklus pindahna cai antara terrasphere (darat), oceanosphere (laut), jeung atmosphere (udara) disebut [[hydrologic cycle]].\n\nAya dua widang utama dina elmu hidrologi. Kahiji [[surface-water hydrology]] nu museurkeun kana cai dina jeung luhureun taneuh. Conto tina \'\'hidrologi permukaan\'\' nyaeta banjir jeung kasaatan. Kaduana nyaeta hidrologi cai-taneuh atawa [[geohydrology]], nu museurkeun kana distribusi jeung pindahna cai di handapeun taneuh (contona, [[groundwater]]). Hidrologi cai-taneh penting keur dipake dina [[water supply]], [[irrigation]] jeung [[environmental engineering]]. Catetan yen cai di lautan dipisahkeun tina elmu hidrologi sarta dipikanyaho ku istilah [[oceanography]]. Sarta cai di atmosphere leuwih diajarkuen dina [[meteorology]]. \n\nKaasup dina hidrologi oge elmu gerak cai sarta [[water-borne constituents]] — materials carried either as dissolved quantities or in separate phases. A related facet of hydrology is the determination of statistical flow prediction in rivers and streams. This information is essential to design and evaluation of natural and man-made channels, bridge openings and dams. [[Stream gage]] (U.S. Geological Survey terminology) data have been collected and tabulated by the United States Geological Survey for many years and much of it is available online for analysis.\n\nTempo oge: [[water resources]] - [[virtual water]]\n\n==Tumbu kaluar==\n\n*[http://www.cig.ensmp.fr/~hubert/glu/aglo.htm INTERNATIONAL GLOSSARY OF HYDROLOGY].\n*[http://www.usgs.gov U.S. Geological Survey].','',13,'Budhi','20040902005506','',0,0,0,0,0.541280085939,'20050216033917','79959097994493'); INSERT INTO cur VALUES (1196,0,'Groundwater','[[de:Grundwasser]]\n\n\'\'\'Cai taneuh\'\'\' mangrupa [[cai]] naon waé nu kapanggih na jero taneuh. It is found in [[aquifer]]s, in the [[pore]] spaces of rocks, in unconsolidated sediments, as [[permafrost]], and as [[soil]] [[moisture]]. Groundwater flows to the surface naturally at [[spring (water)|spring]]s and seeps and often forms [[oasis|oases]] or swamps. It may also be tapped artificially by the digging of [[well]]s. \n\nGroundwater is a long-term \'reservoir\' of the natural [[water cycle]], as opposed to short-term water reservoirs like the atmosphere and surface water. It is naturally replenished from above, as surface water from [[Precipitation (meteorology)|precipitation]] sinks into the ground. \n\nGroundwater is often contained in [[aquifer|aquifers]], which are subterranean areas (or layers) of porous material that channel the groundwater\'s flow. Aquifers can be confined or unconfined. A \'\'\'confined aquifer\'\'\' follows a downward grade from a \'\'recharge zone\'\' and can become pressurized as it flows. This can create [[artesian well]]s that flow freely without the need of a pump. The top of an \'\'\'unconfined aquifer\'\'\' is called the [[water table]], where water pressure is equal to atmospheric pressure. The region between the land surface and the water table is called the \'\'\'vadose zone\'\'\' (Latin for shallow); in this region, water is under pressure less than atmospheric pressure (suction).\n\n==Problems with groundwater==\nGroundwater is a highly useful and abundant resource, but it does not renew itself rapidly. If groundwater is extracted intensively, as for [[irrigation]] in arid regions, it may become depleted. The most evident problem that may result from this is a lowering of the [[water table]] beyond the reach of existing wells. Wells must consequently be deepened to reach the groundwater; in places like [[India]], the water table has dropped hundreds of feet due to over-extraction. A lowered water table may, in turn, cause other problems.\n\nThe film of ground water around particles of an aquifer of unconsolidated sediment actually holds the particles apart, and the removal of this water will compact the sediment. Thus the aquifer is permanently reduced in capacity, and the surface of the ground may also subside. The city of [[New Orleans, Louisiana]] is actually below sea level today, and its subsidence is partly caused by removal of ground water under it.\n\nGenerally (but not always) ground water flows in the same direction as the slope of the surface. The recharge zone of an aquifer near the seacoast is likely to be inland, often at considerable distance. In these coastal areas, a lowered water table may induce [[sea water|seawater]] to reverse the flow toward the sea. Sea water moving inland is called a [[saltwater intrusion]]. Alternatively, [[salt]] from [[mineral]] beds may leach into the groundwater of its own accord.\n\nSometimes the water movement from the recharge zone to the place where it is withdrawn may take centuries. When the usage of water is greater than the recharge, it is referred to as \'\'mining\'\' water. Under those circumstances it is not a renewable resource.\n\nIn [[India]] and [[Bangladesh]], a drop in the water table has been associated with [[arsenic]] contamination. It is thought that irrigation for [[rice]] production since late 1970s resulted in the withdrawal of large quantities of groundwater, which caused the local water table to drop, allowing [[oxygen]] to enter the ground and touching off a reaction that [[leaching|leaches]] out arsenic from [[pyrite]] in the soil. The actual mechanism, however, is yet to be identified with certainty.\n\nNot all groundwater problems are caused by over-extraction. [[Pollutant]]s dumped on the ground may leach into the soil, and work their way down into aquifers. Movement of water within the aquifer is then likely to spread the pollutant over a wide area, making the groundwater unusable. See [[environmental engineering]] and [[remediation]].\n\nWater table conditions are frequently of importance to [[agriculture|agricultural]] [[irrigation]], [[waste disposal]] (including [[nuclear waste]]), and other [[ecology|ecological]] issues.\n\n==Related topics==\n* [[Aquifer]]\n* [[Water table]]\n* [[Hydrologic cycle]]\n* [[Hydrogeology]]\n[[Category:Forms of water]]','',3,'Kandar','20040818083246','',0,0,0,0,0.502180529061,'20040818083246','79959181916753'); INSERT INTO cur VALUES (1197,0,'Analisis_varian','#REDIRECT [[Analisa varian]]','',13,'Budhi','20040908004409','',0,1,0,0,0.825735809119172,'20040908004409','79959091995590'); INSERT INTO cur VALUES (1198,0,'Likelihood-ratio_test','\'\'\'Tes rasio-likelihood\'\'\' ngarupakeun tes statistik nu ngandelkeun kana ngitung tes statistik tina [[ratio|babandingan]] nilai maksimum [[likelihood function|fungsi likelihood]] dina kaayaan null hipotesa maksimal nu mibanda watesan kendor. If that ratio is Λ and the [[null hypothesis]] holds, then for commonly occurring families of [[probability distribution]]s, −2 log Λ has a particularly handy asymptotic distribution. Many common test statistics such as the [[Z-test]], the [[F-test]] and [[Uji kuadrat-chi Pearson]] can be phrased as log-likelihood ratios or approximations thereof.\n\nMany of these approximations were quite useful when computers did not exist, but now that taking a log is really no more vexing than multiplying two numbers, other approximations may be more useful, especially in special cases where the approximations are suspect.\n\nA statistical model is often a parametrized family of probability density functions or probability mass functions \'\'f\'\'θ(\'\'x\'\'). A null hypothesis is often stated by saying the parameter θ is in a specified subset Θ0 of the parameter space Θ. The [[likelihood function]] is \'\'L\'\'(θ) = \'\'L\'\'(θ| \'\'x\'\') = p(\'\'x\'\'|θ) = \'\'f\'\'θ(\'\'x\'\') is a function of the parameter θ with \'\'x\'\' held fixed at the value that was actually observed, i.e., the data. The \'\'\'likelihood ratio\'\'\' is\n\n:\\Lambda(x)=\\frac{\\sup\\{\\,L(\\theta\\mid x):\\theta\\in\\Theta_0\\,\\}}{\\sup\\{\\,L(\\theta\\mid x):\\theta\\in\\Theta\\,\\}}.\n\nThis is a function of the data \'\'x\'\', and is therefore a [[statistic]]. The \'\'\'likelihood-ratio test\'\'\' rejects the null hypothesis if the value of this statistic is too small, and is justified by the [[Neyman-Pearson lemma]]. How small is too small depends on the significance level of the test, i.e., on what probability of [[Type I error]] is considered tolerable (\"Type I error\" consist of rejection of a null hypothesis that is true).\n\nIf the null hypothesis is true, then −2 log Λ will be asymptotically [[chi-squared distribution|χ2 distributed]] with degrees of freedom equal to the difference in dimensionality of Θ and Θ0.\n\nFor instance, in the case of Pearson\'s test, we might try to compare two coins to determine whether they have the same probability of coming up heads. Our observation can be put into a contingency table with rows corresponding to the coin and columns corresponding to heads or tails. The elements of the contingency table will be the number of times the coin for that row came up heads or tails. The contents of this table are our observation X.\n\n\n \n \n \n\n \n \n \n\n \n \n \n\n
\'\'\'Heads\'\'\' \'\'\'Tails\'\'\'
\'\'\'Coin 1\'\'\' k1H k1T
\'\'\'Coin 2\'\'\' k2H k2T
\nHere ω consists of the parameters p1H, p1T, p2H, and p2T which are the probability that coin 1 (2) comes up heads (tails). The hypothesis space H is defined by the usual constraints on a distribution, pij ≥ 0, pij ≤ 1, and piH + piT = 1. The null hypothesis H0 is the sub-space where p1j = p2j. In all of these constraints, i = 1,2 and j = H,T.\n\nThe hypothesis and null hypothesis can be rewritten slightly so that they satisfy the constraints for the log-likelihood ratio to have the desired nice distribution. Since the constraint causes the two-dimensional H to be reduced to the one-dimensional H0, the asymptotic distribution for the test will be χ2(1), the χ2 distribution with one degree of freedom.\n\nFor the general contingency table, we can write the log-likelihood ratio statistic as\n\n:-2 \\log \\Lambda = \\sum_{i,j} k_{ij} \\log {p_{ij} \\over m_{ij}}. \n\n[[Bayesian]] criticisms of classical likelihood ratio tests focus on two issues: \n#the [[supremum]] function in the calculation of the likelihood ratio, saying that this takes no account of the uncertainty about θ and that using maximum likelihood estimates in this way can promote complicated alternative hypotheses with an excessive number of free parameters;\n#testing the probability that the sample would produce a result as extreme \'\'or more extreme\'\' under the null hypothesis, saying that this bases the test on the probability of extreme events that not happen. \nInstead they put forward methods such as [[Bayes factor]]s, which explicitly take uncertainty about the parameters into account, and which are based on the evidence which did occur. \n\n== Tempo oge ==\n* [[Likelihood]] and [[likelihood principle]]\n* [[Statistik]]','',13,'Budhi','20041224204511','',0,0,1,0,0.99727934366,'20050208034238','79958775795488'); INSERT INTO cur VALUES (1199,0,'F-test','\'\'\'F-test\'\'\' nyaeta tes [[statistik]] numana tes statistik mibanda [[sebaran-F]] lamun null hipotesis bener. Variasi hipotesis nu gede dina aplikasi statistik dites make F-tes. Diantarana:\n\n*Hipotesis kelipatan mean sebaran normal , sakabehna mibanda [[simpangan baku]] nu sarua. Test hipotesis diharepkeun leuwih hade dipikanyaho ku make mean dina F-tes, sarta masalah sederhana dina [[analisa varian]].\n\n*Hipotesa tina simpangan baku dua sebaran normal sarua sarta saterusna dibandingkeun.\n\n\n{{pondok}}\n\n[[en:F-test]]\n[[nl:F-toets]]','',3,'Kandar','20041122083124','',0,0,0,0,0.515846180038,'20050303211247','79958877916875'); INSERT INTO cur VALUES (1200,0,'Unimodal','\'\'\'Unimodal\'\'\' atawa \'\'\'SkyTran\'\'\' diusulkeun ku [[Douglas Malewicki]] keur hiji sistim [[personal rapid transit|kandaraan pribadi]] nu gancangna 160km/h (100mph). Unggal mobil bakal maju dina luhureun rel ngagunakeun sistim magnet. Sistim [[magnetic levitation|magnetik levitasi]] ngarupakeun sistim \"[[Inductrack]]\" pasip make [[Halbach array|aturan Halbach]], saperti nu diwangun ku ahli fisika [[William Post]] di [[Lawrence Livermore Laboratories|Laboratorium Lawrence Livermore]].\n\nSistem rekayasa ieu leuwih nyaman, aman sarta gampang dipake utama keur sistim transportasi umum saperti mobil jeung beus.\n\nHal nu istimewa tina Unimodal nyaeta museurkeun kana harga nu murah tur efisien. Jaringan jalan utama dijieun tina waja (lain tina semen/beton iwal ti dina pondasina) nu ngarupakeun hasil produksi masal. Transportasi sejen utamana \"mobil dina rel nu miring\" sarta sarta kurang efisien keur mobil nu dipake.\n\nPamakaean magnetik levitasi dimaksudkeun keur ngurangan beaya perawatan. Unggal gerakan dina sistim ieu merlukeun material anu saeutik. Ku sabab itu disebutna \"tetapan padat\". Kauntungan sejenna nyaeta saeutik gesekan, halus sarta teu gandeng.\n\n==Tumbu kaluar==\n*http://www.unimodal.com\n*http://www.skytran.net','',13,'Budhi','20041225231644','',0,0,0,0,0.70784737389,'20041225231644','79958774768355'); INSERT INTO cur VALUES (1201,0,'Mode','\'\'\'\'\'Mode\'\'\'\'\' ngabogaan sababaraha harti:\n\n* Dina [[statistik]], \'\'\'mode\'\'\' nyaeta nilai nu mibanda angka observasi panggedena, disebut nilai atawa nilai nu pangremenna bijil. Mode lain hal anu unik, teu saperti [[arithmetic mean]] jeung [[median]]. Leuwih gampang dipake lamun nilai atawa observasi lain data numeris: contona, mode tina {1, 2, 2, 2, 3, 9} nyaeta 2, mode tina {apple, apple, banana, orange, orange, orange, peach} nyaeta \'\'orange\'\'.\n\n: Tempo oge: [[summary statistics]], [[descriptive statistics]]\n\n* In [[fashion]] the \'\'\'mode\'\'\' is also the largest number, but of the number of people following that trend.\n\n* In [[music]] a \'\'\'mode\'\'\' is a kind of scale; see [[musical mode]].\n\n* In [[computer software]], a \'\'\'mode\'\'\' is distinct method of operation within a computer program. Three popular examples of software employing modes:\n**[[vi]] - has one mode for inserting text, and a separate mode for entering commands. Some people also call vi\'s ability to line-edit a \"mode\" (even though it is launched outside of vi\'s normal interface, by invoking \"[[ex]]\" from the [[operating system]]\'s [[command line interface]].)\n** [[Emacs]] - has many modes that can be evoked based on file type to more easily edit files of a certain type. Modes are written in Emacs\'s [[Lisp programming language|LISP]], and all modes may not be included with all versions. \n** [[CIOS]] (Cisco Internetworking Operating System) - in order to gain the privilege to execute certain commands, you must enter a certain mode that allows you to execute that command.\n\n* In a [[waveguide]] or [[cavity]] the \'\'\'mode\'\'\' is one of the possible patterns of [[electromagnetic field]]. Available patterns are derived from [[Maxwell\'s equations]] and the applicable [[boundary condition]]s. They may be [[longitudinal mode|longitudinal]] or [[transverse mode|transverse]].\n** An example of [[waveguide]] \'\'\'mode\'\'\': [[fiber optic]] \'\'\'mode\'\'\'.\n** An example of [[cavity]] \'\'\'mode\'\'\': [[laser]] \'\'\'mode\'\'\'.\n\n* In [[acoustics]], a \'\'\'mode\'\'\' is one of the possible patterns of vibration, analogous to waveguide and cavity modes, only that electrical and magnetical fields are replaced by velocity and displacement. Each mode has a characteristic vibrational frequency and damping. See also: [[Ernst Chladni]], [[Cymatics]].\n** An example of acoustic modes: An \"ideal\" guitar string of length L, fixed at both ends, will have modes in the shape of sin(n*x*pi/L), where n is the mode number.\n\n* See also [[modality]].\n\n{{disambig}}\n\n[[fr:Mode]] [[nl:Modus]]','',13,'Budhi','20040818001027','',0,0,0,0,0.597241008932,'20040818001027','79959181998972'); INSERT INTO cur VALUES (1202,0,'Hydrologic_cycle','#REDIRECT [[water cycle]]','',13,'Budhi','20040817070514','',0,1,0,1,0.410168475197,'20040817070552','79959182929485'); INSERT INTO cur VALUES (1203,0,'Daur_cai','\'\'\'Daur cai\'\'\' (sacara husus dipikawanoh/katelah ogé \'\'\'daur hidrologis\'\'\') nujul kana parobahan wujud antara cair, padet, jeung gas; sarta parobahan nu sinambung [[cai]] sajeroeun [[hidrosfir]], antara [[atmosfir marcapada]], [[darat|lemah]], [[cai permukaan]], [[cai taneuh]], jeung [[tutuwuhan]]. Daurna bisa dibagi kana opat fase utama: \'\'[[évaporasi]]\'\', \'\'[[présipitasi (météorologi)|présipitasi]]\'\', infiltrasi, jeung \'\'[[aliran (cai)|runoff]]\'\'.\n\n* Évaporasi sacara umum nyaéta pindahna cai tina awak cai permukaan ka atmosfir, kaasup [[transpirasi]] tina tutuwuhan; sahingga kadang sok disebut \'\'[[évapotranspirasi]]\'\'.\n* Uap atmosfir bisa ngibun jadi [[awan]], sarta ragrag salaku présipitasi. Ieu umumna lumangsung dina wujud [[hujan]], tapi [[salju]] sarta wujud séjénna ogé kaasup. Présipitasi kadang lumangsung na sagara, sabab dina kaayaan normal, [[pagunungan]] perlu pikeun naratas kondensasi jeung ngabentukna awan.\n* Infiltrasi/nyerep kana taneuh mangrupa alihan tina cai permukaan jadi cai taneuh. Laju serep gumantung kana [[perméabilitas]] (daya serep) taneuh atawa batu sarta faktor-faktor séjén. Cai taneuh gerakna lambat pisan, sarta bisa balik deui jadi cai permukaan atawa diteundeun dina \'\'[[aquifer]]\'\' dina mangsa réwuan taun. It generally returns to the surface at lower elevations under the usual force of [[gravity]], but may also rise under pressure, as in the case of an [[artesian]] well.\n* \'\'Runoff\'\' nyaéta rupa-rupa cara cai permukaan ngumbara nepi ka [[sagara]]. Cai ngalir ngaliwatan [[walungan]] sarta nyangsang di [[situ]]. Teu sakabéh cai nyampurnakeun fase \'\'runoff\'\', sabab bisa nguap saméméh nepi ka sagara.\n\n==Tumbu kaluar==\n* [http://www.und.edu/instruct/eng/fkarner/pages/cycle.htm Daur Hidrologis] \'\'ti [http://www.und.edu/instruct/eng/fkarner/earth.htm Earthscape]\'\'\n\n* [http://www.grow.arizona.edu/water/hydrologiccycle/hydrologiccycle.shtml Daur Hidrologis] \'\'ti [http://www.grow.arizona.edu/ GROW]\'\'\n\n==Tempo ogé==\n* [[daur biokimiawi]]\n\n[[en:Water cycle]] [[simple:Water cycle]]\n\n[[Category:Ékologi]]','',3,'Kandar','20041222101706','',0,0,0,0,0.533334010529,'20050203164813','79958777898293'); INSERT INTO cur VALUES (1204,0,'Permeability','\'\'\'Permeability\'\'\' ngabogaan sabaraha harti:\n\n# Dina [[electromagnetism]], \'\'\'[[permeability (electromagnetism)|permeability]]\'\'\' nyaeta tingkat magnetisasi material nu pakait jeung medan magnet.\n# Dina [[géologi]], \'\'\'[[permeability (geology)|permeability]]\'\'\' nyaeta ukuran kamampuh material keur ngaliwatkeun cai.\n{{disambig}}\n\n[[da:permeabilitet]] [[de:Permeabilität]]','',13,'Budhi','20040901002326','',0,0,0,0,0.664792122163,'20040901002326','79959098997673'); INSERT INTO cur VALUES (1205,0,'Surface_water','\'\'\'Surface water\'\'\' is [[cai|water]] on the ground or in a [[stream]], [[river]], [[lake]], [[sea]] or [[ocean]]; as opposed to [[groundwater]].','',3,'Kandar','20040818083108','',0,0,0,0,0.358503691553,'20040818083108','79959181916891'); INSERT INTO cur VALUES (1206,0,'Cai','{| width=\"300\" border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" style=\"margin-left:1em\"\n|+ \'\'\'Pasipatan\'\'\'\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#FFDEAD\" | Umum\n|-\n| Ngaran\n| Cai\n|-\n| Diagram\n| [[Image:Diagram molekul cai.png|150px|Diagram molekul cai, jeung ukuranana]]\n|-\n| [[Rumus kimiawi]]\n| [[Hidrogén|H]]2[[Oksigén|O]]\n|-\n| [[warna|Katémbongna]]\n| Cairan teu warnaan\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#FFDEAD\" | Fisik\n|-\n| [[Beurat atom|Beurat rumus]]\n| 18.01528 [[unit massa atom|amu]]\n|-\n| [[Titik lééh]]\n| [[1 E2 K|273.15 K]] (0 [[celsius|°C]])\n|-\n| [[Titik golak]]\n| [[1 E2 K|373.15 K]] (100 [[celsius|°C]])\n|-\n| [[Temperatur kritis]]\n| 674 K\n|-\n| Tekenan kritis\n| \'\'2.21 × 107 Pa\'\'\n|-\n| [[Density]]\n| 1.0 ×103 [[kilogram|kg]]/[[metre|m]]3 at 4[[celsius|°C]]\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#FFDEAD\" | Térmokimia\n|-\n| [[Standard enthalpy change of formation|ΔfH0gas]]\n| -241.83 [[joule|kJ]]/[[mol (unit)|mol]]\n|-\n| ΔfH0cair\n| -285.83 kJ/mol\n|-\n| ΔfH0padet\n| -291.83 kJ/mol\n|-\n| [[Éntropi molar baku|S0gas, 1 bar]]\n| 188.84 J/mol·K\n|-\n| S0cair, 1 bar\n| 69.95 J/mol·K\n|-\n| S0padet\n| 41 J/mol·K\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#FFDEAD\" | Kasalametan\n|-\n| [[Ingestion]]\n| Dipikabutuh keur [[hirup]]; loba teuing nginum ngakibatkeun ngeri sirah, lieur, keram, sarta bisa bahaya pikeun atlit\n|-\n| [[Inhalation]]\n| Non-toxic. Can dissolve surfactant of lungs. Suffocation in water is called [[drowning]].\n|-\n| [[Kulit]]\n| Prolonged immersion may cause flaking (desquamation).\n|-\n| [[Panon]]\n| Teu bahaya.\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#FFDEAD\" | \n\nUnit [[SI]] digunakeun mun perlu. Iwal mun disebutkeun, biasana dina kaayaan [[Temperatur jeung tekenan baku|baku]].\n

[[Inorganic table information|Bantahan jeung acuan]]\n\n|}\n\n\'\'\'Cai\'\'\' ngarupakeun hiji [[sanyawa kimiawi]] jeung [[molekul polar]] nu [[cair]] dina [[temperatur jeung tekenan baku]] (\'\'standard temperature and pressure\'\', STP). Cai mibanda [[rumus kimiawi]] [[hidrogén|H]]2[[oksigén|O]], nu hartina hiji [[molekul]] cai diwangun ku dua [[atom]] [[hidrogén]] jeung hiji atom [[oksigén]]. Cai bisa dipanggihan di ampir sakabéh tempat di [[Marcapada]] sarta dipikabutuh ku sadaya nu [[hirup]]. Kira 70% beungeut Marcapada katutupan ku cai. Cai geus kapanggih aya di sababaraha banda di [[tatasurya]] jeung di saluareunana dina rupa [[és]]. Pentingna cai pikeun kahirupan terestrial geus ngagiring kana panyangka yén ayana dina wujud cair di mana waé sagigireun di Marcapada ieu bisa nyadiakeun habitat nu ngadukung pikeun kahirupan [[ékstraterestrial]].\n\n==Ihtisar==\n[[Wujud padet]] cai dikenal salaku [[és]]; [[wujud gas]]na katelah [[uap cai]] (atawa \'\'[[steam]]\'\'). Unit temperatur (tadina darajat [[Celsius]], ayeuna [[Kélvin]]) ditangtukeun dina kontéks [[titik tripel]] cai, 273.16 K (0.01 °C) jeung 611.2 Pa, temperatur jeung tekenan nalika cai padet, cair, jeung gas araya dina kaayaan kasatimbangan. Cai mintonkeun sababaraha paripolah nu anéh pisan, kaasup kabentukna padetan cai nonkristalin (\'\'glassy\'\') \'\'[[vitreous ice]]\'\'.\n\nDina temperatur luhureun 647 [[Kélvin|K]] jeung tekenan luhureun 22.064 [[pascal|MPa]], sakumpulan molekul cai ngalaman hiji kaayaan \'\'superkritis\'\', dimana guruntulan kawas-cair ngambang di antara fase kawas-uap.\n\nThe [[liquid water path]] is a measure of the amount of liquid water in an air column.\n\n==Awak cai==\n\'\'\'Awak cai\'\'\' bisa mangrupa [[sagara]], [[laut]], [[situ]], [[walungan]], [[curug]], [[kanal]], [[balong]], jeung sajabana. Tempo [[sumberdaya cai]] pikeun béja ngeunaan asupan cai bersih. Tempo ogé: [[cilaut]], \'\'[[fresh water]]\'\', jeung \'\'[[underwater]]\'\'.\n\nKandungan cai di Marcapada kira (jumlah asupan cai sadunya) aya 1,360,000,000 km³ (326,000,000 mil³) nu kabagi mangrupa:\n\n* 1,320,000,000 km³ (316,900,000 mil³ atawa 97.2%) di sagara \n* 25,000,000 km³ (6,000,000 mil³ atawa 1.8%) salaku glasir jeung és\n* 13,000,000 km³ (3,000,000 mile³ atawa 0.9%) citaneuh.\n* 250,000 km³ (60,000 mil³ atawa 0.02%) di situ, laut darat, jeung walungan \n* 13,000 km³ (3,100 mil³ atawa 0.001%) uap cai atmosfir dina sakali mangsa tinangtu.\n\n==Sipat bipolar cai==\nHiji ciri penting cai nyaéta sipat [[molekul polar|polarna]]. Molekul cai ngabentuk hiji juru, with hydrogen atoms at the tips and oxygen at the vertex. Since oxygen has a higher [[electronegativity]] than hydrogen, the side of the molecule with the oxygen atom has a partial negative charge. A molecule with such a charge difference is called a [[dipole]]. The charge differences cause water molecules to be attracted to each other (the relatively positive areas being attracted to the relatively negative areas) and to other polar molecules. This attraction is known as [[hydrogen bond]]ing.\n\nThis relatively weak (relative to the covalent bonds within the water molecule itself) attraction results in physical properties such as a relatively high [[boiling point]], because a lot of [[heat]] energy is necessary to break the hydrogen bonds between molecules. For example, [[sulfur]] is the element below oxygen in the periodic table, and its equivalent compound, hydrogen sulfide (H2S) does not have hydrogen bonds, and though it has twice the molecular weight of water, it is a gas at [[room temperature]]. The extra bonding between water molecules also gives liquid water a large [[specific heat capacity]].\n\nHydrogen bonding also gives water an unusual behaviour when freezing. Just like most other materials, the liquid becomes denser with lowering temperature. However, unlike most other materials, when cooled to near freezing point, the presence of hydrogen bonds means that the molecules, as they rearrange to minimise their energy, form a structure that is actually of lower density: hence the solid form, ice, will float in water. In other words, water expands as it freezes (most other materials shrink on solidification). Liquid water reaches its highest density at a temperature of 4 °C. This has an interesting consequence for water life in winter. Water chilled at the surface becomes denser and sinks, forming convection currents that cool the whole water body, but when the temperature of the lake water reaches 4°C, water on the surface, as it chills further, becomes \'\'less dense\'\', and stays as a surface layer which eventually forms ice. Since downward convection of colder water is blocked by the density change, any large body of water frozen in winter will have the bulk of its water still liquid at 4°C beneath the icy surface, allowing fish to survive. This is one of the principal examples of finely-tuned physical properties that support life on Earth that is used as an argument for the [[anthropic principle]].\n\nAnother consequence is that ice will melt if sufficient pressure is applied.\n\n==Cai salaku pangleyur==\nCai ogé ngarupakeun hiji [[pangleyur]] nu hadé alatan polaritasna. Sipat pangleyur cai kacida pentingna dina [[biologi]], sabab loba réaksi biokimiawi anu ngan bisa lumangsung dina kaayaan [[leyuran]] cai (kayaning réaksi dina [[sitoplasma]] jeung na [[getih]]). Cai ogé dipaké dina angkutan [[molekul biologis]]. \n\nNalika sanyawa ionik atawa polar asup kana cai, mangka bakal dikurilingan ku molekul cai. Ukuran molekul cai nu cukup leutik ngamungkinkeun molekul-molekul cai nyulusup sabudeureun hiji molekul \'\'solute\'\'. The partially negative dipoles of the water are attracted to positively charged components of the solute, and vice versa for the positive dipoles. \n\nIn general, ionic and polar substances such as [[acid]]s, [[alcohol]]s, and [[salt]]s are easily soluble in water, and nonpolar substances such as fats and oils are not. Nonpolar molecules stay together in water because it is energetically more favorable for the water molecules to hydrogen bond to each other than to engage in [[van der Waals force|van der Waals interactions]] with nonpolar molecules.\n\nAn example of an ionic solute is [[sodium chloride|table salt]]; the sodium chloride, NaCl, separates into Na+ [[cation]]s and Cl- [[anion]]s, each being surrounded by water molecules. The ions are then easily transported away from their crystalline lattice into solution. An example of a nonionic solute is [[sucrose|table sugar]]. The water dipoles hydrogen bond to the dipolar regions of the sugar molecule and allow it to be carried away into solution.\n\n==Kohési jeung tegangan permukaan==\nBeungkeut hidrogén nu kuat ngajadikeun cai mibanda kakohésifan nu luhur jeung, konsékuénsina, [[tegangan permukaan]]. This is evident when small quantities of water are put onto a nonsoluble surface and the water stays together as drops. This feature is important when water is carried through [[xylem]] up stems in plants; the strong intermolecular attractions hold the water column together, and prevent tension caused by [[transpiration pull]]. Other liquids with lower surface tension would have a higher tendency to "rip", forming vacuum or air pockets and rendering the xylem vessel inoperative.\n\n==Konduktivitas==\nCai \'\'murni\'\' sabenerna ngarupakeun [[insulator]] nu alus ([[konduktor]] goréng), nu hartina \'\'teu\'\' ngalirkeun [[listrik]]. Ku sabab cai boga sipat pangleyur hadé, mimindengna cai téh ngandung \'\'[[solute]]\'\' nu leyur di jerona, utamana uyah. Mun cai mibanda pangotor nu karitu, nya jadi bisa listrik leuwih hadé, sabab pangotor kayaning uyah ngandung [[ion]] bébas dina leyuran cai di mana listrik bisa ngalir.\n\n==Éléktrolisis==\nCai bisa dibeulah jadi unsur-unsur panyusunna, hidrogén jeung oksigén, ku jalan ngalirkeun arus. Prosés ieu disebut \'\'éléktrolisis\'\'. \nMOlekul cai sacara alami peupeus jadi ion H+ jeung OH- nu dibetot ka [[katoda]] jeung [[anoda]]. \nNa katoda, dua ion H+ nyokot éléktron jadi gas H2. Na anoda, opat ion OH- ngagabung sarta ngaleupaskeun gas O2, cai molekular, jeung opat éléktron. Gas ngabulukbuk kana beungeut cai, nu saterusna bisa dikumpulkeun.\n\n==Réaktivitas==\n\nSacara kimiawi, cai téh [[amfotérik]]: bisa meta salaku hiji asam atawa basa. Kadang istilah \'\'hydroxic acid\'\' dipaké nalika cai meta salaku asam dina hiji réaksi kimiawi. Dina pH 7 (nétral), kadar ion [[hidroksida]] (OH-) sarua jeung ion [[hidronium]] (H3O+) atawa ion [[hidrogén]] (H+). Mun [[kasatimbangan]] kaganggu, leyuran jadi asam (kadar ion hidronium leuwih luhur) atawa basa (kadar ion hidroksida leuwih luhur).\n\nCai bisa meta salaku asam atawa basa dina hiji réaksi. Nurutkeun sistim [[Brønsted-Lowry]], asam ditangtukeun salaku spésiés nu nyumbang proton (ion H+) dina hiji réaksi, sedengkeun alkali salaku nu narima proton. Nalika réaksi jeung asam nu leuwih kuat, cai meta salaku alkali, sarta bakal meta salaku asam mun réaksi jeung asam nu leuwih lemah. Pikeun conto, cai bakal nampa hiji H+ ti HCl dina kasatimbangan:\n\n:HCl + H2O → H3O+ + Cl-\n\nAnd so here is acting as an alkali, by receiving an H+ ion. An acid donates a H+ ion, and water can also do this, such as the reaction with NaOH:\n\n:NH3 + H2O → NH4+ + OH-\n\n===pH in Practice===\nIn theory, pure water has a pH of 7. In practice, pure water is very difficult to produce. Water left exposed to air for any length of time will rapidly dissolve carbon dioxide, forming a solution of carbonic acid, with a limiting pH of ~5.7 (reference: Kendall, J. (1916), \'\'Journal of the American Chemical Society\'\' 38 (11): 2460-2466).\n\n==Ngamurnikeun cai==\nNgamurnikeun cai perlu pikeun rupa-rupa kaperluan industri, pon kitu ogé keur konsimsi. Manusa merlukeun cai nu teu loba teuing ngandung uyah atawa nu séjénna. Pangotor nu ilahar kapanggih di antarana bahan kimiawi atawa [[kuman|baktéri]]. Some solutes are acceptable and even desirable for perceived taste enhancement. Water that is suitable for drinking is termed \'\'\'potable water\'\'\'.\n\nGenep métode umum pikeun ngamurnikeun cai:\n#\'\'\'Disaring\'\'\': Water is passed through a [[sieve]] that catches small particles. The tighter the mesh of the sieve, the smaller the particles must be to pass through. Filtering is not sufficient to completely purify water, but it is often a necessary first step, since such particles can interfere with the more thorough purification methods.\n#\'\'\'Digolakkeun\'\'\': Water is heated to its boiling point long enough to inactivate or kill [[microorganism]]s that normally live in water at room temperature. In areas where the water is \"hard\", (containing dissolved calcium salts), boiling decomposes the [[bicarbonate]] ion, resulting in some (but not all) of the dissolved calcium being precipitated in the form of [[calcium carbonate]]. This is the so-called \"fur\" that builds up on kettle elements etc. in hard water areas. With the exception of calcium, boiling does not remove solutes of higher boiling point than water, and in fact increases their concentration (due to some water being lost as vapour)\n#\'\'\'Disaring ku karbon\'\'\': [[Charcoal]], a form of [[carbon]] with a high surface area due to its mode of preparation, adsorbs many compounds, including some toxic compounds. Water is passed through [[Activated carbon|activated charcoal]] to remove such contaminants. This method is most commonly used in household water filters and fish tanks. Household filters for drinking water sometimes also contain [[silver]], trace amounts of silver ions having a bactericidal effect.\n#\'\'\'Disuling\'\'\': [[Distillation]] involves boiling the water to produce water [[vapour]]. The water vapour then rises to a cooled surface where it can condense back into a liquid and be collected. Because the solutes are not normally vaporized, they remain in the boiling solution. Even distillation does not completely purify water, because of contaminants with similar boiling points and droplets of unvaporized liquid carried with the steam. However, 99.9% pure water can be obtained by distillation.\n#\'\'\'Osmosis balik\'\'\': Mechanical pressure is applied to an impure solution to force pure water through a [[semi-permeable membrane]]. The term is \'\'reverse [[osmosis]]\'\', because normal osmosis would result in pure water moving in the other direction to dilute the impurities. Reverse osmosis is theoretically the most thorough method of large-scale water purification available, although perfect semi-permable membranes are difficult to create.\n#\'\'\'Kromatografi panukeur ion\'\'\': In this case, water is passed through a charged resin column that has side chains that trap calcium, magnesium, and other heavy metal ions. In many laboratories, this method of purification has replaced distillation, as it provides a high volume of very pure water more quickly and with less energy use than other processes. Water purified in this way is called \'\'deionized water\'\'.\n\n[[Image:Cai.jpg|right|250px|Cai]]\n\n==Wasting water==\n\'\'\'Wasting water\'\'\' is the misuse of water, i.e. using it unnecessarily. An example is the use of water, particularly water purified to human safe drinking standards, in unnecessary irrigation. Also, in homes, water may be wasted if the [[toilet]] is flushed unnecessarily or the tank leaks. Causing water to become [[pollution|polluted]] may be the biggest single misuse of water. To the extent that a pollutant limits other uses of the water, it becomes a waste of the resource, regardless of benefits to the polluter. However, in some cities, such as [[Hong Kong]], sea water is extensively used for flushing toilet citywide as a mean to conserve fresh water resources.\n\n==Mitologi==\nCai ngarupakeun salasahiji tina opat [[unsur klasik]] babarengan jeung [[seuneu]], [[taneuh]], jeung [[hawa]], nu diajénan salaku [[ylem]], atawa unsur dasar [[mayapada]]. Water was considered cold and moist. In the theory of the four [[bodily humour]]s, water was associated with [[phlegm]]. \n\nCai ogé ngarupakeun salasahiji ti [[Opat Unsur]] dina [[Taoisme]] [[Cina]], bareng jeung [[taneuh]], [[seuneu]], [[kai]], jeung [[logam]].\n\n==Ajén cai dina agama==\nCai dianggap nyucikeun dina rupa-rupa agama, kayaning [[Islam]], [[Yahudi]], jeung [[Sikh]]. PIkeun conto, [[wudu]] dina Islam jeung [[baptis]] di garéja [[Kristen]] migunakeun cai bersih/murni. Nya kitu ogé dina ngamandian mayit pikeun Islam jeung Yahudi.\n\n==Dihidrogén monoksida==\nPara [[kimiawan]] sakapeung ngaheureuykeun cai salaku \'\'\'dihidrogén monoksida\'\'\' atawa \'\'\'[[DHMO]]\'\'\', ngaran kovalén sistimatis pikeun ieu molekul, hususna dina [[parodi]] of chemical research that call for this \"lethal chemical\" to be banned. Dina taun 2004, kota [[Aliso Viejo, California]] ampir ngalarang cangkir \'\'foam\'\' satutasna katalungtik yén DHMO geus dipaké dina produksina (tempo [http://slashdot.org/articles/04/03/16/1419252.shtml?tid=133&tid=186]).\n\nNgaran asam sistimatis pikeun cai nyéta \'\'\'asam hidroksida\'\'\' (\'\'hydroxic acid\'\' atawa \'\'hydroxilic acid\'\'), najan istilah ieu jarang dipaké.\n\nSarupa jeung éta, ngaran alkali sistimatis pikeun cai nyéta \'\'\'hidrogén hidroksida\'\'\' (\'\'hydrogen hydroxide\'\') – boh ngaran asam atawa alkali pikeun cai mémang aya sabab cai bisa meta salaku asam atawa alkali, gumantung kakuatan asam atawa alkali lawan réaksina ([[amfotér]]).\n\n==Hukum jeung pengembangan cai==\nWorld Water Development Report [[UNESCO]] (WWDR, 2003) tina World Water Assessment Program nunjukkeun yén 20 taun kahareup dunya bakal nyanghareupan an unprecedented lack of drinking water. Jumlah cai nu bisa aya pikeun masarakat ditaker nurun nepi ka 30%. Nu jadi sabab nyaéta kontaminasi, [[pamanasan global]], jeung masalah politis.\n\n40% pangeusi dunya kakurangan cai pikeun [[higiéne]] nu minimal. Leuwih ti 2,2 juta urang maot dina taun [[2000]] alatan [[kasakit]] nu patali jeung konsumsi cai nu kacemar. Taun 2004, the [[United Kingdom|UK]] [[charity]] [[WaterAid]] ngalaporkeun yén unggal 15 detik aya saurang budak nu maot alatan kasakit nu patali jeung cai, padahal éta kasakit kagolongkeun babari dicegahna.\n\nThe report indicates large global disparities in the raw volume of available water: from 10 m³ per person per year in [[Kuwait]] to 812.121 m³ in [[French Guiana]]. However, richer countries such as Kuwait can more easily cope with low water availability.\n\nIn the [[United States]] [[water law]] is divided between two [[legal doctrine]]s: [[riparian water rights]], used in the eastern and southern states where there is an abundance of water, and the [[appropriation doctrine]] (or [[Colorado doctrine]]), used in the arid western states.\n\n==Kaén jeung pakéan==\n\nSababaraha rupa [[kaén]] kayaning [[anduk]] sacara husus dijieun pikeun nyerep cai.\n\nSababaraha [[pakéan]] dijieun pikeun ngajaga tina cai (conto [[jas hujan]]), atawa pikeun digunakeun dina cai (\'\'[[swimsuit]]\'\').\n\n== Tempo ogé ==\n* [[Cai mineral]]\n** [[Arrowhead Water]]\n** [[Aquafina]]\n* [[Dehidrasi]]\n* [[DHMO|Dihidrogén monoksida (DHMO)]]\n* [[Cai sulingan ganda]]\n* [[Cai nginum]]\n* [[Drought]]\n* [[Evapotranspiration]]\n* [[Fresh water]]\n* [[Banjir]]\n* [[Cai beurat]]\n* [[Cai suci]]\n* [[Hidrografi]]\n* [[Hidrologi]]\n* [[Irigasi]]\n* [[Mpemba effect]] - bisa teu cipanas beku leuwih cepet batan citiis?\n* [[Polywater theory]]\n* [[precipitation (meteorology)|Precipitation]]\n* [[Hujan]]\n* [[Cilaut]]\n* [[Trasvasement]]\n* [[Wastewater]]\n* [[Mutu cai]]\n\n== Tumbu kaluar ==\n* [http://www.worldwaterforum.org/ World Water Forum]\n* [http://www.unesco.org/water/wwap/ World Water Assessment Program]\n* [http://unesdoc.unesco.org/images/0012/001295/129556e.pdf United Nations\' World Water Development Report]\n* [http://www.lsbu.ac.uk/water/ Water Structure and Behaviour]\n* [http://www.sahra.arizona.edu/newswatch/ SAHRA - Global Water Newswatch]\n* [http://www.dhmo.org/ A spoof site on the \"dangers\" of dihydrogen monoxide]\n* [http://www.rsd-solar.com/ Water distillation using only the sun]\n* [http://www.siwi.org/ Stockholm International Water Institute] (SIWI)\n\n[[ar:ماء]] [[ca:Aigua]] [[cy:Dŵr]] [[da:Vand]] [[de:Wasser]] [[en:Water]] [[eo:Akvo]] [[es:Agua]] [[et:Vesi]] [[fi:Vesi]] [[fr:Eau]] [[id:Air]] [[ja:水]] [[ko:물]] [[la:Aqua]] [[ms:Air]] [[nah:Atl]] [[nds:Water]] [[nl:water]] [[pl:Woda]] [[ru:Вода]] [[simple:Water]] [[sl:voda]] [[sv:Vatten]] [[tokipona:telo]] [[vo:Vat]] [[zh:水]] [[he:מים]]\n\n[[Category:Wujud cai]]\n[[Category:Sanyawa anorganik]]\n[[Category:Dahareun jeung inuman]]\n[[Category:Bahan]]','',3,'Kandar','20040826090111','',0,0,0,0,0.081040812694,'20050216033918','79959173909888'); INSERT INTO cur VALUES (1207,0,'Degrees_of_freedom','#REDIRECT [[Tingkat kabebasan]]\n','Degrees of freedom dipindahkeun ka Tingkat kabebasan',13,'Budhi','20040817072918','',0,1,0,1,0.393449279846111,'20040817072918','79959182927081'); INSERT INTO cur VALUES (1208,0,'Parameter_statistik','\'\'\'Parameter statistik\'\'\' nyaeta parameter indeks tina kulawarga [[probability distribution|sebaran probabiliti]]. \n\nDiantara kulawarga parameterisasi distribusi nyaeta [[sebaran normal]], [[Poisson distribution|sebaran Poisson]], [[sebaran binomial]], jeung [[sebaran eksponensial]]. Kulawarga [[sebaran normal]] ngabogaan dua parameter, nyaeta [[mean]] jeung [[varian]]: lamun dina kasus husus, sebaran dipikanyaho sacara pasti. Kulawarga [[sebaran chi-kuadrat]], di bagean sejen, ngan ngabogaan hiji parameter, nyaeta tingkat kabebasan.\n\nDina [[statistical inference|kaputusan statistik]], parameter kadang-kadang dicokot tina data nu teu ka observasi, sarta dina ieu kasus statistikawan kudu narik kasimpulan dumasar kana observasi sebaran variabel random nurut kana sebaran probabiliti dina patarosan, atawa leuwih pastina nangtukeun dumasar kana sampel random nu cokot tina populasi nu keur ditalungtik. Dina kaayaan sejen, paramater bisa pasti sacara alami tina prosedur sampling atawa tipe prosedur statistik nu dipake (contona, jumlah [[tingkat kabebasan]] dina [[Pearson\'s chi-squared test|tes chi-kuadrat Pearson]]).','',13,'Budhi','20040907094626','',0,0,0,0,0.17897799992,'20040907094626','79959092905373'); INSERT INTO cur VALUES (1209,0,'Sebaran_beta','Dina [[tiori probabiliti]] jeung [[statistik]], \'\'\'sebaran beta\'\'\' nyaeta [[probability distribution]] kontinyu dina [[probability density function]] nu dihartikeun dina interval [0, 1]:\n\n: f(x) = [\\mbox{constant}]\\cdot x^{a-1}(1-x)^{b-1}.\n\nnumana \'\'a\'\' jeung \'\'b\'\' ngarupakeun parameter nu kudu leuwih gede ti nol.\n\nLamun \"angger\" kaasup sacara eksplisit, densiti ditempokeun saperti:\n\n: f(x) = \\frac{x^{a-1}(1-x)^{b-1}}{\\int_0^1 u^{a-1} (1-u)^{b-1}\\, du}\n= \\frac{\\Gamma(a+b)}{\\Gamma(a)\\Gamma(b)}\\, x^{a-1}(1-x)^{b-1} \n= \\frac{1}{B(a,b)}\\, x^{a-1}(1-x)^{b-1} \n\nnumana Γ jeung B nyaeta [[fungsi gamma]] jeung [[fungsi beta]].\n\nKasus husus sebaran beta, lamun \'\'a\'\' = 1 jeung \'\'b\'\' = 1, nyaeta [[sebaran seragam]] standar. \n\n[[Nilai ekspektasi]] jeung [[varian]] beta [[variabel random]] \'\'X\'\' nu mibanda parameter \'\'a\'\' jeung \'\'b\'\' dirumuskeun ku:\n\n: \\mbox{E}(X) = \\frac{a}{a+b}, \n: \\mbox{var}(X) = \\frac{ab}{(a+b)^2(a+b+1)}. \n\nDi bagean sejen, lamun [[nilai ekspektasi]] jeung [[varian]] beta [[variabel random]] \'\'X\'\' dipikanyaho, parameter \'\'a\'\' jeung \'\'b\'\' diitung make rumus,k.:\n\n: a = \\mbox{E}(X)\\left(\\frac{\\mbox{E}(X)}{\\mbox{var}(X)}[1-\\mbox{E}(X)]-1\\right), \n\n: b = a\\frac{1-\\mbox{E}(X)}{\\mbox{E}(X)} \n\nnumana 0 < E(\'\'X\'\') < 1 jeung 0 < var(\'\'X\'\') < E(\'\'X\'\') (1 − E(\'\'X\'\')).\n\n[[Category:Probability distributions]]\n[[de:Betaverteilung]]\n[[es:Distribución beta]]','',13,'Budhi','20041224211257','',0,0,1,0,0.233825362396,'20041224211257','79958775788742'); INSERT INTO cur VALUES (1210,0,'Uji_kuadrat-chi_Pearson','\'\'\'Tes [[Karl Pearson|Pearson\'s]] chi-kuadrat\'\'\' (χ2) salah sahiji variasi tina [[tes chi-kuadrat]] – procedure [[statistik]] nu hasilna di-\'\'evaluasi\'\' dumasar kana [[sebaran chi-kuadrat]]. It tests a [[null hypothesis]] that the relative frequencies of occurrence of observed events follow a specified frequency distribution. The events must be mutually exclusive. One of the simplest examples is the hypothesis that an ordinary six-sided die is \"fair\", i.e., all six outcomes occur equally often.\nChi-square is calculated by finding the difference between each observed and theoretical frequency, squaring them, dividing each by the theoretical frequency, and taking the sum of the results:\n\n: \\chi^2 = \\sum {(O - E)^2 \\over E}\n\nwhere:\n\n:\'\'O\'\' = an observed frequency\n:\'\'E\'\' = an expected (theoretical) frequency, asserted by the null hypothesis\n\nFor example, to test the hypothesis that a random sample of 100 people has been drawn from a population in which men and women are equal in frequency, the observed number of men and women would be compared to the theoretical frequencies of 50 men and 50 women. If there were 45 men in the sample and 55 women:\n\n: \\chi^2 = {(45 - 50)^2 \\over 50} + {(55 - 50)^2 \\over 50} = 1\n\nThere is one [[degrees of freedom|degree of freedom]] in the comparison (since either difference between observed and expected frequencies, once known, dictates the other). Consultation of the [[sebaran chi-kuadrat]] for 1 degree of freedom shows that the [[probability]] of observing this difference if men and women are equally numerous in the population is greater than 0.3. This probability is higher than conventional criteria for [[statistical significance]], so normally we would accept the null hypothesis that the number of men in the population is the same as the number of women.\n\nPearson\'s chi-square is used to assess two types of comparison: tests of goodness of fit and tests of independence. A test of goodness of fit establishes whether or not an observed [[sebaran frekuensi]] differs from a theoretical distribution. A test of independence assesses whether paired observations on two variables are independent of each other – for example, whether people from different regions differ in the frequecy with which they report that they support a political candidate.\n\nPearson\'s chi-square is the original and most widely-used chi-square test. \n\nThe null distribution of the Pearson statistic is only approximated as a chi-square distribution. This approximation arises as the true distribution, under the null hypothesis, of the expected value is given by a Binomial distribution:\n: E =^d Bi(n,p) \nwhere:\n:\'\'p\'\' = probability, under the null hypothesis\n:\'\'n\'\' = number of samples\nIn the above example the hypothesised probability of a male observation is 0.5, with 100 samples. Thus we expect to observe 50 males. \n\nWhen comparing the Pearson test statistic against a chi-squared distribution, the above binomial distribution is approximated as a Gaussian (normal) distribution:\n\n: \\mbox{Bin}(n,p) \\approx^d \\mbox{N}(np, np(1-p)) \n\nBy definition, a sum of k standard normal variates, Z, is distributed as chi-square with k degrees of freedom:\n\n: \\sum_{i=1}^k Z^2_i =^d \\chi^2_k \n\nIn cases whereby the expected value, E, is found to be small (indicating either a small underlying population probability, or a small number of observations), the normal approximation of the binomial distribution can fail, and in such cases it is found to be more appropriate to use a [[likelihood-ratio test|likelihood ratio]]-based test statistic.\n\nSee also [[Yates\' correction for continuity]], [[median test]].','',13,'Budhi','20050104235220','',0,0,0,0,0.28805477884,'20050104235220','79949895764779'); INSERT INTO cur VALUES (1211,0,'Integer','The \'\'\'integers\'\'\' consist of the [[natural numbers]] (0, 1, 2, ...) and their [[negative and non-negative numbers|negatives]] (−1, −2, −3, ...; −0 is equal to 0 and therefore not included as a separate integer). The [[set]] of all integers is usually denoted in [[mathematics]] by \'\'\'Z\'\'\' (or Z in [[blackboard bold]], \\mathbb{Z}), which stands for \'\'Zahlen\'\' ([[German language|German]] for \"numbers\"). They are also known as the \'\'\'whole numbers\'\'\', although that term is also used to refer only to the positive integers (with or without [[zero]]).\n\nIntegers can be added, subtracted and multiplied, the result being an integer.\nAny two integers can be compared. Introducing the \nnegative integers makes it possible to solve all equations of the form\n:\'\'a\'\' + \'\'x\'\' = \'\'b\'\'\n:where \'\'a\'\' and \'\'b\'\' are constant natural numbers for the unknown \'\'x\'\'. If \'\'x\'\' is constrained to the natural numbers, only some of these equations are solvable.\n\nMathematicians express the fact that all the usual laws of arithmetic are valid in the integers by saying that (\'\'\'Z\'\'\', +, *) is a commutative [[ring (algebra)|ring]].\n\n\'\'\'Z\'\'\' is a [[total order|totally ordered set]] without upper or lower bound. The ordering of \'\'\'Z\'\'\' is given by\n: ... < −2 < −1 < 0 < 1 < 2 < ...\nWe call an integer \'\'positive\'\' if it is greater than zero; zero itself is not considered to be positive. The order is compatible with the algebraic operations in the following way:\n# if \'\'a\'\' < \'\'b\'\' and \'\'c\'\' < \'\'d\'\', then \'\'a\'\' + \'\'c\'\' < \'\'b\'\' + \'\'d\'\'\n# if \'\'a\'\' < \'\'b\'\' and 0 < \'\'c\'\', then \'\'ac\'\' < \'\'bc\'\'\n\nLike the natural numbers, the integers form a [[countably infinite]] set.\n\nThe integers do not form a [[field (mathematics)|field]] since for instance there is no integer \'\'x\'\' such that 2\'\'x\'\' = 1. The smallest field containing the integers is the [[rational number]]s.\n\nAn important property of the integers is \'\'division with remainder\'\': given two integers \'\'a\'\' and \'\'b\'\' with \'\'b\'\'≠0, we can always find integers \'\'q\'\' and \'\'r\'\' such that\n:\'\'a\'\' = \'\'b\'\' \'\'q\'\' + \'\'r\'\'\nand such that 0 <= \'\'r\'\' < |\'\'b\'\'| (see [[absolute value]]). \'\'q\'\' is called the \'\'quotient\'\' and \'\'r\'\' is called the \'\'remainder\'\' resulting from division of \'\'a\'\' by \'\'b\'\'. The numbers \'\'q\'\' and \'\'r\'\' are uniquely determined by \'\'a\'\' and \'\'b\'\'. This shows that the greatest common divisor of two integers \'\'a\'\' and \'\'b\'\' is equal to the greatest common divisor of the two numbers, namely, \'\'b\'\' and \'\'r\'\', with smaller sum. This observation is the base for the [[Euclidean algorithm]] for computing [[greatest common divisor]]s.\n\nAll of this can be abbreviated by saying that \'\'\'Z\'\'\' is a [[Euclidean domain]].\nThis implies that \'\'\'Z\'\'\' is a [[principal ideal domain]] and that whole numbers can be written as products of [[prime number|primes]] in an essentially unique way. This is the [[fundamental theorem of arithmetic]].\n\nThe branch of [[mathematics]] which studies the integers is called [[number theory]].\n----\nAn \'\'\'integer\'\'\' is often one of the primitive [[datatype]]s in [[computer language]]s. However, these \"integers\" can only represent a subset of all mathematical integers, since \"real-world\" computers are of finite capacity. Integer datatypes are typically implemented using a fixed number of [[bit]]s, and even variable-length representations eventually run out of storage space when trying to represent especially large numbers. On the other hand, theoretical models of [[digital computer]]s, e.g., [[Turing machine]]s, usually do have infinite (but only [[countable]]) capacity.\n\nKeur informasi nu leuwih jentre, tempo [[Integer (computer science)]].\n\n{{quantity}}\n[[Category:Integers]] [[Category:Number theory]] [[Category:Set theory]][[Category:Group theory]]\n\n[[da:Heltal]]\n[[de:Ganze Zahlen]]\n[[et:Täisarv]]\n[[eo:Entjera nombro]]\n[[es:Número entero]]\n[[fr:Entier relatif]]\n[[id:Bilangan bulat]]\n[[is:Heiltölur]]\n[[it:Numeri interi]]\n[[ja:整数]]\n[[nl:Geheel getal]]\n[[no:Heltall]]\n[[pl:Liczby ca%B3kowite]]\n[[pt:Inteiros]]\n[[sl:Celo število]]\n[[sv:Heltal]]\n[[zh:%E6%95%B4%E6%95%B0]]','',13,'Budhi','20040901003714','',0,0,0,0,0.512754702248,'20040901003714','79959098996285'); INSERT INTO cur VALUES (1212,0,'Characteristic_function','Sababaraha matematikawan ngagunakeun frase \'\'\'characteristic function\'\'\' nu sarua jeung \"[[indicator function]]\". The indicator function of a [[subset]] \'\'A\'\' of a [[set]] \'\'B\'\' is the [[Fungsi (matematik)|function]] with domain \'\'B\'\', whose value is 1 at each point in \'\'A\'\' and 0 at each point that is in \'\'B\'\' but not in \'\'A\'\'.\n\n----\n\nIn [[probability theory]], the \'\'\'characteristic function\'\'\' of any [[probability distribution]] on the [[real number|real]] line is given by the following formula, where \'\'X\'\' is any [[random variable]] with the distribution in question:\n\n:\\varphi_X(t) = \\operatorname{E}\\left(e^{itX}\\right) \n = \\int_\\Omega e^{itx}\\, dF_X(x)\n = \\int_{-\\infty}^{\\infty} f_X(x)\\, e^{itx}\\,dx.\n\nHere \'\'t\'\' is a [[real number]], E lambang [[nilai ekspektasi]] and \'\'F\'\' is the [[cumulative distribution function]]. The last form is valid only when \'\'f\'\'--the [[probability density function]]--exists. The form preceding it is a [[Riemann-Stieltjes integral]] and is valid regardless of whether a density function exists.\n\nIf \'\'X\'\' is a [[vector space|vector]]-valued random variable, one takes the argument \'\'t\'\' to be a vector and \'\'tX\'\' to be a [[dot product]].\n\nA characteristic function exists for any random variable. More than that, there is a bijection between cumulative probability functions and characteristic functions. In other words, two probability distributions never share the same characteristic function.\n\nGiven a characteristic function φ, it is possible to reconstruct the corresponding cumulative probability distribution function \'\'F\'\':\n\n:F_X(y) - F_X(x) = \\lim_{\\tau \\to +\\infty} \\frac{1} {2\\pi}\n \\int_{-\\tau}^{+\\tau} \\frac{e^{-itx} - e^{-ity}} {it}\\, \\varphi_X(t)\\, dt.\n\nIn general this is an [[improper integral]]; the function being integrated may be only conditionally integrable rather than [[Lebesgue integral|Lebesgue-integrable]], i.e. the integral of its absolute value may be infinite.\n\nCharacteristic functions are used in the most frequently seen proof of the [[central limit theorem]].\n\nCharacteristic functions can also be used to find [[moment (mathematics)|moments]] of random variable. Provided that \'\'n\'\'-th moment exists, characteristic function can be differentiated \'\'n\'\' times and\n\n:\\operatorname{E}\\left(X^n\\right) = i^n\\, \\varphi_X^{(n)}(0)\n = i^n\\, \\left.\\frac{d^n}{dt^n}\\right|_{t=0} \\varphi_X(t)\n\nRelated concepts include the [[moment-generating function]] and the [[probability-generating function]].\n\nThe characteristic function is closely related to the [[Fourier transform]]:\nthe characteristic function of a distribution with density function \'\'f\'\' is proportional to the inverse Fourier transform of \'\'f\'\'.','',13,'Budhi','20041224212708','',0,0,1,0,0.90464936658,'20041224212708','79958775787291'); INSERT INTO cur VALUES (1213,0,'Tes_chi-kuadrat','\'\'\'Tes chi-kuadrat\'\'\' nyaeta [[hypothesis test]] numana tes statistik ngabogaan [[sebaran chi-kuadrat]] lamun null hipotesisna bener.\n\nIeu kaasup:\n\n* [[Uji kuadrat-chi Pearson]]\n* \'\'Sababaraha\'\' [[likelihood-ratio test]] nyaeta \'\'ngadeukeutan\'\' tes chi-kuadrat lamun ukuran sampelna gede. Geus ilahar dipake dina [[logistic regression]]. Tes rasio-likelihood nu teu pakait jeung tes chi-kuadrat; contona: tes-\'\'F\'\' dina analisa varian sarta tes-\'\'t\'\' ngarupakeun tes resio-likelihood, sanajan statistik tes teu ngabogaan sebaran chi-kuadrat dina kaayaan null hipotesis.\n* [[Yates\' chi-square test]], atawa koreksi Yates keur kontinyu\n* [[Mantel-Haenszel chi-square test]]\n* [[linear-by-linear association chi-square test]]\n\n:\'\' please add tests, history, etc. \'\'\n\n\n{{pondok}}\n\n[[lv:Či kvadrāta kritērijs]]\n[[pl:test zgodności chi-kwadrat]]','',13,'Budhi','20041224204606','',0,0,1,0,0.850748272078,'20050303211247','79958775795393'); INSERT INTO cur VALUES (1214,0,'Régrési_liniér','Dina [[statistik]], \'\'\'linear regression\'\'\' is a method of estimating the conditional [[nilai ekspektasi]] of one variable \'\'y\'\' given the values of some other variable or variables \'\'x\'\'.\nThe variable of interest, \'\'y\'\', is conventionally called the \"[[dependent variable]]\".\nThe terms \"endogenous variable\" and \"output variable\" are also used.\nThe other variables \'\'x\'\' are called the \"[[independent variable]]s\".\nThe terms \"exogenous variables\" and \"input variables\" are also used.\nThe dependent and independent variables may be scalars or vectors.\nIf the independent variable is a vector, one speaks of \'\'multiple linear regression\'\'.\n\nThe term \'\'independent\'\' variable suggests that its value can be chosen at will, and the \'\'dependent\'\' variable is an effect, i.e., causally dependent on the independent variable, as in a [[stimulus-response model]]. Although many linear regression models are formulated as models of cause and effect, the direction of causation may just as well go the other way, or indeed there need not be any causal relation at all.\n\n\'\'Regression\'\', in general, is the problem of estimating a conditional expected value. Linear regression is called \"linear\" because the relation of the dependent to the independent variables is a [[linear function]] of some parameters. Regression models which are not a linear function of the parameters are called [[nonlinear regression]] models. A [[neural network]] is an example of a nonlinear regression [[model]].\n\nStill more generally, regression may be viewed as a special case of [[density estimation]]. The [[joint probability|joint distribution]] of the dependent and independent variables can be constructed from the [[conditional probability|conditional distribution]] of the dependent variable and the [[marginal probability|marginal distribution]] of the independent variables.\nIn some problems, it is convenient to work in the other direction: \nfrom the joint distribution, the conditional distribution of the dependent variable can be derived.\n\n==Historical remarks==\n\nThe earliest form of linear regression was the [[method of least squares]],\nwhich was published by [[Adrien Marie Legendre|Legendre]] in 1805,\nand by [[Carl Friedrich Gauss|Gauss]] in 1809.\nThe term \"least squares\" is from Legendre\'s term, \'\'moindres quarrés\'\'.\nHowever, Gauss claimed that he had known the method since 1795.\n\nLegendre and Gauss both applied the method to the problem of determining, from astronomical observations, the orbits of bodies about the sun.\n[[Leonhard Euler|Euler]] had worked on the same problem (1748) without success.\nGauss published a further development of the theory of least squares in 1821, including a version of the [[Gauss-Markov theorem]].\n\nThe term \"reversion\" was used in the [[nineteenth century]] to describe a biological phenomenon, namely that the progeny of exceptional individuals tend on average to be less exceptional than their parents, and more like their more distant ancestors. [[Francis Galton]] studied this phenomenon, and applied the slightly misleading term \"[[regression toward the mean|regression towards mediocrity]]\" to it (parents of exceptional individuals also tend on average to be less exceptional than their children). For Galton, regression had only this biological meaning, but his work (1877, 1885) was extended by [[Karl Pearson]] and [[George Udny Yule|G.U. Yule]] to a more general statistical context (1897, 1903). In the work of Pearson and Yule, the joint distribution of the dependent and independent variables is assumed to be Gaussian. This assumption was weakened by [[Ronald A. Fisher|R.A. Fisher]] in his works of 1922 and 1925.\nFisher assumed that the conditional distribution of the dependent variable is Gaussian, but the joint distribution need not be. In this respect, Fisher\'s assumption is closer to Gauss\'s formulation of 1821.\n\n==Statement of the linear regression model==\n\nA linear regression model is typically stated in the form\n\n: y = \\alpha + \\beta x + \\varepsilon \n\nThe right hand side may take other forms, but generally comprises a [[linear combination]] of the parameters, here denoted α and β. The term ε represents the unpredicted or unexplained variation in the dependent variable; it is conventionally called the \"error\" whether it is really a [[measurement error]] or not. The error term is conventionally assumed to have [[nilai ekspektasi]] equal to zero, as a nonzero expected value could be absorbed into α. See also [[errors and residuals in statistics]]; the difference between an error and a residual is also dealt with below.\n\nAn equivalent formulation which explicitly shows the linear regression as a model of conditional expectation is\n\n: \\mbox{E}(y|x) = \\alpha + \\beta x \\, \n\nwith the [[conditional probability|conditional distribution]] of \'\'y\'\' given \'\'x\'\' essentially the same as the distribution of the error term.\n\nA linear regression model need not be affine, let alone linear, in the independent variables \'\'x\'\'. For example, \n\n: y = \\alpha + \\beta x + \\gamma x^2 + \\varepsilon\n\nis a linear regression model, for the right-hand side is a linear combination of the parameters α, β, and γ. In this case it is useful to think of \'\'x\'\'2 as a new independent variable, formed by modifying the original variable \'\'x\'\'. Indeed, any linear combination of functions \'\'f\'\'(\'\'x\'\'), \'\'g\'\'(\'\'x\'\'), \'\'h\'\'(\'\'x\'\'), ..., is linear regression model, \nso long as these functions do not have any free parameters (otherwise the model is generally a nonlinear regression model). The least-squares estimates of α, β, and γ are linear in the response variable \'\'y\'\', and nonlinear \'\'x\'\' (they are nonlinear in \'\'x\'\' even if the γ and α terms are absent; if only β were present then doubling all observed \'\'x\'\' values would multiply the least-squares estimate of β by 1/2).\n\n== Parameter estimation ==\n\nOften in linear regression problems statisticians rely on the [[Carl Friedrich Gauss|Gauss]]-[[Andrei Andreevich Markov|Markov]] assumptions:\n* The random errors ε\'\'i\'\' have expected value 0.\n* The random errors ε\'\'i\'\' are uncorrelated (this is weaker than an assumption of [[statistical independence|probabilistic independence]]).\n* Kasalahan random ε\'\'i\'\' ngarupakeun \"homoscedastic\", dina hal ieu, sakabehna mibanda [[varian]] nu sarua.\n(See also [[Gauss-Markov theorem]]. That result says that under the assumptions above, least-squares estimators are in a certain sense optimal.)\n\nSometimes stronger assumptions are relied on:\n* The random errors ε\'\'i\'\' have expected value 0.\n* They are [[statistical independence|independent]].\n* Maranehna [[sebaran normal|kasebar normal]].\n* Sakabehna mibanda varian nu sarua.\n\nIf \'\'x\'\'\'\'i\'\' is a vector we can take the product β\'\'x\'\'\'\'i\'\' to be a \"dot-product\".\n\nA statistician will usually \'\'\'estimate\'\'\' the unobservable values of the parameters α and β by the [[least squares|\'\'\'method of least squares\'\'\']], which consists of finding the values of \'\'a\'\' and \'\'b\'\' that minimize the sum of squares of the \'\'\'residuals\'\'\'\n\n: e_i = y_i - (a + bx_i).\n\nThose values of \'\'a\'\' and \'\'b\'\' are the \"least-squares estimates.\" The residuals may be regarded as estimates of the errors; see also [[errors and residuals in statistics]]. \n\nNotice that, whereas the errors are independent, the residuals cannot be independent because the use of least-squares estimates implies that the sum of the residuals must be 0, and the dot-product of the vector of residuals with the vector of x-values must be 0, i.e., we must have\n\n: e_1 + \\cdots + e_n = 0\n\nand\n\n: e_1 x_1 + \\cdots + e_n x_n = 0.\n\nThese two linear constraints imply that the vector of residuals must lie within a certain (\'\'n\'\' − 2)-dimensional subspace of R\'\'n\'\'; hence we say that there are \"\'\'n\'\' − 2 degrees of freedom for error\". If one assumes the errors are normally distributed and independent, then it can be shown to follow that 1) the sum of squares of residuals\n\n: e_1^2 + \\cdots + e_n^2\n\nis distributed as\n\n: \\sigma^2 \\chi^2_{n - 2},\n\ni.e., the sum of squares divided by the error-variance σ2, has a [[sebaran chi-kuadrat]] with \'\'n\'\' − 2 degrees of freedom, and 2) the sum of squares of residuals is actually probabilistically independent of the estimates \'\'a\'\', \'\'b\'\' of the parameters α and β.\n\nThese facts make it possible to use [[sebaran-t student]] with \'\'n\'\' − 2 degrees of freedom (so named in honor of the pseudonymous \"[[William Sealey Gosset|Student]]\") to find confidence intervals for α and β.\n\nDenote by capital Y the column vector whose ith entry is yi, and by capital X the \'\'n\'\'×2 matrix whose second column contains the xi as its ith entry, and whose first column contains n 1s. Let ε be the column vector containing the errors εi. Let δ and d be respectively the 2×1 column vector containing α and β and the 2×1 column vector containing the estimates a and b. Then the model can be written as\n\n: Y = X \\delta + \\varepsilon\n\nwhere ε is normally distributed with expected value 0 (i.e., a column vector of 0s) and variance σ2 In, where In is the n×n identity matrix. The matrix Xd (where (remember) d is the vector of estimates) is then the orthogonal projection of Y onto the column space of X.\n\nThen it can be shown that\n\n: d = (X\' X)^{-1}\\; X\' Y\n\n(where X\' is the transpose of X) and the sum of squares of residuals is\n\n: Y\' (I_n - X (X\' X)^{-1} X\')\\, Y\n\nThe fact that the matrix X(X\'X)-1X\' is a [[symmetric matrix|symmetric]] [[idempotent]] matrix is incessantly relied on both in computations and in proofs of theorems. The linearity of d as a function of the vector Y, expressed above by saying d = (X\' X)-1 X\' Y, is the reason why this is called \"linear\" regression. Nonlinear regression uses nonlinear methods of estimation.\n\nThe matrix In - X (X\' X)-1 X\' that appears above is a symmetric idempotent matrix of rank n - 2. Here is an example of the use of that fact in the theory of linear regression. The finite-dimensional [[spectral theorem]] of [[linear algebra]] says that any real symmetric matrix M can be diagonalized by an [[orthogonal matrix]] G, i.e., the matrix G\'MG is a diagonal matrix. If the matrix M is also idempotent, then the diagonal entries in G\'MG must be idempotent numbers. Only two real numbers are idempotent: 0 and 1. So In-X(X\'X)-1X\', after diagonalization, has \'\'n\'\' − 2 0s and two 1s on the diagonal. That is most of the work in showing that the sum of squares of residuals has a chi-square distribution with n−2 degrees of freedom.\n\n:\'\'Note: A useful alternative to linear regression is [[robust regression]] in which mean [[approximation error|absolute error]] is minimized instead of mean squared error as in linear regression. Robust regression is computationally much more intensive than linear regression and is somewhat more difficult to implement as well.\'\'\n\n=== Summarizing the data ===\n\nWe sum the observations, the squares of the \'\'Y\'\'s and \'\'X\'\'s and the products \'\'XY\'\' to obtain the following quantities.\n\n: S_X = x_1 + x_2 + \\cdots + x_n\nand S_Y similarly.\n: S_{XX} = x_1^2 + x_2^2 + \\cdots + x_n^2\nand SYY similarly.\n: S_{XY} = x_1 y_1 + x_2 y_2 + \\cdots + x_n y_n\n\n=== Estimating beta ===\n\nWe use the summary statistics above to calculate b, the estimate of beta.\n\n: b = {n S_{XY} - S_X S_Y \\over n S_{XX} - S_X S_X}\n\n=== Estimating alpha ===\n\nWe use the estimate of beta and the other statistics to estimate alpha by:\n\n: a = {S_Y - b S_X \\over n}\n\n=== Displaying the residuals ===\n\nThe first method of displaying the residuals use the [[histogram]] or [[Cumulative distribution function|cumulative distribution]] to depict the similarity (or lack thereof) to a [[normal distribution]]. Non-normality suggests that the model may not be a good summary description of the data.\n\nWe plot the residuals,\n\n(y - \\hat{a} - \\hat{b}x)\n\nagainst the independent variable, \'\'x\'\'. There should be no discernible trend or pattern if the model is satisfactory for this data. Some of the possible problems are:\n*Residuals increase (or decrease) as the independent variable increases -- indicates mistakes in the calculations -- find the mistakes and correct them.\n*Residuals first rise and then fall (or first fall and then rise) -- indicates that the appropriate model is (at least) quadratic. See [[polynomial regression]].\n*One residual is much larger than the others and opposite in sign -- suggests that there is one unusual observation which is distorting the fit -- \n**Verify its value before publishing \'\'or\'\'\n**Eliminate it, document your decision to do so, and recalculate the statistics.\n:[[Studentized residual]]s can be used in [[outlier]] detection.\n\n=== Statistik tambahan ===\n\nJumlah kuadrat simpangan bisa dibagi-bagi saperti dina [[analisa varian|ANOVA]] keur nembongkeun yen bagean tina dispersi variabel terikat bisa diterangkeun ku variabel bebas.\n\n\'\'\'Koefisien korelasi\'\'\', r, bisa diitung ku\n: r = {n S_{XY} - S_X S_Y \\over \\sqrt{(n S_{XX} - S_X^2) (n S_{YY} - S_Y^2)}}\n\nStatistik ieu nembongkeun ukuran sakumaha hade garis lempeng keur nerangkeun data. Nilai nu ngadeukeutan kana angka nol nembongkeun yen model teu epektip. r2 ngarupakeun interpreati nu remen dipake salaku bagean tina variabiliti nu diterangkeun ku variabel bebas, X\n\n==References==\n\n===Historical===\n\n* [[Adrien-Marie Legendre|A.M. Legendre]]. \'\'Nouvelles méthodes pour la détermination des orbites des comètes\'\' (1805). \"Sur la Méthode des moindres quarrés\" appears as an appendix.\n\n* [[Carl Friedrich Gauss|C.F. Gauss]]. \'\'Theoria Motus Corporum Coelestium in Sectionibus Conicis Solem Ambientum\'\'. (1809)\n\n* C.F. Gauss. \'\'Theoria combinationis observationum erroribus minimis obnoxiae\'\'. (1821/1823)\n\n* [[Charles Darwin]]. \'\'The Variation of Animals and Plants under Domestication\'\'. (1869) \'\'(Chapter XIII describes what was known about reversion in Galton\'s time. Darwin uses the term \"reversion\".)\'\'\n\n* [[Francis Galton]]. \"Typical laws of heredity\", Nature 15 (1877), 492-495, 512-514, 532-533. \'\'(Galton uses the term \"reversion\" in this paper, which discusses the size of peas.)\'\'\n\n* Francis Galton. Presidential address, Section H, Anthropology. (1885) \'\'(Galton uses the term \"regression\" in this paper, which discusses the height of humans.)\n\n* Francis Galton. \"Regression Towards Mediocrity in Hereditary Stature,\" \'\'Journal of the Anthropological Institute\'\', 15:246-263 (1886). \'\'(Facsimile at: [http://www.mugu.com/galton/essays/1880-1889/galton-1886-jaigi-regression-stature.pdf])\'\'\n\n* [[G. Udny Yule]]. \"On the Theory of Correlation\", J. Royal Statist. Soc., 1897, p. 812-54.\n\n* [[Karl Pearson]], G. U. Yule, Norman Blanchard, and Alice Lee. \"The Law of Ancestral Heredity\", \'\'Biometrika\'\' (1903)\n\n* [[Ronald Fisher|R.A. Fisher]]. \"The goodness of fit of regression formulae, and the distribution of regression coefficients\", J. Royal Statist. Soc., 85, 597-612 (1922)\n\n* R.A. Fisher. \'\'Statistical Methods for Research Workers\'\' (1925)\n\n===Modern theory===\n\n===Modern practice===\n\n==External links==\n* [http://members.aol.com/jeff570/mathword.html Earliest Known uses of some of the Words of Mathematics]. See: [http://members.aol.com/jeff570/e.html] for \"error\", [http://members.aol.com/jeff570/g.html] for \"Gauss-Markov theorem\", [http://members.aol.com/jeff570/m.html] for \"method of least squares\", and [http://members.aol.com/jeff570/r.html] for \"regression\".\n* [http://www.wessa.net/esteq.wasp Online linear regression calculator.]\n* [http://www.ruf.rice.edu/~lane/stat_sim/reg_by_eye/ Online regression by eye (simulation).]\n* [http://zunzun.com/ Online curve and surface fitting.]\n\n[[nl:Lineaire regressie]]\n[[de:Lineare Regression]]\n[[Category:Statistics]]','/* Parameter estimation */',13,'Budhi','20040917053809','',0,0,0,0,0.326692951064,'20041231123527','79959082946190'); INSERT INTO cur VALUES (1215,0,'Fungsi_gamma','[[de:Gammafunktion]]\n[[es:Función gamma]]\n[[fr:Fonction Gamma d\'Euler]] [[it:funzione Gamma]] [[ja:ガンマ関数]] [[ko:감마함수]] [[pl:Funkcja gamma]] [[sl:funkcija gama]]\n[[Image:Gamma.png|thumb]]\n[[Image:Gamma_abs.png|thumb]]\nDina [[matematik]], \'\'\'fungsi gamma\'\'\' nyaeta [[Fungsi (matematik)|fungsi]] nu leuwih lega tina konsep [[factorial|faktorial]] kana [[complex number|wilangan kompleks]].\n\n==Harti==\n\nLambang Γ(\'\'z\'\') dumasar ka [[Adrien-Marie Legendre]]. Lamun bagean real tina wilangan kompleks \'\'z\'\' positip, mangka [[integral]]\n:\n\\Gamma(z) = \\int_0^\\infty t^{z-1}\\,e^{-t}\\,dt\n\npasti konvergen. Migunakeun [[integration by parts|integral parsial]], bisa ditembongkeun yen \n:\\Gamma(z+1)=z\\Gamma(z)\\,.\n\nSabab Γ(1) = 1, dina kaitan ieu ngakibatkeun yen\n\n:\\Gamma(n+1)=n!\\,\n\nkeur sakabeh [[natural number|wilangan natural]] \'\'n\'\'. Ieu bisa dipake keur ngalegaan Γ(\'\'z\'\') jadi [[meromorphic function|fungsi meromorpik]] diartikeun keur sakabar wilangan kompleks \'\'z\'\' ial \'\'z\'\' = 0,  −1, −2, −3, ... ku [[analytic continuation|analisa kontinyu]]. \nHal nu leuwih lega ilaharna dumasar salaku fungsi gamma.\nNotasi alternatip nu kadangkala dipake nyaeta \'\'\'fungsi Pi\'\'\', nu dina watesan fungsi gamma nyaeta\n\n:\\Pi(z) = \\Gamma(z+1) = z\\Gamma(z).\n\nKadangkala oge manggihkeun \n\n:\\pi(z) = {1 \\over \\Pi(z)}\\,\n\nnu ngarupakeun hiji [[entire function|fungsi sakabehna]], diartikeun keur sakabeh wilangan kompleks. Yen π(\'\'z\'\') ngarupakeun sakabeh nu diperlukeun anu teu mibanda kutub, mangka Γ(\'\'z\'\') teu mibanda [[zero|nol]].\n\nBisa oge nilai keur fungsi gamma dina non-integer nyaeta\n\n:\\Gamma\\left(\\frac{1}{2}\\right)=\\sqrt{\\pi}.\n\nFungsi gamma mibanda hiji [[pole (complex analysis)|kutub]] orde 1 dina \'\'z\'\' = −\'\'n\'\' keuw sakabeh [[natural number|wilangan alami]] \'\'n\'\'; [[residue (complex analysis)|sesana]] diberekeun ku\n\n:\\operatorname{Res}(\\Gamma,-n)=\\frac{(-1)^n}{n!}.\n\nBentuk kakali fungsi gamma saterusna nyaeta valid keur sakabeh wilangan kompleks \'\'z\'\' nu lain integer non-positip:\n\n:\\Gamma(z) = \\frac{e^{-\\gamma z}}{z} \\prod_{n=1}^\\infty \\left(1 + \\frac{z}{n}\\right)^{-1} e^{z/n}\n\nnumana γ ngarupakeun [[Euler-Mascheroni constant|konstanta Euler-Mascheroni]].\n\n[[Bohr-Mollerup theorem|TeoremaBohr-Mollerup]] nangtukeun yen antara sakabeh fungsi dilegaan ku fungsi faktorial kana wilangan riil positip, ngan lamun fungsi gamma ngarupakeun log-convex.\n\n== Kaitan jeung fungsi sejen ==\n\nDina integral di luhur, nu ngahartikeun fungsi gamma, watesan integralna geus ditangtukeun.\n[[incomplete gamma function|Fungsi gama nu teu lengkep]] ngarupakeun fungsi nu ditangtukeun ku nuturkeun wates luhur atawa handap tina integral jadi variabel.\n\nTurunan logaritma fungsi gamma disebutna [[digamma function|fungsi digamma]].\n\n==Tempo oge==\n*[[Fungsi beta]].\n*[[Stirling\'s approximation]]\n\n== Rujukan ==\n\n* M. Abramowitz and I. A. Stegun, eds. \'\'Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables\'\'. New York: Dover, 1972. \'\'(See Chapter 6.)\'\'\n\n* G. Arfken and H. Weber. \'\'Mathematical Methods for Physicists\'\'. Harcourt/Academic Press, 2000. \'\'(See Chapter 10.)\'\'\n\n* W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling. \'\'Numerical Recipes in C\'\'. Cambridge, UK: Cambridge University Press, 1988. \'\'(See Section 6.1.)\'\'\n\n== Tumbu kaluar ==\n\n* [http://mathworld.wolfram.com/GammaFunction.html Gamma function at MathWorld].','',0,'62.224.36.117','20050130113208','',0,0,0,0,0.309784777141,'20050130113208','79949869886791'); INSERT INTO cur VALUES (1216,0,'Sebaran_eksponensial','Dina [[probability theory|teori probabiliti]] jeung [[statistik]], \'\'\'sebaran eksponensial\'\'\' nyaeta [[probability distribution|sebaran probailiti]] kontinyu nu mibanda [[probability density function]] (pdf)\n\n[[Image:Exponential pdf.png|thumb|Pdf of exponential distribution for λ =0.5, 1.0, and 1.5.]]\n\n:\nf(t) = \\left\\{\\begin{matrix}\n\\lambda e^{-\\lambda t} &,\\; t \\ge 0, \\\\\n0 &,\\; t < 0.\n\\end{matrix}\\right.\n\nnumana λ > 0 ngarupakeun parameter sebaran.\n\n[[Cumulative distribution function]] diberekeun ku\n\n:\nF(x) = 1-e^{-\\lambda t}\n\\,\\!\n\n\n[[Nilai ekspektasi]] jeung [[simpangan baku]] [[variabel random]] eksponensial duaana nyaeta 1/λ (sarta [[varian]]na nyaeta 1/λ2.)\n\nSebaran eksponensial dipake keur model [[Poisson process|proses Poisson]], numana kaayaanna obyek awal dina tetapan A bisa robah kana tetapan B nu mibanda konstanta probabiliti per satuan waktu λ. Waktu nu robah dina tetapan sabenerna dijelaskeun ku variabel random eksponensial nu mibanda parameter λ. Sanajan kitu, integral ti 0 ka \'\'T\'\' dina \'\'f\'\' ngarupakeun probabiliti nu obyekna dina tetapan B nyaeta waktu \'\'T\'\'.\n\nSebaran eksponensial bisa ditempo salaku lawan tina [[geometric distribution|sebaran geometrik]], nu ngajelaskeun wilangan [[Bernoulli trial]] penting keur proses diskrit ka robahna tetapan. Beda jeung sebaran eksponensial nu ngajelaskeun waktu keur proses kontinyu kana robahna tetapan.\n\nConto variabel nu ngadeukeutan sebaran eksponensial nyaeta:\n\n* waktu kajadian kacilakaan mobil saterusna\n* waktu narima telpon saterusna (anggap narima loba telpon unggal poe, atawa narima telpon ti jalama nu beda waktuna)\n* jarak antara [[mutation|mutasi]] dina rante[[DNA]]\n* jarak antara \'\'roadkill\'\'\n* waktu \'\'penguraian\'\' radioaktif \n* jumlah alungan dadu dina alungan 6 11 kali dina baris\n\nSipat penting tina sebaran eksponensial nyaeta [[memorylessness|kurang memori]]. Ieu hartina yen variabel random \'\'T\'\' kasebar eksponsial, [[conditional probability|probabiliti kondisional]] nurut kana\n\n:P(T > s + t\\; |\\; T > t) = P(T > s) \\;\\; \\hbox{for all}\\ s, t \\ge 0. \n\nIeu hartina yen [[conditional probability|probabiliti kondisional]] yen perlu ngadagoan, contona, leuwih ti 10 detik samemeh datang mimiti, diberekeun yen waktu datang teu kajadian sanggeus 30 detik, teu beda tina probabiliti mimiti nu merlukeun waktu ngadagoan leuwih ti 10 detik keur nu datang mimiti. Ieu sok salah harti ku siswa nu nyokot pangajaran probabiliti: kanyataanna yen P(\'\'T\'\' > 40 | \'\'T\'\' > 30) = P(\'\'T\'\' > 10) \'\'lain\'\' hartina yen kajadian \'\'T\'\' > 40 sarta \'\'T\'\' > 10 hal nu bebas. Kasimpulanna: \"\'\'memorlessness\'\'\" sebaran probabiliti waktu ngadagoan \'\'T\'\' salili datang mimiti hartina\n\n:\\mathrm{(Right)}\\ P(T>40 \\mid T>30)=P(T>10).\n\n\'\'Lain\'\' hartina\n\n:\\mathrm{(Wrong)}\\ P(T>40 \\mid T>30)=P(T>40).\n\nIeu kudu bebas. Dua kajadian ieu \'\'heunteu\'\' bebas.\n\n==Generating variabel ku sebaran eksponensial==\n\nDiberekeun variabel random \'\'Y\'\' nu mibanda [[sebaran seragam]] dina interval (0;1], variabel\n\n:T=\\frac{-\\ln Y}{\\lambda}\n\nngabogaam sebaran eksponensia; nu mibanda parameter λ.\n\n[[Category:Probability distributions]]\n[[de:Exponentialverteilung]] [[sv:exponentialfördelning]] [[it:variabile casuale Esponenziale Negativa]]','',13,'Budhi','20040917030816','',0,0,0,0,0.553635074549,'20041231123527','79959082969183'); INSERT INTO cur VALUES (1217,0,'Sebaran_gamma','Dina [[tiori probabiliti]] jeung [[statistik]], \'\'\'sebaran gamma\'\'\' nyaeta [[probability distribution]] kontinyu. [[Probability density function]] bisa digambarkeun di watesan [[fungsi gamma]]:\n\n: f(x) = x^{k-1} \\frac{e^{-x/\\theta}}{\\Gamma(k)\\,\\theta^k} \n \\ \\ \\ \\ \\mathrm{for\\ } x > 0\n\nnumana \'\'k\'\' > 0 nyaeta \'\'parameter bentuk\'\' jeung θ > 0 nyaeta \'\'parameter skala\'\' sebaran gamma .\n\n[[Cumulative distribution function]] bisa ditembongkeun dina watesan [[incomplete gamma function]],\n\n: F(x) = \\int_0^x f(u)\\,du \n = \\frac{\\gamma(k, x/\\theta)}{\\Gamma(k)} \n\n[[Nilai ekspektasi]] sarta [[varian]] tina [[variabel random]] gamma \'\'X\'\' nyaeta:\n\n:\n\\begin{matrix}\n E(X) = k \\theta \\\\\n\\\\\n \\mathrm{var}(X) = k \\theta^2\n\\end{matrix}\n\n\nLamun X_1 ngabogaan sebaaran gamma mibanda parameter k_1 jeung θ, \nsarta X_2 ngabogaan sebaran gamma mibanda paramater k_2 jeung θ,\nmangka X_1 + X_2 ngabogaan sebaran gamma mibanda parameter k_1 + k_2 jeung θ.\n\nLamun \'\'k\'\' sarua jeung 1, sebaran gamma ngarupakeun [[sebaran eksponensial]] mibanda parameter θ.\nJumlah \'\'n\'\' variabel eksponensial, sakabehna mibanda parameter θ nu sarua, ngarupakeun variabel gamma nu mibanda parameter \'\'n\'\' jeung θ.\n\nLamun \'\'k\'\' ngarupakeun integer, sebaran gamma ngarupakeun [[Erlang distribution]] (keur ngahargaan ka [[A.K. Erlang]]) sarta sebaran probabiliti waktu tunggu tina nu-\'\'k\'\' \"datang\" dina hiji-dimensi [[Poisson process]] nu mibanda intensitas 1/θ. \n\nLamun \'\'k\'\' ngarupakeun satengah-integer sarta θ = 2, mangka sebaran distribution ngarupakeun [[sebaran chi-kuadrat]] nu mibanda \'\'2 k\'\' tingkat kabebasan.\n\nSebaran gamma ngarupakeun sebaran probabiliti [[infinite divisibility|infinitely divisible]] .\n\n== Sumber sejen ==\n\n* R.V. Hogg and A.T. Craig. \'\'Introduction to Mathematical Statistics\'\', 4th edition. New York: Macmillan, 1978. \'\'(See Section 3.3.)\'\'\n\n[[Category:Probability distributions]]','',13,'Budhi','20041224211327','',0,0,1,0,0.384027277764,'20041224211327','79958775788672'); INSERT INTO cur VALUES (1218,0,'Tembok','[[de:Mauer]] [[fr:Mur]] [[simple:Wall]]\n\nA \'\'\'wall\'\'\' is a usually solid structure that defines and sometimes protects space. Most commonly, a wall separates space in buildings into [[room|rooms]], or protects or delineates a space in the open air. There are three principal types of structural walls: building walls, exterior boundary walls, and retaining walls.\n\n[[image:stone-wall-by-eiffel-2004-public-domain.jpg|thumb|Stone wall of an English barn]]\nBuilding walls have two main purposes: to support roofs and ceilings, and to divide space, providing security against intrusion and weather. Such walls most often have three or more separate components. In today\'s construction, a building wall will usually have the structural elements (such as 2×4 studs in a house wall), [[insulation]], and finish elements, or surface (such as [[drywall]] or [[paneling]]). In addition, the wall may house various types of [[electrical wiring]] or [[plumbing]]. Electrical outlets are usually mounted in walls. Building walls frequently become works of art, such as when [[mural]]s are painted on them.\n\nBoundary walls include privacy walls, boundary-marking walls, and city walls. These intergrade into [[fence]]s; the conventional differentiation is that a fence is of minimal thickness and often is open in nature, while a wall is usually more than a nominal thickness and is completely closed, or opaque. More to the point, if an exterior structure is made of wood or wire, it is generally referred to as a fence, while if it is made of masonry, it is considered a wall. A common term for both is \'\'\'barrier\'\'\', convenient if it is partly a wall and partly a fence, e.g. the [[Israeli West Bank barrier]].\n\nBefore the invention of [[artillery]], many [[Europe]]an [[city|cities]] had [[city wall|protective walls]]. Since they are no longer relevant for defense, the cities have grown beyond their walls, and many of the walls have been torn down. Extreme examples of boundary walls include the [[Great Wall of China]] and [[Hadrian\'s Wall]].\n\nIn areas of rocky soils around the world, farmers (and their slaves, as in the [[United States]] before slavery was abolished) have often pulled large quantities of stone out of their fields to make farming easier, and have stacked those stones to make walls that either mark the field boundary, or the property boundary, or both.\n\n[[Retaining wall]]s are a special type of wall, that may be either external to a building or part of a building, that serves to provide a barrier to the movement of earth, stone or water. The ground surface or water on one side of a retaining wall will be noticeably higher than on the other side. A [[dike (construction)]] is one type of retaining wall, as is a [[levee]].\n\nThe term \'\'\'\"the Wall\"\'\'\' frequently referred to the [[Berlin Wall]], erected during the [[Cold War]], which fell in [[1989]].\n\n==Tempo oge==\n* [[List of walls]]\n* \'\'[[The Wall]]\'\'\n* [[Wallpaper]]\n* [[Separation wall]]\n* [[Shared residency|Mr Justice Wall]]','/* See also */',13,'Budhi','20040817234732','',0,0,0,0,0.314239477885,'20040817234732','79959182765267'); INSERT INTO cur VALUES (1219,0,'Wall','#REDIRECT [[Tembok]]\n','Wall dipindahkeun ka Tembok',13,'Budhi','20040817104303','',0,1,0,1,0.490039002606682,'20040817104303','79959182895696'); INSERT INTO cur VALUES (1220,0,'Hateup','\'\'\'Hateup\'\'\' nyaeta bagean pangluhurna nu nutupan [[building|wangunan]]. Flat roofs are often covered with [[tar]] and [[gravel]] and provided with drains to run off [[rain]] and [[snow]]. Other shaped roofs are built to naturally shed water, these include: \n\n

[[Image:R_roof_types.png]]
Ridged roof types
\n*lean-to\n*single-sloped\n*ridged\n**pitched or gabled\n***shaped gable\n***dutch gable\n***crow-step gable\n***corbie-step gable\n**saddleback\n**hipped\n**half-hipped\n**mansard\n**pavilion\n*concial\n*domical\n*pyramidal\n\nSome building styles, for example, [[geodesic dome|geodesic]] and [[A-frame]], blur the distinction between [[wall]] and roofs. Pitched roofs are often covered with [[asphalt]] [[shingle]]s (in the [[United States|US]]) although [[thatch]], [[wood]] [[shake]], [[steel]], [[corrugated galvanised iron]], [[slate]] and [[tile]] roofs are used elsewhere. Newer systems include [[solar panel|solar shingle]]s which generate [[electricity]] as well as cover the roof.\n \n[[image:roof.croyde.arp.750pix.jpg|thumb|left|250px|A roof tiled in imitation of thatch. Seen at Croyde, north Devon, England ]]\n\nSeveral systems of construction transmit the weight of the roof to the walls of the building and tie the roof into the structure. These include: ashlar-piece, brace (can be arched or wind), collar-beam, crown-post, hammer-beam and -post, king (or queen) post, purlin, rafter (common or principal), ridge beam, ridge-board, strut, tie-beam ([[Tie rod]]), truss, and wall-plate.\n\nBy extension one can speak of the roof of a [[tent]], [[automobile]], etc. A [[convertible]] is an automobile built with a folding, retracting, or removable roof.\n\nSee also [[Roof garden]].\n\n[[de:Dach]]\n[[pl:dach]]\n[[sv:Yttertak]]','',13,'Budhi','20041225225918','',0,0,1,0,0.093838598623,'20041225225918','79958774774081'); INSERT INTO cur VALUES (1221,0,'Roof','#REDIRECT [[Hateup]]\n','Roof dipindahkeun ka Hateup',13,'Budhi','20040817104748','',0,1,0,1,0.269847204228721,'20040817104748','79959182895251'); INSERT INTO cur VALUES (1222,0,'Efek_ukuran','Dina [[tes hipotesa statistik]] jeung analisa [[statistical power|power]], \'\'\'efek ukuran\'\'\' nyaeta ukuran tina [[statistical significance|statistically significant]] [[treatment effect]] – hal eta, beda antara karakter matematik (biasana [[mean]]) tina sebaran [[dependent variable]] pakait jeung tingkatan husus tina [[independent variable]] sarta karakteristik nu sarua tina sakabeh sebaran dihartikeun ku bedana tingkat variabel bebas. Contona, lamun mean tina skor mean sakabeh grup percobaan nyokot tes 100, hiji grup dihartikeun miboga lalaku, sarta skor mean eta lalaki 120, mangka efek \'\'perawatan\'\' keur lalaki nyaeta 102 - 100 = 2.\n\nSaprak variabel terikat diukur dina loba beda skala, analisa efek ukuran diperlukeun keur konversi kana format baku, contona :\n\n* [[skor standar]] sarua jeung efek\n* persentasi varian diterangkeun ku [[correlation]] antara variabel bebas jeung terikat\n* [[rasio ganjil]]\n\n\n{{pondok}}','',13,'Budhi','20050104065723','',0,0,0,0,0.985027636394,'20050303211247','79949895934276'); INSERT INTO cur VALUES (1223,0,'Skor_standar','Dina [[statistik]], \'\'\'skor standar\'\'\' (\'\'z\'\') nyaeta kuantitas \'\'tak-berdimensi\'\' nu asalna tina \'\'subtraksi\'\' [[sample mean]] tina individu skor (atah) sarta dibagi ku bedana [[simpangan baku]]:\n\n: z = {X - \\bar{X} \\over s}\n\nNilai \'\'z\'\' ngagambarkeun lobana simpangan baku antara skor atah jeung mean; nilai z negatip lamun skor atah sahandapeun mean, positip lamun saluhureunna.\n\nSebutan sejen keur skor standar nyaeta \'\'\'skor\'\'\'-\'\'\'z\'\'\'. Proses konversina kadangkala disebut \'\'\'standarisasi\'\'\'.\n\nKonversi ka skor standar bisa dijieun ku ngabandingkeun jeung ngombinasikeun ukuran skala. \n\nContona, nilai ujian dua siswa tina kelas nu beda bisa dibandingkeun ku konversi unggal skor siswa dumasar kana skor mean jeung simpangan baku manehna di kelasna. Siswa nu mibanda skor standar pangluhurna nunjukeun hal nu hade, tinimbang lamun skor kotorna handap. [http://soeweb.syr.edu/faculty/ddgilbri/assess/StandardScores.html]\n\nLamun data dikombinasikeun atawa di-skala, elimanisasi standarisasi kajadian dina \'\'pemberat\'\' ku sabab bedana mean jeung simpangan baku. Ieu hal penting dina [[linear regression]] waktu data ngarupakeun sampel mean tinimbang observasi pribadi.\n\nSkor standar ngarupakeun loba dipake keur data nu kasebar [[sebaran normal|normal]], sanajan teu bisa disebutkeun yen urang teu merlukeun sarat dina ngagunakeun informasi ngeunaan data [[Skewness|skewed]]. Standar skor oge diperlukeun dina skor [[percentile rank]] sebaran normal.\n\n==Standarisasi dina matematik statistik==\nDina [[statistik matematis]], [[variabel acak]] \'\'X\'\' ngarupakeun \'\'\'standarisasi\'\'\' dipake dina (populasi) mean jeung simpangan baku teoritis:\n:Z = {X - \\mu \\over \\sigma}\nnumana μ = E(\'\'X\'\') ngarupakeun [[mean]] sarta σ² = Var(\'\'X\'\') varian ti [[probability distribution]] \'\'X\'\'.\n\nLamun variabel acak dina ieu kaayaan ngarupakeun [[sample mean]]:\n\n:\\bar{X}=\\sum_{i=1}^n X_i\n\nmangka versi standarisasi nyaeta\n\n:Z={\\bar{X}-\\mu\\over\\sigma/\\sqrt{n}}\n\n==Tempo oge==\n* [[moment (mathematics)]]\n* [[central moment]]\n* [[sampling distribution]]','/* Standarisasi dina matematik statistik */',13,'Budhi','20041225130521','',0,0,1,0,0.970344749731,'20041225130521','79958774869478'); INSERT INTO cur VALUES (1224,0,'Régrési','[[sv:Regression]]\n[[de:Regression]]\n[[en:Regression]]\n\nSacara umum, \'\'\'regresi\'\'\' nyaeta pindah ka arah tukang. Sacara husus:\n* Watesan keur eksplorasi, with the assistance of a therapist, of (possibly unpleasant) past memories as part of the treatment for mental illnesses. See [[psychotherapy]], [[hypnotherapy]].\n* A re-introduction of a defect into a later revision of a product. See [[engineering]], [[regression testing]].\n* The phenomenon by which the sea retreats, or regresses, as a consequence of lowering sea level. See [[geology]].\n* In [[statistics]]:\n** The phenomenon, that, when two related variables are measured, the expected value of the second is closer to the mean than the measured value of the first. See [[regression toward the mean]].\n** A method where the [[mean]] of one or more [[random variable]]s is predicted conditioned on other (measured) random variables. See [[regression analysis]].\n\n\n{{pondok}}\n{{disambig}}','',3,'Kandar','20041125100225','',0,0,0,0,0.132716444383,'20050303211247','79958874899774'); INSERT INTO cur VALUES (1225,0,'Danie_G._Krige','\'\'\'Danie G. Krige\'\'\', nepi ka kiwari Profésor di [[Universitas Witwatersrand]], Républik [[Afrika Kidul]], salasaurang [[géologi|ahli géologi]] di Afrika Kidul nu ngenalkeun [[géostatistik]]. Téhnik [[kriging]] dumasar kana ngaran manéhna. Pagawéan émpirisna keur ngévaluasi sumberdaya mineral [1] dirumuskeun dina taun [[1960]]-an ku ahli rékayasa Perancis [[Georges Matheron]].\n\n== Sumber séjén ==\n1. \'\'\'Krige, D.G.\'\'\' A statistical approach to some basic mine valuation problems on the Witwatersrand. 1951. J. of Chem., Metal, and Mining Soc. of South Africa, Vol. 52, No. 6, pp. 119-139.\n\n{{pondok}}\n\n[[Category:Géolog]]','',3,'Kandar','20050125101656','',0,0,0,0,0.681703307983,'20050303211247','79949874898343'); INSERT INTO cur VALUES (1226,0,'Gaussian_process','\'\'\'Proses Gaussian\'\'\' ngarupakeun [[stochastic process]] {\'\'X\'\'\'\'t\'\'}\'\'t\'\', numana unggal [[linear combination]] (terhingga) tina \'\'X\'\'\'\'t\'\', ngarupakeun [[sebaran normal]]. Konsep ieu make ngaran [[Carl Friedrich Gauss]] sabab sebaran normal kadangkala disebut oge \'\'sebaran Gaussian distribution\'\', sanajan Gauss lain nu mimiti nalungtik ieu distribusi. Catetan yen sababaraha pengarang (contona B. Simon dina rujukan di handap ieu) oge nganggap yen variabel \'\'X\'\'\'\'t\'\' miboga mean sarua jeung nol. Alternatipna, ieu proses Gaussian [[iff]] keur susunan terhingga ditempokeun ku \'\'t\'\'1, ..., \'\'t\'\'\'\'k\'\' \n\n: \\vec{\\mathbf{X}}_{t_1, \\ldots, t_k} = (\\mathbf{X}_{t_1}, \\ldots, \\mathbf{X}_{t_k}) \n\nngarupakeun nilai-vektor variable random Gaussian. Migunakeun [[characteristic function]] variabel random, bisa dirumuskeun sipat Gaussian saperti:{\'\'X\'\'\'\'t\'\'}\'\'t\'\' ngarupakeun Gaussian iff keur unggal susunan terhingga nunjukkeun \'\'t\'\'1, ..., \'\'t\'\'\'\'k\'\' numana riil positip σ\'\'l j\'\' jeung riil μ\'\'j\'\' mangka\n\n: \\operatorname{E}\\left(\\exp\\left(i \\ \\sum_{\\ell=1}^k t_\\ell \\ \\mathbf{X}_{t_\\ell}\\right)\\right) = \\exp \\left(-\\frac{1}{2} \\, \\sum_{\\ell, j} \\sigma_{\\ell j} t_\\ell t_j + i \\sum_\\ell \\mu_\\ell t_\\ell\\right). \n\nAngka σ\'\'l j\'\' jeung μ\'\'j\'\' nempokeun bakal jadi variabel kovarian jeung mean dina ieu proses.\n\n[[Wiener process]] leuwih luas di-pelajari tinimbang proses Gaussian.\n\nProses Gaussian bisa dipake salaku [[Fungsi (matematik)|fungsi]] [[prior probability distribution]] dina [[Bayesian inference]]. Nilai kaputusan kontinyu nu mibanda prior proses Gaussian dipikanyaho salaku [[Gaussian process regression]].\n\n==Rujukan==\n\n* R. M. Dudley, \'\'Real Analysis and Probability\'\', Wadsworth and Brooks/Cole, 1989.\n\n* B. Simon, \'\'Functional Integration and Quantum Physics\'\', Academic Press, 1979.\n\n==Tumbu kaluar==\n\n* [http://www.cs.toronto.edu/~carl/gp.html The Gaussian Processes Web Site]\n\n[[Category:Stochastic processes]]','',13,'Budhi','20041224212806','',0,0,1,0,0.005685684739,'20041224212806','79958775787193'); INSERT INTO cur VALUES (1227,0,'Fungsi_(matematik)','Dina [[matematik]], \'\'\'fungsi\'\'\' nyaéta hiji \'\'hubungan,\'\' saperti unggal [[unsur (matematik)|unsur]] tina [[set|susunan]] ngarupakeun gabungan tina susunan unsur unik séjénna (nu mungkin sarua). Konsep fungsi jadi dasar pikeun sababaraha widang matematik sarta sakabéh [[élmu]] kuantitatif.\n\nWatesan \'\'\'fungsi\'\'\', \'\'\'mapping\'\'\', \'\'\'map\'\'\', \'\'\'transformation\'\'\' sarta \'\'\'operator\'\'\' ngarupakeun hal nu ilaharna meh sarua.\n\n==Intuitive introduction==\nEssentially, a function is a \"rule\" that assigns a [[unique]] [[output]] to each given [[input]]. Here are some examples of functions:\n\n*Each person has a favorite colour (red, orange, yellow, green, cyan, blue, indigo, or violet). The colour is a function of the person. For example, John has favorite colour red, while Kim has favorite colour violet. Here, the input is the person, and the output is one of the 8 colours.\n*Some children are selling lemonade in the summer. The number of lemonades they sell is a function of the temperature outside. For example, if it is 85 degrees outside, they sell 10 lemonades, but if it is 95 degrees outside, they sell 25 lemonades. Here, the input is the temperature, and the output is the number of lemonades they sell.\n*A stone is dropped from different stories of a tall building. The dropped stone may take 2 seconds to fall from the second storey, and (only) 4 seconds to fall from the 10th storey. Here, the input is the storey, and the output is the number of seconds. The relevant \'\'function\'\' describes the relationship between the time it takes the stone to reach the ground and the storey. (\'\'See [[acceleration]]\'\')\n\nThe \"rule\" defining a function can be specified by a [[formula]], a [[mathematical relation|relationship]], or simply a table listing the outputs against inputs. The most important feature of a function is that it is [[determinism|deterministic]], always producing the same [[output]] from the same [[input]]. In this way, a function may be thought of as a \"[[machine]]\" or a \"[[black box]]\", converting a valid input into a unique output. The input is often called the \'\'argument\'\' of the function, and the output the \'\'value\'\' of the function.\n\nA very common type of function occurs when the argument and the function value are both [[number]]s, the functional relationship is expressed by a formula, and the value of the function is obtained by direct substitution of the argument into the formula. Consider for example\n:f(x)=x^{2}\nwhich assigns to any number \'\'x\'\' its square.\n\nA straightforward generalization is to allow functions depending on several arguments. For instance,\n:g(x,y) = xy \nis a function which takes two numbers \'\'x\'\' and \'\'y\'\' and assigns to them their product, \'\'xy\'\'. It might seem that this is not really a function as we described above, because this \"rule\" depends on two inputs. However, if we think of the two inputs together as a single \'\'[[ordered pair|pair]]\'\' (\'\'x\'\', \'\'y\'\'), then we can interpret \'\'g\'\' as a function -- the argument is the ordered pair (\'\'x\'\', \'\'y\'\'), and the function value is \'\'xy\'\'.\n\nIn the sciences, we often encounter functions that are not given by (known) formulas. Consider for instance the temperature distribution on earth over time: this is a function which takes location and time as arguments and gives as output the temperature at that location at that time.\n\nWe have seen that the intuitive notion of function is not limited to computations using single numbers and not even limited to computations; the mathematical notion of function is still more general and is not limited to situations involving numbers. Rather, a function links a \"domain\" (set of inputs) to a \"codomain\" (set of possible outputs) in such a way that every [[naive set theory|element]] of the domain is associated to precisely one element of the codomain. Functions are abstractly defined as certain [[mathematical relation|relations]], as will be seen below. Because of this generality, the function concept is fundamental to virtually every branch of mathematics.\n\n==Sajarah==\n\nAs a mathematical term, \"\'\'\'function\'\'\'\" was coined by [[Gottfried Leibniz|Leibniz]] in [[1694]], to describe a quantity related to a [[curve]], such as a curve\'s [[slope]] or a specific [[point]] of a curve. The functions Leibniz considered are today called [[derivative|differentiable functions]], and they are the type of function most frequently encountered by nonmathematicians. For this type of function, one can talk about [[limit of a function|limit]]s and [[derivative]]s; both are measurements of the change of output values associated to a change of input values, and these measurements are the basis of [[calculus]].\n\nThe word function was later used by [[Leonhard Euler|Euler]] during the mid-[[18th century]] to describe an [[Expression (mathematics)|expression]] or formula involving various [[parameter|argument]]s, e.g. \'\'f\'\'(\'\'x\'\') = sin(\'\'x\'\') + \'\'x\'\'3. \n\nDuring the [[19th century]], mathematicians started to formalize all the different branches of mathematics. [[Karl Weierstrass|Weierstrass]] advocated building calculus on [[arithmetic]] rather than on [[geometry]], which favoured Euler\'s definition over Leibniz\'s (see [[arithmetization of analysis]]). \n\nBy broadening the definition of functions, mathematicians were then able to study \"strange\" mathematical objects such as continuous functions that are nowhere differentiable. These functions were first thought to be only theoretical curiosities, and they were collectively called \"monsters\" as late as the turn of the 20th century. However, powerful techniques from [[functional analysis]] has shown that these functions are actually more common than differentiable functions. Such functions have since been applied to the modelling of physical phenomena such as [[Brownian motion]].\n\nTowards the end of the 19th century, mathematicians started trying to formalize all of mathematics using [[axiomatic set theory|set theory]], and they sought to define every mathematical object as a [[set]]. [[Johann Peter Gustav Lejeune Dirichlet|Dirichlet]] and [[Nikolai Ivanovich Lobachevsky|Lobachevcky]] independently and almost simultaneously gave the modern \"formal\" definition of function (see [[#Formal definition|formal definition]] below).\n\nIn this definition, a function is a special case of a [[mathematical relation|relation]]. In most cases of practical interest, however, the differences between the modern definition and Euler\'s definition are negligible.\n\nThe notion of \'\'\'function\'\'\' as a rule for computing, rather than a special kind of relation, has been formalized in [[mathematical logic]] by means of the [[lambda calculus]].\n\n==Dadaran formal==\n\nFormally, a function \'\'f\'\' from a set \'\'X\'\' of input values to a set \'\'Y\'\' of possible output values (written as \'\'f\'\' : \'\'X\'\' → \'\'Y\'\') is a [[binary relation|relation]] between \'\'X\'\' and \'\'Y\'\' which satisfies:\n#\'\'f\'\' is \'\'total\'\': for all \'\'x\'\' in \'\'X\'\', there exists a \'\'y\'\' in \'\'Y\'\' such that \'\'x f y\'\' (\'\'x\'\' is \'\'f\'\'-related to \'\'y\'\'), i.e. for each input value, there is at least one output value in \'\'Y\'\'.\n#\'\'f\'\' is \'\'many-to-one\'\': if \'\'x f y\'\' and \'\'x f z\'\', then \'\'y\'\' = \'\'z\'\'. i.e., many input values can be related to one output value, but one input value cannot be related to many output values.\n\nFor each input value \'\'x\'\' in the domain, the corresponding unique output value \'\'y\'\' in the codomain is denoted by \'\'f\'\'(\'\'x\'\').\n\nA more concise expression of the above definition is the following: a function from \'\'X\'\' to \'\'Y\'\' is a [[subset]] \'\'f\'\' of the [[cartesian product]] \'\'X\'\' × \'\'Y\'\', such that for each \'\'x\'\' in \'\'X\'\', there is a unique \'\'y\'\' in \'\'Y\'\' such that the ordered pair (\'\'x\'\', \'\'y\'\') is in \'\'f\'\'.\n\nThe set of all functions \'\'f\'\' : \'\'X\'\' → \'\'Y\'\' is denoted by \'\'YX\'\'. Note that \'\'|YX| = |Y||X|\'\' (refer to [[Cardinal number#Formal_definition|Cardinal numbers]]).\n\nA relation between \'\'X\'\' and \'\'Y\'\' that satisfies condition (1) is a \'\'\'[[multivalued function]]\'\'\'. Every function is a multivalued function, but not every multivalued function is a function. A relation between \'\'X\'\' and \'\'Y\'\' that satisfies condition (2) is a \'\'\'[[partial function]]\'\'\'. Every function is a partial function, but not every partial function is a function. In this encyclopedia, the term \"function\" will mean a relation satisfying both conditions (1) and (2), unless otherwise stated.\n\nConsider the following three examples:\n\n\n\n\n\n\n\n\n
[[image:notMap1.png]] This relation is total but not many-to-one; the element 3 in \'\'X\'\' is related to two elements \'\'b\'\' and \'\'c\'\' in \'\'Y\'\'. Therefore, this is a multivalued function, but \'\'not\'\' a function.
[[image:notMap2.png]] This relation is many-to-one but not total; the element 1 in \'\'X\'\' is not related to any element of \'\'Y\'\'. Therefore, this is a partial function, but \'\'not\'\' a function.
[[image:mathmap.png]] This relation is both total and many-to-one, and so it is a function from \'\'X\'\' to \'\'Y\'\'. The function can be given explicitly as \'\'f\'\' = {(1, a), (2, d), (3, c)} or as\n:f(x)=\\left\\{\\begin{matrix} a, & \\mbox{if }x=1 \\\\ d, & \\mbox{if }x=2 \\\\ c, & \\mbox{if }x=3. \\end{matrix}\\right.\n
\n\n==Domains, codomains, and ranges==\n\n\'\'X\'\', the set of input values, is called the [[Function domain|domain]] of \'\'f\'\', and \'\'Y\'\', the set of \'\'\'possible\'\'\' output values, is called the [[codomain]]. The [[function range|range]] of \'\'f\'\' is the set of all \'\'\'actual\'\'\' outputs {\'\'f\'\'(\'\'x\'\') : \'\'x\'\' in the domain}. Beware that sometimes the codomain is incorrectly called the range because of a failure to distinguish between possible and actual values. \nAn [[endofunction]] is a function whose domain and range are identical.\n\nIn computer science, the [[datatype]]s of the arguments and return values specify the domain and codomain (respectively) of a [[subprogram]]. So the domain and codomain are constraints imposed initially on a function; on the other hand the range has to do with how things turn out in practice.\n\n==Injective, surjective and bijective functions==\n\nSeveral types of functions that are very useful have special names: \n*[[Injective]] (one-to-one) functions send different arguments to different values; in other words, if \'\'x\'\' and \'\'y\'\' are members of the domain of \'\'f\'\', then \'\'f\'\'(\'\'x\'\') = \'\'f\'\'(\'\'y\'\') only if \'\'x\'\' = \'\'y\'\'.\n*[[Surjective]] (onto) functions have their range equal to their codomain; in other words, if \'\'y\'\' is any member of the codomain of \'\'f\'\', then there exists at least one \'\'x\'\' such that \'\'f\'\'(\'\'x\'\') = \'\'y\'\'.\n*[[Bijective function]]s are both injective and surjective; they are often used to show that the sets \'\'X\'\' and \'\'Y\'\' are the \"same size\" in some sense.\n\n==Images and preimages==\n\nThe \'\'[[image (mathematics)|image]]\'\' of an element \'\'x\'\'∈\'\'X\'\' under \'\'f\'\' is the output \'\'f\'\'(\'\'x\'\'). \n\nThe image of a subset A⊂\'\'X\'\' under \'\'f\'\' is the subset of \'\'Y\'\' defined by\n:\'\'f\'\'(A) := {\'\'f\'\'(x) : x in A}. \n \nNotice that the range of \'\'f\'\' is the image \'\'f\'\'(\'\'X\'\') of its domain. In our function above, the image of {2,3} under \'\'f\'\' is \'\'f\'\'({2, 3}) = {c, d} and the range of \'\'f\'\' is {a, c, d}.\n\nNote that with this definiton, the direct image \'\'f\'\' becomes a function whose domain is the set of all subsets of \'\'X\'\' (also known as the [[power set]] of \'\'X\'\') and whose codomain is the power set of \'\'Y\'\'. Note that the same notation is used for the original function \'\'f\'\' and its direct image. This is a common convention; the intended usage must be inferred by context.\n\nThe \'\'preimage\'\' (or \'\'inverse image\'\') of a set BY under \'\'f\'\' is the subset of X defined by\n:\'\'f\'\' −1(B) := {x in \'\'X\'\' : \'\'f\'\'(x)∈B}.\nIn our function above, the preimage of {a, b} is \'\'f\'\' −1({a, b}) = {1}.\n\nNote that with this definiton, \'\'f\'\' −1 becomes a function whose domain is the power set of \'\'Y\'\' and whose codomain is the power set of \'\'X\'\'\'.\n\nSome consequences that follow immediately from these definitions are:\n*f(A1 ∪ A2) = f(A1) ∪ f(A2).\n*f(A1 ∩ A2) ⊆ f(A1) ∩ f(A2).\n*f −1(B1 ∪ B2) = f −1(B1) ∪ f −1(B2).\n*f −1(B1 ∩ B2) = f −1(B1) ∩ f −1(B2).\n*f(f −1(B)) ⊆ B.\n*f −1(f(A)) ⊇ A.\n\nThese are valid for arbitrary subsets \'\'A\'\', \'\'A\'\'1 and \'\'A\'\'2 of the domain and arbitrary subsets \'\'B\'\', \'\'B\'\'1 and \'\'B\'\'2 of the codomain.\nThe results relating images and preimages to the algebra of [[set theoretic intersection|intersection]] and [[set theoretic union|union]] work for any collections of subsets, not just for pairs of subsets.\n\n==Graph of a function==\n\nThe [[graph of a function]] \'\'f\'\' is the set of all [[ordered pair]]s(\'\'x\'\', \'\'f\'\'(\'\'x\'\')), for all \'\'x\'\' in the domain \'\'X\'\'. There are theorems formulated or proved most easily in terms of the graph, such as the [[closed graph theorem]].\n\nIf \'\'X\'\' and \'\'Y\'\' are real lines, then this definition coincides with the familiar sense of graph. Below is the graph of a cubic function:\n\n[[Image:cubicpoly.png]]\n\nThis function is surjective but not injective.\n\nNote that since a relation on the two sets \'\'X\'\' and \'\'Y\'\' is usually formalized as a subset of \'\'X\'\'×\'\'Y\'\', the formal definition of function actually identifies the function \'\'f\'\' with its graph.\n\n==Conto fungsi==\n\n(More can be found at [[List of functions]].)\n\n* The relation \'\'wght\'\' between persons in the United States and their weights at a particular time.\n* The relation between nations and their capitals, if we exclude those nations that maintain multiple capitals [http://geography.about.com/library/misc/bl2capitals.htm].\n* The relation \'\'sqr\'\' between [[natural number]]s n and their squares n2.\n* The relation \'\'ln\'\' between \'\'positive\'\' [[real number]]s x and their [[natural logarithm]]s ln(x). Note that the relation between real numbers and their natural logarithms is not a function because not every real number has a natural logarithm; that is, this relation is not total.\n* The relation \'\'dist\'\' between points in the plane R2 and their distances from the origin (0,0).\n* The relation \'\'grav\'\' between a point in the punctured plane R2 \\ {(0,0)} and the vector describing the [[gravitational force]] that a certain mass at that point would experience from a certain other mass at the origin (0,0).\n\nMost commonly used types of mathematical functions involving [[addition]], [[division]], [[exponent]]s, [[logarithm]]s, [[multiplication]], [[polynomial]]s, [[radical]]s, [[rational]]s, [[subtraction]], and [[trigonometric functions|trigonometric expressions]]. They are sometimes collectively referred as \'\'\'elementary functions\'\'\' -- but the meaning of this term varies among different branches of mathematics. Example of non-elementary functions (or [[special function]]s) are [[Bessel function]]s sarta [[fungsi gamma]].\n\n==\'\'n\'\'-ary function: function of several variables==\n\nFunctions in applications are often \'\'\'functions of several variables\'\'\': the values they take depend on a number of different factors. From a mathematical point of view all the variables must be made explicit in order to have a functional relationship - no \'hidden\' factors are allowed. Then again, from the mathematical point of view, there is no qualitative difference between functions of one and of several variables. A function of three real variables is just a function that applies to triples of real numbers. The following paragraph says this in more formal language.\n\nIf the domain of a function is a subset of the [[Cartesian product]] of n sets then the function is called an \'\'n-ary function\'\'.\nFor example, the relation \'\'dist\'\' has the domain R × R and is therefore a [[binary function]].\nIn that case \'\'dist\'\'((x,y)) is simply written as \'\'dist\'\'(x,y).\n\nAnother name applied to some types of functions of several variables is [[operation]]. In [[abstract algebra]], operators such as \"*\" are defined as binary functions; when we write a formula such as \'\'x\'\'*\'\'y\'\' in this context, we are implicitly invoking the function *(\'\'x\'\',\'\'y\'\'), but writing it in a convenient [[infix]] notation.\n\nAn important theoretical paradigm, [[functional programming]], takes the function concept as central. In that setting, the handling of \'\'\'functions of several variables\'\'\' becomes an operational matter, for which the [[lambda calculus]] provides the basic [[syntax]]. The composition of functions (see under \'\'\'composing functions\'\'\' immediately below) becomes a question of explicit forms of [[substitution]], as used in the [[substitution rule]] of [[calculus]]. In particular, a formalism called [[currying]] can be used to reduce \'\'n\'\'-ary functions to functions of a single variable.\n\n==Composing functions==\n\nThe functions fX → Y and gY → Z can be \'\'composed\'\' by first applying f to an argument x and then applying g to the result.\nThus one obtains a function g o f: X → Z defined by (g o f)(x) := g(f(x)) for all x in X.\nAs an example, suppose that an airplane\'s height at time t is given by the function h(t) and that the oxygen concentration at height x is given by the function c(x).\nThen (c o h)(t) describes the oxygen concentration around the plane at time t.\n\nIn the mid-[[20th century]], some mathematicians decided that writing \"\'\'g\'\'o\'\'f\'\'\" to mean \"first apply \'\'f\'\', then apply \'\'g\'\'\" was too confusing and decided to change notations. They wrote \"\'\'xf\'\'\" for \"\'\'f\'\'(\'\'x\'\')\" and \"\'\'xfg\'\'\" for \"\'\'g\'\'(\'\'f\'\'(\'\'x\'\'))\". However, this movement never caught on, and nowadays this notation is found only in old books.\n\n[[Image:FNGraph_screenshot.png|right|thumb|Various functions graphed using the FNGraph application]]\n\nThe functions g and f are [[commutative]] if g o f=f o g.\nIf\nYX\nthen \nf may compose with itself; this\nis sometimes denoted f 2. (Do not confuse it with the notation\ncommonly seen in \n[[trigonometric identity|trigonometry]].) \nThe \'\'\'functional powers\'\'\'\nf of n \n= f n o f\n= f n+1\nfor\n[[natural number|natural]] \nn\nfollow immediately. This is a generalized version of the common \'\'f\'\'-1 for an [[inverse function]]. On their heels comes the idea of \'\'\'functional root\'\'\';\ngiven f and n, find a g such that\ngn=f. \n([[Richard Feynman]] \nillustrated practical use of functional roots in one of his anecdotal books.\n<which?>\nTasked with building an \n[[analog computer|analogue]]\n[[Trigonometric_function|arctan]] \ncomputer and finding its parts overstressed, he instead designed a machine for a functional root <fifth?> of arctan and chained enough copies to make the arctan machine.)\n\n=== Inverse function ===\nIf a function \'\'f\'\':\'\'X\'\'→\'\'Y\'\' is [[bijective]] then preimages of any element \'\'y\'\' in the codomain \'\'Y\'\' is a singleton. A function taking \'\'y\'\'∈\'\'Y\'\' to its preimage \'\'f\'\'−1(\'\'y\'\') is a well-defined function called the \'\'\'[[Inverse function|inverse]]\'\'\' of \'\'f\'\' and is denoted by \'\'f\'\'−1.\n\nAn example of an inverse function, for \'\'f\'\'(\'\'x\'\') = 2\'\'x\'\', is \'\'f\'\'(\'\'x\'\')−1 = \'\'x\'\'/2. The inverse function is the function that \"undoes\" its original. See also [[inverse image]].\n\nInverses are sometimes difficult or impossible to find. Consider \'\'f\'\'(\'\'x\'\') = \'\'x\'\'2. The function \'\'f\'\'(\'\'x\'\') = √\'\'x\'\' is not an inverse when the domain of \'\'f\'\' is \'\'R\'\'. (As -22 is 4, but √4 is either 2 or -2).\n\n===Restrictions and extensions===\nSuppose that X is a [[subset]] of Y and that \n\n:f:Y\\rightarrow Z\n\nis a function. Let \n\n:i:X\\hookrightarrow Y \n\nbe the [[inclusion function]] \n\n:i(x)=x\n\nfor \'\'x ∈ X\'\'.\n\nThe \'\'restriction\'\' of f to X is then the function f|X = f \\circ i. Intuitively, this is the same function as f except that we restrict the domain of f to X.\n\nAn \'\'extension\'\' of a function g:X\\to Z is a function f:Y\\to Z defined on a [[superset]] Y of X such that f|X=g. Provided the [[Function_domain|domain]] of g is not the [[universal set]], g always has lots of extensions.\n\n== Pointwise operations ==\n\nIf fX → R and gX → R are functions with common domain X and codomain is a [[ring (mathematics)|ring]] R, then one can define the sum function f + g: X → R and the product function f × g: X → R as follows:\n:(f + g)(x) := f(x) + g(x);\n:(f × g)(x) := f(x) × g(x);\nfor all x in X.\n\nThis turns the set of all such functions into a ring. The binary operations in that ring have as domain ordered pairs of functions, and as codomain functions. This is an example of climbing up in abstraction, to functions of more complex types.\n\nBy taking some other [[abstract algebra|algebraic structure]] A in the place of R, we can turn the set of all functions from X to A into an algebraic structure of the same type in an analogous way.\n\n== Computable and non-computable functions ==\n\nThe number of [[computable]] functions from integers to integers is [[countable]], because the number of possible algorithms is. The number of all functions from integers to integers is higher: the same as the [[cardinality]] of the [[real number]]s. This argument shows that there are functions from integers to integers that are not computable. For examples of noncomputable functions, see the articles on the [[halting problem]] and [[Rice\'s theorem]].\n\n==Functions from the categorical viewpoint==\n\nIn the context of [[category theory]], a function no longer represents a rule for taking an input to an output, but instead represents a relationship between its domain and its codomain. Since these functions are no longer functions in the usual sense, they are usually referred to as [[morphism]]s. A morphism is then an ordered triple (\'\'X\'\', \'\'Y\'\', \'\'f\'\'), where \'\'f\'\' is a \"function\" with domain \'\'X\'\' and codomain \'\'Y\'\'. Since \'\'X\'\' and \'\'Y\'\' do not necessarily correspond to a set of objects, however, morphisms do not always behave like functions, and, for example, enlarging the codomain (which does nothing to a function) gives a different morphism which you cannot identify with the original one.\n\nOrdinary functions are sometimes referred to as morphisms when they are morphisms in a [[concrete category]].\n\n==References==\n*[http://archives.math.utk.edu/visual.calculus/ Visual Calculus] by [[Lawrence S. Husch]], [[University of Tennessee]] ([[2001]])\n\n\n== External links ==\n* [http://functions.wolfram.com/ http://functions.wolfram.com], a compendium of formulae for and visualizations of mathematical functions\n* [http://math.hws.edu/xFunctions/ xFunctions] is a versatile Java applet for exploring functions graphically. It can be used on line or downloaded for use off line.\n\n[[da:Funktion (matematik)]]\n[[de:Funktion (Mathematik)]]\n[[es:Función matemática]]\n[[eo:Funkcio]]\n[[et:Funktsioon (matemaatika)]]\n[[fr:fonction]]\n[[he:פונקציה]]\n[[id:Fungsi]]\n[[it:Funzione (matematica)]]\n[[ja:関数 (数学)]]\n[[nl:functie (wiskunde)]]\n[[pl:Funkcja matematyczna]]\n[[pt:Função]]\n[[sv:Funktion]][[Category:Set theory]]','/* Examples of functions */',13,'Budhi','20041224211453','',0,0,1,0,0.445871848821,'20050316081936','79958775788546'); INSERT INTO cur VALUES (1228,0,'Prior_probability_distribution','#REDIRECT [[Prior probability]]','',0,'220.31.240.165','20040817131941','',0,1,0,1,0.786224511818,'20040817132048','79959182868058'); INSERT INTO cur VALUES (1229,0,'Prior_probability','A \'\'\'prior probability\'\'\' is a [[conditional probability|marginal probability]], interpreted as a description of what is known about a variable in the absence of some [[evidence]].\nThe \'\'[[posterior probability]]\'\' is then the [[conditional probability]] of the variable taking the evidence into account. \nThe posterior probability is computed from the prior and the [[likelihood function]] via [[Bayes\' theorem]].\n\nAs \'\'prior\'\' and \'\'posterior\'\' are not terms used in [[frequency probability|frequentist]] analyses,\nthis article uses the vocabulary of [[Bayesian probability]] and [[Bayesian inference]].\n\nThroughout this article, for the sake of brevity the term \'\'variable\'\' encompasses observable variables, latent (unobserved) variables, parameters, and hypotheses.\n\n== Prior probability distribution ==\n\nIn [[Bayesian probability|Bayesian]] [[statistical inference]], a \'\'\'prior probability distribution\'\'\', often called simply the \'\'\'prior\'\'\', of an uncertain quantity \'\'p\'\' (for example, suppose \'\'p\'\' is the proportion of voters who will vote for John Kerry) is the [[probability distribution]] that would express one\'s uncertainty about \'\'p\'\' before the \"data\" (for example, an opinion poll) are taken into account. It is meant to attribute uncertainty rather than randomness to the uncertain quantity.\n\nOne applies [[Bayes\' theorem]], multiplying the prior by the [[likelihood function]] and then normalizing, to get the \'\'posterior probability distribution\'\', which is the conditional distribution of the uncertain quantity given the data.\n\nA prior is often the purely subjective assessment of an experienced expert. Some will choose a \'\'[[conjugate prior]]\'\' when they can, to make calculation of the posterior distribution easier. \n\n== Informative priors ==\n\nAn \'\'informative prior\'\' expresses specific, definite information about a variable.\nAn example is a prior distribution for the temperature at noon tomorrow.\nA reasonable approach is to make the prior a [[sebaran normal]] with [[nilai ekspektasi]] equal to today\'s noontime temperature, with [[varian]] equal to the day-to-day variance of atmospheric temperature.\n\nThis example has a property in common with many priors,\nnamely, that the posterior from one problem (today\'s temperature) becomes the prior for another problem (tomorrow\'s temperature); pre-existing evidence which has already been taken into account is part of the prior and as more evidence accumulates the prior is largely by the evidence rather than any original assumption, provided that the original assumption admitted the possibility of what the evidence is suggesting. The terms \"prior\" and \"posterior\" are generally relative to a specific datum or observation.\n\n== Uninformative priors ==\n\nAn \'\'uninformative prior\'\' expresses vague or general information about a variable.\nThe term \"uninformative prior\" is a misnomer; such a prior might be called a \'\'not very informative prior\'\'.\nUninformative priors can express information such as \"the variable is positive\" or \"the variable is less than some limit\".\n\nThe use of an uninformative prior typically yields results which are not too different from conventional statistical analysis,\nas the likelihood function often yields more information than the uninformative prior.\n\nSome attempts have been made at finding probability distributions in some sense logically required by the nature of one\'s state of uncertainty; these are a subject of philosophical controversy. For example, [[Edwin T. Jaynes]] has published an argument [\'\'a reference here would be useful\'\'] based on [[Lie group]]s that if one is so uncertain about the value of the aforementioned proportion \'\'p\'\' that one knows only that at least one voter will vote for Kerry and at least one will not, then the conditional probability distribution of \'\'p\'\' given one\'s state of ignorance is the [[sebaran seragam]] dina interval [0, 1].\n\n== Improper priors ==\n\nIf Bayes\' therorem is written as \n:P(A_i|B) = \\frac{P(B | A_i) P(A_i)}{\\sum_j P(B|A_j)P(A_j)}\\, ,\nthen it is clear that it would remain true if all the prior probabilities P(Ai) and P(Aj) were multiplied by a given constant; the same would be true for a [[continuous random variable]]. The posterior probabilites will still sum (or integrate) to 1 even if the prior values do not, and so the priors only need be specified in the correct proportion. \n\nTaking this idea further, in many cases the sum or integral of the prior values may not even need to be finite to get sensible answers for the posterior probabilities. When this is the case, the prior is called an \'\'\'improper prior\'\'\'. Some statisticians use improper priors as uninformative priors. For example, if they need a prior distribution for the mean and variance of a random variable, they may assume p(m,v)~1/v (for v>0) which would suggest that any value for the mean is equally likely and that a value for the positive variance becomes less likely in inverse proportion to its value. Since\n:\\int_{-\\infty}^{\\infty} dm\\, = \\int_{0}^{\\infty} \\frac{1}{v} \\,dv = \\infty \nthis would be an improper prior both for the mean and for the variance. \n \n== Sumber sejen ==\n\n* Andrew Gelman, John B. Carlin, Hal S. Stern, and Donald B. Rubin. \'\'Bayesian Data Analysis\'\', 2nd edition. CRC Press, 2003.\n\n[[Category:Probability and statistics]]','/* Uninformative priors */',13,'Budhi','20041224032424','',0,0,1,0,0.105052588556,'20041231123527','79958775967575'); INSERT INTO cur VALUES (1230,0,'Kovarian','Dina [[probability theory]] jeung [[statistik]], \'\'\'covariance\'\'\' antara dua nilai-[[real number |real]] [[variabel random]] \'\'X\'\' jeung \'\'Y\'\', nu mibanda [[nilai ekspektasi]] \'\'E\'\'(\'\'X\'\') = μ jeung \'\'E\'\'(\'\'Y\'\') = ν diartikeun ku:\n: \\operatorname{cov}(X, Y) = E((X - \\mu) (Y - \\nu)).\nIeu sarua jeung rumus di handap nu ilahar dipake keur ngitung dina kaayaan nu sabenerna:\n: \\operatorname{cov}(X, Y) = \\operatorname{E}(X Y) - \\mu \\nu\n\nKeur vektor-kolom variabel random \'\'X\'\' jeung \'\'Y\'\' mibanda nilai μ jeung ν, sarta \'\'n\'\' jeung \'\'m\'\' komponen skalar, kovarian dihartikeun jadi matrik \'\'n\'\'×\'\'m\'\' \n\n:\\operatorname{cov}(X, Y) = \\operatorname{E}((X-\\mu)(Y-\\nu)^\\top).\n\nLamun \'\'X\'\' jeung \'\'Y\'\' [[statistical independence|independent]], mangka kovarian sarua jeung nol. Hal ieu sabab dina kaayaan bebas, E(X·Y) = E(X)·E(Y). Sabalikna, sanajan, teu bener: mungkin yen \'\'X\'\' sarta \'\'Y\'\' teu bebas, kovarian-na masih keneh nol.\n\nLamun \'\'X\'\' jeung \'\'Y\'\' nilai-riil variabel random sarta \'\'c\'\' ngarupakeun konstanta (\"konstanta\", di hal ieu, hartina non-random), mangka nuturkeun kanyataan ngarupakeun akibat tina harti kovarian:\n\n:\\operatorname{cov}(X, X) = \\operatorname{var}(X)\n:\\operatorname{cov}(X, Y) = \\operatorname{cov}(Y, X)\n:\\operatorname{cov}(cX, Y) = c\\, \\operatorname{cov}(X, Y)\n:\\operatorname{cov}\\left(\\sum_i{X_i}, \\sum_j{Y_j}\\right) = \\sum_i{\\sum_j{\\operatorname{cov}\\left(X_i, Y_j\\right)}}\n\nKeur nilai-vektor variabel random, cov(\'\'X\'\', \'\'Y\'\') sarta cov(\'\'Y\'\', \'\'X\'\') masing-masing transpos.\n\nKovarian kadangkala disebut ukuran \"linear bebas\" antara dua variabel random. Ieu teu frase lain sarua hartina yen harti nu leuwih formal dina aljabar linier (tempo [[linear dependence]]), sanajan hartina henteu pakait. [[Correlation]] ngarupakeun konsep pakait nu raket dipake keur ngukur tingkat kabebasan dua variabel.\n\n[[de:Kovarianz]]\n[[it:Covarianza]]\n[[no:Kovarians]]','',13,'Budhi','20040917031949','',0,0,0,0,0.895058020435,'20040917031949','79959082968050'); INSERT INTO cur VALUES (1231,0,'Kernel_(mathematics)','Kecap \'\'\'\'\'kernel\'\'\'\'\' mibanda sababaraha harti dina [[matematik]], kadang pakait jeung hal sejen, kadangkala heunteu. Di handap ieu sababaraha artikel ngeunaan kernel leuwih jentre dina : [[kernel (algebra)]], [[kernel of a function]].\n\n==Operator Kernel==\n\nDina [[mathematical analysis|analysis]], one consider an integral [[linear operator|operator]] T which transforms a [[Fungsi (matematik)|function]] f into a function Tf given by the [[integral (calculus)|integral]] formula\n\n: (Tf)(x) := \\int_{-\\infty}^{\\infty} K(x,y)f(y)\\, dy.\n\nThe function \'\'K\'\' that appears in this formula is the \'\'\'kernel\'\'\' of the operator \'\'T\'\'. This usage applies also to [[convolution]] operators such as the [[Dirichlet kernel]]. This type of kernel is used in the [[kernel trick]] which has applications in several fields of applied mathematics.\n\n==Kernels in algebra and category theory==\n\nUnrelated to this, if \'\'f\'\' is any [[Fungsi (matematik)|function]] in any context, then the \'\'kernel\'\' of \'\'f\'\' is a certain [[equivalence relation]] on the [[domain (function)|domain]] of \'\'f\'\' which is defined in terms of \'\'f\'\'. For more on this in general, see [[kernel of a function]].\n\nThis notion is used heavily in [[abstract algebra]]. But in the case of [[Mal\'cev algebra]]s, it can be replaced by a simpler definition; the \'\'kernel\'\' of a [[homomorphism]] f is the [[preimage]] under f of the [[zero element]] of the [[codomain]]. For more on this, see [[kernel (algebra)]].\n\nFinally, for this last notion of kernel is generalised in a certain sense in [[category theory]]; the \'\'kernel\'\' of a [[morphism]] \'\'f\'\' is the [[difference kernel]] of \'\'f\'\' and the corresponding [[zero morphism]] (if this exists). For more on this, see [[kernel (category theory)]].\n\n=== Kernel of a linear map ===\n\nPerhaps the best-known case of the concept of kernel in algebra is that of the kernel of a [[linear map]]. The kernel of a linear map is the same thing as its [[null space]].','/* Kernels in algebra and category theory */',13,'Budhi','20041224212848','',0,0,1,0,0.777558816959,'20041224212848','79958775787151'); INSERT INTO cur VALUES (1232,0,'Posterior','#REDIRECT [[Zootomical_terms_of_location]]','',13,'Budhi','20040817132655','',0,1,0,1,0.044899808264,'20040817132743','79959182867344'); INSERT INTO cur VALUES (1233,0,'Zootomical_terms_of_location','In [[zootomy]], several terms are used to describe the location of [[organ (anatomy)|organ]]s and other structures in the body of [[bilateria|bilateral]] [[animal]]s. These terms are listed and explained here. In some cases, the terminology in [[human anatomy]] may differ from that in general [[anatomy]] (see below). Some specific details of human anatomy are described under [[anatomical position]].\n\n==Directions==\n[[Image:Anatomical-directions-kangaroo.jpg|right|frame|Anatomical directions and planes shown on a kangaroo.]]\n\n===General usage===\nAnimals typically have one end with a head and mouth, with the opposite end often having the anus and tail. The head end is the \'\'\'cranial\'\'\' end; the tail end is the \'\'\'caudal\'\'\' end. Within the head itself, \'\'\'rostral\'\'\' refers to the direction toward the end of the nose, and caudal is still used to refer to the tail direction.\n\nThe surface or side of the body normally oriented upwards, away from the pull of gravity,\nis the \'\'\'dorsal\'\'\' side; the opposite side, typically the one closest to the ground when walking on all legs, swimming or flying, is the \'\'\'ventral\'\'\' side. For example: in [[vertebrate]]s, the [[spine (anatomy)|spine]] or nerve chord is located on the \'\'dorsal\'\' side of the organism. A cow\'s udder is on the \'\'ventral\'\' side. A dolphin\'s dorsal fin is, unsurprisingly, on the \'\'dorsal\'\' side. \n\nThe right and left side (sometimes in [[Latin]]: \'\'\'dexter\'\'\' - right, and \'\'\'sinister\'\'\' - left) are given as viewed from the animal that is described.\n\n===Usage in human anatomy===\nIn human anatomy, the body and its parts are always described using the assumption that the body is in [[anatomical position]], i.e. standing upright.\n\nPortions of the body which are closer to the head end are \"\'\'\'superior\'\'\'\" (\"upper\"); those which are farther away are \"\'\'\'inferior\'\'\'\" (\"lower\") -- superior corresponds to cranial, and inferior to caudal. Objects near the front are \"\'\'\'anterior\'\'\'\"; those near the rear are \"\'\'\'posterior\'\'\'\" -- these correspond respectively to \"ventral\" and \"dorsal\". On the limbs, an object closer to the main body is \"\'\'\'proximal\'\'\'\"; an object farther away is \"\'\'\'distal\'\'\'\".\n\nThe terms \"anterior\" and \"posterior\" should not be used when referring to most animals however, and are particularly incorrect for [[quadruped]]s.\n\n==Planes==\n===General usage===\nThree basic reference planes are used in zoological anatomy. The \'\'\'sagittal\'\'\' plane divides the body into left and right halves. A \'\'\'coronal\'\'\' plane divides the body into dorsal and ventral halves. A \'\'\'transverse\'\'\' plane divides the body into cranial and caudal halves. \n\n===Usage in human anatomy===\nSometimes the orientation of certain planes need to be distinguished, for instance in [[medical imaging]] techniques such as [[computed axial tomography|CT scans]], [[magnetic resonance imaging|MRI scans]] or [[positron emission tomography|PET scans]]. One imagines a human in [[anatomical position]] (standing, arms hanging down with palms to the front) and an X-Y-Z [[cartesian coordinate system|coordinate system]] with the X-Y plane parallel to the ground, the X-axis going from left to right, the Y-axis passing from front to back, and the Z-axis going up and down.\n\n*A \'\'\'transverse\'\'\' or \'\'\'axial\'\'\' plane is an X-Y plane, parallel to the ground, which (in humans) separates the superior from the inferior, or put another way, the head from the feet. \n*A \'\'\'coronal\'\'\' or \'\'\'frontal\'\'\' plane is an X-Z plane, perpendicular to the ground, which (in humans) separates the anterior from the posterior, the front from the back, the ventral from the dorsal.\n*A \'\'\'sagittal\'\'\' plane is a Y-Z plane, perpendicular to the ground and to the coronal plane, which separates left from right. The midsagittal plane is the specific sagittal plane that is exactly in the middle of the body.\n\n==Relative directions==\nStructures near the midline are called \'\'\'medial\'\'\' and those near the sides of animals are called \'\'\'lateral\'\'\'. Therefore, medial structures are closer to the midsagittal plane, lateral structures are further from the midsagittal plane. Structures in the midline of the body are \'\'\'median\'\'\'. For example, your cheeks are lateral to your nose and the tip of the nose is in the median line. \n\nStructures that are close to the center of the body are \'\'\'proximal\'\'\' or \'\'\'central\'\'\', while ones far removed are \'\'\'distal\'\'\' or \'\'\'peripheral\'\'\'. For example, the hands are at the distal end of the arms, while the shoulders are at the proximal ends. These terms can also be used relatively to organs, for example the proximal end of the [[urethra]] is attached to the [[urinary bladder | bladder]].\n\nStructures on or closer to the body´s surface are \'\'\'superficial\'\'\' (or \'\'\'external\'\'\') and those further inside are \'\'\'profound\'\'\' or \'\'\'deep\'\'\' (or \'\'\'internal\'\'\'). \n\nWhen speaking of inner organs, \'\'\'visceral\'\'\' means close to or attached to the organ, while \'\'\'parietal\'\'\' is more distant. For example, the visceral [[pleural cavity|pleura]] is attached to the lung and the parietal pleura is attached to the chest wall.\n\n===Relative directions in the limbs===\nIn the limbs, the terms \'\'\'cranial\'\'\' and \'\'\'caudal\'\'\' are used in the regions proximal to the carpus (the [[wrist]], in the forelimb) and the tarsus (the [[ankle]] in the hindlimb). Objects and surfaces closer to or facing towards the head are \'\'cranial\'\'; those facing away or further from the head are \'\'caudal\'\'. \n\nDistal to the carpal joint, the term \'\'\'dorsal\'\'\' replaces \'\'\'cranial\'\'\' and \'\'\'palmar\'\'\' replaces \'\'\'caudal\'\'\'. Similarly, distal to the tarsal joint the term \'\'\'dorsal\'\'\' replaces \'\'\'cranial\'\'\' and and \'\'\'plantar\'\'\' replaces \'\'\'caudal\'\'\'. For example, the top of a [[dog]]\'s [[paw]] is its \'\'dorsal\'\' surface; the underside, either the \'\'palmar\'\' (on the forelimb) or the \'\'plantar\'\' (on the hindlimb) surface.\n\nThe sides of the forearm are named after its bones: Structures closer to the [[radius (bone)|radius]] are \'\'\'radial\'\'\', and structures closer to the [[ulna]] are \'\'\'ulnar\'\'\'. Similarly, in the lower leg, structures near the [[tibia]] (shinbone) are \'\'\'tibial\'\'\' and structures near the [[fibula]] are \'\'\'fibular\'\'\' (or \'\'\'peroneal\'\'\').\n\n==Relative Motions==\n\n\'\'\'Flexion\'\'\' means approximating adjacent parts of the body (usually at a joint) and \'\'\'extension\'\'\' means separating them. For example, the legs are flexed at the knee joints when sitting down, and extended when standing up. Generally, flexion produces an acute [[angle]] between adjacent parts, with its vertex at the joint, and extension produces an obtuse angle. One exception to this rule is in the [[ankle joint]] where moving the foot such that the toes move upwards is [[dorsiflexion]] and moving the foot such that the toes move downwards is [[plantar flexion]].\n\n\'\'\'Adduction\'\'\' means moving a part of the body toward or past its median line or toward the long axis of a limb. \'\'\'Abduction\'\'\' means moving a part of the body away from its median line or away from the long axis of a limb. For example, adducting the thighs brings the legs together, and abducting the thighs spreads the legs apart. Similarly, adducting the fingers brings them into contact with one another, and abducting the fingers spreads them apart.\n\n\'\'\'Rotation\'\'\' means moving a part about its long axis, for example, in turning the neck. \'\'\'Supination\'\'\' means rotation of the forearm such that the palm of the hand faces forward or upward, and \'\'\'pronation\'\'\' means rotation of the forearm such that the palm of the hand faces backward or downward; the forearm with the hand is supinated or pronated at the [[elbow]]. Similar movements may be accomplished at the [[ankle]], where supination results in the foot tipping inward relative to its long axis, and pronation results in the foot tipping outward; \'\'overpronation\'\' may contribute to the condition [[flatfoot]].\n\nAn \'\'\'anterograde\'\'\' motion is in the normal direction of flow, while \'\'\'retrograde\'\'\' means reversed flow. For example, passage of food from the mouth to the stomach is in an anterograde direction, and [[GERD|gastric reflux]] is in a retrograde direction.\n\n== Tempo oge ==\n\n[[Nomina Anatomica Veterinaria]]\n\n[[Category:Anatomi]]','/* Tempo oge */',20,'DiN','20050303205847','',0,0,1,0,0.164722377045,'20050303205847','79949696794152'); INSERT INTO cur VALUES (1234,0,'Panyakit_Alzheimer','(\'\'Seratan Kang Ilén Kardani ti milis Kisunda\'\')\n\nPanyakit B (belik, boson, budeg, bodo, balelo, balangah, busiat, bedegong, jsb) anu ku urang kulon mah disebut Alzheimer atawa Senile Dementia tea, nyaeta turuna kapinteran jeung fungsi mental kusabab aya perobahan tina jaringan otak, bisa kulantaran sel otak anu murungkut, pambuluh darah otak anu acak-acakan, atawa bisa oge jarak antara sel otak ngaanggangan sabab kurangna substansi anu dipake komunikasi antara sel-sel otak. Panyakit ieu biasana nyerang ka jelema anu geus kolot katompernakeun, babandinganana tina sapuluh rebu urang (nu geus karolot) bakal aya salapan urang anu keuna ku ieu panyakit, lolobana mah karandapan ku awewe.\n\nJaringan otak merlukeun zat anu disebut acetylcholine, somatostatin, P substance, jeung eropinephrine. Kakurangan zat kasebut bakal ngakibatkeun nuruna fungsi mental atawa timbulna panyakit B. Pangaruh luar saperti kadaharan anu loba ngandung alumunium jeung mangan, atawa infeksi tina sumsum tulang belakang, bisa oge ngalantarankeun timbulna ieu panyakit.\n\nCiri-ciri panyakit B:\n\n*Kapinteran mimiti turun (bodo - intellectual decline).\n*Panca indra kurang sensitif (budeg jsb)\n*Hese neangan kecap keur nyarita (balelo - anomia).\n*Teu bisa migawe pagawean sapopoe (belegug - apraxia).\n*Poho kana kaparigelan anu kungsi kacangking (boloho).\n*Teu bisa konsentrasi (balangah).\n*Paroman bingung (bengong)\n*Kurang ingetan, biasana teu bisa ngingetkeun anu can lila kajadian.\n*Embung campur gaul jeung batur.\n*Leungiteun karikatan (boyot - slow movement).\n*Gampang aral (ngulit bawang - agitation).\n*Teu bisa ngandali palawangan (boson - incontinence).\n\nKumaha mariksana?\n\nLamun aya nu gering sarupa kitu, biasana sirahna dipariksa make: CT Scan, sinar-X, MRI (Magnetic Resonance Imaging) atawa ku EEG (Electroencephalography). Tina hasil pamariksaan bakal kapanggih karusakan naon anu karandapan ku otakna.\n\nKumaha ngubaranana?\n\nNya teuing atuh, da tepi ka kiwari oge can aya obat anu tokcer keur ngilangkeun panyakit B. Aya oge obat iwal ukur ngajaga efek samping tina panyakit B, sarupaning: Tacrine phosphatidyl choline, anti-psychotics, serotonin, carbamazepine, anticonvulsant jsb.\n\nKumaha ngurus jalma anu boga panyakit B?\n\n*Ulah diantep sosoranganan, utamana lamun ka jalan.\n*Ulah mercayakeun ka budak sina ngurus manehna.\n*Lamun teu bisa nalingakeun, leuwih hade dititipkeun ka panti jompo.\n*Amankeun barang-barang anu matak pibahayaeun.\n\n[[Category:Panyakit]]\n\n{{pondok}}','',3,'Kandar','20050105170701','',0,0,0,0,0.049569777702,'20050303211247','79949894829298'); INSERT INTO cur VALUES (1235,0,'Exponential_function','[[da:Eksponentialfunktion]]\n[[de:Exponentialfunktion]]\n[[fr:Exponentielle]]\n[[pl:Funkcja_wyk%C5%82adnicza]]\n[[Category:Complex analysis]]\n\'\'\'Fungsi eksponen\'\'\' ngarupakeun salah sahiji [[Fungsi (matematik)|fungsi]] penting dina [[matematik]]. It is written as exp(\'\'x\'\') or \'\'e\'\'\'\'x\'\', where \'\'e\'\' is the [[e (mathematical constant)|base of the natural logarithm]].\n\n[[image:exp.png|right|The exponential function is nearly flat (climbing slowly) for negative x\'s, and climbs quickly for positive x\'s.]]\n\nAs a function of the \'\'[[real number|real]]\'\' variable \'\'x\'\', the [[graph of a function|graph]] of \'\'e\'\'\'\'x\'\' is always positive (above the \'\'x\'\' axis) and increasing (viewed left-to-right). It never touches the \'\'x\'\' axis, although it gets arbitrarily close to it (thus, the \'\'x\'\' axis is a horizontal [[asymptote]] to the graph). Its [[inverse function]], the [[natural logarithm]], ln(\'\'x\'\'), is defined for all positive \'\'x\'\'.\n\nSometimes, especially in the [[science]]s, the term \'\'\'exponential function\'\'\' is reserved for functions of the form \'\'ka\'\'\'\'x\'\',\nwhere \'\'a\'\', called the \'\'base\'\', is any positive real number. This article will focus initially on the exponential function with base \'\'e\'\'.\n\nIn general, the [[variable]] \'\'x\'\' can be any real or [[complex number|complex]] number, or even an entirely different kind of mathematical object; see the [[#Formal definition|formal definition below]].\n\n==Sipat==\n\nUsing the natural logarithm, one can define more general exponential functions. The function\n: a^x=e^{x \\ln a}\ndefined for all \'\'a\'\' > 0, and all real numbers \'\'x\'\', is called the \'\'\'exponential function with base\'\'\' \'\'\'\'\'a\'\'\'\'\'.\n\nNote that the equation above holds for \'\'a\'\' = \'\'e\'\', since\n: e^{x \\ln e}=e^{x\\left(1\\right)}=e^x.\n\nExponential functions \"translate between addition and multiplication\" as is expressed in the following \'\'exponential laws\'\':\n: a^0 = 1\n: a^1 = a\n: a^{x + y} = a^x a^y\n: a^{x y} = \\left( a^x \\right)^y\n: {1 \\over a^x} = \\left({1 \\over a}\\right)^x = a^{-x}\n: a^x b^x = (a b)^x\n\nThese are valid for all positive real numbers \'\'a\'\' and \'\'b\'\' and all real numbers \'\'x\'\' and \'\'y\'\'. Expressions involving [[fraction]]s and [[Radical (mathematics)|roots]] can often be simplified using exponential notation because:\n: {1 \\over a} = a^{-1}\nand, for any \'\'a\'\' > 0, real number \'\'b\'\', and integer \'\'n\'\' > 1:\n: \\sqrt[n]{a^b} = \\left(\\sqrt[n]{a}\\right)^b = a^{b/n}\n\n==Derivatives and differential equations==\n\nThe importance of exponential functions in mathematics and the sciences stems mainly from properties of their [[derivative]]s. In particular,\n\n: {d \\over dx} e^x = e^x\n\nThat is, \'\'e\'\'\'\'x\'\' is its own [[derivative]], a property unique among real-valued functions of a real variable. Other ways of saying the same thing include:\n*The slope of the graph at any point is the height of the function at that point.\n*The rate of increase of the function at \'\'x\'\' is equal to the value of the function at \'\'x\'\'.\n*The function solves the [[differential equation]] \'\'y\'\'′ = \'\'y\'\'.\n\nIn fact, many differential equations give rise to exponential functions, including the [[Schrödinger equation]] and the [[Laplace\'s equation]] as well as the equations for [[simple harmonic motion]].\n\nFor exponential functions with other bases:\n\n: {d \\over dx} a^x = (\\ln a) a^x\n\nThus \'\'any\'\' exponential function is a [[constant]] multiple of its own derivative.\n\nIf a variable\'s growth or decay rate is [[proportionality (mathematics)|proportional]] to its size — as is the case in unlimited population growth (see [[Malthusian catastrophe]]), continuously compounded [[interest]], or [[radioactive decay]] — then the variable can be written as a constant times an exponential function of time.\n\n==Formal definition==\n\nThe exponential function e\'\'x\'\' can be defined in two equivalent ways, as an [[infinite series]]:\n: e^x = \\sum_{n = 0}^{\\infty} {x^n \\over n!} = 1 + x + {x^2 \\over 2!} + {x^3 \\over 3!} + {x^4 \\over 4!} + \\cdots\nor as the [[limit of a sequence]]:\n: e^x = \\lim_{n \\to \\infty} \\left( 1 + {x \\over n} \\right)^n\n\nIn these definitions, n! stands for the [[factorial]] of \'\'n\'\' and \'\'x\'\' can be any [[real number]], [[complex number]], element of a [[Banach algebra]] (for example, a [[square matrix]]), or member of the field of [[p-adic numbers|\'\'p\'\'-adic numbers]].\n\nFor further explanation of these definitions and a proof of their equivalence, see the article [[Definitions of the exponential function]].\n\n== On the complex plane ==\n\nWhen considered as a function defined on the [[complex number|complex plane]], the exponential function retains the important properties\n: e^{z + w} = e^z e^w\n: e^0 = 1\n: e^z \\ne 0\n: {d \\over dz} e^z = e^z\nfor all \'\'z\'\' and \'\'w\'\'.\n\nIt is a [[holomorphic function]] which is periodic with [[imaginary number|imaginary]] period 2 \\pi i and can be written as\n: e^{a + bi} = e^a (\\cos b + i \\sin b)\nwhere \'\'a\'\' and \'\'b\'\' are real values. This formula connects the exponential function with the [[trigonometric function]]s and to the [[hyperbolic function]]s. Thus we see that all [[elementary function]]s except for the [[polynomial]]s spring from the exponential function in one way or another.\n\nSee also [[Eulers formula in complex analysis]] [[Euler\'s formula]].\n\nExtending the natural logarithm to complex arguments yields a [[multi-valued function]], ln(\'\'z\'\'). We can then define a more general exponentiation:\n: z^w = e^{w \\ln z}\nfor all complex numbers \'\'z\'\' and \'\'w\'\'. This is also a multi-valued function. The above stated exponential laws remain true if interpreted properly as statements about multi-valued functions.\n\nThe exponential function maps any [[line]] in the complex plane to a [[logarithmic spiral]] in the complex plane with the center at the [[origin]]. This can be seen by noting that the case of a line parallel with the real or imaginary axis maps to a line or [[circle]].\n\n== Matrices and Banach algebras ==\n\nThe definition of the exponential function given above can be used verbatim for every [[Banach algebra]], and in particular for square [[matrix (mathematics)|matrices]]. In this case we have\n: e^{x + y} = e^x e^y \\mbox{ if } xy = yx\n: e^0 = 1\n: \'\'e\'\'\'\'x\'\' is invertible with inverse \'\'e\'\'−\'\'x\'\'\nIn addition, the derivative of exp at the point \'\'x\'\' is that linear map which sends \'\'u\'\' to \'\'u\'\' · \'\'e\'\'\'\'x\'\'.\n\nIn the context of non-commutative Banach algebras, such as algebras of matrices or operators on [[Banach space|Banach]] or [[Hilbert space|Hilbert]] spaces, the exponential function is often considered as a function of a real argument:\n: f(t) = e^{t A}\nwhere \'\'A\'\' is a fixed element of the algebra and \'\'t\'\' is any real number. This function has the important properties\n: f(s + t) = f(s) f(t)\n: f(0) = 1\n: f\'(t) = A f(t)\n\n== On Lie algebras ==\nThe \"exponential map\" sending a [[Lie algebra]] to the [[Lie group]] that gave rise to it shares the above properties, which explains the terminology. In fact, since \'\'\'R\'\'\' is the Lie algebra of the Lie group of all positive real numbers with multiplication, the ordinary exponential function for real arguments is a special case of the Lie algebra situation. Similarly, since the Lie algebra M(\'\'n\'\', \'\'\'R\'\'\') of all square real matrices belongs to the Lie group of all invertible square matrices, the exponential function for square matrices is a special case of the Lie algebra exponential map.\n\n==Tempo oge==\n*[[exponential growth]]','',13,'Budhi','20041224213352','',0,0,1,0,0.731811902827,'20041224213352','79958775786647'); INSERT INTO cur VALUES (1236,0,'Natural_logarithm','[[Category:Complex analysis]]\nThe \'\'\'natural logarithm\'\'\' is the [[logarithm]] to the base \'\'[[e (mathematical constant)|e]]\'\', where \'\'e\'\' is approximately equal to 2.71828... (no exact fraction can be given, as \'\'e\'\' is an [[irrational number]] just like [[pi]]). The natural logarithm is defined for all positive [[real number|real numbers]] \'\'x\'\' and can also be defined for non-zero [[complex number]]s as will be explained below. Although this function was not introduced by [[John Napier|Napier]], it is sometimes known as the \'\'\'Naperian Logarithm\'\'\'. \n
\n[[image:ln .png|The natural logarithm goes to minus infinity as x goes to 0.]]
\nln(x)\n
\n\n==Notational conventions==\n\nMathematicians generally understand either \"ln(\'\'x\'\')\" or \"log(\'\'x\'\')\" to mean loge(\'\'x\'\'), i.e., the natural logarithm of \'\'x\'\', and write \"log10(\'\'x\'\')\" if the base-10 logarithm of \'\'x\'\' is intended. Engineers, biologists, and some others write only \"ln(\'\'x\'\')\" or (occasionally) \"loge(\'\'x\'\')\" when they mean the natural logarithm of \'\'x\'\', and take \"log(\'\'x\'\')\" to mean log10(\'\'x\'\'). \n\nMost of the reason for thinking about base-10 logarithms became obsolete shortly after about 1970 when hand-held calculators became widespread (for more on this point, see [[common logarithm]]). Nonetheless, since calculators are made and often used by engineers, the conventions to which engineers were accustomed continued to be used on calculators, so now most non-mathematicians take \"log(\'\'x\'\')\" to mean the base-10 logarithm of \'\'x\'\' and use only \"ln(\'\'x\'\')\" to refer to the natural logarithm of \'\'x\'\'. As recently as 1984, [[Paul Halmos]] in his autobiography heaped contempt on what he considered the childish \"ln\" notation, which he said no mathematician had ever used. (The notation was in fact invented in 1893 by Irving Stringham, professor of mathematics at [[University of California, Berkeley|Berkeley]].) At the time of this writing (2003), many mathematicians have adopted the \"ln\" notation, but \"log\" also remains in widespread use.\n\nTo avoid all confusion, Wikipedia uses the notation ln(\'\'x\'\') for the natural logarithm of \'\'x\'\' and log10(\'\'x\'\') for the base-10 logarithm of \'\'x\'\'.\n\n==Ln is the inverse of the natural exponential function==\n\nThis function is the [[inverse function]] of the [[exponential function]],\nthus it holds \n:e^{\\ln(x)} = x \\,\\!      for all positive \'\'x\'\' and \n:\\ln(e^x) = x \\,\\!      for all real \'\'x\'\'.\n\nLogarithms can be defined to any positive base other than 1, not just \'\'e\'\', and they are always useful for solving equations in which the unknown appears as the exponent of some other quantity.\n\n==What\'s so \"natural\" about them?==\n\nInitially, it seems that in a world using base 10 for nearly all calculations, this base would be more \"natural\" than base \'\'e\'\'. The reason we call ln(\'\'x\'\') \"natural\" is twofold: first, the natural logarithm can be defined quite easily using a simple integral or [[Taylor series]] as will be explained below; this is not true of other logarithms. Second, expressions in which the unknown variable appears as the exponent of \'\'e\'\' occur much more often than exponents of 10 (because of the \"natural\" properties of the [[exponential function]] which allow it to describe growth and decay behaviors), and so the natural logarithm is more useful in practice.\nTo put it concretely, consider the problem of differentiating a logarithmic function:\n:\\frac{d}{dx}\\log_b(x) =\\frac{1}{x \\cdot \\ln b} \nWhen \'\'x\'\' is equal to 1, and the base (b) is \'\'e\'\', then the slope of the graph will be 1.\n\n== Definitions ==\n\n\nFormally, ln(\'\'a\'\') may be defined as the area under the graph ([[integral]]) of\n1/\'\'x\'\' from 1 to \'\'a\'\', that is,\n:\\ln(a)=\\int_1^a \\frac{1}{x}\\,dx.\n\nThis defines a logarithm because it satisfies the fundamental property\nof a logarithm:\n:\\ln(ab)=\\ln(a)+\\ln(b) \\,\\!\nThis can be shown by defining \\phi(t)=at and using the [[substitution rule|substitution rule of integration]] as follows:\n\n:\n\\ln (ab) \n= \\int_1^{ab} \\frac{1}{x} \\; dx \n= \\int_1^a \\frac{1}{x} \\; dx \\; + \\int_a^{ab} \\frac{1}{x} \\; dx \n=\\int_1^{a} \\frac{1}{x} \\; dx \\; + \\int_1^{b} \\frac{1}{t} \\; dt \n= \\ln (a) + \\ln (b)\n\n\nThe number e can then defined as the unique real number with ln(e) = 1.\n\nAlternatively, if the [[exponential function]] has been defined first using an [[infinite series]], the natural logarithm may be defined as its [[inverse function]], meaning ln(\'\'x\'\') is that number for which e^{ln(x)} = x Since the range of the exponential function is all positive real numbers and since the exponential function is strictly increasing, this is well-defined for all positive \'\'x\'\'.\n\n== Derivative, Taylor series and complex arguments ==\n\nThe [[derivative]] of the natural logarithm is given by\n:\\frac{d}{dx}\\ln(x)=\\frac{1}{x}.\nThis leads to the [[Taylor series]]\n:\\ln(1+x)=\\sum_{n=1}^\\infty \\frac{(-1)^{n+1}}{n} x^n\\quad{\\rm for}\\quad \\left|x\\right|<1.\n\nOne may define ln(\'\'z\'\') also for all non-zero [[complex number|complex numbers]] \'\'z\'\'. The above Taylor expansion remains valid for all \'\'complex\'\' numbers \'\'x\'\' with absolute value less than 1. If the non-zero complex number \'\'z\'\' is expressed in [[polar coordinate system|polar coordinates]] as z = r e^{i \\phi} with \'\'r\'\' > 0 and -\\pi < \\phi \\le \\pi, then\n:\\ln(z) = \\ln(r) + i\\phi \\,\\!\nSo defined, ln is [[holomorphic function|holomorphic]] for all complex numbers which are not non-positive reals, and it has the property\n:e^{\\ln(z)} = z \\,\\!     for all nonzero \'\'z\'\'\nOne has to be careful, because several properties familiar from the real logarithm are no longer valid for this complex extension. For example, ln(\'\'e\'\'\'\'z\'\') does not always equal \'\'z\'\', and ln(\'\'zw\'\') does not always equal ln(\'\'z\'\') + ln(\'\'w\'\').\n\nA somewhat more natural definition of ln(\'\'z\'\') interprets it as a [[multi-valued function]]: for z = r e^{i \\phi} we set\n:\\ln(z) = \\ln(r) + i(\\phi + 2 \\pi k) \\,\\! : \'\'k\'\' any [[integer]] }\nThis is the set of \'\'all\'\' complex numbers \'\'u\'\' for which e^u = z, because e^{2\\pi i} = 1(see [[Euler\'s identity]]). \n\n\nThe preferred way to deal with multivalued functions like this in complex analysis is via [[Riemann surface]]s: the function ln is then non defined on the complex plane but instead on a suitable Riemann surface having countably many \"leaves\" and the values of the function differ by 2π\'\'i\'\' from leaf to leaf.\n\n== The natural logarithm in integration ==\n\nThe natural logarithm allows simple [[integral|integration]] of functions of the form \'\'g\'\'(\'\'x\'\') = \'\'f\'\' \'(\'\'x\'\')/\'\'f\'\'(\'\'x\'\'): an [[antiderivative]] of \'\'g\'\'(\'\'x\'\') is given by ln(|\'\'f\'\'(\'\'x\'\')|). This is the case because of the [[chain rule]] and the following fact:\n\n:{d \\over dx}\\left( \\ln \\left| x \\right| \\right) = {1 \\over x}\n\nHere is an example in the case of \'\'g\'\'(\'\'x\'\') = tan(\'\'x\'\'):\n\n:\\int \\tan (x) \\,dx = \\int {\\sin (x) \\over \\cos (x)} \\,dx\n:\\int \\tan (x) \\,dx = \\int {-{d \\over dx} \\cos (x) \\over {\\cos (x)}} \\,dx\nLetting \'\'f\'\'(\'\'x\'\') = cos(\'\'x\'\') and f\'(\'\'x\'\')= - sin(\'\'x\'\'):\n:\\int \\tan (x) \\,dx = -\\ln{\\left| \\cos (x) \\right|} + C\n:\\int \\tan (x) \\,dx = \\ln{\\left| \\sec (x) \\right|} + C\n\nwhere \'\'C\'\' is an [[arbitrary constant of integration]].\n\nThe natural logarithm can be integrated using [[integration by parts]]:
\n\n:\\int \\ln (x) \\,dx = x \\ln (x) - x + C\n\n\'\'Tempo oge\'\': [[Logarithmic integral]]\n\n[[fr:logarithme naturel]]\n[[ja:自然対数]]\n[[pl:Logarytm naturalny]]','/* The natural logarithm in integration */',13,'Budhi','20040901070836','',0,0,0,0,0.73896286345,'20040901070836','79959098929163'); INSERT INTO cur VALUES (1237,0,'Mathematical_product','#redirect [[product (mathematics)]]','',13,'Budhi','20040818003307','',0,1,0,1,0.047405229903,'20040818003356','79959181996692'); INSERT INTO cur VALUES (1238,0,'Product_(mathematics)','[[fr:Produit mathématique]]\n\nDina [[matematik]], \'\'\'produk\'\'\' nyaeta hasil [[multiplication|multiplying]], or an expression that identifies [[divisor|factor]]s to be multiplied. The order in which [[real number|real]] or [[complex number|complex]] numbers are multiplied has no bearing on the product; this is known as the [[commutativity|commutative law]] of multiplication. When [[matrix (mathematics)|matrices]] or members of various other [[associative algebra]]s are multiplied the product usually depends on the order of the factors; in other words, matrix multiplication, and the multiplications in those other algebras, are non-commutative.\n\nSeveral products are considered in mathematics:\n* Products of the various classes of [[number]]s\n* The [[dot product]] and [[cross product]] are forms of multiplication of [[vector (spatial)|vector]]s.\n* The product of [[matrix (mathematics)|matrices]]; see [[matrix multiplication]].\n* The pointwise product of two [[Fungsi (matematik)|fungsi]].\n* Products in [[ring (mathematics)|rings]] and [[field (mathematics)|field]]s of many kinds.\n* It is often possible to form the product of two (or more) mathematical objects to form another object of the same kind, e.g. \n** the [[cartesian product|cartesian product of sets]],\n** the [[product of groups]], \n** the [[product of rings]],\n** the [[product topology|product of topological spaces]],\n** for the general treatment, see [[product (category theory)]].','',13,'Budhi','20041224213607','',0,0,1,0,0.605845448377,'20041224213607','79958775786392'); INSERT INTO cur VALUES (1239,0,'Geometric_mean','The \'\'\'geometric mean\'\'\' of a set of [[positive data]] is defined as the [[product (mathematics)|product]] of all the members of the set, raised to a power equal to the [[reciprocal]] of the number of members. \n\nIn a formula: the geometric mean of \n\'\'a1\'\', \'\'a2\'\', ..., \'\'an\'\' is (a_1 \\cdot a_2 \\dotsb a_n)^{1/n}, which is \\sqrt[n]{a_1 \\cdot a_2 \\dotsb a_n}.\n\nThe geometric mean is useful to determine \"average factors\". For example, if a stock rose 10% in the first year, 20% in the second year and fell 15% in the third year, then we compute the geometric mean of the factors 1.10, 1.20 and 0.85 as (1.10 × 1.20 × 0.85)1/3 = 1.0391... and we conclude that the stock rose on average 3.91 percent per year.\n\nThe geometric mean of a data set [[inequality of arithmetic and geometric means|is always smaller than or equal to]] the set\'s [[arithmetic mean]] (the two means are equal if and only if all members of the data set are equal). This allows the definition of the [[arithmetic-geometric mean]], a mixture of the two which always lies in between.\n\nThe geometric mean is also the \'\'arithmetic-harmonic mean\'\' in the sense that if two [[sequence|sequences]] (\'\'a\'\'\'\'n\'\') and (\'\'h\'\'\'\'n\'\') are defined:\n:a_{n+1} = \\frac{a_n + h_n}{2}, \\quad a_1=\\frac{x + y}{2}\nand\n:h_{n+1} = \\frac{2}{\\frac{1}{a_n} + \\frac{1}{h_n}}, \\quad h_1=\\frac{2}{\\frac{1}{x} + \\frac{1}{y}}\nthen \'\'a\'\'\'\'n\'\' and \'\'h\'\'\'\'n\'\' will converge to the geometric mean of \'\'x\'\' and \'\'y\'\'.\n\n\n==Pakaitna jeung sebaran log-normal==\n\nThe geometric mean is also related to the [[log-normal distribution]].\nThe log-normal distribution is a distribution which is normal for the logarithm\ntransformed values. By a simple set of logarithm transformations we see that the\ngeometric mean is the exponentiated value of the mean of the log transformed\nvalues, e.g. emean(ln(X));\n\nTo see this, the [[product]] form of the geometric mean computation is expressed as:\n\n:\\left(\\prod_{i=1}^Nx_i\\right)^{1/n}\n\nBy using [[logarithmic identities]] to transform the formula, we can express the multiplications as a sum and the power as a multiplication.\n\n:\\exp\\left[\\frac1n\\sum_{i=1}^N\\ln x_i\\right].\n\nThis is simply computing the [[arithmetic mean]] of the logarithm transformed values of x_i (i.e. the arithmetic mean in log space) and then using the exponentiation to return the computation to real space.\n\n==Tempo oge==\n\n[[average]], [[arithmetic mean]], [[arithmetic-geometric mean]], [[generalized mean]], [[harmonic mean]], [[geometric standard deviation]], [[inequality of arithmetic and geometric means]], [[log-normal distribution]], [[product]].\n\n==Tumbu kaluar==\n\n*[http://www.sengpielaudio.com/calculator-geommean.htm Calculation of the geometric mean of two numbers and comparison to the arithmetic solution]\n*[http://www.cut-the-knot.org/Generalization/means.shtml Arithmetic and geometric means]\n\n[[nl:meetkundig gemiddelde]]\n[[pl:%C5%9Arednia geometryczna]]','/* Relationship to the log-normal distribution */',13,'Budhi','20041224085411','',0,0,1,0,0.725185155741,'20041224085411','79958775914588'); INSERT INTO cur VALUES (1240,0,'Geometri_simpangan_baku','\'\'\'Geometri simpangan baku\'\'\' ngajelaskeun kumaha sumebarna data tina susunan average nu ditempo nyaeta [[geometric mean]]. Lamun mean tina susunan {\'\'A\'\'1, \'\'A\'\'2, ... , \'\'A\'\'n} dilambangkeun ku μ\'\'g\'\', maka geomteri simpangan baku nyaeta\n\n: \\sigma_g = \\exp \\left( \\sqrt{ \\sum_{i=1}^n ( \\ln A_i - \\ln \\mu_g )^2 \\over n } \\right) \\qquad \\qquad (1) .\n\n==Panurunan==\n\nLamun geometri mean nyaeta\n: \\mu_g = \\sqrt[n]{ A_1 A_2 ... A_n } \nsaterusna dicokot dina bentuk [[natural logarithm]] dua sisi ngahasilkeun\n: \\ln \\mu_g = {1 \\over n} \\ln (A_1 A_2 ... A_n) .\nHasil logaritma ngarupakeun jumlah logaritma, sabab kitu\n: \\ln \\mu_g = {1 \\over n} [ \\ln A_1 + \\ln A_2 + ... + \\ln A_n ] .\nBisa ditempo yen \\ln \\, \\mu_g ngarupakeun [[arithmetic mean]] tina susunan data \\{ \\ln A_1, \\ln A_2, ..., \\ln A_n \\} , saba kitu aritmetika simpangan baku tina susunan nu sarua bakal jadi \n: \\ln \\sigma_g = \\sqrt{ \\sum_{i=1}^n ( \\ln A_i - \\ln \\mu_g )^2 \\over n } .\n\'\'\'Koreksi: aritmetika simpangan baku susunan ieu nunjukeun hal nu bener. Ngan heunteu keur simpangan baku. Ngabuktikeun salahna, itung kovarian dua susunan data ku cara di luhur. Hasil eksponensial nunjukeun yen kovarian teu-negatif, nu taya alesan (kovarian bisa jadi negatif).\'\'\nHasil eksponensial dua sisi dina persamaan (1). Q.E.D.\n\n==Geometri skor standar==\n\nGeometri versi [[skor standar]] nyaeta\n\n: z = {\\ln ( x/\\mu_g ) \\over \\ln \\sigma_g } .\n\nLamun data geometri mean, simpangan baku, jeung skor-z dipikanyaho, maka [[raw score]] bisa di-rekonstruksi ku\n: x = \\mu_g \\sigma_g^z. \n\n==Hubunganna jeung sebaran log-normal==\nGeometri simpangan baku pakait jeung [[sebaran Log-normal|sebaran log-normal]].\nSebaran log-normal nyaeta sebaran normal hasil transformasi nilai logaritmik. Ku cara susunan transformasi logaritma sederhana bisa ditempo ten geometri simpangan baku ngarupakeun nilai eksponensial tina simpangan baku nilai transformasi log(e.g. exp(stdev(ln(A))));\n\nSabab kitu, sampel data geometri mean jeung geometri simpangan baku ti populasi log geometric mean jeung geometric simpangan baku bisa dipake keur nga-estimasi confidence interval ku jalan arithmetic mean jeung simpangan baku nu digunakeun keur nga-estimasi confidence interval dina sebaran normal. Keur diskusi sacara lengkep tempo di [[sebaran Log-normal|sebaran log-normal]].\n\n==Tempo ogé==\n\n[[geometric mean]], [[sebaran Log-normal]], [[natural logarithm]]\n\n[[en:Geometric standard deviation]]','/* Geometri skor standar */',13,'Budhi','20040908040712','',0,0,0,0,0.224879019998,'20040908040712','79959091959287'); INSERT INTO cur VALUES (1241,0,'Log-normal_distribution','#REDIRECT [[Sebaran Log-normal]]\n','Log-normal distribution dipindahkeun ka Sebaran Log-normal',13,'Budhi','20040818014815','',0,1,0,1,0.879119044057204,'20040818014815','79959181985184'); INSERT INTO cur VALUES (1242,0,'Skor_atah','Dina [[statistik]] sarta analisa data, \'\'\'skor atah\'\'\' nyaeta data asli nu acan dirobah – contona, hasil tina [[test]] siswa (contona, angka tina jawaban nu bener) salaku lawan tina skor sanggeus dirobah kana [[skor standar]] atawa rengking atawa nu sarupa.','',13,'Budhi','20040908040737','',0,0,0,0,0.368037573233,'20040908040737','79959091959262'); INSERT INTO cur VALUES (1243,0,'Geometric_standard_deviation','#REDIRECT [[Geometri simpangan baku]]\n','Geometric standard deviation dipindahkeun ka Geometri simpangan baku',13,'Budhi','20040818021521','',0,1,0,1,0.586053638333505,'20040818021521','79959181978478'); INSERT INTO cur VALUES (1244,6,'Exp.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040818033513','',0,0,0,1,0.292911090229555,'20041224213352','79959181966486'); INSERT INTO cur VALUES (1245,6,'Anatomical-directions-kangaroo.jpg','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040818033721','',0,0,0,1,0.706394566880907,'20050303205905','79959181966278'); INSERT INTO cur VALUES (1246,0,'List_of_probability_topics','This is a \'\'\'list of probability topics\'\'\', by Wikipedia page. \nIt overlaps with the (alphabetical) [[daptar jejer statistis]]. There are also the [[list of probabilists]] and [[list of statisticians]].\n\n==General aspects==\n\n*[[Probability]]\n*[[Randomness]], [[Pseudorandomness]], [[Quasirandom]]\n*[[Randomization]], [[hardware random number generator]]\n*[[Random number generator]]\n*[[Random sequence]]\n*[[Coin flipping]]/tossing\n*[[Uncertainty]]\n*[[Statistical variability]]\n*[[Observational error]]\n*[[Average]]\n*[[Probability interpretations]]\n*[[Markovian]]\n*[[Statistical regularity]]\n*[[Central tendency]]\n*[[Bean machine]]\n*[[Relative frequency]]\n*[[Frequency probability]]\n*[[Maximum likelihood]]\n*[[Bayesian probability]]\n*[[Principle of indifference]]\n*[[Cox\'s theorem]]\n*[[Eclectic probability]]\n*[[Principle of maximum entropy]]\n*[[Information entropy]]\n*[[Urn problem]]s\n*[[Extractor]]\n*[[Aleatoric]], [[aleatoric music]]\n*[[Free probability]]\n*[[Exotic probability]]\n*[[Schrödinger method]]\n\n==Foundations of probability theory==\n\n*[[Probability theory]]\n*[[Sample space]]\n*[[Probability space]]\n*[[Probability axioms]]\n*[[Normalizing constant]]\n*[[Event (probability theory)]]\n*[[Elementary event]]\n*[[Mutually exclusive]]\n*[[Boole\'s inequality]]\n*[[Probability density function]]\n*[[Cumulative distribution function]]\n*[[Law of total probability]]\n*[[Law of total expectation]]\n*[[Law of total variance]]\n*[[Almost surely]]\n*[[Cox\'s theorem]]\n*[[Edwin Thompson Jaynes]]\n*[[Bayesianism]]\n*[[Prior probability]]\n*[[Posterior probability]]\n*[[Borel\'s paradox]]\n*[[Bertrand\'s paradox]]\n*[[Coherence (philosophical gambling strategy)]]\n*[[Dutch book]]\n\n==[[Random variable]]s==\n\n*[[Discrete random variable]]\n**[[Probability mass function]]\n*[[Constant random variable]]\n*[[Nilai ekspektasi]]\n**[[Jensen\'s inequality]]\n*[[Varian]]\n**[[Simpangan baku]]\n**[[Geometric standard deviation]]\n*[[Moment (mathematics)]]\n**[[Moment about the mean]]\n**[[Standardized moment]]\n***[[Skewness]]\n***[[Kurtosis]]\n***[[Locality]]\n**[[Cumulant]]\n**[[Factorial moment]]\n*[[Multivariate random variable]]\n*[[Independent identically-distributed random variables]]\n*[[Statistical independence]]\n**[[Conditional independence]]\n**[[Pairwise independence]]\n**[[Covariance]]\n**[[Covariance matrix]]\n**[[De Finetti\'s theorem]]\n*[[Correlation]]\n**[[Uncorrelated]]\n**[[Correlation function]]\n*[[Canonical correlation]]\n*[[Convergence of random variables]]\n*[[Markov\'s inequality]]\n*[[Chebyshev\'s inequality]]\n*[[Chernoff\'s inequality]]\n*[[Laws of large numbers]]\n**[[Asymptotic equipartition property]]\n**[[Typical set]]\n*[[Martingale]]\n**[[Azuma\'s inequality]]\n*[[Random field]]\n*[[Borel-Cantelli lemma]]\n\n==[[Conditional probability]]==\n\n*[[Conditional expectation]]\n*[[Conditional distribution]]\n*[[Marginal distribution]]\n*[[Bayes\' theorem]]\n*[[de Finetti\'s theorem]]\n*[[Rule of succession]]\n*[[Conditional independence]]\n\n==[[Probability distribution]]s==\n\n*[[Bose-Einstein statistics]]\n*[[Bernoulli distribution]]\n**[[Bernoulli trial]]\n*[[Sebaran beta]]\n*[[Sebaran binomial]]\n*[[Cantor distribution]]\n*[[Cauchy distribution]]\n*[[Continuity correction]]\n*[[Degenerate distribution]]\n*[[Erlang distribution]]\n*[[Sebaran eksponensial]]\n**[[Exponential family]]\n*[[Sebaran-F]]\n*[[Fermi-Dirac statistics]]\n*[[Fisher-Tippett distribution]]\n*[[Sebaran gamma]]\n*[[Geometric distribution]]\n*[[Graphical model]]\n*[[Maxwell-Boltzmann statistics]]\n*[[Moment (mathematics)]]\n**[[Moment about the mean]]\n**[[Standardized moment]]\n***[[Skewness]]\n***[[Kurtosis]]\n***[[Locality]]\n**[[Cumulant]]\n**[[Factorial moment]]\n**[[Nilai ekspektasi]]\n**[[Varian]]\n*[[Negative binomial distribution]]\n*[[Normal distribution]], also called the Gaussian distribution\n**[[Error function]]\n**[[Multivariate normal distribution]]\n**[[Matrix normal distribution]]\n*[[Memorylessness]]\n*[[Pareto distribution]]\n*[[Poisson distribution]]\n*[[Prior probability distribution]]\n*[[Sebaran chi-kuadrat]]\n*[[Sebaran-t student]]\n*[[Total variation|Total variation distance]]\n*[[Triangular distribution]]\n*[[Weibull distribution]]\n*[[Sebaran Wishart]]\n*[[Zeta distribution]]\n*[[Infinite divisibility]]\n\n== Properties of probability distributions ==\n\n*[[Central limit theorem]]\n**[[Illustration of the central limit theorem]]\n**[[Concrete illustration of the central limit theorem]]\n**[[Berry-Esséen theorem]]\n*[[Characteristic function]]\n*[[Edgeworth series]]\n*[[Location parameter]]\n*[[Maxwell\'s theorem]]\n*[[Moment-generating function]]\n*[[Probability-generating function]]\n*[[Vysochanskiï-Petunin inequality]]\n*[[Mutual information]]\n*[[Kullback-Leibler divergence]]\n\n==[[Applied probability]]==\n\n*\'\'Empirical findings\'\'\n**[[Benford\'s law]]\n**[[Pareto principle]]\n**[[Zipf\'s law]]\n\n==[[Stochastic process]]es==\n\n*[[Bernoulli process]]\n*[[Branching process]]\n*[[Brownian motion]]\n**[[Geometric Brownian motion]]\n**[[Wiener equation]]\n*[[Chapman-Kolmogorov equation]]\n*[[Ergodic theory]]\n*[[Galton-Watson process]]\n*[[Gauss-Markov process]]\n*[[Gaussian process]]\n*[[Girsanov\'s theorem]]\n*[[Ito\'s lemma]]\n*[[Law of the iterated logarithm]]\n*[[Lévy flight]]\n*[[Markov chain]]\n**[[Examples of Markov chains]]\n*[[Markov property]]\n**[[Hidden Markov model]]\n*[[Poisson process]]\n*[[Population process]]\n*[[Queueing theory]]\n**[[Erlang unit]]\n*[[Random walk]]\n*[[Random walk Monte Carlo]]\n*[[Stochastic calculus]]\n*[[Time series analysis]]\n**[[Anomali deret waktu]]\n*[[Wiener process]]\n\n==Geometric probability==\n\n*[[Buffon\'s needle]]\n*[[Integral geometry]]\n*[[Hadwiger\'s theorem]]\n\n==[[Statistics]]==\n\n*[[List of statistical topics]]\n*[[Statistical sample]]\n**[[Sampling (statistics)]]\n**[[Data point]]\n**[[Data set]]\n**[[Statistical population]]\n**[[Statistical phenomena]]\n*[[Statistical theory]]\n*[[Statistical inference]]\n*[[Null hypothesis]]\n*[[Confidence interval]]\n*[[Margin of error]]\n*[[Interval estimasi]]\n*[[Titik estimasi]]\n*[[Estimator]]\n*[[Bias (statistics)]]\n*[[Gauss-Markov theorem]]\n*[[Likelihood-ratio test]]\n*[[Multivariate statistics]]\n*[[Analisa varian]]\n*[[ANCOVA]]\n*[[Bayesian inference]]\n\n==[[Applied statistics]]==\n\n*[[Linear regression]]\n*[[Statistical unit]]\n*[[Statistical assembly]]\n*[[Model statistik]]\n\n==[[Gambling]]==\n\n*[[Luck]], [[chance]]\n*[[Game of chance]]\n*[[Odds]]\n*[[Betting]]\n**[[Spread betting]]\n*[[Bookmaker]]\n*[[Pari-mutuel gambling]]\n*[[Gambler\'s fallacy]]\n*[[Inverse gambler\'s fallacy]]\n*[[Pascal\'s wager]]\n*[[Gambler\'s ruin]]\n*[[Poker probability]]\n**[[Poker probability (Texas hold \'em)]]\n**[[Pot odds]]\n*[[Roulette]]\n**[[Martingale (roulette system)]]\n**[[The man who broke the bank at Monte Carlo]]\n*[[Lottery]]\n**[[Lottery machine]]\n**[[Draft lottery (1969)]]\n**[[Pachinko]]\n*[[Coherence (philosophical gambling strategy)]]\n\n==Coincidence==\n\n*[[Birthday paradox]]\n*[[Index of coincidence]]\n*[[Bible code]]\n*[[Spurious relationship]]\n\n==Algorithmics==\n\n*[[Probable prime]]\n*[[Probabilistic algorithm]] = [[Randomised algorithm]]\n*[[Metoda Monte Carlo]]\n*[[Las Vegas algorithm]]\n*[[Probabilistic Turing machine]]\n*[[Stochastic programming]]\n*[[Probabilistically checkable proof]]\n*[[Box-Muller transform]]\n*[[Metropolis algorithm]]\n*[[Gibbs sampling]]\n*[[Inverse transform sampling method]]\n\n==[[Financial mathematics]]==\n\n*[[Risk]]\n*[[Value at risk]]\n*[[Market risk]]\n*[[Risk-neutral measure]]\n*[[Volatility]]\n*[[Technical analysis]]\n\n==[[Physics]]==\n\n*[[Probability amplitude]]\n*[[Statistical physics]]\n*[[Boltzmann factor]]\n*[[Feynman-Kac formula]]\n*[[Fluctuation theorem]]\n*[[Information entropy]]\n*[[Vacuum expectation value]]\n*[[Brownian ratchet]]\n*[[Cosmic variance]]\n\n==[[Percolation theory]]==\n\n==[[Genetics]]==\n\n*[[Punnett square]]\n*[[Hardy-Weinberg principle]]\n\n==Historical==\n\n*\'\'[[The Doctrine of Chances]]\'\'\n\n[[Category:Topic lists]]','/* [[Statistics]] */',13,'Budhi','20041224044759','',0,0,1,0,0.661715139477,'20050208062724','79958775955240'); INSERT INTO cur VALUES (1247,0,'Simpangan_mutlak','\'\'\'Simpangan mutlak\'\'\' salah sahiji unsur susunan data nyaeta beda mutlak antara unsur jeung titik nu diberekeun. Titik tipikal tina simpangan ngarupakeun ukuran nilai boh [[median]] atawa [[mean]] tina susuna data.\n\n\'\'\'Rata-rata simpangan mutlak\'\'\' tina susunan data nyaeta [[average]] simpangan mutlak sarta [[kasimpulan statistik]] tina [[statistical dispersion]] atawa [[statistical variability|variability]]. \n\nRata-rata simpangan mutlak tina susunan data {\'\'x\'\'0, \'\'x\'\'1, ..., \'\'x\'\'\'\'n\'\'-1} is:\n:\\frac{\\sum_{i=0}^{n-1} |x_i-\\hat{x}|}{n}\ndimana \\hat{x} ngarupakeun nilai pilihan [[central tendency]] tina susunan data numana rata-rata simpangan mutlak keur diukur.\n\nMedian ngarupakeun titik minimal tina rata-rata simpangan mutlak susunan data. Contona, keur susunan {1,2,2,4,6}, median nyaeta 2 sedengkeun mean sarua jeung 3. Rata-rata simpangan mutlak tina median nyaeta (1+0+0+2+4)/5=1.4 sedengkeun rata-rata simpangan mutlak tina mean (kadangkala disebut \'\'\'simpangan mean\'\'\') nyaeta (2+1+1+1+3)/5=1.6.\n\nSacara umum, rata-rata simpangan mutlak tina mean nyaeta antara hiji sarta dua kali rata-rata simpangan mutlak tina median; kurang atawa sarua jeung [[simpangan baku]].','',13,'Budhi','20040904234950','',0,0,0,0,0.008223628163,'20040904235031','79959095765049'); INSERT INTO cur VALUES (1248,0,'Accuracy_and_precision','Dina [[science]], [[rékayasa]], [[industry]] and [[statistik]], \'\'\'akurasi\'\'\' is the degree of conformity of a measured or calculated quantity to its actual, nominal, or some other reference, value. \'\'\'Precision\'\'\' characterises the degree of mutual agreement among a series of individual measurements, values, or results.\n\n==A useful analogy==\n\nIn a common analogy illustrating the difference between \'\'accuracy\'\' and \'\'precision\'\', repeated measurements are compared to [[arrow]]s that are fired at a target. Accuracy describes the closeness of arrows to the [[bullseye]] at the target center. Arrows that strike closer to the bullseye are considered more accurate. The closer a system\'s measurements to the accepted value, the more accurate the system is considered to be.\n\nTo continue the analogy, precision would be size of the arrow cluster. When all arrows are grouped tightly together, the cluster is considered precise since they all struck close to the same spot, if not necessarily near the bullseye. The measurements are precise, though not necessarily accurate.\n\nHowever, it is \'\'not\'\' possible to reliably achieve accuracy without precision - if the arrows are not grouped close to one another, they cannot all be close to the bullseye.\n\n==Quantifying accuracy and precision==\n\nIdeally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the known value.\n\nThe accuracy and precision of a measurement process is usually established by repeatedly measuring some [[traceability|traceable]] reference standard. Such standards are defined in the [[SI|International System of Units]] and maintained by national standards organisations such as the [[National Institute of Standards and Technology]].\n\n[[Image:Accuracy_and_precision.png]]\n\nAccuracy is characterised as the difference between the [[mean]] of the measurements and the reference value, the [[bias (statistics)|bias]]. Establishing and correcting for bias is necessary for [[kalibrasi]].\n\nPrecision is usually characterised in terms of the [[standard deviation]] of the measurements, sometimes called the measurement process\'s [[standard error (statistics)|standard error]].\n\nA common convention in science and engineering is to express accuracy and/or precision implicitly by means of [[significant figures]]. Here, when not explicitly stated, the margin of error is understood to be one-half the value of the last significant place. For instance, a recording of \'8430 lbs\' would imply a margin of error of 5 lbs (the last significant place is the tens place), while \'8000 lbs\' would imply a margin of 500 lbs. To indicate a more accurate measurement that just happens to lie near a round number, one would use scientific notation: \'8.000 x 10^3 lbs\' indicates a margin of 0.5 lbs. However, reliance on this convention can lead to [[false precision]] errors when accepting data from sources that do not obey it.\n\nPrecision is sometimes stratified into:\n*\'\'Repeatability\'\' - the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and\n*\'\'Reproducibility\'\' - the variation arising using the same measurement process among different instruments and operators, and over longer time periods.','/* Quantifying accuracy and precision */',13,'Budhi','20041229230128','',0,0,1,0,0.833927902781,'20041229230128','79958770769871'); INSERT INTO cur VALUES (1249,0,'Alignments_of_random_points','
[[Image:Leylines80of137.png|Image of leyline simulation]]
\'\'80 4-point near-alignments of 137 random points\'\'
\n\n[[Statistik]] shows that if you put lots of [[random]] points on a bounded flat surface you can find many \'\'\'alignments of random points\'\'\'. Some people think that this shows that such things as [[ley line]]s exist naturally as [[coincidence]]s, and are therefore not interesting phenomena. Other people see this as a failure to understand [[scientific method]] which is about setting particular criteria for particular comparisons which can then reveal levels of [[probability]].\n\nOne precise definition which expresses the generally accepted meaning of \"alignment\" as: \n:\'\'a set of points, chosen from a given set of landmark points, all of which lie within at least one straight path of a given width w\'\'\n\nOne simple definition of \"straight path of width w\" is the set of all points within a distance of \'\'w\'\'/2 of a [[straight line]] on a plane, or a [[great circle]] on a sphere, or in general any [[geodesic]] on any other kind of [[manifold]]. Note that in general an uncountable number of infinitesimally different straight paths will contain any given set of points that are aligned in this way, so only the existence of at least one straight path is important to consider whether a set of points is an alignment. For this reason, it is easier to count the sets of points, rather than the paths themselves.\n\nThe width \'\'w\'\' is important: it allows the fact that real-world features are not mathematical points, and that their positions need not line up exactly for them to be considered in alignment.\n\nFor example, using a 1mm pencil line to draw alignments on an 50000:1 [[Ordnance Survey]] map, a suitable value of \'\'w\'\' would be 50m.\n\n== An estimate of the probability of alignments existing by chance ==\n\nStatistically, finding alignments on a landscape gets progressively easier as the area to be considered increases. One way of understanding this phenomenon is to see that the increase in the number of possible [[combination]]s of points in that area overwhelms the decrease in the probability that any given set of points in that area line up.\n\nThe number of alignments found is very sensitive to the allowed width \'\'w\'\', increasing approximately proportionately to \'\'w\'\'\'\'k\'\'-2, where \'\'k\'\' is the number of points in an alignment.\n\nFor those interested in the mathematics, the following is a very approximate estimate of the likelihood of alignments, assuming a plane covered with uniformly distributed \"significant\" points.\n\nConsider a set of \'\'n\'\' points in an area with approximate diameter \'\'d\'\'. Consider a valid line to be one where every point is within distance \'\'w\'\'/2 of the line (that is, lies on a track of width \'\'w\'\'.\n\nConsider all the unordered sets of \'\'k\'\' points from the \'\'n\'\' points, of which there are\n\n: \\frac {n!} {(n-k)!k!} \n\nWhat is the probability that any given set of points is co-linear in this way? Let\'s very roughly consider the line between the \"leftmost\" and \"rightmost\" two points of the \'\'k\'\' selected points (for some arbitrary left/right axis: we can choose top and bottom for the exceptional vertical case). These two points are by definition on this line. For each of the remaining \'\'k\'\'-2 points, the probability that the point is \"near enough\" to the line is roughly \'\'w\'\'/\'\'d\'\'. \n\nSo, the expected number of k-point ley lines is very roughly \n\n: \\frac {n!} {(n-k)!k!} \\left({\\frac{w}{d}}\\right)^{k-2}\n\nFor \'\'n\'\' >> \'\'k\'\' this is approximately\n\n: \\frac {n^k} {k!} \\left({\\frac{w}{d}}\\right)^{k-2}\n\nNow assume that area is equal to d^2, and say there is a density α of points such that n = \\alpha d^2.\n\nThen we have the expected number of lines equal to:\n\n: \\frac {\\alpha^k d^{2k}} {k!} \\left( {\\frac{w}{d}} \\right)^{k-2}\n\nand an area density of k-point lines of:\n\n: \\frac 1 {d^2} \\frac {\\alpha^k d^{2k}} {k!} \\left( {\\frac{w}{d}} \\right)^{k-2}\n\nGathering the terms in \'\'k\'\' we have an areal density of k-point lines of:\n\n: d^k \\frac {\\alpha^k} {k!} w^{k-2}\n\nThus, contrary to intuition, the number of k-point lines expected from random chance increases much more than linearly with the size of the area considered.\n\n== Computer simulation of alignments ==\n\n
[[image:leylines.png|Image of ley line simulation]]
\'\'607 4-point alignments of 269 random points\'\'
\n\n[[Computer simulation]]s show that points on a plane tend to form alignments similar to those found by ley hunters in numbers consistent with the order-of-magnitude estimates above, suggesting that ley lines may also be generated by chance. This phenomenon occurs regardless of whether the points are generated pseudo-randomly by computer, or from data sets of non-magical features such as pizza restaurants.\n\nIt is easy to find alignments of 4 to 8 points in reasonably small data sets with \'\'w\'\' = 50m.\nChoosing large areas or larger values of \'\'w\'\' makes it easy to find alignments of 20 or more points.\n\n==Tempo oge== \n* [[ley line]]s\n\n==Tumbu kaluar==\n* [http://www.glastonburytor.org.uk/tor-leymap.html A ley line map]\n* [http://www.boo.net/~jasonp/leyline.html Ley Lines and Coincidence:] discussion and computer simulation results\n* [http://www.megalithic.co.uk/asb_mapsquare.php The Megalithic Map] (which illustrates the distribution of major megaliths in the UK)\n* [http://www.anima.demon.co.uk/index.html \'\'Megalithia\'\'], a similar website with grid references for over 1,400 sites\n* [http://www.genuki.org.uk/big/parloc/download.html GENUKI Parish Database], including grid references for over 14,000 UK churches and register offices\n* [http://www.gazetteer.co.uk/ The Gazetteer of British Place Names] with over 50,000 entries\n\n[[Category:Geometry]]\n[[Category:Statistics]]','',13,'Budhi','20041224085307','',0,0,1,0,0.131898791125,'20041224085307','79958775914692'); INSERT INTO cur VALUES (1250,0,'Ancillary_statistic','Dina [[statistik]], \'\'\'simpangan statistik\'\'\' statistik numana [[probability distribution]] teu gumantung kana probability distributions nu ditempo nyaeta sebaran populasi statistik tina data nu dicokot. Konsep ieu mimiti dikenalkeun ku ahli statistik genetik Sir [[Ronald Fisher]].\n\n==Conto==\n\n* Anggap \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun [[independent identically distributed random variables|bebas sarta kasebar identik]], sarta [[sebaran normal |kasebar normal]] mibanda [[nilai ekspektasi]] μ jeung [[varian]] 1. (The use as an example, of this particular parametrized family of probability distributions, all having the same variance, is unrealistic, in that it amounts to a situation in which the statistician somehow \'\'knows\'\' the \'\'exact\'\' value of the polpulation variance, but can only estimate the population mean by using the observed values of the data \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\'.) Let\n\n::\\overline{X}_n=(X_1+\\,\\cdots\\,+X_n)/n\n\n:be the sample mean. The [[random variable]]\n\n::\\overline{X}_n-\\mu\n\n:is \'\'\'\'\'not\'\'\'\'\' an ancillary statistic, even though its probability distribution does not depend on μ That is because it is \'\'not a statistic\'\', since its value depends on the unobservable population mean μ\n\n:The random variable\n\n::\\max\\{\\,X_1,\\dots,X_n\\,\\}-\\min\\{\\,X_1,\\dots,X_n\\,\\}\n\n:\'\'is\'\' an ancillary statistic, because\n:*Its probability distribution does not change as μ changes, and\n:* it depends only on the data \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' and not on the unobservable parameter μ, i.e., it is a statistic.\n\n* In [[baseball]], suppose a scout observes a batter in \'\'N\'\' at-bats. Suppose (unrealistically) that the number \'\'N\'\' is chosen by some random process that is [[statistical independence|independent]] of the batter\'s ability -- say a coin is tossed after each at-bat and the result determines whether the scout will stay to watch the batter\'s next at-bat. The eventual data are the number \'\'N\'\' of at-bats and the number \'\'X\'\' of hits. The observed [[batting average]] \'\'X\'\'/\'\'N\'\' fails to convey all of the information available in the data because it fails to report the number \'\'N\'\' of at-bats (e.g., a batting average of 0.400, which is very high, based on only five at-bats does not inspire anywhere near as much confidence in the player\'s ability than a 0.400 average based on 100 at-bats). The number \'\'N\'\' of at-bats is an ancillary statistic because\n:* It is a part of the observable data (it is a \'\'statistic\'\'), and\n:* Its probability distribution does not depend on the batter\'s ability, since it was chosen by a random process independent of the batter\'s ability.\n\n:This ancillary statistic is an \'\'\'ancillary complement\'\'\' to the observed batting average \'\'X\'\'/\'\'N\'\', i.e., the batting average \'\'X\'\'/\'\'N\'\' is not a [[sufficiency (statistics)|sufficient statistic]], in that it conveys less than all of the relevant information in the data, but conjoined with \'\'N\'\', it becomes sufficient.','/* Conto */',13,'Budhi','20040917032203','',0,0,0,0,0.698587502678,'20040917032203','79959082967796'); INSERT INTO cur VALUES (1251,0,'Anomali_deret_waktu','\'\'\'Anomali deret waktu\'\'\' nyaeta lobana deviasi [[deret waktu]] tina [[mean]]. Harti sejen nyaeta itungan keur sakabeh deret waktu, contona keur unggal jam dina sapoe lamun siklus poe-an tina sababaraha variabel dicokot. Salaku pangganti mean aritmetik, indikator sejenna nyaeta [[locality]] oge bisa dipake, saperti oge [[median]] dina analisa sacara numerik.\n\nDina [[atmospheric sciences]], [[annual cycle]] iklim biasana make nilai mean. Conto nu kawentar dina anomali deret waktu atmosfer nyaeta indeks [[Southern Oscillation]] (SOI) jeung indeks [[North Atlantic Oscillation]]. SOI nyaeta komponen atmosfer [[El Niño]], sedengkeun [[NAO]] ngarupakeun pangaruh penting keur [[weather]] di [[Europe]] ku ayana modifikasi [[storm track]] nu datangna ti Atlantik.','',13,'Budhi','20041004003550','',0,0,0,0,0.174851964775,'20041004003550','79958995996449'); INSERT INTO cur VALUES (1252,0,'Autoregressive_conditional_heteroskedasticity','Dina [[econometrics]],\nmodel \'\'\'autoregressive conditional heteroskedasticity\'\'\' (ARCH) nimbangkeun yen wates salah [[varian]] ayeuna jadi fungsi wates salah varian dina waktu samemehna. \n\nLamun [[autoregressive moving average model]] di-asumsikeun keur kasalahan, modelna nyaeta model \'\'\'generalized autoregressive conditional heteroskedasticity\'\'\' (GARCH).\n\nSacara umum, lamun tes keur [[heteroskedasticity]] dina model econometric, tes nu panghadena [[White test]]. Hal sejen, lamun pakait jeung data [[deret waktu]], tes panghadena nyaeta tes Engle\'s ARCH. \n\n==Sumber sejen==\n\n* Tim Bollerslev. \"Generalized Autorregressive Conditional Heteroskedasticity\", \'\'Journal of Econometrics\'\', 31:307-327, 1986.\n\n* [[Robert F. Engle]]. \"Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation\", Econometrica 50:987-1008, 1982. \'\'(the paper which sparked the general interest in ARCH models)\'\'\n\n* Robert F. Engle. \"GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics\", \'\'Journal of Economic Perspectives\'\' 15(4):157-168, 2001. \'\'(a short, readable introduction)\'\'\n\n[[Category:statistics]]','',13,'Budhi','20041004003649','',0,0,0,0,0.940631328589,'20041004003649','79958995996350'); INSERT INTO cur VALUES (1253,0,'Perbandingan_Bayesian_model','Model data posterior probabiliti, P(H|D), ngagunakeun [[Bayes\' theorem]]:\n:P(H|D) = P(D|H)P(H)/P(D)\n\nWates konci data-dependent P(D|H) nyaeta [[likelihood]], jeung kadangkala disebut kajadian keur model H; evaluasi nu bener ngarupakeun konci dina model perbandingan Bayes.\n\nKajadian umumna [[normalizing constant]] atawa [[partition function]] tina kaputusan sejen, disebut model paramater kaputusan H ti data D.\n\nHal nu asup akal di model dua beda H1 jeung H2, parametrised ku model vektor \\theta_1 jeung \\theta_2 nu ditaksir make [[Bayes factor]] dirumuskeun ku\n\n: \\frac{P(D|H2)}{P(D|H1)} \n= \\frac{\\int P(\\theta_2|H2)P(D|\\theta_2,H2)\\,d\\theta_2}\n{\\int P(\\theta_1|H1)P(D|\\theta_1,H1)\\,d\\theta_1\n}.\n\n\n== Sumber sejen ==\n* Gelman, A., Carlin, J.,Stern, H. and Rubin, D. Bayesian Data Analysis. Chapman and Hall/CRC.(1995)\n\n* Bernardo, J., and Smith, A.F.M., Bayesian Theory. John Wiley. (1994)\n\n* Lee, P.M. Bayesian Statistics. Arnold.(1989).\n\n* Denison, D.G.T., Holmes, C.C., Mallick, B.K., Smith, A.F.M., Bayesian Methods for Nonlinear Classification and Regression. John Wiley. (2002).\n\n* Richard O. Duda, Peter E. Hart, David G. Stork (2000) \'\'Pattern classification\'\' (2nd edition), Section 9.6.5, p. 487-489, Wiley, ISBN 0471056693\n* Chapter 24 in [http://omega.math.albany.edu:8008/JaynesBook.html Probability Theory - The logic of science] by [[Edwin_Thompson_Jaynes|E. T. Jaynes]], 1994.\n* [[David J.C. MacKay]] (2003) Information theory, inference and learning algorithms, CUP, ISBN 0521642981, (also [http://www.inference.phy.cam.ac.uk/mackay/itila/book.html available online])\n\n== Tumbu kaluar ==\n\n* [http://www.inference.phy.cam.ac.uk/mackay/itila/ The on-line textbook: Information Theory, Inference, and Learning Algorithms], by [[David J.C. MacKay]], has many chapters on Bayesian methods, including introductory examples; compelling arguments in favour of Bayesian methods; state-of-the-art [[Monte Carlo methods]], [[message-passing methods]], and [[variational methods]]; and examples illustrating the intimate connections between Bayesian inference and [[data compression]].','',13,'Budhi','20040820234829','',0,0,0,0,0.925218183978,'20040820234926','79959179765170'); INSERT INTO cur VALUES (1254,0,'Sebaran_binomial','Dina [[matematik]], \'\'\'sebaran binomial\'\'\' ngarupakeun [[probability distribution]] diskrit nu ngajelaskeun angka \'\'keberhasilan\'\' tina sekuen \'\'n\'\' [[statistical independence|independent]] percobaan enya/heunteu, unggal nu hasil mibanda [[kamungkinan|probabiliti]] \'\'p\'\'. Saperti oge hasil/gagalna percobaan disebut oge percobaan Bernoulli atawa [[Bernoulli trial]]. Sebaran binomial ngarupakeun dasar nu kawentar keur [[binomial test]] tina [[statistical significance]].\n\nConto tipikalna nyaeta: 5% populasi ngarupakeun HIV-positip. Anjeun nyokot 500 urang sacara acak. Kumaha cara yen anjeun meunang 30 atawa leuwih HIV-positip?\nJumlah HIV-positip nu dicokot ku anjeun ngarupakeun [[variabel random]] \'\'X\'\' nu nuturkeun sebaran binomial mibanda \'\'n\'\' = 500 sarta \'\'p\'\' = .05. Hartina urang museurkeun kan probabiliti Pr[\'\'X\'\' ≥ 30].\n\nSacara umum, lamun variabel random \'\'X\'\' nuturkeun sebaran binomial mibanda paramater \'\'n\'\' sarta \'\'p\'\', dituliskeun \'\'X\'\' ~ B(\'\'n\'\', \'\'p\'\'). Probabiliti nu pasti sukses \'\'k\'\' dirumuskeun ku\n\n: P\\left[X = k\\right] = {n \\choose k} p^k \\left(1-p\\right)^{n-k}\\ \\mbox{for}\\ k = 0, 1, 2, \\cdots, n \n\ndimana\n\n:{n \\choose k}={n! \\over k!(n-k)!}\n\nngarupakeun [[binomial coefficient]] \"\'\'n\'\' milih \'\'k\'\'\" (oge dilambangkeun ku \'\'C\'\'(\'\'n\'\', \'\'k\'\')), ti mana ngaran sebaran. Rumus bisa dipikaharti saperti kieu: urang hayang \'\'k\'\' sukses (\'\'p\'\'\'\'k\'\') sarta \'\'n\'\' − \'\'k\'\' gagal ((1 − \'\'p\'\')\'\'n\'\' − \'\'k\'\'). Sanajan kitu, sukses \'\'k\'\' bisa kajadian dimana wae diantara \'\'n\'\' percobaan, sarta dimana C(\'\'n\'\', \'\'k\'\') beda jalan kasebarna sukses \'\'k\'\' dina sekuen \'\'n\'\' percobaan.\n\nLamun \'\'X\'\' ~ B(\'\'n\'\', \'\'p\'\'), mangka [[nilai ekspektasi]] \'\'X\'\' nyaeta \n: E\\left[X\\right] = np \nsarta [[varian]] nyaeta\n\n: \\mbox{var}\\left(X\\right) = np(1-p).\n\nNilai nu leuwih siga atawa [[mode]] \'\'X\'\' diberekeun ku integer panggedena kurang atawa sarua jeung (\'\'n\'\'+1)\'\'p\'\'; lamun \'\'m\'\' = (\'\'n\'\'+1)\'\'p\'\' ngarupakeun interger sorangan, mangka \'\'m\'\' − 1 sarta \'\'m\'\' duanana ngarupakeun mode.\n\nLamun \'\'X\'\' ~ B(\'\'n\'\', \'\'p\'\') sarta \'\'Y\'\' ~ B(\'\'m\'\', \'\'p\'\') ngarupakeun variabel binomial bebas, mangka \'\'X\'\' + \'\'Y\'\' oge ngarupakeun variabel binomial; sebaranna nyaeta \n\n: B\\left(n+m, p\\right).\n\nDua sebaran penting nu ngadeukeutan sebaran binomial nyaeta:\n\n[[image:BinDistApprox_large.png|right|250px|thumb|Binomial PDF and Normal approximation for n=6 and p=0.5.]]\n*Lamun \'\'np\'\' sarta \'\'n\'\'(1 − \'\'p\'\') leuwih gede ti 5 atawa sejenna, mangka \'\'pendekatan\'\' panghadena (dumasar kana [[continuity correction]] nu mungkin dipake) ka B(\'\'n\'\', \'\'p\'\') dirumuskeun ku [[sebaran normal]]\n\n:: N\\left(np, np\\left(1-p\\right)\\right).\n\n:\'\'Pendekatan\'\' ieu ngarupakeun \'\'\'\'\'huge time-saver\'\'\'\'\'; sajarahna, ieu mimiti dipake sebaran normal, dimimitian ku [[Abraham de Moivre]] dina bukuna \'\'[[The Doctrine of Chances]]\'\' taun 1733. Kiwari, bisa ditempo sabab tina [[central limit theorem]], B(\'\'n\'\', \'\'p\'\') ngarupakeun jumlah \'\'n\'\' bebas, \'\'identically distributed\'\' 0-1 [[indicator variable]]. \'\'\'Inget:\'\'\' ieu \'\'pendekatan\'\' hasilna teu akurat lamun teu make [[continuity correction]].\'\'\'Catetan:\'\'\' gambar nembongkeun normal and binomial [[probability density function]] (PDF) sarta lain [[cumulative distribution function]].\n\n:Contona, anggap anjeun nyokot sampel random \'\'n\'\' ti masarakat nu populasi loba sarta nyebutkeun ten maranehna satuju kana hiji \'\'pernyataan\'\'. Proporsi masakarat nu satuju tangtu gumantung kana sampel. Lamun grup sampel \'\'n\'\' masarakat diulang sarta bener-bener random, proprosi bakal nuturkeun sebaran normal nu mibanda mean sarua kana proporsi satuju sabenerna \'\'p\'\' dina populasi sarta mibanda simpangan baku σ = (\'\'p\'\'(1 − \'\'p\'\')/\'\'n\'\')1/2. Ukuran sampel \'\'n\'\' badag ngarupakeun hal nu hade sabab simpangan baku bakal jadi leutik, nu ngijinkeun keur estimasi nu hade keur paramater \'\'p\'\' nu teu dipikanyaho.\n\n*Lamun \'\'n\'\' badag sarta \'\'p\'\' leutik, mangka \'\'np\'\' ukuranna sedeng, mangka [[Poisson distribution]] mibanda parameter λ = \'\'np\'\' ngarupakeun \'\'pendekatan\'\' nu hade keur B(\'\'n\'\', \'\'p\'\').\n\nRumus keur [[Bézier curve]]s kailhaman ku sebaran binomial.\n\n[[Category:Probability distributions]]\n[[de:Binomialverteilung]]\n[[it:Variabile casuale Binomiale]]','',13,'Budhi','20040917032249','',0,0,0,0,0.147532932995,'20040917032249','79959082967750'); INSERT INTO cur VALUES (1255,0,'Normalizing_constant','Konsep ngeunaan \'\'\'normalizing constant\'\'\' ningkat dina [[probability theory]] jeung dina widang [[matematik]] sejenna.\n\n==Definition and examples==\n\nDina [[probability theory|tiori probabiliti]], \'\'\'normalisasi konstanta\'\'\' nyaeta konstanta nu di unggal tempat fungsi non negatip kudu dikalikeun dina usaha keur meunangkeun [[probability density function|fungsi probabiliti densiti]] atawa [[probability mass function|fungsi probabiliti masa]]. Contona, urang mibanda\n\n:\\int_{-\\infty}^\\infty e^{-x^2/2}\\,dx=\\sqrt{2\\pi\\,},\n\nmangka\n\n: \\varphi(x) = \\frac{1}{\\sqrt{2\\pi\\,}} e^{-x^2/2} \n\nngarupakeun fungsi densiti probabiliti. Hal ieu ngarupakeun densiti standar [[sebaran normal]]. (\'\'Standar\'\', dina kasus ieu hartina [[nilai ekspektasi]] sarua jeung 0 sarta [[varian]] sarua jeung 1.)\n\nSimilarly,\n\n:\\sum_{n=0}^\\infty \\frac{\\lambda^n}{n!}=e^\\lambda ,\n\nand consequently\n\n:f(n)=\\frac{\\lambda^n e^{-\\lambda}}{n!}\n\nis a probability mass function on the set of all nonnegative integers. This is the probability mass function of the [[Poisson distribution]] with expected value λ.\n\nThe normalizing constant for the [[Boltzmann distribution]] plays a central role in [[statistical mechanics]]. In that context, the normalizing constant is called the [[partition function (statistical mechanics)|partition function]].\n\n==Bayes\' theorem==\n\n[[Bayes\' theorem]] says that the posterior probability measure is proportional to the product of the prior probability measure and the [[likelihood function]] . \'\'Proportional to\'\' implies that one must multiply or divide by a normalizing constant in order to assign measure 1 to the whole space, i.e., to get a probability measure. In a simple discrete case we have\n\n:P(H_0|D) = \\frac{P(D|H_0)P(H_0)}{P(D)}\n\nwhere P(H0) is the prior probability that the hypothesis is true; P(D|H0) is the [[conditional probability]] of the data given that the hypothesis is true, but given that the data are known it is the [[likelihood function|likelihood]] of the hypothesis (or its parameters) given the data; P(H0|D) is the posterior probability that the hypothesis is true given the data. P(D) should be the probability of producing the data, but on its own is difficult to calculate, so an alternative way to describe this relationship is as one of proportionality:\n\n:P(H_0|D) \\sim P(D|H_0)P(H_0).\n\nSince P(H|D) is a probability, the sum over all possible (mutually exclusive) hypotheses should be 1, leading to the conclusion that\n\n:P(H_0|D) = \\frac{P(D|H_0)P(H_0)}{\\sum_i P(D|H_i)P(H_i)} .\n\nIn this case, the value \n\n:P(D)=\\sum_i P(D|H_i)P(H_i) \\;\n\nis the \'\'normalizing constant\'\'. It can be extended from countably many hypotheses to uncountably many by replacing the sum by an integral.\n\n==Non-probabilitistic uses==\n\nThe [[Legendre polynomials]] are characterized by [[orthogonality]] with respect to the uniform measure on the interval [− 1, 1] and the fact that they are \'\'\'normalized\'\'\' so that their value at 1 is 1. The constant by which one multiplies a polynomial in order that its value at 1 will be 1 is a normalizing constant.','/* Definition and examples */',13,'Budhi','20040917032325','',0,0,0,0,0.401022942923,'20041231123527','79959082967674'); INSERT INTO cur VALUES (1256,0,'Partition_function','[[fr:Fonction partage d\'un entier]]\n\n*Dina [[number theory]], tempo [[Partition function (number theory)]]\n*Dina [[statistical mechanics]], tempo [[Partition function (statistical mechanics)]]\n*Dina [[quantum field theory]], tempo [[Partition function (quantum field theory)]]\n*Dina [[game theory]], tempo [[Partition function (game theory)]]\n\n{{disambig}}','',13,'Budhi','20040818061955','',0,0,0,0,0.406500634927,'20040818061955','79959181938044'); INSERT INTO cur VALUES (1257,0,'Bayes_factor','Dina [[statistik]], the use of \'\'\'Bayes factors\'\'\' is a [[Bayesian]] alternative to classical [[hypothesis testing]].\n\nGiven a [[model]] selection problem in which we have to choose between two models \'\'M\'\'1 and \'\'M\'\'2, on the basis of a [[data vector]] \'\'\'\'\'x\'\'\'\'\'. The Bayes factor \'\'K\'\' is given by \n\n:K = \\frac{p(x|M_1)}{p(x|M_2)}.\n\nIn a sense this is a [[likelihood-ratio test]]. Generally, the models \'\'M\'\'1 and \'\'M\'\'2 will be [[persamaan paramétrik|parametrised]] by vectors of [[parameter]]s \\theta_1 and \\theta_2; thus \'\'K\'\' is given by\n\n:K = \\frac{p(x|M_1)}{p(x|M_2)} = \\frac{\\int \\,p(\\theta_1|M_1)p(x|\\theta_1 M_1)d\\theta_1}{\\int \\,p(\\theta_2|M_2)p(x|\\theta_2 M_2)d\\theta_2}.\n\nA value of \'\'K\'\' > 1 means that the data indicate that \'\'M\'\'1 is more likely than \'\'M\'\'2 and vice versa. [[Harold Jeffreys]] gave a scale for interpretation of \'\'K\'\':\n\n{|\n!K !!Strength of evidence\n|-\n! < 1 \n| Negative (supports M2) \n|-\n!1 to 3 \n| Barely worth mentioning\n|-\n!3 to 12 \n| Positive\n|-\n!12 to 150 \n| Strong \n|-\n! > 150 \n| Very strong\n|}\n\nMany Bayesian statisticians would use a Bayes factor as part of making a choice, but would also combine it with their estimates of the [[prior probability]] of each of the models and the [[loss function]]s associated with making the wrong choice.\n\n==Conto==\nSuppose we have a [[random variable]] which produces either a success or a failure. We want to consider a model \'\'M\'\'1 where the probability of success is \'\'q\'\'=1/2, and another model \'\'M\'\'2 where \'\'q\'\' is completely unknown and we take a [[prior distribution]] for \'\'q\'\' which is [[sebaran seragam|uniform]] on [0,1]. We take a sample of 200, and find 115 success and 85 failures. The likelihood is \n:{200 \\choose 115}q^{115}(1-q)^{85}.\nSo we have \n:P(X=115|M_1)={200 \\choose 115}\\left({1 \\over 2}\\right)^{200}=0.00595...\nbut \n:P(X=115|M_2)=\\int_{q=0}^1 1{200 \\choose 115}q^{115}(1-q)^{85}dq = {1 \\over 201} = 0.00497...\n \nThe ratio is then 1.197..., which is \"barely worth mentioning\" even if it points very slightly towards \'\'M\'\'1. \n\nThis is not the same as a classical likelihood ratio test, which would have found the [[maximum likelihood]] estimate for \'\'q\'\', namely 115/200=0.575, and from that get a ratio of 0.1045..., and so pointing towards \'\'M\'\'2. A [[frequentist]] hypothesis test would have produced an even more dramatic result, saying that that \'\'M\'\'1 could be rejected at the 5% confidence level, since the probability of getting 115 or more successes from a sample of 200 if \'\'q\'\'=1/2 is 0.0200..., and as a two-tailed test of getting a figure as extreme as or more extreme than 115 is 0.0400... Note that 115 is more than two standard deviations away from 100. \n\n\'\'M\'\'2 is a more complex model than \'\'M\'\'1 because it has a free parameter which allows it to model the data more closely. The ability of Bayes factors to take this into account is a reason why [[Bayesian inference]] has been put forward as a theoretical justification for and generalisation of [[Occam\'s razor]], reducing [[Type I error]]s.\n\n==Tempo oge==\n* [[Bayesian model comparison]]\n \n[[Category:Statistics]]','/* Conto */',13,'Budhi','20041224032248','',0,0,1,0,0.716825600582,'20041225130852','79958775967751'); INSERT INTO cur VALUES (1258,0,'Bayesian','\'\'\'Bayesian\'\'\' hartina metoda kamungkinan jeung statistik nu pakait jeung Reverend [[Thomas Bayes]] (c. 1702-1761) sarta [[Bayes\' theorem]] dina conditional probability. Sababarha widang nu terus diwangun sanggeus anjeunna pupus, nyaeta:\n* [[Bayesian probability]]\n* [[Bayesian inference]]\n* [[Bayesian network]]\n* [[Bayes factor]]\n* [[Bayesian model comparison]]\n* [[Bayesian filtering]]\n* [[Empirical Bayes method]]\n* [[Naive Bayesian classification]]\n\n\n{{disambig}}','',13,'Budhi','20040818222257','',0,0,0,0,0.201780935843,'20040818225627','79959181777742'); INSERT INTO cur VALUES (1259,0,'Sebaran_Weibull','Dina [[tiori probabiliti]] jeung [[statistik]], \'\'\'sebaran Weibull\'\'\' (nyokot tina ngaran [[Wallodi Weibull]]) nyaeta [[probability distribution]] kontinyu nu mibanda [[probability density function]]\n\n: f(x) = (k/\\lambda) (x/\\lambda)^{(k-1)} e^{-(x/\\lambda)^k} \\qquad \\mbox{for } x>0\n\nnumana \'\'k\'\' >0 nyaeta \'\'parameter bentuk\'\' jeung λ > 0 nyaetra \'\'parameter skala\'\' sebaran.\n\n[[Image:Weibull1.png]][[Image:Weibull2.png]]\n\nFungsi kumulatip densiti diartikeun ku \n: F(x) = 1- e^{-(x/\\lambda)^k} \\qquad \\mbox{for } x>0\n\n[[Sebaran eksponensial]] (lamun \'\'k\'\' = 1) sarta [[Rayleigh distribution|sebaran Rayleigh]] (lamun \'\'k\'\' = 2) ngarupakeun dua kasus husus dina sebaran Weibull. \n\nsebaran Weibull geus ilahar dipake dina model waktu sanggeus alat teknis gagal.\nLamun laju gagalna alat nurun dumasar kana waktu, mangka pilih \'\'k\'\' < 1 (hasil tina nurunna densiti \'\'f\'\'). Lamun laju gagalna alat angger kana waktu, mangka pilih \'\'k\'\' = 1, hasil tina nurunna fungsi \'\'f\'\'. Lamun laju gagalna alat naek kana waktu, mangka pilih \'\'k\'\' > 1 sarta tangtukeun densiti \'\'f\'\' nu naek ka arah maksimum sarta nurun salawasna. Pabrik salawasna nyadiakeun bentuk sarta skala paramater keur sebaran waktu hirup tina sababaraha alat. Sebaran Weibull bisa oge dipake model sebaran kecepatan angin di lokasi di bumi. Unggal lokasi dicirikeun ku sabagean parameter bentuk jeung skala.\n\n[[Nilai ekspektasi]] sarta [[simpangan baku]] tina [[variabel acak]] Weibull bisa ditembongkeun dina watesan [[fungsi gamma]]:\n\n:E(X) = λ Γ((k + 1) / k) sarta\n\n:var(X) = λ2[Γ((k + 2) / k) - Γ2((k + 1) / k)]\n\n==Tumbu kaluar==\n* [http://www.xycoon.com/Weibull.htm The Weibull distribution (with examples, properties, and calulators).]\n* [http://www.itl.nist.gov/div898/handbook/eda/section3/weibplot.htm The Weibull plot.]\n\n[[Category:Probability distributions]]\n[[sv:Weibullfördelning]]','',13,'Budhi','20041224211550','',0,0,1,0,0.76452431584,'20041224211550','79958775788449'); INSERT INTO cur VALUES (1260,0,'Wishart_distribution','In [[statistics]], the \'\'\'Wishart distribution\'\'\', named in honor of John Wishart, is any of a family of [[probability distribution]]s for nonnegative-definite [[matrix (math)|matrix]]-valued [[random variable]]s (\"random matrices\"), defined as follows. Suppose\n\n:X_1\\sim N_p(0,V),\n\ni.e. \'\'X\'\'1 is a \'\'p\'\'×1 column-vector-valued random variable (a \"random vector\") that is [[multivariate normal distribution | normally distributed]], whose [[expected value]] is the \'\'p\'\'×1 column vector whose entries are all zero, and whose [[variance]] is the \'\'p\'\'×\'\'p\'\' nonnegative definite matrix \'\'V\'\'. We have\n\n:E(X)=\\mu\nand\n:\\mbox{var}(X)=E((X-\\mu)(X-\\mu)\')=V\n\nwhere the transpose of any matrix \'\'A\'\' is denoted \'\'A\'\'′.\n\nFurther suppose \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' are [[statistical independence | independent]] and identically distributed. Then the Wishart distribution is the [[probability distribution]] of the \'\'p\'\'×\'\'p\'\' random matrix\n\n:S=\\sum_{i=1}^n X_i X_i\'.\n\nOne indicates that \'\'S\'\' has that probability distribution\nby writing\n\n:S\\sim W_p(V,n).\n\nThe positive integer \'\'n\'\' is the number of \'\'degrees of freedom\'\'.\n\nIf \'\'p\'\' = 1 and \'\'V\'\' = 1 then this distribution is a chi-square distribution.\n\nThe Wishart distribution arises frequently in [[likelihood-ratio test]]s in multivariate statistical analysis.\n\n[[Category:Probability distributions]]','',13,'Budhi','20040818064503','',0,0,0,1,0.081460502037,'20040818064503','79959181935496'); INSERT INTO cur VALUES (1261,0,'Sebaran_Wishart','Dina [[statistik]], \'\'\'sebaran Wishart\'\'\', ngaran keur ngahargaan ka John Wishart, salah sahiji kulawarga [[probability distribution]] keur nonnegative-definite nilai-[[matrix (math)|matrix]] [[variabel random ]] (\"matriks random\"), diartikeun di handap ieu. Anggap\n\n:X_1\\sim N_p(0,V),\n\ndina hal ieu \'\'X\'\'1 nyaeta \'\'p\'\'×1 nilai-vektor-kolom variabel random (\"vektor random\") nu ngarupakeun [[sebaran normal]], numana [[nilai ekspektasi]] nyaeta \'\'p\'\'×1 vektor kolom nu asup sakabehna nol, sarta [[varian]] nyaeta \'\'p\'\'×\'\'p\'\' matrik nonnegative definite \'\'V\'\'. Urang ngabogaan\n\n:E(X)=\\mu\njeung\n:\\mbox{var}(X)=E((X-\\mu)(X-\\mu)\')=V\n\ndimana unggal transpose matrik \'\'A\'\' dilambangkeun \'\'A\'\'′.\n\nSaterusna tempo \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' ngarupakeun [[statistical independence | independent]] and identically distributed. Saterusna sebaran Wishart nyaeta [[probability distribution]] tina matrik random \'\'p\'\'×\'\'p\'\' \n\n:S=\\sum_{i=1}^n X_i X_i\'.\n\nSalah sahiji yen \'\'S\'\' mibanda sebaran probabiliti dituliskeun ku\n\n:S\\sim W_p(V,n).\n\nInteger positip \'\'n\'\' ngarupakeun angka \'\'tingkat kabebasan\'\'.\n\nLamun \'\'p\'\' = 1 jeung \'\'V\'\' = 1 mangka ieu sebaran ngarupakeun sebaran chi-kuadrat.\n\nSebaran Wishart sering dipake [[likelihood-ratio test]] dina analisa multivariate statistik.\n\n[[Category:Probability distributions]]','',13,'Budhi','20040917032400','',0,0,0,0,0.149278617534,'20040917032400','79959082967599'); INSERT INTO cur VALUES (1263,0,'Bayesian_network','\'\'\'Jaringan Bayesian\'\'\' atawa \'\'\'Jaringan kapercayaan Bayesian\'\'\' nyaeta titik [[directed acyclic graph|grafik siklus langsung]] nu ngagambarkeun [[variabél]] jeung busur nu ngagambarkeun [[dependence relations|hubungan bebas]] antar variabel. Lamun hiji busur ti titik \'\'A\'\' ka titik sejen \'\'B\'\', bisa disebutkeun yen \'\'A\'\' ngarupakeun \'\'\'indung\'\'\' ti \'\'B\'\'. If a node has a known value, it is said to be an \'\'\'evidence\'\'\' node. A node can represent any kind of variable, be it an observed measurement, a parameter, a [[latent variable]], or a hypothesis. Nodes are not restricted to representing random variables; this is what is \"[[Bayesian]]\" about a Bayesian network.\n\nA Bayesian network is a representation of the joint distribution over all the variables represented by nodes in the graph. Let the variables be \'\'X(1)\'\', ..., \'\'X(n)\'\'. Let \'\'parents(A)\'\' be the parents of the node \'\'A\'\'. Then the joint distribution for \'\'X(1)\'\' through \'\'X(n)\'\' is represented as the product of the probability distributions \'\'p(X(i)\'\' | \'\'parents(X(i)))\'\' for \'\'i\'\' from 1 to \'\'n\'\'. If \'\'X\'\' has no parents, its probability distribution is said to be \'\'\'unconditional\'\'\', otherwise it is \'\'\'conditional\'\'\'.\n\nQuestions about dependence among variables can be answered by studying the graph alone. It can be shown that the graphical notion called [[d-separation]] corresponds to the notion of \'\'\'conditional independence\'\'\': if nodes \'\'X\'\' and \'\'Y\'\' are d-separated (given specified evidence nodes), then variables \'\'X\'\' and \'\'Y\'\' are independent given the evidence variables.\n\nIn order to carry out numerical calculations, it is necessary to further specify for each node \'\'X\'\' the probability distribution for \'\'X\'\' conditional on its parents. The distribution of \'\'X\'\' given its parents may have any form. However, it is common to work with discrete or Gaussian distributions, since that simplifies calculations.\n\nThe goal of inference is typically to find the conditional distribution of a subset of the variables, conditional on known values for some other subset (the \'\'\'evidence\'\'\'), and integrating over any other variables. Thus a Bayesian network can be considered a mechanism for automatically constructing extensions of [[Bayes\' theorem]] to more complex problems. \n\nBayesian networks are used for [[model]]ling knowledge in [[gene regulatory network]]s, [[medicine]], [[engineering]], [[text analysis]], [[image processing]], and [[decision support system]]s.\n\n==Tempo oge==\n\n*[[Machine learning]]\n\n== Sumber sejen ==\n* Enrique Castillo, José Manuel Gutiérrez, and Ali S. Hadi. \'\'Expert Systems and Probabilistic Network Models\'\'. Springer-Verlag, New York, 1997. ISBN 0-387-94858-9\n* Judea Pearl, \"Fusion, propagation, and structuring in belief networks\". \'\'Artificial Intelligence\'\', 29(3):241-288, 1986.\n\n[[Category:Machine learning]]\n\n[[de:Bayessches Netz]]','',13,'Budhi','20041224085004','',0,0,1,0,0.572010847075,'20041224085004','79958775914995'); INSERT INTO cur VALUES (1264,0,'Bayesian_filtering','Bayesian filtering nyaeta proses nu ngagunakeun [[Bayesian probability|Bayesian statistical methods]] keur klasifikasi dokument dina sababaraha kategori. \n\nBayesian filtering gained currency when it was described in the paper \"A Plan for Spam\" by [[Paul Graham]][http://www.paulgraham.com/spam.html], and has become popular as a mechanism to distinguish [[spam (e-mail)|spam]] [[email]]s from desirable emails. Many modern mail programs such as [[Mozilla Thunderbird]] implement Bayesian spam filtering.\n\nBayesian filters rely on the fact that particular words have different likelihoods of occurring across different categories. For instance, most email users will seldom see the word \"[[Viagra]]\" in legitimate email, but will encounter it frequently in spam email. To \'train\' the filter, the user must manually indicate into which category a particular document belongs, and the filter will then assign a probability to each word in the email.\n\nThis probability indicates the likelihood that, in the absence of any other evidence, the document belongs in a particular category. For instance, most spam filter users will end up assigning a very high spam probability to the words \"Viagra\" and \"Refinance\", but a very high not-spam probability to words they only see in legitimate emails, such as the names of friends and family members. When all of the evidence is taken together and a final spam probability is computed, the filter will mark the email as spam if it is considered extremely likely to be such.\n\nThe advantage of Bayesian spam filtering is that it can be trained on a user-by-user basis. The spam a user receives often has some relevance (and therefore statistical clustering), as for instance placing a personal ad may increase the likelihood of receiving personal-ad-related spam. The legitimate email a user receives will also tend to have a significant amount of statistical clustering, as many of a person\'s coworkers, friends, and family members will choose to discuss related subjects, and therefore use similar words. Because these two sets of words are unique for each user, Bayesian spam filtering can potentially offer greater filtering accuracy.\n\nWhile Bayesian filtering is most often used to identify spam, the technique can potentially be applied to classify any sort of document.\n\nThere are many good spam filters available. One of the most popular is PopFile which is available in sourceforge.net. This software is trained to differenciate between spam and legitimate mail and classify them accordingly.\n\n==Tumbu kaluar==\n*[http://www.paulgraham.com/spam.html A Plan for Spam]','/* External link */',13,'Budhi','20040901223221','',0,0,0,0,0.803810798937,'20040901223221','79959098776778'); INSERT INTO cur VALUES (1265,0,'Métode_émpiris_Bayes','Dina [[statistik]], \'\'\'métoda émpiris Bayes\'\'\' kaasup:\n\n*An \"underlying\" [[probability distribution]] of some unobservable quantity assigned to each member of a [[statistical population]]. This quantity is a [[random variable]] if a member of the population is chosen at random. The probability distribution of this random variable is not known, and is thought of as a property of the population.\n\n*An observable quantity assigned to each member of the population. When a random sample is taken from the population, it is desired first to estimate the \"underlying\" probability distribution, and then to estimate the value of the unobservable quantity assigned to each member of the sample.\n\nThis is probably incomprehensible without concrete examples.\n\n==Conto==\n\n===The original example, introduced by [[Herbert Robbins]] in 1956===\n\nEach customer of an insurance company has an \"accident rate\" Θ and is insured against \"accidents\"; the probability distribution of Θ is the \"underlying\" distribution, and is unknown. The number of \"accidents\" suffered by each customer in a specified baseline time period has a [[Poisson distribution]] whose expected value is the particular customer\'s \"accident rate\". That number of \"accidents\" is the observable quantity. A crude way to estimate the underlying probability distribution of the \"accident rate\" Θ is to estimate the proportion of members of the whole population suffering 0, 1, 2, 3, ... accidents during the specified time period to be equal to the corresponding proportion in the observed random sample. Having done so, it is then desired the \"accident rate\" of each customer in the sample. One may use the [[conditional probability|conditional]] expected value of the \"accident rate\" Θ given the observed number \'\'X\'\' of \"accidents\" during the baseline period. Given the assumed Poisson distribution of accidents, one can show that\n\n:E(\\Theta\\mid X=x)={(x+1)P(X=x+1) \\over P(X=x)}.\\qquad\\qquad\\qquad (*)\n\nThe quantities P(\'\'X\'\' = \'\'x\'\' + 1) and P(\'\'X\'\' = \'\'x\'\') must be estimated based on the sample. That is why the word \'\'empirical\'\' appears in the name of this concept. The conditional expected value of Θ given the observed value \'\'X\'\' = \'\'x\'\' is found by using [[Bayes\' theorem]]. That is why the word \'\'Bayes\'\' appears.\n\nThus, if a customer suffers six \"accidents\" during the baseline period, that customer\'s estimated \"accident rate\" is 7 × [the proportion of the sample who suffered 7 \"accidents\"] / [the proportion of the sample who suffered 6 \"accidents\"].\n\n\'\'\'Proof of the identity labeled with the asterisk above:\'\'\'\n\nDenote the [[probability density function]] of the underlying \"accident rate\" \\Theta by f_\\Theta(\\theta) (as is often done in probability theory, we use capital letters for random variables and corresponding lower-case letters for the dummy variables in the density or mass functions). Denote the conditional [[probablity mass function]] of the number of accidents suffered by a randomly chosen customer during the baseline period, given that that customer\'s \"accident rate\" is \\theta, by f_{X\\mid\\Theta=\\theta}(x). This conditional distribution was assumed to be a Poisson distribution; therefore we have\n\n:f_{X\\mid\\Theta=\\theta}(\\theta)={\\theta^x e^{-\\theta} \\over x!}.\n\nBy [[Bayes\' theorem]], the conditional probability density function of \\theta given the event \'\'X\'\' = \'\'x\'\' is\n\n:{\\theta^x e^{-\\theta} \\over x!}f_{X\\mid\\Theta=\\theta}(x)/[\\mbox{normalizing}\\ \\mbox{constant}].\n\nThe [[normalizing constant]] by which we divide is the integral with respect to \\theta from 0 to ∞ of the function in the numerator. Consequently, the conditional expected value of \\Theta given the observed number \'\'x\'\' of accidents is\n\n:{\\int_0^\\infty \\theta f_\\Theta(\\theta)f_{X\\mid\\Theta=\\theta}(x)\\,d\\theta \\over \\int_0^\\infty f_\\Theta(\\theta)f_{X\\mid\\Theta=\\theta}(x)\\,d\\theta}={\\int_0^\\infty \\theta f_\\Theta(\\theta){\\theta^x e^{-\\theta} \\over x!}\\,d\\theta \\over \\int_0^\\infty f_\\Theta(\\theta){\\theta^x e^{-\\theta} \\over x!}\\,d\\theta}={\\int_0^\\infty \\theta^{x+1} e^{-\\theta} f_\\Theta(\\theta)\\,d\\theta \\over \\int_0^\\infty \\theta^x e^{-\\theta} f_\\Theta(\\theta)\\,d\\theta}\n\n\n:={E\\left(\\Theta^{x+1} e^{-\\Theta}\\right) \\over E\\left(\\Theta^x e^{-\\Theta}\\right)}={(x+1)! E(P(X=x+1\\mid \\Theta)) \\over x! E(P(X=x\\mid \\Theta))}.\n\nBy the [[law of total probability]] (and the routine cancellation of factorials), this is equal to\n\n\n:{(x+1) P(X=x+1) \\over P(X=x)}.\n\n===An example involving the normal distribution===\n\nSuppose the weights of a large population of 35-year-old men are [[normal distribution|normally distributed]] with expected value μ and standard deviation σ. A crude measuring instrument measures a man\'s weight with a measurement error that is normally distributed with expected value 0 and standard deviation τ. The man\'s true weight is not observable; his weight measured with error is observed. The conditional probability distribution of a randomly chosen man\'s true weight, given his weight-measured-with-error, can be found by using [[Bayes\' theorem]], and then the conditional expected value can be used as an estimate of his true weight, \'\'\'provided\'\'\' that the values of μ, σ, and τ are \'\'known\'\'. But they are not. One may use the data to estimate the standard deviation of the measurement errors by measuring each man multiple times. One may similarly estimate the population average weight and the population standard deviation of weights by weighing multiple men. These estimates of parameters based on the data are the occasion for the use of the word \'\'empirical\'\'. Finally, one may then estimate the aforementioned conditional expected true weight by using Bayes\' theorem.\n\n:\'\'Mathematical details are still to be added here.\'\'\n\n==Sumber sejen==\n\n* Herbert Robbins, \'\'An Empirical Bayes Approach to Statistics\'\', Proceeding of the Third Berkeley Symposium on Mathematical Statistics, volume 1, pages 157-163, University of California Press, Berkeley, 1956.','',13,'Budhi','20041224082621','',0,0,1,0,0.303844642501,'20041231123527','79958775917378'); INSERT INTO cur VALUES (1266,0,'Naive_Bayesian_classification','\'\'\'Naive Bayesian classification\'\'\' is a simple probabilistic [[classification]] method. A more descriptive term for the underlying probability model is \'\'independent feature model\'\'. The term \'\'naive Bayes\'\' refers to the fact that the probability model can be derived using [[Bayes\' Theorem]] (credited to [[Thomas Bayes]]) and that it incorporates strong independences assumption that often have no bearing in reality, hence are (deliberately) naive. Depending on the precise nature of the probability model, naive Bayes classifiers can be trained very efficiently in a [[supervised learning]] setting. In many practical applications, parameter estimation for naive Bayes models uses the method of [[maximum likelihood]]; in other words, one can work with the naive Bayes model without believing in [[Bayesian probability]] or using any Bayesian methods.\n\n== The naive Bayes probabilistic model ==\n\nAbstractly, the probability model for a classifier is a conditional model\n\n:p(C \\vert F_1,\\dots,F_n)\\,\n\nover a dependent class variable C with a small number of outcomes or \'\'classes\'\', conditional on several feature variables F_1 through F_n. The problem is that if the number of features n is large or when a feature can take on a large number of values, then basing such a model on probability tables is infeasible. We therefore reformulate the model to make it more tractable.\n\nUsing [[Bayes\' theorem]], we write\n\n:p(C \\vert F_1,\\dots,F_n) = \\frac{p(C) \\ p(F_1,\\dots,F_n\\vert C)}{p(F_1,\\dots,F_n)}\n\nIn practice we are only interested in the numerator of that fraction, since the denominator does not depend on C and the values of the features F_i are given, so that the denominator is effectively constant.\nThe numerator is equivalent to the [[joint probability]] model\n\n:p(C, F_1, \\dots, F_n)\\,\n\nwhich can be rewritten as follows, using repeated applications of the definition of [[conditional probability]]:\n\n:p(C, F_1, \\dots, F_n)\\,\n:= p(C) \\ p(F_1,\\dots,F_n\\vert C)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2,\\dots,F_n\\vert C, F_1)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C, F_1) \\ p(F_3,\\dots,F_n\\vert C, F_1, F_2)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C, F_1) \\ p(F_3\\vert C, F_1, F_2) \\ p(F_4,\\dots,F_n\\vert C, F_1, F_2, F_3)\n\nand so forth. Now the \"naive\" conditional independence assumptions come into play: assume that each feature F_i is conditionally [[statistical independence|independent]] of every other feature F_j for j\\neq i. This means that\n\n:p(F_i \\vert C, F_j) = p(F_i \\vert C)\\,\n\nand so the joint model can be expressed as\n\n:p(C, F_1, \\dots, F_n)\n= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C) \\ p(F_3\\vert C) \\ \\dots\n:= p(C) \\prod_{i=1}^n p(F_i \\vert C)\n\nThis means that under the above independence assumptions, the conditional distribution over the class variable C can be expressed like this:\n\n:p(C \\vert F_1,\\dots,F_n) = \\frac{1}{Z} p(C) \\prod_{i=1}^n p(F_i \\vert C)\n\nwhere Z is a scaling factor dependent only on F_1,\\dots,F_n, i.e., a constant if the values of the feature variables are known.\n\nModels of this form are much more manageable, since they factor into a so-called \'\'class prior\'\' p(C) and independent probability distributions p(F_i\\vert C). If there are k classes and if a model for p(F_i) can be expressed in terms of r parameters, then the corresponding naive Bayes model has (\'\'k\'\' - 1) + \'\'n\'\' \'\'r\'\' \'\'k\'\' parameters. In practice, often k=2 (binary classification) and r=1 ([[Bernoulli variable]]s as features) are common, and so the total number of parameters of the naive Bayes model is 2n+1, where n is the number of binary features used for prediction.\n\n== Parameter estimation ==\n\nIn a [[supervised learning]] setting, one wants to estimate the parameters of the probability model. Because of the independent feature assumption, it suffices to estimate the class prior and the conditional feature models independently, using the method of [[maximum likelihood]], [[Bayesian inference]] or other parameter estimation procedures.\n\n== Constructing a classifier from the probability model ==\n\nThe discussion so far has derived the independent feature model, that is, the naive Bayes \'\'\'probability model\'\'\'. The naive Bayes \'\'\'classifier\'\'\' combines this model with a [[decision rule]]. One common rule is to pick the hypothesis that is most probable; this is known as the \'\'maximum a posteriori\'\' or \'\'MAP\'\' decision rule. The corresponding classifier is the function \\mathit{classify} defined as follows:\n\n:\\mathit{classify}(f_1,\\dots,f_n) = \\mathop{\\mathrm{argmax}}_c \\ p(C=c) \\prod_{i=1}^n p(F_i=f_i\\vert C=c)\n\n== Discussion ==\n\nThe naive Bayes classifier has several properties that make it surprisingly useful in practice, despite the fact that the far-reaching independence assumptions are often violated. Like all probabilistic classifiers under the MAP decision rule, it arrives at the correct classification as long as the correct class is more probable than any other class; class probabilities do not have to be estimated very well. In other words, the overall classifier is robust to serious deficiencies of its underlying naive probability model. Other reasons for the observed success of the naive Bayes classifier are discussed in the literature cited below.\n\nIn real life, the naive Bayes approach is more powerful than might be expected from the extreme simplicity of its model; in particular, it is fairly robust in the presence of non-independent attributes wi. Recent theoretical analysis has shown why the naive Bayes classifier is so robust.\n== Example: document classification ==\n\nHere is a worked example of naive Bayesian classification to the [[document classification]] problem.\nConsider the problem of classifying documents by their content, for example into [[spamming|spam]] and non-spam [[E-mail]]s. Imagine that documents are drawn from a number of classes of documents which can be modelled as sets of words where the (independent) probability that the i-th word of a given document occurs in a document from class \'\'C\'\' can be written as \n\n:p(w_i \\vert C)\\,\n\n(For this treatment, we simplify things further by assuming that the probability of a word in a document is independent of the length of a document, or that all documents are of the same length).\n\nThen the probability of a given document \'\'D\'\', given a class \'\'C\'\', is\n\n:p(D\\vert C)=\\prod_i p(w_i \\vert C)\\,\n\nThe question that we desire to answer is: \"what is the probability that a given document \'\'D\'\' belongs to a given class \'\'C\'\'?\"\n\nNow, by their definition, (see [[Probability axiom]])\n\n:p(D\\vert C)={p(D\\cap C)\\over p(C)}\n\nand \n\n:p(C\\vert D)={p(D\\cap C)\\over p(D)}\n\nBayes\' theorem manipulates these into a statement of probability in terms of [[likelihood]].\n\n:p(C\\vert D)={p(C)\\over p(D)}\\,p(D\\vert C)\n\n\nAssume for the moment that there are only two classes, \'\'S\'\' and ¬\'\'S\'\'. \n\n:p(D\\vert S)=\\prod_i p(w_i \\vert S)\\,\n\nand\n\n:p(D\\vert\\neg S)=\\prod_i p(w_i\\vert\\neg S)\\,\n\nUsing the Bayesian result above, we can write:\n\n:p(S\\vert D)={p(S)\\over p(D)}\\,\\prod_i p(w_i \\vert S)\n\n:p(\\neg S\\vert D)={p(\\neg S)\\over p(D)}\\,\\prod_i p(w_i \\vert\\neg S)\n\nDividing one by the other gives:\n\n:{p(S\\vert D)\\over p(\\neg S\\vert D)}={p(S)\\,\\prod_i p(w_i \\vert S)\\over p(\\neg S)\\,\\prod_i p(w_i \\vert\\neg S)}\n\nWhich can be re-factored as:\n\n:{p(S)\\over p(\\neg S)}\\,\\prod_i {p(w_i \\vert S)\\over p(w_i \\vert\\neg S)}\n\nThus, the probability ratio p(\'\'S\'\' | \'\'D\'\') / p(¬\'\'S\'\' | \'\'D\'\') can be expressed in terms of a series of [[likelihood ratio]]s. \nThe actual probability p(\'\'S\'\' | \'\'D\'\') can be easily computed from log (p(\'\'S\'\' | \'\'D\'\') / p(¬\'\'S\'\' | \'\'D\'\')) based on the observation that p(\'\'S\'\' | \'\'D\'\') + p(¬\'\'S\'\' | \'\'D\'\') = 1. \n\nTaking the [[logarithm]] of all these ratios, we have:\n\n:\\ln{p(S\\vert D)\\over p(\\neg S\\vert D)}=\\ln{p(S)\\over p(\\neg S)}+\\sum_i \\ln{p(w_i\\vert S)\\over p(w_i\\vert\\neg S)}\n\nThis technique of \"[[log-likelihood ratio]]s\" is a common technique in statistics.\nIn the case of two mutually exclusive alternatives (such as this example), the conversion of a log-likelihood ratio to a probability takes the form of a [[sigmoid curve]]: see [[logit]] for details. \n\n== See also ==\n\n* [[Bayesian inference]] (esp. as Bayesian techniques relate to [[Spam (e-mail)|spam]])\n* [[boosting]]\n* [[fuzzy logic]]\n* [[logistic regression]]\n* [[neural network]]s\n* [[Perceptron]]\n* [[Support vector machine]]\n\n==References==\n\n* Pedro Domingos and Michael Pazzani. \"On the optimality of the simple Bayesian classifier under zero-one loss\". \'\'Machine Learning\'\', 29:103-­130, 1997. \'\'(also online at [http://citeseer.nj.nec.com CiteSeer]: [http://citeseer.nj.nec.com/domingos97optimality.html])\'\'\n\n* Irina Rish. \"An empirical study of the naive Bayes classifier\". IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence. \'\'(available online: [http://www.intellektik.informatik.tu-darmstadt.de/~tom/IJCAI01/Rish.pdf PDF], [http://www.research.ibm.com/people/r/rish/papers/ijcai-ws.ps PostScript])\'\'\n\n==External links==\n* [http://citeseer.nj.nec.com/30545.html Naive Bayesian learning]\n\n[[Category:Machine learning]]\n[[Category:Statistics]]','',13,'Budhi','20040818225540','',0,0,0,1,0.120080447346,'20041231124655','79959181774459'); INSERT INTO cur VALUES (1267,0,'Klasifikasi_naif_Bayésian','\'\'\'Klasifikasi Naive Bayesian\'\'\' ngarupakeun metoda [[classification|klasifikasi]] probabiliti sederhana. Watesan nu leuwih jentre dina kaayaan model probibiliti nyaeta \'\'independent feature model\'\'. Watesan \'\'naive Bayes\'\' dumasar kana kanyataan yen model probabiliti bisa diturunkeun ngagunakeun [[Bayes\' Theorem]] (keur ngahargaan [[Thomas Bayes]]) sarta pakait kacida jeung asumsi bebas nu teu kapanggih di alam nyata, sabab kitu ngarupakeun (sacara ngahaja) naive. Gumantung kana katepatan pasti tina model probiliti, klasifikasi naive Bayes bisa direntetkeun kacida efisien dina susunan [[supervised learning]]. Dina pamakean praktis, parameter estimasi keur model naive Bayes make metoda [[maximum likelihood]]; dina basa sejen, hiji hal bisa digawekeun mibanda model naive Bayes bari teu nuturkeun [[Bayesian probability]] atawa ngagunakeun unggal metoda Bayesian.\n\n== Model probabiliti naive Bayes ==\n\nSacara abstrak, model probabiliti klasifikasi ngarupakeun model kondisional\n\n:p(C \\vert F_1,\\dots,F_n)\\,\n\ndina kelas variabel terikat C mibanda sajumlah leutik hasil atawa \'\'kelas\'\', kondisional dina sababaraha sipat variabel F_1 nepi ka F_n. Masalahna lamun jumlah sipat n badag atawa waktu sipat bisa dicokot tina nilai wilangan nu badag, mangka dumasar kana model dina tabel probabiliti ngarupakeun hal \'\'infeasible\'\'. Mangak kudu dirumuskeun duei modelna keur nyieun nu leuwih hade.\n\nNgangunakeun [[Bayes\' theorem]], dituliskeun\n\n:p(C \\vert F_1,\\dots,F_n) = \\frac{p(C) \\ p(F_1,\\dots,F_n\\vert C)}{p(F_1,\\dots,F_n)}\n\nDina praktekna urang ngan museurkeun kana pembilang, pembagi heunteu gumantung kana C sarta nilai sipat F_i diberekeun, mangka pembagi ngarupakeun konstanta.\nPembilang sarua jeung model [[joint probability]] \n\n:p(C, F_1, \\dots, F_n)\\,\n\nnu bisa dituliskeun saperti di handap, ngagunakeun pamakean pengulangan tina harti [[conditional probability]]:\n\n:p(C, F_1, \\dots, F_n)\\,\n:= p(C) \\ p(F_1,\\dots,F_n\\vert C)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2,\\dots,F_n\\vert C, F_1)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C, F_1) \\ p(F_3,\\dots,F_n\\vert C, F_1, F_2)\n:= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C, F_1) \\ p(F_3\\vert C, F_1, F_2) \\ p(F_4,\\dots,F_n\\vert C, F_1, F_2, F_3)\n\njeung saterusna. Kiwari asumsi \"naive\" kondisional bebas loba dipake: anggap unggal sipat F_i ngarupakeun [[statistical independence|independent]] dina unggal sipat F_j keur j\\neq i. Ieu hartina yen\n\n:p(F_i \\vert C, F_j) = p(F_i \\vert C)\\,\n\nsarta model gabungan ditembongkeun ku\n\n:p(C, F_1, \\dots, F_n)\n= p(C) \\ p(F_1\\vert C) \\ p(F_2\\vert C) \\ p(F_3\\vert C) \\ \\dots\n:= p(C) \\prod_{i=1}^n p(F_i \\vert C)\n\nIeu hartina yen dina kaayaan asumsi bebas di luhur, sebaran kondisional dina kelas variabel C bisa ditembongkeun saperti kieu:\n\n:p(C \\vert F_1,\\dots,F_n) = \\frac{1}{Z} p(C) \\prod_{i=1}^n p(F_i \\vert C)\n\nnumana Z ngarupakeun faktor skala terikat ngan dina F_1,\\dots,F_n, contona, konstanta lamun nilai sipat variabel dipikanyaho.\n\nModel dina bentuk ieu leuwih gamapang diurus, ti saprak ieu faktor disebut \'\'kelas prior\'\' p(C) sarta sebaran probabiliti bebas p(F_i\\vert C). Lamun didinya kelas k classes sarta lamun model keur p(F_i) bisa digambarkeun dina watesan parameter r, mangka pakait jeung model naive Bayes ngabogaan parameter (\'\'k\'\' - 1) + \'\'n\'\' \'\'r\'\' \'\'k\'\'. Dina praktek, salawasna k=2 (klasifikasi biner) sarta r=1 ([[Bernoulli variable]] salaku sipat) ngarupakeun hal umum, sarta jumlah wilangan parameter tina model naive Bayes nyaeta 2n+1, numana n ngarupakeun wilangan sipat biner nu dipake keur prediksi.\n\n== Parameter estimasi ==\n\nDina watesan [[supervised learning]], kahayang nga-estimasi parameter tina model sebaran. Sabab asumsi sipat bebas, eta cukup keur estimasi kelas prior jeung model sipat kondisional bebas, ku make metoda [[maximum likelihood]], [[Bayesian inference]] atawa prosedur parameter estimasi sejenna.\n\n== Ngawangun klasifikasi tina model probabiliti ==\n\nDiskusi leuwih jentre diturunkeun tina sipat model bebas, nyaeta, \'\'\'model probabiliti\'\'\' naive Bayes. \'\'\'Klasifikasi\'\'\' naive Bayes ngombinasikeun ieu model nu mibanda [[decision rule]]. Salah sahiji aturan nu umum keur nangtukeun hipotesa nu leuwih mungkin; dipikanyaho salaku aturan kaputusan \'\'maksimum posterior\'\' atawa \'\'MAP\'\'. Klasifikasi pakait ngarupakeun fungsi \\mathit{classify} nu dihartikeun saperti:\n\n:\\mathit{classify}(f_1,\\dots,f_n) = \\mathop{\\mathrm{argmax}}_c \\ p(C=c) \\prod_{i=1}^n p(F_i=f_i\\vert C=c)\n\n== Diskusi ==\n\nKlasifikasi naive Bayes ngabogaan sababaraha sipat nu ilahar dipake dina praktek, despite the fact that the far-reaching independence assumptions are often violated. Like all probabilistic classifiers under the MAP decision rule, it arrives at the correct classification as long as the correct class is more probable than any other class; class probabilities do not have to be estimated very well. In other words, the overall classifier is robust to serious deficiencies of its underlying naive probability model. Other reasons for the observed success of the naive Bayes classifier are discussed in the literature cited below.\n\nIn real life, the naive Bayes approach is more powerful than might be expected from the extreme simplicity of its model; in particular, it is fairly robust in the presence of non-independent attributes wi. Recent theoretical analysis has shown why the naive Bayes classifier is so robust.\n\n== Conto: klasifikasi dokumen ==\n\nConto didieu pagawean nu make klasifikasi naive Bayesian classification keur masalah [[document classification]].\nConsider the problem of classifying documents by their content, for example into [[spamming|spam]] and non-spam [[surélék|E-mail]]s. Imagine that documents are drawn from a number of classes of documents which can be modelled as sets of words where the (independent) probability that the i-th word of a given document occurs in a document from class \'\'C\'\' can be written as \n\n:p(w_i \\vert C)\\,\n\n(For this treatment, we simplify things further by assuming that the probability of a word in a document is independent of the length of a document, or that all documents are of the same length).\n\nThen the probability of a given document \'\'D\'\', given a class \'\'C\'\', is\n\n:p(D\\vert C)=\\prod_i p(w_i \\vert C)\\,\n\nThe question that we desire to answer is: \"what is the probability that a given document \'\'D\'\' belongs to a given class \'\'C\'\'?\"\n\nNow, by their definition, (see [[Probability axiom]])\n\n:p(D\\vert C)={p(D\\cap C)\\over p(C)}\n\nand \n\n:p(C\\vert D)={p(D\\cap C)\\over p(D)}\n\nBayes\' theorem manipulates these into a statement of probability in terms of [[likelihood]].\n\n:p(C\\vert D)={p(C)\\over p(D)}\\,p(D\\vert C)\n\n\nAssume for the moment that there are only two classes, \'\'S\'\' and ¬\'\'S\'\'. \n\n:p(D\\vert S)=\\prod_i p(w_i \\vert S)\\,\n\nand\n\n:p(D\\vert\\neg S)=\\prod_i p(w_i\\vert\\neg S)\\,\n\nUsing the Bayesian result above, we can write:\n\n:p(S\\vert D)={p(S)\\over p(D)}\\,\\prod_i p(w_i \\vert S)\n\n:p(\\neg S\\vert D)={p(\\neg S)\\over p(D)}\\,\\prod_i p(w_i \\vert\\neg S)\n\nDividing one by the other gives:\n\n:{p(S\\vert D)\\over p(\\neg S\\vert D)}={p(S)\\,\\prod_i p(w_i \\vert S)\\over p(\\neg S)\\,\\prod_i p(w_i \\vert\\neg S)}\n\nWhich can be re-factored as:\n\n:{p(S)\\over p(\\neg S)}\\,\\prod_i {p(w_i \\vert S)\\over p(w_i \\vert\\neg S)}\n\nThus, the probability ratio p(\'\'S\'\' | \'\'D\'\') / p(¬\'\'S\'\' | \'\'D\'\') can be expressed in terms of a series of [[likelihood ratio]]s. \nThe actual probability p(\'\'S\'\' | \'\'D\'\') can be easily computed from log (p(\'\'S\'\' | \'\'D\'\') / p(¬\'\'S\'\' | \'\'D\'\')) based on the observation that p(\'\'S\'\' | \'\'D\'\') + p(¬\'\'S\'\' | \'\'D\'\') = 1. \n\nTaking the [[logarithm]] of all these ratios, we have:\n\n:\\ln{p(S\\vert D)\\over p(\\neg S\\vert D)}=\\ln{p(S)\\over p(\\neg S)}+\\sum_i \\ln{p(w_i\\vert S)\\over p(w_i\\vert\\neg S)}\n\nThis technique of \"[[log-likelihood ratio]]s\" is a common technique in statistics.\nIn the case of two mutually exclusive alternatives (such as this example), the conversion of a log-likelihood ratio to a probability takes the form of a [[sigmoid curve]]: see [[logit]] for details.\n\n== Tempo oge ==\n\n* [[Bayesian inference]] (esp. as Bayesian techniques relate to [[Spam (e-mail)|spam]])\n* [[boosting]]\n* [[fuzzy logic]]\n* [[logistic regression]]\n* [[neural network]]s\n* [[Perceptron]]\n* [[Support vector machine]]\n\n==Sumber sejen==\n\n* Pedro Domingos and Michael Pazzani. \"On the optimality of the simple Bayesian classifier under zero-one loss\". \'\'Machine Learning\'\', 29:103-­130, 1997. \'\'(also online at [http://citeseer.nj.nec.com CiteSeer]: [http://citeseer.nj.nec.com/domingos97optimality.html])\'\'\n\n* Irina Rish. \"An empirical study of the naive Bayes classifier\". IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence. \'\'(available online: [http://www.intellektik.informatik.tu-darmstadt.de/~tom/IJCAI01/Rish.pdf PDF], [http://www.research.ibm.com/people/r/rish/papers/ijcai-ws.ps PostScript])\'\'\n\n==Tumbu kaluar==\n* [http://citeseer.nj.nec.com/30545.html Naive Bayesian learning]\n\n[[Category:Machine learning]]\n[[Category:Statistics]]','/* Conto: klasifikasi dokumen */',13,'Budhi','20041231124957','',0,0,1,0,0.713360221923,'20041231124957','79958768875042'); INSERT INTO cur VALUES (1268,0,'Ékonométri','[[it:Statistica economica]] [[nl:Econometrie]] [[sv:Ekonometri]] [[de:Ökonometrie]]\n\n\'\'\'\'\'Ekonometri\'\'\'\'\' sacara literatur hartina \'ukuran ekonomi\', ngarupakeun cabang tina [[ékonomi]] nu make [[statistik|metoda statistik]] keur diajar [[empirical|sacara empiris]] téori ékonomi jeung nu pakait. Ekonometri ngarupakeun kombinasi tina [[mathematical economics|matematika ékonomi]], statistik, statistik ékonomi jeung tiori ékonomi. \n\nThe two main purposes of econometrics are to give empirical content to economic theory and also to empirically verify economic theory. For example, econometrics could empirically verify if indeed a given demand curve slopes downward as economic theory would suggest. Empirical content is also given in that a numerical value would be given to this slope, while economic theory alone is usually mute on actual specific values.\n\nAn econometrician often changes qualitative statements into a quantitative mathematical form that lends itself to measurement. These statements can then be empirically proven, disproven, measured, and compared. Econometrics differs from statistics done in other fields since controlled experiments are often impractical, so econometics has to frequently deal with data as is.\n\nArguably the most important tool of econometrics is regression analysis (for an overview of a linear implementation of this framework, see [[linear regression]]).\n\nEconometric analysis can often be divided into [[time-series analysis]] and [[cross-sectional analysis]]. Time-series analysis examines variables over time, such as the effect of interest rates on national expenditure. Cross-sectional analysis studies relationship between different variables at a point in time. For instance, the relationship between income, locality, and personal expenditure. When time-series analysis and cross-sectional analysis are conducted simultaneously on the same [[Statistical sample|sample]], it is called [[panel analysis]]. If the sample is different each time, it is called pooled cross section data.\n\nA simple example of a relationship in econometrics is:\n\n:Personal Expenditure = Propensity to Spend * Income + random error \n\nThis statement asserts that the amount a person spends is dependent on their [[income]] and their willingness to spend [[money]]. If we can observe personal expenditure and income, techniques such as [[Linear regression|regression analysis]] can then be applied to find the value of the coefficients, here just the propensity to spend. The estimated coefficient can then be compared across samples (such as different countries or income brackets) and conclusions made. \n\nThe above example can also be used to illustrate the many difficulties facing the applied econometrician. For instance, do we really know that the above relationship is correct? Perhaps the true relationship between personal expenditure and income is non-linear (that is, curved). Even if we know the correct theory, it is not certain we can meaure personal expenditure and income correctly. For instance, the value of work by e.g. [[homemaker]]s is not recorded although it contributes to income. There are also a variety of statistical pitfalls that potentially lead to incorrect conclusions. Econometrics has dealt extensively with such issues. Often it turns out to be difficult to fully implement the resulting methods in practice.\n\nIn order to classify business and industry, econometricians rely on two main systems: [[SIC]] codes and more recently [[NAICS]] codes.\n\n==People==\n\n[[Nobel Prize]] for [[Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel|Economic Sciences]] recipients in the field of econometrics:\n\n* [[Jan Tinbergen]] and [[Ragnar Frisch]] were awarded in [[1969]] (the first Nobel Price for Economic Sciences) for having developed and applied dynamic models for the analysis of economic processes\n* [[Lawrence Klein]] was awarded in [[1980]] for his computer modeling work in the field.\n* [[Daniel McFadden]] and [[James Heckman]] shared the award in [[2000]] for their work in microeconometrics. McFadden founded the econometrics lab at the [[University of California, Berkeley]].\n* [[Robert Engle]] and [[Clive Granger]] were awarded in [[2003]] for work on analysing economic time series. Engle pioneered the method of [[autoregressive conditional heteroskedasticity]] (ARCH) and Granger the method of [[cointegration]].','',13,'Budhi','20041224084339','',0,0,1,0,0.467813498558,'20050208111611','79958775915660'); INSERT INTO cur VALUES (1269,0,'Autoregressive_moving_average_model','Dina [[statistik]], \'\'\'model autoregressive moving average (ARMA)\'\'\' nyaeta aplikasi tipikal nu dipake dina data [[deret waktu]]. \n\nAnggap urang boga dua deret waktu , \'\'x\'\'1, \'\'x\'\'2, \'\'x\'\'3, ..., jeung \'\'y\'\'1, \'\'y\'\'2, \'\'y\'\'3, .... Deret \'\'x\'\' sacara \'\'konvensional\'\' teu bisa \"sacara pasti\" di-\'\'prediksi\'\' ku pangaruh atawa parobahan \'\'y\'\'. Urang dihareokeun keur ngira-ngira \'\'y\'\'\'\'t\'\'. Lamun model prediksi ngan miboga watesan \'\'x\'\', model disebut model \'\'moving average\'\' (MA). Lamun model prediksi ngan miboga watesan \'\'y\'\', model disebut model \'\'autoregressive\'\' (AR). Lamun prediski miboga duanana watesan boh \'\'x\'\' sarta \'\'y\'\' terms, model disebut model \'\'autoregressive moving average\'\' (ARMA). \n\n== Model moving average ==\n\nLambang MA(\'\'q\'\') hartina model moving average mibanda watesan \'\'q\'\'. Model MA(\'\'q\'\') bisa dituliskeun\n\n: y_t = x_t + \\theta_1 x_{t-1} + \\cdots + \\theta_q x_{t-q}\n \n\nkeur sababraha koefisien θ1, ..., θ\'\'q\'\'. Model moving average model ngarupakeun hal penting dina [[finite impulse response]] filter nu mibanda sawangan tambahan dina eta tempat.\n\n== Model Autoregressive ==\n\nLambang AR(\'\'p\'\') hartina model autoregressive mibanda watesa \'\'p\'\'. Model AR(\'\'p\'\') bisa dituliskeun\n\n: y_t = \\phi_1 y_{t-1} + \\cdots + \\phi_p y_{t-p} \n\nkeur sababaraha koefisien φ1, ..., φ\'\'p\'\'. Model autoregressive model ngarupakeun hal penting dina [[infinite impulse response]] filter nu mibanda sawangan tambahan dina eta tempat.\n\n== Model Autoregressive moving average ==\n\nLambang ARMA(\'\'p\'\', \'\'q\'\') hartina model mibanda watesan \'\'p\'\' autoregressive sarta watesan \'\'q\'\' moving average. Ieu model ngarupakeun jumlah tina model AR jeung MA,\n\n: y_t = \\phi_1 y_{t-1} + \\cdots + \\phi_p y_{t-p} \n + x_t + \\theta_1 x_{t-1} + \\cdots + \\theta_q x_{t-q}\n\n\n== Generalisasi ==\n\nKawengku kana \'\'y\'\'\'\'t\'\' dina nilai \'\'x\'\' atawa \'\'y\'\' samemehna dianggap bakal linier iwal dina kasus husus. Lamun dependen nonlinear, model sacara husus disebut \'\'nonlinear moving average\'\' (NMA), \'\'nonlinear autoregressive\'\' (NAR), atawa model \'\'nonlinear autoregressive moving average\'\' (NARMA) .\n\nModel autoregressive moving average models bisa digeneralisir make cara sejen. Tempo oge model [[autoregressive conditional heteroskedasticity]] (ARCH) sarta model [[autoregressive integrated moving average]] (ARIMA).\n\n== Rujukan ==\n\n* [[George E.P. Box]] and F.M. Jenkins. \'\'Time Series Analysis: Forecasting and Control\'\', second edition. Oakland, CA: Holden-Day, 1976.\n\n[[Category:Statistics]]\n\n[[de:ARMA-Modelle]]','',13,'Budhi','20041004003735','',0,0,0,0,0.904811426953,'20041004003735','79958995996264'); INSERT INTO cur VALUES (1270,0,'Heteroskedasticity','Dina [[statistik]], sekuen atawa vektor tina [[random variable]] disebut \'\'\'heteroskedastic\'\'\' lamun variabel random dina sekuen atawa vektor beda jeung [[varian]]. Lawanna disebut [[homoscedasticity]]. (Di Amerika, umumna dieja \'\'homoscedastic\'\'. Hiji hal nu husus dina aturan ejaan Amerika nu leuwih ilahar tinimbang ejaan Inggris).\n\nWaktu make teknik variasi dina statistik, saperti [[least squares|ordinary least squares]] (OLS), jumlah anu di-asumsikeun dijieun tipikal. Salah sahijina nyaeta watesan nu dijieun konstan nyaeta [[varian]]. Hal ieu bakal jadi bener lamun watesan observasi kasalahan asalna tina sebaran nu identik.\n\n\'\'\'Heteroskedasticity\'\'\' (aka skewedness, lawan: homoskedasticity) ngalawan asumsi ieu. Contona, watesan kasalahan bisa robah atawa naek unggal observasi, something that is often the case with cross sectional atawa ukuran [[deret waktu]]. Heteroskedasticity is often studied as part of [[econometrics]], which frequently deals with data exhibiting it. It comes in two forms, pure and impure. Because there are so many types of each, most textbooks limit themselves to dealing with heteroskedasticity in general, or one or two examples.\n\n==Consequences==\nThe consequences are similar to [[serial correlation]]. \n# When OLS to is applied heteroskedastic models it is no longer a minimum variance estimator. The variances and standard errors are understated.\n# The variance of the sample betas increases.\n\n==Conto==\nHeteroskedasticity often occurs when there is a large difference between the size of observations. \n\n# [1] cites a cross sectional example: Comparing states with widely differing populations, such as Rhode Island and California.\n# Imagine you are watching a rocket take off nearby and measuring the distance it has travelled once each second. In the first couple of seconds your measurements may be accurate to the nearest centimeter, say. However, 5 minutes later as the rocket recedes into space, the accuracy of your measurements may only be good to 100m, because of the increased distance, atmospheric distortion and a variety of other factors. The data you collect would exhibit heteroskedasticity.\n\n==Sumber sejen==\nThere are a great many references. Most statistics text books will include at least some material on heteroskedasticity. \n# Studenmund, A.H. Using Econometrics 2nd Ed. ISBN 0-673-52125-7. Devotes a chapter to heteroskedasticity.','',13,'Budhi','20041004003841','',0,0,0,0,0.037566527742,'20041004003841','79958995996158'); INSERT INTO cur VALUES (1271,0,'Dérét_waktu','[[de:Zeitreihenanalyse]]\n\n[[Category:Stochastic processes]]\n\nDina [[statistik]] jeung [[signal processing|signal proses]], \'\'\'deret waktu\'\'\' nyaeta sekuen [[data point|titik data]], diukur dina nurunna waktu, pamisah rohangan tina interval waktu nu sarua.\n\'\'\'\'\'Analisa\'\' deret waktu\'\'\' ngandung sababaraha metoda nu nyoba ngartikeun deret waktu, salawasna dipikaharti dina kaayan teori titik data (timana data datang ? kumaha nga-generate-na?), atawa keur nyieun ramalan ([[prediction|prediksi]]). \'\'\'\'\'Prediksi\'\' deret waktu\'\'\' ngarupakeun [[model]] nu dipake keur prediksi kajadian nu bakal datang dumasar kana kanyaho nu geus kaliwat: keur prediksi titik data samemeh diukur. Conto ilahar nyaeta harga mimiti di [[stock|pasar saham]] dumasar kana kajadian poe samemehna.\n\nModel keur deret waktu bisa mibanda sababara bentuk. Dua kelas nu penting nyaeta model \'\'moving average\'\' (MA) jeung model \'\'autoregressive\'\' (AR). Dua kelas ieu bisa ditempo leuwih jentre dina kaca ngeunaan [[autoregressive moving average model]]s (ARMA).\n\n==Tempo ogé==\n\n[[prédiksi liniér]], [[anomali dérét waktu]], [[trend estimation]], [[prediction interval]]\n\n\n{{pondok}}','/* Tempo oge */',3,'Kandar','20041125020947','',0,0,0,0,0.325992821402,'20050303211247','79958874979052'); INSERT INTO cur VALUES (1272,0,'Homoscedasticity','Dina [[statistik]], a sequence or a vector of [[random variable]]s is \'\'\'homoscedastic\'\'\' if all random variables in the sequence or vector have the same finite [[varian]]. \nThe complement is called [[heteroscedasticity]]. The assumption of homoscedasticity \nsimplifies mathematical and computational treatment and may lead to good estimation results (e.g. in [[data mining]]) even if the assumption is not true. \n\n(In Britain, it is sometimes spelled \'\'homoskedastic\'\'. It is an exception to the rule that American spellings are usually more faithful to the etymologies than British spellings.)','',13,'Budhi','20040907114026','',0,0,0,0,0.061643219116,'20040907114026','79959092885973'); INSERT INTO cur VALUES (1273,0,'Heteroscedasticity','#REDIRECT [[Heteroskedasticity]]','',13,'Budhi','20040818232932','',0,1,0,1,0.363638502715,'20040818232932','79959181767067'); INSERT INTO cur VALUES (1274,0,'Kuadrat_leutik','\'\'(jejer ieu masih merlukeun tambahan nu leuwih jentre, nerangkeun dina metoda Gauss)\'\'\n\n\'\'\'Kuadrat pangleutikna\'\'\' atawa \'\'\'Least squares\'\'\' nyaeta teknik [[Optimization (mathematics)|optimasi]] [[matematik]] nu dipake keur manggihkeun \"ragkep hade\" atawa \"best fit\" tina susunan data ku ngaminimalkeun bedama jumlah kuadrat (disebut \'\'[[errors and residuals in statistics|sesa]]\'\') antara fungsi rangkep jeung data.\n\nIeu geus ilahar dipake dina [[curve fitting|kurva rangkep]]. Loba [[optimization problems|masalah optimasi]] bisa ditembongkeun dina bentuk kuadrat leutik, saperti dina ngaminimalkeun [[energy|tanaga]] atawa ngamaksimalkeun [[entropy|entropi]].\n\nTempo [[linear regression|régrési liniér]] sarta [[Gauss-Markov theorem|teorema Gauss-Markov]]. Teorema Gauss-Markov nyebutkeun yen estimator kuadrat-leutik ngarupakeun hal nu pang-optimal-na.\n\nKeur make metoda kuadrat leutik ilaharna make fungsi \'\'f\'\'(\'\'x\'\'), nu ngabogaan sababaraha wilangan konstanta nu teu dipikanyaho (contona \'\'f\'\'(\'\'x\'\') = \'\'mx\'\' + \'\'b\'\', numana \'\'m\'\' sarta \'\'b\'\' teu dipikanyaho), sarta panggihkeun nilai \'\'m\'\' jeung \'\'b\'\' ku ngaminimalkeun jumlah kuadrat sesa (nyaeta, jumlah dina watesan (\'\'y\'\'\'\'i\'\' − \'\'f\'\'(\'\'x\'\'\'\'i\'\'))2). Mangka mibanda persamaan keur kurva, \'\'y\'\' = \'\'f\'\'(\'\'x\'\'), bentuk nu diperlukeun, nyaeta rangkep panghadena dina titik data(\'\'x\'\'\'\'i\'\', \'\'y\'\'\'\'i\'\').\n\nKeur fungsi [[linear|linier]] \'\'f\'\' tempo [[linear least squares|kuadrat leutik linier]].\n\n==Tumbu kaluar==\n* http://www.physics.csbsju.edu/stats/least_squares.html\n* http://www.zunzun.com\n* http://www.orbitals.com/self/least/least.htm\n\n{{Linear_algebra}}\n[[sv:Minsta kvadratmetoden]]\n[[de:Methode der kleinsten Quadrate]]\n[[Category:Aljabar abstrak]] [[Category:Aljabar]] [[Category:Aljabar linear]] [[Category:Statistik]]','kategori',20,'DiN','20050303205322','',0,0,0,0,0.771859453885,'20050303205322','79949696794677'); INSERT INTO cur VALUES (1275,0,'Serial_correlation','#REDIRECT [[Autocorrelation]]','',13,'Budhi','20040818233155','',0,1,0,1,0.994913747532,'20040818233155','79959181766844'); INSERT INTO cur VALUES (1276,6,'Weibull1.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040818234853','',0,0,0,1,0.653239594449512,'20041224211550','79959181765146'); INSERT INTO cur VALUES (1277,6,'Weibull2.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040818234922','',0,0,0,1,0.147014302338487,'20041224211550','79959181765077'); INSERT INTO cur VALUES (1278,0,'Rayleigh_distribution','#redirect [[Multipath propagation]]','',13,'Budhi','20040818235223','',0,1,0,1,0.825012458407,'20040818235223','79959181764776'); INSERT INTO cur VALUES (1279,0,'Informasi_Fisher','Dina [[statistik]], \'\'\'informasi Fisher\'\'\' \'\'I\'\'(θ), nyaeta [[information]] [[random variable]] nu bisa diobservasi mawa kanyaho ngeunaan parameter nu teu ka observasi θ nu gumantung kana [[probability distribution]] \'\'X\'\', ngarupakeun [[score (statistics)|score]] [[varian]]. Sabab skor [[expectation]] nyaeta nol, bisa dituliskeun salaku \n\n:\nI(\\theta)=E\\left(\\left[\\frac{\\partial}{\\partial\\theta}\n\\log f(X;\\theta)\\right]^2\\right)\n\n\nnumana \'\'f\'\' ngarupakeun [[probability density function]] variabel random \'\'X\'\'. \nInformasi Fisher saterusna ngarupakeun ekspektasi kuadrat tina skor. Variabel random mawa informasi Fisher nu luhur nu ngakibatkeun nilai mutlak skor oge jadi luhur (inget yen skor ekspektasi nyaeta nol).\n\nKonsep ieu dipake keur ngahargaan ka ahli genetis jeung statistikawan [[Ronald Fisher]].\n\nCatetan yen informasi nu dihartikeun di luhur lain fungsi tina observasi sabagean, salaku variabel \'\'X\'\' geus ngabogaan \'\'average\'\'. Konsep informasi gampang dipake keur ngabandingkeun dua metoda observasi dina proses random nu sarua.\n\nInformasi saperti nu geus dihartikeun di luhur bisa ditulis dina bentuk\n:\nI(\\theta)=-E\\left[\n\\frac{\\partial^2}{\\partial\\theta^2}\n\\log f(X;\\theta)\n\\right]\n\nsarta saterusna log ekspektasi ngarupakeun turunan kadua ti \'\'X\'\' nu pakait jeung \'\'θ\'\'. Informasi saterusna geus katempo ngarupakeun ukuran \"kaseukeutan\" nu ngadukung kurva deukeut kana [[maximum likelihood|maximum likelihood estimate]] \'\'θ\'\'. Kurva dukungan nu \"Kodol\" (nu ngabogaan nilai minimum deet) bakal ngabogaan turunan ekspektasi kadua nu lemah, sarta saterusna informasi nu lemah; sabalikna bentuk nu seukeut bakal ngabogaan nilai turunan kadua nu luhur sarta saterusna nilai informasi nu luhur.\n\nInformasi ngarupakeun tambahan, dina hal ieu informasi dicokot tina dua eksperimen [[independent]], ngarupakeun jumlah tina eta informasi:\n\n:\nI_{X,Y}(\\theta)=I_X(\\theta)+I_Y(\\theta).\n\n\nHal ieu kusabab jumlah varian dua variabel random bebas ngarupakeun jumlah eta varian. Hal ieu nuturkeun yen informasi dina ukuran sampel random \'\'n\'\' nyaeta \'\'n\'\' kali dina ukuran hiji sampel(lamun eta observasi bebas).\n\nInformasi ieu disaratkeun ku [[sufficiency (statistics)|sufficient statistic]] nyaeta sarua jeung sampel \'\'X\'\'. Ieu geus katempo ku make kriteria faktorisasi Fisher keur kacukupan statistis. Lamun \'\'T(X)\'\' cukup keur θ, mangka\n\n:\nf(X;\\theta)=g(T(X),\\theta)\\times h(X)\n\n\nkeur sababaraha fungsi \'\'g\'\' jeung \'\'h\'\' (tempo [[sufficient statistic]] keur katerangan leuwih lengkep). Dina kanyataanna persamaan informasi nuturkeun bentuk \n\n:\n\\frac{\\partial}{\\partial\\theta} \\log\\left[f(X ;\\theta)\\right]=\n\\frac{\\partial}{\\partial\\theta} \\log\\left[g(T(X);\\theta)\\right]\n\n\n(numana ieu kasus sabab \'\'h\'\'(\'\'X\'\') ngarupakeun θ) bebas sarta harti keur informasi information diberekeun di luhur. Leuwih umum, lamun \'\'T=t(X)\'\' ngarupakeun [[statistic]], mangka \n\n:\nI_T(\\theta)\\leq I_X(\\theta)\n\nnu sarua lamun jeung lamun \'\'T\'\' ngarupakeun kacukupan statistik.\n\n[[Cramér-Rao inequality]] netepkeun yen informasi Fisher bolak balik ngarupakeun water handap dina varian keur unggal \'\'unbiased estimator\'\' θ.\n\n===Conto===\n\nInformasi dipiboga dina \'\'n\'\' [[Bernoulli trial]] bebas, nu unggal probabiliti sukses \'\'θ\'\' bisa diitung siga di handap ieu. Runduyannana, \'\'a\'\' ngagambarkeun jumlah sukses , \'\'b\'\' jumlah gagal, sarta \'\'n=a+b\'\' ngarupakeun jumlah sakabeh percobaan.\n\n:\nI(\\theta)= -E\\left(\\frac{\\partial^2}{\\partial\\theta^2}\n\\log(f(X;\\theta)\\right)\n\n::=-E\\left(\\frac{\\partial^2}{\\partial\\theta^2}\n\\log\\left[\\theta^a\\cdot(1-\\theta)^b\\frac{(a+b)!}{a!b!}\n\\right]\\right)\n\n::=-E\\left(\n \\frac{\\partial^2}{\\partial\\theta^2}\\left[a\\log\\theta\n+b\\log(1-\\theta)\\right]\\right)\n\n::=-E\\left(\\frac{\\partial}{\\partial\\theta}\\left[\n\\frac{a}{\\theta}-\\frac{b}{1-\\theta}\\right]\\right)\n\n::=+E\\left(\\frac{a}{\\theta^2}+\\frac{b}{(1-\\theta)^2}\\right)\n\n::=\\frac{n\\theta}{\\theta^2}+\\frac{n(1-\\theta)}{(1-\\theta)^2}\n\n::=\\frac{n}{\\theta(1-\\theta)}\n\nGaris kahiji sakadar ngahartikeun informasi; kadua migunakeun kanyataan kandungan informasi dina kacukupan statistik saru jeung eta sampel sorangan; garis katilu ngan perluasan watesan [[logarithm|log]] (jeung ngaleungitkeun konstant), kaopat jeung kalima ngan proses diferensiasi wrt \'\'θ\'\', kagenep ngagantikeun \'\'a\'\' jeung \'\'b\'\' ku ekspektasina , sarta katujuh ngarupakaeun manipulasi aljabar.\n\nHasil kabehannana, nyaeta\n:\nI(\\theta)=\\frac{n}{\\theta(1-\\theta)}\n\nbisa katempo yen dumasar kana ekspektasi, saprak ngarupakeun varian bolak balik tian jumlah \'\'n\'\' Bernoulli variabel random.\n\nDina kasus paramete θ ngarupakeun nilai vektor, informasi ngarupakeun harti-positip tina matriks, nu dihartikeun sameter dina parameter ruang; akibatna [[differential geometry]] dipake dina ieu topik. Tempo [[Fisher information metric]].\n\n[[Category:Statistics]][[Category:Information theory]]','',13,'Budhi','20040907114546','',0,0,0,0,0.475479302684,'20041225131128','79959092885453'); INSERT INTO cur VALUES (1280,0,'Fisher\'s_exact_test','[[Category:Statistics]]\n\n\'\'\'Fisher\'s Exact Test\'\'\' nyaeta tes [[statistical significance]] dipake dina analisa [[nominal data|categorical data]] dina waktu ukuran [[sample]] leutik. Istilah ieu dimimitian ku [[Ronald Fisher|R. A. Fisher]].\n\nTes dipake keur nangtukeun siginifikan nu pakait antara dua variabel dina a 2 x 2 [[contingency table]]. Dina kaayaan sampel badag bisa digunakeun [[tes chi-kuadrat]]. However, this test is not suitable when the \"expected values\" in any of the cells of the table is below 10 and there is only one [[tingkat kabebasan]]: the [[sampling distribution]] of the test statistic that is calculated is only approximately equal to the theoretical chi-squared distribution, and the approximation is inadequate in these conditions (which arise when sample sizes are small, or the data are very unequally distributed among the cells of the table). The Fisher test is, as its name states, exact, and it can therefore be used regardless of the sample characteristics. It becomes difficult to calculate with large samples or well-balanced tables, but fortunately these are exactly the conditions where the chi-square test is available.\n\nThe need for the Fisher test arises when we have data that are divided into two categories in two separate ways. For example, a sample of teenagers might be divided into male and female on the one hand, and those that are and are not currently dieting on the other. We hypothesise, perhaps, that the proportion of dieting individuals is higher among the women than among the men, and we want to test whether any difference of proportions that we observe is significant. The data might look like this:\n\n
\n\n\n\n\n\n
menwomentotal
dieting1910
not dieting11314
totals121224
\n
\n\nThese data would not be suitable for analysis by a chi-squared test, because the expected values in the table are all below 10, and in a 2 x 2 contingency table, the number of degrees of freedom is always 1. \n\nTo proceed with the Fisher test, w have to introduce some notation. We represent the cells by the letters \'\'a, b, c\'\' and \'\'d\'\', call the totals across rows and columns \'\'marginal totals\'\', and represent the grand total by \'\'n\'\'. So the table now looks like this:\n\n
\n\n\n\n\n\n
menwomentotal
dieting\'\'a\'\'\'\'b\'\'\'\'a\'\'+\'\'b\'\'
not dieting\'\'c\'\'\'\'d\'\'\'\'c\'\'+\'\'d\'\'
totals\'\'a\'\'+\'\'c\'\'\'\'b\'\'+\'\'d\'\'\'\'n\'\'
\n
\n\nFisher showed that the [[probability]] of obtaining any such set of values could be calculated from the [[multinomial distribution]], and that it equalled:\n\n
\n: p = {\\frac {(a+b)!(c+d)!(a+c)!(b+d)!}{n!a!b!c!d!}}\n
\n\nwhere the symbol ! indicates the [[factorial]], i.e. 1 multiplied by 2 multiplied by 3 etc, up to the number whose factorial is required.\n\nThis formula gives the exact probability of observing this particular arrangement of the data on the [[null hypothesis]] that the proportions of dieters and non-dieters among men and women are equal in the population from which our sample was drawn. However, this is not the required significance of the difference of proportions in the table. As usual in significance testing, we also have to consider possible results that are more extreme than the one we observed. Fisher showed that we only have to consider cases where the marginal totals are the same as in the observed table. In the example, there is only one such; it would look like this:\n\n
\n\n\n\n\n\n
menwomentotal
dieting01010
not dieting12214
totals121224
\n
\n\nIn order to calculate the significance of the observed data, i.e. the total probability of observing data as extreme or more extreme if the [[null hypothesis]] is true, we have to calculate the \'\'p\'\' values for both these tables, and add them together. This gives a [[one-tailed test]]; for a [[two-tailed test]] we must also consider tables that are equally extreme but in the opposite direction. Unlike most statistical tests, it is not always the case that the two-tailed significance level is exactly twice the one-tailed significance level. In the example above, the one-tailed significance level is 0.0014; calculation of the two-tailed significance level is left as an exercise for the reader.\n\nCalculating significance values for the Fisher exact test is slow and requires care even with the aid of a computer, because the factorial terms quickly become very large, and with larger samples, the number of possible tables more extreme than that observed quickly becomes substantial. Even for small samples (which fortunately is where the test is usually needed), the calculations are tedious, but published tables are available; they are bulky, because the grand total and two of the four cell sizes have to be specified. Given these data, the table then gives the criterial value of the third cell size for specified significance levels. The observed table may have to be re-arranged (for example by rearranging the rows or the columns) to make it compatible with the way the significance levels are tabulated. Most modern [[statistical package]]s will calculate the significance of Fisher tests, in some cases even where the chi-squared approximation would also be acceptable.','',13,'Budhi','20040903113742','',0,0,0,0,0.257266542994,'20040904065517','79959096886257'); INSERT INTO cur VALUES (1281,0,'Fisher\'s_linear_discriminator','Dipublikasi ku [[Ronald Fisher]] taun [[1936]] dina \"The Use of Multiple Measures in Taxonomic Problems\".','',13,'Budhi','20040819003600','',0,0,0,1,0.898820428596,'20040819003600','79959180996399'); INSERT INTO cur VALUES (1282,0,'Uji_Kolmogorov-Smirnov','Dina [[statistik]], tes \'\'\'Kolmogorov-Smirnov\'\'\' dipake keur ngabedakeun dua [[probability distribution|distributions]] empiris atawa ngabedakeun sebaran empiris jeung sebaran tiori.\n\nCumulative distribution empiris keur \'\'n\'\' observasi \'\'yi\'\' diartikeun ku \'\'E\'\'(\'\'x\'\') = Σ \'\'i\'\' (\'\'yi < x\'\'). Tes statistik dua-sisi Kolmogorov-Smirnov dirumuskeun ku \n\n:D_n^{+}=\\max(E(x)-F(x))\n\n:D_n^{-}=\\max(F(x)-E(x))\n\nnumana \'\'F\'\'(\'\'x\'\') nyaeta sebaran hipotesa atawa sebaran empiris sejenna. Probability distributions dua statistik ieu, nunjukkeun yen null hypothesis sebaran sarua nyaeta bener, henteu gumantung kana hipotesa sebaran, salila kontinyu. [[Donald Knuth|Knuth]] nunjukkeun sacara jentre kumaha cara analisa signifikan tina pasangan statistik ieu. Loba masarakat nu make max(\'\'Dn+, Dn-\'\'), tapi sebaran dina ieu statistik leuwih hese keur direngsekeun.\n\nHiji catetan dina kaayaan variabel bebas \'\'berulang\'\', saperti poe dina sataun atawa poe dina saminggu, [[Kuiper\'s test]] leuwih hade dipake. Numerical Recipes ngarupakeun sumber nu hade keur informasi ieu. \nCatetan saterusna, tes Kolmogorov-Smirnov leuwih sensitip dina titik nu deukeut kana median sebaran tinimbang dina tungtungna. [[Anderson-Darling test]] salah sahiji tes nu nunjukkeun kasaruaan sensitip di tungtung.\n\n==Tumbu kaluar==\n*http://www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm - A lovely explanation of the one-sided KS test \n*http://www.io.com/~ritter/JAVASCRP/NORMCHIK.HTM - JavaScript code that implements both the one-sided and two-sided tests. \n*As always, Numerical Recipes (ISBN 0521431085) is a prime resource for this sort of thing (see http://www.nr.com/nronline_switcher.html for a discussion).\n\n\n[[de:Kolmogorow-Smirnow-Test]]\n[[en:Kolmogorov-Smirnov test]]\n[[it:Test di Kolmogorov-Smirnov]]\n[[nl:Kolmogorov-Smirnov]]','interwiki',0,'213.21.174.172','20041223165343','',0,0,0,0,0.918307587466,'20041223165343','79958776834656'); INSERT INTO cur VALUES (1283,0,'Donald_Knuth','[[Image:Knuth.jpeg|thumb|Donald Knuth]]\n\n\'\'\'Donald Ervin Knuth\'\'\' (lahir [[January 10]], [[1938]] di [[Milwaukee, Wisconsin|Milwaukee]], [[Wisconsin]]) salah saurang nu ngamimitian [[computer science|computer scientist]] sarta Professor Emeritus di [[Stanford University]].\n\nKnuth is best known as the author of the multi-volume \'\'[[The Art of Computer Programming]]\'\', one of the most highly respected references in the computer science field. He practically created the field of rigorous [[analysis of algorithms]], and made many seminal contributions to several branches of [[theoretical computer science]]. He is the creator of the [[TeX|TEX]] typesetting system and of the [[Metafont]] font design system, and pioneered the concept of [[literate programming]].\n\nKnuth is considered a [[famous programmer]], known for his [[geek]] humor: as examples, he pays a finder\'s fee of $2.56 for any typos/mistakes discovered in his books because \'\'\"256 pennies is one hexadecimal dollar\".\'\' (His bounty for errata in \'\'3:16 Bible Texts Illuminated,\'\' is, however, $3.16). Version numbers of his [[TeX|TEX]] software approach [[pi|\\pi]], that is versions increment in the style 3, 3.1, 3.14 and so on, version numbers of [[Metafont]] approach [[E (mathematical constant)|e]] similarly; he once warned users of his software, \'\'\"Beware of bugs in the above code; I have only proved it correct, not tried it.\"\'\' ([http://www-cs-faculty.stanford.edu/~knuth/faq.html source])\n\nKnuth is the author of \'\'3:16 Bible Texts Illuminated\'\' ([[1991]]), ISBN 0895792524, in which he attempts to examine the Bible by a process of \"stratified random sampling,\" namely an analysis of chapter 3, verse 16 of each book. Each verse is accompanied by a rendering in calligraphic art, contributed by a group of calligraphers under the leadership of [[Herman Zapf]].\n\nHe received his [[bachelor\'s degree]] in [[mathematics]] at the [[Case Institute of Technology]], now known as [[Case Western Reserve University]]. He earned a [[Ph.D.]] in mathematics from the [[California Institute of Technology]] in [[1963]]. In [[1968]] he became a member of the [[faculty]] of [[Stanford University]], where he was awarded the singular academic title of \'\'Professor Emeritus of the Art of Computer Programming\'\'. He has received various other awards including the [[Turing Award]], the [[National Medal of Science]], the [[John von Neumann Medal]] and the [[Kyoto Prize]]. In [[2003]] he was elected as a Fellow of the [[Royal Society]].\n\nKnuth\'s hobbies include music, and specifically playing the [[organ (music)|organ]]. He has a pipe organ installed in his home. Knuth disclaims any particular talent in the instrument, however. He does not use [[email]], saying that he used it from about 1975 until [[January 1]], [[1990]], and that was enough for one lifetime. He finds it more efficient to respond to correspondence in \"batch mode\", such as one day every three months, to be sent by [[snail mail]].\n\nHe is married to Jill Knuth, who published a book on [[liturgy]]. They have two children.\n\nKnuth published his first \"scientific\" article in a school magazine in [[1957]] under the title \"Potrzebie System of Weights and Measures,\" part of which included defining the [[fundamental unit]] of [[length]] as the thickness of [[MAD Magazine|\'\'MAD\'\' magazine]] #26, and naming the fundamental unit of [[force]] \"whatmeworry\". \'\'MAD\'\' magazine bought the article and published it in the June 1957 issue.\n\nIn [[1971]], Knuth was the recipient of the first [[Association for Computing Machinery|ACM]] [[Grace Murray Hopper Award]].\n\n==Tempo oge==\n* [[Knuth-Morris-Pratt algorithm]]\n* [[Knuth\'s up-arrow notation]]\n* The [[Knuth-Bendix completion algorithm]]\n\n==Interviews, Q&A==\n* [http://www.literateprogramming.com/clb93.pdf Computer Literacy, 1993]\n* [http://www.tug.org/TUGboat/Articles/tb17-1/tb50knut.pdf TUG Florida, 1995]\n* [http://www.ntg.nl/maps/pdf/16_14.pdf Dr. Dobb\'s Journal, 1996]\n* [http://web.archive.org/web/19981205171451/www.awl.com/cseng/innovations/winter96/knuth.html AW Innovations, 1996]\n* [http://bulletin.cstug.cz/pdf/bul964.pdf Czech TUG, 1996]\n* [http://www.ntg.nl/maps/pdf/16_15.pdf Amsterdam, 1996]\n* [http://www.amazon.com/exec/obidos/tg/feature/-/4165 Amazon, 1997]\n* [http://technetcast.ddj.com/tnc_play_stream.html?stream_id=199 Boston ACM, 1999]\n* [http://www.technologyreview.com/view/article.asp?p=11380 Technology Review, 1999]\n* [http://www.tug.org/TUGboat/Articles/tb22-1-2/tb70knut.pdf U.K. TUG, 1999]\n* [http://www.salon.com/tech/feature/1999/09/16/knuth salon.com, 1999]\n* [http://www.tug.org/TUGboat/Articles/tb21-2/tb67advo.pdf\nAdvogato, 2000]\n* [http://www.ams.org/notices/200203/fea-knuth.pdf AMS, 2001]\n* [http://www.geekchic.com/repliq6.htm Geek Celebs, 2001]\n* [http://www.tug.org/TUGboat/Articles/tb23-3-4/tb75knuth.pdf Oslo, 2002]\n* [http://www.heise.de/ct/02/05/190 c\'t, 2002 (in german)]\n\n==Tumbu kaluar==\n* [http://quote.wikipedia.org/wiki/Donald_Knuth Wikiquote - Quotations from Donald Knuth]\n* [http://www-cs-faculty.stanford.edu/~knuth/ The Stanford home page of Donald Knuth]\n* [http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Knuth.html Long biography of Knuth]\n* [http://www.softpanorama.org/People/Knuth/index.shtml Donald Knuth: Leonard Euler of Computer Science (Softpanorama)]\n\n[[Category:Computer pioneers|Knuth, Donald]]\n[[Category:Computer scientists|Knuth, Donald]]\n[[Category:Mathematicians|Knuth, Donald]]\n[[Category:Programmers|Knuth, Donald]]\n[[Category:Technology writers|Knuth, Donald]]\n\n[[da:Donald E. Knuth]]\n[[de:Donald Knuth]]\n[[eo:Donald KNUTH]]\n[[fr:Donald Ervin Knuth]]\n[[nl:Donald Knuth]]\n[[ja:ドナルド・クヌース]]\n[[pl:Donald Knuth]]\n[[ro:Donald E. Knuth]]\n[[zh-cn:高德纳]]\n[[zh-tw:高德納]]\n[[sv:Donald Knuth]]\n[[ko:%EB%8F%84%EB%84%90%EB%93%9C_%ED%81%AC%EB%88%84%EC%8A%A4]]','/* See also */',13,'Budhi','20041224084042','',0,0,1,0,0.092567030849,'20050208111611','79958775915957'); INSERT INTO cur VALUES (1284,0,'Uji_Kuiper','Dina [[statistik]], \'\'\'uji Kuiper\'\'\' raket jeung [[uji Kolmogorov-Smirnov]] nu geus leuwih ilahar dipaké (atawa leuwih ilahar disebut uji K-S). Sakumaha uji K-S, kuantitas D+ jeung D- diitung nu nunjukkeun simpangan maksimum saluhureun jeung sahandapeun dua sebaran kumulatif nu keur dibandingkeun. The trick with Kuiper\'s test is to use the quantity D+ + D- as the test statistic. This small change makes Kuiper\'s test as sensitive in the tails as at the median and also makes it invariant on cyclic transformations of the independent variable. [[Uji Anderson-Darling]] mangrupa uji séjén nu nyadiakeun sénsitivitas nu sawanda na buntut (Ing. \'\'tail\'\') salaku médian, tapi teu nyadiakeun invarians siklik.\n\nThis invariance makes Kuiper\'s test invaluable when testing for variations by time of year or day of the week or time of day. One example would be to test the hypothesis that computers fail more in some parts of the year than others. To test this, we would collect the dates on which the test set of computers had failed and build a cumulative distribution. The null hypothesis is that the failures are uniformly distributed. Kuiper\'s statistic does not change if we change the beginning of the year and doesn\'t require that we bin failures into months or anything like that.\n\nA test like this would, however, tend to miss the fact that failures occur only on weekends since weekends are spread throughtout the year. This inability to distinguish distributions with a comb-like shape from continuous distributions is a key problem with all statistics based on a variant of the K-S test.','',3,'Kandar','20041224015552','',0,0,0,0,0.904054280326,'20041224015552','79958775984447'); INSERT INTO cur VALUES (1285,0,'Cramér-Rao_inequality','Dina [[statistik]], \'\'\'Ka-teusarua-an Cramér-Rao\'\'\', ngaran keur ngahargaan ka [[Harald Cramér]] jeung [[Calyampudi Radhakrishna Rao]], netepkeun yen saling dina [[Fisher information]] ngeunaan parameter θ ngarupakeun wates handap dina [[varian]] tina [[bias (statistics)|unbiased]] estimator. Dina sababaraha kasus, taya unbiased estimator sabenerna dina wates handap ieu.\n\nDina sabarabaha kasus oge, \'\'biased\'\' estimator bisa mibanda varian jeung [[mean kuadrat kasalahan]] numana \'\'handap\'\' tina wates handap Cramér-Rao (wates hanap ngan dipake keur estimators nu unbiased). Tempo [[bias (statistics)]].\n\n==Bukti==\n\nAnggap [[variabel random]] \'\'X\'\', ngabogaan [[probability density function]] \'\'f(x,θ)\'\'. Di dieu \'\'T\'\' = \'\'t\'\'(\'\'X\'\') nyaeta [[statistic]] dipake salaku [[estimator]] keur \'\'θ\'\'. Lamun \'\'V\'\' ngarupakeun [[score]], nyaeta\n\n:\nV=\\frac{\\partial}{\\partial\\theta}\\log f(X;\\theta).\n\n\nmangka [[expectation]] \'\'V\'\', ditulikeun \'\'E(V)\'\', sarua jeung. Lamun urang nganggap [[covariance]] cov(\'\'V\'\', \'\'T\'\') \'\'V\'\' sarta \'\'T\'\' urang ngabogaan cov(\'\'V\'\', \'\'T\'\') = E(\'\'VT\'\') sabab ekspektasi \'\'V\'\' sarua jeung zero. Ngalegaan tina rumus ieu urang ngabogaan\n\n:\n{\\rm cov}(V,T)=E\\left(\nT\\cdot\\frac{\\partial}{\\partial\\theta}\\log f(X;\\theta)\n\\right).\n\nIeu bisa dilegaan ku ngagunakeun identitas \n:\\frac{\\partial}{\\partial\\theta}\\log Q=\\frac{1}{Q}\\frac{dQ}{d\\theta}\n\n\nsarta harti ekspektasi nu diberekeun, sanggeus nunda \'\'f\'\'(\'\'x\'\'; θ),\n\n:\n\\int t(x)\\left\\{\\frac{\\partial}{\\partial\\theta} f(x;\\theta)\\right\\}\\, dx.\n\n\nAyeuna lamun turunan ditukerkeun ku integral, mangka ieu ngan sakadar turunan (wrt \'\'θ\'\') tina ekspektasi \'\'t\'\'(\'\'X\'\'), atawa\n \n:\\frac{\\partial}{\\partial\\theta}E(T).\n\nSabab \'\'T\'\' ngarupakeun unbiased, ekspektasi-na θ; we are left with 1.\n\n[[Cauchy-Schwarz inequality]] nembongkeun yen\n\n:\n{\\rm var\\ } T\\times{\\rm var\\ } V \\geq {\\rm cov}(V,T)=1,\n\nmangka dina kasus ieu\n\n:\n{\\rm var\\ }T \\geq \\frac{1}{{\\rm var\\ } V} = \\frac{1}{I(\\theta)}\n\n\ndimana \'\'I(θ)\'\' ngarupakeun [[Fisher information]]. Ieu ngarupakeun kateusaruaan Cramér-Rao; aya di wates dina varian tina unbiased estimators.\n\n[[efficiency (statistics)|Efisiensi]] \'\'T\'\' dihartikeun ku\n\n:e(T)=\\frac{1/I(\\theta)}{{\\rm var\\ }T}\n\natawa varian minimum nu mungkin keur unbiased estimator dibagi ku varian nu sabenerna. Mangka wates handap Cramér-Rao diberekeun ku \'\'e\'\'(\'\'T\'\') ≤ 1.\n\n[[Category:Statistics]]','',13,'Budhi','20041224113611','',0,0,1,0,0.179933925709,'20041224113611','79958775886388'); INSERT INTO cur VALUES (1286,6,'Leylines80of137.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040819030315','',0,0,0,1,0.775352759077542,'20041224085308','79959180969684'); INSERT INTO cur VALUES (1287,6,'Leylines.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040819030509','',0,0,0,1,0.435720919105896,'20041224085308','79959180969490'); INSERT INTO cur VALUES (1288,6,'Atisan.png','Conto molekul, dicokot ti Wikipédia vérsi Inggris','Conto molekul, dicokot ti Wikipédia vérsi Inggris',3,'Kandar','20040819040722','',0,0,0,1,0.852546349030497,'20041218130435','79959180959277'); INSERT INTO cur VALUES (1289,0,'Raw_score','#REDIRECT [[Skor atah]]\n','Raw score dipindahkeun ka Skor atah',13,'Budhi','20040819040954','',0,1,0,1,0.955569018568442,'20040819040954','79959180959045'); INSERT INTO cur VALUES (1290,0,'El_Niño','[[image:el-nino.gif|right|thumb|400px|Chart of ocean surface temperature anomaly during the last strong El Niño in December 1997]]\n\n\'\'\'El Niño\'\'\' and \'\'\'La Niña\'\'\' are major temperature fluctuations in the [[Pacific Ocean]]. They are Pacific signatures of the global \'\'\'ENSO\'\'\' phenomenon (\'\'\'El Niño-Southern Oscillation\'\'\'). Their effect on climate in the southern hemisphere is profound. Their role in [[global warming]] or cooling is an area of active research, with no clear consensus yet.\n\nEl Niño was originally recognized by fishermen off the coast of [[South America]] as the appearance of unusually warm water in the Pacific Ocean. El Niño is the warming of the surface waters of the eastern equatorial [[Pacific Ocean]] that occurs at irregular intervals of 2-7 years, usually lasting 1-2 years. Along the west coast of [[South America]], southerly winds promote the [[upwelling]] of cold, nutrient-rich water that sustains large [[fish]] populations, that sustain abundant sea birds, whose droppings support the [[fertilizer]] industry. Near the end of each calendar year, a warm current of nutrient-poor tropical water replaces the cold, nutrient-rich surface water of the [[Humboldt Current]]. Because this condition often occurs around [[Christmas]], it was named El Niño ([[Spanish language|Spanish]] for boy child, referring to the Child [[Jesus Christ |Christ]]). In most years the warming lasts only a few weeks or a month, after which the weather patterns return to normal and fishing improves. However, when El Niño conditions last for many months, more extensive ocean warming occurs and economic results can be disastrous. \n\nEl Niño\'s weather effects depend on the location, time of year, and the particular episode. Typically, winters are warmer than normal in the upper midwest states of the U.S., while central and southern California, and the southeastern U.S., are wetter than normal. The Pacific Northwest states, on the other hand, tend to be drier during an El Niño. During a La Niña, by contrast, the midwestern U.S. tends to be drier than normal. Often, an El Niño is associated with drier, hotter summers in parts South America and [[Europe]], although the western coast of South America and parts of Central America can be much wetter than usual. There is often drought in both [[Australia]] and [[Africa]]. \n\n== ENSO ==\nENSO is a set of interacting parts of a single global system of climate fluctuations that come about as a consequence of [[atmospheric circulation]]. ENSO is the most prominent known source of interannual variability in weather and climate around the world (~3 to 8 years), though not all areas are affected. The Southern Oscillation (SO) is a global-scale seesaw in atmospheric pressure between [[Indonésia]]/North [[Australia]], and the southeast Pacific. Its measure is through the Southern Oscillation Index (SOI). Global ENSO has signatures in the Pacific, Atlantic and Indian Oceans. In the Pacific, during major warm events El Niño warming extends over much of the tropical Pacific and becomes clearly linked to the SOI intensity. While ENSO events are basically in phase between the Pacific and Indian Oceans, ENSO events in the Atlantic Ocean lag those in the Pacific by 12-to-18 months. Many of the countries most affected by ENSO events are developing countries within main continents (South America, Africa...), with economies that are largely dependent upon their agricultural and fishery sectors as a major source of food supply, employment, and foreign exchange. New capabilities to predict the onset of ENSO events in the three oceans can have global socio-economical impacts. While ENSO is a global and natural part of the Earth\'s climate, whether its intensity or frequency may change as a result of global warming is an important concern. Low-frequency variability has been evidenced. Interdecadal modulation of ENSO might exist.\n\nIn the Pacific, La Niña is characterized by unusually cold ocean temperatures in the Equatorial Pacific, compared to El Niño, which is characterized by unusually warm ocean temperatures in the same area. La Niña usually comes after El Niño.\n\n==Tumbu kaluar== \n* [http://www.pmel.noaa.gov/tao/elnino/el-nino-story.html NOAA explanation]\n\n----\n\n\'\'\'\'\'El Niño\'\'\' is also the nickname of [[Spain|Spanish]] [[golf]]er [[Sergio García]].\'\'\n\n[[da:El Niño]] [[de:El Niño]] [[fr:El Niño]] [[ja:エルニーニョ]] [[nl:El Niño]] [[pl:El Niño]] [[zh-cn:厄尔尼诺现象]]\n[[Category:Environment]]','',3,'Kandar','20041122094403','',0,0,0,0,0.629424916408,'20041122094403','79958877905596'); INSERT INTO cur VALUES (1291,6,'El-nino.gif','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040819051022','',0,0,0,1,0.220206076484365,'20041122094407','79959180948977'); INSERT INTO cur VALUES (1292,6,'Exponential_pdf.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040819052916','',0,0,0,1,0.234323357450146,'20040917030816','79959180947083'); INSERT INTO cur VALUES (1293,0,'Anomaly_time_series','#REDIRECT [[Anomali deret waktu]]\n','Anomaly time series dipindahkeun ka Anomali deret waktu',13,'Budhi','20040819055641','',0,1,0,1,0.510998588531277,'20040819055641','79959180944358'); INSERT INTO cur VALUES (1294,0,'Sosiologi','\'\'\'Sosiologi\'\'\' nyaéta élmu ngeunaan [[aturan sosial]] sarta nu pakait jeung [[prosés]]na, sarta ngabagi masyarakat lain ngan ukur salaku individu, tapi anggota ti [[asosiasi]], [[Group (sociology)|golongan]], jeung [[institusi]].\n\nA typical textbook definition of sociology calls it the study of the social lives of humans, groups and [[society|societies]]. Sociology is interested in our behavior as social beings; thus the sociological field of interest ranges from the analysis of short contacts between anonymous [[individual]]s on the street to the study of [[globalization|global social processes]].\n\n==Introduction==\nSociology as a discipline emerged in the [[19th century]] as an academic response to the challenge of [[modernity]]: as the world is becoming smaller and more integrated, people\'s experience of the world is increasingly atomized and dispersed. Sociologists hoped not only to understand what held social groups together, but also to develop an \"antidote\" to [[social disintegration]]. \n\nToday sociologists research macro-[[structure]]s that organize society, such as [[race]] or [[ethnicity]], [[social class|class]] and [[gender role|gender]], and institutions such as the [[family]]; social processes that represent deviation from, or the breakdown of, these structures, including [[crime]] and [[divorce]]; and micro-processes such as interpersonal interactions. \n\nSociologists often rely on [[quantitative method]]s of [[social research]] to describe large patterns in social relationships, and in order to develop models that can help predict social change and how people will respond to social change. Other branches of sociology believe that [[qualitative method]]s -- such as focused interviews, group discussions and ethnographic methods -- allow for a better understanding of social processes. An appropriate middle ground is that both approaches are complementary, that results from each approach can fill in results from the other approaches. For example, the quantitative methods can describe the large or general patterns, while the qualitative approaches can help to understand how individuals understand or respond to those changes.\n\n==Sajarah==\nSosiologi ngarupakeun ulikan nu kaitung anyar ti antara disiplin [[élmu sosial]] séjénna kayaning [[ékonomi]], [[élmu politik]], [[antropologi]], jeung [[psikologi]].\n\nIstilah ieu dikedalkeun ku [[Auguste Comte]], nu miharep bisa ngahijikeun sakabéh ulikan ngeunaan umat manusa--kaasup sajarah, psikologi, jeung ékonomi. Skéma sosiologis anjeunna pribadi nyirikeun kaayaan [[abad ka-18]]; anjeunna percaya yén sadaya kahirupan manusa geus ngaliwatan hambalan-hambalan sajarah nu sarua nu, if one could grasp this progress, one could prescribe the remedies for social ills.\n\nIn the end, Sociology did not replace the other social sciences, but came to be another of them, with its own particular emphases in terms of subject matter and methods. Today, Sociology studies humankind\'s organizations and social institutions, largely by a comparative method. It has concentrated particularly on the organization of complex [[industrial society|industrial societies]].\n\n==Major branches==\n*[[Functionalism (sociology)|Functionalism]]\n*[[conflict theory]]\n*[[interactionism]] or Social Action theory and [[symbolic-interactionism]]\n\n==Specialised areas==\n\nSociologists study a great variety of topics. To get a good idea of the range of topics, visit the International Sociological Association\'s [http://www.ucm.es/info/isa/rc.htm Research Committee\'s page] which lists topics such as Aging, Arts, Armed Conflict, Disasters, Futures Research, Health, Law, Leisure, Migration, Population, Religion, Tourism, Women in Society, Work, and many others. The American Sociological Association\'s [http://www.asanet.org/sections/general.html sections page] lists sections covering many of the same topics, as well as others.\n\nBelow are some of these areas and topics, with links to Wikipedia discussions of these areas and topics.\n\n*[[Economic sociology]]\n*[[Environmental sociology]]\n*[[Economic development]]\n*[[Human ecology]] (sometimes included into sociology proper)\n*[[Industrial sociology]]\n*[[Medical sociology]]\n*[[micro-sociology|Micro sociology]]\n*[[Political sociology]]\n*[[Program evaluation]]\n*[[Rural sociology]]\n*[[Sociology of religion]]\n*[[Sociology of science and technology]]\n*[[Systems theory]]\n*[[Behavioral finance|Sociology of Markets]]\n*[[Sociology of industrial relations]]\n*[[Social change]]\n*[[Demography|Social demography]]\n*[[Sociology of disaster]]\n*[[Urban sociology]]\n\n==Key sociological topics==\n*[[sociology of knowledge]] (or: [[social constructionism]])\n*[[structuralism]]\n*[[social class|class]]\n*[[race]]\n*[[gender role|gender/sex]]\n*[[culture]]\n*[[deviance]]\n*[[justified irresponsibility]]\n*[[role]] and [[role homogeneity]]\n*[[Labour (economics)|work]]\n*[[role]]\n*[[social structure]]\n*[[modernity]]\n*[[generation]]s\n*[[new institutionalism]]\n\n==Sociology and the Internet==\nThe [[Internet]] is of interest for sociologists in three views at least: as a tool for [[social research|research]], for example by using [[online questionnaires]] instead of paper ones, as a discussion platform (see \'External links\' section below), and as a research topic. Sociology of the Internet in the last sense includes analysis of online communities (e.g. as found in newsgroups), virtual communities and [[Virtual World|virtual worlds]] organisational change catalysed through new media like the Internet, and societal change at-large in the transformation from [[industrial society|industrial]] to [[informational society]] (or to [[information society]]).\n\n== Terms and methods==\n*\'\'[[sociological perspective]]\'\'\n*\'\'[[social fact]]\'\'\n*\'\'[[belonging]]\'\'\n\n\'\'\'Methods:\'\'\' [[quantitative method]], [[qualitative method]], [[ethnography]]\n\n==Sociologists==\nSee [[List of sociologists]] for sociologists with entries in Wikipedia.\n\nFamous sociologists include [[Auguste Comte]], [[Emile Durkheim]], [[Ferdinand Toennies]] (Ferdinand Tönnies), [[Georg Simmel]], [[Max Weber]], [[Albion Woodbury Small]], [[Charles Horton Cooley]], [[Ibn Khaldun]], [[Pitirim Sorokin]], [[Vilfredo Pareto]], [[Robert E. Park]], [[Karl Mannheim]], [[Talcott Parsons]], [[Robert K. Merton]], [[Peter Blau]], [[Reinhard Bendix]], [[Norbert Elias]], [[Ralf Dahrendorf]], [[John Rex]], [[David Lockwood]], [[Erving Goffman]], [[Harold Garfinkel]], and [[Anthony Giddens]]. [[Karl Marx]] would not have called himself a sociologist, but his thought has had an immense impact on sociological theory. Other references can be found in the \"Famous Sociologists\" section [http://www2.fmg.uva.nl/sociosite/topics/sociologists.html] of the SocioSite [http://www.sociosite.net].\n\n==Comparison to other social sciences==\nIn the early 20th century, sociologists and psychologists who conducted research in non-industrial societies contributed to the development of [[anthropology]]. It should be noted, however, that anthropologists also conducted research in industrial societies. Today sociology and anthropology are better contrasted according to different theoretical concerns and methods rather than objects of study. \n\nSociology has some links with [[social psychology]], but the former is more interested in social structures and the later in social behaviors\n\nA distinction should be made between these and forensic studies within these disciplines, particularly where anatomy is involved. These latter studies might be better named as [[Forensic psychology]].\n\n==Tiori sosial==\nSocial theory is a distinction applied to the work considered outside of the mainstream of sociology. Among sociologists who model their work on the successful sciences of physics or chemistry, social theory may be applied to all work produced outside of the [[scientific method]], in contradistinction to a \'\'sociological\'\' theory which has been \"correctly\" tested. However, a natural science model has never completely predominated sociology, nor has there ever been much consensus, even among the adherents of that model, as to what would constitute valid evidence or even the proper unit of analysis. Consequently, the distinction between sociology and social theory has always been more reflective of classifier than the theory described as belonging to one or the other. Many theorists prefer to describe themselves as social theorists because they are critical of the sociological community or were not trained as sociologists.\n\n[[Marxism|Marxist theory]], [[critical theory]], [[Post-colonialism|post-colonial theory]], [[feminist theory]], [[Structuralism|structuralist theory]], [[Post-structuralism|post-structuralist theory]], [[queer theory]], [[Postmodernism|Postmodern theory]], and other theories probably unmentioned have all at times been considered outside the mainstream of sociology and been referred to as social theory. However, as all these theories have been adopted to some extent by mainstream sociology, distinctions are made less often.\n\nSee also [[:Category:Philosophy]].\n\n== Tempo oge ==\n\nSee also: [[criminology]], [[disabilities]], [[education]], [[etiquette]], [[Frankfurt School]], [[Gemeinschaft and Gesellschaft]], [[gender & sexuality]], [[Marxism]], [[mass media]], [[media studies]], [[Milgram experiment]], [[revolution]], [[social engineering (political science)|social engineering]], [[political economy]], [[race & ethnicity]], [[social control]], [[social movement]]s, [[tautology]], [[teleology]], [[theory]], [[sociological imagination]], [[socioeconomic system]]s, [[racism]], [[social order]], [[social structure]], [[social issue]], [[scale (social sciences)]]\n, [[List of publications in sociology| Important publications in sociology]]\n\n==Tumbu kaluar==\n*[http://www.ucm.es/info/isa/ International Sociological Association ISA]\n*[http://www.asanet.org/ American Sociological Association ASA]\n*[http://www.sociosite.net SocioSite] at University of Amsterdam\n*[http://www.theory.org.uk Social theory for fans of popular culture]\n*[http://www.angelfire.com/or/sociologyshop/socsnip.html Sociological Snippets]\n*[http://www.conferencealerts.com/socio.htm Conference alerts - sociology]\n*[http://www.sociolog.com/ Julian Dierkes\' Comprehensive Guide to Sociology]\n*[http://www.appliedsoc.org/ Society for Applied Sociology]\n*[http://gsociology.icaap.org/methods/ Methods in Social Science Research]\n[[Category:Sociology]]\n[[Category:Topic lists]]\n\n[[af:Sosiologie]]\n[[ast:Socioloxía]]\n[[bg:Социология]]\n[[ca:Sociologia]]\n[[cs:Sociologie]]\n[[da:Sociologi]]\n[[de:Soziologie]]\n[[en:Sociology]]\n[[eo:Sociologio]]\n[[es:Sociología]]\n[[et:Sotsioloogia]]\n[[eu:Soziologia]]\n[[fa:جامعه‌شناسی]]\n[[fr:Sociologie]]\n[[fy:Sosjology]]\n[[gl:Socioloxía]]\n[[he:סוציולוגיה]]\n[[hi:समाज शास्त्र]]\n[[hr:Sociologija]]\n[[hu:Szociológia]]\n[[ia:Sociologia]]\n[[id:Sosiologi]]\n[[it:Sociologia]]\n[[ja:社会学]]\n[[ko:사회학]]\n[[la:Sociologia]]\n[[lt:Sociologija]]\n[[lv:Sociologija]]\n[[ms:Sosiologi]]\n[[nds:Soziologie]]\n[[nl:Sociologie]]\n[[no:Sosiologi]]\n[[pl:Socjologia]]\n[[pt:Sociologia]]\n[[ro:Sociologie]]\n[[ru:Социология]]\n[[simple:Sociology]]\n[[sl:Sociologija]]\n[[sr:Социологија]]\n[[sv:Sociologi]]\n[[tr:Sosyoloji]]\n[[uk:Соціологія]]\n[[zh:社会学]]','HasharBot - warnfile Adding:ro,zh,ru,id,eu,ko,hi,hu,he Modifying:zh-cn,zh-tw',0,'81.220.107.14','20041110061425','',0,0,0,0,0.129632484228,'20050103081414','79958889938574'); INSERT INTO cur VALUES (1295,0,'Public_affairs','\'\'\'Public affairs\'\'\' ngawengku kabeh watesan kaasup [[public policy]] saperti oge [[public administration]], duanana raket pakait sarta ngagambarkeun kaayaan [[political science]] oge [[economics]].\n\nDiskusi kawijakan publik ngarupakeun hal umum jeung milukeun partisan, sarta urang nganggap yen partisipan dina diskusi kawijakan publik mibanda pandangan husus nu nempo leuwih jentre dina diskusi. \n\n\'\'Public affairs\'\', di bagean sejen, umumna ngaku bakal jadi \'\'non-partisan\'\'.\nHal ieu museurkuen kana metoda adminitrasi publik, saperti nu geus kagambarkeun dina conto sajarah.\n\n\'\'Public affairs\'\' bisa diartikeun ku \"manajemen lembaga nu pakait jeung kauntungan\" (Jeremy Kane, co-founder of EPPA, pan-European public affairs advisers).\n\n[[Social activism]] kaasup kagiatan nu kawentar sarta [[commentary]] dina \'\'public affairs\'\'.\n\nJejer dina topik \'\'public affairs\'\':\n* [[state]], [[government]]. [[forms of government]]\n** [[republic]]\n** [[democracy]]\n** [[monarchy]]\n* [[security]]\n** [[crime]], [[criminal justice]]\n** [[military]]\n** [[civil defense]], [[emergency preparedness]], [[community emergency response team]]s\n* [[regulation]], [[deregulation]]\n** [[public health]], [[pollution]], [[emissions trading]]\n** [[industrial policy]], [[investment policy]], [[tax, tariff and trade]]\n* [[budget]]\n** [[taxation]]\n** [[socialism]]\n** [[technocracy]]\n*[[management]]\n*[[public affairs degrees]]\n\n[[eo:Publikaferoj]]\n[[it:Affari pubblici]]','',13,'Budhi','20040904222305','',0,0,0,0,0.988472670311,'20040904222305','79959095777694'); INSERT INTO cur VALUES (1296,6,'Diagram_molekul_cai.png','Ti Wikipédia vérsi Inggris','Ti Wikipédia vérsi Inggris',3,'Kandar','20040819115503','',0,0,0,1,0.852022901039592,'20040826090113','79959180884496'); INSERT INTO cur VALUES (1297,0,'Prediction_interval','#REDIRECT [[Prediksi interval]]\n','Prediction interval dipindahkeun ka Prediksi interval',13,'Budhi','20040820001721','',0,1,0,1,0.727118770337774,'20040820001721','79959179998278'); INSERT INTO cur VALUES (1298,0,'Kolmogorov-Smirnov_test','#REDIRECT [[Kolmogorov-Smirnov tes]]\n','Kolmogorov-Smirnov test dipindahkeun ka Kolmogorov-Smirnov tes',13,'Budhi','20040820012143','',0,1,0,1,0.0795251793037403,'20040820012143','79959179987856'); INSERT INTO cur VALUES (1299,0,'Harmonic_mean','[[pl:%C5%9Arednia harmoniczna]]\n\nDina [[matematik]], the \'\'\'harmonic mean\'\'\' is one of several methods of calculating an [[average]].\n\nThe harmonic mean of the positive [[real number]]s \'\'a\'\'1,...,\'\'a\'\'\'\'n\'\' is defined to be\n\n:H = \\frac{n}{\\frac{1}{a_1} + \\frac{1}{a_2} + ... + \\frac{1}{a_n}}\n\nThe harmonic mean is never larger than the [[geometric mean]] or the [[arithmetic mean]] (see [[generalized mean]]).\n\nIn certain situations, the harmonic mean provides the correct notion of \"[[average]]\". For instance, if for half the \'\'distance\'\' of a trip you travel at 40 miles per hour and for the other half of the \'\'distance\'\' you travel at 60 miles per hour (i.e. less time), then your average speed for the trip is given by the harmonic mean of 40 and 60, which is 48. Similarly, if in an electrical circuit you have two [[resistor|resistors]] connected \'\'in parallel\'\', one with 40 [[ohm]]s and the other with 60 ohms, then the average resistance is 24 ohms, which is half of the harmonic mean, as there are as many paths for current to travel as there are resistors (i.e. if you replace each resistor by a 24 ohm resistor, the total resistance will stay the same). Typically the harmonic mean is appropriate for situations when the average of a [[rate]] is desired.\n\nAnother formula for the harmonic mean of two numbers is to multiply the two numbers, and divide that quantity by the arithmetic mean of the two numbers. In mathematical terms:\n\n:\\frac {\\alpha \\cdot \\beta} {\\left(\\frac{\\alpha + \\beta} {2} \\right)}\n\nThis is equivalent to the formula above, but simpler for some calculations.\n\n==Conto==\n\nIn [[optics|geometric optics]], the [[mirror equation]] can be described in terms of a harmonic mean. Consider the case of a concave [[spherical mirror]]. Let its object distance be \'\'p\'\', its image distance be \'\'q\'\', and its radius of curvature be \'\'R\'\'. Then \'\'R\'\' is the \'\'\'harmonic mean\'\'\' of \'\'p\'\' and \'\'q\'\'.\n\nThe focus of a spherical mirror lies halfway between the center of curvature and the vertex, so that the focal distance \'\'f\'\' is half of the radius of curvature. Since \'\'R\'\' is the harmonic mean of \'\'p\'\' and \'\'q\'\', this means that the object and its image must lie on either side of the center of curvature: not both on the same side. It also means that both object and image lie beyond the focus (away from the vertex), i.e. \'\'p > R/2\'\' and \'\'q > R/2\'\'. But if \'\'p = R/2\'\' then \'\'q = \\infty \'\', or if \'\'q = R/2\'\' then \'\'p = \\infty \'\'. This is also true of harmonic means in general, independently of any concave spherical mirror.\n\nIf \'\'p\'\' and \'\'q\'\' are a pair of finite positive numbers, then both of them must each be larger than half of their harmonic mean.\n\n==Tumbu kaluar==\n* [[Diatessaron (harmony)]]\n* [[Tertius minor]]','/* See also */',13,'Budhi','20040901063340','',0,0,0,0,0.463503705088,'20040901063340','79959098936659'); INSERT INTO cur VALUES (1300,0,'Robust','Referring to the health, strength and durability of something. In [[computer|computing]] terms, being robust is reliability or being available seven days a week, twenty-four hours a day. Robustness is an important characterists of the [[internet]] because [[network]] design is a key factor in the availability of [[data]].\n\n==Conto==\n\n* Robust [[e-mail]] allows a company to convert most of their [[communication|communications]] from paper to electronic.\n* Robust [[Web]] sites allow customers to purchase items worldwide at any time of day and without fear of errors.\n* Robust [[computers]] perform without stress or downtime, improving productivity.\n* People prefer robust, always-on networking systems such as [[Integrated Services Digital Network|ISDN]] versus dialup, even if they are not much faster.\n* [[OpenBSD]] is considered more robust than [[Linux]] is considered more robust than [[Microsoft Windows|Windows]].\n\nA robust [[file sharing]] [[Computer program|program]] may not provide all the desired data all the time but will deliver reliably, matching queries and completing [[download|downloads]].\n\nSee also: [[Programming]] | [[Security]] | [[Data Haven]]','/* Examples */',13,'Budhi','20040901070416','',0,0,0,0,0.199163190182,'20041231124655','79959098929583'); INSERT INTO cur VALUES (1301,0,'Susunan_data','Dina [[statistik]], \'\'\'susunan data\'\'\' nyaéta [[set]] tina [[data]] nu eusina:\n#daptar [[subjék panalungtikan]] jeung\n#[[data vector]] nu silih pakait.\n\nTempo ogé: [[Tiori statistik]]','',3,'Kandar','20050208063122','',0,0,0,0,0.025685790007,'20050208063122','79949791936877'); INSERT INTO cur VALUES (1302,0,'Tabel_lambang_matematis','__NOTOC__\nDina [[matematik]], a set of symbols is frequently used in mathematical expressions.\nAs mathematicians are familiar with these symbols, they are not explained each time they are used.\nSo, for mathematical novices, the following table lists many common symbols together with their name, pronunciation and related field of mathematics.\nAdditionally, the second line contains an informal definition, and the third line gives a short example.\n\n\'\'\'Catetan:\'\'\' Mun sababaraha lambang teu némbongan sakumaha mistina, panyaksrak anjeun can sagemblengna ngalarapkeun [[HTML]] 4 [[character entity|character entities]], atawa anjeun kudu nginstal [[aksara]] tambahan.\nAnjeun bisa mariksa panyaksrak anjeun di [http://www.alanwood.net/demos/ent4_frame.html dieu]. \n\n\n\n \n \n \n \n \n \n\n\n\n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
LambangNgaranDibacaKategori

+

\n
[[tambah]]\nplus\n[[aritmétik]]\n
4 + 6 = 10 nu hartina mun opat ditambahkeun ka genep, jumlahna, atawa hasilna, nyéta 10.
43 + 65 = 108; 2 + 7 = 9\n\n

\n
[[kurang]]\nminus\n[[aritmétik]]\n
9 − 4 = 5 nu hartina mun salapan dikurangan opat, hasilna bakal lima. Tanda minus ogé nandakeun yén hiji angka [[angka négatif jeung non-négatif|négatif]]. Pikeun conto, 5 + (−3) = 2 hartina mun lima ditambahkeun jeung négatif tilu, hasilna dua.
87 − 36 = 51\n\n


\n
[[material implication]]\n implies; if .. then\n [[propositional calculus|propositional logic]]\n
\'\'A\'\' ⇒ \'\'B\'\' means: if \'\'A\'\' is true then \'\'B\'\' is also true; if \'\'A\'\' is false then nothing is said about \'\'B\'\'.
→ may mean the same as ⇒, or it may have the meaning for [[Fungsi (matematik)|function]]s mentioned further down\n
\'\'x\'\' = 2  ⇒  \'\'x\'\'2 = 4 is true, but \'\'x\'\'2 = 4   ⇒  \'\'x\'\' = 2 is in general false (since \'\'x\'\' could be −2)\n\n


\n
[[material equivalence]]\n if and only if; iff\n [[propositional calculus|propositional logic]]\n
\'\'A\'\' ⇔ \'\'B\'\' means: \'\'A\'\' is true if \'\'B\'\' is true and \'\'A\'\' is false if \'\'B\'\' is false\n
\'\'x\'\' + 5 = \'\'y\'\' + 2  ⇔  \'\'x\'\' + 3 = \'\'y\'\'\n\n

\n
[[logical conjunction]] or \'\'\'meet\'\'\' in a [[lattice (order)|lattice]]\n and\n [[propositional calculus|propositional logic]], [[lattice (order)|lattice theory]]\n
the statement \'\'A\'\' ∧ \'\'B\'\' is true if \'\'A\'\' and \'\'B\'\' are both true; else it is false\n
\'\'n\'\' < 4  ∧  \'\'n\'\' > 2  ⇔  \'\'n\'\' = 3 when n is a [[natural number]]\n\n

\n
[[logical disjunction]] or \'\'\'join\'\'\' in a [[lattice (order)|lattice]]\n or\n [[propositional calculus|propositional logic]], [[lattice (order)|lattice theory]]\n
the statement \'\'A\'\' ∨ \'\'B\'\' is true if \'\'A\'\' or \'\'B\'\' (or both) are true; if both are false, the statement is false\n
\'\'n\'\' ≥ 4  ∨  \'\'n\'\' ≤ 2  ⇔ \'\'n\'\' ≠ 3 when n is a [[natural number]]\n\n

¬
/

\n
[[logical negation]]\n not\n [[propositional calculus|propositional logic]]\n
the statement ¬\'\'A\'\' is true if and only if \'\'A\'\' is false
a slash placed through another operator is the same as \"¬\" placed in front\n
¬(\'\'A\'\' ∧ \'\'B\'\') ⇔ (¬\'\'A\'\') ∨ (¬\'\'B\'\'); x ∉ S  ⇔  ¬(x ∈ S)\n\n

\n
[[universal quantification]]\n for all; for any; for each\n [[predicate logic]]\n
∀ \'\'x\'\': \'\'P\'\'(\'\'x\'\') means: \'\'P\'\'(\'\'x\'\') is true for all \'\'x\'\'
∀ \'\'n\'\' ∈ \'\'\'N\'\'\': \'\'n\'\'2 ≥ \'\'n\'\'

\n
[[existential quantification]]\n there exists\n [[predicate logic]]\n
∃ \'\'x\'\': \'\'P\'\'(\'\'x\'\') means: there is at least one \'\'x\'\' such that \'\'P\'\'(\'\'x\'\') is true\n
∃ \'\'n\'\' ∈ \'\'\'N\'\'\': \'\'n\'\' + 5 = 2\'\'n\'\'\n\n

=

\n
[[equality (mathematics)|equality]]\n equals\n everywhere\n
x = y means: x and y are different names for precisely the same thing\n
1 + 2 = 6 − 3\n\n

:=

:⇔

\n
[[definition]]\n is defined as\n everywhere\n
x := y or x ≡ y means: x is defined to be another name for y (but note that ≡ can also mean other things, such as [[congruence]])
P :⇔ Q means: P is defined to be logically equivalent to Q\n
cosh \'\'x\'\' := (1/2)(exp \'\'x\'\' + exp (−\'\'x\'\')); \'\'A\'\' XOR \'\'B\'\' :⇔ (\'\'A\'\' ∨ \'\'B\'\') ∧ ¬(\'\'A\'\' ∧ \'\'B\'\')\n\n

{ , }

\n
[[set]] brackets\n the set of ...\n [[naive set theory|set theory]]\n
{a,b,c} means: the set consisting of a, b, and c\n
\'\'\'N\'\'\' = {0,1,2,...}\n\n

{ : }
{ | }

\n
set builder notation\n the set of ... such that ...\n [[naive set theory|set theory]]\n
{\'\'x\'\' : \'\'P\'\'(\'\'x\'\')} means: the set of all \'\'x\'\' for which \'\'P\'\'(\'\'x\'\') is true. {\'\'x\'\' | \'\'P\'\'(\'\'x\'\')} is the same as {\'\'x\'\' : \'\'P\'\'(\'\'x\'\')}.\n
{\'\'n\'\' ∈ \'\'\'N\'\'\' : \'\'n\'\'2 < 20} = {0,1,2,3,4}\n\n


{}

\n
[[empty set]]\n empty set\n [[naive set theory|set theory]]\n
{} means: the set with no elements; ∅ is the same thing\n
{\'\'n\'\' ∈ \'\'\'N\'\'\' : 1 < \'\'n\'\'2 < 4} = {}\n \n


\n
set membership\n in; is in; is an element of; is a member of; belongs to\n [[naive set theory|set theory]]\n
\'\'a\'\' ∈ \'\'S\'\' means: \'\'a\'\' is an element of the set \'\'S\'\'; \'\'a\'\' ∉ \'\'S\'\' means: \'\'a\'\' is not an element of \'\'S\'\'\n
(1/2)−1 ∈ \'\'\'N\'\'\'; 2−1 ∉ \'\'\'N\'\'\'\n\n


\n
[[subset]]\n is a subset of\n [[naive set theory|set theory]]\n
\'\'A\'\' ⊆ \'\'B\'\' means: every element of \'\'A\'\' is also element of \'\'B\'\'
\'\'A\'\' ⊂ \'\'B\'\' means: A ⊆ B but \'\'A\'\' ≠ \'\'B\'\'\n
\'\'A\'\' ∩ \'\'B\'\' ⊆ \'\'A\'\'; \'\'\'Q\'\'\' ⊂ \'\'\'R\'\'\'\n\n

\n
[[set theoretic union]]\n the union of ... and ...; union\n [[naive set theory|set theory]]\n
\'\'A\'\' ∪ \'\'B\'\' means: the set that contains all the elements from \'\'A\'\' and also all those from \'\'B\'\', but no others\n
\'\'A\'\' ⊆ \'\'B\'\'  ⇔  \'\'A\'\' ∪ \'\'B\'\' = \'\'B\'\'\n\n

\n
[[set theoretic intersection]]\n intersected with; intersect\n [[naive set theory|set theory]]\n
\'\'A\'\' ∩ \'\'B\'\' means: the set that contains all those elements that \'\'A\'\' and \'\'B\'\' have in common\n
{\'\'x\'\' ∈ \'\'\'R\'\'\' : \'\'x\'\'2 = 1} ∩ \'\'\'N\'\'\' = {1}\n\n

\\

\n
[[set theoretic complement]]\n minus; without\n [[naive set theory|set theory]]\n
\'\'A\'\' \\ \'\'B\'\' means: the set that contains all those elements of \'\'A\'\' that are not in \'\'B\'\'\n
{1,2,3,4} \\ {3,4,5,6} = {1,2}\n\n

( )
[ ]
{ }

\n
[[Fungsi (matematik)|function]] application; grouping\n of\n [[naive set theory|set theory]]\n
for function application: f(x) means: the value of the function f at the element x
for grouping: perform the operations inside the parentheses first\n
If f(x) := x2, then f(3) = 32 = 9; (8/4)/2 = 2/2 = 1, but 8/(4/2) = 8/2 = 4\n\n

\'\'f\'\':\'\'X\'\'→\'\'Y\'\'

\n
function arrow\n from ... to\n [[function (mathematics)|function]]s\n
fX → Y means: the function f maps the set X into the set Y\n
Consider the function fZ → N defined by f(x) = x2 \n\n

N

\n
[[natural numbers]]\n N\n [[number]]s\n
\'\'\'N\'\'\' means {0,1,2,3,...}, but see the article on [[natural number]]s for a different convention.\n
{|\'\'a\'\'| : \'\'a\'\' ∈ \'\'\'Z\'\'\'} = \'\'\'N\'\'\'\n\n

Z

\n
[[integer]]s\n Z\n [[number]]s\n
\'\'\'Z\'\'\' means: {...,−3,−2,−1,0,1,2,3,...}\n
{\'\'a\'\' : |\'\'a\'\'| ∈ \'\'\'N\'\'\'} = \'\'\'Z\'\'\'\n\n

Q

\n
[[rational numbers]]\n Q\n [[number]]s\n
\'\'\'Q\'\'\' means: {\'\'p\'\'/\'\'q\'\' : \'\'p\'\',\'\'q\'\' ∈ \'\'\'Z\'\'\', \'\'q\'\' ≠ 0}\n
3.14 ∈ \'\'\'Q\'\'\'; π ∉ \'\'\'Q\'\'\'\n\n

R

\n
[[real numbers]]\n R\n [[number]]s\n
\'\'\'R\'\'\' means: {limn→∞ \'\'a\'\'\'\'n\'\' : ∀ \'\'n\'\' ∈ N: a\'\'n\'\' ∈ Q, the limit exists}\n
π ∈ \'\'\'R\'\'\'; √(−1) ∉ \'\'\'R\'\'\'\n\n

C

\n
[[complex numbers]]\n C\n [[number]]s\n
\'\'\'C\'\'\' means: {\'\'a\'\' + \'\'bi\'\' : \'\'a\'\',\'\'b\'\' ∈ \'\'\'R\'\'\'}\n
\'\'i\'\' = √(−1) ∈ \'\'\'C\'\'\'\n\n

<
>

\n
comparison\n is less than, is greater than\n [[partial order]]s\n
\'\'x\'\' < \'\'y\'\' means: \'\'x\'\' is less than \'\'y\'\'; \'\'x\'\' > \'\'y\'\' means: \'\'x\'\' is greater than \'\'y\'\'\n
\'\'x\'\' < \'\'y\'\'  ⇔  y > x\n\n


\n
comparison\n is less than or equal to, is greater than or equal to\n [[partial order]]s\n
x ≤ y means: x is less than or equal to y; \'\'x\'\' ≥ \'\'y\'\' means: \'\'x\'\' is greater than or equal to \'\'y\'\'\n
\'\'x\'\' ≥ 1  ⇒  \'\'x\'\'2 ≥ \'\'x\'\'\n\n

\n
[[square root]]\n the principal square root of; square root\n [[real numbers]]\n
√\'\'x\'\' means: the positive number whose square is \'\'x\'\'\n
√(\'\'x\'\'2) = |\'\'x\'\'|\n\n

\n
[[infinity]]\n infinity\n [[number]]s\n
∞ is an element of the [[extended real number line|extended number line]] that is greater than all real numbers; it often occurs in [[mathematical limit|limits]]\n
limx→0 1/|\'\'x\'\'| = ∞\n\n

π

\n
[[pi]]\n pi\n [[Euclidean geometry]]\n
π means: the ratio of a [[circle]]\'s circumference to its diameter\n
\'\'A\'\' = π\'\'r\'\'² is the area of a circle with radius \'\'r\'\'\n\n

!

\n
[[factorial]]\n factorial\n [[combinatorics]]\n
\'\'n\'\'! is the product 1×2×...×\'\'n\'\'\n
4! = 24\n\n

| |

\n
[[absolute value]]\n absolute value of\n [[number]]s\n
|x| means: the distance in the [[real line]] (or the [[complex plane]]) between x and [[zero]]\n
|\'\'a\'\' + \'\'bi\'\'| = √(\'\'a\'\'2 + \'\'b\'\'2)\n\n

|| ||

\n
[[normed vector space|norm]]\n norm of; length of\n [[functional analysis]]\n
||x|| is the norm of the element \'\'x\'\' of a [[normed vector space]]\n
||\'\'x\'\'+\'\'y\'\'|| ≤ ||\'\'x\'\'|| + ||\'\'y\'\'||\n\n

\n
[[addition|summation]]\n sum over ... from ... to ... of\n [[arithmetic]]\n
\'\'k\'\'=1\'\'n\'\' \'\'a\'\'\'\'k\'\' means: \'\'a\'\'1 + \'\'a\'\'2 + ... + \'\'a\'\'\'\'n\'\'\n
\'\'k\'\'=14 \'\'k\'\'2 = 12 + 22 + 32 + 42 = 1 + 4 + 9 + 16 = 30\n\n

\n
[[multiplication|product]]\n product over ... from ... to ... of\n [[arithmetic]]\n
\'\'k\'\'=1\'\'n\'\' \'\'a\'\'\'\'k\'\' means: \'\'a\'\'1\'\'a\'\'2···\'\'a\'\'\'\'n\'\'\n
\'\'k\'\'=14 (\'\'k\'\' + 2) = (1  + 2)(2 + 2)(3 + 2)(4 + 2) = 3 × 4 × 5 × 6 = 360\n\n

\n
[[integration]]\n integral from ... to ... of ... with respect to\n [[calculus]]\n
\'\'a\'\'\'\'b\'\' \'\'f\'\'(\'\'x\'\') d\'\'x\'\' means: the signed [[area]] between the \'\'x\'\'-axis and the [[graph (functions)|graph]] of the [[Fungsi (matematik)|function]] \'\'f\'\' between x = \'\'a\'\' and x = \'\'b\'\'\n
0\'\'b\'\' x2 d\'\'x\'\' = \'\'b\'\'3/3; ∫\'\'x\'\'2 d\'\'x\'\' = \'\'x\'\'3/3\n\n

\'\'f\'\' \'

\n
[[derivative]]\n derivative of f; f prime\n [[calculus]]\n
\'\'f\'\' \'(\'\'x\'\') is the derivative of the function \'\'f\'\' at the point \'\'x\'\', i.e., the [[slope]] of the [[tangent]] there\n
If \'\'f\'\'(\'\'x\'\') = \'\'x\'\'2, then \'\'f\'\' \'(\'\'x\'\') = 2\'\'x\'\' and \'\'f\'\' \''(\'\'x\'\') = 2\n\n

\n
[[gradient]]\n [[del]], [[nabla]], [[gradient]] of\n [[calculus]]\n
∇\'\'f\'\' (x1, …, x\'\'n\'\') is the vector of partial derivatives (\'\'df\'\' / \'\'dx\'\'1, …, \'\'df\'\' / \'\'dx\'\'\'\'n\'\')\n
If \'\'f\'\' (\'\'x\'\',\'\'y\'\',\'\'z\'\') = 3\'\'xy\'\' + \'\'z\'\'² then ∇\'\'f\'\' = (3\'\'y\'\', 3\'\'x\'\', 2\'\'z\'\')
\nA transparent image for text is: Image:Del.gif ([[Image:Del.gif]]).\n\n

\n
[[Partial derivative|partial]]\n partial derivative of\n [[calculus]]\n
With \'\'f\'\' (x1, …, x\'\'n\'\'), ∂f/∂xi is the derivative of \'\'f\'\' with respect to xi, with all other variables kept constant.\n
If \'\'f\'\'(x,y) = x2y, then ∂\'\'f\'\'/∂x = 2xy\n\n

\n
[[perpendicular]]\n is perpendicular to\n [[orthogonality]]\n
\'\'x\'\' ⊥ \'\'y\'\' means: \'\'x\'\' is perpendicular to \'\'y\'\'; or more generally \'\'x\'\' is orthogonal to \'\'y\'\'.\n
\n\n

\n
[[bottom element]]\n the bottom element\n [[Lattice (order)|lattice theory]]\n
\'\'x\'\' = ⊥ means: \'\'x\'\' is the smallest element. \n
\n\n
\n \'\'insert more (suggestions are the inequality symbols); some symbols are used in examples before they are defined\'\'\n \n \n
\n
\n\n
\n\nIf some of these symbols are used in a Wikipedia article that is intended for beginners, it may be a good idea to include a statement like the following, (below the definition of the subject), in order to reach a broader audience:\n:\'\'This article uses [[table of mathematical symbols|mathematical symbols]].\'\'\n\nThe article [[Wikipédia:Cara ngédit kaca]] contains information about how to produce these math symbols in Wikipedia articles.\n\n==Tumbu kaluar==\n* Jeff Miller: \'\'Earliest Uses of Various Mathematical Symbols, http://members.aol.com/jeff570/mathsym.html\n* TCAEP - Institute of Physics, http://www.tcaep.co.uk/science/symbols/maths.htm\n\n[[de:Tabelle mit mathematischen Symbolen]] [[en:Table of mathematical symbols]] [[ja:数学記号の表]] [[sv:Tabell över matematiska symboler]]','',13,'Budhi','20041224213316','',0,0,1,0,0.861188137374,'20041224213316','79958775786683'); INSERT INTO cur VALUES (1303,0,'Generalized_mean','Lamun \'\'t\'\' ngarupakeun [[real number|wilangan riil]] nu teu mibanda nilai nol, we can define the \'\'\'generalized mean with exponent \'\'t\'\'\'\'\' of the positive real numbers \'\'a\'\'1,...,\'\'a\'\'\'\'n\'\' as\n\n:\nM(t) = \\left( \\frac{1}{n} \\sum_{i=1}^n a_{i}^t \\right) ^ {-t}\n\n\nThe case \'\'t\'\' = 1 yields the [[arithmetic mean]] and the case \'\'t\'\' = −1 yields the [[harmonic mean]]. As \'\'t\'\' approaches 0, the [[limit]] of M(\'\'t\'\') is the [[geometric mean]] of the given numbers, and so it makes sense to \'\'define\'\' M(0) to be the geometric mean. Furthermore, as \'\'t\'\' approaches ∞, M(\'\'t\'\') approaches the maximum of the given numbers, and as \'\'t\'\' approaches −∞, M(\'\'t\'\') approaches the minimum of the given numbers.\n\nIn general, if −∞ ≤ \'\'s\'\' < \'\'t\'\' ≤ ∞, then\n\n:M(s)\\leq M(t)\n\nand the two means are equal if and only if \'\'a\'\'1 = \'\'a\'\'2 = ... = \'\'a\'\'\'\'n\'\'. Furthermore, if \'\'a\'\' is a positive real number, then the generalized mean with exponent \'\'t\'\' of the numbers \'\'aa\'\'1,..., \'\'aa\'\'\'\'n\'\' is equal to \'\'a\'\' times the generalized mean of the numbers \'\'a\'\'1,..., \'\'a\'\'\'\'n\'\'.\n\nThis could be generalized further to the [[generalised f-mean|generalized f-mean]]: \n\n: M = f^{-1}\\left({\\frac{1}{n}\\sum_{i=1}^n{f(x_i)}}\\right) \n\nand again a suitable choice of an invertible f(\'\'x\'\') will give the arithmetic mean with f(\'\'x\'\') = \'\'x\'\', the geometric mean with f(\'\'x\'\') = log(\'\'x\'\'), the harmonic mean with f(\'\'x\'\') = 1/\'\'x\'\', and the generalized mean with exponent \'\'t\'\' with f(\'\'x\'\') = \'\'x\'\'\'\'t\'\'. But other functions could be used, such as f(\'\'x\'\') = e\'\'x\'\'.\n\n==Tempo oge==\n\n[[average]]\n\n[[pl:%C5%9Arednia uog%C3%B3lniona]]','',13,'Budhi','20041225232417','',0,0,1,0,0.573678890045,'20041225232417','79958774767582'); INSERT INTO cur VALUES (1304,0,'Sample_mean','#REDIRECT [[arithmetic mean]]','',13,'Budhi','20040820055357','',0,1,0,1,0.9003509562,'20040820055357','79959179944642'); INSERT INTO cur VALUES (1305,0,'Data_set','#REDIRECT [[Susunan data]]\n','Data set dipindahkeun ka Susunan data',13,'Budhi','20040820060057','',0,1,0,1,0.216269616239024,'20040820060057','79959179939942'); INSERT INTO cur VALUES (1306,0,'Set','[[Category:Mathematics]][[Category:Set theory]]\n:\'\'This article is about sets in [[mathematics]]. For other meanings, see [[Set (disambiguation)]].\'\'\n\nThe concept of \'\'\'sets\'\'\', first set forth rigorously by the mathematician [[Georg Cantor]] who in the nineteenth century developed [[set theory]], one of the central unifying ideas of [[mathematics]], has been since the late twentieth century included in the mathematics curriculum at the elementary school level. Loosely defined, a set is a collection of objects called [[element]]s, for example, a flock of birds, a school of fish, a murder of crows, etc.\n\n==Ways of describing a set==\nA set may be described by words, for example, \"the counties in the San Luis Valley of Colorado\" or \"all even numbers between 1 and 191\". Another way to describe a set is by listing the elements, {Alamosa, Conejos, Costilla, Mineral, Rio Grande, Saguache} or {2, 4, 6,..., 188, 190}. When a list is long, it is customary [[mathematical notation|notation]] to list the first three elements followed by three dots then the last two elements. In customary mathematical notation sets are named using [[uppercase letter]]s; elements of sets are denoted by [[lowercase letter]]s. For example, x \\in A says, in mathematical notation, that the element x belongs to the set A. See more on terminology and notation below. \n\n==Definitions of sets==\nIn mathematics, a set is a collection of elements such that two sets are equal if, and only if, every element of one is also an element of the other. It does not matter in what order, or how many times, the elements are listed in the collection.\n\nBy contrast, a collection of elements in which multiplicity but not order is relevant is called a [[multiset]]. Other related concepts are described below.\n\nIf a set has \'\'n\'\' elements, where \'\'n\'\' is a [[natural number]] (possibly 0), then the set is said to be a \'\'\'finite set\'\'\' with [[cardinality]] \'\'n\'\'.\n\n\'\'\'Infinite sets\'\'\'\n\nInfinite sets are sets which do not have \'\'n\'\' elements where \'\'n\'\' is a [[natural number]]. Infinite sets have an infinite number of elements, giving them a special property. The special property of infinite sets which makes them inherently different from finite sets is that you can remove \'\'n\'\' elements from infinite sets and the set that remains will have the same [[cardinality]] as before. For instance if you remove the numbers 1 to 1 million from the set of the [[natural number]]s the set that remains will have the same [[cardinality]] as the set of the [[natural number]]s. This is obviously not the case for finite sets, for if you remove \'\'n\'\' elements from a finite set the cardinality of that set will be reduced by \'\'n\'\'.\n\nIntuitively one might think that the [[cardinality|cardinalities]] of all infinite sets are equal. However, this is not the case. See below in this article, [[Cantor\'s theorem]] and [[Cantor\'s diagonal argument]] for more information on this topic.\n\nAlso, for a discussion of the properties and axioms concerning the construction of sets, see the articles on [[naive set theory|naïve set theory]] and [[axiomatic set theory]]. Here we give only a brief overview of the concept.\n\n==Introduction==\n\nSets are one of the basic concepts of [[mathematics]].\nA set is, more or less, just a collection of entities, called its \'\'\'elements\'\'\'. Standard notation uses braces around the list of elements, as in:\n\n: {red, green, blue}\n: {red, red, blue, red, green, red, red, green, red, red, blue}\n: {x : x is an additive primary color}\n\nAll three lines above denote the same set.\nAs you see, it is possible to describe one and the same set in different ways: either by listing all its elements (best for small finite sets) or by giving a defining property of all its elements.\n\n==Set terminology==\n\n
[[Image:Mathematical_set.png]]
\n\nIf A and B are sets and every x in A is also contained in B, then A is said to be a [[subset]] of B, denoted A \\subseteq B. Note that this includes the case where \'\'A\'\'=\'\'B\'\'. If at least one element in B is not also in A, A is called a \'\'[[proper subset]]\'\' of B, denoted A \\subset B. Every set has as subsets itself, called the \'\'improper subset\'\', and the [[empty set]] {} or \\emptyset. The fact that an element x belongs to the set A is denoted x \\in A.\n\nThe \'\'[[union (set theory)|union]]\'\' of a collection of sets S = {S_1, S_2, S_3, \\cdots} is the set of all elements contained in at least one of the sets S_1, S_2, S_3, \\cdots\n\nThe \'\'[[intersection (set theory)|intersection]]\'\' of a collection of sets T = {T_1, T_2, T_3, \\cdots} is the set of all elements contained in all of the sets.\n\nThese unions and intersections are denoted\n\n:S_1 \\cup S_2 \\cup S_3 \\cup \\cdots\n\nand\n\n:T_1 \\cap T_2 \\cap T_3 \\cap \\cdots\n\nrespectively.\n\nThe set of all subsets of X is called its [[power set]] and is denoted 2^X or P(X).\nThis power set is a [[Boolean algebra]] under the operations of union and intersection.\n\nIf there is a [[bijection|one-to-one correspondence]] between the elements of two sets, the two sets are said to have the \'\'same cardinality\'\'. [[Cantor\'s theorem|Cantor’s theorem.]] states that the cardinality of the power set of a set A is strictly greater than the cardinality of A itself. \n\nThe ‘number of elements’ in a certain set is called the [[cardinal number]] of the set and denoted |A| for a set A (for a finite set this is an ordinary number, for an [[infinite set]] it differentiates between different \"degrees of infiniteness\", named \\aleph_0 ([[aleph]] zero), \\aleph_1, \\aleph_2 ...).\n\nThe set of [[Fungsi (matematik)|functions]] from a set \'\'A\'\' to a set \'\'B\'\' is sometimes denoted by \'\'B\'\'\'\'A\'\'. It is a generalisation of the power set in which 2 could be regarded as the set {0,1} (see [[natural number]]).\n\nThe \'\'\'[[cartesian product]]\'\'\' of two sets \'\'A\'\' and \'\'B\'\' is the set of [[ordered pair]]s\n: A \\times B= \\{(a,b) : a \\in A \\mbox{ and } b \\in B\\}\n\nThe \'\'\'sum\'\'\' or \'\'\'disjoint union\'\'\' of two sets \'\'A\'\' and \'\'B\'\' is the set\n: \'\'A\'\'+\'\'B\'\' = \'\'A\'\'×{0} \\cup \'\'B\'\'×{1}.\n\n==Examples of sets of numbers==\n\nNote: In this section, \'\'a\'\', \'\'b\'\', and \'\'c\'\' are [[natural number]]s, and r and s are [[real number]]s.\n# [[Natural number]]s are used for counting. A [[blackboard bold]] capital \'\'N\'\' (\\mathbb{N}) often represents this set.\n# [[Integer]]s appear as solutions for x in equations like x + a = b. A blackboard bold capital \'\'Z\'\' (\\mathbb{Z}) often represents this set (for the German \'\'Zahlen\'\', meaning \'\'numbers\'\', because I is used for the set of imaginary numbers).\n# [[Rational number]]s appear as solutions to equations like a + bx = c. A blackboard bold capital \'\'Q\'\' (\\mathbb{Q}) often represents this set (for \'\'quotient\'\', because R is used for the set of real numbers).\n# [[Algebraic number]]s appear as solutions to [[polynomial]] equations (with integer coefficients) and may involve [[radical]]s and certain other [[irrational number]]s. A blackboard bold capital \'\'A\'\' (\\mathbb{A}) or a \'\'Q\'\' with an overline often represents this set.\n# [[Real number]]s include the algebraic numbers as well as the [[transcendental number]]s, which can’t appear as solutions to polynomial equations with rational coefficents. A blackboard bold capital \'\'R\'\' (\\mathbb{R}) often represents this set.\n# [[Imaginary numbers]] appear as solutions to equations such as x2 + r = 0 where r > 0.\n# [[Complex number]]s are the sum of a real and an imaginary number: r + si. Here both r and s can equal zero; thus, the set of real numbers and the set of imaginary numbers are subsets of the set of complex numbers. A blackboard bold capital \'\'C\'\' (\\mathbb{C}) often represents this set.\n\n==Special remarks about terminology==\n\nCare must be taken with verbal descriptions of sets. One can describe in words a set whose existence is paradoxical. If one assumes such a set exists, an apparent [[paradox]] or [[antinomy]] may occur. [[Axiomatic set theory]] was created to avoid these problems.\n\nFor example, suppose we call a set \'\'well-behaved\'\' if it doesn\'t contain itself as an element. Now consider the set S of all well-behaved sets. Is S itself well-behaved? There is no consistent answer; this is [[Russell\'s paradox|Russell’s paradox]].\n\nIn axiomatic set theory, the set S is either not allowed (in the case of the Zermelo-Fränkel axioms, whether or not the [[axiom of regularity]] is included) or is considered to be a proper class (in the case of the von Neumann-Bernays-Gödel axioms), and we have no paradox.\n\n==Konsep pakait==\n\nDina matematik, watesan umum keur indeks koleksi elemen nyaeta \'\'[[family (mathematics)|family]]\'\'. Conto kulawarga nu hade nyaeta [[sequence]]. \n\nDina [[computer science]]:\n* [[list]] nyaeta struktur data pakait raket jeung sekuen sarta ilahar dipake keur nembongkeun susunan;\n* [[Bag (mathematics)|bag]] ngarupakeun multisusun \'\'terhingga\'\'.\n\n\n[[bg:Множество]]\n[[de:Menge (Mathematik)]]\n[[es:Conjunto]]\n[[eo:Aro]]\n[[fr:Ensemble]]\n[[nl:Verzameling]]\n[[ja:集合]]\n[[pl:Zbi%C3%B3r]]\n[[pt:Conjunto]]\n[[ru:Множество]]\n[[sl:množica]]\n[[fi:Joukko]]\n[[sv:Mängd]]\n[[uk:Множина]]\n[[zh:集合]]','/* Set terminology */',13,'Budhi','20041224213722','',0,0,1,0,0.636886786035,'20041224213722','79958775786277'); INSERT INTO cur VALUES (1307,0,'Subjék_panalungtikan','Dina [[biostatistik]] atawa [[statistik prikologis]], organisme naon baé (sato atawa tutuwuhan) nu rék ditengetan atawa nu geus ditengetan téh kuurang disebutna \'\'\'subjék panalungtikan\'\'\' (Ing. \'\'research subject\'\'). Dina [[panalungtikan survéy]] jeung [[jajal pamanggih]], subjékna mindeng disebut salaku \'\'réspondén\'\'.\n\nDina panalungtikan nu maké subjék manusa, hiji jejer nu kalintang penting nyaéta ayana [[Informed consent|informed consent]] and human subject protection. Aya loba tungtunan, nu sadayana pikeun mastikeun yén subjék kalawan jéntré geus dipasihan terang kumaha jadina éta panalungtikan, partisipasina, akibat-akibat nu bisa kajadian, yén aranjeunna tiasa kaluar iraha baé tanpa konsékuénsi naon-naon, ka saha mun rek nanya, jsb. Sadaya panalungtikan nu ngajeujeutkeun subjék manusa kudu ngawengku sababaraha aspék panyalindungan subjék manusa.\n\n==Tumbu kaluar==\n\n* [http://gsociology.icaap.org/methods Free resources in social research methods] has a link to resources for human subject protection. \n\nBalik ka [[statistik]] -- [[modél statistik]] -- [[ngarencanakeun panalungtikan statistik]]','',3,'Kandar','20041229073009','',0,0,0,0,0.182251952208,'20041229073051','79958770926990'); INSERT INTO cur VALUES (1308,0,'Data_vector','#REDIRECT [[data point]]','',13,'Budhi','20040820060456','',0,1,0,1,0.28886763765,'20040820060542','79959179939543'); INSERT INTO cur VALUES (1309,0,'Data_point','Dina [[statistik]], \'\'\'titik data\'\'\' is a single \'\'typed\'\' [[measurement]]. Here \'\'type\'\' is used in a way compatible with [[datatype]] in [[computing]]; so that the type of measurement can specify whether the measurement results in a [[Boolean]] value from {yes, no}, an [[integer]] or [[real number]], or some [[Vector (spatial)|vector]] or [[array]]. The implication of \'\'point\'\' is therefore that the data may be plotted in a graphic display, but in many cases the data are processed numerically before that is done.\n\n==See also==\n\n*[[Datum]]\n*[[Data]]\n*[[Data processing]]','',13,'Budhi','20040901064304','',0,0,0,0,0.826966789005,'20041226005019','79959098935695'); INSERT INTO cur VALUES (1310,0,'Decision_theory','\'\'\'Teori kaputusan\'\'\' nyaeta widang antar disiplin elmu, pakait sarta mindeng dipake ku praktisi dina widang [[matematik]], [[statistik]], [[economics|ekonomi]], [[philosophy|filosofi]], [[management|manajemen]] sarta [[psychology|psikologi]]. Teori ieu museur kana kaputusan optimal nu bakal dipake dina kaayaan nu husus.\n\n==Normative and descriptive decision theory==\n\nMost of decision theory is \'\'normative\'\' or \'\'prescriptive\'\', i.e. it is concerned with identifying the best decision to take, assuming an ideal decision taker who is fully informed, able to compute with perfect accuracy, and fully rational. However, since it is obvious that people do not typically behave in optimal ways, there is also a related area of study, which is a \'\'descriptive\'\' or \'\'positive\'\' discipline, attempting to describe what people will actually do. Since the normative, optimal decision often creates hypotheses for testing against actual behaviour, the two fields are closely linked. Furthermore it is possible to relax the assumptions of perfect information, rationality and so forth in various ways, and produce a series of different prescriptions or predictions about behaviour, allowing for further tests of the kind of decision-making that occurs in practice.\n\n==What kinds of decision need a theory?==\n\nDecision theory is only relevant in decisions that are difficult for some reason. A few types of decision have attracted particular attention:\n*riskless choice between incommensurable commodities\n*choice under uncertainty\n*intertemporal choice\n*social decisions\n\n===Choice between incommensurable commmodities===\n\nThis area is concerned with the decision whether to have, say, one ton of guns and 3 tons of butter, or 2 tons of guns and 1 ton of butter. This is the classic subject of study of [[microeconomics]] and is rarely considered under the heading of decision theory, but such choices are often in fact part of the issues that are considered within decision theory.\n\n===Choice under uncertainty=== \n\nThis area represents the heartland of decision theory. [[Daniel Bernoulli]] stated that, when faced with a number of actions each of which could give rise to more than one possible outcome with different probabilities, the rational procedure is to identify all possible outcomes, determine their values (positive or negative) and the probabilities that they will result from each course of action, and multiply the two to give an \'\'expected value\'\'. The action to be chosen should be the one that gives rise to the highest total expected value. In reality people do not behave like this, at least if \"value\" is taken to mean \"objective financial value\" - otherwise no-one would either gamble or take out insurance. Within behavioural decision theory, this has led to various dilutions of the expected value theory; for example, objective probabilities can be replaced by subjective estimates, and objective values by subjective utilities, giving rise to the [[subjectively expected utility]] or SEU theory. The [[prospect theory]] of [[Daniel Kahneman]] and [[Amos Tversky]] is another alternative to the expected value model within behavioural decision theory.\n\n[[Pascal\'s Wager|Pascal\'s wager]] is a classic example of a choice under uncertainty. The uncertainty, according to [[Blaise Pascal|Pascal]], is whether or not God exists. And the personal belief or non-belief in God is the choice to be made.\n\n===Intertemporal choice===\n\nThis area is concerned with the kind of choice where different actions lead to outcomes that are realised at different points in time. If I receive a windfall of several thousand dollars, I could spend it on an expensive holiday, giving me immediate pleasure, or I could invest it in a pension scheme, giving me an income at some time in the future. What is the optimal thing to do? The answer depends partly on factors such as the expected rates of interest and inflation, my life expectancy, and my confidence in the pensions industry. However even with all those factors taken into account, human behaviour again deviates greatly from the predictions of prescriptive decision theory, leading to alternative models in which, for example, objective interest rates are replaced by subjective discount rates.\n\n===Social decisions===\n\nSome decisions are difficult because of the need to take into account how other people in the situation will respond to the decision that is taken. The analysis of such social decisions is the business of [[game theory]], and is not normally considered part of decision theory, though it is closely related.\n\n==Complex decisions==\n\nOther areas of decision theory are concerned with decisions that are difficult simply because of their complexity, or the complexity of the organisation that has to take them. In such cases the issue is not the deviation between real and optimal behaviour, but the difficulty of determining the optimal behaviour in the first place.\n\n==References==\n\n* Robert Clemen. \'\'Making Hard Decisions: An Introduction to Decision Analysis\'\', 2nd edition. Belmont CA: Duxbury Press, 1996. \'\'(covers normative decision theory)\'\'\n* D.W. North. \"A tutorial introduction to decision theory\". \'\'IEEE Trans. Systems Science and Cybernetics\'\', 4(3), 1968. Reprinted in Pearl & Shafer. \'\'(also about normative decision theory)\'\'\n* Glenn Shafer and Judea Pearl, editors. \'\'Readings in uncertain reasoning\'\'. Morgan Kaufmann, San Mateo, CA, 1990.\n\n[[Category:Social philosophy]]','',13,'Budhi','20050218051748','',0,0,0,0,0.134376485895,'20050218051748','79949781948251'); INSERT INTO cur VALUES (1311,0,'Histogram','Dina [[statistik]], \'\'\'histogram\'\'\' nyaeta [[graphical display|tampilan grafis]] tina tabulasi frekuensi.\nDina hal ieu,\nhistogram nyaeta versi grafis tina tabel nu nembongkeun babandingan kasus kana sababaraha atawa lobana kategori husus. Kategori ieu ilahar mangrupa hal nu husus saperti taya interval nu tumpang tindih dina sababaraha variabel.\n\nAya dua cara keur nembongkeun tabel nu sarua,\nsarta dua rupa histogram saperti ditembongkeun di handap ieu. \nHiji nemobongkeun jumlah kasus per satuan interval,\nmangka legana wewengkon di handapeun kurva sarua jeung jumlah sakabeh kasus.\nNu sejenna nembongkeun jumlah kasus per satuan interval dibagi ku total jumlah kasus, mangka legana wewengkon di andapeun kurva sarua jeung 1.\n\nAs an example we consider data collected by the U.S. Census Bureau on time to travel to work (2000 census, [http://www.census.gov/prod/2004pubs/c2kbr-33.pdf], Table 5).\nThe census found that there were 124 million people who work outside of their homes. \nPeople were asked how long it takes them to get to work,\nand their responses were divided into categories:\nless than 5 minutes, more than 5 minutes and less than 10, more than 10 minutes and less than 15, and so on.\nThis table shows the numbers of people per category in thousands,\nso the 4,180 means 4,180,000.\n\n
\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Interval Width No. in interval(No. in interval)/width
0 5 4,180 836
5 5 13,687 2,737
10 5 18,618 3,723
15 5 19,634 3,926
20 5 17,981 3,596
25 5 7,190 1,438
30 5 16,369 3,273
35 5 3,212 642
40 5 4,122 824
45 15 9,200 613
60 30 6,461 215
90 60 3,435 57
\n
\n\nThe data shown in the preceding table are displayed graphically by the following diagram.\nThe area of each bar is equal to the total number of people in that category,\nso the total area of all bars is equal to the total number of people in the survey (124 million).\n\nAn interesting feature of this diagram is the spike in the 30 to 35 minutes category.\nIt seems likely that this is an artifact:\nhalf an hour is a common unit of informal time measurement,\nso people whose travel times were perhaps a little less than or a little greater than 30 minutes might be inclined to answer \"30 minutes\".\n\n
\n
[[Image:Travel_time_histogram_total_n.png]]\n\nHistogram of travel time, US 2000 census. Area under the curve equals the total number of cases.
\n\nNow the same data are shown in a slightly different fashion.\nThe area of each bar is equal to the proportion of people, of all the people in the survey, who fall into that category.\nSo the total area of all the bars is equal to 1.\n\n
\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Interval Width No. in interval(No. in interval)/(total no.)/width
0 5 4,180 0.0067
5 5 13,687 0.0220
10 5 18,618 0.0300
15 5 19,634 0.0316
20 5 17,981 0.0289
25 5 7,190 0.0115
30 5 16,369 0.0263
35 5 3,212 0.0051
40 5 4,122 0.0066
45 15 9,200 0.0049
60 30 6,461 0.0017
90 60 3,435 0.0004
\n
\n\nThe preceding table is displayed graphically by the following diagram.\nThe second figure differs from the first only in the vertical scale.\nWhich figure should be used depends on the purpose of the histogram;\nif the absolute numbers are important, then the first form is more useful,\nand the second form is more useful if proportions are important.\n\n
\n
[[Image:Travel_time_histogram_total_1.png]]\n\nHistogram of travel time, US 2000 census. Area under the curve equals 1.
\n\n== Tumbu kaluar ==\n\n* [http://www.census.gov/population/www/socdemo/journey.html Journey To Work and Place Of Work] \'\'(location of census document cited in example)\'\'\n\n[[Category:Statistics]]\n\n[[de:Histogramm]]\n[[pl:Histogram]]','',13,'Budhi','20041224150519','',0,0,1,0,0.019454892734,'20041224150519','79958775849480'); INSERT INTO cur VALUES (1312,6,'Travel_time_histogram_total_n.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040820061519','',0,0,0,1,0.842772574017544,'20041224150528','79959179938480'); INSERT INTO cur VALUES (1313,6,'Travel_time_histogram_total_1.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040820061637','',0,0,0,1,0.565054052104292,'20041224150528','79959179938362'); INSERT INTO cur VALUES (1314,0,'Kalibrasi_(statistik)','\'\'\'Kalibrasi\'\'\' dina [[statistik]] nyaéta sabalikna tina prosés [[régrési liniér|régrési]]. \'\'Masalah kalibrasi\'\' (Ing. \'\'calibration problem\'\') nyaéta digunakeunana data nu dipikanyaho dina hubungan observasi antara variabel terikat jeung variabel bebas keur nyieun estimasi nilai variabel bebas sejenna tina observasi anyar dina variabel terikat. \n\nSalah sahiji contona nyaeta dina nangtukeun umur, saperti make buleudan [[tree|kai]] keur [[dendrochronology|dendrokronologi]] atawa [[carbon-14|karbon-14]] keur [[radiometric dating|nangtukeun umur make radiometrik]]. Panalungtikan ieu [[causality|dumasar]] kana umur tina obyek nu ditangtukeun umurna, tinimbang hal sejen, sarta dipake dina metoda keur estimasi umur dumasar kana observasi anyar.\n\nMasalah dina make ieu kalibrasi nyaeta perlu model keur ngahubungkeun umur nu diobservasi keur ngaminimalkeun kasalahan dina observasi atawa ngaminimalkeun kasalahan dina nangtukeun umur. Dua cara pendekatan bakal mere hasil nu beda, sarta ieu beda bakal ngagedean lamun make dipake keur [[extrapolation|ekstrapolasi]] dina sababaraha jauh tina hasil nu dipikanyaho.\n\n==Tempo ogé==\n*[[Kalibrasi]]','/* Tempo ogé */',13,'Budhi','20041229230413','',0,0,1,0,0.062356970768,'20041229230413','79958770769586'); INSERT INTO cur VALUES (1315,0,'Consistency_(statistics)','Dina [[statistik]], \'\'\'estimator konsisten\'\'\' nyaeta [[estimator]] nu [[convergence in probability|converges in probability]] kana lobana nu geus diestimasi salaku ukuran sampel nu tumuwuh.\n\nEstimator \'\'t\'\'\'\'n\'\' (dimana \'\'n\'\' ngarupakeun ukuran sampel) ngarupakeun estimator konsisten keur [[parameter]] θ lamun jeung ngan lamun, keur sakabeh ε > 0, teu nempo sakumaha leutikna, urang ngabogaan\n\n:\n\\lim_{n\\to\\infty}{\\rm Prob}\\left\\{\n\\left|\nt_n-\\theta\\right|<\\epsilon\n\\right\\}=1.\n','',13,'Budhi','20040901222956','',0,0,0,0,0.890607019835,'20040901222956','79959098777043'); INSERT INTO cur VALUES (1316,0,'Rancangan_percobaan','[[statistik|Statistikawan]] nu ngamimitian mikirkeun metoda keur \'\'\'desain percobaan\'\'\' nyaeta [[Ronald Fisher|Sir Ronald A. Fisher]]. Anjeunna ngajelaskeun kumaha tes [[hypothesis]] hiji wanoja ngabedakan mana nu mimiti diasupkeun kana cangkir antara susu jeung gula. Katempona siga hal nu sapele, cara anjeunna keur ngagambarkeun ide penting dina desain percobaan.\n\nDesain [[experiment|percobaan]] diwangun dumasar kana [[analisa varian]], kumpulan model nu varianna diobservasi dibagi-bagi kana sababaraha komponen, dumasar kana faktor nu beda saperti diestimasi jeung/atawa di tes. \n\nPangwangunan teori [[linear model]] nuturkeun sarta ngaleuwihan kasus nu ditalungktik samemehna. Kiwari, uraian teori nu leuwih jentre dina [[Abstract Algebra|abstract algebra]] sarta [[combinatorics]].\n\nTempo oge: [[ngarencanakeun panalungtikan statistik]] – [[survey sampling]] – [[independent variable]] – [[dependent variable]]\n\n==Tempo ogé==\n* [[statistik]]\n* [[tiori statistik]]\n\n==Tumbu kaluar==\n*[http://www-groups.dcs.st-andrews.ac.uk/~history/Mathematicians/Fisher.html Biografi R. A. Fisher]\n\n[[Category:Métode ilmiah]]','',3,'Kandar','20050208063143','',0,0,0,0,0.521963807066,'20050208063143','79949791936856'); INSERT INTO cur VALUES (1317,0,'Modél_statistik','\'\'\'Model statistik\'\'\' dipake dina [[applied statistics|statistik terapan]]. Tilu notasi dasar cukup keur ngajelaskeun sakabeh model statistik. \n# Urang milih [[statistical unit|satuan statistik]] keur kaperluan observasi langsung. Sababaraha observasi dina satuan waktu nu sarua disebutna [[longitudinal research|panalungtikan longitudinal]]. Observasi tina sababaraha [[statistical attributes|sipat statistik]] ngarupan cara ilahar keur nalungtik hubungan antara sipat hiji satuan.\n# Urang mokuskeun kana [[statistical population|populasi statistik]] satuan (atawa [[set|susunan]]) nu sarua tinimbang unggal satuan statistik. [[Survey sampling]] salah sahiji conto tina tipe ieu pamakean.\n# Urang museurkeun kana [[statistical assembly]] numana fungsi bagean susunan tina [[statistical unit|satuan statistik]]. [[Physiology|Psikologi]] salah sahiji conto nu nalungtik rada tina susunan satuan. Model nu ilahar dipake dina tipe ieu panalungtikan nyaeta [[stimulus-response model|model respon-rangsangan]].','',13,'Budhi','20040906225244','',0,0,0,0,0.534042344212,'20041229073051','79959093774755'); INSERT INTO cur VALUES (1318,0,'Baseball_statistics','Bagean nu katempo dina kaulinan [[baseball]] nyaeta ngumpulkeun [[statistik]] terus-terusan keur nangtukeun kasuksesan pamaen. Dimimitian ku [[Henry Chadwick]] dina [[19th century]] nu ngarancang konsep [[batting average]] dumasar kana panglaman dina [[cricket (sport)|cricket]]. Loba watesan nu dipake keur kaulinan [[softball]]. Umumna [[abbreviation]] statistik nu dipake dijelaskeun di handap ieu:\n\n==Hitting statistics==\n* 1B - [[Single (baseball)|Single]]\n* 2B - [[Double (baseball)|Double]]\n* 3B - [[Triple (baseball)|Triple]]\n* AB - [[At bat]]\n* BA - [[Batting average]]\n* BB - [[Base on balls]] (also called a \"walk\")\n* CS - [[Caught stealing]]\n* EBH - [[Extra base hit]] (Sometimes EB or XBH)\n* FC - [[Fielder\'s choice]]\n* G - [[Games played]]\n* G/F - [[Ground ball fly ball ratio]]\n* GIDP - [[Double play|Ground into Double play]]\n* H - [[Hit (baseball statistics)|Hit]]\n* HBP - [[Hit by pitch]]\n* HR - [[Home run]]\n* OBP - [[On base percentage]]\n* OPS - [[On-base plus slugging]]\n* PA - [[Plate appearance]]\n* R - [[Run (baseball statistics)|Run]]\n* RBI - [[Run batted in]]\n* SB - [[Stolen base]]\n* SF - [[Sacrifice fly]]\n* SH - [[Sacrifice hit]]\n* SLG - [[Slugging percentage]]\n* SO - [[Strike out]] (also abbreviated \'\'K\'\')\n* TB - [[Total bases]]\n\n==Pitching statistics==\n* AVG - [[Opponents batting average]]\n* BB - [[Base on balls]] (also called a \"walk\")\n* BS - [[Blown save]]\n* CG - [[Complete game]]\n* ER - [[Earned run]]\n* ERA - [[Earned run average]]\n* GIR - [[Games in relief]]\n* GF - [[Games finished]]\n* GP - [[Games pitched]]\n* G/F - [[Ground ball fly ball ratio]]\n* GS - [[Games started]]\n* H/9 - [[Hits per nine innings]]\n* HLD - [[Hold (baseball statistics)|Hold]]\n* IBB - [[Intentional base on balls]]\n* IRA - [[Inherited runs allowed]]\n* IP - [[Innings pitched]]\n* R/9 - [[Runs per nine innings]]\n* SHO - [[Shutout]]\n* SO - [[Strikeout]] (also abbreviated \'\'K\'\')\n* SO/9 - [[Strikeouts per nine innings]]\n* SV - [[Save (baseball statistics)|Save]]\n* TBF - [[Total batters faced]]\n* W - [[Win (baseball statistics)|Win]] (also related: \'\'\'winning percentage\'\'\')\n* L - [[Win (baseball statistics)|Loss]]\n* W+S - [[Relief wins plus saves]]\n* WHIP - [[Walks plus hits per inning pitched]]\n\n==Fielding statistics==\n* A - [[Assist (baseball statistics)|Assist]]\n* DP - [[Double play]]\n* E - [[Error (baseball statistics)|Error]]\n* FP - [[Fielding percentage]]\n* PB - [[Passed ball]]\n* PO - [[Putout]]\n* TC - [[Total chances]]\n* TP - [[Triple play]]\n* WP - [[Wild pitch]]\n\n==Tempo oge==\n* [[Triple crown (baseball)|Triple Crown in Major League Baseball]]\n* [[MLB Most Valuable Player Award]] winners\n* [[Cy Young Award]] winners\n* [[MLB Rookie of the Year Award]] winners\n* [[Gold Glove|Gold Glove Award]] winners\n\n==Watesan sejen==\n* [[Ball (baseball statistics)|Ball]]\n* [[Strike (baseball statistics)|Strike]]\n* [[Strike zone]]\n\n==Rujukan==\n*[[sabermetrics]]\n*[http://www.mlb.com/NASApp/mlb/mlb/baseball_basics/mlb_basics_official_scorer.jsp Official Baseball Rules, Section 10 - Scoring] from http://www.mlb.com\n*Find statistics for all of major league history at http://www.Baseball-Reference.com/\n\n[[Category:Baseball statistics]]','',13,'Budhi','20040904231853','',0,0,0,0,0.824580427178,'20040904231853','79959095768146'); INSERT INTO cur VALUES (1319,0,'Binary_classification','\'\'\'Binary classification\'\'\' is the task of classifying the members of a given [[set]] of objects into two groups on the basis of whether they have some property or not. Some typical binary classification tasks are \n\n* medical testing to determine if a patient has certain disease or not (the classification property is the disease)\n* quality control in factories; ie. deciding if a new product is good enough to be sold, or if it should be discarded (the classification property is being good enough)\n* deciding whether a page or an article should be in the result set of a search not (the classification property is the relevance of the article - typically the presence of a certain word in it)\n\nClassification in general is one of the problems studied in [[computer science]], in order to automatically learn classification systems; some methods suitable for learning binary classifiers include the [[decision tree|decision trees]], [[Bayesian network|Bayesian networks]], [[support vector machine|support vector machines]], and [[neural network|neural networks]].\n\nSometimes, classification tasks are trivial. Given 100 balls, some of then red and some blue, a human with normal color vision can easily separate them into red ones and blue ones. However, some tasks, like those in practical medicine, and those interesting from the computer science point-of-view, are far from trivial, and produce also faulty results.\n\n==Tes hipotesis==\nDina [[tes hipotesa statistik]] tradisional, the tester start with a [[null hypothesis]] and an [[alternative hypothesis]], performs an experiment, and then decides whether or not to reject the null hypothesis in favour of the alternative.\n\nA positive or [[statistically significant]] result is one which rejects the null hypothesis. Doing this when the null hypothesis is in fact true - a false positive - is a [[Type I error]]; doing this when the null hypothesis is false is a true positive.\n\nA negative or not statistically significant result is one which does not reject the null hypothesis. Doing this when the null hypothesis is in fact false - a false negative - is a [[Type II error]]; doing this when the null hypothesis is true is a true negative.\n\n==Evaluasi klasifikasi biner==\nTo measure the performance of a medical test, the concepts [[sensitivity (tests)|sensitivity]] and [[specificity]] are often used; these concepts are readily usable for the evaluation of any binary classifier. Say we test some people for the presence of a disease. Some of these people have the disease, and our test says they are positive. They are called \'\'true positives\'\'. Some have the disease, but the test claims they don\'t. They are called \'\'false negatives\'\'. Some don\'t have the disease, and the test says they don\'t - \'\'true negatives\'\'. Finally, we might have healthy people who have a positive test result \'\'false positives\'\'.\n\n\'\'\'Sensitivity\'\'\' is the proportion of people that tested positive of all the positive people tested; that is (true positives) / (true positives + false negatives). It can be seen as \'\'the probability that the test is positive given that the patient is sick\'\'. The higher the sensitivity, the less real cases of diseases go undetected (or, in the case of the factory quality control, the less faulty products go to the market).\n\n\'\'\'Specificity\'\'\' is the proportion of people that tested negative of all the negative people tested; that is (true negatives) / (true negatives + false positives). As with sensitivity, it can be looked at as \'\'the probability that the test is negative given that the patient is not sick\'\'. The higher the specificity, the less healthy people are labeled as sick (or, in the factory case, the less money the factory loses by discarding good products instead of selling them).\n\nIn theory, sensitivity and specificity are independent in the sense that it is possible to achieve 100 % in both (for instance, the human classifying the red and blue balls most likely does). In practice, there often is a tradeoff, and you can\'t achieve both. [\'\'Explanation why should go here.\'\']\n\nIn addition to sensitivity and specificity, the performance of a binary classification test can be measured with \'\'\'positive and negative prediction values\'\'\'. These are possibly more intuitively clear: the positive prediction value answers the question \"how likely it is that I really have the disease, given that my test result was positive?\". It is calculated as (true positives) / (true positives + false positives); that is, it is the proportion of true positives out of all positive results. (The negative prediction value is the same, but for negatives, naturally.)\n\nOne should note, though, one important difference between the these concepts. That is, sensitivity and specificity are independent from the population in the sense that they don\'t change depending on what the proportion of positives and negatives tested are. Indeed, you can determine the sensitivity of the test by testing \'\'only\'\' positive cases. However, the prediction values are dependent on the population.\n\nAs an example, say that you have a test for a disease with 99 % sensitivity and 99 % specificity. Say you test 2000 people, and 1000 of them are sick and 1000 of them are healthy. You are likely to get about 990 true positives, 990 true negatives, and 10 of false positives and negatives each. The positive and negative prediction values would be 99 %, so the people can be quite confident about the result. \n\nSay, however, that of the 2000 people only 100 are really sick. Now you are likely to get 99 true positives, 1 false negative, 1881 true negatives and 190 false positives. Of the 190+99 people tested positive, only 99 really have the disease - that means, intuitively, that given that your test result is positive, there\'s only 34.2 % chance that you really have the disease. On the other hand, given that your test result is negative, you can really be reassured: there\'s only 1 chance in 1881, or 0.05% probability, that you have the disease despite of your test result.\n\n\nThe [[receiver operating characteristic]] is a graphical way of visualizing the performance of binary classifiers.\n\n\nSee also:\n* [[prosecutor\'s fallacy]]\n* [[Bayesian inference#Simple examples of Bayesian inference|Examples of Bayesian inference]]','/* Tes hipotesis */',13,'Budhi','20050104065822','',0,0,0,0,0.799407893233,'20050104065822','79949895934177'); INSERT INTO cur VALUES (1320,0,'Box_plot','Dina [[descriptive statistics]], a \'\'\'box plot\'\'\' is a convenient way of graphically depicting the [[five-number summary]], which consists of the smallest observation, lower [[quartile]], [[median]], upper [[quartile]] and largest observation.\n\nThe box plot may also identify [[outlier]]s and possibly the [[sample mean|mean]].\n\nA plain-text version might look like this:\n\n +-----+-+\n * o --------| + | |----\n +-----+-+\n\n +---+---+---+---+---+---+---+---+---+---+\n 0 1 2 3 4 5 6 7 8 9 10\n\nFor this [[data set]] (values are approximate, based on the figure):\n* smallest observation (\'\'minimum\'\') = .5\n* lower quartile = 7\n* median = 8.5\n* upper quartile = 9\n* largest observation (\'\'maximum\'\') = 10\n* mean = 8\n* the value 3.5 is a \"mild\" outlier\n* the value .5 is an \"extreme\" outlier\n* the smallest value that is \'\'not\'\' an outlier is 5\n* the data is [[skewness|skewed]] to the left (\'\'negatively skewed\'\')\n\nThe horizontal lines (the \"whiskers\") extend to at most 1.5 times the box width\n(the [[interquartile range]]) from the ends of the box. They must end \nat an observed value, thus connecting all the values outside the box\nthat are not more than 1.5 times the box width away from the box.\n\nThere are alternative implementations of this detail of the box plot\nfor various software packages, such as the whiskers extending to at most the\n5th and 95th (or some more extreme) percentiles. Not only do they not conform to \n[[John Tukey|Tukey\'s]] original definition. They also tend to produce \n\"outliers\" for all data sets larger than ten, no matter what the shape \nof the distribution.\n\n[[pl:wykres pudełkowy]]','',13,'Budhi','20040824010521','',0,0,0,0,0.863064248982,'20040904061658','79959175989478'); INSERT INTO cur VALUES (1321,0,'Business_statistics','\'\'\'Statistik bisnis\'\'\' ngarupakeun cabang [[applied statistics]] loba dipake keur ngumpulkeun data salaku hasil tina bisnis atawa lembaga pamarentah. Sipat sumber ieu pengulangan nu angger tina deret data. Hal ieu ngajadikeun [[deret waktu]] penting keur bisnis statistik.\n\nSababaraha teknik [[Marketing]] oge dipake leuwih [[Multivariate statistics]] lanjut dina segmen pasar, manajemen merk sarta teknik posisi produk.','',13,'Budhi','20041004003918','',0,0,0,0,0.081263929178,'20041004003918','79958995996081'); INSERT INTO cur VALUES (1322,0,'Ladislaus_Bortkiewicz','\'\'\'Ladislaus Josephovich Bortkiewicz\'\'\' ([[August 7]], [[1868]] - [[July 15]], [[1931]]) salah saurang [[Russian people|Russian]] [[economist]] jeung [[statistician]] katurunan [[Poland|Polish]].\n\nBortkiewicz lahir [[St. Petersburg]], [[Imperial Russia]] (ayeuna [[Russia]]) sarta tamat sarjana hukum dina taun [[1890]].\n\nTaun [[1898]] manehna ngaluarkeun buku ngeunaan [[Poisson distribution]], judulna \'\'The Law of Small Numbers\'\'. In this book he first noted that events with low frequency in a large population follow a Poisson distribution even when the probabilities of the events varied. It was that book that made the Prussian cavalry horse-kick data famous. The data give the number of soldiers killed by being kicked by a horse each year in each of 14 cavalry corps over a 20-year period. Bortkiewicz showed that those numbers follow a Poisson distribution. The book also examined data on child-suicides. Some historians of mathematics have argued that the Poisson distribution should have been named the \"Bortkiewicz distribution.\"\n\nIn political economy, Bortkiewicz is important for his analysis of Marx\'s reproduction schema in the last two volumes of [[Das Kapital|Capital]]. Bortkiewicz identified a [[transformation problem]] in Marx\'s work which, if proven, would profoundly undermine Marx\'s claim to have provided a consistent account of capitalist economics. This work provided the basis of major elaborations by [[Joseph Schumpeter]] and [[Paul Sweezy]] among others.\n\nBortkiewicz died in [[Berlin]], [[Germany]].\n\n==External link==\n\n* [http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Bortkiewicz.html Biographical sketch] on the web site of the [[University of St. Andrews]] (in [[Scotland]])\n\n[[Category:Statisticians|Bortkiewicz, Ladislaus]]\n[[Category:Economists|Bortkiewicz, Ladislaus]]','',13,'Budhi','20040824011044','',0,0,0,0,0.113483795018,'20041225235727','79959175988955'); INSERT INTO cur VALUES (1323,0,'Canonical_correlation','Dina [[statistik]], \'\'\'analisa canonical correlation\'\'\', dimimitian ku [[Harold Hotelling]], nyaeta turus keur nyieun matrik cross-covariance.\n\nDiberekeun dua vektor kolom \'\'X\'\' = (\'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\')′ and \'\'Y\'\' = (\'\'Y\'\'1, ..., \'\'Y\'\'\'\'m\'\')′ of random variables with finite second moments, one may define the cross-covariance cov(\'\'X\'\', \'\'Y\'\') to be the \'\'n\'\'×\'\'m\'\' matrix whose \'\'ij\'\' entry is the [[covariance]] cov(\'\'X\'\'\'\'i\'\', \'\'Y\'\'\'\'j\'\'). (Sometimes this is called simply the covariance between \'\'X\'\' and \'\'Y\'\'. But sometimes one speaks of the \"covariance\" of \'\'X\'\', intending the \'\'n\'\'×\'\'n\'\' matrix of covariances between the pairs of scalar components of \'\'X\'\'. Sometimes the latter matrix is called the variance of \'\'X\'\'.)\n\nCanonical correlation analysis seeks vectors \'\'a\'\' and \'\'b\'\' such that the real random variables \'\'a\'\'′ \'\'X\'\' and \'\'b\'\'′ \'\'Y\'\' (where the row-vector \'\'a\'\'′ is the transpose of the column-vector \'\'a\'\') maximize the [[correlation]] ρ(\'\'a\'\'′ \'\'X\'\', \'\'b\'\'′ \'\'Y\'\' ). The random vectors \'\'U\'\' = \'\'a\'\'′ \'\'X\'\' and \'\'V\'\' = \'\'b\'\'′ \'\'Y\'\' are the \'\'\'\'\'first pair of canonical variables\'\'\'\'\'. Then one seeks vectors maximizing the same correlation subject to the constraint that they are to be uncorrelated with the first pair of canonical variables; this gives the \'\'\'\'\'second pair of canonical variables\'\'\'\'\', etc.','',13,'Budhi','20040901063901','',0,0,0,0,0.726305819455,'20040901063901','79959098936098'); INSERT INTO cur VALUES (1324,0,'Common-_and_special-causes','{| border=1 align=left\n|\n|\'\'\'Alternative name\'\'\'\n|-\n|Common cause\n|\n{|\n|Chance cause\n|-\n|Non-assignable cause\n|-\n|Noise\n|}\n|-\n|Special cause\n|\n{|\n|Assignable cause\n|-\n|Signal\n|}\n|}\n\n\'\'\'Common- and special-causes\'\'\' are the two distinct origins of variation, in a [[process]] that features in the [[statistics|statistical]] thinking and methods of [[Walter A. Shewhart]] and [[W. Edwards Deming]]. However, it can be argued that they were recognised and discussed as early as [[1703]] by [[Gottfried Leibniz]] and are particularly important in the thinking of [[economist]]s [[Frank Knight]], [[John Maynard Keynes]] and [[G. L. S. Shackle]]. Several alternative names have been used over the years.\n\n==Origins and concepts==\n\nIn [[1703]], [[Jacob Bernoulli]] wrote to [[Gottfried Leibniz]] to discuss their shared interest in applying [[mathematics]] and [[probability]] to games of chance. [[Jacob Bernoulli|Bernoulli]] speculated whether it would be possible to gather [[mortality]] data from gravestones and thereby calculate, by their existing practice, the [[probability]] of a man currently aged 20 years outliving a man aged 60 years. [[Gottfried Leibniz|Leibniz]] replied that he doubted this was possible as:\n\n\'\'Nature has established patterns originating in the return of events but only for the most part. New illnesses flood the human race, so that no matter how many experiments you have done on corpses, you have not thereby imposed a limit on the nature of events so that in the future they could not vary.\'\'\n\nThis captures the central idea that some variation is predictable, at least approximately in frequency. This \'\'common-cause variation\'\' is evident from the experience base. However, new, unanticipated, emergent or previously neglected phenomena (\'\'e.g.\'\' \"new diseases\") result in variation outside the historical experience base. [[Walter A. Shewhart|Shewhart]] and [[W. Edwards Deming|Deming]] argued that such \'\'special-cause variation\'\' is fundamentally unpredictable in frequency of occurrence or in severity.\n\n[[John Maynard Keynes]] emphasised the importance of special-cause variation when he wrote:\n\n\'\'By “uncertain” knowledge … I do not mean merely to distinguish what is known for certain from what is only probable. The game of roulette is not subject, in this sense, to uncertainty ... The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention … About these matters there is no scientific basis on which to form any calculable probability whatever. We simply do not know!\'\'\n\n==Harti==\n\n===Common-cause variation===\n\nCommon-cause variation is characterised by:\n\n*Phenomena constantly active within the system;\n*Variation predictable [[probability|probabilistically]];\n*Irregular variation within an historical experience base; and\n*Lack of significance in individual high or low values.\n\nThe outcomes of a [[roulette]] wheel are a good example of common-cause variation. Common-cause variation is the \'\'noise\'\' within the system.\n\n[[Walter A. Shewhart]] originally used the term \'\'chance-cause\'\'. The term \'\'common-cause\'\' was coined by [[Harry Alpert]] in [[1947]]. [[Walter A. Shewhart|Shewhart]] called a process that features only common-cause variation \'\'in [[statistical control]]\'\'. This term is deprecated by some modern statisticians who prefer the phrase \'\'stable and predictable\'\'.\n\n===Special-cause variation===\n\nSpecial-cause variation is characterised by:\n\n*New, unanticipated, emergent or previously neglected phenomena within the system;\n*Variation inherently unpredictable, even [[probability|probabilistically]];\n*Variation outside the historical experience base; and\n*Evidence of some inherent change in the system or our knowledge of it.\n\nSpecial-cause variation always arives as a surprise. It is the \'\'signal\'\' within a system.\n\n[[Walter A. Shewhart]] originally used the term \'\'assignable-cause\'\'. The term \'\'special-cause\'\' was coined by [[W. Edwards Deming]].\n\n==Importance to economics==\n\n[[John Maynard Keynes]] and [[Frank Knight]] both discussed the inherent unpredictability of economic systems in their work and used it to criticise the mathematical approach to [[economics]], in terms of expected [[utility]], developed by [[Ludwig von Mises]] and others. [[John Maynard Keynes|Keynes]] in particular argued that economic systems did not automatically tend to the equilibrium of full employment owing to their agents\' inability to predict the future. As he remarked in \'\'[[General Theory of Employment Interest and Money|The General Theory of Employment, Interest and Money]]\'\':\n\n\'\'… as living and moving beings, we are forced to act … [even when] our existing knowledge does not provide a sufficient basis for a calculated mathematical expectation.\'\'\n\n[[John Maynard Keynes|Keynes]]\'s thinking was at odds with the [[classical liberalism]] of the [[Austrian school]] of [[economist]]s but [[G. L. S. Shackle]] recognised the importance of [[John Maynard Keynes|Keynes]]\'s insight and sort to formalise it within a [[free-market]] philosophy.\n\n==Importance to industrial management==\n\n[[Harry Alpert]] observed:\n\n\'\'A riot occurs in a certain prison. Officials and sociologists turn out a detailed report about the prison, with a full explanation of why and how it happened here, ignoring the fact that the causes were common to a majority of prisons, and that the riot could have happened anywhere.\'\'\n\nThe quote recognises that there is a tempation to react to an extreme outcome and to see it as significant, even where its causes are common to many situations and the distincive circumstances surrounding its occurrence, the results of mere chance. Such behaviour has many implications within management, often leading to interventions in processes that merely increase the level of variation and frequency of undesirable outcomes.\n\n[[W. Edwards Deming|Deming]] and [[Walter A. Shewhart|Shewhart]] both advocated the [[control chart]] as a means of managing a business [[process]] in an economically efficient manner.\n\n==Importance to statistics==\n\n===Deming and Shewhart===\n\nWithin the [[frequency probability]] framework, there is no process whereby a [[probability]] can be attached to the future occurrence of special cause . However the [[bayesian probability|bayesian]] approach does allow such a [[probability]] to be specified. The existence of special-cause variation led [[John Maynard Keynes|Keynes]] and [[W. Edwards Deming|Deming]] to an interest in [[bayesian probability]] but no formal synthesis has ever been forthcoming. Most statisticians of the Shewhart-Deming school take the view that special causes are not embedded in either experience or in current thinking (that\'s why they come as a surprise) so that any subjective probability is doomed to be hopelessly badly [[calibration (probability)|calibrated]] in practice.\n\nIt is immediately apparent from the [[Gottfried Leibniz|Leibniz]] quote above that there are implications for [[sampling (statistics)|sampling]]. [[W. Edwards Deming|Deming]] observed that in any forecasting activity, the [[population (statistics)|population]] is that of future events while the [[sampling frame]] is, inevitably, some [[subset]] of historical events. [[W. Edwards Deming|Deming]] held that the disjoint nature of [[population (statistics)|population]] and [[sampling frame]] was inherently problematic once the existence of special-cause variation was admitted, rejecting the general use of [[probability]] and conventional [[statistics]] in such \nsituations. He articulated the difficulty as the distinction between [[enumerative and analytic studies]].\n\n[[Walter A. Shewhart|Shewhart]] argued that, as processes subject to special-cause variation were inherently unpredictable, the usual techniques of probability could not be used to separate special- from common-cause variation. He developed the [[control chart]] as a statistical heuristic to distinguish the two types of variation. Both [[W. Edwards Deming|Deming]] and [[Walter A. Shewhart|Shewhart]] advocated the [[control chart]] as a means of assessing a process\'s state of [[statistical control]] and as a foundation for forecasting.\n\n===Keynes===\n\n[[John Maynard Keynes|Keynes]] identified three domains of [[probability]]:\n\n*[[Frequency probability]];\n*Subjective or [[Bayesian probability]]; and\n*Events lying outside the possibility of any description in terms of [[probability]] (special causes)\n\n- and sought to base a [[probability theory]] thereon.\n\n==Bibliography==\n\n*Deming, W E (1975) On probability as a basis for action, \'\'The American Statistician\'\', 29(4), pp146-152\n*Deming, W E (1982) \'\'Out of the Crisis: Quality, Productivity and Competitive Position\'\' ISBN 0521305535\n*Keynes, J M (1921) \'\'A Treatise on Probability\'\', ISBN 0333107330 \n*Keynes, J M (1936) \'\'The General Theory of Employment Interest and Money\'\' ISBN 1573921394\n*Knight, F H (1921) \'\'Risk, Uncertainty and Profit\'\' ISBN 1587981262\n*Shackle, G L S (1972) \'\'Epistemics and Economics: A Critique of Economic Doctrines\'\' ISBN 1560005580\n*Shewhart, W A (1931) \'\'Economic Control of Quality of Manufactured Product\'\' ISBN 73890760\n*Shewhart, W A (1939) \'\'Statistical Method from the Viewpoint of Quality Control\'\' ISBN 0486652327\n*Wheeler, D J & Chambers, D S (1992) \'\'Understanding Statistical Process Control\'\' ISBN 0945320132','/* Definitions */',13,'Budhi','20040907063429','',0,0,0,0,0.408215759046,'20041224120715','79959092936570'); INSERT INTO cur VALUES (1325,0,'Completeness_(statistics)','Anggap [[variabel random]] \'\'X\'\' (which may be a sequence\n(\'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\') of [[scalar]]-valued\nrandom variables), has a probability distribution belonging to a known\nfamily of probability distributions, parametrized by θ, which\nmay be either [[vector (spatial)|vector]]- or scalar-valued. A function \'\'g\'\'(\'\'X\'\')\nis an \'\'\'unbiased estimator of zero\'\'\' if the expectation\nE(\'\'g\'\'(\'\'X\'\')) remains zero regardless of the value of the\nparameter θ. Then \'\'X\'\' is a \'\'\'complete statistic\'\'\'\nprecisely if it admits no such unbiased [[estimator]] of [[zero]].\n\nFor example, suppose \'\'X\'\'1, \'\'X\'\'2\nare [[statistical independence|independent]], identically\ndistributed random variables,\n[[normal distribution|normally distributed]] with\nexpecation θ and variance 1. Then\n\'\'X\'\'1 — \'\'X\'\'2 is an unbiased\nestimator of zero. Therefore the pair\n(\'\'X\'\'1, \'\'X\'\'2) is \'\'not\'\' a complete\nstatistic. On the other hand, the sum\n\'\'X\'\'1 + \'\'X\'\'2\ncan be shown to be a complete statistic. That means that there\nis no non-zero function \'\'g\'\' such that\n\n:E(g(X_1+X_2))\n\nremains zero regardless of changes in the value of θ.\nThat fact may be seen as follows.\nThe probability distribution of\n\'\'X\'\'1 + \'\'X\'\'2\nis normal with expectation 2θ and variance 2.\nIts probability density function is therefore\n\n:{\\rm constant}\\cdot\\exp\\left(-(x-2\\theta)^2/4\\right).\n\nThe expectation above would therefore be a constant times\n\n:\\int_{-\\infty}^\\infty g(x)\\exp\\left(-(x-2\\theta)^2/4\\right)\\,dx.\n\nA bit of algebra reduces this to\n\n:[{\\rm a\\ nowhere\\ zero\\ function\\ of\\ }\\theta]\\times\\int_{-\\infty}^\\infty\nh(x)\\,e^{x\\theta}\\,dx{\\rm\\ where\\ }h(x)=g(x)\\,e^{-x^2/4}.\n\nAs a function of θ this is a two-sided [[Laplace transform]]\nof \'\'h\'\'(\'\'x\'\'), and cannot be identically zero unless \'\'h\'\'(\'\'x\'\')\nzero almost everywhere.\n\nOne reason for the importance of the concept is the [[téoréma Lehmann-Scheffé]],\nwhich states that a statistic that is complete, [[sufficiency (statistics)|sufficient]], and [[bias (statistics)|unbiased]] is the best unbiased estimator, i.e., the one that has a smaller mean squared error than any other unbiased estimator, or, more generally, a smaller expected loss, for any [[convex function|convex]] loss function.','',13,'Budhi','20041225233440','',0,0,1,0,0.608183646858,'20041225233440','79958774766559'); INSERT INTO cur VALUES (1326,0,'Komposisi_data','Dina [[statistik]], \'\'\'komposisi data\'\'\' nyaeta data dina unggal [[data point]] ngarupakeun \'\'n\'\'-tuple tina wilangan nonnegative nu jumlahna sarua jeung 1. Sacara tipikal unggal komponen \'\'n\'\' tina unggal titik data \'\'p\'\'\'\'i\'\' (\'\'p\'\'1, ..., \'\'p\'\'\'\'n\'\') ngagambarkeun yen porsi (atawa \"persentase\") satuan statistik kana kategori nu ka-\'\'i\'\' dina urutan kategori \'\'n\'\'.\n\nContona,\n\n*Unggal titik data pakait kana susunan batuan disusun ku tilu mineral nu beda; batuan mibanda 10% mineral kahiji, 30% nu kadua, sarta sesana 60% nu pakait jeung triple (0.1, 0.3, 0.6); susunan data kudu mibanda hiji tina triple keur unggal batuan dina sampel batuan.\n\n*Unggal titik data nu pakait kana hiji kota; hiji kota numana 35% ngagem agama Kristen, 55% Muslim, 6% Yahudi, sarta sesana 4% ageman sejen, tangtu pakait jeung quadruple (0.35, 0.55, 0.06, 0.04); susunan data bakal pakait jeung ugeran dina eta kota.\n\n{{msg:stub}}','',13,'Budhi','20041203234540','',0,0,0,0,0.874625031778,'20041203234705','79958796765459'); INSERT INTO cur VALUES (1327,0,'Correlation','[[de:Korrelation]][[it:correlazione]]\nDina [[tiori probabiliti]] sarta [[statistik]], \'\'\'korelasi\'\'\', oge disebut \'\'koefisien korelasi\'\'\', antara dua [[variabel acak]] diitung ku ngabagi [[kovarian]]-na ku hasil kali [[simpangan baku]]na (lamun simpangan baku terhingga). Dumasar kana corollary [[Cauchy-Schwarz inequality]] mangka korelasi teu bisa leuwih ti 1 dina [[absolute value|nilai mutlak]].\n\nKorelasi sarua jeung 1 dina kasus hubungan linier naek, −1 dina kasus hubungan linier nurun, saerta sababaraha nilai antara dina sakabeh kasus sejenna, nembongkeun tingkat kabebasan linier antar variabel. Koefisien pangdeukuetna nyaeta −1 atawa 1, pakait antar variabel kacida raketna.\n\nLamun variabel [[Statistical independence|bebas]] mangka korelasi sarua jeung 0, tapi tibalik lain sabenerna sabab koefisien korelasi katembong ngan hubungan linier antara dua variabel. Dina conto ieu: Anggap variabel random \'\'X\'\' kasebar seragam dina interval antara −1 ka 1, sarta \'\'Y\'\' = \'\'X\'\'2. Mangka \'\'Y\'\' ditangtukeun ku \'\'X\'\', mangka \'\'X\'\' jeung \'\'Y\'\' jauh tina dua variabel bebas, korelasina sarua jeung nol; duanana taya korelasi.\n\n==\"Correlation does not imply causation\"==\n\nThe conventional mantra that \"correlation does not imply causation\" is treated in the article titled [[spurious relationship]].\n\n==Statistical estimation of population correlations by sample correlations==\n\nIf several values of \'\'X\'\' and \'\'Y\'\' have been measured, then the [[Pearson product-moment correlation coefficient]] can be used to estimate the correlation of \'\'X\'\' and \'\'Y\'\'.\nThe coefficient is especially important if \'\'X\'\' and \'\'Y\'\' are both [[sebaran normal|normally distributed]] and follow the [[linear regression]] model.\n\n==Non-parametric statistics==\n\nPearson\'s correlation coefficient is a [[statistik parametrik]], and it may be less useful if the underlying assumption of normality is violated. [[non-parametric statistics|Non-parametric]] correlation methods, such as [[Spearman\'s rank correlation coefficient|Spearman\'s ρ]] and [[Kendall\'s tau correlation coefficient]] may be useful when distributions are not normal; they are a little less powerful than parametric methods if the assumptions underlying the latter are met, but are less likely to give distorted results when the assumptions fail.\n\n==Other measures of dependence among random variables==\n\nTo get a measure for more general dependencies in the data (also nonlinear) it is better to use the [[rasio korelasi]] which is able to detect almost any functional dependency, or [[mutual information]] which detects even more general dependencies.\n\n==Tumbu kaluar==\n\n:[http://www.statsoft.com/textbook/stathome.html Statsoft Electronic Textbook]','',13,'Budhi','20041224211031','',0,0,1,0,0.125535581319,'20041224211031','79958775788968'); INSERT INTO cur VALUES (1328,0,'Beta_distribution','#REDIRECT [[Sebaran beta]]\n','Beta distribution dipindahkeun ka Sebaran beta',13,'Budhi','20040820224559','',0,1,0,1,0.296952569202476,'20040820224559','79959179775440'); INSERT INTO cur VALUES (1329,0,'Fungsi_béta','Dina [[matematik]], \'\'\'fungsi béta\'\'\', mimitina disebut ogé [[integral Euler]], nyaéta hiji [[fungsi husus]] nu diartikeun ku\n:\\mathrm B(x,y) = \\int_0^1t^{x-1}(1-t)^{y-1}\\,dt\n\nFungsi béta nyaéta [[simétrik]], hartina \n:\\mathrm B(x,y) = \\mathrm B(y,x).\n\nNgabogaan bentuk séjén, kaasup:\n:\n \\mathrm B(x,y)=\\frac{\\Gamma(x)\\Gamma(y)}{\\Gamma(x+y)}\n\n\n:\n \\mathrm B(x,y)=2\\int_0^{\\pi/2}\\sin^{2x-1}\\theta\\cos^{2y-1}\\theta\\,d\\theta,\n \\qquad{\\mathrm Re}(x)>0,\\ {\\mathrm Re}(y)>0\n \n\n:\n \\mathrm B(x,y)=\\int_0^\\infty\\frac{t^{x-1}}{(1+t)^{x+y}}\\,dt,\n \\qquad{\\mathrm Re}(x)>0,\\ {\\mathrm Re}(y)>0\n \n\n:\n \\mathrm B(x,y)=\\frac{1}{y}\\sum_{n=0}^\\infty(-1)^n\\frac{(x)_{n+1}}{n!(x+n)}\n \n\nnumana (\'\'x\'\')\'\'n\'\' nyaeta [[falling factorial]].\n\nTempo ogé: [[integral Euler]], [[falling factorial]], [[fungsi gamma]]\n\n[[en:Beta function]]\n[[nl:Betafunctie]]\n[[sl:funkcija beta]]','',3,'Kandar','20050131041850','',0,0,0,0,0.229510421972,'20050131041850','79949868958149'); INSERT INTO cur VALUES (1330,0,'Sebaran_seragam','Dina [[matematik]], \'\'\'sebaran seragam\'\'\' nyaeta [[probability distribution]] sederhana. Sebaran bisa [[discrete random variable|discrete]] atawa [[continuous random variable|continuous]]. Dina kasus \'\'diskrit\'\', bisa di-karakterisasi ku nyebutkeun yen sakabeh nilai sarua kamungkinanna. Dina kasus \'\'kontinyu\'\' yen sakabeh panjang [[interval]] nu sarua ngabogaan kamungkinan nu sarua.\n\n== Kasus diskrit ==\n\nVariabel random nu mibanda unggal nilai \'\'n\'\' nu mungkin \'\'x\'\'1, \'\'x\'\'2, ..., \'\'x\'\'\'\'n\'\' ngabogaan kamungkinan nu sarua dina sebaran seragam diskrit, saterusna kamungkinan keur unggal hasil \'\'x\'\'\'\'i\'\' nyaeta 1/\'\'n\'\'. Conto gampang dina sebaran seragam diskrit nyaeta ngalungkeun dadu. Nilai nu mungkin \'\'x\'\' nyaeta 1, 2, 3, 4, 5, 6; dina unggal alungan, kamungkinan salah sahiji nilai muncul nyaeta 1/6.\n\nDina kasus nilai variabel random nu mibanda sebaran normal ngarupakeun [[real number|riil]], ngamungkinkeun keur ngagambarkeun fungsi kumulatif sebaran dina watesan \'\'degenarate\'\' sebaran, nyaeta \n\n:F(x)={1\\over N}\\sum_{i=1}^N\\theta(x-x_i)\n\nnumana Heavyside [[step function]] θ(\'\'x\'\') ngarupakeun CDF tina degenerate sebaran dina \'\'x\'\' = 0.\n\n== Kasus kontinyu ==\n\nDina kasus kontinyu, sebaran seragam disebut oge \'\'\'sebaran bujursangkar\'\'\' sabab bentuk tina fungsi densiti probabiliti (tempo di handap). Hal ieu di-parameterisasi ku nilai pangleutikna jeung panggedena tina kaseragaman-sebaran [[random variable]] nu dicokot nyaeta \'\'a\'\' jeung\n\'\'b\'\'. [[Probability density function]] sebaran seragam nyaeta:\n\n:\n p(x)=\\left\\{\\begin{matrix}\n \\frac{1}{b - a} & \\ \\ \\ \\mbox{for }a \\leq x \\leq b \\\\\n 0 & \\mbox{elsewhere}\n \\end{matrix}\\right.\n\n\nsarta [[cumulative distribution function]] nyaeta:\n\n:\n F(x)=\\left\\{\\begin{matrix}\n 0 & \\mbox{for }x < a \\\\\n \\frac{x - a}{b - a} & \\ \\ \\ \\mbox{for }a \\le x < b \\\\\n 1 & \\mbox{for }x \\ge b\n \\end{matrix}\\right.\n\n\nGrapik pungsi densiti probabiliti keur sebaran seragam siga di handap ieu:\n\n[[image:uniform_pdf.png|center|314px]]\n\n
\'\'\'Pungsi densiti probabiliti tina sebaran seragam kontinyu\'\'\'
\n\nKeur [[random variable]] nu nuturkeun sebaran ieu, [[nilai ekspektasi]] nyaeta (a + b)/2 sarta [[simpangan baku]] nyaeta\n(b - a)/√12.\n\nSebaran ieu bisa dipake keur susunan nu leuwih kompleks tinimbang interval. Lamun \'\'S\'\' ngarupakeun susunan Borel positip, ukuran \'\'terhingga\'\', sebaran probabiliti seragam dina \'\'S\'\' bisa dihusukeun ku nyebutkeun yen pdf nyaeta nol diluar \'\'S\'\' sarta sacara angger sarua jeung 1/\'\'K\'\' dina \'\'S\'\', numana \'\'K\'\' ukuran Lebesgue tina \'\'S\'\'.\n\n=== Standar sebaran seragam ===\n\n\'\'Standard sebaran seragam\'\' nyaeta sebaran seragam kontinyu nu mibanda susunan nilai \'\'a\'\' jeung \'\'b\'\' nyaeta 0 jeung 1, mangka nilai variabel random ngan antara 0 jeung 1.\n\n=== Sampling tina sebaran seragam ===\n\nWaktu digawe make probabiliti, karasa mangpaatna keur nga-run percobaan saperi dina simulasi komputer. Loba [[programming language]] nu ngabogaan kamampuan keur nyaruakeun [[Pseudorandom number sequence|pseudo-random numbers]] nu epektip kasebar dumasar kana standar sebaran seragam. \n\nLamun \'\'u\'\' ngarupakeun nilai sampel tina standar sebaran seragam , mangka nilai \'\'a\'\' + (\'\'b\'\' - \'\'a\'\')\'\'u\'\' nuturkeun sebaran seragam nu di-parameterisasi ku \'\'a\'\' jeung \'\'b\'\', saperti nu dijelaskeun di luhur. Transpromasi sejenna bisa digunakeun keur nyaruakeun sebaran statistik sejenna tina sebaran seragam (tempo \'\'pamakean\'\' di handap)\n\n=== Pamakean sebaran seragam ===\n\nDina [[statistik]], lamun [[p-value]] dipake salaku tes statistik keur [[null hypothesis]] sederhana, jeung sebaran test statistik kontinyu , mangka tes statistik bakal kasebar seragam antara 0 jeung 1 lamun null hypothesis bener.\n\nSanajan sebaran seragam teu ilahar kapanggih di alam, sabageanna bisa dipake keur sampling tina sebaran acak.\n\nMetoda nu geus ilahar nyaeta [[inverse transform sampling method]], nu make [[cumulative distribution function]] (CDF) tina target variabel random. Metoda ieu kacida ngabantu dina pagawean tioritis. Saprak simulasi make metoda ieu merlukeun \'\'inverting\'\' CDF tina variabel target, metoda alternatipna geus dibagi keur kasus numana CDF teu dipikanyaho dina bentuk raket. Salah sahiji metodana nyaeta [[rejection sampling]]. \n\n[[Sebaran normal]] ngarupakeun conto penting mangsa metoda \'\'inverse transform\'\' teu episien. Sanajan kitu, eta ngarupakeun metoda eksak, [[Box-Muller transformation]], nu make \'\'inverse transform\'\' keur konversi dua [[random variable]] seragam bebas ka dua [[sebaran normal]] random variabel bebas.\n\n[[Category:Probability distributions]]\n[[it:variabile casuale Uniforme discreta]]\n[[de:Laplace-Verteilung]]','/* Standar sebaran seragam */',13,'Budhi','20041224032650','',0,0,1,0,0.122277788875,'20041224032650','79958775967349'); INSERT INTO cur VALUES (1331,0,'Gambaran_kongkrit_teorema_central_limit','Jejer ieu ngagambarkeun [[central limit theorem|tiori central limit]] ngaliwatan conto keur \'\'penghitungan\'\' bisa diitung sacara gancang ku leungeun dina kertas, teu saperti conto-intesip dina jejer [[illustration of the central limit theorem|gambaran dina teorema central limit]]. Anggap sebaran probabiliti [[variabel random]] \'\'X\'\' beuratna sarua dina 1, 2, jeung 3:\n\n:X=\\left\\{\\begin{matrix} 1 & \\mbox{with}\\ \\mbox{probability}\\ 1/3, \\\\\n2 & \\mbox{with}\\ \\mbox{probability}\\ 1/3, \\\\\n3 & \\mbox{with}\\ \\mbox{probability}\\ 1/3.\n\\end{matrix}\\right.\n\nFungsi probabiliti massa tina variabel random \'\'X\'\' digambarkeun ku:\n\n o o o\n -------------\n 1 2 3\n\nKatembong jelas teu siga kurva bentuk-bel.\n\nAyeuna tempo jumlah dua kopi-an \'\'X\'\' bebas:\n\n:\\left\\{\\begin{matrix}\n1+1 & = & 2 \\\\\n1+2 & = & 3 \\\\\n1+3 & = & 4 \\\\\n2+1 & = & 3 \\\\\n2+2 & = & 4 \\\\\n2+3 & = & 5 \\\\\n3+1 & = & 4 \\\\\n3+2 & = & 5 \\\\\n3+3 & = & 6\n\\end{matrix}\\right\\}\n=\\left\\{\\begin{matrix}\n2 & \\mbox{with}\\ \\mbox{probability}\\ 1/9 \\\\\n3 & \\mbox{with}\\ \\mbox{probability}\\ 2/9 \\\\\n4 & \\mbox{with}\\ \\mbox{probability}\\ 3/9 \\\\\n5 & \\mbox{with}\\ \\mbox{probability}\\ 2/9 \\\\\n6 & \\mbox{with}\\ \\mbox{probability}\\ 1/9\n\\end{matrix}\\right\\}\n\n\nFungsi probabiliti massa tina jumlah ieu digambarkeun ku:\n\n o\n o o o\n o o o o o\n ----------------------------\n 2 3 4 5 6\n\nIeu oge can katembong leuwih siga tina kurva bentuk-bell, tapi, saperti bentuk-bel sarta teu saperti fungsi probabiliti massa \'\'X\'\' eta sorangan, leuwih luhur dibagian tengah tinimbang di dua sisina.\n\nAyeuna tempo jumlah \'\'tilu\'\' kopian bebas ieu random variabel:\n\n:\\left\\{\\begin{matrix}\n1+1+1 & = & 3 \\\\\n1+1+2 & = & 4 \\\\\n1+1+3 & = & 5 \\\\\n1+2+1 & = & 4 \\\\\n1+2+2 & = & 5 \\\\\n1+2+3 & = & 6 \\\\\n1+3+1 & = & 5 \\\\\n1+3+2 & = & 6 \\\\\n1+3+3 & = & 7 \\\\\n2+1+1 & = & 4 \\\\\n2+1+2 & = & 5 \\\\\n2+1+3 & = & 6 \\\\\n2+2+1 & = & 5 \\\\\n2+2+2 & = & 6 \\\\\n2+2+3 & = & 7 \\\\\n2+3+1 & = & 6 \\\\\n2+3+2 & = & 7 \\\\\n2+3+3 & = & 8 \\\\\n3+1+1 & = & 5 \\\\\n3+1+2 & = & 6 \\\\\n3+1+3 & = & 7 \\\\\n3+2+1 & = & 6 \\\\\n3+2+2 & = & 7 \\\\\n3+2+3 & = & 8 \\\\\n3+3+1 & = & 7 \\\\\n3+3+2 & = & 8 \\\\\n3+3+3 & = & 9 \n\\end{matrix}\\right\\}\n=\\left\\{\\begin{matrix}\n3 & \\mbox{with}\\ \\mbox{probability}\\ 1/27 \\\\\n4 & \\mbox{with}\\ \\mbox{probability}\\ 3/27 \\\\\n5 & \\mbox{with}\\ \\mbox{probability}\\ 6/27 \\\\\n6 & \\mbox{with}\\ \\mbox{probability}\\ 7/27 \\\\\n7 & \\mbox{with}\\ \\mbox{probability}\\ 6/27 \\\\\n8 & \\mbox{with}\\ \\mbox{probability}\\ 3/27 \\\\\n9 & \\mbox{with}\\ \\mbox{probability}\\ 1/27\n\\end{matrix}\\right\\}\n\n\nFungsi probabiliti tina jumlah ieu digambarkeun ku:\n\n o\n o o o\n o o o\n o o o\n o o o o o\n o o o o o\n o o o o o o o\n ---------------------------------\n 3 4 5 6 7 8 9\n\nIeu heunteu ngan leuwih gede di tengah tinimbang dua sisina, tapi pindah ka arah tengah ti sisi nu sejen, miring nu mimiti naek sarta saterusna turun, siga kurva bentuk-bel.\n\nUrang bisa ngitung tingkatna tina susnan kana kurva bentuk-bel siga di handap ieu. Tempo\n\n:Pr(\'\'X\'\'1 + \'\'X\'\'2 + \'\'X\'\'3 ≤ 7) = 1/27 + 3/27 + 6/27 + 7/27 + 6/27 = 23/27 = 0.851 851 851 ... .\n\nSakumaha raket hal ieu ngadeukeutan kana [[sebaran normal|normal]]? Ieu bisa ditempo tina nilai ekspektasi \'\'Y\'\' = \'\'X\'\'1 + \'\'X\'\'2 + \'\'X\'\'3 nyaeta 6 sarta simpangan baku \'\'Y\'\' ngarupakeun akar kuadrat 2. Saprak \'\'Y\'\' ≤ 7 (kateusaruaan lemah) lamun jeung lamun \'\'Y\'\' < 8 (kateusaruaan kuat), bisa make koreksi kontinyu sarta ditembongkeun ku\n\n:\\mbox{Pr}(Y\\leq 7.5)\n=\\mbox{P}\\left({Y-6 \\over \\sqrt{2}}\\leq{7.5-6 \\over \\sqrt{2}}\\right)\n=\\mbox{Pr}(Z\\leq 1.606602\\dots)\\approx 0.8555778\n\nnumana \'\'Z\'\' ngarupakeun standar normal sebaran. Beda antara 0.85185... sarta 0.8556... katempo beuki ngaleutikan waktu eta ditempo salaku wilangan variabel random bebas nu ditambahkeun ngan tilu.','',13,'Budhi','20040907065800','',0,0,0,0,0.894073791287,'20040907065922','79959092934199'); INSERT INTO cur VALUES (1332,0,'Conditional_distribution','Diberekeun dua sebaran gabungan [[variabel random]] \'\'X\'\' jeung \'\'Y\'\', \'\'\'sebaran kondisional probabiliti\'\'\' of \'\'Y\'\' given \'\'X\'\' (written \"\'\'Y\'\' | \'\'X\'\'\") is the [[probability distribution]] of \'\'Y\'\' when \'\'X\'\' is known to be a particular value.\n\nFor [[discrete random variable]]s, the [[conditional probability]] mass function can be written as \'\'P\'\'(\'\'Y\'\' = \'\'y\'\' | \'\'X\'\' = \'\'x\'\'). From the definition of [[conditional probability]], this is \n\n:P(Y=y|X=x) = \\frac{P(X=x,Y=y)}{P(X=x)}= \\frac{P(X=x|Y=y) P(Y=y)}{P(X=x)}\n\nSimilarly for [[continuous random variable]]s, the conditional [[probability density function]] can be written as \'\'p\'\'\'\'Y\'\'|\'\'X\'\'(\'\'y\'\' | \'\'x\'\') and this is \n\n:p_{Y|X}(y|x) = \\frac{p_{X,Y}(x,y)}{p_X(x)}= \\frac{p_{X|Y}(x|y)p_Y(y)}{p_X(x)}\n\nwhere \'\'p\'\'\'\'X\'\',\'\'Y\'\'(x, y) gives the [[joint distribution]] of \'\'X\'\' and \'\'Y\'\', while \'\'p\'\'\'\'X\'\'(\'\'x\'\') gives the [[marginal distribution]] for \'\'X\'\'.\n\nThe concept of the conditional distribution of a continuous random variable is not as intuitive as it might seem: [[Borel\'s paradox]] shows that conditional probability density functions need not be invariant under coordinate transformations.\n\nIf for discrete random variables \'\'P\'\'(\'\'Y\'\' = \'\'y\'\' | \'\'X\'\' = \'\'x\'\') = \'\'P\'\'(\'\'Y\'\' = \'\'y\'\') for all \'\'x\'\' and \'\'y\'\', or for continuous random variables \'\'p\'\'\'\'Y\'\'|\'\'X\'\'(\'\'y\'\' | \'\'x\'\') = \'\'p\'\'\'\'Y\'\'(\'\'y\'\') for all x and y, then \'\'Y\'\' is said to be [[Statistical independence|independent]] of \'\'X\'\' (and this implies that \'\'X\'\' is also independent of \'\'Y\'\').\n\nSeen as a function of \'\'y\'\' for given \'\'x\'\', \'\'P\'\'(\'\'Y\'\' = \'\'y\'\' | \'\'X\'\' = \'\'x\'\') is a probability and so the sum over all \'\'y\'\' (or integral if it is a density) is 1. Seen as a function of \'\'x\'\' for given \'\'y\'\', it is a [[likelihood]], so that the sum over all \'\'x\'\' need not be 1.\n\n[[Category:Probability distributions]]','',13,'Budhi','20040907070457','',0,0,0,0,0.58339009694,'20041231123527','79959092929542'); INSERT INTO cur VALUES (1333,0,'Conditional_independence','[[Category:Probability theory]]\n\nIn [[probability theory]], two events \'\'A\'\' and \'\'B\'\' are \'\'\'conditionally independent\'\'\' given a third event \'\'\'C\'\'\' precisely if the occurrence or non-occurrence of \'\'A\'\' and \'\'B\'\' are [[statistical independence|independent]] events in their conditional [[probability distribution]] given \'\'C\'\'. Dua [[variabel acak]] \'\'X\'\' jeung \'\'Y\'\' are \'\'\'conditionally independent\'\'\' given an event \'\'C\'\' if they are independent in their conditional probability distribution given \'\'C\'\'. Two random variables \'\'X\'\' and \'\'Y\'\' are conditionally independent given a third random variable \'\'W\'\' if for any measureable set \'\'S\'\' of possible values of \'\'W\'\', \'\'X\'\' and \'\'Y\'\' are conditionally independent given the event [\'\'W\'\' ∈ \'\'S\'\'].\n\n==Uses in Bayesian statistics==\n\nLet \'\'p\'\' be the proportion of voters who will vote \"yes\" in an upcoming referendum. In taking an opinion poll, one chooses \'\'n\'\' voters randomly from the population. For \'\'i\'\' = 1, ..., \'\'n\'\', let \'\'X\'\'\'\'i\'\' = 1 or 0 according as the \'\'i\'\'th chosen voter will or will not vote \"yes\".\n\nIn a [[frequentism|frequentist]] approach to statistical inference one would not attribute any probability distribution to \'\'p\'\' (unless the probabilities could be somehow interpreted as relative frequencies of occurrence of some event or as proportions of some population) and one would say that \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' are [[statistical independence|independent]] random variables.\n\nBy contrast, in a [[Bayesian probability|Bayesian]] approach to statistical inference, one would assign a probability distribution to \'\'p\'\' regardless of the non-existence of any such \"frequency\" interpretation, and one would construe the probabilities as degrees of belief that \'\'p\'\' is in any interval to which a probability is assigned. In that model, the random variables \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' are \'\'not\'\' independent, but they are \'\'\'conditionally independent\'\'\' given the value of \'\'p\'\'. In particular, if a large number of the \'\'X\'\'s are observed to be equal to 1, that would imply a high conditional probability, given that observation, that \'\'p\'\' is near 1, and thus a high conditional probability, given that observation, that the \'\'next\'\' \'\'X\'\' to be observed will be equal to 1.\n\n==Tempo oge==\n\n[[de Finetti\'s theorem]]','',13,'Budhi','20041224214831','',0,0,1,0,0.667884465152,'20041224214831','79958775785168'); INSERT INTO cur VALUES (1334,0,'Analisa_conjoint','\'\'\'Analisa conjoint\'\'\', disebut model komposisi multi-attribute, nyaeta teknik [[statistik]] nu aslina tina [[mathematics|mathematical]] [[psychology]]. Ayeuna dipake di loba widang [[social science]] jeung [[applied science]] kaasup [[marketing]], [[product management]], jeung [[operations research]].\n\n\'\'Tempo oge\'\': [[Conjoint analysis (in marketing)]]\n\n{{msg:stub}}','',13,'Budhi','20040823223850','',0,0,0,0,0.174312095239,'20040823223956','79959176776149'); INSERT INTO cur VALUES (1335,0,'Control_chart','\'\'\'Kontrol chart\'\'\', oge dipikanyago salaku \'\'\'\'Shewhart chart\'\'\'\' atawa \'\'\'\'process-behaviour chart\'\'\'\' ngarupakeun alat [[statistik]] intended to assess the nature of variation in a [[process]] and to facilitate forecasting and management.\n\n==History==\n\nThe control chart was invented by [[Walter A. Shewhart]] while working for the [[Western Electric Company]]. The company\'s engineers had been seeking to improve the reliability of their telephony transmission systems. Because amplifiers and other equipment had to be buried underground, there was a business need to reduce the frequency of failures and repairs. By [[1920]] they had already realised the importance of reducing variation in a manufacturing process. Moreover, they had realised that continual process-adjustment in reaction to non-conformance actually increased variation and degraded quality. Shewhart framed the problem in terms of [[Common- and special-causes]] of variation and, on [[May 16]] [[1924]], wrote an internal memo introducing the control chart as a tool for distinguishing between the two. Shewhart stressed that bringing a production process into a state of [[statistical control]], where there is only [[Common- and special-causes|common-cause]] variation, and keeping it in control, is necessary to predict future output and to manage a process economically.\n\nIn [[1938]], [[Walter A. Shewhart|Shewhart\'s]] innovation came to the attention of [[W. Edwards Deming]], then working at the [[United States Department of Agriculture]] but about to become mathematical advisor to the [[United States Census Bureau]]. Over the next half a century, [[W. Edwards Deming|Deming]] became the foremost champion and exponent of [[Walter A. Shewhart|Shewhart\'s]] work. After the defeat of [[Japan]] at the close of [[World War II]], [[W. Edwards Deming|Deming]] served as statistical consultant to the [[SCAP|Supreme Commander of the Allied Powers]]. His ensuing involvement in Japanese life, and long career as an industrial consultant there, spread [[Walter A. Shewhart|Shewhart\'s]] thinking, and the use of the control chart, widely in Japanese manufacturing industry throughout the [[1950s]] and [[1960s]].\n\nMore recent use and development of control charts in the Shewhart-Deming tradition has been championed by [[Donald J. Wheeler]]. Control charts play a central role in the [[Six Sigma]] management strategy.\n\n==Details==\n\nA control chart is a [[run chart]] of a sequence of [[quantitative]] [[data]] with three horizontal lines drawn on the chart:\n\n*A \'\'centre line\'\', drawn at the [[process]] [[mean]];\n\n*An \'\'upper control-limit\'\' (also called an \'\'upper natural process-limit\'\' drawn three [[standard deviation]]s above the centre line; and\n\n*A \'\'lower control-limit\'\' (also called a \'\'lower natural process-limit\'\' drawn three [[standard deviation]]s below the centre line.\n\nCommon cause variation plots as an irregular pattern, mostly within the control limits. Any observations outside the limits, or patterns within, suggest (\'\'signal\'\') a [[Common- and special-causes|special-cause]] (see \'\'Rules\'\' below). The [[run chart]] provides a context in which to interpret signals and can be beneficially annotated with events in the business.\n\n\'\'picture to follow\'\'\n\n===Choice of limits===\n\n[[Walter A. Shewhart|Shewhart]] set \'\'3-sigma\'\' limits on the following basis.\n\n*The coarse result of [[Chebyshev\'s inequality]] that, for any [[probability distribution]], the [[probability]] of an outcome greater than \'\'k\'\' [[standard deviation]]s from the [[mean]] is at most 1/\'\'k\'\'2. \n\n*The finer result of the [[Vysochanskii-Petunin inequality ]], that for any [[monotonic function|unimodal]] [[probability distribution]], the [[probability]] of an outcome greater than \'\'k\'\' [[standard deviation]]s from the [[mean]] is at most 5/9\'\'k\'\'2. \n\n*The empirical investigation of sundry [[probability distribution]]s that at least 99% of observations occurred within three [[standard deviation]]s of the [[mean]].\n\n[[Walter A. Shewhart|Shewhart]] summarised he conclusions by saying:\n\n\'\'... the fact that the criterion which we happen to use has a fine ancestry in highbrow statistical theorems does not justify its use. Such justification must come from empirical evidence that it works. As the practical engineer might say, the proof of the pudding is in the eating.\'\'\n\nThough he initially experimented with limits based on [[probability distribution]]s, [[Walter A. Shewhart|Shewhart]] ultimately wrote:\n\n\'\'Some of the earliest attempts to characterise a state of statistical control were inspired by the belief that there existed a special form of frequency function\'\' f \'\'and it was early argued that the normal law characterised such a state. When the normal law was found to be inadequate, then generalised functional forms were tried. Today, however, all hopes of finding a unique functional form\'\' f \'\'are blasted.\'\'\n\nThe control chart is intended as a heuristic. [[W. Edwards Deming|Deming]] insisted that it is not an [[hypothesis test]] and is not motivated by the [[Neyman-Pearson lemma]]. He contended that the disjoint nature of [[population (statistics)|population]] and [[sampling frame]] in most industrial situations compromised the use of conventional statistical techniques. [[W. Edwards Deming|Deming]]\'s intention was to seek insights into the [[cause system]] of a [[process]] \'\'...under a wide range of unknowable circumstances, future and past ...\'\'. He claimed that, under such conditions, \'\'3-sigma\'\' limits provided \'\'... a rational and economic guide to minimum economic loss...\'\' from the two errors:\n\n#\'\'Ascribe a variation or a mistake to a special cause when in fact the cause belongs to the system (common cause).\'\'\n\n#\'\'Ascribe a variation or a mistake to the system (common causes) when in fact the cause was special.\'\'\n\n===Calculation of standard deviation===\n\nAs for the calculation of control limits, the [[simpangan baku]] required is that of the [[Common- and special-causes|common-cause]] variation in the [[process]]. Hence, the usual [[estimator]], in terms of sample variance, is not used as this estimates the total squared-error loss from both [[common- and special-causes]] of variation.\n\nMetoda sejen nu dipake dina hungan antara [[rentang (statistik)|range]] tina sampel jeung [[simpangan baku]]na diturunkeun ku [[Leonard H. C. Tippett]], an estimator which tends to be less influenced by the extreme observations which typify [[Common- and special-causes|special-cause]]s .\n\n==Rules for detecting signals==\n\nThe two most common sets are:\n\n*[[Western Electric rules]]; and\n*[[Donald J. Wheeler]]\'s rules.\n\nThere has been particular controversy as to how long a run of observations, all on the same side of the centre line, should count as a signal, with 7, 8 and 9 all being advocated by various writers.\n\nThe most important principle for choosing a set of rules is that the choice be made before the data is inspected. Choosing rules once the data have been seen tends to increase the economic losses arising from \'\'error 1\'\' owing to [[testing hypotheses suggested by the data|testing effects suggested by the data]].\n\n==Alternative bases==\n\nIn [[1935]], the [[British Standard|British Standards Institution]], under the influence of [[Egon Pearson]] and against [[Walter A. Shewhart|Shewhart]]\'s spirit, adopted control charts, replacing \'\'3-sigma\'\' limits with limits based on percentage points of the [[normal distribution]]. This move continues to be represented by [[John Oakland]] and others but has been widely deprecated by writers in the Shewhart-Deming tradition.\n\n==Criticisms==\n\nSeveral authors have criticised the control chart on the grounds that it violates the [[likelihood principle]]. However, the priniciple is itself controversial and supporters of control charts further argue that, in general, it is impossible to specify a [[likelihood function]] for a [[process]] not in [[statistical control]], especially where knowledge about the [[cause system]] of the process is weak.\n\n==Types of chart==\n\n*[[Individuals/ moving-range chart]] (\'\'ImR chart\'\' or \'\'XmR chart\'\')\n*[[XbarR chart]] (\'\'Shewhart chart\'\')\n*[[p-chart]]\n*[[np-chart]]\n*[[c-chart]]\n*[[u-chart]]\n*[[Averages as individuals chart]]\n*[[Three-way chart]]\n*[[z-chart]]\n*[[EWMA chart]] (\'\'Exponentially-Weighted Moving Average chart\'\')\n\n[http://www.itl.nist.gov/div898/handbook/pmc/pmc.htm Monitoring and Control]\n\n==Bibliography==\n\n*Deming, W E (1975) On probability as a basis for action, \'\'The American Statistician\'\', 29(4), pp146-152\n*Deming, W E (1982) \'\'Out of the Crisis: Quality, Productivity and Competitive Position\'\' ISBN 0521305535\n*Oakland, J (2002) \'\'Statistical Process Control\'\' ISBN 0750657669 \n*Shewhart, W A (1931) \'\'Economic Control of Quality of Manufactured Product\'\' ISBN 73890760\n*Shewhart, W A (1939) \'\'Statistical Method from the Viewpoint of Quality Control\'\' ISBN 0486652327\n*Wheeler, D J (2000) \'\'Normality and the Process-Behaviour Chart\'\' ISBN 0945320566\n*Wheeler, D J & Chambers, D S (1992) \'\'Understanding Statistical Process Control\'\' ISBN 0945320132\n[http://www.itl.nist.gov/div898/handbook/index.htm NIST/SEMATECH e-Handbook of Statistical Methods]','/* Calculation of standard deviation */',13,'Budhi','20041224234553','',0,0,1,0,0.485103341977,'20041224234553','79958775765446'); INSERT INTO cur VALUES (1336,0,'Harald_Cramér','\'\'\'Harald Cramér\'\'\' ([[September 25]], [[1893]] - [[October 5]], [[1985]]) nyaeta [[Sweden|Swedish]] [[mathematician]] jeung [[statistician]], hususna dina [[statistics|mathematical statistics]]. Cramér oge mere kontribusi keur sebaran [[prime number|prime]] jeung [[twin prime]].\n\n\'\'\'Tempo oge:\'\'\' [[Cramér\'s conjecture]], [[Cramér-Rao inequality]]\n\n==Tempo oge==\n* http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Cramer_Harald.html\n\n[[Category:Statisticians|Cramér, Harald]]\n\n[[sv:Harald Cramér]]','',13,'Budhi','20040820233711','',0,0,0,0,0.658879377255,'20041225235727','79959179766288'); INSERT INTO cur VALUES (1337,0,'Curve_fitting','In the [[philosophy of science]], and [[science]] generally, and in [[statistics]], the \'\'\'curve fitting problem\'\'\' is how to choose among an infinite number of curves that fit the graphically-represented [[data point]]s, normally by finding a mathmatical expresion to create the curve. \n\nThe simplest curve is said to be preferable. This is thought to be related to [[Occam\'s Razor]] in so far as there is a preference for simplicity among a family of curves just as there is a preference of simplicity among competing theories. \n\nCommonly used procedures are [[least squares]] fitting, [[linear regression]], and nonlinear regression. One of the difficulties in curve fitting is to choose the functional form of the data for parameter optimization. Computers are often used to perform curve fitting procedures. Computers do this by solving a system of equations to find the parameters of the function that minimize the squared error. The [[gradient descent]] algorithm is often used for this purpose.\n\n\n== Rujukan ==\n\nAudi, R., Ed. (1996) The Cambridge Dictionary of Philosophy. Cambridge, Cambridge University Press. curve fitting problem p.172-173.\n\n==Tumbu kaluar==\n*[http://www.ebicom.net/~dhyams/cftp.htm Curve Expert (shareware)] fits functions to data (limited to one dependant and one independent variable.) \n*[http://zunzun.com Online curve and surface fitting]\n*[http://www.systat.com TableCurve2D and TableCurve3D by Systat] automates curve fitting\n\n{{stub}}','/* References */',13,'Budhi','20040907063259','',0,0,0,0,0.658110568141,'20040907063259','79959092936740'); INSERT INTO cur VALUES (1338,0,'Cross-validation','Dina [[statistik]] \'\'\'validasi-silang\'\'\' nyaeta praktek [[partition of a set|ngabagi]] [[statistical sample|sample]] tina [[data]] kana \'\'subsampel\'\' saperti analisa ngarupakeun rarangkay mimiti dina \'\'subsample\'\' tunggal, saterusna subsamples are retained \"blind\" in order for subsequent use in confirming and validating the initial analysis.\n\nCross-validation is important in guarding against [[testing hypotheses suggested by the data]], especially where further [[statistical sample|samples]] are hazardous, costly or impossible ([[uncomfortable science]]) to collect.\n\n[[Category:Statistics]]','',13,'Budhi','20040907071724','',0,0,0,0,0.796296255568,'20040907071724','79959092928275'); INSERT INTO cur VALUES (1339,0,'Cross_tab','\'\'\'Cross tabs\'\'\' (atawa tabulasi silang) ngagambarkeun gabungan sebaran tina dua [[variable | variabel]] atawa leuwih. They are usually presented in a [[matrix (mathematics)|matrix]], called a \'\'\'contingency table\'\'\'. Whereas a frequency distribution table describes the distribution of one [[variable]], a contingency table describes the distribution of two or more variables simultaneously. It merges two or more frequency distribution tables into one. Each cell gives the number of respondents that gave that combination of responses, that is, each cell contains a single cross tabulation.\n\nThe following is an example of a 2 × 3 contingency table. The variable “Wikipedia usuage” has three categories: heavy user, light user, and non user. These categories are all inclusive so the columns sum to 100%. The other variable “intelligence” has two categories: smart, and air head. These categories are not all inclusive so the rows need not sum to 100%. Each cell gives the percentage of subjects that share that combination of traits.\n\n
\n\n
smartair head
heavy Wiki user 70%5%
light Wiki user25%35%
non Wiki user5%60%
\n\n
\n\n\'\'\'Cross tabs are frequently used because:\'\'\'\n# They are easy to understand. They appeal to people that do not understand the more sophisticated measures.\n# They can be used with any level of data: nominal, ordinal, interval, or ratio - cross tabs treat all data as if it is nominal\n# A table can provide greater insight than single statistics\n# It solves the problem of empty or sparse cells\n
\n\n\'\'\'The statistics associated with cross tabs are:\'\'\'\n*\'\'\'Chi-squared\'\'\' - This tests the statistical significance of the cross tabulations. Chi-squared should not be calculated for percentages. The cross tabs must be converted back to absolute counts (numbers) before calculating chi-squared. Chi-squared is also problematic when any cell has a joint frequency of less than five. \n*\'\'\'Contingency Coefficient\'\'\' - This tests the strength of association of the cross tabulations. It is a variant of the \'\'\'phi coefficient\'\'\' that adjusts for statistical significance. Values range from 0 (no association) to 1 (the theoretical maximum possible association). \n*\'\'\'Cramer’s V\'\'\' - This tests the strength of association of the cross tabulations. It is a variant of the \'\'\'phi coefficient\'\'\' that adjusts for the number of rows and columns. Values range from 0 (no association) to 1 (the theoretical maximum possible association). \n*\'\'\'Lambda Coefficient\'\'\' - This tests the strength of association of the cross tabulations when the variables are measured at the nominal level. Values range from 0 (no association) to 1 (the theoretical maximum possible association). \'\'\'Asymmetric lambda\'\'\' measures the percentage improvement in predicting the dependent variable. \'\'\'Symmetric lambda\'\'\' measures the percentage improvement when prediction is done in both directions. \n*\'\'\'Tau b\'\'\' - This tests the strength of association of the cross tabulations when both variables are measured at the ordinal level. It makes adjustments for ties and is most suitable for square tables. Values range from -1 (no association) to +1 (the theoretical maximum possible association). \n*\'\'\'Tau c\'\'\' - This tests the strength of association of the cross tabulations when both variables are measured at the ordinal level. It makes adjustments for ties and is most suitable for rectangular tables. Values range from -1 (no association) to +1 (the theoretical maximum possible association). \n*\'\'\'Gamma\'\'\' - This tests the strength of association of the cross tabulations when both variables are measured at the ordinal level. It makes no adjustment for either table size or ties. Values range from -1 (no association) to +1 (the theoretical maximum possible association). \n\n\n\'\'See also : [[marketing]], [[marketing research]], [[quantitative marketing research]]\'\'','',13,'Budhi','20041224115654','',0,0,1,0,0.522386441716,'20041224115654','79958775884345'); INSERT INTO cur VALUES (1341,0,'Cronbach\'s_alpha','\'\'\'Cronbach\'s α\'\'\' is a quantity defined in [[multivariate statistics]]. It has an important use as measure of the [[reliability]] of a [[psychometrics|psychometric]] instrument, since it assesses the extent to which a set of test items can be treated as measuring a single [[latent variable]]. It was first named as such in the article: Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika 1951;16:297-333, although an earlier version is the Kuder-Richardson Formula 20 (often shortened to KR-20), which is the equivalent for dichotomous items, and Louis Guttman (1945) developed the same quantity under the name lambda-2.\n\nCronbach\'s α is defined as the mean [[correlation]] between each of a set of items, all of which have been measured for every member of a sample, with the mean of all the other items. It is related to the outcome of an [[analisa varian]] of the item data into variance due to the individuals in the sample and variance due to the items. The higher the proportion of variance due to individuals, the higher Cronbach\'s α.\n\nα can take values between minus infinity and 1 (although only positive values make sense). As a rule of thumb, a proposed psychometric instrument should only be used if an α value of 0.8 or higher is obtained on a substantial sample. However the standard of reliability required varies between fields of [[psychology]]: cognitive tests (tests of [[intelligence (trait)|intelligence]] or achievement) tend to be more reliable than tests of [[attitude]]s or [[personality]]. There is also variation within fields: it is easier to construct a reliable test of a specific attitude than of a general one, for example.\n\nAlthough this description of the use of α is given in terms of psychology, the [[statistic]] can be used in any discipline.\n\nTempo oge: [[statistik]] sarta [[tiori statistik]]\n\n[[Category:Psychometrics]]','',3,'Kandar','20050208063155','',0,0,0,0,0.141488739355,'20050208063155','79949791936844'); INSERT INTO cur VALUES (1342,0,'Cricket_statistics','[[Cricket (sport)|Cricket]] nyaeta [[sport|olahraga]] nu nga-generate wilangan [[statistik]] nu loba.\n\nStatistics are recorded for each player during a match, and aggregated over a career. At the professional level, statistics for [[Test cricket]], [[one-day cricket|one-day internationals]], and [[first-class cricket]] are recorded separately. However, since Test matches are a form of first-class cricket, a player\'s first-class statistics will \'\'include\'\' his Test match statistics - but not vice versa.\n\n== General statistics ==\n* \'\'\'Matches\'\'\' (Mat): Number of matches played.\n* \'\'\'Catches\'\'\' (Ct): Number of catches taken.\n* \'\'\'Stumpings\'\'\' (St): Number of stumpings made (as a [[wicket-keeper]]).\n\n== Batting statistics ==\n* \'\'\'[[Innings]]\'\'\' (I): The number of innings in which the batsman actually batted.\n* \'\'\'Not Outs\'\'\' (NO): The number of times the batsman was not out at the conclusion of an innings.\n* \'\'\'Runs\'\'\' (R): The number of runs scored.\n* \'\'\'Highest Score\'\'\' (HS): The highest score ever made by the batsman.\n* \'\'\'[[Batting average|Batting Average]]\'\'\' (Ave): The total number of runs by the total number of innings in which the batsman was out. Ave = Runs/[I - NO]\n* \'\'\'Centuries\'\'\' (100): The number of innings in which the batsman scored one hundred runs or more.\n* \'\'\'Half-centuries\'\'\' (50): The number of innings in which the batsman scored fifty to ninety-nine runs (centuries do not count as half-centuries as well).\n* \'\'\'Balls Faced\'\'\' (BF): The total number of balls received, including no balls but not including wides.\n* \'\'\'Strike Rate\'\'\' (SR): The number of runs scored per 100 balls faced. (SR = [100 * Runs]/BF)\n\n== Bowling statistics ==\n* \'\'\'[[Over (cricket)|Over]]s\'\'\' (O): The number of overs bowled.\n* \'\'\'Balls\'\'\' (B): The number of balls bowled. Overs is more traditional, but balls is a more useful statistic because the number of balls per over has varied historically.\n* \'\'\'[[Over (cricket)|Maiden Overs]]\'\'\' (M): The number of maiden overs (overs in which the bowler conceded zero runs) bowled.\n* \'\'\'[[run (cricket)|Runs]]\'\'\' (R): The number of runs conceded.\n* \'\'\'[[Wicket]]s\'\'\' (W): The number of wickets taken.\n* \'\'\'[[No ball]]s\'\'\' (Nb): The number of no balls bowled.\n* \'\'\'[[Wide (cricket)|Wide]]s\'\'\' (Wd): The number of wides bowled.\n* \'\'\'[[bowling average|Bowling Average]]\'\'\' (Ave): The average number of runs conceded per wicket. (Ave = Runs/W)\n* \'\'\'Economy Rate\'\'\' (Econ): The average number of runs conceded per [[over (cricket)|over]]. (Econ = 6 * Runs/Balls)\n* \'\'\'Best Bowling\'\'\' (BB): The bowler\'s best bowling performance in an innings, defined as firstly the greatest number of wickets, secondly the fewest runs conceded for that number of wickets.\n* \'\'\'Five-wickets in an innings\'\'\' (5w): The number of innings in which the bowler took at least five wickets.\n* \'\'\'Ten-wickets in a match\'\'\' (10w): The number of matches in which the bowler took at least ten wickets; recorded for Tests and first-class matches only.\n* \'\'\'Strike Rate\'\'\' (SR): The average number of balls bowled per wicket taken. (SR = Balls/W)\n\n== Analysis of cricket statistics ==\n\nAlthough cricket statistics have been recorded since the late 1800s, they have mostly been regarded by fans in a traditional manner of simply comparing the numbers between players. This contrasts with [[baseball]], which generates a similar profusion of statistical records. [[Baseball statistics]] have been studied in greater detail, leading to the field of [[sabermetrics]], which has produced several new statistics expressly designed to give better indications of the relative strengths and values of players.\n\nThis sort of detailed analysis has not yet been generally applied to cricket statistics, although some statisticians are beginning to look at cricket with an eye to providing a similar depth of analysis. Professional cricket [[coach (sport)|coaches]] are using [[computer]] records of ball-by-ball play to obtain more detailed statistical analysis of player performances than ever before. However, these analyses have seen little spread into the public knowledge of the fan community.\n\nOne example of a proposed new cricket statistic is a figure to better indicate a batsman\'s value than his batting average. Since the average is somewhat inflated by the presence of any not out innings, some have argued that a more indicative statistic would be the number of runs scored per innings, regardless of whether the batsman was out or not. Although arguably achieving the goal of measuring a batsman\'s worth more accurately, this proposed statistic has mostly been ignored by cricket fans.\n\n== Dynamic and graphical statistics ==\n\nThe advent of saturation [[television]] coverage of professional cricket has provided an impetus to develop new and interesting forms of presenting statistical data to viewers. Television networks have thus invented several new ways of presenting statistics.\n\nThese include displaying two-dimensional plots of shot directions and distances on an overhead view of a cricket field, and graphs of run scoring and wicket taking numbers plotted against time or balls bowled over a career or within a match. These graphics can be changed dynamically by computer as statistics evolve during a game.\n\n[[Category:Cricket]]','',13,'Budhi','20041224224427','',0,0,1,0,0.442448606921,'20041231121518','79958775775572'); INSERT INTO cur VALUES (1343,0,'Covariance_matrix','Dina [[statistik]], \'\'\'[[covariance]] matrix\'\'\' nyaruakeun konsep [[varian]] tina hiji ka \'\'n\'\' [[dimension]], dina basa sejen, bentuk nilai-[[scalar]] [[random variable]] ka nilai-[[vector space|vector]] random variables ([[tuple]] tina variabel random skalar). Lamun \'\'X\'\' ngarupakeun nilai-skalar variabel random nu mibanda [[nilai ekspektasi]] μ mangka variance-na nyaeta\n\n:\\sigma^2={\\rm var}(X)=E((X-\\mu)^2)\n\nLamun \'\'X\'\' nyaeta hiji \'\'n\'\'-ku-1 nilai-vektor kolon variabel random whose expected value is an \'\'n\'\'-by-1 column vector μ then its variance is the \'\'n\'\'-by-\'\'n\'\' nonnegative-definite [[matrix (mathematics)|matrix]]\n\n:\\Sigma={\\rm var}(X)=E((X-\\mu)(X-\\mu)^\\top)\n\nThe entries in this matrix are the covariances between the \'\'n\'\' different scalar components of \'\'X\'\'. Since the covariance between a scalar-valued random variable and itself is its variance, it follows that, in particular, the entries on the diagonal of this matrix are the variances of the scalar components of \'\'X\'\'. This may appear to be a property of this matrix that depends on which coordinate system is chosen for the space in which the random vector \'\'X\'\' resides. However, it is true generally that if \'\'u\'\' is any unit vector, then the variance of the projection of \'\'X\'\' on \'\'u\'\' is \'\'u\'\'TΣ\'\'u\'\'. (This point is expanded upon somewhat at [http://www.wikipedia.org/wiki/Talk:Covariance_matrix]. It is a consequence of an identity that appears below.)\n\nNomenclatures differ. Some statisticians, following the probabilist [[William Feller]], call this the \'\'\'variance\'\'\' of the random vector \'\'X\'\', because it is the natural generalization to higher dimensions of the 1-dimensional variance. Others call it the \'\'\'covariance matrix\'\'\', because it is the matrix of [[covariance]]s between the scalar components of the vector \'\'X\'\'.\n\nWith scalar-valued random variables \'\'X\'\', we have the identity\n:{\\rm var}(aX)=a^2{\\rm var}(X)\nif \'\'a\'\' is constant, i.e., not random. If \'\'X\'\' is an \'\'n\'\'-by-1 column vector-valued random variable and \'\'A\'\' is an \'\'m\'\'-by-\'\'n\'\' constant (i.e., non-random) matrix, then \'\'AX\'\' is an \'\'m\'\'-by-1 column vector-valued random variable, whose variance must therefore be an \'\'m\'\'-by-\'\'m\'\' matrix. It is\n:{\\rm var}(AX)=A\\Sigma A^\\top\n\nThis covariance matrix (though very simple) is a very useful tool in many\nvery different areas. From it a [[transformation matrix]] can be derived\nthat allows one to completely decorrelate\nthe data or, from a different point of view, to find an optimal basis\nfor representing the data in a compact way.\nThis is called \'\'\'PCA\'\'\' ([[principal components analysis]]) in [[statistics]] and \'\'\'KL-Transform\'\'\' (Karhunen-Loève transform) in [[image processing]].','',13,'Budhi','20040917032513','',0,0,0,0,0.404655306323,'20040917032513','79959082967486'); INSERT INTO cur VALUES (1344,0,'Rasio_korelasi','Dina [[statistik]], \'\'\'rasio korelasi\'\'\' nyaeta ukuran hubungan antara [[statistical dispersion|dispersi statistik]] dina [[category|kategori]] individu jeung dispersi lintasan tina sakabeh populasi atawa sampel.\n\nUpamana unggal observasi nyaeta yxi numana x nembongkeun kategori nu di-observasi sarta xi nyaeta ngaran tina bagian observasi. Urang bakal nuliskeun nx keur jumlah observasi dina kategori x (teu pati penting keur nilai nu beda tina x) sarta \n:\\overline{y_x}=\\frac{\\sum_i y_{xi}}{n_x} and \\overline{y}=\\frac{\\sum_x n_x \\overline{y_x}}{\\sum_x n_x}\nmaka rasio korelasi η ([[eta]]) dihartikeun salaku \n:\\eta^2 = \\frac{\\sum_x n_x (\\overline{y_x}-\\overline{y})^2}{\\sum_{xi} (y_{xi}-\\bar{y})^2} nu bisa oge ditulis saperti \\frac{\\sigma_{\\overline{y}}^2}{\\sigma_{y}^2}.\n\nHal ieu ngarupakeun catetan penting lamun hubungan antara nilai x \\;\\ jeung nilai \\overline{y_x} linier (nu salawasna bener lamun ngan dua kamungkinan keur x) hal ieu bakal mere hasil nu sarua saperti [[correlation coefficient|koefisien korelasi]]; maka lamun taya rasio korelasi bakal leuwih gede dina besaran, sanajan angger teu leuwih ti 1 dina eta besaran. Hal ieu bisa dipake keur mutuskeun hubungan non-linier.','',13,'Budhi','20041224102752','',0,0,0,0,0.312271213304,'20041224102814','79958775897247'); INSERT INTO cur VALUES (1345,0,'Correlation_implies_causation_(logical_fallacy)','\'\'\'Correlation implies causation\'\'\', also known as \'\'\'cum hoc ergo propter hoc\'\'\', is a [[logical fallacy]] by which two events that occur together are claimed to be cause and effect. \n\nFor example:\n:\'\'Teenage boys eat lots of [[chocolate]]\'\'.\n:\'\'Teenage boys have [[acne]]\'\'.\n:\'\'Therefore, chocolate causes acne\'\'.\n\nThis argument, and any of this pattern, is an example of a false [[categorical syllogism]]. One observation about it is that the fallacy ignores the possibility that the correlation is coincidence. But we can always pick an example where the correlation is as robust as we please. If chocolate-eating and acne were strongly correlated across cultures, and remained strongly correlated for decades or centuries, it probably is not a coincidence. In that case, the fallacy ignores the possibility that there is a [[common cause]] of eating chocolate and having acne. See [[joint effect]].\n\nFor example:\n:\'\'Ice-cream sales are strongly (and robustly) correlated with crime rates\'\'. \n:\'\'Therefore, ice-cream causes crime\'\'.\n\nThe above argument commits the cum hoc ergo propter hoc fallacy, because in fact the explanation is that high temperatures increase crime rates (presumably by making people irritable) as well as ice-cream sales.\n\nAnother observation is that the direction of the causation is wrong and should be the other way around. \n\nFor example:\n:\'\'Gun ownership is correlated with crime\'\'.\n:\'\'Therefore, gun ownership leads to crime\'\'.\n\nThe facts could easily be the other way round: increase in crime could lead to more gun ownership with concerned citizens. See: [[wrong direction]].\n\nAnother example illustrating this fallacy was a study which found that British arts funding levels had an extremely close correlation with [[Antarctic]] [[penguin]] populations.\n\nThe statement \"correlation does not imply [[causation]]\" notes that it is dangerous to deduce causation from a [[statistical correlation]]. If you only have A and B, a correlation between them does not let you infer A causes B, or vice versa, much less \'deduce\' the connection. In fact, if you only have these two occurrences, even the most powerful inference techniques built on Bayesian Networks can\'t help much. But if there was a common cause, and you had that data as well, then often you can establish what the correct structure is. Likewise (and perhaps more usefully) if you have a common effect of two independent causes.\n\nBut while often ignored, the advice is often overstated, as if to say there is no way to infer causal structure from statistical data. Clearly we should not conclude that ice-cream causes criminal tendencies (or that criminals prefer ice-cream to other refreshments!), but the previous story shows that we expect the correlation to point us towards the real causal structure. Robust correlations often imply some sort of causal story, whether common cause or something more complicated. [[Hans Reichenbach]] suggested the [[Principle of the Common Cause]], which asserts basically that robust correlations have causal explanations, and if there is no causal path from A to B (or vice versa), then there must be a common cause, though possibly a remote one. \n\nReichenbach\'s principle is closely tied to the [[Causal Markov Condition]] used in [[Bayesian networks]]. The theory underlying Bayesian networks sets out conditions under which you can infer causal structure, when you have not only correlations, but also partial correlations. In that case, certain nice things happen. For example, once you consider the temperature, the correlation between ice-cream sales and crime rates vanishes, which is consistent with a common-cause (but not diagnostic of that alone).\n\nIn statistics literature this issue is often discussed under the headings of spurious correlation and [[Simpson\'s paradox]].\n\n[[David Hume]] argued that any form of causality cannot be perceived (and therefore cannot be known or proven), and instead we can only perceive correlation. However, we can use the [[Scientific method]] to rule out false causes. \n\n==Humorous example==\n\nAn entertaining demonstration of this fallacy once appeared in an episiode of \'\'[[The Simpsons]]\'\' (Season 7, \"Much Apu about Nothing\"):\n\n:Homer: Not a bear in sight. The \"Bear Patrol\" must be working like a charm!
\n:Lisa: That\'s specious reasoning, Dad.
\n:Homer: Thank you, dear.
\n:Lisa: By your logic I could claim that this rock keeps tigers away.
\n:Homer: Oh, how does it work?
\n:Lisa: It doesn\'t work.
\n:Homer: Uh-huh.
\n:Lisa: It\'s just a stupid rock. But I don\'t see any tigers around, do you?
\n:Homer: Lisa, I want to buy your rock.\n\n== Tempo oge ==\n\n* [[Post hoc]] ergo propter hoc\n\n[[Category:Logical fallacies]]','/* See also */',13,'Budhi','20040902061927','',0,0,0,0,0.333370842195,'20040904064417','79959097938072'); INSERT INTO cur VALUES (1346,0,'Hypothesis_testing','#REDIRECT [[Statistical hypothesis testing]]','',13,'Budhi','20040820231507','',0,1,0,1,0.676985252964,'20040820231507','79959179768492'); INSERT INTO cur VALUES (1347,0,'Model','\'\'\'Model\'\'\' istilah nu biasa dipake dina sababaraha widang:\n\n*Dina [[science]] jeung [[technology]], \'\'\'model\'\'\' harti abstrak atawa teori nu ngagambarkeun hiji fenomena atawa kajadian; tempo [[model (abstract)|model]]. Keur model dina kajadian husus, tempo \'\'\'[[model (economics)]]\'\'\', \'\'\'[[model (macroeconomics)]]\'\'\', \'\'\'[[model statistik]]\'\'\' jeung \'\'\'[[mathematical model]]\'\'\'.\n\n* Dina [[Neuro-linguistic programming|Neuro-linguistic programming (NLP)]] modelling refers to the systematic unpacking and sequencing of the conscious and unconscious processes - see [[Modeling (NLP)]].\n\n*In [[science]], [[technology]], and [[leisure]] for \'\'\'models\'\'\' as physical representations see [[model (physical)|model]].\n\n*For \'\'\'models\'\'\' in [[society]], [[art]], [[fashion]], and [[cosmetics]], see [[role model]], [[model (person)|model]] or [[supermodel]].\n\n*In world politics, \'\'\'MODEL\'\'\' refers to the \'\'[[Movement for Democracy in Liberia]]\'\' organization.\n\n*In [[video games]] or computer modelling, a [[Model_(game)|model]] is a fully-[[3D computer graphics|3D]], [[polygon]]al object or character.\n\n*In [[automobiles]], a \'\'\'model\'\'\' is a type of vehicle sold under a [[marque]]\n\n{{disambig}}','',13,'Budhi','20040908022428','',0,0,0,0,0.206920363105,'20040908022428','79959091977571'); INSERT INTO cur VALUES (1348,0,'Persamaan_paramétrik','[[Category:Multivariate calculus]]\n\nDina [[matematik]], \'\'\'persamaan parametrik\'\'\' nyaeta hubungan eksplisit dua atawa leuwih variabel dina watesan hiji atawa leuwih parameter bebas. Sacara abstraks, [[relation]] dijelaskeun dina bentuk [[equation]], jeung nembongkeun oge bayangan bentuk fungsi, sebutkeun, \'\'R\'\'\'\'n\'\'. Sanajan kitu aya sababaraha hal anu leuwih akurat keur diartikeun salaku \'\'representasi parametrik\'\'. Tempo oge [[parameter]], [[parametrization]], [[regular parametric representation]].\n\nContona, persamaan [[parabola]] sederhana,\n\n:y=x^2,\n\nbisa di-parameterisasi ku ngagunakeun parameter bebas t, sarta disusun di bentuk\n\n:x=t,y=t^2.\n\nSanajan dina conto samemehna ampir ngadeukeutan hal \'\'trivial\'\', parameter di handap ieu milu kana [[circle]] radius a:\n\n:x\\equiv a\\cos t,y\\equiv a\\sin t.\n\nAhirna, bentuk geometri penting nu ampir teu mungkin keur ngajelaskeun persamaan tunggal tapi ngabogaan gambaran nu hade dina bentuk persamaan parametrik :\n\n:x\\equiv a\\cos t\n\n:y\\equiv a\\sin t\n\n:z\\equiv bt\n\nnumana ngajelaskeun kurva tilu-dimensi, [[helix]], nu ngabogaan radius \'\'a\'\' sarta ningkat ku 2 \\pi b satuan per turn. (Catetan yen persamaan identik dina [[plane]] keur circle; kanyataanna, helix ngan sakadar \'a circle whose ends don\'t have the same \'\'z\'\'-value\'.\n\nSababaraha gambaran di luhur umumna ditulis salaku\n\n:r(t)\\equiv(x(t),y(t),z(t))=(a\\cos t,a\\sin t, bt)\n\nCara ieu keu ngagambarkeun kurva sacara praktis tur efisien; contono, bisa [[integrate]] jeung [[differentiate]] saperti watesan kurva. Saterusna, bisa dijelaskeun [[velocity]] partikel nuturkeun pola parameter di handap ieu:\n\n:v(t)\\equiv r\'(t)=(x\'(t),y\'(t),z\'(t))=(-a\\sin t,a\\cos t, b)\n\nsarta [[acceleration]] nyaeta:\n\n:a(t)\\equiv r\'\'(t)=(x\'\'(t),y\'\'(t),z\'\'(t))=(-a\\cos t,-a\\sin t, 0)\n\nSacara umum, kurva parametrik ngaruppakeun fungsi hiji parameter bebas (umumnya dilambangkeun ku t). Parameterisasi permukaan, leuwih ilahar digunakeun saperti dina aplikasi [[vector calculus]] saperti [[Stokes\' theorem]], ngarupakeun pungsi 2 parameter, leuwih ilahar (s,t) or (u,v). \n\nConto parameter permukaan nyaeta (capless) [[cylinder]] diberekeun ku\n\n:r(u,v)\\equiv(x(u,v),y(u,v),z(u,v))=(a\\cos u,a\\sin u, v)\n\nKanyataan yen gambaran silinder ieu ngarupakeun kajadian waktu hiji persamaan nu ditempo ngagambarkeun lingkatan dina bidang, nu diijinkeun keur dicokot tina [[wiktionary:arbitrary|arbitrary]] nilai \'\'z\'\'.','',13,'Budhi','20040827032445','',0,0,0,0,0.953384625704,'20040827040927','79959172967554'); INSERT INTO cur VALUES (1349,0,'Harold_Jeffreys','Sir \'\'\'Harold Jeffreys\'\'\' ([[22 April]] [[1891]] - [[18 March]] [[1989]]) ngarupakeun matematikawan, statistikawan, geofisikawan jeung astronomiwan.\n\nAnjeunna dilahirkeun [[Fatfield]], [[County Durham]], diajar di [[Armstrong College]] di [[Newcastle-upon-Tyne]], nu bagean ti [[University of Durham]] tapi saterusna jadi [[University of Newcastle]]. Tamat ti dinya indit ka [[St John\'s College, Cambridge]] sarta jadi pangajar dina taun [[1914]]. Di [[Cambridge University]] anjeunna ngawulang [[matematik]], saterusna [[geophysics]] sarta ahirna jadi [[Plumian Professor of Astronomy]].\n\nAnjeunna nikah jeung matematikawan oge fisikawan, Bertha Swirles (1903-1999), dina taun [[1940]] sarta babarengan nulis \'\'Methods of Mathematical Physics\'\'.\n\nSalah sahiji kontribusina nyaeta [[Bayesian]] keur pendekatan [[probability]], sarta ide-na yen [[planetary core]] bumi ngarupakeun cairan. Anjeunna [[knight]]ed dina [[1953]].\n\n== Rujukan ==\n\n* Maria Carla Galavotti. \"Harold Jeffreys\' Probabilistic Epistemology: Between Logicism And Subjectivism\". \'\'British Journal for the Philosophy of Science\'\', 54(1):43-57 (March 2003). \'\'(A review of Jeffreys\' approach to probability; includes remarks on [[R.A. Fisher]], [[Frank P. Ramsey]], and [[Bruno de Finetti]]. Also online: [http://www3.oup.co.uk/phisci/hdb/Volume_54/Issue_01/default.html])\'\'\n\n==Tumbu kaluar==\n* [http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Jeffreys.html MacTutor biography]\n* [http://www.ldeo.columbia.edu/vetlesen/recipients/1962/jeffreys_bio.html Biography of Vetlesen Prize Winner - Sir Harold Jeffreys]\n* [http://www.economics.soton.ac.uk/staff/aldrich/jeffreysweb.htm Harold Jeffreys as a Statistician]','',13,'Budhi','20040823221544','',0,0,0,0,0.85521567513,'20041224120806','79959176778455'); INSERT INTO cur VALUES (1350,0,'Prior_distribution','#redirect [[prior probability]]','',13,'Budhi','20040820232643','',0,1,0,1,0.180637300564,'20040820232643','79959179767356'); INSERT INTO cur VALUES (1351,0,'Bayesian_model_comparison','#REDIRECT [[Perbandingan Bayesian model]]\n','Bayesian model comparison dipindahkeun ka Perbandingan Bayesian model',13,'Budhi','20040820234926','',0,1,0,1,0.789600720433146,'20040820234926','79959179765073'); INSERT INTO cur VALUES (1353,0,'Élmu_bahan','\'\'\'Élmu bahan\'\'\' ngawengku bagian-bagian ti [[kimia]], [[fisika]], [[géologi]], ogé [[biologi]] nu patali jeung sipat-sipat fisik, kimiawi, atawa biologis rupa-rupa bahan/matéri. Élmu ieu biasana dianggap salaku élmu terapan, sabab sipat-sipat nu diulik biasana dipatalikeun jeung tujuan industrial. \n\nMaterials science encompasses all four classes of materials, the study of each of which may be considered a separate field: metals (1) and [[metallurgy]], ceramics(2), [[semiconductor]]s and other electronic materials, polymers(3), composites (4), and [[biomaterial]]s which may consist of the materials classes 1-4. Metallurgy and ceramics have long and separate histories as engineering disciplines, but because the science that underlies these disciplines applies to all classes of materials, materials science is recognized as a distinct discipline.\n\nÉlmu bahan aya patalina jeung [[rékayasa bahan]], nu cenderung museur kana téhnik ngolah (casting, rolling, welding, [[ion implantation]], [[crystal growth]], [[thin-film deposition]], [[sintering]], [[glass]]blowing, jsb.), téhnik analitis ([[mikroskop éléktron]], [[difraksi sinar-X]], [[kalorimétri]], [[nuclear microscopy (HEFIB)]] jsb.), rancang bahan, sarta untung/rugina dina produksi industrial.\n\n== Sub-widang élmu bahan ==\n* [[Nanotéhnologi]] --- ngulik jeung nyipta bahan hasil rékayasa molekular ([[nanomaterial]]) nu strukturna dina ukuran [[nanométer]].\n* [[Kristalografi]] --- ngulik fisika kristal, kaasup\n** [[crystallographic defect|defects in crystals]], such as grain boundaries and dislocations, and their effects on physical properties;\n** téhnik [[difraksi]], pikeun idéntifikasi [[fase (fisika)|fase]].\n* [[Métalurgi]] --- ngulik logam\n* [[Keramik]]\n* [[Biomaterial]]\n* [[Kimia bahan padet]] --- ngulik kimia nu lumangsung dina bahan padet\n* [[Fisika bahan padet]] --- biasana dianggap ulikan pangaruh kuantum na bahan padet, kayaning [[semikonduktor|semikonduksi]] atawa [[superkonduktor|superkonduksi]].\n* [[Continuum mechanics]] --- the study of solids and fluids, assuming that they are continuous materials (rather than made of atoms).\n\nNote that some practitioners often consider [[rheology]] a sub-field of materials science, because it can cover any material that flows. However, a typical rheology paper covers non-Newtonian [[fluid dynamics]], so we place it as a sub-field of Continuum mechanics. See also [[granular material]].\n\n== Jejer nu patali dina fisika ==\n* [[Térmodinamik]], pikeun stabilitas, transformasi, jeung diagram fase.\n* [[Kinetik]], dilarapkeun kana laju transformasi jeung [[difusi]].\n\n== Tempo ogé ==\n* [[Timeline of materials technology]]\n* [[Bio-based material]]s\n* [[Kristal cair]]\n\n{{CabangKimia}}\n\n[[Category:Élmu alam]]\n\n[[en:Material science]] [[nl:Materiaalkunde]] [[fr:Sciences des matériaux]] [[zh:材料科学]]','',3,'Kandar','20040823095430','',0,0,0,1,0.740571803758,'20040823102334','79959176904569'); INSERT INTO cur VALUES (1354,0,'Nanotéhnologi','[[Image:Nanogear.jpg|thumb|300px|Nanotéhnologi ngembangkeun téhnologi bahan-bahan nu lalembut; ieu mangrupa modél \"gilinding nano\" nu gedéna ukur sababaraha atom.]]\n\'\'\'\'\'Nanotéhnologi\'\'\'\'\' salaku istilah koléktif nujul ka perkembangan [[téhnologi|téhnologis]] dina skala [[nanométer]], biasana 0.1-100nm (Sananométer sarua jeung sapersarébu mikrométer atawa sapersajuta miliméter). Istilah ieu kadang diterapkeun ka sakur téhnologi [[mikroskop|mikroskopik]].\nDue to the small size at which nanotechnology operates, physical phenomena not observed at the macroscopic scale dominate. These nanoscale phenomena include [[quantum mechanics | quantum]] size effects and short range forces such as [[van der Waals force]]s. Furthermore the vastly increased ratio of surface area to volume promotes surface phenomena. \nSince the progress of computers is growing expotentially it is believed that it will develop into nanotechnology in the near future.\n\nIn fiction and media, \"nanotechnology\" often refers to hypothetical [[molecular nanotechnology]] (also known as \"MNT\").\n\n==Sajarah==\n\nThe first mention of nanotechnology (not yet using that name) occurred in a talk given by [[Richard Feynman]] in 1959, entitled \'\'[[There\'s Plenty of Room at the Bottom]]\'\'. Feynman suggested a means to develop the ability to manipulate atoms and molecules \"directly\", by developing a set of one-tenth-scale machine tools analogous to those found in any machine shop. These small tools would then help to develop and operate a next generation of one-hundredth-scale machine tools, and so forth. As the sizes get smaller, we would have to redesign some tools because the relative strength of various forces would change. [[Gravity]] would become less important, surface tension would become more important, [[van der Waals]] attraction would become important, etc. Feynman mentioned these scaling issues during his talk. Nobody has yet effectively refuted the feasibility of his proposal.\n\nThe term \'Nano-Technology\' was created by Tokyo Science University professor Norio Taniguchi in 1974 to describe the precision manufacture of materials with nanometer tolerances.\nIn the 1980s the term was reinvented and its definition expanded by [[K Eric Drexler]], particularly in his 1986 book \'\'[[Engines of creation|Engines of Creation: The Coming Era of Nanotechnology]]\'\'. He explored this subject in much greater technical depth in his MIT doctoral dissertation, later expanded into \'\'Nanosystems: Molecular Machinery, Manufacturing, and Computation\'\' [http://www.zyvex.com/nanotech/nanosystems.html]. Computational methods play a key role in the field today because nanotechnologists can use them to design and simulate a wide range of molecular systems.\n\n==Bahan, parabot, jeung téhnologi anyar==\n\nPartikel atawa artéfak nu alami atawa jieunan mindeng mibanda kualitas jeung kapabilitas nu béda ti bahan makroskopikna. [[Emas]], pikeun conto, nu sacara kimiawi inert na skala normal, bisa dipaké salaku [[katalis]] kimiawi na skala nano. \n\n\'\'Tempo ogé (this list should be transformed into text eventually!):\'\' \n*\'\'[[Bucky ball]]\'\'\n*[[Tabung nano]]\n*[[Kabel nano]]\n*[[Pori nano]]\n*[[Cingcin nano]]\n\n*[[Mékanokimia]]\n*[[Nanoactuator]]\n*[[Nanobearing]]\n*[[Nanocontact]]\n*[[Nanomotor]]\n*[[Nanorotor]]\n*[[Nanosensor]]\n*[[Nanoshell]]\n*[[Nanotransistor]]\n*[[Self replication]]\n*[[Nanofactory]]\n*[[Nanomedicine]]\n*[[Bionanotechnology]]\n*[[Nanoelectronics]]\n**[[Molecular electronics]]\n**[[Nanocomputing]]\n**[[Molecular transistor]]s\n*[[Nanowhisker]]\n*[[Supramolecular assemblies]]\n*[[Self assembly]]\n*[[Nanocrystal]]s\n*[[Self organizing systems]] (monolayers, colloids)\n*[[Nanocrystallites]]\n*[[Nanosynthesis]]\n*[[Nanoporous materials]]\n*[[Nanocomposite]]\n\n==Potential risks==\nAn often cited, but not scientifically tangible worst-case scenario is the so-called [[grey goo]], a substance into which the surface objects of the earth might be transformed by amok-running, self-replicating nano-robots. Defenders point out that smaller objects are more susceptible to damage from radiation and heat (due to greater surface area-to-volume ratios): nanomachines would quickly fail when exposed to harsh climates. More realistic are criticisms that point to the potential [[toxicity]] of new classes of nanosubstances that could adversely affect the stability of [[cell wall]]s or disturb the [[immune system]] when inhaled or digested. Objective risk assessment can profit from the bulk of experience with long-known microscopic materials like carbon [[soot]] or [[asbestos]] fibres.\n\n== Rujukan ==\n===Karya rujukan nu mangpaat kiwari===\n\n*[http://www.iop.org/EJ/journal/0957-4484 Nanotechnology], jurnal éléktronik ti taun [[1990]], sadia di wéb ogé CD-ROM.\n*[http://pubs.acs.org/journals/nalefd/ Nano Letters], jurnal éléktronik wedalan American Chemical Society.\n\n===Nanotéhnologi na fiksi===\n\nNanotechnology has also become a prominent theme in [[science fiction]] [http://www.geocities.com/asnapier/nano/n-sf/], for example with the [[Borg]] in [[Star Trek]], the games [[Deus Ex]] and [[Metal Gear Solid]], [[Alexandr Lazarevich]]\' \'\'[[The NanoTech Network]]\'\' [http://www.webcenter.ru/~lazarevicha/ntn_toc.htm], [[Greg Bear]]\'s \'\'[[Blood Music]]\'\', [[Michael Crichton]]\'s \'\'Prey\'\', and [[Neal Stephenson]]\'s book \'\'[[Neal Stephenson/The Diamond Age|The Diamond Age]]\'\'.\n\n== Jejer nu patali ==\n* [[Atikan nanotéhnologi]]\n* [[Rékayasa molekular]]\n* [[Foresight Institute]]\n* [[NEMS]]\n* [[Rékayasa protéin]]\n* [[MEMS]]\n* [[Immortality]]\n\n== Inohong ==\n* [[Richard Feynman]]\n* [[K. Eric Drexler]]\n* [[Ralph Merkle]]\n* [[Richard Smalley]]\n\n== Tumbu kaluar ==\n* [http://dmoz.org/Science/Technology/Nanotechnology/ Open Directory Project] nanotechnology category *[http://www.royalsoc.ac.uk/nanotechnology/ Nanotechnology Science Policy on Nanotechnology] Report by [[Royal Society]]\n* [http://www.foresight.org/ Foresight Institute]\n* [http://www.etcgroup.org/search.asp?theme=11 ETC Group] research on social impacts and dangers of nanotechnology\n* [http://crnano.org/ Center for Responsible Nanotechnology] policy research\n* [http://www.cnsi.ucla.edu/ California Nanosystems Institute] at UCLA\n* [http://nanotech-now.com/ Nanotech Now] comprehensive portal\n* [http://www.nanotechweb.org/ Institute of Physics] nanotechnology portal\n* [http://www.howstuffworks.com/nanotechnology.htm How Stuff Works] introduction\n* [http://nanodot.org/ Nanodot] technology forum, sponsored by [[Foresight Institute]]\n* [http://www.nano.gov/ National Nanotechnology Initiative] the United States federal research and development program \n* [http://nanoDiamond.info/ NanoDiamond] atomic level design of a very high strength-to-weight ratio material\n* [http://www.foresight.org/EOC/ Engines of creation, 1986] by [[K. Eric Drexler]] online edition, formats: HTML, PDF, PDB\n* [http://www.memx.com MEMX, Inc.] MEMS firm\n* [http://www.zyvex.com/nano Zyvex Corp.] first company dedicated to building an assembler\n* [http://www.smalltimes.com/ Small Times] news about MEMS and nanotechnology\n* [http://www.sciam.com/nanotech Scientific American] nanotechnology articles\n* [http://www.iop.org/journals/nano/ Institute of Physics] nanotechnology journal\n* [http://www.ethicsweb.ca/nanotechnology/ Ethical Issues in Nanotechnology]\n* [http://disinfopedia.org/wiki.phtml?title=nanotechnology Disinfopedia] \'\'Nanotechnology\'\' as hype term\n* [http://www.nano-hive.com/ Nano-Hive: Nanospace Simulator] free software for modeling nanotech entities\n* [[PNAS]] supplement: [http://www.pnas.org/content/vol99/suppl_2/ \'\'Nanoscience: Underlying Physical Concepts and Phenomena\'\']\n* [http://www.nanoapex.com/ NanoApex LLC] News on Nanotechnology\n* [http://www.nanoaging.com/nanotechnology/ The NanoAging Institute] Anti-Aging Nanotechnology\n* [http://www.fantasyarts.net/Nanotechnology_Art.htm Nanotechnology Art] Images of actual and imagined nanotechnology\n\n\n\n{{LapangTéhnologi}}\n\n[[da:Nanoteknologi]] [[de:Nanotechnologie]] [[en:Nanotechnology]] [[es:Nanotecnología]] [[fr:Nanotechnologie]] [[ja:ナノテクノロジー]] [[nl:Nanotechnologie]] [[pl:Nanotechnologia]] [[sv:Nanoteknologi]] [[th:นาโนเทคโนโลยี]] [[zh-cn:纳米科技]]\n\n[[Category:Nanotéhnologi]]','/* Tumbu kaluar */',3,'Kandar','20040823103810','',0,0,0,0,0.111281841114,'20041101055106','79959176896189'); INSERT INTO cur VALUES (1355,10,'LapangTéhnologi','{| style=\"margin:0 auto;\" align=center width=100% id=toc\n|align=center style=\"background:#ccccff\"| \n\'\'\'Lapang utama [[téhnologi]]\'\'\'\n|align=\"center\" style=\"background:#ccccff\" |[http://en.wikipedia.org/w/wiki.phtml?title=MediaWiki:LapangTéhnologi&action=edit Edit]\n|-\n|align=center| [[Biotéhnologi]] | [[Téhnologi komputer]] | [[Rékayasa listrik]] | [[Éléktro]] | [[Mikrotéhnologi]] | [[Nanotéhnologi]] | [[Rékayasa biomédis]] | [[Energy storage]] | [[Mesin]] | [[Space technology]] | [[Téhnologi inti]] | [[Téhnologi visual]] | [[Téhnologi jeung alat militér|Téhnologi pakarang]] | [[Telekomunikasi]] | [[Angkutan]] \n|-\n|}','',3,'Kandar','20040823103244','',0,0,0,1,0.054434613816,'20040823104347','79959176896755'); INSERT INTO cur VALUES (1358,0,'Biotéhnologi','\'\'\'Biotéhnologi\'\'\' nyaéta [[téhnologi]] nu dumasar kana [[biologi]], utamana nalika dilarapkeun dina [[agrikultur]], [[élmu pangan]], jeung [[tatamba]].\n\nTi antara dadaran nu béda-béda ngeunaan biotéhnologi, nu panglengkepna dirumuskeun ku \"[[Konvénsi ngeunaan Kabinékaan Biologis]]\" Persarikatan Bangsa-bangsa (\'\'United Nations\'\', [[UN]]),\n\n:\"Biotéhnologi nyaéta larapan téhnologis naon baé nu migunakeun sistim biologis, organisme hirup, atawa turunanana, nu tujuanana pikeun ngarobah hasil atawa prosés pikeun tujuan husus.\"\n\nSalasahiji bagian biotéhnologi nyaéta digunakeunana [[organisme]] ku [[manusa]] sacara langsung pikeun ngahasilkeun, misalna, [[bir]], produk [[susu]], jeung [[kulit]]. [[Baktéri]] alami ogé aya nu dijeujeutkeun dina industri pertambangan dina \'\'[[bioleaching]]\'\'. Guna séjénna di antarana dina daur ulang, ngolah runtah, meresihan tempat-tempat nu kacemaran ku kagiatan industri ([[bioremediasi]]) atawa produksi agén \'\'[[biowar]]\'\'.\n\nAya ogé larapan biotéhnologi nu teu migunakeun organisme hirup, di antarana [[chip DNA]] nu dimangpaatkeun dina widang [[genetik]], atawa panglacak [[radioaktif]] dina widang kadokteran.\n\nNajan biotéhnologi ku masarakat awam dipatalikeun jeung [[kloning]] jeung [[rékayasa genetik]], biotéhnologi ditujukeun pikeun ngaronjatkeun alat-alat kadokteran sarta solve problems related to the production of biologically derived products, not the whimsical manipulation of life.\n\nKiwari, biotéhnologi, atawa biotéhnologi modern, mindeng dipatalikeun jeung dimangpaatkeunana [[mikroorganisme]] nu sacara genetik geus dirobah kayaning E. coli or yeast for producing substances like [[insulin]] or [[antibiotics]]. It can also refer to [[transgenic animals]] or [[transgenic plants]], such as Bt corn. Genetically altered Mammalian cells, such as [[Chinese Hamster]] ovarian cells, are also widely used to manufacture pharmaceuticals.\n\n== Sub-widang biotéhnologi ==\n\nThere are number of jargon terms for sub-fields of biotechnology. \n\n\'\'\'Red biotechnology\'\'\' is biotechnology applied to [[medical]] processes. An example would include an organism designed to produce an [[antibiotic]], or engineering genetic cures to diseases through [[genome|genomic manipulation]].\n\n\'\'\'White biotechnology\'\'\', also known as \'\'\'grey biotechnology\'\'\', is biotechnology applied to [[Industry|industrial]] processes. An example would include an organism designed to produce a useful chemical. White biotechnology tends to consume less resources that traditional processes when used to produce industrial goods.\n\n\'\'\'Green biotechnology\'\'\' is biotechnology applied to [[agricultural]] processes. An example would include an organism designed to grow under specific environmental conditions or in the presence (or absence) of certain agricultural chemicals. Green biotechnology tends to produce more environmentally friendly solutions then traditional industrial agriculture. An example of this would include a plant engineered to express a [[pesticide]], thereby eliminating the need for external application of pesticides.\n\nThe term \'\'\'blue biotechnology\'\'\' has also been used to describe the marine and aquatic applications of biotechnology, but its use is relatively rare.\n\n== Biotechnology timeline==\n\n* 8000BC Collecting of [[seed]]s for replanting. Evidence that [[Babylonians]], [[Egyptians]] and [[Romans]] used [[selective breeding]] ([[artificial selection)]] practices to improve [[livestock]].\n* 6000BC Brewing [[beer]], [[fermenting]] [[wine]], baking [[bread]] with help of [[yeast]]\n* 4000BC Chinese made [[yoghurt]] and [[cheese]] with [[lactic acid|lactic-acid-producing]] bacteria\n* 1500 Plant collecting around the world\n* [[1800]] [[Nikolai I. Vavilov]] created comprehensive research on breeding animals\n* [[1880]] Microorganisms discovered\n* [[1856]] [[Gregor Mendel]] started recombinant plant genetics\n* [[1919]] [[Karl Ereky]], a Hungarian engineer, first used the word biotechnology\n* [[1980]] Modern biotech is characterized by [[recombinant DNA technology]]. The [[prokaryote]] model, [[E. coli]], is used to produce [[insulin]] and other medicine, in human form. (About 5% of diabetics are allergic to animal insulins available before)\n* [[1992]] FDA approves of the first GM food from [[Calgene]]: \"flavor saver\" tomato\n* [[2000]] Completion of the [[Human Genome Project]]\n\n==Maskapé biotéknologi==\n\n*[[Genentech]]\n*biocon -india\n*shantha biotech-india\n*ZymoGenetics\n*Monsanto\n*AmGen\n\n==Tempo ogé==\n\n*[[biokimia]]\n*[[bioréaktor]]\n*[[rékayasa genetik]]\n*[[genetically modified food]]\n*[[intein]]\n*[[biologi molekular]]\n*[[véktor éksprési]]\n*[[biotéhnologi industri]]\n\n{{Téhnologi}}\n\n[[de:Biotechnologie]] [[en:Biotechnology]] [[fr:Biotechnologie]] [[ja:バイオテクノロジー]] [[la:Biotechnologia]] [[nl:Biotechnologie]] [[pl:Biotechnologia]]\n\n[[Category:Téhnologi]] [[Category:Lingkungan]] [[Category:Biologi]]\n[[Category:Étik]] [[Category:Biotéhnologi]]','',3,'Kandar','20041203095953','',0,0,0,0,0.972142893808,'20041203095953','79958796904046'); INSERT INTO cur VALUES (1359,6,'Uniform_pdf.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040823220700','',0,0,0,1,0.0571459252919498,'20041224032651','79959176779299'); INSERT INTO cur VALUES (1360,0,'Conjoint_analysis','#REDIRECT [[Analisa conjoint]]\n','Conjoint analysis dipindahkeun ka Analisa conjoint',13,'Budhi','20040823223956','',0,1,0,1,0.916927495893955,'20040823223956','79959176776043'); INSERT INTO cur VALUES (1361,0,'Variabel_random_diskrit','Dina [[matematik]], [[variabel random]] ngarupakeun \'\'\'diskrit\'\'\' lamun eta [[probability distribution]] oge disckrit; \'\'\'sebaran probibiliti diskrit\'\'\' lamun satemenna dikarakterisasi ku [[probability mass function]]. Mangka \'\'X\'\' variabel random diskrit lamun \n\n:\\sum_u P(X=u) = 1\n\nsalaku \'\'u\'\' ngaliwatan susunan tina sakabeh nilai mungkin variabel random \'\'X\'\'.\n\n[[Poisson distribution]], [[Bernoulli distribution]], [[sebaran binomial]], [[geometric distribution]], sarta [[negative binomial distribution]] dipikanyaho salaku sebaran probabiliti diskrit.\n\nLamun variabel random variable ngarupakeun diskrit mangka [[set]] sakabeh nilai mungkin bisa dianggap [[finite]] sarta [[countably infinite]], sabab jumlah nu teu bisa diitung unggal positive [[real number]] positip (nagrupakeun wates handap pangleutikna tina sakabeh susunan jumlah parsial) salawasna kasebar nuju takhingga.\n\n[[nl:discrete stochastische variabele]]','',13,'Budhi','20040907094841','',0,0,0,0,0.388071898086,'20040907094841','79959092905158'); INSERT INTO cur VALUES (1362,0,'Continuous_random_variable','[[pl:zmienna losowa ciągła]]\nBy one convention, [[variabel acak]] \'\'X\'\' is called \'\'\'continuous\'\'\' if its [[cumulative distribution function]] is [[continuous]]. That is equivalent to saying that Pr[\'\'X\'\' = \'\'a\'\'] = 0 for all [[real number]]s \'\'a\'\', i.e.: the probability that \'\'X\'\' attains the value \'\'a\'\' is zero, for any number \'\'a\'\'.\n\nWhile for a [[discrete random variable]] one could say that an [[event]] with [[probability]] zero is impossible, this can not be said in the case of a continuous random variable, because then no value would be possible.\n\nThis [[paradox]] is solved by realizing that the probability that \'\'X\'\' attains a value in an [[uncountable]] set (for example an [[interval (mathematics)|interval]]) can not be found by adding the probabilities for individual values.\n\nBy another convention, the term \"continuous random variable\" is reserved for random variables that have [[probability density function]]s. A random variable with the [[Cantor distribution]] is continuous according to the first convention, and according to the second, is neither continuous nor discrete nor a weighted average of continuous and discrete random variables.\n\nIn practical applications random variables are often either discrete or continuous.','',13,'Budhi','20041224114521','',0,0,1,0,0.223925120767,'20041224114521','79958775885478'); INSERT INTO cur VALUES (1363,0,'Interval','[[nl:Interval]]\nWatesan \'\'\'\'\'interval\'\'\'\'\' dipake dina sabaraha hal anu pakait jeung [[matematik]] jeung dina [[music]]:\n\nSee:\n* [[interval (mathematics)]] \n* [[interval (time)]]\n* [[interval (music)]]\n\n{{disambig}}','',13,'Budhi','20040826035206','',0,0,0,0,0.615953413125,'20040826035323','79959173964793'); INSERT INTO cur VALUES (1364,0,'Step_function','#REDIRECT [[Heaviside step function]]','',13,'Budhi','20040824004744','',0,1,0,1,0.030149464975,'20040824004827','79959175995255'); INSERT INTO cur VALUES (1365,0,'Heaviside_step_function','[[de:Heaviside-Funktion]]\n[[fr:Fonction d\'étape de Heaviside]]\n[[ja:ヘヴィサイドの階段関数]] [[pl:Funkcja skokowa Heaviside\'a]]\n\n
[[Image:HeavisideStepFunction.png|The Heaviside step function]]
\n\n\'\'\'Fungsi Heaviside step\'\'\', ngaran nu dipake keur ngahargaan [[Oliver Heaviside]], is a [[continuous|discontinuous]] [[Fungsi (matematik)|function]] whose value is [[zero]] for negative inputs and [[one]] elsewhere:\n:H(x)=\\left\\{\\begin{matrix} 0 : x < 0 \\\\ 1 : x \\ge 0 \\end{matrix}\\right. \n\nThe function is used in the mathematics of [[signal processing]] to represent a signal that switches on at a specified time and stays switched on indefinitely. Its [[derivative]] is formally the [[Dirac delta function]].\n\nIt is the [[cumulative distribution function]] of a [[variabel acak]] which is [[almost surely]] 0. (See [[constant random variable]].)\n\nThe Heaviside function is the integral of the [[Dirac delta function]]. The value of H(0) is of very little importance, since the function is often used within an [[integration|integral]]. Some writers give H(0) = 0, some H(0) = 1. H(0) = 0.5 is often used, since it maximizes the [[symmetry]] of the function. This makes the definition:\n\n:H(x)=\\left\\{\\begin{matrix} 0 : x < 0 \\\\ \\frac{1}{2} : x = 0 \\\\ 1 : x > 0 \\end{matrix}\\right. \n\nThis is sometimes notated by a subscript, as in H0.5(x), which means that H(0) = 0.5. This notation is also used to represent a completely different concept, however; an x offset:\n\n:H_c(x) = H(x - c)\\,\\!\n\nwhere \'\'c\'\' is a positive offset in the \'\'x\'\'-dimension of the transition from 0 to 1. In other words, \'\'H\'\'3(\'\'x\'\') = \'\'H\'\'(\'\'x\'\' − 3) would be zero until \'\'x\'\' = 3, and would transition to 1 for \'\'x\'\' > 3. The meaning of the subscript should be given in context.\n\nThe question of the [[Fourier transform]] of H is an interesting example for the theory of [[distribution]]s. It is often stated that it is 1/x, up to a [[normalizing constant]]. But near x=0 that cannot be justified: the definition must be given in terms of \'\'[[Cauchy principal value|principal value]]\'\' limit, and the transform isn\'t to be treated simply as a function. The corresponding [[convolution|convolution operator]] is the \'\'[[Hilbert transform]]\'\'.\n\nOften an integral representation of the step function is useful,\n:H(x)=-{1\\over 2i\\pi}\\int_{-\\infty}^\\infty {d\\tau \\over \\tau+i\\epsilon} \ne^{-i\\tau x},\nin the limit \\epsilon\\to 0.\n\n\n== Related topics ==\n* [[Step response]]\n* [[Negative and non-negative numbers]]','',13,'Budhi','20041224213835','',0,0,1,0,0.129961109315,'20041224213835','79958775786164'); INSERT INTO cur VALUES (1366,0,'Programming_language',':\'\'An alternate rewrite has been has been [[User:K.lee/Programming_language_rewrite|proposed]]. Please refer to it for large rewrites.\'\'\n----\n\'\'\'Basa program\'\'\' atawa \'\'\'basa komputer\'\'\' nyaeta teknik komunikasi standar keur mere parentah ka [[computer|komputer]]. It is a set of [[syntax|syntactic]] and [[semantic]] rules used to define [[computer program]]s. A language enables a programmer to precisely specify what data a computer will act upon, how these data will be stored/transmitted, and precisely what [[algorithm|actions]] to take under various circumstances.\n\n\n\n==Features of a programming language==\nEach programming language can be thought of as a set of formal specifications concerning syntax, vocabulary, and meaning.\n\nThese specifications usually include:\n* Data and Data Structures\n* Instruction and [[Control flow|Control Flow]] \n* Reference Mechanisms and Re-use \n* Design Philosophy \n\nMost languages that are widely used, or have been used for a considerable period of time, have standardization bodies that meet regularly to create and publish formal definitions of the language, and discuss extending or supplementing the already extant definitions.\n\n===Data types and data structures===\nInternally, all data in a modern digital computer are stored simply as zeros or ones ([[Binary numeral system|binary]]). The data typically represent information in the real world such as names, bank accounts and measurements and so the low-level binary data are organised by programming languages into these high-level concepts.\n\nThe particular system by which data are organized in a program is the \'\'[[datatype|type system]]\'\' of the programming language; the design and study of type systems is known as [[type theory]]. Languages can be classified as \'\'[[static typing|statically typed]]\'\' systems, and \'\'[[dynamic typing|dynamically typed]]\'\' languages. Statically-typed languages can be further subdivided into languages with manifest types, where each variable and function declaration has its type explicitly declared, and \'\'type-inferred\'\' languages. It is possible to perform type inference on programs written in a dynamically-typed language, but it is entirely possible to write programs in these languages that make type inference infeasible. Sometimes type-inferred and dynamically-typed languages are called \'\'[[latent typing|latently typed]]\'\'.\n\nWith statically-typed languages, there usually are pre-defined types for individual pieces of data (such as numbers within a certain range, strings of letters, etc.), and programmatically named values (variables) can have only one fixed type, and allow only certain operations: numbers cannot change into names and vice versa. Examples of these languages are: [[C programming language|C]], [[C Plus Plus|C++]] and [[Java programming language|Java]].\n\nDynamically-typed languages treat all data locations interchangeably, so inappropriate operations (like adding names, or sorting numbers alphabetically) will not cause errors until run-time. Examples of these languages are:\n[[Objective-C]], [[Lisp programming language|Lisp]], [[JavaScript]], [[Tcl]] and [[Prolog]].\n\nType-inferred languages superficially treat all data as not having a type, but actually do sophisticated analysis of the way the program uses the data to determine which elementary operations are performed on the data, and therefore deduce what type the variables have at compile-time. Type-inferred languages can be more flexible to use, while creating more efficient programs; however, this capability is difficult to include in a programming language implementation, so it is relatively rare. Examples of these languages are: [[Haskell programming language|Haskell]], [[MUMPS]] and [[ML programming language|ML]].\n\nStrongly typed languages do not permit the usage of values as different types; they are rigorous about detecting incorrect type usage, either at runtime for dynamically typed languages, or at compile time for statically typed languages. [[Ada programming language|Ada]], [[Java programming language|Java]], [[ML programming language|ML]], and [[Python programming language|Python]] are examples of strongly typed languages. \n\nWeakly typed languages do not strictly enforce type rules or have an explicit type-violation mechanism, often allowing for undefined behavior, segmentation violations, or other unsafe behavior if types are assigned incorrectly. [[C programming language|C]], [[assembly language]], [[C plus plus|C++]], and [[Tcl]] are examples of weakly typed languages.\n\nNote that \'\'strong\'\' vs. \'\'weak\'\' is a continuum; [[Java programming language|Java]] is a strongly typed language relative to [[C programming language|C]], but is weakly typed relative to [[ML programming language|ML]]. Use of these terms is often a matter of perspective, much in the way that an [[assembly language]] programmer would consider [[C programming language|C]] to be a [[High-level programming language|high-level language]] while a [[Java programming language|Java]] programmer would consider [[C programming language|C]] to be a [[Low-level programming language|low-level language]].\n\nNote that \'\'strong\'\' and \'\'static\'\' are orthogonal concepts. [[Java programming language|Java]] is a strongly, statically typed language. [[C programming language|C]] is a weakly, statically typed language. [[Python programming language|Python]] is a strongly, dynamically typed language. [[Tcl]] is a weakly, dynamically typed language. But beware that some people incorrectly use the term \'\'strongly typed\'\' to mean \'\'strongly, statically typed\'\', or, even more confusingly, to mean simply \'\'statically typed\'\'--in the latter usage, [[C programming language|C]] would be called \'\'strongly typed\'\', despite the fact that [[C programming language|C]] doesn\'t catch that many type errors and that it\'s both trivial and common to defeat its type system (even accidentally).\n\nMost languages also provide ways to assemble complex [[data structure]]s from built-in types and to associate names with these new combined types (using arrays, lists, stacks, files). \n\n[[Object orientation|Object oriented]] languages allow the programmer to define data-types called \"Objects\" which have their own intrinsic functions and variables (called methods and attributes respectively). A program containing objects allows the objects to operate as independent but interacting sub-programs: this interaction can be designed at coding time to model or simulate real-life interacting objects. This is a very useful, and intuitive, functionality. Programs such as [[Python programming language|Python]] and [[Ruby programming language|Ruby]] have developed as OO (Object oriented) languages. They are comparatively easy to learn and to use, and are gaining popularity in professional programming circles, as well as being accessible to non-professionals. These more intuitive languages have increased the public availability and power of customised computer applications.\n\nAside from when and how the correspondence between expressions and types is determined, there\'s also the crucial question of what types the language defines at all, and what types it allows as the values of expressions (\'\'expressed values\'\') and as named values (\'\'denoted values\'\'). Low-level languages like C typically allow programs to name memory locations, regions of memory, and compile-time constants, while allowing expressions to return values that fit into machine registers; ANSI C extended this by allowing expressions to return \'\'struct\'\' values as well (see [[record (computer science)|record]]). [[functional programming|Functional languages]] often allow variables to name run-time computed values directly instead of naming memory locations where values may be stored. Languages that use [[Computer memory garbage collection|garbage collection]] are free to allow arbitrarily complex data structures as both expressed and denoted values. \n\nFinally, in some languages, procedures are allowed only as denoted values (they cannot be returned by expressions or bound to new names); in others, they can be passed as parameters to routines, but cannot otherwise be bound to new names; in others, they are as freely usable as any expressed value, but new ones cannot be created at run-time; and in still others, they are first-class values that can be created at run-time.\n\n===Instruction and control flow===\nOnce data has been specified, the machine must be instructed how to perform operations on the data. Elementary statements may be specified using keywords or may be indicated using some well-defined grammatical structure. \nEach language takes units of these well-behaved statements and combines them using some ordering system. Depending on the language, differing methods of grouping these elementary statements exist. This allows one to write programs that are able to cover a variety of input, instead of being limited to a small number of cases. Furthermore, beyond the data manipulation instructions, other typical instructions in a language are those used for [[Control flow|control flow]] (branches, definitions by cases, loops, backtracking, functional composition). \n\n\n\n===Design philosophies===\nFor the above-mentioned purposes, each language has been developed using a special design or philosophy. \nSome aspect or another is particularly stressed by the way the language uses data structures, or by which its special notation encourages certain ways of solving problems or expressing their structure. \n\nSince programming languages are artificial languages, they require a high degree of discipline to accurately specify which operations are desired. Programming languages are not error tolerant; however, the burden of recognising and using the special vocabulary is reduced by help messages generated by the programming language implementation.\nThere are a few languages which offer a high degree of freedom in allowing self-modification in which a program re-writes parts of itself to handle new cases. Typically, only machine language and members of the [[Lisp programming language|Lisp family]] ([[Common Lisp]], [[Scheme programming language|Scheme]]) provide this capability. Some languages such as [[MUMPS]] and is called [[dynamic recompilation]]; [[emulator]]s and other [[virtual machine]]s exploit this technique for greater performance.\n\nThere are a variety of ways to classify programming languages. \nThe distinctions are not clear-cut; a particular language standard may be implemented in multiple classifications. \nFor example, a language may have both compiled and interpreted implementations.\n\nIn addition, most compiled languages contain some run-time interpreted features. The most notable example is the familiar I/O format string, which is written in a specialized, little language and which is used to describe how to convert program data to or from an external representation. This string is typically interpreted at run time by a specialized format-language interpreter program included in the run-time support libraries. Many programmers have found the flexibility of this arrangement to be very valuable.\n\n==History of programming languages==\nThe development of programming languages , unsurprisingly, follows closely the development of the physical and electronic processes used in today\'s computers.\n\n[[Charles Babbage]] is often credited with designing the first computer-like machines, which had several programs written for them (in the equivalent of [[assembly language]]) by [[Ada Lovelace]]. \n\n[[Alan Turing]] used the theoretical construct of a [[Turing machine]] which behaves in principle in all relevant ways like modern computers, according to the low level program which is input. \n\nIn the [[1940s]] the first recognisably modern, electrically powered computers were created. Some military calculation needs were a driving force in early computer development, such as encryption, decryption, trajectory calculation and massive number crunching needed in the development of atomic bombs. At that time, computers were extremely large, slow and expensive: advances in electronic technology in the post-war years led to the construction of more practical electronic computers. At that time only [[Konrad Zuse]] imagined the use of a programming language (developed eventually as [[Plankalkül]]) like those of today for solving problems.\n\nSubsequent breakthroughs in electronic technology (transistors, integrated circuits, and chips) drove the development of increasingly reliable and more usable computers. This was paralleled by the development of a variety of standardised computer languages to run on them. The improved availability and ease of use of computers led to a much wider circle of people who can deal with computers. The subsequent explosive development has resulted in the Internet, the ubiquity of personal computers, and increased use of computer programming, through more accessible languages such as [[Python programming language|Python]], [[Visual Basic]], etc..\n\n\n\n==Classifications of programming languages==\n* [[Agile programming language]]\n* [[Array programming language]]\n* [[Concatenative programming language]]\n* [[Concurrent programming language]]\n* [[Declarative programming language]]\n* [[Domain-specific programming language]]\n* [[Dynamic programming language]]\n* [[Educational programming language]]\n* [[Esoteric programming language]]\n* [[Functional programming language]]\n* [[General-purpose programming language]]\n* [[Logical programming|Logic programming language]]\n* [[Object-oriented programming language]]\n* [[Procedural programming language]]\n* [[Scripting programming language]]\n\n==Major Languages==\nThe following are major programming languages used by at least several thousand programmers worldwide:\n{{List_of_programming_languages}}\n\n==Formal semantics==\nThe rigorous definition of the meaning of programming languages is the subject of [[Formal semantics]].\n\n==Tempo oge==\n*\'\'\'List of programming languages\'\'\'\n**[[Alphabetical list of programming languages]]\n**[[Categorical list of programming languages]]\n**[[Programming language timeline|Chronological list of programming languages]]\n**[[Generational list of programming languages]]\n**[[List of esoteric programming languages]]\n*[[Compiler]]\n*[[binding (computer science)|binding]]\n*[[Hello world program]], examples of a simple program in many different programming languages\n*[[Software engineering]] and [[List of software engineering topics]]\n\n== Tumbu kaluar ==\n*[http://merd.sourceforge.net/pixel/language-study/syntax-across-languages/ Syntax Patterns for Various Languages]\n*[http://sources.wikipedia.org/Source_code Wikisource Source Code Examples]\n*[http://www.99-bottles-of-beer.net/ 99 Bottles of Beer] - One application written in 621 different programming languages.\n*[http://dmoz.org/Computers/Programming/Languages/ Open Directory - Computer Programming Languages]\n\n[[Category:Computer terminology]]\n[[Category:Programming]]\n\n[[af:Programmeertaal]]\n[[bg:Език за програмиране]]\n[[ca:Llenguatge Informàtic]]\n[[cs:Programov%C3%A1n%C3%AD]]\n[[da:Programmeringssprog]]\n[[de:Programmiersprache]]\n[[et:Programmeerimiskeel]]\n[[eo:Komputillingvo]]\n[[es:Lenguaje de programación]]\n[[fr:Programmation]]\n[[he:שפת תכנות]] \n[[ia:Linguage de programmation]]\n[[ja:プログラミング言語]]\n[[ko:프로그래밍]]\n[[lt:Programavimo kalba]]\n[[nl:Programmeertaal]]\n[[no:Programmeringsspråk]]\n[[pl:J%EAzyk programowania]]\n[[pt:Linguagens_de_programa%C3%A7%C3%A3o]]\n[[fi:Ohjelmointikieli]]\n[[sv:Programmeringsspråk]]\n[[tokipona:toki pali]]\n[[zh-cn:%E7%A8%8B%E5%BA%8F%E8%AE%BE%E8%AE%A1%E8%AF%AD%E8%A8%80]]\n[[zh-tw:程式設計語言]]','',13,'Budhi','20041225233631','',0,0,1,0,0.09146089437,'20041231121518','79958774766368'); INSERT INTO cur VALUES (1367,0,'Pseudorandom_number_sequence','\'\'\'Pseudorandom number sequence\'\'\' is a [[sequence]] of numbers that has been computed by some defined arithmetic process but is effectively a [[random number]] sequence for the purpose for which it is required. \n\nAlthough a pseudorandom number sequence in this sense often appears to lack any definite pattern, any pseudorandom number generator with a finite internal state will repeat after a very long sequence of numbers. This can be proved using the [[pigeonhole principle]]. \n\n\'\'Tempo oge:\'\' [[Pseudorandom number generator]].','',13,'Budhi','20040824005500','',0,0,0,0,0.61385717225,'20040824005500','79959175994499'); INSERT INTO cur VALUES (1368,0,'Ajén-P','Dina [[statistik]], \'\'\'nilai-p\'\'\' tina variabel random T nyaeta [[probability theory|probability]] Pr(T ≤ tobserved) numana T bakal dianggap leuwih gede atawa sarua jeung nilai observasi tobserved, dina kayaan [[null hypothesis]] dianggap bener.\n\nDina basa sejen, anggapan yen null hypothesis sederhana ditolak lamun tes [[statistic]] \'\'T\'\' leuwih gede tinimbang nilai kritis \'\'c\'\'. Kira-kira dina sabagean kasus T nu di-observasi sarua jeung tobserved. Mangka nilai-p tina T dina eta kasus probabiliti yen T bakal sarua atawa leuwih ti tobserved.\n\nThe p-value does not depend on unobservable parameters, but only on the data, i.e., it is observable; it is a \"statistic.\" In classical frequentist inference, one rejects the null hypothesis if the p-value is smaller than a number called the \'\'level\'\' of the test. In effect, the p-value itself is then being used as the test statistic. If the level is 0.05, then the probability that the p-value is less than 0.05, given that the null hypothesis is true, is 0.05, provided the test statistic has a continuous distribution. In that case, the p-value is [[sebaran seragam|uniformly distributed]] if the null hypothesis is true.\n\n==Frequent misunderstandings==\n\nThere are several common misunderstandings about p-values. All of the following statements are \'\'\'FALSE\'\'\': \n\na) The p-value is the probability that the [[null hypothesis]] is true, justifying the \"rule\" of considering as significant p-values closer to 0 (zero). \n\nComment: In fact, [[frequentism|frequentist statistics]] does not, and cannot, attach probabilities to hypotheses. Comparison of Bayesian and classical approaches shows that p can be very close to zero while the posterior probability of the null is very close to unity. This is the \'\'\'Jeffreys-Lindley Paradox\'\'\'.\n\nb)The p-value is the probability of falsely rejecting the null hypothesis. This error is called the [[prosecutor\'s fallacy]].\n\nComment: Suppose one selects the 5% significance level. The Type I error rate is the \'\'\'average\'\'\' value over all possible outcomes of the p-value in the range 0 to 0.05. If after carrying out the calculation the p-value is computed to be, say, 0.049999 then the Type I error rate is in fact around 29%. On the other hand, if the p-value is very close to zero then the Type I error rate is much lower than 5%.\n\nc) The p-value is the probability that a replicating experiment would not yield the same conclusion.\n\n==Rujukan==\n\n\"Calibration of P-values for Testing Precise Null Hypotheses\". Sellke, T., Bayarri, M.J. and Berger, J. (2001) \'\'The American Statistician\'\' (55), 62--71.','',13,'Budhi','20041224032000','',0,0,1,0,0.60949597117,'20041224120634','79958775967999'); INSERT INTO cur VALUES (1369,0,'Inverse_transform_sampling_method','The \'\'\'inverse transform sampling method\'\'\' is a method of sampling a number at\nrandom from any [[probability distribution]], given its [[cumulative distribution function]] (cdf).\n\nThe problem that the inverse transform sampling method solves is as follows:\n\n*Anggap X bakal jadi [[variabel acak]] numana sebaranna bisa dijelaskeun ku cdf d(\'\'x\'\').\n*We want to generate values of \'\'x\'\' which are distributed according to this distribution.\n\nMany [[programming language]]s have the ability to generate [[pseudorandom number sequence|pseudo-randomnumbers]] which are effectively distributed according to the standard [[sebaran seragam]]. If a random variable has that distribution, then the probability of its falling within any subinterval (\'\'a\'\', \'\'b\'\') of the interval from 0 to 1 is just the length \'\'b\'\' - \'\'a\'\' of that subinterval.\n\nThe inverse transform sampling method works as follows:\n#Generate a random number from the standard uniform distribution; call this \'\'u\'\'.\n#Compute the value for \'\'x\'\' which has the associated cdf value \'\'u\'\'; call this \'\'x\'\'\'\'chosen\'\'.\n#Take \'\'x\'\'\'\'chosen\'\' to be the random number drawn from the distribution described by d(\'\'x\'\').\n\nThe following diagram may help the reader to visualise how the method works:\n\n[[image:inverse_transform_sampling.png]]\n\n
\'\'\'Sampling using the inverse transform method\'\'\'
\n\n=== See also ===\nThe [[rejection sampling method]].','',13,'Budhi','20041224214737','',0,0,1,0,0.616237483274,'20041224214737','79958775785262'); INSERT INTO cur VALUES (1370,0,'Rejection_sampling','For sampling values from an arbitrary [[probability distribution]] function\n\nAlso called the \'\'\'acceptance-rejection method\'\'\'.','',13,'Budhi','20040824005853','',0,0,0,1,0.07685597943,'20040824005853','79959175994146'); INSERT INTO cur VALUES (1371,0,'Box-Muller_transformation','#REDIRECT [[Box-Muller transform]]','',13,'Budhi','20040824010021','',0,1,0,1,0.638984372206,'20040824010058','79959175989978'); INSERT INTO cur VALUES (1372,0,'Box-Muller_transform','A \'\'\'Box-Muller transform\'\'\' is a method of generating pairs of [[statistical independence|independent]] [[normal distribution|normally distributed]] [[random number]]s, given a source of [[sebaran seragam|uniformly distributed]] random numbers. There are two kinds:\n\n#Given \'\'r\'\' and \'\'φ\'\' independently uniformly distributed in (0,1], compute:\n#:z_0 = \\cos(2 \\pi \\varphi) \\cdot \\sqrt{-2 \\ln r}\n#:and \n#:z_1 = \\sin(2 \\pi \\varphi) \\cdot \\sqrt{-2 \\ln r}\n#: \n#Given \'\'x\'\' and \'\'y\'\' independently uniformly distributed in [−1,1], set \'\'R\'\' = \'\'x\'\'2 + \'\'y\'\'2. If \'\'R\'\' = 0 or \'\'R\'\' > 1, throw them away and try another pair (\'\'x\'\', \'\'y\'\'). Then, for these filtered points, compute: \n#:z_0 = x \\cdot \\sqrt{\\frac{-2 \\ln R}{R}}\n#:and \n#:z_1 = y \\cdot \\sqrt{\\frac{-2 \\ln R}{R}}\n\nThe first method uniformly distributes numbers within a unit circle with [[polar coordinates]] (\'\'r\'\',\'\'2πφ\'\'), while in the second method all points left after this filtering process will be uniformly distributed within a [[unit circle]] using [[cartesian coordinates]] (\'\'x\'\',\'\'y\'\'), with \'\'R\'\' as the square of the distance from the origin.\n\nThe second method is typically faster because it uses only one [[transcendental function]] instead of at least two, even though it throws away 1-π/4 ≈ 21.46% of the total input uniformly distributed random number pairs generated, i.e. throws away 4/π−1 ≈ 0.2732 uniformly distributed random number pairs per [[Topics named after Carl Friedrich Gauss|Gaussian]] random number pair generated, requiring 4/π ≈ 1.2732 input random numbers per output random number.\n\n== Tumbu kaluar ==\n* [http://www.taygeta.com/random/gaussian.html Generating Gaussian Random Numbers]','',13,'Budhi','20041224032500','',0,0,1,0,0.408198629696,'20041224032500','79958775967499'); INSERT INTO cur VALUES (1373,0,'Research_subject','#REDIRECT [[Subjék panalungtikan]]\n','Research subject dipindahkeun ka Subjék panalungtikan',3,'Kandar','20040824090936','',0,1,0,1,0.413199734327569,'20040824090936','79959175909063'); INSERT INTO cur VALUES (1374,0,'Informed_consent','\'\'\'Informed consent\'\'\' is a [[law|legal]] condition whereby a person can be said to have given [[consent]] based upon a full appreciation and understanding of the facts and implications of any actions, with the individual being in possession of all of their faculties (not [[mentally retarded]] or [[mentally ill]]), and their [[judgment]] not being [[impaired]] at the time of consenting (by [[sleep]]iness, [[intoxication]] by [[alcohol]] or [[drug]]s, other [[health]] problems, etc.).\n\nIn many countries, people cannot give informed consent until they reach a certain age.\nThe argument is that as a child the person might be incapable of comprehending the arguments and information, and thus could give consent, but even after the act of informing the child the consent would not be considered as based on being informed. The term [[age of consent]] is especially applied to consenting to [[sexual act]]s.\n\n\nSome acts can not legally take place because of a lack of informed consent, e.g. sexual acts, in other cases consent of legal parents or guardians of a child on its behalf is valid.\n\nPeople must give informed consent before medical operations, and doctors have been [[struck off]] in the [[United Kingdom]] for not giving their patients a full awareness of the risks associated with such things as medical trials of new medications and operations.\nIn one case a doctor performing routine surgery on a woman noticed that she had cancerous tissue in her womb.\nHe took the decision to remove the woman\'s womb, however as she had not given informed consent for this operation, the doctor was judged by the [[General Medical Council]] to have acted negligently.\nThe council said that the woman should have been informed of her condition, and allowed to make her own decision.\n\nThe question of whether informed consent needs to be formally given before [[sexual intercourse]] or other sexual activity, and whether this consent can be withdrawn at any time during the act, is an issue which is currently being discussed in the United States in regard to [[rape]] and [[sexual assault]] legislation.\n\nIt may not be possible to give consent to certain activities in certain jurisdictions; see the [[Operation Spanner]] case for an example of this in the UK.\n\nInformed consent is also important in [[Social research|social research]]. For example in [[Survey research|survey research]], people need to give informed consent before they participate in the survey.\n\nTempo ogé:\n* [[Safe, sane and consensual]]\n* [[Consensual crime]]\n\n[[de:Informed consent]]\n[[es:consentimiento informado]]\n[[ja:%E3%82%A4%E3%83%B3%E3%83%95%E3%82%A9%E3%83%BC%E3%83%A0%E3%83%89%E3%83%BB%E3%82%B3%E3%83%B3%E3%82%BB%E3%83%B3%E3%83%88]]','',13,'Budhi','20050101220942','',0,0,0,0,0.301449660818,'20050101220942','79949898779057'); INSERT INTO cur VALUES (1375,0,'Uniform_distribution','#REDIRECT [[Sebaran seragam]]\n','Uniform distribution dipindahkeun ka Sebaran seragam',13,'Budhi','20040824215619','',0,1,0,1,0.315216214689628,'20040824215619','79959175784380'); INSERT INTO cur VALUES (1376,6,'Bahamsagital.png','Ti \'\'Gray\'s Anatomy\'\' édisi 1918','Ti \'\'Gray\'s Anatomy\'\' édisi 1918',3,'Kandar','20040825095441','',0,0,0,1,0.336481901199074,'20050315050829','79959174904558'); INSERT INTO cur VALUES (1377,10,'SistimDigéstif','
\n{| style=\"margin:0 auto;\" align=center width=\"75%\" id=toc\n|align=center style=\"background:#ccccff\"| \'\'\'[[Sistim digéstif]]\'\'\'\n|-\n|align=center| \n[[Baham]] -\n[[Faring]] -\n[[Ésofagus]] -\n[[Burih]] -\n[[Pankréas]] -\n[[Gallbladder]] -\n[[Ati]] -\n[[Peujit leutik]] ([[duodenum]], [[yeyunum]], [[ilieum]]) - [[Kolon (anatomi)|Kolon]] -\n[[Cecum]] -\n[[Réktum]] -\n[[Bool]]\n|}','',3,'Kandar','20040825102102','',0,0,0,1,0.653347142811,'20040825102102','79959174897897'); INSERT INTO cur VALUES (1378,0,'Interval_(mathematics)','[[de:Intervall (Mathematik)]] [[fr:Intervalle (mathématiques)]] [[he:קטע (מתמטיקה)]] [[ja:区間 (数学)]] [[nl:Interval (wiskunde)]]\n[[Category:Topology]]\nIn [[elementary algebra]], an \'\'\'interval\'\'\' is a set that contains every [[real number]] between two indicated numbers, and possibly the two numbers themselves. \'\'\'Interval notation\'\'\' is where the permitted values for a [[variable]] are expressed as ranging over an interval; for example, \"5 < x < 9\" shows interval notation. By convention, the interval \"(10,20)\" stands for all real numbers between 10 and 20, not including 10 or 20. On the other hand, the interval \"[10,20]\" includes every number between 10 and 20 \'\'along with\'\' the numbers 10 and 20. Other possibilities are listed below.\n\nIn higher [[mathematics]], a formal definition is the following: An \'\'\'interval\'\'\' is a [[subset]] \'\'S\'\' of a [[total order|totally ordered set]] \'\'T\'\' with the property that whenever \'\'x\'\' and \'\'y\'\' are in \'\'S\'\' and \'\'x\'\' < \'\'z\'\' < \'\'y\'\' then \'\'z\'\' is in \'\'S\'\'.\n\nAs mentioned above, a particularly important case is when \'\'T\'\' = \'\'\'R\'\'\', the set of [[real number]]s.\n\nIntervals of \'\'\'R\'\'\' are of the following eleven different types\n(where \'\'a\'\' and \'\'b\'\' are real numbers, with \'\'a\'\' < \'\'b\'\'):\n\n# (\'\'a\'\',\'\'b\'\') = { \'\'x\'\' | \'\'a\'\' < \'\'x\'\' < \'\'b\'\' }\n# [\'\'a\'\',\'\'b\'\'] = { \'\'x\'\' | \'\'a\'\' ≤ \'\'x\'\' ≤ \'\'b\'\' }\n# [\'\'a\'\',\'\'b\'\') = { \'\'x\'\' | \'\'a\'\' ≤ \'\'x\'\' < \'\'b\'\' }\n# (\'\'a\'\',\'\'b\'\'] = { \'\'x\'\' | \'\'a\'\' < \'\'x\'\' ≤ \'\'b\'\' }\n# (\'\'a\'\',∞) = { \'\'x\'\' | \'\'x\'\' > \'\'a\'\' }\n# [\'\'a\'\',∞) = { \'\'x\'\' | \'\'x\'\' ≥ \'\'a\'\' }\n# (-∞,\'\'b\'\') = { \'\'x\'\' | \'\'x\'\' < \'\'b\'\' }\n# (-∞,\'\'b\'\'] = { \'\'x\'\' | \'\'x\'\' ≤ \'\'b\'\' }\n# (-∞,∞) = \'\'\'R\'\'\' itself, the set of all [[real number]]s\n# {\'\'a\'\'}\n# the [[empty set]]\n\nIn each case where they appear above, \'\'a\'\' and \'\'b\'\' are known as \'\'\'endpoints\'\'\' of the interval.\nNote that a square bracket [ or ] indicates that the endpoint is included in the interval, while a round bracket ( or ) indicates that it is not.\nFor more information about the notation used above, see [[Naive set theory]].\n\nIntervals of type (1), (5), (7), (9) and (11) are called \'\'\'open intervals\'\'\' (because they are [[open set]]s) and intervals (2), (6), (8), (9), (10) and (11) \'\'\'closed intervals\'\'\' (because they are [[closed set]]s).\nIntervals (3) and (4) are sometimes called \'\'\'half-closed\'\'\' (or, not surprisingly, \'\'\'half-open\'\'\') intervals.\nNotice that intervals (9) and (11) are both open \'\'and\'\' closed, which is not the same thing as being half-open and half-closed.\n\nIntervals (1), (2), (3), (4), (10) and (11) are called \'\'\'bounded intervals\'\'\' and intervals (5), (6), (7), (8) and (9) \'\'\'unbounded intervals\'\'\'.\nInterval (10) is also known as a \'\'\'singleton\'\'\'.\n\nThe \'\'\'length\'\'\' of the bounded intervals (1), (2), (3), (4) is \'\'b\'\'-\'\'a\'\' in each case. The \'\'\'total length\'\'\' of a [[sequence]] of intervals is the sum of the lengths of the intervals. No allowance is made for the [[Set theoretic intersection|intersection]] of the intervals. For instance, the total length of the [[sequence]] {(1,2),(1.5,2.5)} is 1+1=2, despite the fact that the [[Set theoretic union|union]] of the sequence is an interval of length 1.5.\n\nIntervals play an important role in the theory of [[integration]], because they are the simplest [[set]]s whose \"size\" or \"measure\" or \"length\" is easy to define (see above).\nThe concept of measure can then be extended to more complicated sets, leading to the [[Borel measure]] and eventually to the [[Lebesgue measure]].\n\nIntervals are precisely the [[connectedness|connected]] subsets of \'\'\'R\'\'\'. They are also precisely the [[convex]] subsets of \'\'\'R\'\'\'.\nSince a [[continuous]] image of a connected set is connected,\nit follows that if \'\'f\'\': \'\'\'R\'\'\'→\'\'\'R\'\'\' is a continuous function and \'\'I\'\' is an interval, then its image \'\'f\'\'(\'\'I\'\') is also an interval.\nThis is one formulation of the [[intermediate value theorem]].\n\n== Intervals in partial orders ==\n\nIn [[order theory]], one usually considers [[partially ordered set]]s. However, the above notations and definitions can immediately be applied to this general case as well. Of special interest in this general setting are intervals of the form [\'\'a\'\',\'\'b\'\'].\n\nFor a partially ordered set (\'\'P\'\', ≤) and two elements \'\'a\'\' and \'\'b\'\' of \'\'P\'\', one defines the set\n: [\'\'a\'\', \'\'b\'\'] = { \'\'x\'\' | \'\'a\'\' ≤ \'\'x\'\' ≤ \'\'b\'\' }\nOne may choose to restrict this definition to pairs of elements with the property that \'\'a\'\' ≤ \'\'b\'\'. Alternatively, the intervals without this condition will just coincide with the [[empty set]], which in the former case would not be considered as an interval.\n\n== Interval arithmetic ==\n\n\'\'\'Interval arithmetic\'\'\', also called \'\'\'interval mathematics\'\'\', \'\'\'interval analysis\'\'\', and \'\'\'interval computations\'\'\', has been introduced in 1956 by M. Warmus. It defines a set of operations which can be applied on intervals :\n\nT · S = { \'\'x\'\' | there is some \'\'y\'\' in \'\'T\'\', and some \'\'z\'\' in \'\'S\'\', such that \'\'x\'\' = \'\'y\'\' · \'\'z\'\' }\n\n* [\'\'a\'\',\'\'b\'\'] + [\'\'c\'\',\'\'d\'\'] = [\'\'a\'\'+\'\'c\'\', \'\'b\'\'+\'\'d\'\']\n* [\'\'a\'\',\'\'b\'\'] - [\'\'c\'\',\'\'d\'\'] = [\'\'a\'\'-\'\'d\'\', \'\'b\'\'-\'\'c\'\']\n* [\'\'a\'\',\'\'b\'\'] * [\'\'c\'\',\'\'d\'\'] = [min (\'\'ac\'\', \'\'ad\'\', \'\'bc\'\', \'\'bd\'\'), max (\'\'ac\'\', \'\'ad\'\', \'\'bc\'\', \'\'bd\'\')]\n* [\'\'a\'\',\'\'b\'\'] / [\'\'c\'\',\'\'d\'\'] = [min (\'\'a/c\'\', \'\'a/d\'\', \'\'b/c\'\', \'\'b/d\'\'), max (\'\'a/c\'\', \'\'a/d\'\', \'\'b/c\'\', \'\'b/d\'\')]\n\nDivision by an interval containing zero is not possible.\n\nThe addition and multiplication operations are [[commutative]], [[associative]] and sub-[[distributive]]: the set \'\'X\'\' ( \'\'Y\'\' + \'\'Z\'\' ) is a subset of \'\'XY\'\' + \'\'XZ\'\'.\n\n==Notasi alternatip==\nCara sejen keur nuliskeun interval, ilaharna katempo di [[France]] sarta sababarha nagara Eropa sejenna, nyaeta:\n\n* ]\'\'a\'\',\'\'b\'\'[ = { \'\'x\'\' | \'\'a\'\' < \'\'x\'\' < \'\'b\'\' }\n* [\'\'a\'\',\'\'b\'\'] = { \'\'x\'\' | \'\'a\'\' ≤ \'\'x\'\' ≤ \'\'b\'\' }\n* [\'\'a\'\',\'\'b\'\'[ = { \'\'x\'\' | \'\'a\'\' ≤ \'\'x\'\' < \'\'b\'\' }\n* ]\'\'a\'\',\'\'b\'\'] = { \'\'x\'\' | \'\'a\'\' < \'\'x\'\' ≤ \'\'b\'\' }\n\n==Tumbu kaluar==\n\n*[http://www.cs.utep.edu/interval-comp/icompwww.html Interval computations research centers]\n\n[[Category:Order theory]]','/* Notasi alternatip */',13,'Budhi','20040904222825','',0,0,0,0,0.653395669373,'20041224115318','79959095777174'); INSERT INTO cur VALUES (1379,0,'Parametric_equation','#REDIRECT [[Persamaan parametrik]]\n','Parametric equation dipindahkeun ka Persamaan parametrik',13,'Budhi','20040827032510','',0,1,0,1,0.736760892660134,'20040827032510','79959172967489'); INSERT INTO cur VALUES (1380,0,'Persamaan_parametrik','#REDIRECT [[Persamaan paramétrik]]\n','Persamaan parametrik dipindahkeun ka Persamaan paramétrik',3,'Kandar','20040827040927','',0,1,0,1,0.674358790437094,'20040827040927','79959172959072'); INSERT INTO cur VALUES (1381,0,'Parameter','#REDIRECT [[Paraméter]]\n','Parameter dipindahkeun ka Paraméter',3,'Kandar','20040827041426','',0,1,0,1,0.161511304938711,'20040827041426','79959172958573'); INSERT INTO cur VALUES (1382,0,'Cauchy_distribution','#REDIRECT [[Sebaran Cauchy]]\n','Cauchy distribution dipindahkeun ka Sebaran Cauchy',13,'Budhi','20040827063549','',0,1,0,1,0.784480184115917,'20040827063549','79959172936450'); INSERT INTO cur VALUES (1383,8,'Acct_creation_throttle_hit','Punten, anjeun geus nyieun $1 rekening, teu bisa nyieun deui.','',3,'Kandar','20050203192255','',0,0,0,0,0.806332327801,'20050203192255','79949796807744'); INSERT INTO cur VALUES (1384,8,'Deleteimgcompletely','Hapus sadaya révisi','',3,'Kandar','20040827080502','',0,0,0,1,0.117774454466,'20040827080502','79959172919497'); INSERT INTO cur VALUES (1385,8,'Fileexists','Koropak nu ngaranna kieu geus aya, mangga parios $1 mun anjeun teu yakin rék ngaganti.','',3,'Kandar','20040904051122','',0,0,0,0,0.923119068576,'20040904051122','79959095948877'); INSERT INTO cur VALUES (1386,8,'Illegalfilename','Ngaran koropak \"$1\" ngandung aksara nu teu diwenangkeun pikeun judul kaca. Mangga gentos ngaranna tur cobi muatkeun deui.','',3,'Kandar','20040904051223','',0,0,0,0,0.665009712644,'20040904051223','79959095948776'); INSERT INTO cur VALUES (1387,8,'Newwindow','(buka na jandéla anyar)','',3,'Kandar','20040827082741','',0,0,0,1,0.279112646952,'20040827082741','79959172917258'); INSERT INTO cur VALUES (1388,8,'Nextpage','Kaca salajengna ($1)','',3,'Kandar','20040827083328','',0,0,0,1,0.675069552229,'20040827083328','79959172916671'); INSERT INTO cur VALUES (1389,8,'Qbsettingsnote','Préferénsi ieu ngan bisa jalan dina kulit \'Standard\' jeung \'CologneBlue\'.','',3,'Kandar','20040827085854','',0,0,0,1,0.891930020364,'20040827085854','79959172914145'); INSERT INTO cur VALUES (1390,0,'Sebaran_Chi-kuadrat','#REDIRECT [[Sebaran chi-kuadrat]]\n','Sebaran Chi-kuadrat dipindahkeun ka Sebaran chi-kuadrat',3,'Kandar','20040827090459','',0,1,0,1,0.437867036497097,'20040827090459','79959172909540'); INSERT INTO cur VALUES (1391,0,'Dimension','#REDIRECT [[Diménsi]]\n','Dimension dipindahkeun ka Diménsi',3,'Kandar','20040830092639','',0,1,0,1,0.835894660871378,'20040830092639','79959169907360'); INSERT INTO cur VALUES (1392,0,'Integral',': \'\'This article deals with the concept of an integral in [[mathematics|mathematical]] [[calculus]]. For other meanings of \"integral\" see [[integration]].\'\'\n\n{{Calculus}}\n\nDina [[calculus]], [[Fungsi (matematik)|fungsi]] \'\'\'integral\'\'\' ngaurapkeun \'\'generalisasi\'\' [[area]], [[mass]], [[volume]], [[sum]], sarta [[total]]. Teu siga di proses [[derivative|differentiation]], aya sababaraha harti nu beda ngeunaan integral, gumantung kana beda teknikna. Sanajan kitu, dua cara nu beda dina fungsi integrasi bakal mere hasil nu sarua lamun duanana digawekeun.\n\n[[Image:Area under curve.png|thumb|203px|Integral defined as area under a curve]]\n\nIntegral kontinyu, fungsi nilai-riil positip \'\'f\'\' tina variable riil \'\'x\'\' antara sisi kenca \'\'a\'\' sarta sisi katuhu \'\'b\'\' nembongkeun batas wewengkeun ku garis \'\'x=a\'\', \'\'x=b\'\', sumbu-\'\'x\'\', sarta kurva dihartikeun ku grapik \'\'f\'\'. Leuwih resmi, lamun anggap \'\'S\'\'={(\'\'x\'\',\'\'y\'\'):\'\'a\'\'≤\'\'x\'\'≤\'\'b\'\',0≤\'\'y\'\'≤\'\'f(x)\'\'}, mangka integral \'\'f\'\' antara \'\'a\'\' jeung \'\'b\'\' ngarupakeun [[measure]] \'\'S\'\'.\n\n[[Leibniz]] ngawanohkeun notasi baku [[long s]] keur integral. Integral dina paragrap samemegna bisa ditulis \\int_a^b f(x)\\,dx. Tanda ∫ ngalambakeun integral, \'\'a\'\' jeung \'\'b\'\' ngarupakeun titik tungtung [[interval]], \'\'f(x)\'\' nyaeta fungsi nu di-integralkeun, sarta \'\'dx\'\' notasi keur variabel integrasi. Sajarahna, \'\'dx\'\' ngagambarkeun wilangan nu takhingga, sarta s panjang singkatan keur \"jumlah\". Sanajan kitu, teori integral modern diwangun ku dasar nu beda sarta simbol tradisional ngan sakadar [[Mathematical notation|notation]]. \n[[Image:Areabetweentwographs.png|thumb|287px|Finding the area between two graphs]]\nAs an example, if \'\'f\'\' is the constant function \'\'f(x)=3\'\', then the integral of \'\'f\'\' between 0 and 10 is the area of the rectangle bounded by the lines \'\'x=\'\'0, \'\'x=\'\'10, \'\'y=\'\'0, and \'\'y=3\'\'. The area is 10\'\'c\'\', so the value of the integral is 30.\n\nIntegrals can be taken over regions other than intervals. In general, the integral over a set \'\'E\'\' of a function \'\'f\'\' is written ∫Ef(x)dx. Here \'\'x\'\' need not be a real number, but, for instance, a [[vector]] in \'\'\'R\'\'\'3. [[Fubini\'s theorem]] shows that such integrals can be rewritten as an iterated integral. In other words, the integral can be calculated by integrating one coordinate at a time.\n\nIf a function has an integral, it is said to be \'\'integrable\'\'.\nThe function for which the integral is calculated is called the \'\'\'integrand\'\'\'.\nIntegrals are sometimes called \'\'\'definite integrals\'\'\' to emphasize that they result in a number, not another function. This is to distinguish them from \'\'\'indefinite integrals\'\'\', which are another name for an [[antiderivative]].\nIf the domain of the function is the [[real number]]s, and if the region of integration is an [[interval (mathematics)|interval]], then\nthe [[infimum|greatest lower bound]] of the interval is called the \'\'lower limit of integration\'\', and the [[supremum|least upper bound]] is called the \'\'upper limit of integration\'\'.\n\n== Ngitung integrals ==\n\nThe most basic technique for computing integrals of one real variable is based on the [[Fundamental Theorem of Calculus]]. It proceeds like this:\n\n#Choose a function \'\'f(x)\'\' and an interval [\'\'a\'\',\'\'b\'\'].\n#Find an [[antiderivative]] of \'\'f\'\', that is, a function \'\'F\'\' such that \'\'F\' \'\'=\'\'f\'\'.\n#By the Fundamental Theorem of Calculus, \\int_a^b f(x)\\,dx = F(b)-F(a).\n#Therefore the value of the integral is \'\'F(b)-F(a)\'\'.\n\nNote that the integral is not actually the antiderivative (it is a number), but the fundamental theorem allows us to use antiderivatives to evaluate integrals.\n\nThe difficult step is finding an antiderivative of \'\'f\'\'. It is rarely possible to glance at a function and write down its antiderivative. More often, it is necessary to use one of the many techniques that have been developed to evaluate integrals. Most of these techniques rewrite one integral as a different one which is hopefully more tractable. Techniques include:\n\n*[[substitution rule|Integration by substitution]]\n*[[Integration by parts]]\n*[[trigonometric substitution|Integration by trigonometric substitution]]\n*[[Partial fractions in integration|Integration by partial fractions]]\n\nEven if these techniques fail, it may still be possible to evaluate the integral. The next most common technique is [[Residue (complex analysis)|residue calculus]]. There are also many less common ways of calculating definite integrals; for instance, [[Parseval\'s identity]] can be used to transform the integral of a square into an infinite sum. Occasionally an integral can be evaluated by a trick; for an example of this, see [[Gaussian integral]].\n\nComputation of volumes of [[solid of revolution|solids of revolution]] can usually be done with [[disk integration]] or [[shell integration]].\n\nSpecific results which have been worked out by various techniques are collected in the [[list of integrals]].\n\n=== Approximation of definite integrals ===\n\nDefinite integrals may be approximated using several methods. One popular method, called the [[rectangle method]] or the [[trapezoidal rule]], relies on dividing the function into a series of rectangles and finding the sum. Another well-known method is [[Simpson\'s rule]].\n\nSome integrals cannot be found exactly, and others are so complex that finding the exact answer would be extremely time-consuming or computationally-intensive. Approximation, however, is a process which relies only on variable substitution, multiplication, addition, and division. It can be done easily and quickly by modern graphing calculators and computers. Many real-world applications of calculus rely on integral approximation because of the complexity of formulas and unnecessary nature of an exact answer.\n\n=== Integrals and computerized algebra systems ===\n\nMany professionals, educators, and students now use [[computerized algebra systems]] to make difficult (or simply tedious) algebra and calculus problems easier. The design of such a computer algebra system is nontrivial as systematic methods of antidifferentiation are difficult to formulate.\n\nOne difficulty is that it is not always possible to find \"nice formulae\" for antiderivatives. For instance, there is a (nontrivial) proof that there is no nice function (e.g., involving sin, cos, exp, polynomials, roots and so on) whose derivative is exp(-\'\'x\'\'2). As such, computerized algebra systems have no hope of being able to find an antiderivative for this particular function. Unfortunately, functions that have nice antiderivatives are the exception. If one writes a large random expression involving exponentials and polynomials, the odds are almost nil that it will have an antiderivative. (This statement can be made formal, but it is difficult to do so.)\n\nOne of the difficulties is to decide what set of functions to use as building blocks for antiderivatives. Usually, we need a set of antiderivatives closed under, say, multiplication and composition. This set of antiderivatives should also include polynomials, perhaps quotients, exponentials, logarithms, sines and cosines. The [[Risch-Norman algorithm]] is able to compute any integral of such a shape; that is, if the antiderivative involves polynomials, sines, cosines, etc..., the Risch-Norman algorithm will be able to compute it. Extended versions of this algorithm are implemented in [[Mathematica]] and [[Maple computer algebra system]].\n\nSome special integrands occur often enough to warrant special study. In particular, it may be useful to have, in the set of antiderivatives, the special functions of physics (like the [[Legendre function]]s, the [[Hypergeometric function]], [[fungsi gamma]] jeung saterusna.) Extending the Risch-Norman algorithm so that it includes these functions is possible but challenging.\n\nMost humans are not able to integrate such general formulae, so in a sense computers are more skilled at integrating highly complicated formulae. On the other hand, very complex formulae are unlikely to have closed-form antiderivatives, so this advantage is dubious.\n\n== Improper integrals ==\n\nNot all integrals can be evaluated using a single limit process. An integral which can only be evaluated by considering it as the limit of integrals on successively larger and larger integrals is called an \'\'\'[[improper integral]]\'\'\'. Improper integrals usually turn up when the [[range of a function|range]] of the function is infinite or, in the case of the [[Riemann integral]], when the [[domain of a function|domain]] is infinite. One common example of an improper integral is the [[Cauchy principal value]].\n\n== Definitions of the integral ==\n\nThe most important integrals are the [[Riemann integral]] and the [[Lebesgue integral]]. The Riemann integral was created by [[Bernhard Riemann]] and was the first [[rigor]]ous definition of the integral. The Lebesgue integral was created by [[Henri Lebesgue]] to integrate a wider class of functions and to prove very strong [[theorem]]s about interchanging [[limit]]s and integrals.\n\nAlthough the Riemann and Lebesgue integrals are the most important ones, a number of others exist, including but not limited to:\n\n* the [[Daniell integral]]\n* the [[Darboux integral]], a variation of the Riemann integral\n* the [[Denjoy integral]], an extension of both the Riemann and Lebesgue integrals\n* the [[Haar integral]]\n* the [[Henstock-Kurzweil integral]], an extension of both the Riemann and Lebesgue integrals (also called HK-integral)\n* the [[Henstock-Kurzweil-Stieltjes integral]] (also called HK-Stieltjes integral)\n* the [[Lebesgue-Stieltjes integral]] (also called Lebesgue-Radon integral)\n* the [[Perron integral]], which is equivalent to the restricted [[Denjoy integral]]\n* the [[Riemann-Stieltjes integral]], an extension of the Riemann integral\n\n==Tempo oge== \n* [[calculus]]\n* [[list of integrals]]\n* [[derivative]]s\n* [[limit (mathematics)|limit]]s.\n* [[Fungsi (matematik)|fungsi]]\n* [[algebra]]\n\n==External links==\n* [http://integrals.wolfram.com/ The Integrator] by [[Wolfram Research]]\n* [http://wims.unice.fr/wims/wims.cgi?module=tool/analysis/function.en Function Calculator] from [[WIMS]]\n\n[[Category:Calculus]]\n[[de:Integralrechnung]]\n[[eo:Integralo]]\n[[fr:intégrale]]\n[[nl:Integraal]]\n[[pl:Ca%C5%82ka]]\n[[sv:Integral]]\n[[ja:%E7%A9%8D%E5%88%86]]','/* See also */',13,'Budhi','20041224213952','',0,0,1,0,0.085341773036,'20041225232059','79958775786047'); INSERT INTO cur VALUES (1393,0,'Lebesgue_integration','Dina [[matematik]], \'\'[[integral]]\'\' ngarupakeun konsep umum ngeunaan daerah tina gambar nu teratur ka wewengkon nu diwatesan ku fungsi. \'\'\'Integrasi Lebesgue\'\'\' ngarupakeun rarangkay pagawean keur ngalegaan integral ka fungsi kelas nu kacida gedena.\nIntegral Lebesgue kacida pentingna dina widang matematik nu disebut [[real analysis]] sarta sababaraha widang sejenna.\n\nIntegral Lebesgue dumasar kana ngaran [[Henri Lebesgue]] ([[1875]]-[[1941]]). Cara maca ngaranna nu gampang nyaeta \'\'leh BEG\'\'.\n\n== Panganteur ==\n\n[[Image:Area under curve.png|right|The integral is defined as the area under a curve.]]\n\nFungsi integral \'\'f\'\' bisa dihartikeun salaku wewengkon \'\'S\'\' sahandapeun grapik \'\'f\'\'. Ieu gampang dipikaharti keur fungsi kulawarga saperti polinomial, tapi naon hartina keur fungsi nu leuwih asing? Sacara umum, naha kelas fungsi nu ngarupakeun \"wewengkon sahandapeun kurva\" asup akal? Keur ngajawab ieu patarosan merlukan teori jeung praktek.\n\nAs part of a general movement toward [[formalism]] in mathematics in the [[nineteenth century]], attempts were made to put the integral calculus on a firm foundation. The [[Riemann integral]], proposed by [[Bernhard Riemann]] ([[1826]]-[[1866]]), is a broadly successful attempt to provide such a foundation for the integral. Riemann\'s definition starts with the construction of a sequence of easily-calculated integrals which converge to the integral of a given function. This definition is successful in the sense that it gives the expected answer for many already-solved problems, \nand gives useful results for many other problems.\n\nHowever, the behavior of the Riemann integral in limit processes is difficult to analyze. This is of prime importance, for instance, in the study of [[Fourier series]], [[Fourier transform]]s and other topics. The Lebesgue integral is better able to describe how and when it is possible to take limits under the integral sign. The Lebesgue definition considers a different class of easily-calculated integrals than the Riemann definition, which is the main reason the Lebesgue integral is better behaved.\nThe Lebesgue definition also makes it possible to calculate integrals for a broader class of functions.\nFor example, the function which is 0 where its argument is [[irrational number|irrational]] and 1 otherwise has a Lebesgue integral, but it does not have a Riemann integral.\n\nWe now give a highly technical description. It is possible to skip directly to the \'\'\'discussion\'\'\' heading for further technical and historical justification of the Lebesgue integral if the reader is so inclined.\n\n== Construction of the Lebesgue integral ==\n\nLet μ be a (non-negative) [[measure (mathematics) | measure]] on a [[sigma-algebra]] \'\'X\'\' over a set \'\'E\'\'. (In [[real analysis]], \'\'E\'\' will typically be [[Euclidean space|Euclidean \'\'n\'\'-space]] \'\'\'R\'\'\'\'\'n\'\' or some [[Lebesgue measure|Lebesgue measurable]] subset of it, \'\'X\'\' will be the sigma-algebra of all Lebesgue measurable subsets of \'\'E\'\', and μ will be the Lebesgue measure. In probability and statistics, μ will be a [[probability]] measure on a probability space \'\'E\'\'.)\nWe build up an integral for real-valued functions defined on \'\'E\'\' as follows. \n\nFix a set \'\'S\'\' in \'\'X\'\' and let \'\'f\'\' be the function on \'\'E\'\' whose value is 0 outside of \'\'S\'\' and 1 inside of \'\'S\'\' (i.e., \'\'f\'\'(\'\'x\'\') = 1 if \'\'x\'\' is in \'\'S\'\', otherwise \'\'f\'\'(\'\'x\'\') = 0.) This is called the [[indicator function|\'\'indicator function\'\']] or \'\'characteristic function\'\' of \'\'S\'\' and is denoted 1\'\'S\'\'.\n\nTo assign a value to ∫1\'\'S\'\' consistent with the given measure μ, the only reasonable choice is to set:\n\n:\\int 1_S = \\mu (S)\n\nWe extend by linearity to the [[linear span]] of indicating functions: \n\n:\\int \\sum a_k 1_{S_k} = \\sum a_k \\mu( S_k)\n\nwhere the sum is finite and the coefficients \'\'a\'\'\'\'k\'\' are real numbers. Such a finite [[linear combination]] of indicating functions is called a simple function. Note that a simple function can be written in many ways as a linear combination of characteristic functions, but the integral will always be the same.\n\nNow the difficulties begin as we attempt to take limits so that we can integrate more general functions. It turns out that the following process works and is most fruitful.\n\nLet \'\'f\'\' be a non-negative function supported on the set \'\'E\'\' (we allow it to attain the value +∞, in other words, \'\'f\'\' takes values in the [[extended real number line]].) We define ∫\'\'f\'\' to be the [[supremum]] of ∫\'\'s\'\' where \'\'s\'\' varies over all simple functions which are under \'\'f\'\' (that is, \'\'s\'\'(\'\'x\'\') ≤ \'\'f\'\'(\'\'x\'\') for all \'\'x\'\'.) This is analogous to the lower sums of Riemann. However, we will not build an upper sum, and this fact is important in getting a more general class of integrable functions. One can be more explicit and mention the measure and domain of integration:\n\n:\\int_E f\\,d\\mu := \\sup\\left\\{\\,\\int_E s\\,d\\mu : s\\le f,\\ s\\ \\mbox{simple}\\,\\right\\}\n\nThere is the question of whether this definition makes sense (do simple function or indicating function keep the same integral?) There is also the question of whether this corresponds in any way to a Riemann notion of integration. It is not so hard to prove that the answer to both questions is yes. \n\nWe have defined ∫\'\'f\'\' for \'\'any\'\' non-negative function on \'\'E\'\'; however for some functions ∫\'\'f\'\' will be infinite. Furthermore, desirable additive and limit properties of the integral are not satisfied, unless we require that all our functions are \'\'measurable\'\', meaning that the pre-image of any interval is in \'\'X\'\'. We will make this assumption from now on.\n\nTo handle signed functions, we need a few more definitions. If \'\'f\'\' is a function of the measurable set \'\'E\'\' to the reals (including ± ∞), then we can write \'\'f\'\' = \'\'g\'\' - \'\'h\'\' where \'\'g\'\'(\'\'x\'\') = (\'\'f\'\'(\'\'x\'\') if \'\'f\'\'(\'\'x\'\')>0, 0 otherwise) and \'\'h\'\'(\'\'x\'\') = (-\'\'f\'\'(\'\'x\'\') if \'\'f\'\'(\'\'x\'\') < 0, 0 otherwise). Note that both \'\'g\'\' and \'\'h\'\' are non-negative functions. Also note that |\'\'f\'\'| = \'\'g\'\' + \'\'h\'\'. If ∫|\'\'f\'\'| is finite, then \'\'f\'\' is called \'\'Lebesgue integrable\'\'. In this case, both ∫\'\'g\'\' and ∫\'\'h\'\' are finite, and it makes sense to define ∫\'\'f\'\' by ∫\'\'g\'\' - ∫\'\'h\'\'. It turns out that this definition is the correct one. [[complex number|Complex]] valued functions can be similarly integrated, by considering the real part and the imaginary part separately.\n\n== Properties of the Lebesgue integral ==\n\nEvery reasonable notion of integral needs to be [[linear transformation|linear]] and [[monotonic|monotone]], and the Lebesgue integral is: if \'\'f\'\' and \'\'g\'\' are integrable functions and \'\'a\'\' and \'\'b\'\' are real numbers, then \'\'af\'\' + \'\'bg\'\' is integrable and ∫(\'\'af\'\' + \'\'bg\'\') = \'\'a\'\'∫\'\'f\'\' + \'\'b\'\'∫\'\'g\'\'; if \'\'f\'\' ≤ \'\'g\'\', then ∫\'\'f\'\' ≤ ∫\'\'g\'\'.\n\nTwo functions which only differ on a set of μ-measure zero have the same integral, or more precisely: if μ({\'\'x\'\' : \'\'f\'\'(\'\'x\'\') ≠ \'\'g\'\'(\'\'x\'\')}) = 0, then \'\'f\'\' is integrable if and only if \'\'g\'\' is, and in this case ∫ \'\'f\'\' = ∫ \'\'g\'\'.\n\nOne of the most important advantages that the Lebesgue integral carries over the Riemann integral is the ease with which we can perform limit processes.\nThree theorems are key here.\n\nThe [[monotone convergence theorem]] states that if \'\'f\'\'\'\'k\'\' is a sequence of non-negative measurable functions such that \'\'f\'\'\'\'k\'\'(\'\'x\'\') ≤ \'\'f\'\'\'\'k\'\'+1(\'\'x\'\') for all \'\'k\'\', and if \'\'f\'\' = lim \'\'f\'\'\'\'k\'\', then ∫\'\'f\'\'\'\'k\'\' converges to ∫\'\'f\'\' as \'\'k\'\' goes to infinity. (Note: ∫\'\'f\'\' may be infinite here.)\n\n[[Fatou\'s lemma]] states that if \'\'f\'\'\'\'k\'\' is a sequence of non-negative measurable functions and if \'\'f\'\' = liminf \'\'f\'\'\'\'k\'\', then ∫\'\'f\'\' ≤ liminf ∫\'\'f\'\'\'\'k\'\'. (Again, ∫\'\'f\'\' may be infinite.)\n\nThe [[dominated convergence theorem]] states that if \'\'f\'\'\'\'k\'\' is a sequence of measurable functions with pointwise limit \'\'f\'\', and if there is an integrable function \'\'g\'\' such that |\'\'f\'\'\'\'k\'\'| ≤ \'\'g\'\' for all \'\'k\'\', then \'\'f\'\' is integrable and ∫\'\'f\'\'\'\'k\'\' converges to ∫\'\'f\'\'.\n\n== Equivalent formulations ==\n\nIf \'\'f\'\' is non-negative, then ∫\'\'f\'\' dμ is precisely the area under the curve as measured by the product measure μ × λ where λ is the Lebesgue measure for \'\'\'R\'\'\'.\n\nOne can also circumvent measure theory entirely. \nThe Riemann integral exists for any continuous function \'\'f\'\' of compact support. \nThen we use functional analysis to obtain the integral for more general functions. \nLet \'\'Cc\'\' be the space of all real-valued compactly supported continuous functions of \'\'\'R\'\'\'. Define a norm on \'\'Cc\'\' by\n\n\n:||\'\'f\'\'|| = ∫ |\'\'f\'\'(\'\'x\'\')|\n\nThen \'\'Cc\'\' is a normed vector space (and in particular, it is a metric space.) All metric spaces have completions, so let \'\'L\'\'1 be its completion. This space is isomorphic to the space of Lebesgue integrable functions (modulo sets of measure zero). Furthermore, the Riemann integral ∫ defines a continuous functional on \'\'Cc\'\' which is dense in \'\'L\'\'1 hence ∫ has a unique extension to all of \'\'L\'\'1. This integral is precisely the Lebesgue integral.\n\nIn this formulation, the limit taking theorems are hard to prove. However, in more general cases (such as when the functions, or perhaps the measures, take values in a large vector space instead of \'\'\'R\'\'\'\'\'n\'\') this approach is a fast way of obtaining an integral.\n\n== Discussion ==\n\nHere we discuss the limitations of the Riemann integral and the greater scope offered by the Lebesgue integral. We presume a working understanding of the [[Riemann integral]]. \n\nWith the advent of [[Fourier series]], there arose the need to exchange summation and integral signs much more often. However, the conditions under which ∑\'\'k\'\'∫\'\'f\'\'\'\'k\'\' and ∫∑\'\'k\'\'\'\'f\'\'\'\'k\'\' are equal proved quite elusive in the Riemann framework. It may come as a surprise to the casual reader that these two quantities may not be equal, so an example helps:\n\n*Let \'\'f\'\'\'\'k\'\'(\'\'x\'\') be 1 on (\'\'k\'\', \'\'k\'\'+1] and -1 on (\'\'k\'\'+1, \'\'k\'\'+2] and 0 everywhere else. \n*Then, ∑\'\'k\'\'=1\'\'f\'\'\'\'k\'\'(\'\'x\'\') = \'\'f\'\'(\'\'x\'\') where \'\'f\'\'(\'\'x\'\') is zero everywhere except on (1, 2] where it is 1. Hence, ∫∑\'\'f\'\'\'\'k\'\' = ∫\'\'f\'\' = 1. \n*However, ∫\'\'f\'\'\'\'k\'\' = 0 for every \'\'k\'\', hence ∑∫\'\'f\'\'\'\'k\'\' = 0.\n\nHowever, it was clear from experience that in many very useful situations, the sum and the integral did commute. It was very important to be able to describe which conditions enabled the exchange of the sum and integral signs. Unfortunately, the Riemann integral is poorly equipped to deal with this question; its main useful convergence theorem being the [[uniform convergence theorem]]: if \'\'f\'\'\'\'k\'\' are Riemann-integrable functions of [\'\'a\'\', \'\'b\'\'] converging uniformly to \'\'f\'\', then ∫\'\'f\'\'\'\'k\'\' converges to ∫\'\'f\'\'. Since Fourier series rarely converge uniformly, this theorem is clearly insufficient.\n\nThere are some other technical difficulties with the Riemann integral. \nThese are linked with the limit taking difficulty discussed above.\n\n* If \'\'H\'\'(\'\'x\'\') is a function of [0,1] which is 0 everywhere, except that it is 1 on the rational numbers (see [[nowhere continuous]]), then it is not Riemann integrable. This is because, in the calculation of its upper sum, any rectangle used will have height 1 (because all rectangles contain rational points) and in the lower sum, any rectangle used will have height 0 (because all rectangles contain irrational points.) Hence the lower sum is 0 and the upper sum is 1.\n\n* This means that the [[monotone convergence theorem]] does not hold. The monotone convergence theorem would say that if \'\'f\'\'\'\'k\'\'(\'\'x\'\') is a sequence of non-negative functions increasing monotonically in \'\'k\'\' to \'\'f\'\'(\'\'x\'\'), then the integrals of ∫ \'\'f\'\'\'\'k\'\'(\'\'x\'\') \'\'dx\'\' should converge to ∫ \'\'f\'\'(\'\'x\'\') \'\'dx\'\'. To see why this is so, let {\'\'a\'\'\'\'k\'\'} be an enumeration of all the rational numbers in [0,1] (they are [[countable]] so this can be done.) Then let \'\'g\'\'\'\'k\'\' be the function which is 1 on \'\'a\'\'\'\'k\'\' and 0 everywhere else. Lastly let \'\'f\'\'\'\'k\'\' = \'\'g\'\'1 + \'\'g\'\'2 + ... + \'\'g\'\'\'\'k\'\'. Then \'\'f\'\'\'\'k\'\' is zero everywhere except on a finite set of points, hence its Riemann integral is zero. The sequence \'\'f\'\'\'\'k\'\' is also clearly non-negative and monotonously increasing to \'\'H\'\'(\'\'x\'\'), but \'\'H\'\'(\'\'x\'\') isn\'t Riemann integrable.\n\n* The Riemann integral can only integrate functions on an interval. The simplest extension is to define ∫− ∞\'\'f\'\'(\'\'x\'\') \'\'dx\'\' by the limit of ∫−\'\'a\'\'\'\'a\'\'\'\'f\'\'(\'\'x\'\') \'\'dx\'\' as a goes to +∞. However, this breaks \'\'translation invariance\'\': if \'\'f\'\' and \'\'g\'\' are zero outside some interval [\'\'a\'\', \'\'b\'\'] and are Riemann integrable, and if \'\'f\'\'(\'\'x\'\') = \'\'g\'\'(\'\'x\'\' + \'\'y\'\') for some \'\'y\'\', then ∫ \'\'f\'\' = ∫ \'\'g\'\'. However, with this definition of the [[improper integral]] (this definition is sometimes called the improper [[Cauchy principal value]] about zero), the functions \'\'f\'\'(\'\'x\'\') = (1 if \'\'x\'\' > 0, −1 otherwise) and \'\'g\'\'(\'\'x\'\') = (1 if \'\'x\'\' > 1, −1 otherwise) are translations of one another, but their improper integrals are different. (∫ \'\'f\'\' = 0 but ∫ \'\'g\'\' = − 2.)\n\n=== Towards a better integration theory ===\n\nThe solution, as it turns out, is to study an even simpler problem first. The observation is that, if we have a notion of \'\'length\'\', we can turn it into a notion of \'\'area\'\'. Instead of measuring the area of a surface in the plane, we turn our attention to measuring the length of subsets of the real line. One obvious requirement is that an interval [\'\'a\'\', \'\'b\'\'] should have a length of \'\'b\'\'-\'\'a\'\'. What other demands we should put on the notion of length is less clear, and much effort was put into obtaining a useful definition. In fact, the term \'\'length\'\' was first used, but its construction was misguided, and a later, more useful construction is in use today; it is called the [[measure (mathematics)|measure]].\n\nMeasure theory enables us to calculate the lengths of subsets of the real line. It also fully classifies which sets have a length, and which sets do not have a reasonable notion of length. By spending the extra effort into calculating lengths carefully, we now have a more solid foundation to work with.\n\nOf course, the Riemann integral uses the notion of length anonymously. Indeed, the element of calculation for the Riemann integral is the rectangle [\'\'a\'\', \'\'b\'\'] × [\'\'c\'\', \'\'d\'\'], whose area is calculated to be (\'\'b\'\'-\'\'a\'\')(\'\'c\'\'-\'\'d\'\'). Obviously the numbers \'\'b\'\'-\'\'a\'\' and \'\'c\'\'-\'\'d\'\' are meant to be the lengths of [\'\'a\'\', \'\'b\'\'] and [\'\'c\'\', \'\'d\'\']. However, we can now augment the Riemann integral. Indeed, Riemann could only use rectangles because he could only measure intervals. Equipped with a measure μ, we can calculate the length of sets much more interesting than intervals. So, if \'\'X\'\' and \'\'Y\'\' are μ-measurable, we can easily define the area of the cartesian product \'\'X\'\' × \'\'Y\'\' to be μ(\'\'X\'\') μ(\'\'Y\'\'). This definition clearly generalizes Riemann\'s notion of area of a rectangle. In the context of Lebesgue integration, sets such as \'\'X\'\' × \'\'Y\'\' are sometimes called rectangles, even though they are far more complicated than the quadrilaterals of the same name.\n\nWith the ability to measure the area of more complex rectangles, we can attempt to integrate more complex functions. One crucial, but nonobvious step, was to drop the notion of upper sum. While upper sums work just fine for bounded functions of bounded intervals, there is a clear problem for unbounded functions, or functions which are supported by all of the real line. For instance, the function \'\'f\'\'(\'\'x\'\') = 1/\'\'x\'\'2 for \'\'x\'\' > 1 would necessarily have an infinite upper sum, however it can be shown that this function has a finite integral.\n\nDropping the upper sum robs us of our main way of checking for integrability of functions. It isn\'t obvious how to decide on the integrability of functions while maintaining a consistent theory. It is very fortunate that a simple (if technical) definition is available.\n\nThe resulting theory of integration is much more accurate in describing limit taking processes. Many of the original questions posed by Fourier series (about swapping the integral and summation signs) are answerable using one or another of the various Lebesgue integral limit theorems (the main ones are monotone convergence, dominated convergence and Fatou\'s lemma; see above.)\n\n== Tempo oge ==\n* [[null set]]\n* [[integral|integration]]\n* [[measure]]\n* [[sigma-algebra]]\n* [[Lebesgue measure]]\n\n[[Category:Calculus]]\n[[de:Lebesgue-Integral]]\n[[fr:intégrale de Lebesgue]]','/* Panganteur */',13,'Budhi','20040904223414','',0,0,0,0,0.872037500083,'20050202030550','79959095776585'); INSERT INTO cur VALUES (1394,6,'Area_under_curve.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040831060000','',0,0,0,1,0.865872225599244,'20041224213952','79959168939999'); INSERT INTO cur VALUES (1395,8,'Clearyourcache','\'\'\'Catetan:\'\'\' Sanggeus nyimpen, anjeun perlu ngosongkeun \'\'cache\'\' panyungsi anjeun pikeun nempo parobahanana: \'\'\'Mozilla:\'\'\' klik \'\'reload\'\' (atawa \'\'ctrl-r\'\'), \'\'\'IE/Opera:\'\'\' \'\'ctrl-f5\'\', \'\'\'Safari:\'\'\' \'\'cmd-r\'\', \'\'\'Konqueror\'\'\' \'\'ctrl-r\'\'.','',3,'Kandar','20041030021421','',0,0,0,0,0.860295914048,'20041030021421','79958969978578'); INSERT INTO cur VALUES (1396,8,'Emptyfile','Koropak nu dimuatkeun ku anjeun jigana kosong. Hal ieu bisa jadi alatan sarupaning \'\'typo\'\' na ngaran koropakna. Mangga parios deui yén anjeun leres-leres hoyong ngamuat koropak éta.','',3,'Kandar','20040904050923','',0,0,0,0,0.848584975511,'20040904050923','79959095949076'); INSERT INTO cur VALUES (1397,6,'Areabetweentwographs.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040831074348','',0,0,0,1,0.821677176115734,'20041224213952','79959168925651'); INSERT INTO cur VALUES (1398,8,'Monobook.js','/* tooltips and access keys */ ta = new Object(); ta[\'pt-userpage\'] = new Array(\'.\',\'Kaca pamaké kuring\'); ta[\'pt-anonuserpage\'] = new Array(\'.\',\'Kaca pamaké pikeun IP nu ku anjeun keur diédit\'); ta[\'pt-mytalk\'] = new Array(\'n\',\'Kaca omongan kuring\'); ta[\'pt-anontalk\'] = new Array(\'n\',\'Sawala ngeunaan éditan ti alamat IP ieu\'); ta[\'pt-preferences\'] = new Array(\'\',\'Préferénsi kuring\'); ta[\'pt-watchlist\'] = new Array(\'l\',\'Daptar kaca nu diawaskeun ku anjeun parobahanana.\'); ta[\'pt-mycontris\'] = new Array(\'y\',\'Daptar sumbangsih kuring\'); ta[\'pt-login\'] = new Array(\'o\',\'Anjeun langkung saé lebet log, sanaos teu wajib.\'); ta[\'pt-anonlogin\'] = new Array(\'o\',\'Anjeun langkung saé lebet log, sanaos teu wajib.\'); ta[\'pt-logout\'] = new Array(\'o\',\'Kaluar log\'); ta[\'ca-talk\'] = new Array(\'t\',\'Sawala ngeunaan eusi kaca\'); ta[\'ca-edit\'] = new Array(\'e\',\'Anjeun bisa ngédit kaca ieu. Mangga pigunakeun tombol sawangan saméméh nyimpen.\'); ta[\'ca-addsection\'] = new Array(\'+\',\'Tambihan koméntar kana sawala ieu.\'); ta[\'ca-viewsource\'] = new Array(\'e\',\'Kaca ieu dikonci, tapi anjeun masih bisa muka sumberna.\'); ta[\'ca-history\'] = new Array(\'h\',\'Vérsi heubeul kaca ieu.\'); ta[\'ca-protect\'] = new Array(\'=\',\'Protect this page\'); ta[\'ca-delete\'] = new Array(\'d\',\'Hapus kaca ieu\'); ta[\'ca-undelete\'] = new Array(\'d\',\'Simpen deui éditan kaca ieu nu geus dijieun saméméh dihapus\'); ta[\'ca-move\'] = new Array(\'m\',\'Pindahkeun kaca ieu\'); ta[\'ca-nomove\'] = new Array(\'\',\'Anjeun teu wenang mindahkeun kaca ieu\'); ta[\'ca-watch\'] = new Array(\'w\',\'Tambahkeun kaca ieu kana awaskeuneun kuring\'); ta[\'ca-unwatch\'] = new Array(\'w\',\'Kaluarkeun kaca ieu tina awaskeuneun kuring\'); ta[\'search\'] = new Array(\'f\',\'Téangan wiki ieu\'); ta[\'p-logo\'] = new Array(\'\',\'Tepas\'); ta[\'n-mainpage\'] = new Array(\'z\',\'Sindang ka Tepas\'); ta[\'n-portal\'] = new Array(\'\',\'Ngeunaan proyékna, naon nu bisa dipigawé, di mana néangan naon\'); ta[\'n-currentevents\'] = new Array(\'\',\'Panggihan iber ngeunaan nu lumangsung kiwari\'); ta[\'n-recentchanges\'] = new Array(\'r\',\'Daptar parobahan anyar na wiki.\'); ta[\'n-randompage\'] = new Array(\'x\',\'Muatkeun kaca acak\'); ta[\'n-help\'] = new Array(\'\',\'Tempat pikeun néangan.\'); ta[\'n-sitesupport\'] = new Array(\'\',\'Support us\'); ta[\'t-whatlinkshere\'] = new Array(\'j\',\'Daptar kaca-kaca wiki nu numbu ka dieu\'); ta[\'t-recentchangeslinked\'] = new Array(\'k\',\'Parobahan anyar na kaca-kaca nu numbu ka dieu\'); ta[\'feed-rss\'] = new Array(\'\',\'Asupan RSS pikeun kaca ieu\'); ta[\'feed-atom\'] = new Array(\'\',\'Asupan atom pikeun kaca ieu\'); ta[\'t-contributions\'] = new Array(\'\',\'Témbongkeun daptar sumbangsih pamaké ieu\'); ta[\'t-emailuser\'] = new Array(\'\',\'Kirim surélék ka pamaké ieu\'); ta[\'t-upload\'] = new Array(\'u\',\'Muatkeun koropak gambar atawa média\'); ta[\'t-specialpages\'] = new Array(\'q\',\'Daptar sadaya kaca husus\'); ta[\'ca-nstab-main\'] = new Array(\'c\',\'Témbongkeun eusi kaca\'); ta[\'ca-nstab-user\'] = new Array(\'c\',\'Témbongkeun kaca pamaké\'); ta[\'ca-nstab-media\'] = new Array(\'c\',\'Témbongkeun kaca média\'); ta[\'ca-nstab-special\'] = new Array(\'\',\'Ieu kaca husus, anjeun teu bisa ngédit ku sorangan.\'); ta[\'ca-nstab-wp\'] = new Array(\'a\',\'Témbongkeun kaca proyék\'); ta[\'ca-nstab-image\'] = new Array(\'c\',\'Témbongkeun kaca gambar\'); ta[\'ca-nstab-mediawiki\'] = new Array(\'c\',\'Témbongkeun pesen sistim\'); ta[\'ca-nstab-template\'] = new Array(\'c\',\'Témbongkeun citakan\'); ta[\'ca-nstab-help\'] = new Array(\'c\',\'Témbongkeun kaca pitulung\'); ta[\'ca-nstab-category\'] = new Array(\'c\',\'Témbongkeun kaca kategori\');','',3,'Kandar','20050223043122','',0,0,1,0,0.393759120439,'20050223043122','79949776956877'); INSERT INTO cur VALUES (1399,8,'Listadmins','Daptar kuncén','',3,'Kandar','20041122093059','',0,0,0,0,0.747952839242,'20041122093059','79958877906940'); INSERT INTO cur VALUES (1400,6,'Abu_Abdullah_Muhammad_bin_Musa_al-Khwarizmi.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040901061555','',0,0,0,1,0.51076923451458,'20040901061555','79959098938444'); INSERT INTO cur VALUES (1402,0,'Beta_function','#REDIRECT [[Fungsi beta]]\n','Beta function dipindahkeun ka Fungsi beta',13,'Budhi','20040901064803','',0,1,0,1,0.911765701986631,'20040901064803','79959098935196'); INSERT INTO cur VALUES (1403,8,'Monobook.css',' /* édit koropak ieu pikeun nyaluyukeun kulit \'\'monobook\'\' pikeun sakabéh situs */','',3,'Kandar','20040904050436','',0,0,0,0,0.301773630223,'20040904050436','79959095949563'); INSERT INTO cur VALUES (1404,4,'Log_hapusan','
  • 12:52, 20 Dec 2004 [[User:Kandar|Kandar]] ngahapus \"Knuth\'s up-arrow notation\" (eusina nu heubeul: '&lt;math&gt;Asupkeun rumus di dieu&lt;/math&gt;&lt;nowiki&gt;Insert non-formatted text here&lt;/nowiki&gt;--[[User:143.166.226.17|143.166.226.17]] 11:06, 19 Dec 2004 (UTC)--...')
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  • 07:03, 6 Dec 2004 [[User:Kandar|Kandar]] ngahapus \"Orthogonal projection\" (eusina nu heubeul: '[[Judul tumbu]][Judul tumbu http://www.conto.com]')
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  • 07:56, 23 Nov 2004 [[User:Kandar|Kandar]] ngahapus \"Pitulung\" (eusina nu heubeul: 'Transport, or transportation (as it is called in the United States), is the movement of people and goods from one place to another. The term is derive...')
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  • 07:54, 23 Nov 2004 [[User:Kandar|Kandar]] ngahapus \"Wikipedia:Pitulung\" (eusina nu heubeul: '#REDIRECT [[Pitulung]]')
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  • 07:53, 23 Nov 2004 [[User:Kandar|Kandar]] ngahapus \"Wikipedia:Help\" (eusina nu heubeul: '#REDIRECT [[Wikipedia:Pitulung]]')
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  • 05:27, 6 Nov 2004 [[User:Kandar|Kandar]] ngahapus \"Image:Peta tillu karajaan koréa.png\" (salah ngaran)
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  • 07:08, 1 Nov 2004 [[User:Kandar|Kandar]] ngahapus \"Image:Profil katalis.png\" (eusina rek diganti)
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  • 08:52, 5 Oct 2004 [[User:Kandar|Kandar]] ngahapus \"History of Africa\" (eusina nu heubeul: 'Afrika disebut benua hitam (hideung) naon sebabna? sabab seueur pisan anu hideung, lamun di Bandung mah disebut tutung....')
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  • 04:08, 5 Oct 2004 [[User:Kandar|Kandar]] ngahapus \"Orgasme\" (eusina nu heubeul: 'HAYANG NGASAAN MEMEK ARAB')
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  • 14:13, 26 Sep 2004 [[User:Kandar|Kandar]] ngahapus \"Tiung itil\" (eusina nu heubeul: '[[Im[[Media:Example.mp3]]&lt;nowiki&gt;Insert non-formatted text here&lt;/nowiki&gt;--[[User:203.77.223.7|203.77.223.7]] 03:17, 26 Sep 2004 (UTC)----== Headlin...')
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  • 03:30, 3 Sep 2004 [[User:Kandar|Kandar]] dihapus \"Wikipédia:Pitulung\" (eusina nu heubeul: '[[Media:Example.mp3]]--[[User:Colenak|Colenak]] 10:18, 2 Sep 2004 (UTC)')
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  • 11:44, 1 Sep 2004 [[User:Kandar|Kandar]] dihapus \"Help:Contents\" (eusina nu heubeul: '#REDIRECT [[Pitulung:Eusi]]')
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','ngahapus \"Knuth\'s up-arrow notation\": eusina nu heubeul: \'<math>Asupkeun rumus di dieu</math><nowiki>Insert non-formatted text here</nowiki>--[[User:143.166.226.17|143.166.226.17]] 11:06, 19 Dec 2004 (UTC)--...\'',3,'Kandar','20041220125220','sysop',0,0,0,0,0.292384515788764,'20041220125220','79958779874779'); INSERT INTO cur VALUES (1405,0,'Analisis_faktor','\'\'\'Analisa faktor\'\'\' nyaeta teknik statistik nu aslina tina [[mathematical psychology]]. Ilahar dipake dina elmu sosial jeung [[marketing]], [[product management]], [[operations research]], sarta elmu praktis sejenna nu merlukeun wilangan data anu loba. Maksudna keur manggihkeun pola diantara variasi nilai sabarabaha variabel. This is done by generating artificial dimensions (called factors) that correlate highly with the real variables. \n\n==Analisis faktor dina pamasaran==\n\nThe basic steps are:\n* Identify the salient attributes consumers use to evaluate [[product (business)|products]] in this category.\n* Use [[quantitative marketing research]] techniques (such as [[statistical survey|surveys]]) to collect data from a sample of potential [[customer]]s concerning their ratings of all the product attributes.\n* Input the data into a statistical program and run the factor analysis procedure. The computer will yield a set of underlying attributes (or factors).\n* Use these factors to construct [[perceptual mapping|perceptual maps]] and other [[positioning (marketing)|product positioning]] devices.\n\n=== Information collection ===\n\nThe data collection stage is usually done by marketing research professionals. Survey questions ask the respondant to rate a product from one to five (or 1 to 7, or 1 to 10) on a range of attributes. Anywhere from five to twenty attributes are chosen. They could include things like: ease of use, weight, accuracy, durability, colourfulness, price, or size. The attributes chosen will vary depending on the product being studied. The same question is asked about all the products in the study. The data for multiple products is codified and input into a statistical program such as SPSS or SAS.\n\n=== Analisis ===\nThe analysis will isolate the underlying factors that explain the data. Factor analysis is an interdependence technique. The complete set of interdependent relationships are examined. There is no specification of either dependent variables, independent variables, or causality. Factor analysis assumes that all the rating data on different attributes can be reduced down to a few important dimensions. This reduction is possible because the attributes are related. The rating given to any one attribute is partially the result of the influence of other attributes. The statistical algorithm deconstructs the rating (called a raw score) into its various components, and reconstructs the partial scores into underlying factor scores. The degree of correlation between the initial raw score and the final factor score is called a \'\'factor loading\'\'. There are two approaches to factor analysis: \"[[principal component analysis]]\" (the total variance in the data is considered); and \"common factor analysis\" (the common variance is considered).\n\nThe use of principle components in a semantic space can vary somewhat because the components may only \"predict\" but not \"map\" to the vector space. This produces a statistical principle component use where the most salient words or themes represent the preferred [[Basis]]\n\n===Kapunjulan===\n* both objective and subjective attributes can be used\n* it is fairly easy to do, inexpensive, and accurate\n* it is based on direct inputs from customers\n* there is flexibilty in naming and using dimensions\n\n===Kalemahan===\n* usefulness depends on the researchers ability to develop a complete and accurate set of product attributes - If important attributes are missed the procedure is valueless.\n* naming of the factors can be difficult - multiple attributes can be highly correlated with no appearent reason.\n* factor analysis will always produce a pattern between variables, no matter how random.\n\n==Factor analysis in psychometrics==\n\n===History===\n\nCharles Spearman pioneered the use of factor analysis in the field of psychology, measuring the intelligence of children in a village school. During his testing, he discovered a high correlation between all scores on the tests. Spearman believed that the empirically observed correlation was less than the true correlation between two test subjects. Using a correctional formula devised from knowledge of the degree of the unreliability of the observed factors, he discovered a perfect correlation between all kinds of intelligence. This lead to the postulation of a general intelligence, or g, that is innate in all humans. Spearman went on to test the theory of specialized intelligence, or s. S, supposedly, deals with specific areas, such as logic or verbal ability. According to his theory, all tasks require some use of g and an s factor, so it could be concluded that someone with a high g will perform well on another test for g.\n\nRaymond Cattell expanded on Spearman’s idea of a two-factor theory of intelligence after performing his own tests and factor analysis. He used a multi-factor theory to explain intelligence. Cattell’s theory addressed alternate factors in intellectual development, including motivation and psychology. Cattell also developed several mathematical methods for adjusting psychometric graphs, such as his \"scree\" test and similarity coefficients. His research lead to the development of his theory of crystallized and fluid intelligence, in which crystallized is a set memory and reflexive actions, and fluid is the ability for a person to adjust or reason (think on their feet). Cattell was a strong advocate of factor analysis and psychometrics. He believed that all theory should be derived from research, which supports the continued use of empirical observation and objective testing to study human intelligence. All of their research, of course, is based on the idea that intelligence is measureable.\n\n===Applications in psychology===\nFactor analysis has been used in the study of human intelligence as a method for comparing the outcomes of (hopefully) objective tests and to construct matrices to define correlations between these outcomes, as well as finding the factors for these results. The field of psychology that measures human intelligence using quantitative testing in this way is known as psychometrics (psycho=mental, metrics=measurement).\n\n===Advantages===\n* Offers a much more objective method of testing intelligence in humans\n* Allows for a satisfactory comparison between the results of intelligence tests\n* Provides support for theories that would be difficult to prove otherwise\n\n===Disadvantages===\n* \"...each orientation is equally acceptable mathematically. But different factorial theories proved to differ as much in terms of the orientations of factorial axes for a given solution as in terms of anything else, so that model fitting did not prove to be useful in distinguishing among theories.\" (Sternberg, 1977). This means that even though all rotations are mathematically equal, they all come up with different results, and it is impossible to judge the proper rotation.\n* \"[Raymond Cattell] believed that factor analysis was \'a tool that could be applied to the study of behavior and ... might yield results with an objectivity and reliability rivaling those of the physical sciences (Stills, p. 114).\'\" [http://www.indiana.edu/~intell/rcattell.shtml] In other words, one’s gathering of data would have to be perfect and unbiased, which will probably never happen.\n* Interpreting factor analysis is based on using a “heuristic”, which is a solution that is \"convenient even if not absolutely true\" (Richard B. Darlington). More than one interpretation can be made of the same data factored the same way.\n\n===Bibliography===\n*Charles Spearman. Retrieved July 22, 2004, from http://www.indiana.edu/~intell/spearman.shtml\n*Factor Analysis. (2004). Retrieved July 22, 2004, from http://comp9.psych.cornell.edu/Darlington/factor.htm\n*Factor Analysis. Retrieved July 23, 2004, from http://www2.chass.ncsu.edu/garson/pa765/factor.htm\n*Raymond Cattell. Retrieved July 22, 2004, from http://www.indiana.edu/~intell/rcattell.shtml\n*Sternberg, R.J.(1990). The geographic metaphor. In R.J. Sternberg, Metaphors of mind: Conceptions of the nature of intelligence (pp.85-111). New York: Cambridge. \n*Stills, D.L. (Ed.). (1989). International encyclopedia of the social sciences: Biographical supplement (Vol. 18). New York: Macmillan.\n\n===Tempo oge===\n* [[positioning (marketing)|product positioning]]\n* [[perceptual mapping]]\n* [[marketing research]]\n* [[product management]]\n* [[list of marketing topics]]\n* [[Recomendation system]]\n\n[[de:Faktorenanalyse]]\n[[nl:Factoranalyse]]\n[[Category:Psychometrics]]','/* Factor analysis in marketing */',3,'Kandar','20041222102035','',0,0,0,0,0.016109041411,'20041222102035','79958777897964'); INSERT INTO cur VALUES (1406,0,'Sebaran_frekuensi','Dina [[statistik]], \'\'\'sebaran frekuensi\'\'\' nyaeta daptar nilai variabel nu dicokot tina [[Sampling (statistics)|sampel]]. Daptar ieu ilaharna disusun dumasar kana kuantitas, nembongkeun jumlah waktu unggal nilai nu ngadeukeutan. Conto, lamun 100 urang dibagi kana lima bagean [[Likert item|sikep nilai]] sarta milih dina skala 1 nu nunjukkeun satuju kacida sarta 5 teu satuju kacida, sebaran frekuensi bisa jadi saperti dihandap ieu:\n\n{| border=1 cellspacing=0 cellpadding=2\n!Rangking\n!Tingkat kasatujuan\n!Jumlah\n|-\n|1\n|Satuju kacida\n|25\n|-\n|2\n|Satuju\n|35\n|-\n|3\n|Teu yakin\n|20\n|-\n|4\n|Teu satuju\n|15\n|-\n|5\n|Teu satuju kacida\n|5\n|}\n\n[[Tes hipotesa statistik]] nu kapanggih dina taksiran nilai nu beda sarta sarua antara distribusi frekuensi. Taksiran ieu kaasup ukuran [[Measures of central tendency|kacenderungan ka tengah]] atawa [[Average|rata-rata]], saperti [[mean]] jeung [[median]], sarta ukuran variabiliti atawa [[dispersi statistik]], saperti [[simpangan baku]] atawa [[varian]].\n\nSebaran frekuensi disebut [[Skewness|mencong]] lamun nilai mean jeung median boga nilai nu beda. [[Kurtosis]] tina sebaran frekuensi nyaeta ngumpulna skor dina mean, atawa nembongkeun posisi puncak sebaran sacara grafis—contona dina [[histogram]]. Lamun sebaran puncak sebaran leuwih ti [[sebaran normal]] disebut leptokurtic; lamun kurang disebutna platykurtic.','',13,'Budhi','20050104233849','',0,0,0,0,0.305369808015,'20050104234548','79949895766150'); INSERT INTO cur VALUES (1407,0,'False_positive','A \'\'\'false positive\'\'\', also called \'\'\'false alarm\'\'\', exists when a test reports, incorrectly, that it has found a signal where none exists in reality. Detection [[algorithm]]s of all kinds have the tendency to create such false alarms.\n\nFor example, [[optical character recognition]] ([[OCR]]) may detect an \'a\' where there are only some dots that look like an a to the algorithm being used.\n\nThis is problematic when it happens in [[biometric]] scans, such as [[retina]] scans or [[facial recognition]], when the scanner incorrectly identifies someone as matching a known person, either a person who is entitled to enter the system, or a suspected criminal. \n\nWhen developing such software or hardware there is always a tradeoff between false positives and [[false negative]]s (in which an actual match is not detected). Dina bahasa [[tes hipotesa statistik]], this is a question of balancing the risk of [[Type I error]]s (false positives which reject the [[null hypothesis]] when it is true) against [[Type II error]]s (false negatives which fail to reject the null hypothesis when it is false).\n\nUsually there is some trigger value of how close a match to a given sample must be achieved before the algorithm reports a match. The higher this trigger value is, the more similar an object has to be to be detected and the fewer false positives will be created.\n\nFalse positives are also a significant issue in [[medicine|medical]] testing. In some cases, there are two or more tests that can be used, one of which is simpler and less expensive, but less accurate, than the other. For example, the simplest tests for [[HIV]] and [[hepatitis]] in blood have a significant rate of false positives. These tests are used to screen out possible [[blood transfusion|blood donors]], but more expensive and more precise tests are used in medical practice, to determine whether a person is actually infected with these viruses.\n\nFalse positives can produce serious and counterintuitive problems when the condition being searched for is rare. If a test has a false positive rate of one in ten thousand, but only one in a million samples (or people) is a true positive, most of the \"positives\" detected by the test will be false. The probability that an observed positive result is a false positive may be calculated, and the problem of false positives demonstrated, using [[Bayes\' theorem#An example: False positives|Bayes\' theorem]].\n\n\'\'\'Tempo oge\'\'\': [[Receiver-operator characteristic]]\n\nTempo oge: [[False negative]]\n\n[[de:Falsch positiv]]\n[[nl:Fout-positief en fout-negatief]]','',13,'Budhi','20050104062130','',0,0,0,0,0.436829432117,'20050104062130','79949895937869'); INSERT INTO cur VALUES (1408,0,'Quantile','\'\'Quantiles\'\' ngarupakeun titik penting dicokot dina interval vertikal teratur dina [[cumulative distribution function|fungsi sebaran kumulatif]] variabel random. Ngabagi susunan data nu diparentahkeun kana ukuran sub-susunan data \'\'q\'\' ngarupakeun hal nu penting dina kuantil-\'\'q\'\'; kuantil nyaeta nilai data nu nandaan wates antara susunan data nu ngantay. Put another way, the \'\'p\'\'th \'\'q\'\'-quantile is the value \'\'x\'\' such that the probability that a random variable will be less than \'\'x\'\' is at most \'\'p\'\'/\'\'q\'\' and the probability that a random variable will be less than or equal to \'\'x\'\' is at least \'\'p\'\'/\'\'q\'\'. There are \'\'q\'\'-1 \'\'q\'\'-quantiles, with \'\'p\'\' an integer satisfying 0 < \'\'p\'\' < \'\'q\'\'.\n\nSpecially named quantiles include the [[percentile]]s (\'\'q\'\' = 100), deciles (\'\'q\'\' = 10), quintiles (\'\'q\'\' = 5), [[quartile]]s (\'\'q\'\' = 4), and the [[median]] (\'\'q\'\' = 2). There are 99 percentiles, each corresponding to a quantile represented by an integer number of percent (such as 99%). Deciles are the 10, 20, 30, 40, 50, 60, 70, 80, and 90th percentiles. Quintiles are the 20, 40, 60, and 80th percentiles. Quartiles are the 25, 50, and 75th percentiles. The median is the 50th percentile. Some software programs regard the minimum and maximum as the 0th and 100th percentile, respectively; however, such terminology is an extension beyond traditional statistics definitions. For an infinite population, the \'\'p\'\'th \'\'q\'\'-quantile is the data value where the cumulative distribution function is \'\'p\'\'/\'\'q\'\'. For a finite sample of \'\'N\'\' data points, calculate \'\'Np\'\'/\'\'q\'\'--if this is not an integer, then round up to the next integer to get the appropriate sample number (assuming samples ordered by increasing value); if it is an integer then any value from the value of that sample number to the value of the next can be taken as the quantile, and it is conventional (though arbitrary) to take the average of those two values.\n\nMore formally: the \'\'p\'\'th \'\'q\'\'-quantile of the distribution of a random variable \'\'X\'\' can be defined as the value(s) \'\'x\'\' such that:\n\n:P(X\\leq x)\\geq \\frac{p}{q} \\ \\mathrm{and} \\ P(X\\geq x)\\geq \\frac{q-p}{q}.\n\nIf instead of taking \'\'p\'\' and \'\'q\'\' as integers, the \'\'p\'\'-quantile is based on a [[real number]] \'\'p\'\' with 0<\'\'p\'\'<1 then this becomes: the \'\'p\'\'-quantile of the distribution of a random variable \'\'X\'\' can be defined as the value(s) \'\'x\'\' such that:\n\n:P(X\\leq x)\\geq p \\ \\mathrm{and} \\ P(X\\geq x)\\geq 1-p.\n\nFor example, given the 10 data values {3, 6, 7, 8, 8, 10, 13, 15, 16, 20}, the first quartile is determined by 10*1/4 = 2.5, which rounds up to 3, and the third sample is 7. The second quartile value (same as the median) is determined by 10*2/4 = 5, which is an integer, so take the average of the fifth and sixth values, that is (8+10)/2 = 9, though any value from 8 through to 10 could be taken to be the median. The third quartile value is determined by 10*3/4 = 7.5, which rounds up to 8, and the eighth sample is 15. The motivation for this method is that the first quartile should divide the data between the bottom quarter and top three-quarters. Ideally, this would mean 2.5 of the samples are below the first quartile and 7.5 are above, which in turn means that the third data sample is \"split in two\", making the third sample part of both the first and second quarters of data, so the quartile boundary is right at that sample. (Note that the quartile is the boundary between two quarters, which are the data sets. The first quarter are those data below the first quartile, the second quarter those data between the first and second quartiles, etc. In statistics the first quarter is the lowest quarter, whereas in everyday life, such as ranking students by grade, the first quarter is often regarded as the highest quarter. \n\nStandardized test results are commonly misinterpreted as a student scoring \"in the 80th percentile\", for example, as if the 80th percentile is an interval to score \"in\", which it is not; one can score \"at\" some percentile or between two percentiles, but not \"in\" some percentile.)\n\nIt should be noted that different software packages use slightly varying algorithms, so the answer they produce may be slightly different for any given set of data. Besides the algorithm given above, which is the proper one based on probability, there are at least four other algorithms commonly used (for various reasons, such as of ease of computation, ignorance, etc.).\n\nIf a distribution is symmetrical, then the median is the mean, but this is not generally the case.\n\nQuantiles are useful measures because they are less susceptible to long tailed distributions and outliers. For instance, with a random variable that has an [[sebaran eksponensial]], any particular sample of this random variable will have roughly a 63% chance of being less than the mean. This is because the exponential distribution has a long tail for positive values, but is zero for negative numbers.\n\nEmpirically, if the data you are analyzing are not actually distributed according to your assumed distribution, or if you have other potential sources for outliers that are far removed from the mean, then quantiles may be more useful descriptive statistics than means and other moment related statistics.\n\nClosely related is the subject of [[robust regression]] in which the sum of the absolute value of the observed errors is used in place of the squared error. The connection is that the mean is the single estimate of a distribution that minimizes expected squared error while the median minimizes expected absolute error. Robust regression shares the ability to be relatively insensitive to large deviations in outlying observations.\n\nThe quantiles of a random variable are generally preserved under increasing transformations, in the sense that for example if \'\'m\'\' is the median of a random variable \'\'X\'\' then 2\'\'m\'\' is the median of 2\'\'X\'\', unless an arbitrary choice has been made from a range of values to specify a particular quantile. Quantiles can also be used in cases where only [[ordinal]] data is available.','',13,'Budhi','20050221002309','',0,0,0,0,0.045045862461,'20050221002309','79949778997690'); INSERT INTO cur VALUES (1409,0,'Momen_(matematik)',':\'\'Tempo oge [[moment (physics)]].\'\'\n\nKonsep \'\'\'moment\'\'\' dina [[matematik]] diwangun tina konsep \'\'\'moment\'\'\' dina [[fisika]]. Moment ka-\'\'n\'\' tina fungsi nilai-riil \'\'f\'\'(\'\'x\'\') tina variabel riil nyaeta \n\n:\\mu\'_n=\\int_{-\\infty}^\\infty x^n\\,f(x)\\,dx.\n\nThe \'\'\'problem of moments\'\'\' seeks characterizations of sequences { μ′\'\'n\'\' : \'\'n\'\' = 1, 2, 3, ... } that are sequences of moments of some function \'\'f\'\'.\n\nIf (lower-case) \'\'f\'\' is a [[probability density function]], then the value integral above is called the \'\'n\'\'th moment of the [[probability distribution]]. More generally, if (capital) \'\'F\'\' is a [[cumulative distribution function|cumulative probability distribution function]] of any probability distribution, which may not have a density function, then the \'\'n\'\'th moment of the probability distribution is given by the [[Riemann-Stieltjes integral]]\n\n:E(X^n)=\\int_{-\\infty}^\\infty x^n\\,dF(x),\n\ndimana \'\'X\'\' nyaeta [[variabel random]] nu ngabogaan sebaran ieu.\n\nThe \'\'n\'\'th \'\'\'[[moment about the mean|central moment]]\'\'\' of the probability distribution of a random variable \'\'X\'\' is\n\n:\\mu_n=E((X-\\mu_1\')^n).\n\nTCentral momen kadua nyaeta [[varian]].\n\nThe central momemts are clearly translation-invariant, i.e., the \'\'n\'\'th central moment of \'\'X\'\' is the same as that of \'\'X\'\' + \'\'c\'\' for any constant \'\'c\'\' (in this context \"constant\" means a \'\'non-random\'\' quantity).\n\nThe first moment and the second and third \'\'central\'\' moments are linear in the sense that\n\n:\\mu_1(X+Y)=\\mu_1(X)+\\mu_1(Y)\n\nand\n\n:\\operatorname{var}(X+Y)=\\operatorname{var}(X)+\\operatorname{var}(Y)\n\nand\n\n:\\mu_3(X+Y)=\\mu_3(X)+\\mu_3(Y)\n\nif \'\'X\'\' and \'\'Y\'\' are [[statistical independence|independent]] random variables (independence is not needed for the first of these three identities; for the second it can be weakened to [[correlation|uncorrelatedness]]).\n\nThe central moments beyond the third lack this linearity; in that respect they differ from the [[cumulant]]s (the first three cumulants are the same as the first moment and the second and third \'\'central\'\' moments; the higher cumulants have a more complicated relationship with the central moments).\n\nLike the cumulants, the [[factorial moment]]s of a probability distribution are also polynomial functions of the moments.\n\n[[Category:Probability theory]]\n[[Category:Mathematical analysis]]','',13,'Budhi','20040907115533','',0,0,0,0,0.498312073526,'20041203173307','79959092884466'); INSERT INTO cur VALUES (1410,0,'Moment-generating_function','Dina [[probability theory]] jeung [[statistik]], \'\'\'fungsi moment-generating\'\'\' tina [[variabel random]] \'\'X\'\' nyaeta\n:M_X(t)=E\\left(e^{tX}\\right).\nFungsi moment-generating ngahasilkeun [[moment (mathematics)|moments]] tina [[probability distribution]], nyaeta:\n\n:E\\left(X^n\\right)=M_X^{(n)}(0)=\\left.\\frac{\\mathrm{d}^n}{\\mathrm{d}t^n}\\right|_{t=0} M_X(t).\n\nLamun \'\'X\'\' mibanda [[probability density function]] kontinyu \'\'f\'\'(\'\'x\'\') mangka fungsi moment generating diberekeun ku\n\n:M_X(t) = \\int_{-\\infty}^\\infty e^{tx} f(x)\\,\\mathrm{d}x\n::: = \\int_{-\\infty}^\\infty \\left( 1+ tx + \\frac{t^2x^2}{2!} + \\cdots\\right) f(x)\\,\\mathrm{d}x\n::: = 1 + tm_1 + \\frac{t^2m_2}{2!} +\\cdots,\n\ndimana m_i ngarupakeun [[moment (mathematics)|moment]] ka-\'\'i\'\'.\n\nTeu paduli kana [[probability distribution]] kontinyu atawa heunteu, fungsi moment-generating diberekeun ku [[Riemann-Stieltjes integral]]\n\n:\\int_{-\\infty}^\\infty e^{tx}\\,dF(x)\n\ndimana \'\'F\'\' nyaeta [[cumulative distribution function]].\n\nKonsep nu pakait kaasup [[characteristic function]], [[probability-generating function]], jeung fungsi [[cumulant]]-generating. Fungsi cumulant-generating nyaeta bentuk logaritma tina fungsi moment-generating.','',13,'Budhi','20040902003246','',0,0,0,0,0.182129934049,'20040902003246','79959097996753'); INSERT INTO cur VALUES (1413,0,'Galton-Watson_process','[[Category:Stochastic processes]]\n\nThe \'\'\'Galton-Watson process\'\'\' is a [[stochastic process]] arising from [[Francis Galton]]\'s statistical investigation of the extinction of [[family name|surnames]].\n\n== History ==\n\nThere was concern amongst the [[Victorian era|Victorian]]s that [[aristocratic]] surnames were becoming extinct. Galton originally posed the question regarding the probability of such an event in the [[Educational Times]] of 1837, and the Reverend [[Henry William Watson]] replied with a solution. Together, they then wrote an 1874 paper entitled \'\'On the probability of extinction of families\'\'. However, the concept was previously discussed by [[I. J. Bienaymé]]; see Heyde and Seneta 1977; though it appears that Galton and Watson derived their process independently. For a detailed history see Kendall (1966 and 1975)\n\n== Concepts ==\n\nAssume, as was taken quite for granted in Galton\'s time, that surnames are passed on to all male children by their father. Suppose the number of a man\'s sons to be a [[random variable]] [[probability distribution|distributed]] on the set { 0, 1, 2, 3, ...}. Further suppose the numbers of different men\'s sons to be [[statistical independence|independent]] random variables, all having the same distribution.\n\nThen the simplest substantial mathematical conclusion is that if the average number of a man\'s sons is 1 or less, then their surname will surely die out, and if it is more than 1, then there is more than zero probability that it will survive forever.\n\n== Applications ==\n\nApart from the extinction of family problems, it also has other applications. For example, calculating the probability of [[extinction]] of a small [[population]] of [[organisms]].\n\n==Tempo oge==\n\n:[[branching process]]\n\n== Rujukan ==\n\n* \'\'\'C C Heyde and E Seneta\'\'\' (1977) \'\'I.J. Bienayme: Statistical Theory Anticipated\'\'. Berlin, Germany.\n* \'\'\'D G Kendall\'\'\'. (1966) \'\'[[Journal of the London Mathematical Society]]\'\' \'\'\'41\'\'\':385-406\n* \'\'\'D G Kendall\'\'\'. (1975) \'\'[[Bulletin of the London Mathematical Society]]\'\' \'\'\'7\'\'\':225-253\n\n== Tumbu kaluar ==\n\n* [http://www.mugu.com/browse/galton/search/essays/pages/galton-1874-jaigi-family-extinction_1.htm On the Probability of the Extinction of Families]\n* [http://www-users.york.ac.uk/~pml1/stats/gwproc.ps] paper that took some of the above from.','/* See also */',13,'Budhi','20040904011636','',0,0,0,0,0.366626944564,'20040904011636','79959095988363'); INSERT INTO cur VALUES (1414,0,'Data_clustering','\'\'\'Data clustering\'\'\' is a common technique for data analysis, which is used in many fields, including [[machine learning]], [[data mining]], [[pattern recognition]], [[image analysis]] and [[bioinformatics]]. Clustering consists of partitioning a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait - often similarity or proximity for some defined distance measure.\n\n\nData clustering algorithms can be [[hierarchical]] or [[partitional]], and hierarchical algorithms can be [[agglomerative]] (bottom-up) or [[divisive]] (top-down).\n\n==Hierarchical clustering==\n\n===Introduction===\n\nHierarchical clustering builds a hierarchy of clusters from individual elements. The traditional representation of this hierarchy is a tree, with individual elements at one end and a single cluster with every element at the other.\n\n[[Image:hierarchical_clustering.png|Traditional representation]]\n\nCutting the tree at a given height will give a clustering at a selected precision. In the above example, cutting after the second row will yield clusters {a} {b c} {d e} {f}. Cutting after the third row will yield clusters {a} {b c} {d e f}, which is a coarser clustering, but with fewer clusters.\n\n===Agglomerative hierarchical clustering===\n\nThis methods builds the hierarchy from the individual elements by progressively merging clusters. Again, we have six elements {a} {b} {c} {d} {e} and {f}. the first step is to determine which elements to merge in a cluster. Usually, we want to take the two closest elements, therefore we must define a distance d(element_1,element_2) between elements.\n\nSuppose we have merged the two closest elements {b} and {c}, we now have the following clusters {a} {b c} {d} {e} and {f}, and want to merge them further. But to do that, we need to take the distance between {a} and {b c}, and therefore define the distance between two clusters. Usually the distance between two clusters \\mathcal{A} and \\mathcal{B} is one of the following:\n* the maximum distance between elements of each cluster (also called complete linkage clustering) max_{x \\in \\mathcal{A}, y \\in \\mathcal{B}} d(x,y) \n* the minimum distance between elements of each cluster (also called single linkage clustering) min_{x \\in \\mathcal{A}, y \\in \\mathcal{B}} d(x,y) \n* the mean distance between elements of each cluster (also called average linkage clustering) {1 \\over {card(\\mathcal{A})card(\\mathcal{B})}}\\sum_{x \\in \\mathcal{A}}\\sum_{ y \\in \\mathcal{B}} d(x,y) \n* the sum of all intra cluster variance\n* the increase in variance for the cluster being merged (Ward\'s criterion)\n\nEach of the agglomeration occurs at a certain distance between clusters and one can decide to stop clustering either when the clusters are too far apart to be merged (distance criterion) or when there is a sufficiently small number of clusters (number criterion).\n\n==K-means and derivatives==\n\n===k-means clustering===\n\nThe k-means algorithm assigns each point to the cluster which center (or centroid) is nearest, the centroid being defined as the point which is the average of all the points in the cluster.\n\nAs one can see, this is not a complete definition, because the clusters depend on the centroid and the centroid depend on the cluster, so the following algorithm is used:\n* Choose a number of clusters\n* Assign each point randomly to a cluster\n* Repeat until the algorithm has converged (that is, no more points are changing cluster during one iteration) :\n** Compute the centroid for each cluster, that is the point which coordinates is the mean of all the points in the cluster\n** For each point, assign it to the the cluster which centroid is nearest\n\nThe main advantages of this algorithm are its simplicity and speed, which allows it to run on large datasets. Yet it does not systematically yield the same result with each run of the algorithm, depending on the initial assignation of each point to a cluster.\n\nThe k-means algorithm maximizes inter-cluster (or minimizes intra-cluster) variance, but does not ensure that the solution given is not a local minimum of variance.\n\n===fuzzy c-means clustering===\n\nOne of the problems of the k-means algorithm is that it gives a \'\'hard partitioning\'\' of the data, that is to say that each point is attributed to one and only one cluster. But points on the edge of the cluster, or near another cluster may not be as much \'\'in the cluster\'\' as point in the center of cluster.\n\nTherefore, in fuzzy clustering, each point does not pertain to a given cluster, but has a degree of belonging to a certain cluster, as in [[fuzzy logic]]. For each point \'\'x\'\' we have a coefficient giving the degree of being in the \'\'k\'\'-th cluster u_k(x). Usually, the sum of those coefficients has to be one, so that u_k(x) denotes a probability of belonging to a certain cluster. \\forall x \\sum_{k=1}^{num. clusters} u_k(x) \\ =1\n\nWith fuzzy c-means, the centroid of a cluster is computed as being the mean of all points, weighted by their degree of belonging to the cluster, that is center_k = {{\\sum_x u_k(x) x} \\over {\\sum_x u_k(x)}}. \n\nThe degree of being in a certain cluster is the inverse of the distance to the cluster u_k(x) = {1 \\over d(center_k,x)}, then the coefficients are normalized so that their sum is 1.\n\nThe fuzzy c-means algorithm is greatly similar to the k-means algorithm:\n* Choose a number of clusters\n* Assign randomly to each point coefficients for being in the clusters\n* Repeat until the algorithm has converged (that is, the coefficients\' change between two iterations is no more than \\epsilon, the given sensitivity threshold) :\n** Compute the centroid for each cluster, using the formula above\n** For each point, compute its coefficients of being in the clusters, using the formula above\n\nThe fuzzy c-means algorithm minimizes intra-cluster variance as well, but has the same problems as k-means, the minimum is local minimum, and the results depend on the initial choice of weights.\n\n==Pamakean==\nDina [[biologi]] ngabogaan dua pamakean dina widang komputasi biologi jeung [[bioinformatics]].\n*Dina [[proteomics]], kluster dipake keur ngawangun grup [[proteins]] nu pakait jeung polana. Often such groups contain functionally related proteins, and thus high throughput experiments using [[expressed sequence tag]]s (ESTs) can be a powerful tool for [[genome annotation]], a general aspect of [[genomics]].\n* In [[sequence analysis]], clustering is used to group homologous sequences into [[list of gene families|gene families]]. This is a very important concept in bioinformatics, and [[evolutionary biology]] in general. See evolution by [[gene duplication]].\n\n==Rujukan==\n* Jain, Murty and Flynn: \'\'Data Clustering: A Review\'\', ACM Comp. Surv, 1999. Available [http://citeseer.ist.psu.edu/jain99data.html here]\n* for another presentation of hierarchical, k-means and fuzzy c-means see this [http://www.elet.polimi.it/upload/matteucc/Clustering/tutorial_html/index.html introduction to clustering]. Also has an explanation on mixture of gaussians.\n\n==Tempo oge==\n[[k-means]], [[ANN]]\n\n[[de:clustering]]\n\n[[Category:Machine learning]]','/* Applications */',13,'Budhi','20040904230907','',0,0,0,0,0.275324318221,'20040904230907','79959095769092'); INSERT INTO cur VALUES (1415,0,'De_Finetti\'s_theorem','Dina [[tiori probabiliti]], \'\'\'teorema de Finetti\'\'\' nerangkeun kunaon observasi \'\'bisa digantikeun\'\' ngarupakeun \'\'kondisional\'\' bebas tina sababaraha (umumna) kuantitas teu ka-observasi nu mana [[epistemic probability]] [[probability distribution|distribution]] bakal ditangtukeun. Ieu ngaran keur ngahargaan ka [[Bruno de Finetti]].\n\nSalah sahiji beda antara [[Bayesianism|Bayesian]] jeung metoda [[frequentism|frequentist]] dina [[statistical inference]] nyaeta frequentists often treat observations as [[statistical independence|independent]] that Bayesians treat as \'\'exchangeable\'\'. A Bayesian statistician will often seek the conditional probability distribution of that unobservable quantity given the observable data. The concept of \'\'\'exchangeability\'\'\' (see below) was introduced by de Finetti. De Finetti\'s theorem explains the mathematical relationship between independence and exchangeability.\n\nAn infinite sequence\n:X_1, X_2, X_3, \\dots\nof random variables is said to be \'\'\'exchangeable\'\'\' if for any finite cardinal number \'\'n\'\' and any two finite sequences \'\'i\'\'1, ..., \'\'i\'\'n and \'\'j\'\'1, ..., \'\'j\'\'n, the two sequences\n:X_{i_1},\\dots,X_{i_n}\nand\n:X_{j_1},\\dots,X_{j_n}\nboth have the same probability distribution.\nThe condition of exchangeability is stronger than the assumption of identical distribution of the individual random variables in the sequence, and weaker than the assumption that they are [[independent identically-distributed random variables|independent and identically distributed]]. \n\nA [[random variable]] \'\'X\'\' has a \"Bernoulli distribution\" if P(\'\'X\'\' = 0 or \'\'X\'\' = 1) = 1. \'\'\'De Finetti\'s theorem\'\'\' states that the probability distribution of any infinite exchangeable sequence of Bernoulli random variables is a \"mixture\" of the probability distributions of independent and identically distributed sequences of Bernoulli random variables. \"Mixture\", in this sense, means a weighted average, but this need not mean a finite or countably infinite (i.e., discrete) weighted average: it can be an integral rather than a sum.\n\nHere is a concrete example. Suppose \'\'p\'\' = 2/3 with probability 1/2 and \'\'p\'\' = 9/10 with probability 1/2. Suppose the conditional distribution of the sequence\n:X_1, X_2, X_3, \\dots\ngiven the event that \'\'p\'\' = 2/3, is described by saying that they are independent and indentically distributed and \'\'X\'\'1 = 1 with probability 2/3 and \'\'X\'\'1 = 0 with probability 1 - (2/3). Further, the conditional distribution of the same sequence given the event that \'\'p\'\' = 9/10, is described by saying that they are independent and identically distributed and \'\'X\'\'1 = 1 with probability 9/10 and \'\'X\'\'1 = 0 with probability 1 - (9/10). The independence asserted here is \'\'conditional\'\' independence, i.e., the Bernoulli random variables in the sequence are conditionally independent given the event that \'\'p\'\' = 2/3, and are conditionally independent given the event that \'\'p\'\' = 9/10. But they are not unconditionally independent; they are positively [[correlation|correlated]].\nIn view of the [[law of large numbers|strong law of large numbers]], we can say that\n:\\lim_{n\\rightarrow\\infty}(X_1+\\cdots+X_n)/n = \\left\\{\\begin{matrix}\n2/3 & \\mbox{with probability }1/2 \\\\\n9/10 & \\mbox{with probability }1/2\n\\end{matrix}\\right\\}.\nRather than concentrating probability 1/2 at each of two points between 0 and 1, the \"mixing distribution\" can be any [[probability distribution]] supported on the interval from 0 to 1; which one it is depends on the joint distribution of the infinite sequence of Bernoulli random variables.\n\nAnother way of stating the conclusion of de Finetti\'s theorem is that the Bernoulli random variables are conditionally independent given the [[tail sigma-field]].\n\nThe conclusion of the first version of the theorem above makes sense if the sequence of exchangeable Bernoulli random variables is finite, but the theorem is not generally true in that case. It is true if the sequence can be extended to an exchangeable sequence that is infinitely long. The very simplest example of an exchangeable sequence of Bernoulli random variables that cannot be so extended is the one in which \'\'X\'\'1 = 1 - \'\'X\'\'2 and \'\'X\'\'1 is either 0 or 1, each with probability 1/2. This sequence is exchangeable, but cannot be extended to an exchangeable sequence of length 3, let alone an infinitely long one.','',13,'Budhi','20041224210728','',0,0,1,0,0.712251823727,'20041224210728','79958775789271'); INSERT INTO cur VALUES (1416,0,'Régrési_Deming','\'\'\'Régrési Deming\'\'\' nyaeta metoda [[linear regression]] nu nangtukeun garis panghadena keur susunan data nu pakait. Régrési ieu beda jeung régrési liniér dina ngitung kasalahan boh dina sumbu-\'x\' jeung sumbu-\'y\'.\n\nKeur conto, lamun data dina sumbu-x dipikanyaho henteu mibanda kasalahan, tapi dina sumbu-y mibanda kasalahan, (saperti dina estimasi populasi (y), dina waktu nu dipikanyaho (x)), mangka bisa make régrési liniér sederhana.\n\nLamun duanana susunan data mibanda kasalahan, conto hubungan antara konsentrasi dua material dina getih, régrési Deming mere hasil nu leuwih hade.\n\nHal anu teu nguntungkeun dina régrési Deming nyaeta sacara matematis leuwih kompleks waktu dipake ngitung. Ieu hartina dina ngalakukeun itungan, dina tulisan séjén, atawa dina nulis rumus keur [[spreadsheet]], leuwih hese.\n\n{{msg:stub}}','',13,'Budhi','20041224100319','',0,0,1,0,0.766221781618,'20041224100348','79958775899680'); INSERT INTO cur VALUES (1417,0,'Demografik','\'\'\'Demographics\'\'\' comprises selected characteristics of a population (age and income distribution and trends, mobility, educational attainment, home ownership and employment status, for instance) for purposes social studies. It is also used in [[marketing]], [[marketing research]], opinion research and the study of [[consumer behaviour]]. This article discusses demographics as used in marketing.\n\n==Demographic variables==\n\nMarketers often group [[consumers]] into [[market segment|segments]] based on demographic variables. The most frequently used demographic variables are:\n*age\n*gender\n*[[sexual orientation]]\n*family size\n*family life cycle\n*income\n*occupation\n*education\n*home ownership\n*[[socioeconomics|socioeconomic]] status\n*[[religion]]\n*nationality\nIn addition to demographic variables, marketers can segment a population based on psychographic, geographic, and behavioural variables. See [[market segment]] for a list.\n\n==Demographics is an applied art== \n\nThe term demographics is often used erroneously for [[demography]], the study of human [[population]] and its structure and change. Whereas demography is a descriptive and predictive science, demographics is an applied art and science. In both cases however, the objects of study are the characteristics of human populations. In the case of demography the characteristics being studied tend to emphasize biological processes such as population dynamics, whereas demographics is also concerned with a wide range of economic, social, and cultural characteristics. Demographics is interested in any population characteristic that might be useful in understanding what people think, what they are willing to buy, and how many fit this profile.\n\n==Demographic profiles==\n\nMarketers typically combine several variables to define a \'\'\'demographic profile\'\'\'. A demographic profile (often shortened to \"a demographic\") provides enough information about the typical member of this group to create a mental picture of this hypothetical aggregate. For example, a marketer might speak of the single, [[female]], [[middle-class]], age 18 to 24 demographic.\n\nMarketing researchers typically have two objectives in this regard: first to determine what segments or subgroups exist in the overall population; and secondly to create a clear and complete picture of the characteristics of a typical member of each of these segments. Once these profiles are constructed, they can be used to develop a [[marketing strategies|marketing strategy]] and [[marketing plan]].\n\n==Demographic trends==\n\nMany demographic trends are quite easy to determine. This is due to the predictability of many demographic relationships. If, for example, the birth rate increases during certain years (as indeed happened during the [[baby boom]] years), we can determine that there will be an increase in the demand for baby food and diapers. In several years there will be an increase in the demand for toys and children\'s clothes; after a decade an increased demand for public education, [[video games]] and music [[compact disc|CDs]]; after two decades an increased demand for university services, compact automobiles, rental apartments, wedding photographers, and furniture; after four decades an increase in the demand for houses, sedan cars, [[insurance]], weight-loss centres, and investment services; after six decades an increased demand for health-care services and undertakers. \n\nDemographic trends have been used to explain everything from the demand for vacation properties, to the [[tennis]] craze of the [[1970s]], to election and stock market results. Of course no social phenomena is so simple as to be explicable with demographics alone, but it is a good start. This is the meaning of professor D. Foot\'s (1996) often quoted claim that \"demographics explains about two-thirds of everything\".\n\nDr. Dychtwald (1989) describes the \"aging of [[United States|America]]\" and convincingly argues that the changing age distribution of the American population is \"the most important trend in our time\". He considers the consequences of demographic facts like: the over 50 age group owns 77% of all financial assets in America, accounts for more than 50% of all new car sales (by value), spends more on travel and recreation than any other age group, etc. He asks what will happen to health care systems and social security entitlements (pension benefits) when the greying of America places additional demands on the system while simultaneously reducing the number of contributors into the system.\n\nSterling and Waite (1998) describe this aging trend in terms of \"generational warfare\". They ask what will happen to the value of the real estate and financial assets when the aging baby boomers all try to sell them. How will the younger age cohort react to this?\n\nOther recent demographic trends include the rise of the two income family, the single parent family, and the nuclear family.\n\n==Generational cohorts==\n\nA \'\'\'generational cohort\'\'\' has been defined as \"the aggregation of individuals (within some population definition) who experience the same event within the same time interval\" (Ryder, N., \'\'The cohort as a concept in the study of social change\'\', presented at the 1959 annual meeting of the American Sociological Association). The notion of a group of people bound together by the sharing of the experience of common historical events was first introduced by Karl Mannheim in the early 1920s. Today the concept has found its way into popular culture through well known epitomes like \"baby boomer\" and \"gen-Xer\".\n\nAn interesting study by Strauss and Howe (\'\'The fourth turning\'\') looked at generational similarities and differences going back to the 15th century and concluded that over 80 year spans, generations proceed through 4 stages of about 20 years each. The first phase consists of times of relative crisis and the people born during this period were called \"artists\". The next phase was a \"high\" period and those born in this period were called \"prophets\". The next phase was an \"awakening period\" and people born in this period were called \"nomads\". The final stage was the \"unraveling period\" and people born in this period were called \"heros\". The most recent \"high period\" occurred in the 50s and 60s (hence baby boomers are the most recent crop of \"prophets\").\n\nThe most definitive recent study was done by Schuman and Scott (1989) in 1985 in which a broad sample of adults of all ages were asked, \"What world events over the past 50 years were especially important to them?\". They found that 33 events were mentioned with great frequency. When the ages of the respondents were correlated with the expressed importance rankings, seven distinct cohorts became evident. Today we use the following descriptors for these cohorts:\n*\'\'\'Depression cohort\'\'\' (born from 1912 to 1921) \n**Memorable events : [[The Great Depression]], high levels of [[unemployment]], poverty, lack of creature comforts, financial uncertainty\n**Key characteristics: strive for financial security, risk averse, waste not want not attitude, strive for comfort\n* \'\'\'[[World War Two|WWII]] cohort\'\'\' (born from 1922 to 1927)\n**Memorable events: men leaving to go to war and many not returning, the personal experience of the war, women working in factories, focus on defeating a common enemy\n**Key characteristics: the nobility of sacrifice for the common good, patriotism, team player\n* \'\'\'Post-war cohort\'\'\' (born from 1928 to 1945)\n**Memorable events: sustained economic growth, social tranquility, [[The Cold War]], [[McCarthyism]]\n**Key characteristics: conformity, [[conservatism]], traditional family values\n* \'\'\'Baby Boomer cohort #1\'\'\' (born from 1946 to 1954)\n**Memorable events: [[assassination]] of [[JFK]], [[Robert Kennedy]], and [[Martin Luther King]], political unrest, walk on the moon, [[Vietnam War]], anti-war protests, social experimentation, sexual freedom, [[civil rights movement]], environmental movement, womens movement, protests and riots, experimentation with various intoxicating recreational substances\n**Key characteristics: experimental, individualism, free spirited, social cause oriented\n* \'\'\'Baby Boomer cohort #2\'\'\' (born from 1955 to 1965)\n**Memorable events: [[Watergate]], [[Richard Nixon|Nixon]] resigns, defeat in Vietnam, the oil embargo, raging inflation, gasoline shortages\n**Key characteristics: less optimistic, distrust of government, general cynicism\n* \'\'\'Generation X cohort\'\'\' (born from 1965 to 1976)\n**Memorable events: \'\'Challenger\'\' explosion, [[Iran-Contra]], social malaise, reagonomics, [[AIDS]], safe sex, fall of [[Berlin Wall]], single parent families\n**Key characteristics: quest for emotional security, independent, informality, entrepreneurial \n* \'\'\'N Generation cohort\'\'\' (born from 1977 to date)\n**Memorable events: rise of the [[internet]], [[September 11, 2001 attacks|9-11]] terrorist attack, cultural diversity, 2 wars in [[Iraq]]\n**Key characteristics: quest for physical security and safety, patriotism, heightened fears, acceptance of change\n\n==Criticisms and Qualifications==\nDemographc profiling is essentially an exercise in making generalizations about groups of people. As with all such generalizations we must be aware that many individuals within these groups will not conform to the profile. Demographic techniques are simplifications of reality and should not blind us to the richness of individual complexity. Most importantly, we must not prejudice our view of specific situations by setting up expectations about individuals based on generalizations about groups that they belong to. Demographic information is aggregate and probabilistic information about groups, not about specific individuals.\n\nMost demographic information is culturally specific. The generational cohort information above, for example, applies primarily to North America (and to a lesser extent to Western Europe). Serious errors result when demographic information is applied to groups other than ones similar to those in the original study.\n\n==See also==\n\n* [[Marketing]]\n* [[List of marketing topics]]\n* [[Consumer behaviour]]\n* [[Marketing research]]\n\n==Rujukan==\n* [http://www.ericdigests.org/pre-9214/coping.htm Coping with Changing Demographics]\n* Foot, D. (1996), \'\'Boom, Bust and Echo: How to profit from the coming demographic shift\'\', MacFarlane Walter & Rose, Toronto, 1996, ISBN 0-921912-97-8\n* Dychtwald, K. (1989), \'\'Age Wave: The challenges and opportunities of an aging North America\'\', St. Martins Press, New York, 1989, ISBN 0-87477-441-1\n* Sterling, W. & White, S. (1998), \'\'Boomernomics: The future of your money in the upcoming generational warfare\'\', The Library of Contemporary Thought (Ballantine Publishing), New York, 1998, ISBN 0-345-42583-9\n* Schuman, H. and Scott, J. (1989), Generations and collective memories, \'\'American Psychological Review\'\', vol. 54, 1989, pp. 359-81\n* Meredith, G., Schewe, C., and Haim, A. (2002), \'\'Managing by defining moments: Innovative strategies for motivating 5 very different generational cohorts\'\', Hungry Minds Inc., New York, 2002, ISBN 0-7645-5412-3','/* References */',13,'Budhi','20041224092718','',0,0,1,0,0.583962452404,'20050103081603','79958775907281'); INSERT INTO cur VALUES (1419,0,'Demographic_statistics','Among the kinds of data that national leaders need are the \'\'\'[[Demography|demographic]] statistics\'\'\' of their population. Records of births, deaths, marriages, immigration and emigration and a regular census of population provide information that is key to making sound decisions about national policy.\n\nA useful summary of such data is the [[population pyramid]]. It provides data about the sex and age distribution of the population in an accessible graphical format.\n\nAnother summary is called the [[life table]]. For a \'\'cohort\'\' of persons born in the same year, it traces and projects their life experiences from birth to death. For a given cohort, the proportion expected to survive each year (or decade in an \'\'abridged life table\'\') is presented in tabular or graphical form.\n\nThe ratio of males to females by age indicates the consequences of differing mortality rates on the sexes. Thus, while values above one are common for newborns, the ratio dwindles until it is well below one for the older population.\n\n==Tumbu kaluar==\n* Keur conto, tempo laporan statistik dina [http://www.magnet.mt/home/cos/cospubs/demography/1997/index.htm Malta]\n* [http://www.statcan.ca/english/kits/animat/pyone.htm Population pyramid]\n* [http://www.ac.wwu.edu/~drl/lifetable.htm Life Table]\n\nback to [[applied statistics]]','/* External links */',13,'Budhi','20041224114338','',0,0,1,0,0.906142212407,'20050103081414','79958775885661'); INSERT INTO cur VALUES (1420,0,'Estimasi_densiti','Dina [[kamungkinan|probabiliti]] jeung [[statistik]],\n\'\'\'estimasi densiti\'\'\' nyaeta konstruksi tina estimasi, dumasar kana [[data]] observasi,nu teu ka observasi dina kaayaan [[probability density function|fungsi probabiliti densiti]]. Fungsi densiti nu teu ka-observasi dianggap salaku densiti dina sebaran populasi nu gede; data umumna dianggap salaku sampel random tina populasi.\n\nLoba cara dipake keur ngitung estimasi densiti, kaasup [[Parzen windows|jandela Parzen]] sarta teknik rentang [[data clustering]].\n\nIeu ngarupakeun [[illustration of density estimation|gambaran estimasi densiti]].\n\n== Rujukan ==\n\n* Trevor Hastie, Robert Tibshirani, and Jerome Friedman. \'\'The Elements of Statistical Learning\'\'. New York: Springer, 2001. ISBN 0-387-95284-5. \'\'(See Chapter 6.)\'\'\n\n* D.W. Scott. \'\'Multivariate Density Estimation. Theory, Practice and Visualization\'\'. New York: Wiley, 1992.\n\n* B.W. Silverman. \'\'Density Estimation\'\'. London: Chapman and Hall, 1986.\n\n----\n{{msg:stub}}\n\n[[Category:Probability and statistics]]','',13,'Budhi','20040906025420','',0,0,0,0,0.202759625019,'20040906025443','79959093974579'); INSERT INTO cur VALUES (1421,0,'Illustration_of_density_estimation','Here is an \'\'\'illustration of [[density estimation]]\'\'\'.\nWe consider records of the incidence of diabetes.\nThe following is quoted verbatim from the data set description:\n\n:A population of women who were at least 21 years old, of Pima Indian heritage and living near Phoenix, Arizona, was tested for diabetes according to World Health Organization criteria. The data were collected by the US National Institute of Diabetes and Digestive and Kidney Diseases. We used the 532 complete records after dropping the (mainly missing) data on serum insulin.\n\nIn this example, \nwe will construct three density estimates for \"glu\" (plasma glucose concentration),\none conditional on the presence of diabetes,\nthe second conditional on the absence of diabetes,\nand the third not conditional on diabetes.\nThe conditional density estimates will then be used to construct the probability of diabetes conditional on \"glu\".\n\nThe \"glu\" data are the following.\nThese were obtained from the MASS package of the [[R programming language]]\nas data(Pima.tr) (200 records) and data(Pima.te) (332 records).\nWithin R, ?Pima.tr and ?Pima.te give a fuller account of the data.\n\nFor the records of cases with diabetes (177 records),\nthese are the observed values of \"glu\", measured in milligrams per deciliter:\n\n: 195, 97, 128, 137, 189, 92, 143, 149, 164, 140, 121, 105, 176, 171, 199, 154, 167, 184, 139, 134, 131, 158, 112, 181, 168, 144, 107, 125, 125, 115, 150, 140, 148, 117, 80, 124, 103, 124, 112, 148, 145, 151, 144, 187, 129, 167, 180, 177, 152, 198, 188, 168, 197, 158, 130, 151, 115, 194, 184, 95, 100, 138, 100, 175, 133, 128, 129, 155, 148, 78, 197, 166, 118, 119, 102, 90, 111, 171, 180, 109, 100, 136, 122, 160, 162, 88, 117, 173, 170, 156, 152, 163, 104, 179, 129, 128, 109, 109, 196, 109, 85, 162, 134, 181, 179, 119, 184, 113, 155, 101, 106, 119, 107, 146, 144, 161, 128, 124, 155, 109, 152, 122, 102, 125, 196, 189, 173, 116, 105, 193, 136, 172, 173, 144, 129, 151, 181, 95, 189, 180, 104, 158, 135, 125, 84, 163, 145, 128, 90, 186, 187, 176, 111, 181, 174, 138, 112, 97, 179, 136, 155, 145, 111, 162, 142, 169, 93, 129, 187, 173, 174, 120, 147, 187, 181, 128, 170\n\nFor the records of cases without diabetes (355 records),\nthese are the observed values of \"glu\", measured in milligrams per deciliter: \n\n: 86, 77, 165, 107, 83, 193, 142, 154, 86, 99, 109, 139, 99, 100, 83, 101, 87, 99, 108, 110, 79, 148, 158, 145, 79, 71, 102, 119, 97, 129, 97, 86, 125, 123, 92, 116, 83, 114, 106, 127, 124, 109, 123, 96, 129, 92, 109, 106, 135, 121, 101, 96, 121, 100, 154, 122, 114, 114, 115, 130, 79, 112, 91, 100, 110, 94, 84, 61, 99, 154, 103, 111, 143, 81, 189, 116, 71, 137, 136, 93, 107, 97, 112, 99, 109, 120, 179, 80, 105, 191, 95, 99, 137, 97, 100, 122, 90, 120, 154, 56, 124, 85, 88, 139, 142, 126, 100, 164, 95, 122, 85, 144, 111, 107, 105, 124, 111, 137, 57, 157, 95, 140, 117, 123, 74, 119, 155, 112, 140, 141, 106, 118, 85, 89, 103, 126, 97, 109, 88, 122, 103, 180, 106, 71, 103, 101, 88, 150, 73, 105, 99, 95, 146, 129, 95, 112, 113, 83, 101, 106, 100, 123, 81, 92, 93, 81, 126, 144, 89, 97, 107, 84, 100, 93, 106, 108, 106, 90, 153, 88, 151, 102, 114, 75, 113, 108, 111, 81, 147, 125, 142, 100, 87, 197, 117, 74, 91, 91, 146, 165, 124, 111, 90, 111, 95, 96, 128, 108, 100, 104, 108, 133, 136, 96, 78, 151, 126, 120, 113, 115, 112, 157, 105, 118, 87, 95, 130, 95, 126, 139, 99, 103, 147, 99, 81, 84, 98, 87, 93, 105, 90, 125, 119, 100, 131, 127, 96, 72, 102, 112, 143, 119, 94, 102, 89, 80, 90, 117, 120, 82, 91, 134, 120, 74, 88, 124, 97, 144, 137, 132, 123, 84, 139, 173, 83, 89, 99, 81, 154, 117, 84, 94, 96, 99, 129, 68, 87, 122, 77, 127, 84, 88, 131, 116, 84, 88, 84, 103, 99, 99, 111, 98, 143, 119, 108, 112, 82, 123, 89, 108, 124, 92, 152, 105, 68, 94, 90, 94, 102, 128, 100, 103, 117, 101, 112, 98, 165, 68, 123, 95, 129, 107, 80, 127, 126, 134, 94, 108, 117, 116, 141, 106, 126, 65, 99, 102, 109, 153, 100, 121, 108, 88, 101, 121, 93\n\nThe mean of \"glu\" in the diabetes cases is 143.1 and the standard deviation is 31.26.\nThe mean of \"glu\" in the non-diabetes cases is 110.0 and the standard deviation is 24.29.\nFrom this we see that, in this data set,\ndiabetes cases are associated with greater levels of \"glu\".\nThis will be made clearer by plots of the estimated density functions.\n\nThe first figure shows density estimates of \'\'p\'\'(glu | diabetes=1), \'\'p\'\'(glu | diabetes=0), and \'\'p\'\'(glu).\nThe density estimates are kernel density estimates using a Gaussian kernel.\nThat is,\na Gaussian density function is placed at each data point,\nand the sum of the density functions is computed over the range of the data.\n\n[[Image:P glu given diabetes.png|center|360px]]\n
Estimated density of \'\'p\'\'(glu | diabetes=1) (red), \'\'p\'\'(glu | diabetes=0) (blue), and \'\'p\'\'(glu) (black).
\n\nFrom the density of \"glu\" conditional on diabetes,\nwe can obtain the probability of diabetes conditional on \"glu\" via [[Bayes\' rule]].\nFor brevity, \"diabetes\" is abbreviated \"db.\" in this formula.\n\n: p(\\mbox{diabetes}=1|\\mbox{glu})\n = \\frac{p(\\mbox{glu}|\\mbox{db.}=1)\\,p(\\mbox{db.}=1)}{p(\\mbox{glu}|\\mbox{db.}=1)\\,p(\\mbox{db.}=1) + p(\\mbox{glu}|\\mbox{db.}=0)\\,p(\\mbox{db.}=0)}\n\n\nThe second figure shows the estimated posterior probability \'\'p\'\'(diabetes=1 | glu).\nFrom these data,\nit appears that an increased level of \"glu\" is associated with diabetes.\n\n[[Image:P diabetes given glu.png|center|360px]]\n
Estimated probability of \'\'p\'\'(diabetes=1 | glu).
\n\nThe incidence of diabetes is a topic of great importance,\nand this simple analysis can only begin to suggest avenues of further inquiry.\n\n== References ==\n\n* J.W. Smith, J.E. Everhart, W.C. Dickson, W.C. Knowler, and R.S. Johannes. \"Using the ADAP learning algorithm to forecast the onset of diabetes mellitus\". In \'\'Proceedings of the Symposium on Computer Applications in Medical Care\'\' (Washington, 1988), ed. R.A. Greenes, pp. 261-265. Los Alamitos, CA: IEEE Computer Society Press, 1988.\n\n* Brian D. Ripley. \'\'Pattern Recognition and Neural Networks\'\'. Cambridge: Cambridge University Press, 1996.\n\n== Tumbu kaluar ==\n\n* [http://www.ics.uci.edu/~mlearn/MLSummary.html UCI Machine Learning Repository Content Summary] \'\'(See \"Pima Indians Diabetes Database\" for the original data set of 732 records, and additional notes.)\'\'\n\n== Script ==\n\nThe follow commands of the [[R programming language]] will create the figures shown above.\nThese commands can be entered at the command prompt by using cut and paste.\n\n library (MASS)\n data(Pima.tr)\n\n data(Pima.te)\n\n Pima <- rbind (Pima.tr, Pima.te)\n glu <- Pima[,\'glu\']\n\n d0 <- Pima[,\'type\'] == \'No\'\n d1 <- Pima[,\'type\'] == \'Yes\'\n base.rate.d1 <- sum(d1)/(sum(d1) + sum(d0))\n\n glu.density <- density (glu)\n glu.d0.density <- density (glu[d0])\n glu.d1.density <- density (glu[d1])\n\n approxfun (glu.d0.density$x, glu.d0.density$y) -> glu.d0.f\n approxfun (glu.d1.density$x, glu.d1.density$y) -> glu.d1.f\n\n p.d.given.glu <- function (glu, base.rate.d1)\n {\n p1 <- glu.d1.f(glu) * base.rate.d1\n p0 <- glu.d0.f(glu) * (1 - base.rate.d1)\n p1/(p0+p1)\n }\n\n x <- 1:250\n y <- p.d.given.glu (x, base.rate.d1)\n plot (x, y, type=\'l\', col=\'red\', xlab=\'glu\', ylab=\'estimated p(diabetes|glu)\')\n\n plot (density(glu[d0]), col=\'blue\', xlab=\'glu\', ylab=\'estimate p(glu), \n p(glu|diabetes), p(glu|not diabetes\', main=NA)\n lines (density(glu[d1]), col=\'red\')\n lines (density(glu))\n\n[[Category:Probability and statistics]]','/* External links */',13,'Budhi','20041224114433','',0,0,1,0,0.035002602746,'20041224114433','79958775885566'); INSERT INTO cur VALUES (1422,0,'Dutch_book','Dina [[gambling|judi]] \'\'\'Dutch book\'\'\' atawa \'\'\'lock\'\'\' nyaeta susunan [[odds|ganjil]] sarta[[bet|taruhan]] nu pasti meunang, teu pakait jeung hasil tina judi. Kaayaan ieu pakait jeung [[probability|kamungkinan]] ku ayana kaahengan nu teu [[Coherence (philosophical gambling strategy)|asup akal]].\n\nOne example is where a [[bookmaker]] has offered odds and attracted bets which makes the result irrelevant; in this case the implied probabilities will add up to a number greater than 1.\n{| align=\"center\" border=\"1\" cellpadding=\"2\"\n!Horse number\n!Offered odds:\n!Bets:\n!Implied
probability:\n|-\n|1\n|Evens\n|100\n|0.5\n|-\n|2\n|3 to 1 against\n|50\n|0.25\n|-\n|3\n|4 to 1 against\n|40\n|0.2\n|-\n|4\n|9 to 1 against\n|20\n|0.1\n|-\n|\'\'\'Total\'\'\'\n|\n|\'\'\'210\'\'\'\n|\'\'\'1.05\'\'\'\n|}\nIn this case, whichever horse wins, the bookmaker will pay out 200 (including returning the winning stake) and so make a profit of 10.\n\nIf for some reason Horse 4 was withdrawn and the bookmaker was foolish enough not to adjust the other odds, the implied probabilities would add up to 0.95 and a gambler could lock in a profit of 10, by betting 100, 50 and 40 on the remaining three horses respectively.\n\nOther forms of Dutch books can exist when incoherent odds are offered on exotic bets such as forecasting the order in which horses will finish. With competitive [[fixed-odds gambling]] being offered electronically, gamblers can sometimes create a Dutch book by selecting the best odds from different bookmakers, in effect by undertaking an [[arbitrage]] operation. The bookmakers should react by adjusting the offered odds in the light of demand, so as to remove the potential profit. \n\nIn [[Bayesian probability]], [[Frank Ramsey]] and [[Bruno de Finetti]] required personal degrees of belief to be [[Coherence (philosophical gambling strategy)|coherent]] so that a Dutch book could not be made against them, whichever way bets were made; in other words their degrees of belief had to satisfy the [[axioms of probability]].','',13,'Budhi','20041224210306','',0,0,1,0,0.811956940131,'20041224210306','79958775789693'); INSERT INTO cur VALUES (1423,0,'Chi-square_test','#REDIRECT [[Tes chi-kuadrat]]\n','Chi-square test dipindahkeun ka Tes chi-kuadrat',13,'Budhi','20040902224550','',0,1,0,1,0.726625503717573,'20040902224550','79959097775449'); INSERT INTO cur VALUES (1424,0,'Sampel_random','[[Sample]] nyaeta subsusunan tina [[populasi]] nu gede. \'\'\'Sampel random\'\'\' nyaeta hiji dina unggal item/obyek nu kira-kira/[[chance|mungkin]]/[[kamungkinan]]-na sarua tina populasi nu kacida gedena nu keur dipilih.\n\nTempo oge [[random]], [[random sampling]], [[stratified sampling]], [[survey sampling]], and [[statistical population|populasi statistik]].\n\n{{msg:stub','',13,'Budhi','20040907025214','',0,0,0,0,0.966539229716,'20040907025242','79959092974785'); INSERT INTO cur VALUES (1425,0,'Complex_conjugate','[[de:Konjugation_(Mathematik)]] [[ja:共役複素数]] [[pl:Liczba sprzężona]]\nDina [[matematik]], the \'\'\'complex conjugate\'\'\' \nof a [[complex number]] is given by changing the sign of the imaginary part.\nThus, the conjugate of the complex number \'\'z\'\' = \'\'a\'\' + \'\'ib\'\' (where \'\'a\'\' and \'\'b\'\' are [[real number]]s) is defined to be \'\'z*\'\' = \'\'a\'\' − \'\'ib\'\'. It is also often denoted by a bar over the number, rather than a star.\n\nFor example, (3-2\'\'i\'\')* = 3 + 2\'\'i\'\', \'\'i\'\'* = −\'\'i\'\' and 7* = 7.\n\nOne usually thinks of complex numbers as points in a plane with a [[cartesian coordinate system]]. The \'\'x\'\'-axis contains the real numbers and the \'\'y\'\'-axis contains the multiples of \'\'i\'\'. In this view, complex conjugation corresponds to reflection at the \'\'x\'\'-axis.\n\n== Properties ==\n\nThe properties apply for all complex numbers \'\'z\'\' and \'\'w\'\', unless stated otherwise.\n\n: (\'\'z\'\' + \'\'w\'\')* = \'\'z*\'\' + \'\'w*\'\'\n: (\'\'zw\'\')* = \'\'z*\'\' \'\'w*\'\'\n: (\'\'z/w\'\')* = \'\'z*\'\' / \'\'w*\'\' if \'\'w\'\' is non-zero\n: \'\'z\'\'* = \'\'z\'\' if and only if \'\'z\'\' is real\n: |\'\'z\'\'*| = |\'\'z\'\'|\n: |\'\'z\'\'|2 = \'\'z\'\' \'\'z\'\'*\n: \'\'z\'\'-1 = \'\'z\'\'* / |z|2    if \'\'z\'\' is non-zero\nThe latter formula is the method of choice to compute the inverse of a complex number if it is given in rectangular coordinates.\n\nIf \'\'p\'\' is a [[polynomial]] with [[real number|real]] coefficients, and \'\'p\'\'(\'\'z\'\') = 0, then \'\'p\'\'(\'\'z\'\'*) = 0 as well. Thus the roots of real polynomials outside of the real line occur in complex conjugate pairs.\n\nThe function φ(\'\'z\'\') = \'\'z\'\'* from \'\'\'C\'\'\' to \'\'\'C\'\'\' is [[continuous]]. Even though it appears to be a \"tame\" [[well-behaved]] function, it is not [[holomorphic]]; it reverses orientation whereas holomorphic functions locally preserve orientation. It is [[bijective]] and compatible with the arithmetical operations, and hence is a [[field (mathematics)|field]] automorphism. As it keeps the real numbers fixed, it is an element of the [[Galois group]] of the [[field extension]] \'\'\'C\'\'\' / \'\'\'R\'\'\'. This Galois group has only two elements: φ and the identity on \'\'\'C\'\'\'. Thus the only two field automorphisms of \'\'\'C\'\'\' that leave the real numbers fixed are the identity map and complex conjugation.\n\n== Generalizations ==\n\nTaking the [[conjugate transpose]] (or adjoint) of complex [[matrix (mathematics)|matrices]] generalizes complex conjugation. Even more general is the concept of [[adjoint operator]] for operators on (possibly infinite-dimensional) complex [[Hilbert space]]s. All this is subsumed by the *-operations of [[C-star algebra]]s.\n\nOne may also define a conjugation for [[quaternion]]s: the conjugate of \'\'a\'\' + \'\'bi\'\' + \'\'cj\'\' + \'\'dk\'\' is \'\'a\'\' − \'\'bi\'\' − \'\'cj\'\' − \'\'dk\'\'.\n\nNote that all these generalizations are multiplicative only if the factors are reversed: \n\n:(\'\'zw\'\')* = \'\'w\'\'* \'\'z\'\'*\n\nSince the multiplication of complex numbers is [[commutative]], this reversal is \"invisible\" there.','',13,'Budhi','20041224105419','',0,0,1,0,0.098528537945,'20041224114102','79958775894580'); INSERT INTO cur VALUES (1426,0,'Variance','#REDIRECT [[Varian]]\n','Variance dipindahkeun ka Varian',13,'Budhi','20040903014618','',0,1,0,1,0.755974001955217,'20040903014618','79959096985381'); INSERT INTO cur VALUES (1427,0,'Discrete_random_variable','#REDIRECT [[Variabel random diskrit]]\n','Discrete random variable dipindahkeun ka Variabel random diskrit',13,'Budhi','20040903031636','',0,1,0,1,0.59999352935701,'20040903031636','79959096968363'); INSERT INTO cur VALUES (1428,6,'BinDistApprox_large.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040903045439','',0,0,0,1,0.732045671653045,'20040917032250','79959096954560'); INSERT INTO cur VALUES (1429,4,'Log_muatan','
  • 06:38, 1 Dec 2004 [[User:Kandar|Kandar]] uploaded \"[[:Image:Panonpoé_SOHO.gif|Panonpoé_SOHO.gif]]\" (salinan foto panonpoé ti SOHO)
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','uploaded \"Panonpoé_SOHO.gif\": salinan foto panonpoé ti SOHO',3,'Kandar','20041201063855','sysop',0,0,0,0,0.86024780092784,'20041201063855','79958798936144'); INSERT INTO cur VALUES (1430,0,'Binomial_distribution','#REDIRECT [[Sebaran binomial]]\n','Binomial distribution dipindahkeun ka Sebaran binomial',13,'Budhi','20040903052311','',0,1,0,1,0.10510202041371,'20040903052311','79959096947688'); INSERT INTO cur VALUES (1431,0,'Standard_score','#REDIRECT [[Skor standar]]\n','Standard score dipindahkeun ka Skor standar',13,'Budhi','20040903055523','',0,1,0,1,0.944766730018674,'20040903055523','79959096944476'); INSERT INTO cur VALUES (1432,0,'Covariance','#REDIRECT [[Kovarian]]\n','Covariance dipindahkeun ka Kovarian',13,'Budhi','20040903064402','',0,1,0,1,0.408527619585886,'20040903064402','79959096935597'); INSERT INTO cur VALUES (1433,0,'Pilihan_probabiliti','Loba [[statistician|ahli statistik]] nyoko hiji panempo \'\'\'pilihan\'\'\' dina debat keur ngadukung [[frequency probability|interpretasi frekuensi]] tina [[kamungkinan|probabiliti]] sarta ngadukung [[personal probability|probabiliti personal]]. Hal nu penting tina ieu pilihan nyaeta, \"lamun leumpang siga entog...\". Kabehanna hayang mastikeun yen unggal kaahengan bakal nurut kana [[probability axioms|tiori aksioma probabiliti]] keur alesan interpretasi. Kadangkala maranehanna bakal make metoda nu pakait jeung metoda frekuensi, kadangkala oge make metoda [[Bayesian|Bayes]].\n\nSababaraha [[philosophers|ahli filosofi]] probabiliti ngadukung probabiliti pilihan salaku prinsip tinimbang tina panempo pragmatis. Alesanna yen beda interpretasi dina probabiliti ngarupakeun hal nu beda tina hiji hal jeung hal sejenna, dipake dina kontek nu beda. Conto, interpretasi pobabiliti make metoda frekuensi bisa ditarima keur percobaan nu berulang, interpretasi logika probabiliti dipake dina kasus tunggal nu mibanda informasi awal nu husus, sarta interpretasi probabiliti personal dipake keur kaayaan nu teu pasti. Hal ieu teu bisa disebutkeun yen nu nganalisa teu konsisten.','',13,'Budhi','20041226001715','',0,0,0,0,0.558662043679,'20041226001803','79958773998284'); INSERT INTO cur VALUES (1434,0,'Ekologi_kaliru','\'\'\'Ekologi kaliru\'\'\' mangrupa kasalahan nu remen kajadian dina interpretasi data statistik, numana kaputusan ngeunaan kaayaan individu dumasar kana kumpulan [[aggregate data|komponen statistik]] tina grup dimana eta individu aya.\n\n\'\'\'Conto:\'\'\' Nilai ujian matematika Betty di sakolana A. Di sakola Simon nilai rata-rata matematikana B. Ekologi kaliru nyaeta urang nyimpulkeun yen Betty leuwih pinter matematika tinimbang Simon, kasimpulan anu teu sakuduna dijieun.\n\nTempo ogé [[prosecutor\'s fallacy]].','',13,'Budhi','20041225235242','',0,0,0,0,0.723239548375,'20041225235440','79958774764757'); INSERT INTO cur VALUES (1435,0,'Economic_statistics','#REDIRECT [[Econometrics]]','',13,'Budhi','20040903064940','',0,1,0,1,0.290154075851,'20040903064940','79959096935059'); INSERT INTO cur VALUES (1436,0,'Edgeworth_series','The \'\'\'Edgeworth series\'\'\' or \'\'\'Gram-Charlier A series\'\'\', named in honor of [[Francis Ysidro Edgeworth]], are [[series_(mathematics)|series]] that approximate a [[probability distribution]] in terms of its [[cumulant]]s.\n\nThe key idea of these expansions is to write the [[characteristic function]] of the distribution whose [[probability density function]] is \'\'F\'\' to be approximated in terms of the characteristic function of a distribution with known and suitable properties, and to recover \'\'F\'\' through the inverse [[Fourier transform]].\n\nLet \'\'f\'\' be the characteristic function of the distribution whose density function is \'\'F\'\', and κ\'\'r\'\' its cumulants. We expand in terms of a known distribution with probability density function Ψ, characteristic function ψ, and cumulants γ\'\'r\'\'. The density Ψ is generally chosen to be that of the [[sebaran normal]], but other choices are possible as well. By the definition of the cumulants, we have the following formal identity:\n\n: f(t)=\\exp\\left[\\sum_{r=1}^\\infty(\\kappa_r-\\gamma_r)\\frac{(it)^r}{r!}\\right]\\psi(t)\\,.\n\nBy the properties of the Fourier transform, (\'\'it\'\')\'\'r\'\'ψ(\'\'t\'\') is the Fourier transform of (−1)\'\'r\'\' \'\'D\'\'\'\'r\'\' Ψ(\'\'x\'\'), where \'\'D\'\' is the differential operator with respect to \'\'x\'\'. Thus, we find for \'\'F\'\' the formal expansion\n\n: F(x) = \\exp\\left[\\sum_{r=1}^\\infty(\\kappa_r - \\gamma_r)\\frac{(-D)^r}{r!}\\right]\\Psi(x)\\,.\n\nIf Ψ is chosen as the normal density with mean and variance as given by \'\'F\'\', that is, mean μ = κ1 and variance σ2 = κ2, then the expansion becomes\n\n:\nF(x) = \\exp\\left[\\sum_{r=3}^\\infty\\kappa_r\\frac{(-D)^r}{r!}\\right]\\frac{1}{\\sqrt{2\\pi\\sigma}}\\exp\\left[-\\frac{(x-\\mu)^2}{2\\sigma^2}\\right]\\,.\n\nBy expanding the exponential and collecting terms according to the order of the derivatives, we arrive at the Gram-Charlier A series. If we include only the first two correction terms to the normal distribution, we obtain\n\n: F(x) = \\frac{1}{\\sqrt{2\\pi\\sigma}}\\exp\\left[-\\frac{(x-\\mu)^2}{2\\sigma^2}\\right]\\left[1+\\frac{\\kappa_3}{\\sigma^3}h_3\\left(\\frac{x-\\mu}{\\sigma}\\right)+\\frac{\\kappa_4}{\\sigma^4}h_4\\left(\\frac{x-\\mu}{\\sigma}\\right)\\right]\\,,\n\nwith \'\'h\'\'3 = (\'\'x\'\'3 − 3\'\'x\'\')/3! and \n\'\'h\'\'4 = (\'\'x\'\'4 − 6\'\'x\'\'2 + 3)/4! (these are [[Hermite polynomials]]). Note that this expression is not guaranteed to be positive, and is therefore not a valid probability distribution! The Gram-Charlier A series has the properties of an [[asymptotic expansion]], that is, the best results are usually achieved when only the first couple of terms are used. In general, the expansion cannot be made arbitrarily good by including terms of higher and higher orders.\n\nEdgeworth developed a similar expansion as an improvement to the [[central limit theorem]]. Let \'\'X\'\'\'\'i\'\' be a sequence of identically distributed [[random variable]]s, and \'\'Y\'\'\'\'n\'\' the standardized sum\n\n: Y_n = \\frac{\\sum_{i=1}^n(X_i-\\mbox{E}[X_i])}{\\sqrt{\\sum_{i=1}^n\\mbox{var}[X_i]}}\n\nFurther, let \'\'F\'\'\'\'n\'\' be the probability density function of the variables \'\'Y\'\'\'\'n\'\'. By the central limit theorem, \n\n:\\lim_{n\\rightarrow\\infty} F_n(x) = \\frac{1}{\\sqrt{2\\pi}}\\exp(-x^2/2) \n\nfor every \'\'x\'\', as long as the means and variances are finite and the sum of variances diverges to infinity. (Generally, the conclusion of the central limit theorem is about the limit of [[cumulative distribution functions]], not of probability density funtions, and therefore applies to discrete distributions as well. But discrete distributions are not contemplated in the present context).\n\nNow assume that the random variables \'\'X\'\'\'\'i\'\' have mean μ, variance σ2, and higher cumulants κ\'\'r\'\'\'\'r\'\'λ\'\'r\'\'. If we expand in terms of the unit normal distribution, that is, if we set\n\n:\\Psi(x)=\\exp(-x^2/2)/\\sqrt{2\\pi},\n\nthen the cumulant differences in the formal expression of the characteristic function \'\'f\'\'\'\'n\'\'(t) of \'\'F\'\'\'\'n\'\' are\n\n: \\kappa_1-\\gamma_1 = 0\\,,\n\n: \\kappa_2-\\gamma_2 = 0\\,,\n\n: \\kappa_r-\\gamma_r = \\frac{\\lambda_r}{n^{r/2-1}}; \\qquad r\\geq 3\\,.\n\nThe Edgeworth series is developed similarly to the Gram-Charlier A series, only that now terms are collected according to powers of \'\'n\'\'. Thus, we have \n\n: f_n(t)=\\left[1+\\sum_{j=1}^\\infty \\frac{P_j(it)}{n^{j/2}}\\right] \\exp(-t^2/2)\\,,\n\nwhere \'\'P\'\'\'\'j\'\'(\'\'x\'\') is a [[polynomial]] of degree 3\'\'j\'\'. Again, after inverse Fourier transform, the density function \'\'F\'\'\'\'n\'\' follows as\n\n: F_n(x) = \\Psi(x) + \\sum_{j=1}^\\infty \\frac{P_j(-D)}{n^{j/2}} \\Psi(x)\\,.\n\nThe first three terms of the expansion are\n\n: F_n(x)\\approx \\Psi(x) - \\frac{\\lambda_3 \\Psi^{(3)}(x)}{6\\sqrt{n}} +\\frac{1}{n}\\left[\\frac{\\lambda_4 \\Psi^{(4)}(x)}{24}+\\frac{\\lambda_3^2 \\Psi^{(6)}(x)}{72}\\right]+O(1/n^{3/2})\\,.\n\nHere, Ψ(\'\'j\'\')(\'\'x\'\') is the \'\'j\'\'ths derivative of &Psi(\'\'x\'\') with respect to \'\'x\'\'.\n\n==Further reading==\n\n* D. L. Wallace (1958). Asymptotic approximations to distributions. \'\'Ann. Math. Stat.\'\' 29:635-654.','',13,'Budhi','20041224090432','',0,0,1,0,0.277125088161,'20041224090432','79958775909567'); INSERT INTO cur VALUES (1437,0,'Efficiency_(statistics)','Dina [[statistik]], \'\'\'efficiency\'\'\' is one measure of desirability of an [[estimator]].\n\nThe efficiency of an [[bias (statistics)|unbiased]] [[statistic]] \'\'T\'\' is defined as\n\n:e(T)=\\frac{1/I(\\theta)}{{\\rm var\\ }T}\n\nwhere \'\'I\'\'(θ) is the [[Fisher information]] of the sample. Thus \'\'e\'\'(\'\'T\'\') is the minimum possible variance for an unbiased estimator divided by its actual variance. The [[Cramér-Rao inequality]] proves that \'\'e\'\'(\'\'T\'\') ≤ 1.\n\n\n====Examples====\n\nConsider a sample of size \'\'n\'\' drawn from a normal distribution of\nmean \'\'μ\'\' and unit [[varian]].\n\nThe [[sample mean]] \\overline{x} of the sample\nx_1,\\ldots,x_n, defined as\n\n:\n\\overline{x}={1 \\over n}\\sum_{i=1}^n x_i\n\n\nhas variance 1/n. This is equal to the reciprocal of the [[Fisher information]] from the sample (this is clear from the definition) and thus, by the [[Cramér-Rao inequality]], the sample\nmean is \'\'\'efficient\'\'\' in the sense that its efficiency is one.\n\nNow consider the [[sample median]]. This is an [[bias|unbiased]] and [[consistent]] estimator for \'\'μ\'\'. For large \'\'n\'\' the sample median is approximately normally distributed with mean \'\'μ\'\' and variance \'\'π/(2n)\'\'. The efficiency is thus \'\'2/π\'\', or about 64%. Note that this is the [[asymptote|asymptotic]] efficiency---that is, the efficiency in the limit as sample size \'\'n\'\' tends to infinity. For finite values of \'\'n\'\' the efficiency is higher than this (for example, a sample size of 3 gives an efficiency of about 74%).\n\nMany workers prefer the sample median as an estimator of the mean,\nholding that the loss in efficiency is more than compensated for by\nits enhanced [[robust|robustness]] in terms of its insensitivity to\n[[outlier]]s.\n\n==Relative efficiency==\n\nIf T and T\' are estimators for the [[parameter]] θ, then most people would agree that \'\'T\'\' is \"more efficient\" than \'\'T\'\' ′ if: (i) its [[mean kuadrat kasalahan]] is smaller for at least some value of \\theta, and (ii) the MSE does not exceed that of \'\'T\'\' ′ for any value of θ.\n\nFormally, \n:\nE[(T-\\theta)^2]\\leq E[(T\'-\\theta)^2]\n\nholds for all \\theta, with strict inequality holding somewhere.\n\nThe relative efficiency would be defined as \n\n:\ne(T\',T)=\\frac{E[(T-\\theta)^2]}{E[(T\'-\\theta)^2]}.\n\n\nAlthough \'\'e\'\' is in general a function of θ, in many cases the dependence drops out; if this is so, \'\'e\'\' being less than one would indicate that \'\'T\'\' is preferable, whatever the true value of θ.','/* Relative efficiency */',13,'Budhi','20041224113719','',0,0,1,0,0.20277727591,'20041224113719','79958775886280'); INSERT INTO cur VALUES (1438,0,'A._K._Erlang','\'\'\'Agner Krarup Erlang\'\'\' ([[January 1]], [[1878]] - [[February 3]], [[1929]]) was a [[Denmark|Danish]] [[mathematician]], [[statistician]], and engineer who invented the fields of [[queueing theory]] and [[traffic engineering]].\n\nErlang was born at [[Lonborg]] (Lønborg), near [[Tarm]], in [[Jutland]]. He was the son of a schoolmaster and with his maternal mathematical ancestor [[Thomas Fincke]], he demonstrated his potential from an early age by being able to read books upside down. He passed the \'\'Preliminary Examination\'\' offered by the [[University of Copenhagen]], with distinction, at age 14, after receiving dispensation to sit because he was younger than the usual minimum age.\n\nFor the next two years he taught alongside his father.\n\nWith a distant relative providing free board and lodgings, he prepared for and sat the University of [[Copenhagen]] entrance examination in [[1896]], which he passed with distinction. He won a scholarship to the University of Copenhagen and majored in [[mathematics]], but also studied [[astronomy]], [[physics]] and [[chemistry]]. He graduated in [[1901]] with an MA and subsequently taught at several schools over the next 7 years. He maintained his interest in mathematics and received an award for one paper that he submitted to the University of Copenhagen.\n\nHe was a member of the Danish Mathematicians\' Association and through this met amateur mathematician [[Johan Ludwig Jensen|Johan Jensen]], the Chief Engineer of the [[Copenhagen Telephone Company]], an offshoot of the [[International Bell Telephone Company]]. Erlang subsequently obtained employment with the company in [[1908]]. He worked for the Copenhagen Telephone Company for almost 20 years, until his death in Copenhagen after an abdominal operation.\n\nIt was while working for the Copenhagen Telephone Company that Erlang was presented with the classic problem of determining how many circuits were needed to provide an acceptable telephone service. However, his thinking went further in that he also realised that mathematics could be applied to assess how many operators were needed to handle a given volume of telephone calls. At that time most telephone exchanges used human operators and cord boards to switch telephone calls by means of jack plugs.\n\nOut of necessity, Erlang was a hands-on researcher. He would conduct his own measurements and was prepared to climb into street manholes to do so.\n\nErlang was also an expert in both the history and calculation of the numerical tables of mathematical functions, particularly [[logarithm]]s. He devised new calculation methods for certain forms of mathematical tables.\n\nHe developed his theory concerning telephone traffic over several years. His significant publications include: \n*In 1909 - \"The Theory of Probabilities and Telephone Conversations\" - which proves that the [[Poisson distribution]] applies to random telephone traffic.\n*In 1917 - \"Solution of some Problems in the Theory of Probabilities of Significance in Automatic Telephone Exchanges\" - which contains his classic formulae for loss and waiting time.\n\nThese and other notable papers were translated into English, French and German. His papers were prepared in a very brief style and can be difficult to understand without a background in the field. So that his papers could be studied in the original Danish, one researcher from [[Bell Telephone Laboratories]] learnt the language. \n\nThe British Post Office accepted his formula as the basis for calculating circuit facilities. \n\nHe was an associate of the British [[Institution of Electrical Engineers]]. \n\nThe unit of communication activity in these fields is now known as the [[Erlang unit|erlang]], in recognition of his achievements.\n\n[[Ericsson]] has also named the [[Erlang programming language]], a programming language for large industrial real-time systems, in his honour.\n\nHis name is also given to the statistical [[probability]] distribution that arises from his work.\n\n==Tempo ogé==\n* [[Erlang programming language]]\n* [[Erlang unit]]\n* [[Erlang distribution]]\n* [[Queueing theory]]\n* [[Telecommunications traffic engineering]].\n\n==External links==\n* [http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Erlang.html Biography - from St.Andrews University]\n* [http://pass.maths.org.uk/issue2/erlang/index.html Biography - from Millennium Mathematics Project]\n* [http://www.xycoon.com/erlang.htm Erlang Distribution]\n* [http://www.angustel.ca/reports/Erlang%20B%20&%20C.PDF An Introduction to Erlang B and Erlang C by Ian Angus] (PDF Document - Has terms and formulae plus biography)\n\n[[Category:Statisticians|Erlang, Agner Krarup]]\n[[Category:Engineers|Erlang, Agner Krarup]]\n[[Category:Danish scientists|Erlang, Agner Krarup]]\n[[de:Agner Krarup Erlang]]\n[[nl:Agner Erlang]]\n[[fr:Agner Krarup Erlang]]','/* See also */',13,'Budhi','20050101220605','',0,0,0,0,0.00604674686,'20050101220605','79949898779394'); INSERT INTO cur VALUES (1439,0,'Errors_and_residuals_in_statistics','Dina [[statistik]], konsep \'\'\'kasalahan\'\'\' jeung \'\'\'sesa\'\'\' gampang silih bingungkeun.\n\n\'\'\'\'\'Error\'\'\'\'\' is a misnomer; an \'\'\'error\'\'\' is the amount by which an observation differs from its [[nilai ekspektasi]]; the latter being based on the whole population from which the statistical unit was chosen randomly. The expected value, being the average of the entire population, is typically unobservable. If the average height of 21-year-old men is 5 feet 9 inches, and one randomly chosen man is 5 feet 11 inches tall, then the \"error\" is 2 inches; if the randomly chosen man is 5 feet 7 inches tall, then the \"error\" is −2 inches. The nomenclature arose from random measurement errors in astronomy. It is as if the measurement of the man\'s height were an attempt to measure the population average, so that any difference between the man\'s height and the average is a measurement error.\n\nA \'\'\'residual\'\'\', on the other hand, is an observable \'\'estimate\'\' of the unobservable error. The simplest case involves a random sample of \'\'n\'\' men whose heights are measured. The \'\'sample\'\' average is used as an estimate of the \'\'population\'\' average. Then we have:\n\n*The difference between each man\'s height and the unobservable \'\'population\'\' average is an \'\'error\'\', and\n\n*The difference between each man\'s height and the observable \'\'sample\'\' average is a \'\'residual\'\'.\n\n:\'\'\'\'\'Residuals are observable; errors are not\'\'\'\'\'.\n\nNote that the sum of the residuals is necessarily zero, and thus the residuals are necessarily \'\'not [[statistical independence|independent]]\'\'. The sum of the errors need not be zero; the errors are independent [[random variable]]s if the individuals are chosen from the population independently.\n\n:\'\'\'\'\'Errors are often independent of each other; residuals are usually \'\'not\'\' independent of each other.\'\'\'\'\'\n\n==Conto==\n\nLamun urang nganggap populasi nu [[sebaran normal|kasebar normal]] mibanda mean μ sarta [[simpangan baku]] σ, sarta individu nu dipilih bebas, mangka\n\n:X_1, \\dots, X_n\\sim N(\\mu,\\sigma^2)\n\nsarta sampel mean ngarupakeun sebaran variabel random:\n\n:\\overline{X}\\sim N(\\mu, \\sigma^2/n).\n\nMangka \'\'kasalahan\'\' nyaeta\n\n:\\varepsilon_i=X_i-\\mu,\n\nsedengkeun \'\'sesa\'\' nyaeta\n\n:\\widehat{\\varepsilon}_i=X_i-\\overline{X}.\n\n(Saperti nu ilahar dipake, tanda \"topi\" diluhureun aksara ε nunjukkeun \'\'estimasi\'\' observasi tina kuantitas nu teu kaobservasi disebut ε.)\n\nJumlah kuadrat \'\'\'kasalahan\'\'\', dibagi ku σ2, mibanda [[sebaran chi-kuadrat]] mibanda \'\'n\'\' tingkat kebebasan:\n\n:\\sum_{i=1}^n \\left(X_i-\\mu\\right)^2/\\sigma^2\\sim\\chi^2_n.\n\nThis quantity, however, is not observable. The sum of squares of the \'\'\'residuals\'\'\', on the other hand, is observable. The quotient of that sum by σ2 has a chi-square distribution with only \'\'n\'\' − 1 degrees of freedom:\n\n:\\sum_{i=1}^n \\left(\\,X_i-\\overline{X}\\,\\right)^2/\\sigma^2\\sim\\chi^2_{n-1}.\n\nIt is remarkable that this random variable and the sample mean can be shown to be independent of each other. That fact and the normal and chi-square distributions given above form the basis of [[interval kapercayaan]] calculations relying on [[sebaran-t student]]. The cancellation of σ from the numerator and the denominator in those calculations entails that the absurdity of the seeming assumption that σ2 is known has no harmful effect.\n\n==Tempo ogé==\n\n[[Studentized residual]]','/* Conto */',13,'Budhi','20041225044818','',0,0,1,0,0.674568734912,'20041225044818','79958774955181'); INSERT INTO cur VALUES (1440,0,'Expectation-maximization_algorithm','An \'\'\'expectation-maximization (EM) algorithm\'\'\' is an algorithm for finding [[maximum likelihood]] estimates of parameters in [[probability|probabilistic]] models, where the model depends on unobserved ([[latent]]) variables. EM alternates between performing an expectation (E) step, which computes the expected value of the latent variables, and an maximization (M) step, which computes the maximum likelihood estimates of the parameters given the data and setting the latent variables to their expectation.\n\nIt can be shown that an EM iteration does not decrease the observed data likelihood function,\nand that the only [[stationary point]]s of the iteration are the stationary points of the observed data likelihood function.\nIn practice,\nthis means that an EM algorithm will converge to a [[local maximum]] of the observed data likelihood function.\n\n\"Expectation-maximization\" is a description of a class of related algorithms, \nnot a particular algorithm;\nEM is a recipe or meta-algorithm which is used to devise particular algorithms.\nThe [[Baum-Welch algorithm]] is an example of an EM algorithm applied to [[hidden Markov model]]s.\nAnother example is the EM algorithm for fitting a [[mixture density]] model.\n\nAn EM algorithm can also find [[maximum a posteriori]] (MAP) estimates, by performing MAP estimation in the M step, rather than maximum likelihood.\n\nThere are other methods for finding maximum likelihood estimates,\nsuch as [[gradient descent]], [[conjugate gradient]] or variations of the [[Gauss-Newton method]]. \n\n== Rujukan ==\n\n* Arthur Dempster, Nan Laird, and Donald Rubin. \"Maximum likelihood from incomplete data via the EM algorithm\". \'\'Journal of the Royal Statistical Society\'\', Series B, 39(1):1–38, 1977.\n\n* Radford Neal, Geoffrey Hinton. \"A view of the EM algorithm that justifies incremental, sparse, and other variants\". In Michael I. Jordan (editor), \'\'Learning in Graphical Models\'\' pp 355-368. Cambridge, MA: MIT Press, 1999.\n\n[[Category:Statistics]][[Category:Optimization algorithms]]\n[[Category:Machine learning]]','/* References */',13,'Budhi','20041224224242','',0,0,1,0,0.973895847785,'20041224224242','79958775775757'); INSERT INTO cur VALUES (1441,0,'Exploratory_data_analysis','\'\'\'Exploratory data anaysis (EDA)\'\'\' is that part of [[statistical practice]] concerned with reviewing, communicating and using [[data]] where there is a low level of knowledge about its [[cause system]]. It was so named by [[John Tukey]].\n\nTukey held that too much emphasis in [[statistics]] was placed on evaluating and testing given [[hypothesis|hypotheses]] ([[confirmatory data analysis]]) and that the balance was in need of redressing in favour of using [[data]] to suggest [[hypothesis|hypotheses]] to test. In particular, confusion of the two types of analysis and employing them on the same set of data can lead to [[bias (statistics)|bias]] owing to the effect of [[testing hypotheses suggested by the data]].\n\nThe objectives of EDA are to:\n*Suggest [[hypothesis|hypotheses]] about the [[cause|causes]] of observed [[phenomenon|phenomena]]\n*Assess assumptions on which [[statistical inference]] will be based\n*Support the selection of appropriate [[statistics|statistical]] tools and techniques\n*Provide a basis for further [[data]] collection through [[survey sampling|surveys]] or [[desain percobaan|experiments]]\n\nThe principle [[graph]]ical tools used in EDA are:\n\n*[[Box plot]]\n*[[Histogram]]\n*[[MultiVari chart]]\n*[[Run chart]]\n*[[Pareto chart]]\n*[[Scatter plot]]\n*[[Stem-and-leaf plot]]\n\nThe principle [[quantity|quantitative]] tools are:\n\n*[[Median polish]]\n*[[Letter values]]\n*[[Resistant line]]\n*[[Resistant smooth]]\n*[[Rootogram]]\n\n==Bibliography==\n\n*Hoaglin, D C; Mosteller, F & Tukey, J W (Eds) (1985) \'\'Exploring Data Tables, Trends and Shapes\'\' ISBN 0471097764\n*Hoaglin, D C; Mosteller, F & Tukey, J W (Eds) (1983) \'\'Understanding Robust and Exploratory Data Analysis\'\' ISBN 0471097772\n*Tukey, J W (1977) \'\'Exploratory Data Analysis\'\' ISBN 0201076160\n*Velleman, P F & Hoaglin, D C (1981) \'\'Applications, Basics and Computing of Exploratory Data Analysis\'\' ISBN 087150409X\n\n[[Category:Statistics]]','',13,'Budhi','20041224104601','',0,0,1,0,0.160175159182,'20041224104601','79958775895398'); INSERT INTO cur VALUES (1442,0,'Exponential_family','In [[statistics]], the \'\'\'exponential family\'\'\' of [[probability density function]]s or [[probability mass function]]s comprises those that have the following form:\n\n:f(x|\\eta) = h(x) e^{\\eta^{\\top} T(x) - A(\\eta)}\n\nwhere:\n\n* \'\'h\'\'(\'\'x\'\') is the \'\'reference density\'\',\n\n* η is the \'\'natural parameter\'\', a column vector, so that ηT, its transpose, is a row vector,\n\n* \'\'T\'\'(\'\'x\'\') is called the \'\'[[sufficiency (statistics)|sufficient statistic]]\'\', a column vector whose number of scalar components is the same as that of η. (However, the concept of [[sufficient statistic]] is broader than what may appear from this article.)\n\n* and \'\'A\'\'(η) is a [[normalizing constant]] without which \'\'f\'\'(\'\'x\'\' | η) would not be a probability density or probability mass function. It is the [[cumulant]]-[[generating function]] of the [[probability distribution]] of the sufficient statistic \'\'T\'\'(\'\'X\'\') when the distribution of \'\'X\'\' is that whose density function is \'\'h\'\'.\n\nThe parameter space -- i.e., the set of values of η for which this function is integrable -- is necessarily [[convex]].\n\nThe term \'\'exponential family\'\' is also frequently used to refer to any particular concrete case, i.e., any parametrized family of probability distributions of this form.\n\nSebaran [[Bernoulli distribution|Bernoulli]], [[sebaran normal|normal]], [[sebaran gamma|gamma]], [[sebaran Poisson|Poisson]] and [[sebaran binomial|binomial]] kabehanna ngarupakeun kulawarga eksponensial.\n\nAccording to the Pitman-Koopman-Darmois theorem, only in exponential families is there a [[sufficient statistic]] whose dimension remains bounded as sample size increases. More long-windedly, suppose \'\'X\'\'\'\'n\'\', \'\'n\'\' = 1, 2, 3, ... are [[statistical independence|independent]] identically distributed random variables whose distribution is known to be in some family of probability distributions. Only if that family is an exponential family is there a (possibly vector-valued) [[sufficient statistic]] \'\'T\'\'(\'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\') whose number of scalar components does not increase as the sample size \'\'n\'\' increases.\n\nExponential families are also important in [[Bayesian statistics]]. In Bayesian statistics a [[prior distribution]] is multiplied by a [[likelihood function]] and then normalised to produce a [[posterior distribution]]. In the case of a likelihood which is an exponential family there exists a [[conjugate prior]]. A conjugate prior is one which, when combined with the likelihood and normalised, produces a posterior distribution which is of the same type as the prior. For example, if one is estimating the parameter theta, the success probability, of a binomial distribution then if one chooses to use a beta distribution as one\'s prior, then the posterior is always another beta distribution. This makes the computation of the posterior particularly simple. Similarly, if one is estimating the lambda parameter of a Poisson distribution the use of a gamma prior will lead to another gamma posterior. Conjugate priors are often very flexible and can be very convenient. However, if one\'s belief about the likely value of the theta parameter of a binomial is represented by (say) a bimodal (two-humped) distribution then this cannot be represented by a beta distribution. In general, a likelihood will not belong to an exponential family and thus no conjugate prior exists. The posterior will then have to be computed by numerical methods. Thus, classical [[frequentist]] [[hypothesis testing]] is seriously impeded in the case of likelihoods which are not exponential families, because of the lack of [[sufficient statistics]]. By contrast, Bayesian inference is based on the posterior distribution and can still be carried out if the requisite numerical integrals can be performed either directly or (more usually) by simulation.','',13,'Budhi','20040918224335','',0,0,0,0,0.140041635437,'20041225131128','79959081775664'); INSERT INTO cur VALUES (1443,0,'Koefisien_Gini','\'\'\'Koefisien Gini\'\'\' ngarupakeun ukuran kateusaruaan panghasilan nu diwangun ku statistikawan Italia [[Corrado Gini]]. \'\'\'Indeks Gini\'\'\' sarua jeung koefisien Gini kali 100 (?).\n\nKoefisien Gini ngarupakeun wilangan antara 0 jeung 1, numana 0 hartina persis sarua (unggal jalma miboga panghasilan nu sarua) sarta 1 harti persis teu saruan (saurang boga kabeh panghasilan, nu sejenna teu boga nanaon).\n\nKadangkala koefisien Gini ilahar dipake keur ngukur kateusaruaan panghasilan, bisa dipake keur ngukur kateusaruaan panghasilan - dina pamikiran taya jalma nu mibanda kakayaan negatip.\n\nKoefisien Gini diitung ngagunakeun daerah dina diagram [[Lorenz curve]]. Lamun daerah antara garis persis sarua sarta kurva Lorenz A, sarta daerah sahandapeun kurva Lorenz nyaeta B, mangka koefisien Gini A/(A+B). Ieu ditembongkeun salaku persentase atawa salaku kasaruaan numerik tina persentasi, nilai salawasna antara 0 jeung 1.\n\n==Tempo oge==\n* [[Welfare economics]]\n* [[Income inequality metrics]]\n* [[Lorenz curve]]\n* [[ROC analysis]]\n* [[Social welfare (political science)]]\n\n== Tumbu kaluar ==\n* [http://www.eldis.org/static/DOC2910.htm Measuring income inequality: a new database], with link to dataset\n* [[United Nations Development Programme|UN Human Development]] [http://hdr.undp.org/reports/global/2004/pdf/hdr04_HDI.pdf Report 2004, p50-53]: Gini Index calculated for all countries.\n\n[[eo:Koeficiento_de_Gini]]\n[[de:Gini-Koeffizient]]','',13,'Budhi','20040903214320','',0,0,0,0,0.219146288568,'20040903220210','79959096785679'); INSERT INTO cur VALUES (1444,0,'Graeco-Latin_square','\'\'\'Kuadrat Graeco-Latin\'\'\' \'\'n\'\'×\'\'n\'\' nyaeta tabel nu unggal sel-na mibanda pasangan simbol, susunan simbol tina unggal dua [[set]] unsur \'\'n\'\'. Each pair occurs exactly once in the table. Each symbol in the two, not necessarily distinct, sets occurs exactly once in each row and exactly once in each column. Kuadrat Graeco-Latin dipake dina [[desain percobaan]].\n\nA 4×4 Graeco-Latin square on the sets {\'\'A\'\', \'\'B\'\', \'\'C\'\', \'\'D\'\'} and {α, β, γ, δ} is:\n\n{| border=1\n|\'\'A\'\' α\n|\'\'B\'\' γ\n|\'\'C\'\' δ\n|\'\'D\'\' β\n|-\n|\'\'B\'\' β\n|\'\'A\'\' δ\n|\'\'D\'\' γ\n|\'\'C\'\' α\n|-\n|\'\'C\'\' γ\n|\'\'D\'\' α\n|\'\'A\'\' β\n|\'\'B\'\' δ\n|-\n|\'\'D\'\' δ\n|\'\'C\'\' β\n|\'\'B\'\' α\n|\'\'A\'\' γ\n|}\n\nThe tabular arrangements of {\'\'A\'\', \'\'B\'\', \'\'C\'\', \'\'D\'\'} (Latin characters) alone and {α, β, γ, δ} (Greek characters) alone each forms a [[Latin square]]. Each pair from the two sets (i.e. every element of their [[cartesian product]]) occurs exactly once and we say that the two Latin squares are \'\'[[orthogonal]]\'\'.\n\n==History==\n\nIn the [[1780s]], [[Leonard Euler]] demonstrated methods for constructing Graeco-Latin squares where \'\'n\'\' is odd or a multiple of 4. He further proved that no 2×2 square exists and conjectured that none existed for \'\'n\'\'=4\'\'k\'\'+2, where \'\'k\'\' is a [[natural number]].\n\nIn [[1901]], [[Gaston Tarry]] demonstrated that there was no 6×6 square by enumerating all the possible arrangements of symbols. However, in [[1959]], Parker, Bose and Shrikhande constructed a 10×10 square.\n\nIn 1978, the French writer [[Georges Perec]] used the 10×10 square (believed then to be the only one possible) for the structure of constraints underlying his novel [[Life: A User\'s Manual]].\n\n{{stub}}\n\n==Tempo ogé==\n* [[Latin square]]\n\n[[Category:Matematik]]','',13,'Budhi','20041225234057','',0,0,1,0,0.168900990472,'20041225234057','79958774765942'); INSERT INTO cur VALUES (1445,0,'Modél_grafik','Dina [[probability theory|tiori probabiliti]] sarta [[statistik]], \'\'\'model grapik (GM)\'\'\' ngagambarkeun [[statistical independence|kabebasan]] antara [[variabel random]] make [[graph (mathematics)|grafik]] numana unggal variabel random ngarupakeun hiji titik.\n\nDina kasus sederhana, stuktur jaringan model nyaeta [[\'\'directed acyclic graph\'\']] (DAG). Mangka GM ngagambarkeun faktorisasi gabungan [[probability|probabiliti]] sakabeh variabel random. Leuwih pastina, lamun kajadian \n\n:\'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\',\n\nmangka gabungan probabiliti \n\n:\'\'P\'\'(\'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\'),\n\nsarua jeung hasil [[conditional probability|kondisional probabiliti]] \n\n:P(\'\'Xi\'\' | parents of \'\'Xi\'\') for \'\'i\'\' = 1,...,\'\'n\'\'. \n\nDina basa sejen, faktor [[probability distribution|sebaran gabungan]] kana hasil kali sebaran kondisional. Struktur grafik nunjukeun kabebasan langsung antara variabel. Unggal dua titik nu pakait henteu nurun/naek ngarupakeun kondisional [[statistical independence|bebas]] nu merekeun nilai keur indungna.\n\n\n{{pondok}}','',3,'Kandar','20041124105130','',0,0,0,0,0.632477531038,'20050303211247','79958875894869'); INSERT INTO cur VALUES (1446,0,'Sekuen_Halton','Dina [[statistik]], \'\'\'sekuen Halton\'\'\' leuwih dipikanyaho salaku [[quasi-random sequence|sekuen kuasi-random]], mimiti diwanohkeun dina taun [[1960]] salaku alternatip tina sekuan [[pseudo-random number|wilangan pseudo-random]]. Sekuen ieu dirarancang utamana keur dipake dina simulasi [[integral]] [[Monte Carlo]] nu teu mibanda bentuk-raket dina usaha keur ngurangan varian. \n\nAslina, sekuen Halton dirarancang dumasa kana model deterministik nu make [[prime number|wilangan prima]] salaku dasarna. Sekuen Halton hiji-dimesi dumasar kana wilangan prima \'\'p\'\' (≥ 2) ngeusi dina rohangan 0-1 ku ngabagi kana bagean \'\'p\'\', sarta sacar sistematis dieusikan kana rohangan nu kosong, maka siklus panjang \'\'p\'\' nu disimpen unggal gambar dina unggal segmen. Panjang sekuen Halton \'\'N\'\' saterusna ngandung panjang siklus mimiti p-1, ditambahkeun kana \'\'[N-(p-1)]DIV[p]\'\' panjang siklus “lengkep” \'\'p\'\', sarta, iwal dina kasus dimana \'\'(N+1)MOD(p)=0\'\', oge dina panjang siklus ahir “teu lengkep” final \'\'(N+1)MOD(p)\'\'. \n\nSacara resmi, φp \'\'(i)\'\', unsur ka-\'\'i\'\' dina sekuen Halton dumasar kana wilangan prima \'\'p\'\', ditangtukeun ku nyokot inverse interger radikal \'\'i\'\' dina dasar \'\'p\'\' ku ngagambarkeun ngaliwatan titik radikal, saperti:\n\n[[Image:halton_seq_01.jpg]]\n\ndimana nilai \'\'b0(i), ..., bL(i)\'\' ditangtukeun ku ngarengsekeun:\n\n\n[[Image:halton_seq_03.gif]]\n\n\nUnggal sekuen Halton standar diwangun dina dimensi handap, masalah pakait dicatet antara sekuen nu di-generate tina wilangan prima pangluhurna. Pasti, ieu nembongkeun risiko serius salila estimasi integral dimensi-luhur (misalna, -- \'\'pamilihan model spasial, saperti lokasi atawa rute\'\'). Dina usaha keur nganyahokeun paripolah ieu, sababaraha metoda diusulkeun; salah sahiji solusi nu kawentar nyaeta sekuen Halto (\'\'make koefisien permutasi nu ditangtukeun samemehna digunakeun dina ngawangun sekuen standar\'\').\n\n[[en:Halton sequences]]','link',38,'Robin Patterson','20050208235639','',0,0,1,0,0.547155746979,'20050208235639','79949791764360'); INSERT INTO cur VALUES (1447,0,'Rasio_bencana','\'\'\'Rasio bencana\'\'\' dina [[survival analysis|analisa survival]] nyaeta kasimpulan tina beda antara dua kurva surivival, ngagambarkeun nguranganna resiko kematian dina babandingan [[control experiment|kontrol]] pencegahan, salila waktu nu di perhatikeun. Ieu ngarupakeun bentuk [[relative risk|resiko relatip]]. Model [[Proportional hazards regression|proporsi regresi bencana]] (oge disebut model regeresi Cox ) nganggap yen resiko relatip kematian antara pencegahan jeung kontrol ngarupakeun hal nu angger dina interval waktu. Model ieu dipake salaku algoritma komputer keur nyimpulkeun risiko kematian relatip kana interval waktu dina hiji gambar.
\n

O(treatment) /E(treatment) \\over O(controls) /E(controls) \n

numana O nyaeta jumlah observasi kematian dina grup husus, sarta E jumlah ekspektasi kematian, dumasar kana ieu kaayaan, tapi teu nyokot itungan tina unggal ekspektasi pencegahan. \n\n==Tumbu kaluar==\n* http://www.graphpad.com/www/book/compsurv.htm\n\n==Rujukan==\n* [[Douglas Altman|Altman, DG]]. Practical Statistics for Medical Research. Chapman & Hall. London, 1991. ISBN 0412276305. pp383-4.','',13,'Budhi','20040907005614','',0,0,0,0,0.572590203757,'20040907010615','79959092994385'); INSERT INTO cur VALUES (1448,0,'Kurva_Hubbert','\'\'\'Kurva Hubbert\'\'\', ngaran nu dipake keur ngahargaan ka [[géofisikis]] [[M. King Hubbert]], mangrupa [[derivatif]] tina [[kurva logistik]].\n\nSalah sahiji conto kurva Hubbert nyaéta:\n\n:\nx = {e^{-t}\\over(1+e^{-t})^2}={1\\over2+2\\cosh t}\n\n\n[[Image:Hubbert-curve.png|Plot kurva Hubbert]]\n\nKurva Hubbert raket jeung susunan bentuk, sanajan asalna béda, [[probability density function]] tina [[sebaran normal]]. Kurva ieu asalna tina mode laju éxtraxi [[minyak bumi]]. Dumasar kana ieu modél, laju produksi minyak ditangtukeun ku laju sumur minyak anyar nu kapanggih; \"[[punclut Hubbert]] (\'\'Hubbert peak\'\']]\" dina laju éxtraxi minyak bakal nuturkeun ku nurunna produksi minyak nepi ka béakna.\n\n\'\'Catetan: keur diskusi leuwih jéntré ngeunaan minyak bumi, tempo dina artikel [[punclut Hubbert]].\'\'\n\n[[Category:Matematik]]','',3,'Kandar','20050203100918','',0,0,0,0,0.426581188304,'20050203100918','79949796899081'); INSERT INTO cur VALUES (1449,6,'Hubbert-curve.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040903070047','',0,0,0,1,0.208337938607054,'20040903070553','79959096929952'); INSERT INTO cur VALUES (1450,0,'Hubbert_curve','#REDIRECT [[Kurva Hubbert]]\n','Hubbert curve dipindahkeun ka Kurva Hubbert',13,'Budhi','20040903070643','',0,1,0,1,0.816106865011255,'20040903070643','79959096929356'); INSERT INTO cur VALUES (1451,0,'Illustration_of_the_central_limit_theorem','Dina kaca ieu \'\'\'illustration of the [[central limit theorem]]\'\'\'. \nA [[probability density function]] is shown in the first figure.\nThen the densities of the sums of two, three, and four [[independent]] variables, each having the original density, are shown in the later figures.\nAlthough the original density is far from normal, \nthe density of the sum of just a few variables with that density is much smoother and has some of the qualitative features of the [[normal distribution|normal density]].\n\nA more concrete illustration, in which most of the arithmetic can be done more-or-less instantly by hand, is at [[concrete illustration of the central limit theorem]].\n\nThe densities of the sums of two, three, and four terms were constructed as the [[convolution]] of the original density with itself.\nAs the original density is a [[piecewise]] [[polynomial]] (of degree 0 and 1),\nthe convolutions are also piecewise polynomials,\nof increasing degree.\nThus the convolution of the original density may be considered a means of constructing a piecewise polynomial approximation to the normal density.\n\nThe convolutions were computed via the [[discrete Fourier transform]].\nA list of values \'\'y\'\' = \'\'f\'\'(\'\'x\'\'0 + \'\'k\'\' Δ\'\'x\'\') was constructed, where \'\'f\'\' is the original density function, and Δ\'\'x\'\' is approximately equal to 0.002, and \'\'k\'\' is equal to 0 through 1000.\nThe discrete Fourier transform \'\'Y\'\' of \'\'y\'\' was computed.\nThen the convolution of \'\'f\'\' with itself is proportional to the inverse discrete Fourier transform of the pointwise product of \'\'Y\'\' with itself.\n\n
\n[[Image:Central_limit_thm_1.png|right|frame|\'\'A probability density function\'\']]\n\nWe start with a [[probability density function]].\nThis function, although discontinuous, is far from the most pathological example that could be created. \n\nThis density has [[mean]] 0 and [[standard deviation]] 1.\n\n
\n[[Image:Central_limit_thm_2.png|right|frame|\'\'Density of a sum of two variables\'\']]\n\nNext we compute the density of the sum of two independent variables, each having the above density. \nThe density of the sum is the convolution of the above density with itself.\n\nThe sum of two variables has mean 0 but it has standard deviation √2.\nThe density shown in the figure at right has been rescaled so that its standard deviation is 1.\n\nThis density is already smoother than the original.\nThere are obvious lumps, which correspond to the intervals on which the original density was defined.\n\n
\n[[Image:Central_limit_thm_3.png|right|frame|\'\'Density of a sum of three variables\'\']]\n\nWe then compute the density of the sum of three independent variables, each having the above density. \nThe density of the sum is the convolution of the first density with the second.\n\nThe sum of three variables has mean 0 but it has standard deviation √3.\nThe density shown in the figure at right has been rescaled so that its standard deviation is 1.\n\nThis density is even smoother than the preceding one.\nThe lumps can hardly be detected in this figure.\n\n
\n[[Image:Central_limit_thm_4.png|right|frame|\'\'Density of a sum of four variables\'\']]\n\nFinally, we compute the density of the sum of four independent variables, each having the above density. \nThe density of the sum is the convolution of the first density with the third.\n\nThe sum of four variables has mean 0 but it has standard deviation 2 = √4.\nThe density shown in the figure at right has been rescaled so that its standard deviation is 1.\n\nThis density appears qualitatively very similar to a normal density.\nAny lumps cannot be distinguished by the eye.\n\n[[Category:Probability and statistics]]','',13,'Budhi','20041224224559','',0,0,1,0,0.763303931692,'20041224224559','79958775775440'); INSERT INTO cur VALUES (1452,0,'Independent_components_analysis','\'\'\'Independent components analysis (ICA)\'\'\' is a mathematical method for separating a signal into its most probable additive subcomponent supposing the [[statistical independence]] of the source signals. This assumption is correct in most cases so the blind ICA separation of a mixed signal gives very good results. It is also used for signals that are not supposed to be generated by a mixing for analysis purposes. \n\nThe statistical method reveal hidden factors (independent components), presuming their non-gaussianity.\n\nIt uses [[principal components analysis]] as a first step.\nApply [[whitening]] of the data, and then apply an iterative algorithm (such as an [[adaptive filter]]).\n\nThe ICA searches for [[orthogonal]] components that are mutually statistically independent to describe the input data matrix (composed by the features vectors). This can allow the reconstruction of source signals from several corrupted mixtures thereof.\n\nThe method is important to [[blind signal separation]], [[electroencephalogram|EEG]] analysis and [[FMRI]] analysis.\n\nThis concept can be extended to analyse non physical signals, for instance ICA has been aplied to discover discussions topics on a bag of news list archives.\n\nPakait jeung \n* [[Principal components analysis|PCA]] ([[principal component analysis]])\n* [[varimax rotation]]\n* [[projecting pursuit]]\n* [[Image processing]]\n* [[Signal processing]]','',13,'Budhi','20050101220658','',0,0,0,0,0.131462253226,'20050101220658','79949898779341'); INSERT INTO cur VALUES (1453,0,'Kaputusan_statistik','\'\'\' Kaputusan statistik \'\'\' nyaeta cabang tina [[statistik]] nu ngandung generalisasi tina [[Sampling (statistics)|sampel]] ka [[Statistical population|populasi]], ngararangkay [[test|tes]] [[hypothesis|hipotesa]], nangtukeun hubungan antar [[variabel]], sarta nyieun [[prediction|prediksi]].\n\n{{msg:stub}}','',13,'Budhi','20040907053116','',0,0,0,0,0.899232618929,'20040907053147','79959092946883'); INSERT INTO cur VALUES (1454,0,'Metoda_inpormasi_leherbotol','\'\'\'Metoda inpormasi leherbotol\'\'\' ngarupakeun teknik keur manggihkeun \'\'perdagangan\'\' nu hade antara [[accuracy|akurasi]] jeung [[compression|kompresi]] waktu nyieun kasimpulan (contona [[data clustering|clustering]]) [[variabel random]] \'\'\'X\'\'\' waktu diberekeun joint [[probability distribution|sebaran probabiliti]] antara \'\'\'X\'\'\' jeung variabel observasi \'\'\'Y\'\'\'.\n\n==Tempo oge==\n* [[Information theory|Tiori inpormasi]]\n\n==Tumbu kaluar==\n* [http://citeseer.ist.psu.edu/tishby99information.html Paper by N. Tishby, et. al]\n\n\n[[Category:Machine learning]]\n\n{{stub}}','',13,'Budhi','20040907011756','',0,0,0,0,0.275371245702,'20040907011829','79959092988243'); INSERT INTO cur VALUES (1455,0,'Interaction_(statistics)','Dina [[statistik]], \'\'\'interaksi\'\'\' nyaeta watesan dina [[model statistik]] numana efek dua variabel atawa leuwih teu bisa ditambahkeun sacara langsung.\n\nMangka, for a response \'\'y\'\' and two variables \'\'x\'\'1 and \'\'x\'\'2 an \'\'additive\'\' model would be:\n\n:y = ax_1 + bx_2 + \\mbox{error},\n\n- while,\n\n:y = ax_1 + bx_2 + c(x_1\\times x_2) + \\mbox{error},\n\n- is an example of a model with an \'\'interaction\'\' between variables \'\'x\'\'1 and \'\'x\'\'2 (the word \"errors\" is not to be construed literally; it refers to a [[random variable]] by which \'\'y\'\' differs from the [[nilai ekspektasi]] of \'\'y\'\'). See [[errors and residuals in statistics]], and note that it is easy to confuse errors with residuals, although the two are different.\n\nVery often the interacting variables are categorical variables rather than real numbers. For example, members of a population may be classified by religion and by occupation. If one wishes to predict a person\'s height based only on the person\'s religion and occupation, a simple \'\'additive\'\' model, i.e., a model without interaction, would add to an overall average height an adjustment for a particular religion and another for a particular occupation. A model with interaction, unlike an additive model, could add a further adjustment for the \"interaction\" between that religion and that occupation. This example may cause one to suspect that the word \'\'interaction\'\' is something of a misnomer.\n\nThe consequence of an \'\'interaction\'\' is that the effect of one variable depends on the value of another. This has implications in [[desain percobaan]] as it is misleading to vary one factor at a time.\n\nReal-world examples of [[system]]s that manifest interactions include:\n\n*\'\'Interaction\'\' between adding sugar to coffee and stiring the coffee. Neither of the two individual variables has much effect on sweetness but a combination of the two does.\n\n*\'\'Interaction\'\' between adding [[carbon]] to [[steel]] and quenching. Neither of the two individually has much effect on [[tensile strength|strength]] but a combination of the two has a dramatic effect.\n\n[[Genichi Taguchi]] contended that \'\'interactions\'\' could be eliminated from a [[system]] by appropriate choice of response variable and transformation. However [[George Box]] and others have argued that this is not the case in general.\n\n===Bibliography===\n\nBox, G E P (1990) Do interactions matter? \'\'Quality Engineering\'\' vol 2, pp365-369','',13,'Budhi','20041224104725','',0,0,1,0,0.01737089875,'20041228003003','79958775895274'); INSERT INTO cur VALUES (1456,0,'Interquartile_range','Dina [[statistik deskriptif]], the \'\'\'interquartile range (IQR)\'\'\' is the difference between the third and first [[quartile]]s. The interquartile range is a more stable statistic than the [[Rentang (statistik)|range]], and is usually preferred to that statistic.\n\nSince 25% of the data are less than or equal to the first quartile and 25% are greater than or equal to the third quartile, the difference is the length of an interval that includes about half of the data. This difference should be measured in the same units as the data.\n\n==Percentiles and quartiles==\n\nFor a sample of n observations x_1, x_2, .... x_n the observations are ordered from small to large. From these order statistics you can find the sample percentiles.\n\nIf 0, the 100pth \'\'\'sample percentile\'\'\' has approximately np sample observations smaller less than it and also (n+1)p sample observations greater than it. One way of achieving this is to take the (100p)th sample percentile as the (n+1)p order statisic, provided that (n+1)p is an integer. \n\nIf (n+1)p is not an integer but is equal to r plus some fraction a/b then you can use a linear interpolation between y_r and y_{r+1}.\nSo the 100pth sample percentile is defined as:\n\n:\\tilde{\\pi}_p = y_r +(a/b)(y_{r+1}-y_r)\n\nCertain percentiles have special names. The 50th percentile is the \'\'\'[[median]]\'\'\' of the sample. The 25th, 50th, and 75th percentiles are the first, second and third \'\'\'quartiles\'\'\' of the sample. This gives us \'\'\'five-number summary\'\'\' of a set of data. Its constituents are: minimum, the first quartile, the median, the third quartile and the maximum. Written is this order. \n\nNow the \'\'\'IQR\'\'\' or \'\'\'interquartile range\'\'\' is defined as:\n\n:IQR = \\tilde{r}_3-\\tilde{r}_1.\n\n==Conto==\n\nItungan ieu make data tina kaca [[quartile]].\n\n

\n     i    x[i]\n     1    102\n     2    105\n    ----------- the first quartile, Q[1] = (105+106)/2 = 105.5\n     3    106\n     4    109\n   ------------ the second quartile, Q[2] or median = 109.5\n     5    110\n     6    112\n   ------------ the third quartile, Q[3] = (112+115)/2 = 113.5\n     7    115\n     8    118\n
\n\nTina tabel eta, the \'\'\'interquartile range\'\'\' is 113.5 - 105.5 = 8\n\nTempo ogé: [[statistical dispersion]], [[mean]]','',13,'Budhi','20041224234143','',0,0,1,0,0.553027375393,'20041224234252','79958775765856'); INSERT INTO cur VALUES (1457,0,'Information_geometry','[[Category:Geometry]]\nIn [[mathematics]] and especially in [[statistical inference]], \'\'\'information geometry\'\'\' is the study of [[probability]] and [[information theory|information]] by way of [[differential geometry]]. It reached maturity through the work of [[Shun\'ichi Amari]] in the 1980s, with what is currently the canonical reference book: \'\'Differential-geometrical methods in statistics\'\'.\n\nInformation geometry is based primarily on the [[Fisher information metric]]:\n\n:g_{ij}=\\int \\frac{\\partial \\log p(x,\\theta)}{\\partial \\theta_i} \\frac{\\partial \\log p(x,\\theta)}{\\partial \\theta_j} p(x,\\theta)\\, dx\n\nSubstiting \'\'i\'\' = −ln(\'\'p\'\') from [[information theory]], the formula becomes:\n\n:g_{ij}=\\int \\frac{\\partial i(x,\\theta)}{\\partial \\theta_i} \\frac{\\partial i(x,\\theta)}{\\partial \\theta_j} p(x,\\theta)\\, dx\n\nWhich can be thought of intuitively as: \"The distance between two points on a statistical differential manifold is the amount of information between them, i.e. the informational difference between them.\"\n\nThus, if a point in information space represents the state of a system, then the trajectory of that point will, on average, be a [[random walk]] through information space, i.e. will [[diffusion|diffuse]] according to [[Brownian motion]].\n\nWith this in mind, the information space can be thought of as a [[fitness landscape]], a trajectory through this space being an \"evolution\". The Brownian motion of evolution trajectories thus represents the [[no free lunch]] phenomena discussed by [[Stuart Kauffman]].\n\n===Natural gradient===\nAn important concept in information geometry is the [[natural gradient]]. The concept and theory of the natural gradient suggests an adjustment to the [[Lyapunov function|energy function]] of a [[learning rule]]. This adjustment takes into account the [[curvature]] of the (prior) [[statistical differential manifold]], by way of the Fisher information metric.\n\nThis concept has many important applications in [[blind signal separation]], [[neural network]]s, [[artificial intelligence]], and other engineering problems that deal with information. Experimental results have shown that application of the concept leads to substantial performance gains.\n\n== Rujukan ==\n* Shun\'ichi Amari - \'\'Differential-geometrical methods in statistics\'\', Lecture notes in statistics, Springer-Verlag, Berlin, 1985\n* Shun\'ichi Amari, Hiroshi Nagaoka - \'\'Methods of information geometry\'\', Transactions of mathematical monographs; v. 191, American Mathematical Society, 2000\n\n\n{{msg:stub}}','/* References */',13,'Budhi','20041224221730','',0,0,1,0,0.839079319424,'20041224221730','79958775778269'); INSERT INTO cur VALUES (1458,0,'Dinamika_sistim','[[zh:系统动力学]]\n\n\'\'\'Dinamika sistim\'\'\' sahiji \'\'pendekatan\'\' keur dinamika dina [[dinamika populasi|populasi]], [[system]] [[ecology|ekologi]] sarta [[ékonomi]], nu ilaharna pakait raket. Dinamika sistem dipanggihkeun di awal taun [[1960s]] ku [[Jay W. Forrester]] di [[MIT]] nu ngawangun MIT System Dynamics Group. Dina waktu nu sarua, manehna mimiti make nu nalungtik ngeunaan sistim salila manehna gawe di [[electrical engineering|rekayasa listrik]] keur sistim nu dipake unggal poe. Naha nu dipake sistim dinamik beda tina pendekatan sejen nu diajarkeun dina [[complex system|sistim kompleks]] nu dipake di [[feedback]] loops. [[Stock and flow|\'\'Stocks\'\']] sarta [[Stock and flow|\'\'flows\'\']] ngarupakeun wangunan blok model sistim dinamika. Manehna mantuan ngajelaskeun kumaha sistim pakait ku \'\'feedback loops\'\' nu dijieun [[nonlinearity]] remen kapanggih dina masalah kiwati. Perangkat lunak komputer dipake keur [[computer simulation|simulasi]] [[model]] dinamika sistim nu keur ditalungtik. Running \"what if\" simulations to test certain policies on such a model can greatly aid in understanding how the system changes over time.\n\n==Tumbu kaluar==\n* [http://web.mit.edu/sdg/www/ MIT System Dynamics Group] \n* [http://www.systemdynamics.org The System Dynamics Society] is an international, nonprofit organization devoted to encouraging the development and use of systems thinking and system dynamics around the world\n* [http://web.mit.edu/jsterman/www/DID.html An Annotated Survey of the Essential System Dynamics Literature]\n\n===Perngkat lunak haratis===\n* [http://www.ierm.ed.ac.uk/simile/ Simile] (free for research, educational and personal use)\n* http://www.suite101.com/article.cfm/scientific_computing/85003\n* [http://www.vensim.com/ Vensim] (free for educational and personal use)\n\n===Mailing lists===\n* [http://www.vensim.com/sdmail/sdinfo.html System Dynamics Mailing List]\n* [http://www.jiscmail.ac.uk/lists/simsoc.html Computer Simulation in Social Sciences]\n[[Category:Systems theory]]','',13,'Budhi','20040910011852','',0,0,0,0,0.235390580835,'20041228003003','79959089988147'); INSERT INTO cur VALUES (1459,0,'Survivor_function','The \'\'\'survivor function\'\'\' or \'\'\'reliability function\'\'\' is a property of any [[random variable]] that maps a set of events, usually associated with mortality or failure of some system, onto [[time]]. It captures the [[probability]] that the system will survive beyond a specified time. The term \'\'reliability function\'\' is common in [[engineering]] while the term \'\'survivor function\'\' is used in a broader range of applications, including human mortality.\n\n==Definition==\n\n\'\'Definition.\'\' Let \'\'X\'\' be a random variable with [[cumulative distribution function]] \'\'F\'\'(\'\'t\'\') on the interval [0,∞). Its \'\'survivor-\'\', or \'\'reliability-function\'\' is:\n\n:R(t)=1-F(t).\n\n==Properties==\n\nEvery survivor function \'\'R\'\'(\'\'t\'\') is [[monotone decreasing]].\n\nThe [[time]], \'\'t\'\'=0, represents some origin, typically the beginning of a study or the start of operation of some system. \'\'R\'\'(0) is commonly unity but can be less to represent the [[probability]] that the system fails immediately upon operation.\n\nAgain, lim\'\'t\'\'→∞\'\'R\'\'(\'\'t\'\') is commonly zero but can be greater to represent a system in which [[eternal life]] is possible.\n\n==Related concepts==\n\nSee also:\n\n*[[Hazard rate]]\n*[[Cummulative hazard function]]\n*[[Mean time to failure]]\n*[[Mean residual life]]','',13,'Budhi','20040903073935','',0,0,0,1,0.71913072966,'20040903073935','79959096926064'); INSERT INTO cur VALUES (1460,0,'Fungsi_survivor','\'\'\'Fungsi survivor\'\'\' atawa \'\'\'fungsi reliabiliti\'\'\' nyaeta sipat unggal [[variabel acak]] nu ngagambarkeun susunan kajadian, ilaharna pakait jeung paeh atawa gagalna sababaraha sistim, dumasar kana [[time]]. Ieu kawengku dina [[probability|probabiliti]] nu mana sistim bakal nyalametkeun maneh salila waktu nu ditangtukeun. Watesan \'\'fungsi reliabiliti\'\' ilahar dipake dina widang [[rékayasa]] sabalikna watesan \'\'fungsi survivor\'\' dipake leuwih lega, kaasup dina hurip manusa.\n\n==Harti==\n\nAnggap \'\'X\'\' ngarupakeun variabel bebas nu mibanda [[cumulative distribution function]] \'\'F\'\'(\'\'t\'\') dina interval [0,∞). Maka \'\'fungsi-survivor\'\' atawa \'\'fungsi-reliabiliti\'\' nyaeta:\n\n:R(t)=1-F(t).\n\n==Sipat==\n\nUnggal fungsi \'\'R\'\'(\'\'t\'\') bakal [[monotone decreasing|turun sacara angger]].\n\n[[time|Waktu]], \'\'t\'\'=0, ngagambarkeun kaayaan mimiti, sacara tipikal dimimitian nu nalungtik atawa sistim mimiti dipake. \'\'R\'\'(0) ilaharna satuan tapi bisa kurang keur ngagambarkeun [[probability|probabiliti]] numana sistem gagal teu lila sanggeus operasi.\n\nSakali deui, lim\'\'t\'\'→∞\'\'R\'\'(\'\'t\'\') ilaharna nol tapi bisa oge leuwih gede keur ngagambarkeun [[eternal life|kahirupan dina jero]] sistim nu mungkin.\n\n==Konsep pakait==\n\nTempo oge:\n\n*[[Hazard rate]]\n*[[Cummulative hazard function]]\n*[[Mean time to failure]]\n*[[Mean residual life]]','',13,'Budhi','20041224232346','',0,0,0,0,0.235112252755,'20041224232419','79958775767653'); INSERT INTO cur VALUES (1461,0,'Survival_analysis','\'\'\'Survival analysis\'\'\' is a branch of [[statistics]] which deals with death in biological organisms and failure in mechanical systems. \nThis topic is called \'\'[[reliability theory (engineering)|reliability theory]]\'\' or \'\'reliability analysis\'\' in engineering.\nDeath or failure is called an \"event\" in the survival analysis literature, and so models of death or failure are generically termed \'\'time-to-event models\'\'.\n\nSurvival analysis attempts to answer questions such as: what is the fraction of a population which will survive past a certain time? Of those that survive, at what rate will they die or fail? Can multiple causes of death or failure be taken into account? How do particular circumstances or characteristics increase or decrease the odds of survival?\n\nTo answer such questions, \nit is necessary to define \"lifetime\".\nIn the case of biological survival,\n[[death]] is unambiguous,\nbut for mechanical reliability,\n[[failure]] may not be well-defined,\nfor there may well be mechanical systems in which failure is partial, a matter of degree, or not otherwise not localized in [[time]].\nEven in biological problems,\nsome events (for example, [[myocardial infarction|heart attack]] or other organ failure) may have the same ambiguity.\nThe [[theory]] outlined below assumes well-defined events at specific times;\nother cases may be better treated by models which explicitly account for ambiguous events.\n\nThe theory of survival present here also assumes that death or failure happens just once for each subject.\n\'\'Recurring event\'\' or \'\'repeated event\'\' models relax that assumption.\nThe study of recurring events is relevant in [[systems reliability]].\n\nThis article is phrased primarily in terms of biological survival, \nbut this is just a convenience.\nAn equivalent formulation in terms of mechanical failure can be made by replacing every occurrence of \'\'death\'\' with \'\'failure\'\'.\n\n==General formulation==\n\n=== Survival function ===\n\nThe object of primary interest is the \'\'\'survival function\'\'\', conventionally denoted \'\'S\'\', which is defined as\n\n:S(t) = \\Pr(T > t)\n\nwhere \'\'t\'\' is some time, \'\'T\'\' is the time of death, and \"Pr\" stands for probability. That is: the survival function is the probability that the time of death is later than some specified time.\nThe survival function is also called the \'\'survivor function\'\' or \'\'survivorship function\'\' in problems of biological survival, and the \'\'reliability function\'\' in mechanical survival problems. \nIn the latter case, the reliability function is denoted \'\'R\'\'(\'\'t\'\').\n\nUsually one assumes \'\'S\'\'(0) = 1,\nalthough it could be less than 1 if there is the possibility of immediate death or failure.\nSome survival distributions (for example the Gaussian distribution) have the property that \'\'S\'\'(\'\'t\'\') < 1 for all finite \'\'t\'\',\nbut this point can be finessed or ignored;\nsee the discussion under \"Some survival distributions\" below.\n\nThe survival function must be decreasing: \'\'S\'\'(\'\'u\'\') < \'\'S\'\'(\'\'t\'\') if \'\'u\'\' > \'\'t\'\'.\nThis expresses the notion that survival is only less probable as one ages.\nGiven this property,\nthe lifetime distribution function and event density (\'\'F\'\' and \'\'f\'\' below) are well-defined.\n\nSurvival probability is usually assumed to approach zero as age increases without bound, i.e., \'\'S\'\'(\'\'t\'\') → 0 as \'\'t\'\' → ∞,\nalthough the limit could be greater than zero if [[eternal life]] is possible.\n\n=== Lifetime distribution function and event density ===\n\nRelated quantities are defined in terms of the survival function.\nThe \'\'\'lifetime distribution function\'\'\', conventionally denoted \'\'F\'\', is defined as the complement of the survival function,\n\n:F(t) = \\Pr(T \\le t) = 1 - S(t)\n\nand the derivative of \'\'F\'\' (i.e., the density function of the lifetime distribution) is conventionally denoted \'\'f\'\',\n\n:f(t) = \\frac{d}{dt} F(t)\n\n\'\'f\'\' is sometimes called the \'\'\'event density\'\'\';\nit is the rate of death or failure events per unit time.\n\n=== Hazard function and cumulative hazard function ===\n\nThe \'\'\'hazard function\'\'\', conventionally denoted \\lambda,\nis defined as the event rate at time \'\'t\'\' conditional on survival until time \'\'t\'\' or later,\n\n:\\lambda(t)\\,dt = \\Pr(t < T < t+dt\\,|\\,T > t) = \\frac{f(t)\\,dt}{S(t)} = -\\frac{S\'(t)\\,dt}{S(t)}\n\n\'\'Force of mortality\'\' is a synonym of \'\'hazard function\'\' which is used particularly in [[demographics]].\nThe term \'\'hazard rate\'\' is another synonym.\n\nThe hazard function must be positive, λ(\'\'t\'\') > 0, \nbut is not otherwise constrained;\nthe hazard function may be increasing or decreasing, nonmonotonic, or discontinuous.\nAn example is the \"bathtub\" hazard function,\nwhich is large for small values of \'\'t\'\', decreasing to some minimum, and thereafter increasing again;\nthis can model the property of some mechanical systems to either failure soon after operation, or much later, as the system ages.\n\nThe hazard function can alternatively be represented in terms of the \'\'\'cumulative hazard function\'\'\', conventionally denoted \\Lambda:\n\n:\\Lambda(t) = -\\log S(t)\\,\n\nso\n\n:\\frac{d}{dt} \\Lambda(t) = -\\frac{S\'(t)\\,dt}{S(t)} = \\lambda(t)\n\n=== Quantities derived from the survival distribution ===\n\n\'\'\'Future lifetime\'\'\' at a given time \'\'t\'\'0 is denoted by the time remaining until death, thus future lifetime is T-t_0 in the present notation.\nThe \'\'\'expected future lifetime\'\'\' is the [[nilai ekspektasi]] of future lifetime. Now the event density given survival until t + t_0 or later, given survival until t_0, is just\n\n:\\frac{f(t+t_0)}{S(t_0)},\n\nso the expected future lifetime is given by\n\n:\\frac{1}{S(t_0)} \\int_0^{\\infty} t\\,f(t+t_0)\\,dt\n\nFor t_0 = 0, i.e., at birth, this reduces to the expected lifetime.\n\nIn reliability problems,\nthe expected lifetime is called the \'\'mean time to failure\'\',\nand the expected future lifetime is called the \'\'mean residual lifetime\'\'.\n\nThe probability of individual survival until \'\'t\'\' or later is \'\'S\'\'(\'\'t\'\'), by definition.\nThe expected number of survivors, in a [[population]] of \'\'n\'\' individuals,\nis \'\'n\'\' × \'\'S\'\'(\'\'t\'\'), assuming the same survival function for all.\nThus the expected proportion of survivors is \'\'S\'\'(\'\'t\'\'),\nand the [[varian]] of the proportion of survivors is \'\'S\'\'(\'\'t\'\') × (1-\'\'S\'\'(\'\'t\'\')).\n\nThe age at which a specified proportion of survivors remain can be found by solving the equation \'\'S\'\'(\'\'t\'\') = \'\'q\'\' for \'\'t\'\',\nwhere \'\'q\'\' is the [[quantile]] in question.\nTypically one is interested in the \'\'\'[[median]] lifetime\'\'\', for which \'\'q\'\' = 1/2,\nor other quantiles such as \'\'q\'\' = 0.90 or \'\'q\'\' = 0.99.\n\nOne can also make more complex inferences from the survival distribution.\nIn mechanical reliability problems,\none can bring cost (or [[utility]], more generally) into consideration and solve problems concerning repair or replacement.\nSee [[age-replacement problem]] and [[durability]] for further discussion of this topic.\n\n==Some survival distributions==\n\nSurvival models are constructed by choosing a basic survival distribution. \nIt is straightforward to phrase model fitting and analysis in general terms, \nusing the concepts outlined in under \"General formulation\", above.\nThus it is relatively easy to substitute one distribution for another,\nin order to study the consequences of different choices.\n\nThe choice of survival distribution expresses some particular information about the relation of time and any exogenous variables to survival, and as such, it is analogous to the choice of [[link function]] in [[generalized linear models]]. There are several distributions commonly used in survival analysis, which are listed in the table below. Additional types of distributions can be found in the references.\n\n:\n\\begin{matrix}\n & S(t) \\\\\n\\\\\n\\mbox{Gaussian} & 1-\\Phi(t) \\\\\n\\\\\n\\mbox{Extreme value} & \\exp(-\\exp t) \\\\\n\\\\\n\\mbox{Logistic} & 1/(1+\\exp t)\n\\end{matrix}\n\n\nHere \\Phi indicates the standard normal cumulative distribution function. See [[normal distribution]].\n\n==Fitting parameters to data==\n\nSurvival models can be usefully viewed as ordinary regression models in which the response variable is time.\nHowever,\ncomputing the likelihood function \n(needed for fitting parameters or making other kinds of inferences) \nis complicated by missing data problems which are peculiar to time.\nThe birth and death of a subject may be known,\nin which case the lifetime is known.\nMore generally,\nit may be known only that the date of birth was prior to some date:\nthis is called \'\'left censoring\'\'.\nAlso, \nit may be known only that the date of death is after some date:\nthis is called \'\'right censoring\'\'.\nThe lifetime may be both right and left censored,\nwhich is sometimes called \'\'interval censoring\'\'.\nIt may also happen that subjects with a lifetime less than some threshold may not be observed at all:\nthis is called \'\'truncation\'\'.\nNote that truncation is different from left censoring,\nsince for a left censored datum, \nwe know the subject exists,\nbut for a truncated datum,\nwe may be completely unaware of the subject.\n\nThere are standard examples of censoring and truncation.\nPerhaps the most common is right censoring.\nIf we examine a group of living subjects, \nwe know that each one is alive today, but we do not know their future date of death.\nLeft censoring is also common.\nFor each subject, we know they are alive today but we may not know their date of birth.\nTruncation is also common.\nIn a so-called \'\'delayed entry\'\' study,\nsubjects are not observed at all until they have reached a certain age.\nFor example,\npeople may not be observed until they have reached the age to enter school.\nAny deceased subjects in the pre-school age group would be unknown.\n\nThe [[likelihood function]] for a survival model,\nin the presence of censored data,\nis formulated as follows.\nBy definition the likelihood function is the joint probability of the data given the parameters of the model.\nIt is customary to assume that the data are independent given the parameters.\nThen the likelihood function is the product of the likelihood of each datum.\nIt is convenient to partition the data into four categories:\nuncensored, left censored, right censored, and interval censored.\nThese are denoted \"unc.\", \"l.c.\", \"r.c.\", and \"i.c.\" in the equation below.\n\n: L(\\theta) = \\prod_{T_i\\in unc.} \\Pr(T = T_i|\\theta)\n \\prod_{i\\in l.c.} \\Pr(T < T_i|\\theta)\n \\prod_{i\\in r.c.} \\Pr(T > T_i|\\theta)\n \\prod_{i\\in i.c.} \\Pr(T_{i,r} < T < T_{i,l}|\\theta) \n\nFor an uncensored datum, with T_i equal to the age at death, we have\n\n: \\Pr(T = T_i|\\theta) = f(T_i|\\theta) \n\nFor a left censored datum,\nsuch that the age at death is known to be less than T_i, \nwe have\n\n: \\Pr(T < T_i|\\theta) = F(T_i|\\theta) = 1 - S(T_i|\\theta) \n\nFor a right censored datum, \nsuch that the age at death is known to be greater than T_i, \nwe have\n\n: \\Pr(T > T_i|\\theta) = S(T_i|\\theta) \n\nFor an interval censored datum, \nsuch that the age at death is known to be greater than T_{i,r}\nand less than T_{i,l},\nwe have\n\n: \\Pr(T_{i,r} < T < T_{i,l}|\\theta) \n = S(T_{i,r}|\\theta) - S(T_{i,l}|\\theta) \n\n==References==\n* Regina Elandt-Johnson and Norman Johnson. \'\'Survival Models and Data Analysis.\'\' New York: John Wiley & Sons. 1980/1999.\n\n* Jerald F. Lawless. \'\'Statistical Models and Methods for Lifetime Data\'\', 2nd edition. John Wiley and Sons, Hoboken. 2003.\n\n* Terry Therneau. \"A Package for Survival Analysis in S\". http://www.mayo.edu/hsr/people/therneau/survival.ps, at: http://www.mayo.edu/hsr/people/therneau.html\n\n[[Category:Probability and statistics]]','/* Quantities derived from the survival distribution */',13,'Budhi','20040917032650','',0,0,0,0,0.868852002019,'20040917032650','79959082967349'); INSERT INTO cur VALUES (1462,0,'Survey_sampling','Dina [[statistik]], \'\'\'survey sampling\'\'\' is random selection of a sample from a finite population. It is an important part of [[planning statistical research]] and [[desain percobaan]]. Sophisticated sampling techniques that are both economical and scientifically reliable have been developed.\n\nAn entire industry of public opinion polling as well as the technical activities of the [[United States Census Bureau|U.S. Bureau of the Census]] depends on these techniques. \n\nThe most elementary methodology is called [[simple random sampling]]. Most of the theory of statistics assumes this kind of sampling unless otherwise noted. It assures that every possible subset of the population which has the desired sample size is given the same probability of selection.\n\nThe possibility of very expensive or very atypical samples has lead to a variety of modifications such as [[stratified sampling]], [[cluster sampling]], and [[multistage sampling]]. The most experienced center in these techniques outside the Census Bureau is the [[University of Michigan Survey Research Center]].\n\nIn public opinion polling by private companies or organizations unable to require response, the resulting sample is self-selected rather than random. Volunteering for the sample may be determined by characteristics such as submissiveness or availability. The samples in such surveys are therefore [[non-probability samples]] of the population, and the validity of estimates of [[Parameter|parameters]] based on them is unknown. They are, however, unquestionably random samples of that sizeable subgroup of the population which volunteers for opinion surveys.\n\n== External links ==\n\n* [http://www.census.gov/dmd/www/2khome.htm U.S. Bureau of the Census]\n* [http://www.isr.umich.edu/src/research.html University of Michigan Survey Research Center]','',13,'Budhi','20041224104914','',0,0,1,0,0.210021848422,'20041224104914','79958775895085'); INSERT INTO cur VALUES (1463,0,'Sufficiency_(statistics)','Dina [[statistik]], one often considers a family of [[probability distribution]]s for a [[variabel acak]] \'\'X\'\' (and \'\'X\'\' is often a [[vector space|vector]] whose components are [[scalar]]-valued random variables, frequently [[statistical independence|independent]]) parameterized by a scalar- or vector-valued parameter, which let us call θ. A quantity \'\'T\'\'(\'\'X\'\')\nthat depends on the (observable) random variable X but \'\'\'not\'\'\' on the (unobservable) parameter θ is called a \'\'\'statistic\'\'\'. [[Ronald Fisher|Sir Ronald Fisher]] tried to make precise the intuitive idea that a statistic may capture all of the information in \'\'X\'\' that is relevant to the estimation of θ. A statistic that does that is called a \'\'\'sufficient statistic\'\'\'.\n\n==Mathematical definition==\n\nThe precise definition is this:\n\n:A statistic \'\'T\'\'(\'\'X\'\') is \'\'\'sufficient for θ\'\'\' precisely if the conditional [[probability distribution]] of the data \'\'X\'\' given the statistic \'\'T\'\'(\'\'X\'\') does not depend on θ.\n\nAn equivalent test, known as the \'\'[[Ronald Fisher|Fisher\'s]] factorization criterion\'\', is often used instead.\nIf the [[probability density function]] (in the discrete case, the probability mass function) of \'\'X\'\' is \'\'f\'\'(\'\'x\'\';θ)\'\', then \'\'T\'\' satisfies the factorization criterion if and only if functions \'\'g\'\' and \'\'h\'\' can be found such that\n\n:\nf(x;\\theta)=g\\left(T(x),\\theta\\right)h(x).\n\n\nThis is a product in which one factor, \'\'h\'\', does not depend on θ and the other depends on \'\'x\'\' only through \'\'T\'\'(\'\'x\'\'). The way to think about this is to consider varying \'\'x\'\' in such a way as to maintain a constant value of \'\'T\'\'(\'\'X\'\') and ask whether such a variation has any effect on inferences one might make about \'\'θ\'\'. If the factorization criterion above holds, the answer is \"none\" because the dependence of the likelihood function \'\'f\'\' on \'\'θ\'\' is unchanged.\n\n==Examples==\n\n*If \'\'X\'\'1, ...., \'\'X\'\'\'\'n\'\' are independent [[Bernoulli trial|Bernoulli-distributed]] random variables with expected value \'\'p\'\', then the sum \'\'T\'\'(\'\'X\'\') = \'\'X\'\'1 + ... + \'\'X\'\'\'\'n\'\' is a sufficient statistic for \'\'p\'\'.\n\nThis is seen by considering the joint probability distribution:\n\n:\nP(X=x)=P(X_1=x_1,X_2=x_2,\\ldots,X_n=x_n).\n\n\nBecause the observations are independent, this can be written as\n\n:\np^{x_1}(1-p)^{1-x_1} p^{x_2}(1-p)^{1-x_2}\\cdots p^{x_n}(1-p)^{1-x_n} \n\nand, collecting powers of \'\'p\'\' and 1 − \'\'p\'\' gives\n\n:\np^{\\sum x_i}(1-p)^{n-\\sum x_i}=p^{T(x)}(1-p)^{n-T(x)}\n\n\nwhich satisfies the factorization criterion, with \'\'h\'\'(\'\'x\'\') being just the identity function. Note the crucial feature: the unknown parameter (here \'\'p\'\') interacts with the observation \'\'x\'\' only via the statistic \'\'T\'\'(\'\'x\'\') (here the sum Σ \'\'x\'\'i).\n\n*If \'\'X\'\'1, ...., \'\'X\'\'\'\'n\'\' are independent and uniformly distributed on the interval [0,θ], then max(\'\'X\'\'1, ...., \'\'X\'\'\'\'n\'\' ) is sufficient for θ.\n\nTo see this, consider the joint probability distribution:\n\n:\nP(X=x)=P(X_1=x_1,X_2=x_2,\\ldots,X_n=x_n).\n\n\nBecause the observations are independent, this can be written as\n\n:\n\\frac{H(\\theta-x_1)}{\\theta}\\times\n\\frac{H(\\theta-x_2)}{\\theta}\\times\\ldots\\times\n\\frac{H(\\theta-x_n)}{\\theta}\n\n\nwhere \'\'H\'\'(\'\'x\'\') is the [[Heaviside step function]]. This may be written as\n\n:\n\\frac{H\\left(\\theta-\\max(x_i)\\right)}{\\theta^n}\n\n\nwhich shows that the factorization criterion is satisfied, again with \'\'h(x)\'\' being the identity function.\n\n==The Rao-Blackwell theorem==\n\nSince the conditional distribution of X given \'\'T\'\'(\'\'X\'\') does not depend on θ, neither does the [[conditional expectation|conditional \'\'expected value\'\']] of \'\'g\'\'(\'\'X\'\') given \'\'T\'\'(\'\'X\'\'), where \'\'g\'\' is any (sufficiently well-behaved) function. Consequently that conditional expected value is actually a \'\'statistic\'\', and so is available for use in estimation. If \'\'g\'\'(\'\'X\'\') is any kind of estimator of θ, then typically the conditional expectation of \'\'g\'\'(\'\'X\'\') given \'\'T\'\'(\'\'X\'\') is a better estimator of θ ; one way of making that statement precise is called the \'\'\'[[Rao-Blackwell theorem]]\'\'\'. Sometimes one can very easily construct a very crude estimator \'\'g\'\'(\'\'X\'\'), and then evaluate that conditional expected value to get an estimator that is in various senses optimal.','',13,'Budhi','20050101220415','',0,0,1,0,0.476965628786,'20050101220415','79949898779584'); INSERT INTO cur VALUES (1464,0,'Studentized_residual','In [[statistics]], a \'\'\'Studentized residual\'\'\', named in honor of [[William Sealey Gosset]], who wrote under the pseudonym \'\'\'\'\'Student\'\'\'\'\', is a [[errors and residuals in statistics|residual]] adjusted by dividing it by an estimate of its standard deviation. Studentization of residuals is an important technique in the detection of [[outlier]]s.\n\n==Errors versus residuals==\n\nIt is very important to understand the difference between [[errors and residuals in statistics]]. Consider simple [[linear regression]] model\n\n:Y_i=\\alpha_0+\\alpha_1 x_i+\\varepsilon_i,\n\nwhere the \'\'\'errors\'\'\' ε\'\'i\'\', \'\'i\'\' = 1, ..., \'\'n\'\', are [[statistical independence|independent]] and all have the same variance σ2. The \'\'\'residuals\'\'\' are not the true, and unobservable, errors, but rather are \'\'estimates\'\', based on the observable data, of the errors. When the method of least squares is used to estimate α0 and α1, then the residuals, unlike the errors, cannot be independent since they satisfy the two constraints\n\n:\\sum_{i=1}^n \\hat{\\varepsilon}_i=0\n\nand\n\n:\\sum_{i=1}^n \\hat{\\varepsilon}_i x_i=0.\n\n(Here \\varepsilon_i is the \'\'i\'\'th error, and \\hat{\\varepsilon}_i is the \'\'i\'\'th residual.) Moreover, the residuals, unlike the errors, do not all have the same variance: the variance increases as the corresponding \'\'x\'\'-value gets farther from the average \'\'x\'\'-value. \'\'\'\'\'The fact that the variances of the residuals differ, even though the variances of the true errors are all equal to each other, is the principal reason for the need for Studentization.\'\'\'\'\'\n\n==How to Studentize==\n\nFor this simple model, the \"design matrix\" is\n\n:X=\\left[\\begin{matrix}1 & x_1 \\\\ \\vdots & \\vdots \\\\ 1 & x_n \\end{matrix}\\right]\n\nand the \"hat matrix\" \'\'H\'\' is the matrix of the [[orthogonal projection]] onto the column space of the design matrix:\n\n:H=X(X^T X)^{-1}X^T.\n\nThe \"leverage\" \'\'h\'\'\'\'ii\'\' is the \'\'i\'\'th diagonal entry in the hat matrix. The variance of the \'\'i\'\'th residual is\n\n:\\mbox{var}(\\hat{\\varepsilon}_i)=\\sigma^2(1-h_{ii}).\n\nThe corresponding \'\'\'Studentized residual\'\'\' is then\n\n:{\\hat{\\varepsilon}_i\\over \\hat{\\sigma} \\sqrt{1-h_{ii}\\ }}\n\nwhere \\hat{\\sigma} is an appropriate estimate of σ.\n\n==Internal and external Studentization==\n\nThe estimate of σ2 may be\n\n:\\hat{\\sigma}^2={1 \\over n-2}\\sum_{j=1}^n \\hat{\\varepsilon}_j^2.\n\nBut it is desirable to exclude the \'\'i\'\'th observation from the process of estimating the variance when one is considering whether to consider the \'\'i\'\'th case to be an outlier. Consequently one may use the estimate\n\n:\\hat{\\sigma}_{(i)}^2={1 \\over n-3}\\sum_{j=1}^n \\hat{\\varepsilon}_j^2,\n\nbased on all but the \'\'i\'\'th case. If the latter estimate is used, \'\'excluding\'\' the \'\'i\'\'th case, then the residual is said to be \'\'\'\'\'externally Studentized\'\'\'\'\', if the former is used, \'\'including\'\' the \'\'i\'\'th case, then it is \'\'\'\'\'internally Studentized\'\'\'\'\'.\n\nIf the errors are independent and [[sebaran normal|normally distributed]] with [[nilai ekspektasi]] 0 and varian σ2, then the [[probability distribution]] of the \'\'i\'\'th externally Studentized residual is a [[sebaran-t student]] numana \'\'n\'\' − 3 [[degrees of freedom|tingkat kabebasan]].\n\n[[Category:Statistics]]','/* Internal and external Studentization */',13,'Budhi','20040917054135','',0,0,0,0,0.415190241959,'20041206070345','79959082945864'); INSERT INTO cur VALUES (1465,0,'Stein\'s_lemma','\'\'\'Stein\'s lemma\'\'\', ngaran keur ngahargaan ka [[Charles Stein]], may be characterized as a theorem of [[probability theory]] that is of interest primarily because of its application to [[statistical inference]] -- in particular, its application to [[James-Stein estimation]] and [[empirical Bayes method]]s.\n\n==Statement of the lemma==\n\nSuppose \'\'X\'\' is a [[sebaran normal|normally distributed]] [[random variable]] with [[nilai ekspektasi]] μ and [[varian]] σ2. Further suppose \'\'g\'\' is a function for which the two expectations E( \'\'g\'\'(\'\'X\'\') (\'\'X\'\' − μ) ) and E( \'\'g\'\' ′(\'\'X\'\') ) both exist (the existence of the expectation of any random variable is equivalent to the finiteness of the expectation of its absolute value). Then\n\n:E(g(X)(X-\\mu))=\\sigma^2 E(g\'(X)).\n\nIn order to prove this lemma, recall that the [[probability density function]] for the normal distribution with expectation 0 and variance 1 is\n\n:\\varphi(x)={1 \\over \\sqrt{2\\pi}}e^{-x^2/2}\n\nand that for a normal distribution with expectation μ and varian σ2 is\n\n:{1\\over\\sigma}\\varphi\\left({x-\\mu \\over \\sigma}\\right).\n\nThen use [[integration by parts]].','',13,'Budhi','20040917031640','',0,0,0,0,0.387847576937,'20040917031640','79959082968359'); INSERT INTO cur VALUES (1466,0,'Rumus_prédiksi_Spearman-Brown','\'\'\'Rumus prédiksi Spearman-Brown\'\'\' (ogé dipikanyaho salaku \'\'rumus ramalan Spearman-Brown\'\') nyaéta rumus hubungan [[Reliability (psychometric)|reliabiliti]] [[psychometric|psikometri]] kana panjangna uji:\n\n{\\rho}^*_{xx\'}=\\frac{N{\\rho}_{xx\'}}{1+(N-1){\\rho}_{xx\'}}\n\nnu mana {\\rho}^*_{xx\'} nyaéta prédiksi reliabiliti; N nyaéta jumlah kombinasi \"test\" (tempo di handap); sarta {\\rho}_{xx\'} nyaéta reliabiliti \"tes\" ayeuna. Rumus prédiksi reability ngarupakeun uji anyar nu nyimpen ulangan N ayeuna (atawa sarua jeung nambahkeun bentuk N paralél tina tes ayeuna ka tes ayeuna). Maka N=2 akibatna duka kali panjang tes item nu ditambahkeun ku cara make sipat nu sarua dina tes ayeuna. Nilai N kurang ti hiji mungkin bisa dipake keur prediksi pangaruh dina tes nu pondok.\n\nRumus bisa oge disusun keur prediksi jumlah ulangan nu diperlukeun keur nangtukeun tingkat realibiliti:\n\nN=\\frac{{\\rho}_{xx\'}(1-{\\rho}^*_{xx\'})}\n{{\\rho}^*_{xx\'}(1-{\\rho}_{xx\'})}\n\n\nRumus ieu ilahar dipake ku ahli psikometri keur prediksi reabiliti sanggeus ngarubah panjang tes. Hubungan ieu salah sahiji hal nu penting keur ngarubah-sabagian sarta metoda nu pakait jeung estimasi reabiliti. \n\nRumus ieu oge mantuan ngarti kana hubungan nu teu linier antara tes reabiliti jeung panjang tes.\n\nLamun panjang/pondok tes teu paralel kana tes ayeuna, maka hasil prediksi moal akurat. Contona, lamun luhurna tes reliabiliti dipanjangan ku cara nambahan item nu goreng mangka reliabiliti bisa leuwih handap tinimbang nu diprediksi tina rumus ieu.\n\n[[Item response theory|Tiori respon item]] merlukeun \'\'informasi item\'\' keur ngahasilkeun prediksi nu leuwih hade dina ngaramal parobahan kualitas ukuran ku cara nambahan atawa ngurangan individu item..\n\n[[Category:Psikométrik]]','',3,'Kandar','20041228074634','',0,0,1,0,0.372508336032,'20050125103616','79958771925365'); INSERT INTO cur VALUES (1467,0,'Specificity','Dina [[binary classification|tes biner]], saperti dina tes diagnosa medis keur panyakit di hiji wewengkon, \'\'\'specificity\'\'\' nyaeta proporsi negatip bener tina sakabeh sampel negatip nu di tes, nyaeta\n:{\\rm specificity}=\\frac{\\rm number\\ of\\ true\\ negatives}{{\\rm number\\ of\\ true\\ negatives}+{\\rm number\\ of\\ false\\ positives}}.\n\nTempo\n* [[binary classification|klasifikasi biner]]\n* [[receiver operating characteristic]]\n* [[sensitivity (tests)]]\n* [[statistical significance]]\n* [[Type I error]]','',13,'Budhi','20040907055217','',0,0,0,0,0.178404952017,'20040907055217','79959092944782'); INSERT INTO cur VALUES (1468,0,'Statistical_efficiency','#REDIRECT [[Efficiency_(statistics)]]','',13,'Budhi','20040903084421','',0,1,0,1,0.553242487159,'20040903084421','79959096915578'); INSERT INTO cur VALUES (1469,0,'Estimasi_statistik','Aya sababaraha cara keur ngadiskusikeun \'\'\'estimasi statistik\'\'\'...\n\n== Sasaran ==\n#[[Titik estimasi]]\n#[[Interval estimasi]]\n#multivariate estimation??\n#[[Regression]]/[[Model building]]\n\n== Pendekatan/Filosofi==\n#frequentist, or \'\'classical\'\'\n#[[Bayesian estimation]]\n#fiducial??\n\n== Metoda ==\n\n(\'\'gabungan tina sakabeh nu di luhur\'\')\n\n#[[Maximum likelihood estimation]]\n#[[Method of moments]]\n#[[Least squares]]\n#[[Influence function]]s?\n#[[Interval kapercayaan]] (atawa wewengkon)\n#[[Highest posterior density]] interval/region\n#[[Fiducial]]??\n#\'\'etc...\'\'','/* Metoda */',13,'Budhi','20041225044857','',0,0,1,0,0.169332215641,'20041225044857','79958774955142'); INSERT INTO cur VALUES (1470,0,'Simple_random_sampling','#REDIRECT [[simple random sample]]','',13,'Budhi','20040903084829','',0,1,0,1,0.770006388319,'20040903084900','79959096915170'); INSERT INTO cur VALUES (1471,0,'Sampel_acak_basajan','Dina [[statistik]], \'\'\'sampel acak basajan\'\'\' tina hiji populasi nyaeta sample nu dicokot sacara acak, unggal anggota dina eta populasi mibanda kamungkinan nu sarua pikeun dicokot. Dina populasi nu saeutik, cara nyokot sampelna digawekeun ku cara \"dicokot teu disimpen deui\", nyaeta kucara sacara tarapti milih unggal conto tina populasi.\n\nSacara konsep, nyokot sampel acak basajan ngarupakeun teknik nyokot sampel probibiliti nu pangbasajanna, sanajan kitu langka dipake sabab loba masalah dina makena. Nyokot sampel acak basajan lain ngarupakeun metoda nu epektip. Metoda ieu merlukeun ruang sampel nu kacida gedena sarta hasilna merlukeun waktu ngitung nu lila sarta biaya nu mahal. Lamun paniliti mibanda informasi nu cukup ngeunaan populasi, metoda ieu cukup episien. \n\nKauntunganna nyaeta bebas tina klasifikasi kasalahan sarta merlukeun kanyaho nu teu loba ngeunaan populasi. Dua kaayaan nu hade numana populasi ampir sarua sarta saeutikna informasi ngeunaan populasi. Lamun henteu dina kaayaan tadi, mangka leuwih hade migunakeun stratified sampling. \n\n\n\'\'See also : [[statistik]], [[marketing research]], [[quantitative marketing research]], [[sampling (statistics)|sampling]], [[cluster sampling]], [[multistage sampling]], [[nonprobability sampling]], [[systematic sampling]], [[stratified sampling]]\'\'','',13,'Budhi','20041224221345','',0,0,0,0,0.979155222876,'20041224221345','79958775778654'); INSERT INTO cur VALUES (1472,0,'Systematic_sampling','\'\'\'Systematic sampling\'\'\' is the selection of every kth element from a sampling frame, where k, the sampling interval, is calculated as:\n:::k = Number in population / Number in sample \nUsing this procedure each element in the population has a known and equal probability of selection. This makes systematic sampling functionally similar to [[simple random sampling]]. It is however, much more efficient and much less expensive to do.\n\nThe researcher must ensure that the chosen sampling interval does not hide a pattern. Any pattern would threaten randomness. A random starting point must also be selected.\n\n\'\'Tempo ogé: [[statistik]], [[marketing research]], [[quantitative marketing research]], [[sampling (statistics)|sampling]], [[cluster sampling]], [[multistage sampling]], [[simple random sampling]], [[nonprobability sampling]], [[stratified sampling]]\'\'','',13,'Budhi','20050101220859','',0,0,0,0,0.159160550292,'20050101220859','79949898779140'); INSERT INTO cur VALUES (1473,0,'Stratified_sampling','\'\'\'Stratified sampling\'\'\' nyaeta metoda sampling tina populasi dina [[statistik]].\n\nWhen subpopulations vary considerably, it is advantageous to sample each subpopulation (stratum) independently. \'\'\'Stratification\'\'\' is the process of grouping members of the population into relatively homogeneous subgroups before sampling. The strata should be mutually exclusive : every element in the population must be assigned to only one stratum. The strata should also be collectively exhaustive : no population element can be excluded. Then random sampling is applied within each stratum. This often improves the representativeness of the sample by reducing sampling error. It can produce a [[weighted mean]] that has less variability than the [[arithmetic mean]] of a simple random sample of the population.\n\nThere are several possible strategies:\n#Proportionate allocation uses a [[sampling fraction]] in each of the strata that is proportional to that of the total population. If the population consist of 60% in the male stratum and 40% in the female stratum, then the relative size of the two samples (one males, one females) should reflect this proportion. \n#Optimum allocation (or Disproportionate allocation) - Each stratum is proportionate to the [[standard deviation]] of the distribution of the variable. Larger samples are taken in the strata with the greatest variability to generate the least possible sampling variance.\n\nA real-world example of using stratified sampling would be for a US political [[survey]]. If we wanted the respondents to reflect the diversity of the population of the United States, the researcher would specifically seek to include participants of various minority groups such as race or religon, based on their porpotionality to the total population as mentioned above. A stratified survey could thus claim to be more represenative of the US population than a survey of [[random sampling]] or [[systematic sampling]]. \n\n\'\'\'Advantages:\'\'\'\n* focuses on important subpopulations but ignores irrelevant ones\n* improves the accuracy of estimation\n* efficient \n* sampling equal numbers from strata varying widely in size may be used equate the [[statistical power]] of [[Statistical tests|tests]] of differences between strata.\n\n\'\'\'Disadvantages:\'\'\'\n* can be difficult to select relevant stratification variables\n* not useful when there are no homogeneous subgroups\n* can be expensive\n* requires accurate information about the population.\n\n\n\n\n\'\'See also : [[statistics]], [[marketing research]], [[quantitative marketing research]], [[sampling (statistics)|sampling]], [[cluster sampling]], [[multistage sampling]], [[simple random sampling]], [[nonprobability sampling]], [[systematic sampling]]\'\'','',13,'Budhi','20041224115548','',0,0,1,0,0.854375186308,'20041224115548','79958775884451'); INSERT INTO cur VALUES (1474,0,'Cluster_sampling','\'\'\'Cluster sampling\'\'\' is used when \"natural\" groupings are evident in the population. The total population is divided into groups or clusters. Elements within a cluster should be as heterogeneous as possible. But there should be homogeneity between clusters. Each cluster should be a small scale version of the total population. Each cluster must be mutually exclusive and collectively exhaustive. A random sampling technique is then used on any relevant clusters to choose which clusters to include in the study. In single-stage cluster sampling, all the elements from each of the selected clusters are used. In two-stage cluster sampling, a random sampling technique is applied to the elements from each of the selected clusters.\n\nThe main difference between cluster sampling and [[stratified sampling]] is that in cluster sampling the cluster is treated as the sampling unit so analysis is done on a population of clusters (at least in the first stage). In stratified sampling, the analysis is done on elements within strata. In stratified sampling, a random sample is drawn from each of the strata, whereas in cluster sampling only the selected clusters are studied. The main objective of cluster sampling is to reduce costs by increasing sampling efficiency (This contrasts with stratified sampling where the main objective is to increase precision.). \n\nOne version of cluster sampling is \'\'\'area sampling\'\'\' or \'\'\'geographical cluster sampling\'\'\'. Clusters consist of geographical areas. A geographically dispersed population can be expensive to survey. Greater economy than simple random sampling can be achieved by treating several respondents within a local area as a cluster. It is usually necessary to increase the total sample size to achieve equivalent precision in the [[estimator]]s, but the savings in cost may make that feasible.\n\nIn some situations, cluster analysis is only appropriate when the clusters are approximately the same size. This can be achieved by combining clusters. If this is not possible, \'\'\'probability proportionate to size sampling\'\'\' is used. In this method, the probability of selecting an element in any given cluster varies inversely with the size of the cluster.\n\n\n\'\'Tempo ogé : [[statistik]], [[marketing research]], [[quantitative marketing research]], [[sampling (statistics)|sampling]], [[multistage sampling]], [[simple random sampling]], [[nonprobability sampling]], [[systematic sampling]], [[stratified sampling]]\'\'','',13,'Budhi','20050101221045','',0,0,0,0,0.811289454257,'20050101221045','79949898778954'); INSERT INTO cur VALUES (1475,0,'Multistage_sampling','\'\'\'Multistage sampling\'\'\' nyaeta bentuk kompleks tina [[cluster sampling]]. Using all the sample elements in all the selected clusters may be prohibitively expensive or not necessary. Under these circumstances, multistage cluster sampling becomes useful. Instead of using all the elements contained in the selected clusters, the researcher randomly selects elements from each cluster. Constructing the clusters is the first stage. Deciding what elements within the cluster to use, is the second stage. The technique is used frequently when a complete list of all members of the population does not exist.\n\n\'\'\'Probability-proportional-to-size sampling\'\'\' is a type of multistage cluster sampling. In this method, the probability of selecting an element in any given cluster varies inversely with the size of the cluster.\n\nAlthough cluster sampling and stratified sampling bear some superficial similarities, they are substantially different. In stratified sampling, a random sample is drawn from all the strata, where in cluster sampling only the selected clusters are studied, either in single stage or multi stage.\n\n\n\n\'\'See also : [[statistics]], [[marketing research]], [[quantitative marketing research]], [[sampling (statistics)|sampling]], [[cluster sampling]], [[simple random sampling]], [[nonprobability sampling]], [[systematic sampling]], [[stratified sampling]]\'\'','',13,'Budhi','20050101220516','',0,0,0,0,0.043318530565,'20050101220516','79949898779483'); INSERT INTO cur VALUES (1476,0,'Sebaran_sampling','Dina [[statistik]], \'\'\'sebaran sampling\'\'\' nyaeta [[probability distribution|sebaran probabiliti]], dina kaayaan [[sampling (statistics)|sampling]] dina [[Statistical population|populasi]] diulang, tina [[statistik]] nu diberekeun (kuantitas numerik diitung tina nilai [[data]] dina [[Sampling (statistics)|sample]]).\n\nBentuk (atawa rumus keur) sebaran sampling gumantung kana [[probability distribution|sebaran]] populasi, [[statistik]] nu ditempo sarta ukuran sampel nu dipake.\n\n(Catetan yen rumus nu leuwih presisi nyebutkeun yen sebaran statistik bisa dipake keur \'\'sakabeh sampel nu mungkin\'\' tina ukuran nu diberekeun, henteu ngan sakadar \"dina kaayaan sampling diulang\".)\n\nContona, anggap populasi nu kacida gedena nuturkeun [[sebaran normal|normal]] (ilaharna disebut [[bell curve|kurva bel]]). Asumsi urang mindo nyokot sampe dina sampel nu diberekeun tina populasi sarta ngitung [[sample mean]] ([[arithmetic mean]] nilai data) keur unggal sampel. Sampel nu beda bakal mangaruhan kana bedana sampel means. Sebaran mean ieu nyaeta \"sebaran sampling tina sampel mean\" (keur ukuran sampel nu diberekeun). Sebaran ieu bakal jadi [[sebaran normal|normal]] saprak populasina normal. (Dumasar kana [[central limit theorem|teorema central limit]], lamun populasi teu normal tapi \"bentukna cukup hade\",\nsebaran sampling tina sampel mean bakal masih keneh cukup normal sanajan ukuran sampel kacida gedena).\n\nSimpangan baku tina sebaran sampling ngacu ka [[standar kasalahan (statistis)]] sarta di-estimasi make rumus:\n\n:\\frac{\\sigma}{\\sqrt{N}}\n\nnumana \\sigma mgarupakeun simpangan baku tina sebaran populasi sarta N nyaeta ukuran sampe (jumlah barang) dina sampel.\n\nHal nu penting dina rumus ieu nyaeta kudu ngalikeun opat kali ukuran sampel (4X) ngarah ukuran kasalahanna jadi (1/2). Waktu rarangkay elmu statistik numana biaya ngarupakeun faktor, ieu ngarupakeun faktor nu kudu dipikaharti ngeunaan pentingna biaya.\n\nAlternatipna, anggap [[median]] sampel tina populasi. Ieu ngabogaan sebaran sampling nu beda sacara umum teu normal (tapi masih keneh pakait dina aturan ka-normal-an).\n\n===Tempo oge===\n[[central limit theorem]], [[standard error (statistics)]]','',13,'Budhi','20040906005502','',0,0,0,0,0.999631121754,'20040906005613','79959093994497'); INSERT INTO cur VALUES (1477,0,'Scatterplot','A \'\'\'scatterplot\'\'\' or \'\'\'scatter graph\'\'\' is a [[graph]] used in [[statistik]] to visually display and compare two sets of related quantitative, or numerical, data by displaying only finitely many points, each having a coordinate on a horizontal and a vertical [[axis]].\n\nFor example, if a statistician were studying the effects of [[lung]] capacity on the ability to hold one\'s breath, he would choose a group of people to study, and he would test each one\'s lung capacity (first data set) and how long that person could hold their breath (second data set). Then he would set up a scatter plot, assigning \"lung capacity\" to the horizontal axis, and \"time holding breath\" to the vertical axis. A person with a lung capacity of 400 [[cm|cc]] who held their breath for 21.7 seconds would be represented by a single dot on the scatter plot at the point (400, 21.7) in [[Cartesian coordinates]]. The scatter plot of all the people in the study would enable the statistician to obtain a visual comparison of the two sets of data, and help him to determine what kind of relationship there might be between them.','',13,'Budhi','20050101221134','',0,0,0,0,0.733109450309,'20050101221134','79949898778865'); INSERT INTO cur VALUES (1478,0,'Selection_bias','\'\'\'Seleksi bias\'\'\' nyaeta distorsi kasalahan analisa [[statistik]] dina samemeh- atawa sanggeus-milih sampel. Typically this causes measures of [[statistical significance]] to appear much stronger than they are, but it is also possible to cause completely illusory artifacts. Selection bias can be the result of [[scientific fraud]] which manipulate data directly, but more often is either unconscious or due to biases in the instruments used for observation. For example, astronomical observations will typically find more blue galaxies than red ones simply because most instruments are more sensitive to blue light than red light.\n\nThere are many types of possible selection bias, including:\n\n\'\'\'Time:\'\'\'\n* Selecting end-points of a time series. For example, to maximise a claimed trend, you could start the time series at an unusually low year, and end on a high one.\n* Early termination of a trial at a time when its results seem particularly significant. (Typically couched in [[ethics|ethical]] terms.)\n\'\'\'Space:\'\'\'\n* Selecting spacial regions, including grid size or zero points (see [[stratified sampling]], [[cluster sampling]]). For example, to \"prove\" an association between cancer and a particular locality, you could adjust the size, orientation and alignment of grid cells until most of the local cancers fit in the same grid as the locality. Then round off the dimensions slightly (so they don\'t look quite so contrived), and compare cancer rates in various grid cells using the tests designed for [[random]]ly assigned grids.\n\'\'\'Data:\'\'\'\n* Rejection of \"bad\" data on arbitrary grounds, instead of according to previously stated or generally agreed criteria\n\'\'\'Participants:\'\'\'\n* Pre-screening of trial participants, or advertising for volunteers within particular groups. For example to \"prove\" that smoking doesn\'t affect fitness, advertise for both at the local fitness centre, but advertise for smokers during the advanced aerobics class, and for non-smokers during the weight loss sessions.\n* Discounting trial subjects/tests that did not run to completion. For example, in a test of a dieting program, the researcher may simply reject everyone who drops out of the trial. But most of those who drop out are those for whom it wasn\'t working.\n\'\'\'Studies:\'\'\'\n* Selection of which studies to include in a [[meta-analysis]]\n* Performing repeated experiments and reporting only the most favourable results. (Perhaps relabelling lab records of other experiments as \"calibration tests\", \"instrumentation errors\" or \"preliminary surveys\".)\n* Presenting the most significant result of a [[data dredge]] as if it was a single experiment. (Which is logically the same as the previous item, but curiously is seen as much less dishonest.)\n\nSelection bias is closely related to:\n* [[bias (statistics)|sample bias]], a selection bias produced by an accidental bias in the sampling technique, as against deliberate or unconscious manipulation.\n* [[publication bias]] or [[reporting bias]], the distortion produced in community perception or [[meta-analysis|meta-analyses]] by not publishing uninteresting (usually negative) results, or results which go against the experimenter\'s prejudices, a sponsor\'s interests, or community expectations.\n* [[confirmation bias]], the distortion produced by experiments that are designed to seek confirmatory evidence instead of trying to disprove the hypothesis.\n\n\n\'\'See also:\'\' [[bias (statistics)]]','',13,'Budhi','20041229232744','',0,0,1,0,0.25981377217,'20041229235349','79958770767255'); INSERT INTO cur VALUES (1479,0,'Effect_size','#REDIRECT [[Efek ukuran]]\n','Effect size dipindahkeun ka Efek ukuran',13,'Budhi','20040903091210','',0,1,0,1,0.455520539968759,'20040903091210','79959096908789'); INSERT INTO cur VALUES (1480,0,'Gamma_distribution','#REDIRECT [[Sebaran gamma]]\n','Gamma distribution dipindahkeun ka Sebaran gamma',13,'Budhi','20040903115239','',0,1,0,1,0.829282135543676,'20040903115239','79959096884760'); INSERT INTO cur VALUES (1481,0,'Gini_coefficient','#REDIRECT [[Koefisien Gini]]\n','Gini coefficient dipindahkeun ka Koefisien Gini',13,'Budhi','20040903214354','',0,1,0,1,0.779849088545748,'20040903214354','79959096785645'); INSERT INTO cur VALUES (1482,0,'G-test','Dina [[statistik]], \'\'\'tes-\'\'G\'\'\'\'\' nyaeta tes [[likelihood ratio test|rasio likelihood]] atawa [[maximum likelihood]] [[statistical significance]] nu loba dipake dina kaayaan [[tes chi-kuadrat]] samemehna disarankeun.\n\nThe commonly used chi-squared tests for goodness of fit to a distribution and for independence in [[contingency table]]s are in fact approximations of the [[log-likelihood ratio]] on which the G-tests are based. This approximation was developed by [[Karl Pearson]] because at the time it was unduly laborious to calculate log-likelihood ratios. With the advent of electronic calculators and personal computers, this is no longer a problem. \'\'G\'\'-tests are coming into increasing use, particularly since they were recommended in the 1994 edition of the popular statistics text book by Sokal and Rohlf. \n\nThe general formula for Pearson\'s chi-squared test statistic is\n
\n \\chi^2 = \\sum {(O - E)^2 \\over E}\n
\nwhere O is the frequency observed in a cell, E is the frequency expected on the null hypothesis, and the sum is taken across all cells. The corresponding general formula for \'\'G\'\' is \n
\n G = -2\\sum {O\\times \\ln(O/E) }\n
\nwhere ln denotes the [[natural logarithm]] (log to the base \'\'[[e (mathematical constant)|e]]\'\') and the sum is again taken over all cells.\n\nOn the null hypothesis that the observed frequencies result from random sampling from a distribution with the given expected frequencies, the [[distribution]] of \'\'G\'\' is approximately that of chi-squared, with the same number of [[degrees of freedom]] as in the corresponding chi-squared test.\n\nFor samples of a reasonable size, the \'\'G\'\'-test and the chi-squared test will lead to the same conclusions. However, the approximation to the theoretical chi-square distribution for the \'\'G\'\'-test is better than for the Pearson chi-squared tests in cases where for any cell |\'\'O\'\' − \'\'E\'\'| > \'\'E\'\', and in any such case the \'\'G\'\'-test should always be used.\n\nFor very small samples the [[binomial test]] for goodness of fit, and [[Fisher\'s exact test]] for contingency tables, are preferable to either the chi-squared test or the \'\'G\'\'-test.\n\n==References==\n*Sokal, R. R., & Rohlf, F. J. (1994). \'\'Biometry: the principles and practice of statistics in biological research.\'\', 3rd edition. New York: Freeman. ISBN 0-7167-2411-1.','',13,'Budhi','20041224205840','',0,0,1,0,0.763679058647,'20041224205840','79958775794159'); INSERT INTO cur VALUES (1483,0,'Latin_square','\'\'\'Latin square\'\'\' ngarupakeun tabel \'\'n\'\' × \'\'n\'\' nu dieusi ku \'\'n\'\' lambang nu beda dina sababaraha jalan mangka eta lambang pasti ngan aya sakali dina unggal baris jeung kolom.\n\n
\n\\begin{bmatrix}\n 1 & 2 & 3 \\\\\n 2 & 3 & 1 \\\\\n 3 & 1 & 2 \\\\\n\\end{bmatrix}\n\n\\begin{bmatrix}\n a & b & c \\\\\n b & c & a \\\\\n c & a & b \\\\\n\\end{bmatrix}\n
\n\nLatin squares salaku [[multiplication table]] dina [[quasigroup]], ilahar dipake dina [[desain percobaan]].\n\nNgaran Latin square asalna ti [[Leonard Euler]] nu ngagunakeun simbol ku hurup Latin.\n\n{{msg:stub}}\n\n==Tempo oge== \n* [[Graeco-Latin square]]\n\n[[Category:Mathematics]]\n\n[[de:Lateinisches Quadrat]]\n[[fr:Carré latin]]','',13,'Budhi','20040904013438','',0,0,0,0,0.481436804627,'20040904013438','79959095986561'); INSERT INTO cur VALUES (1484,0,'Latin_hypercube_sampling','Metoda [[statistik]] \'\'\'Latin hypercube sampling\'\'\' diwangun sarta dikumpulkeun ku [[Ronald L. Iman]], J. C. Helton, and J. E. Campbell, saparakanca keur nga-generate sebaran koleksi nu asup akal tina nilai paramater dina sebaran multidimensi.\n\nPaperna \'\'An approach to sensitivity analysis of computer models, Part I. Introduction, input variable selection and preliminary variable assessment.\'\' dina Journal of Quality Technology taun [[1981]].\n\n{{stub}}','',13,'Budhi','20040904134634','',0,0,0,0,0.954165543408,'20040904134634','79959095865365'); INSERT INTO cur VALUES (1485,0,'Law_of_large_numbers','In [[probability theory]], several \'\'\'laws of large numbers\'\'\' say that the average of a [[sequence]] of [[random variables]] with a common [[distribution]] [[convergence of random variables|converges]] (in the senses given below) to their common [[expectation]], in the [[limit]] as the size of the sequence goes to infinity. Various formulations of the law of large numbers, and their associated conditions, specify convergence in different ways. \n\nIn a [[statistics|statistical]] context, laws of large numbers imply that the [[average]] of a random sample from a large population is likely to be close to the [[mean]] of the whole population.\n\nWhen the random variables have a finite variance, the [[central limit theorem]] extends our understanding of the convergence of their average by describing the distribution of the standardised difference between the sum of the random variables and the expectation of this sum. Regardless of the underlying distribution of the random variables, this standardised difference [[convergence in distribution|converges in distribution]] to a [[Normal distribution#Standardizing normal random variables|standard normal random variable]].\n\n==The weak law==\n\nThe \'\'\'weak law of large numbers\'\'\' states that if \'\'X\'\'1, \'\'X\'\'2, \'\'X\'\'3, ... is an infinite [[sequence]] of [[random variable]]s, all of which have the same [[nilai ekspektasi]] μ and the same finite [[varian]] σ2, and they are [[uncorrelated]] (i.e., the [[correlation]] between any two of them is zero), then the sample average\n\n:\\overline{X}_n=(X_1+\\cdots+X_n)/n\n\n[[convergence of random variables|converges in probability]] to μ.\nSomewhat less tersely: For any positive number ε, no matter how small, we have\n\n:\\lim_{n\\rightarrow\\infty}\\operatorname{P}\\left(\\left|\\overline{X}_n-\\mu\\right|<\\varepsilon\\right)=1. \n\n[[Chebyshev\'s inequality]] is used to prove this result.\n\nA consequence of the weak law of large numbers is the [[asymptotic equipartition property]].\n\n==The strong law==\n\nThe \'\'\'strong law of large numbers\'\'\' states that if \'\'X\'\'1, \'\'X\'\'2, \'\'X\'\'3, ... is an infinite sequence of random variables that are [[Independent (probability)|independent]] and identically distributed with common expected value μ, and if  E(|\'\'X\'\'1|) < ∞, then\n\n:\\operatorname{P}\\left(\\lim_{n\\rightarrow\\infty}\\overline{X}_n=\\mu\\right)=1,\n\ni.e., the sample average [[convergence of random variables|converges almost surely]] to μ. \n\nIf we replace the finite expectation condition with a finite second moment condition,  E(\'\'X\'\'12) < ∞, then we obtain both almost sure convergence and [[convergence of random variables|convergence in mean square]]. In either case, these conditions also imply the consequent of the weak law of large numbers, since almost sure convergence implies convergence in probability (as, indeed, does convergence in mean square).\n\nThis law justifies the intuitive interpretation of the expected value of a random variable as the \"long-term average when sampling repeatedly\".\n\n==A weaker law and proof==\n\nProofs of the above weak and strong laws of large numbers are rather involved. The consequent of the slightly weaker form below is implied by the weak law above (since convergence in distribution is implied by convergence in probability), but has a simpler proof.\n\n
\n\'\'\'Theorem.\'\'\' Let \'\'X\'\'1, \'\'X\'\'2, \'\'X\'\'3, ... be a sequence of random variables, independent and identically distributed with common mean μ < ∞, and define the partial sum \'\'S\'\'\'\'n\'\' := \'\'X\'\'1 + \'\'X\'\'2 + ... +\'\'X\'\'\'\'n\'\'. Then,  \'\'S\'\'\'\'n\'\' / \'\'n\'\' converges in distribution to μ.\n
\n\n\'\'\'Proof.\'\'\' (See [[#References|[1]]], p. 174) By [[Taylor\'s theorem]] for [[complex function]]s, the [[characteristic function]] of any random variable, \'\'X\'\', with finite mean μ, can be written as\n\n:\\varphi(t) = 1 + it\\mu + o(t), \\quad t \\rightarrow 0.\n\nThen, since the characteristic function of the sum of random variables is the product of their characteristic functions, the characteristic function of  \'\'S\'\'\'\'n\'\' / \'\'n\'\'  is\n\n:\\left[\\varphi\\left({t \\over n}\\right)\\right]^n = \\left[1 + i\\mu{t \\over n} + o\\left({t \\over n}\\right)\\right]^n \\, \\rightarrow \\, e^{it\\mu}, \\quad \\textrm{as} \\quad n \\rightarrow \\infty.\n\nThe limit  \'\'e\'\'\'\'it\'\'μ  is the characteristic function of the constant random variable μ, and hence by the [[Lévy continuity theorem]],  \'\'S\'\'\'\'n\'\' / \'\'n\'\' converges in distribution to μ. Note that the [[central limit theorem#proof of the central limit theorem|proof of the central limit theorem]], which tells us more about the convergence of the average to μ (when the variance σ 2 is finite), follows a very similar approach.\n\n==References==\n\n#G.R. Grimmett and D.R. Stirzaker (1992). \'\'Probability and Random Processes\'\' 2nd Edition. Clarendon Press, Oxford.\n\n[[de:Gesetz der großen Zahlen]] [[pl:Prawo wielkich liczb]]','/* The weak law */',13,'Budhi','20040917032804','',0,0,0,0,0.142440631586,'20041225232059','79959082967195'); INSERT INTO cur VALUES (1486,0,'Learning_theory_(statistics)','Dina [[statistik]], \'\'\'learning theory\'\'\' is a mathematical field related to the analysis of [[machine learning]] algorithms. \n\nMachine learning algorithms take a training set, form hypotheses or models, and make predictions about the future. Because the training set is finite and the future is uncertain, learning theory usually does not yield absolute guarantees of performance of the algorithms. Instead, probabilistic bounds on the performance of machine learning algorithms are quite common. \n\nIn addition to performance bounds, learning theorists study the time complexity and feasibility of learning. In learning theory, a computation is considered feasible if it can be done in polynomial time. There are two kinds of time complexity results:\n#Positive results --- Showing the a certain class of function is learnable in polynomial time.\n# Negative results - Showing that certain classes cannot be learned in polynomial time.\nNegative results are proven only by assumption. The assumptions the are common in negative results are:\n* Computational complexity - [[Complexity classes P and NP|P]]\\neq[[Complexity classes P and NP|NP]]\n* [[cryptography|Cryptographic]] - [[One-way function]]s exist.\n\nThere are several difference branches of learning theory, which are often mathematically incompatible. This incompatibility arises from using different [[inference]] principles: principles which tell you how to generalize from limited data.\n\nExamples of different branches of learning theory include:\n* [[Probably approximately correct learning]] (PAC learning), proposed by [[Leslie Valiant]];\n* [[Statistical learning theory]], proposed by [[Vladimir Vapnik]];\n* [[Bayesian inference]], arising from work first done by [[Thomas Bayes]].\n* [[Algorithmic learning theory]], from the work of E. M. Gold.\n\nLearning theory has led to practical algorithms. For example, PAC theory inspired [[boosting]], statistical learning theory led to [[support vector machine]]s, and Bayesian inference led to [[belief networks]] (by [[Judea Pearl]]).\n\n\'\'See also:\'\'\n* [[information theory]]\n\n== References ==\n===Surveys===\n* Angluin, D. 1992. Computational learning theory: Survey and selected bibliography. In Proceedings of the Twenty-Fourth Annual ACM Symposium on Theory of Computing (May 1992), pp. 351--369. \n* D. Haussler. Probably approximately correct learning. In AAAI-90 Proceedings of the Eight National Conference on Artificial Intelligence, Boston, MA, pages 1101--1108. American Association for Artificial Intelligence, 1990. http://citeseer.nj.nec.com/haussler90probably.html\n===[[VC dimension]]===\n* V. Vapnik and A. Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications, 16(2):264--280, 1971. \n===Feature selection===\n* A. Dhagat and L. Hellerstein. PAC learning with irrelevant attributes. In Proceedings of the IEEE Symp. on Foundation of Computer Science, 1994. To appear. http://citeseer.nj.nec.com/dhagat94pac.html\n===Inductive inference===\n* E. M. Gold. Language identification in the limit. Information and Control, 10:447--474, 1967. \n===Optimal O notation learning===\n* O. Goldreich, D. Ron. On universal learning algorithms. http://citeseer.nj.nec.com/69804.html\n===Negative results===\n* M. Kearns and L. G. Valiant. 1989. Cryptographic limitations on learning boolean formulae and finite automata. In Proceedings of the 21st Annual ACM Symposium on Theory of Computing, pages 433--444, New York. ACM. http://citeseer.ist.psu.edu/kearns89cryptographic.html\n===[[Boosting]]===\n* Robert E. Schapire. The strength of weak learnability. Machine Learning, 5(2):197--227, 1990 http://citeseer.nj.nec.com/schapire90strength.html\n===[[Occam\'s Razor]]===\n* Blumer, A.; Ehrenfeucht, A.; Haussler, D.; Warmuth, M. K. \"Occam\'s razor\" Inf.Proc.Lett. 24, 377-380, 1987.\n* A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. Learnability and the Vapnik-Chervonenkis dimension. Journal of the ACM, 36(4):929--865, 1989.\n===[[Probably approximately correct learning]]===\n* L. Valiant. A Theory of the Learnable. Communications of the ACM, 27(11):1134--1142, 1984.\n===Error tolerance===\n* Michael Kearns and Ming Li. Learning in the presence of malicious errors. SIAM Journal on Computing, 22(4):807--837, August 1993. http://citeseer.nj.nec.com/kearns93learning.html\n* Kearns, M. (1993). Efficient noise-tolerant learning from statistical queries. In Proceedings of the Twenty-Fifth Annual ACM Symposium on Theory of Computing, pages 392--401. http://citeseer.nj.nec.com/kearns93efficient.html \n===Equivalence===\n* D.Haussler, M.Kearns, N.Littlestone and M.Warmuth, Equivalence of models for polynomial learnability, Proc. 1st ACM Workshop on Computational Learning Theory, (1988) 42-55. \n* L. Pitt and M. K. Warmuth: Prediction preserving reduction, Journal of Computer System and Science 41, 430--467, 1990.\n\nA description of some of these publictions is given at [[List of important publications in computer science#Machine Learning| Important publications in machine learning]].\n\n== External Links ==\n* [http://www.inference.phy.cam.ac.uk/mackay/itila/ On-line book: Information Theory, Inference, and Learning Algorithms], by [[David MacKay]], gives a detailed account of the Bayesian approach to machine learning.\n* [http://www.santafe.edu/~shalizi/reviews/kearns-vazirani/ Review of \'\'An Introduction to Computational Learning Theory\'\']\n* [http://www.santafe.edu/~shalizi/reviews/vapnik-nature/ Review of \'\'The Nature of Statistical Learning Theory\'\']\n* [http://research.microsoft.com/adapt/MSBNx/msbnx/Basics_of_Bayesian_Inference.htm Basics of Bayesian inference]\n\n[[Category:Machine learning]]','',13,'Budhi','20041224224822','',0,0,1,0,0.139162514889,'20041224224822','79958775775177'); INSERT INTO cur VALUES (1487,0,'Téoréma_Lehmann-Scheffé','Dina [[statistik]], \'\'\'téoréma Lehmann-Scheffé\'\'\' netepkeun yen unggal estimator anu [[completeness (statistics)|lengkep]], [[sufficiency (statistics)|cukup]], sarta [[bias (statistics)|teu bias]] ngarupakeun estimator teu bias nu \'\'unik\'\' tina [[nilai ekspektasi]]-na.\n\nCara nu ilahar dipake keur neangan nilai estimator nyaeta migunakeun [[téoréma Rao-Blackwell]].\n\n\n{{pondok}}\n\n[[en:Lehmann-Scheffé theorem]]\n[[Category:Statistik]]','',13,'Budhi','20041225233030','',0,0,0,0,0.961397909076,'20050303211247','79958774766969'); INSERT INTO cur VALUES (1488,0,'Level_of_measurement','\'\'\'Tingkat [[measurement|ukuran]]\'\'\' [[variable|variabel]] dina [[matematik]] sarta [[statistik]] describes how much information the numbers associated with the variable contain. Different mathematical operations on variables are possible, depending on the level at which a variable is measured. In statistics, the kinds of [[descriptive statistics]] and [[significance test]]s that are appropriate depend on the level of measurement of the variables concerned.\n\nFour levels of measurement are usually recognised:\n*\'\'\'Nominal measurement\'\'\'. The numbers are names or labels. They can and often are replaced by verbal names. If two entities have the same number associated with them, they belong to the same category, and that is the only significance that they have. The only comparisons that can be made between variable values are equality and inequality. There are no \"less than\" or \"greater than\" relations among them, nor operations such as addition or subtraction. Examples include: the international telephone code for a country, the numbers on the shirts of players in a sports team, or the number of a bus. The only kind of measure of [[central tendency]] is the mode. [[Information entropy]] is available as a measure of [[statistical dispersion]], but no notion of [[standard deviation]] or the like exists. Variables that are measured only nominally are also called \'\'\'categorical variables\'\'\'.\n*\'\'\'Ordinal measurement\'\'\'. The numbers have all the features of nominal measures and also represent the rank order (1st, 2nd, 3rd etc) of the entities measured. The numbers are [[ordinal]]s. Comparisons of greater and less can be made, in addition to equality and inequality. However operations such as conventional addition and subtraction are still without meaning. A physical example is the [[Mohs scale of mineral hardness]]. Another example is the results of a horse race; which horses arrived first, second, third, etc. are reported, but the time intervals between the horses are not reported. Most measurement in [[psychology]] and other [[social science]]s is at the ordinal level; for example [[attitude (psychology)|attitude]]s and [[IQ]] are only measured at the ordinal level. If customers surveyed report preferring chocolate- to vanilla-flavored ice cream, the data are of this kind. The [[central tendency]] of a distribution an ordinally measured variable can be represented by its mode or its [[median]]; the latter will give more information. Variables measured at the ordinal level are referred to as ordinal variables or \'\'\'rank variables\'\'\'.\n*\'\'\'Interval measurement\'\'\'. The numbers have all the features of ordinal measurement and also are separated by the same interval. In this case, differences between arbitrary pairs of numbers can be meaningfully compared. Operations such as addition and subtraction are therefore meaningful. However, the zero point on the scale is arbitrary, and ratios between numbers on the scale are not meaningful, so operations such as multiplication and division cannot be carried out. On the other hand, negative values on the scale can be used. An example is the year date in many calendars. The central tendency of a distribution an variable measured at the interval level can be represented by its mode, its [[median]] or its [[arithmetic mean]]; the mean will give most information. Variables measured at the interval level are referred to as interval variables, or sometimes as scaled variables, though the latter usage is not obvious and is not recommended.\n*\'\'\'Ratio measurement\'\'\'. The numbers have all the features of interval measurement and also have meaninful ratios between arbitrary pairs of numbers. Operations such as multiplication and division are therefore meaningful. The zero value on a ratio scale is non-arbtrary. Most physical quantities, such as [[mass]], [[length]] or [[energy]] are measured on ratio scales; so is temperature when it is measured in [[kelvin]]s, i.e. relative to [[absolute zero]]. The central tendency of a distribution an variable measured at the interval level can be represented by its mode, its [[median]], its [[arithmetic mean]], or its [[geometric mean]]; however as with an interval scale, the arithmetic mean will give the most useful information. Variables measured at the interval level are referred to as ratio variables.\n\nInterval and/or ratio measurement are sometimes referred to as \"true measurement\", though this usage reflects a lack of understanding of the uses of ordinal measurement. However, it is only quantities measured on ratio scales that can correctly be said to have [[unit]]s of measurement.','',13,'Budhi','20050101221324','',0,0,0,0,0.851396843256,'20050101221324','79949898778675'); INSERT INTO cur VALUES (1489,0,'Lies,_damned_lies,_and_statistics','This well-known saying is part of a phrase attributed to [[Benjamin Disraeli]] and popularized in the U.S. by [[Mark Twain]]: \'\'There are three kinds of lies: \'\'\'lies, damned lies, and statistics\'\'\'.\'\' \n\nThe semi-ironic statement refers to the persuasive power of numbers, and succinctly describes how statistics, even accurate ones, can be used to bolster an inaccurate argument through such methods as selectively choosing data, ignoring bad results and over-emphasizing good results.\n\nThere is some doubt as to whether Disraeli actually coined the statement. Only Twain\'s autobiography backs this assertion; alternative attributions include the radical journalist and politician Henry Labouchère (1831-1912).\n\nThis topic has received many popular expositions, notably the [[1954]] book \'\'How to Lie with Statistics\'\' by Darrell Huff, which is still in print a half-century after it was written.','',13,'Budhi','20040903215624','',0,0,0,1,0.28722148402,'20040903215624','79959096784375'); INSERT INTO cur VALUES (1490,0,'Life_expectancy','In [[demography]], \'\'\'life expectancy\'\'\' is a [[statistical]] measure of the average, or mathematical [[nilai ekspektasi]], of the remaining lifetime of an individual in the given group. For non-human [[organism]]s the term \'\'\'lifespan\'\'\' is often used to indicate the average length of life in a given [[species]].\n\nNotice that the life expectancy is heavily dependent on the criteria used to select the group. In countries with high [[infant mortality]] rates, the life expectancy at birth is highly sensitive to the rate of death in the first few years of life. In these cases, another measure such as life expectancy at age 10 can be used to exclude the effects of infant mortality to reveal the effects of other causes of death. Usually, though, life expectancy at birth is specified. To calculate it, it is assumed that current mortality levels remain constant throughout the lives of the hypothetical newborns.\n\n==Life expectancy over human history==\n\nLife expectancy has dramatically increased over the last few centuries of human history. These changes are largely the result of improvements in public health, medicine and nutrition. The greatest improvements have been made in the richest parts of the world, but the same effects are now spreading to other parts of the world as their economies and infrastructure improve.\n\nBasic life expectancy numbers tend to exaggerate this growth, however. The low level of pre-modern life expectancy is distorted by the previous extremely high [[infant mortality|infant]] and childhood mortality. If a person did make it to the age of forty they had an average of another twenty years to live. Improvements in medicine, public health and nutrition have therefore mainly increased the numbers of people living beyond childhood, with less effect on overall average lifespan.\n\nThese improvements continue to confound the predictions of [[Thomas Malthus]], who predicted what is now known as the [[Malthusian catastrophe]] which would occur when population growth exceeded the capacity of the world to sustain that population. \n\nThe major exception to this general pattern of improvement has been in those countries worst hit by [[AIDS]], principally in Sub-Saharan Africa, which have seen significant falls in life expectancy due to the disease in recent years.\n\nAnother exception is [[Russia]] and other former USSR republics after the [[collapse of the Soviet Union]]. Life expectancy of men dropped to 59.9 years (below the official retirement age), of women to 72.43 years (1999).\n\nIn recent years, [[obesity]]-correlated diseases have become a major public health issue in many countries. The prevalence of obesity is thought to have reduced a potential for longer life expectancy by contributing to the rise of cancers, heart disease and diabetes in the developed world.\n\nThroughout human history most of the increase in life expectancy arose from preventing early deaths. However, many scientists believe this will not stay true in the future, as it will be possible to revert aging. According to [[Leroy Hood]], the life expectancy in the next three decades will increase by 10-20 years thanks to advances in [[DNA sequencing]] and [[nanotechnology]]. Some scientists believe that further advances in medical science may push life expectancy even further, effectively making humans [[immortality|immortal]].\n\nSee also:\n* [[Life expectancy in the 20th century]]\n\n==Variations in life expectancy in the world today==\n\nThere are great variations in life expectancy worldwide, mostly caused by differences in public health, medicine and nutrition from country to country. \n\nThere are also variations between groups within single countries. For example, in the US in the early 20th century there were very large differences in life expectancy between people of different races, which have since lessened. There remain significant differences in life expectancy between men and women in the US and other developed countries, with women outliving men. These differences by sex have been reducing in recent years, with men\'s life expectancy improving at a faster rate than women\'s.\n\nThe damaging effects of habits such as [[tobacco smoking]] and other addictions also make a significant difference to life expectancy.\n\n==See also==\n* [[morbidity]]\n* [[mortality]]\n* [[demography]] (Population studies)\n* [[economics]]\n* [[Longevity]]\n* [[Age-adjusted life expectancy]]\n\n==External links==\n* [http://www.cdc.gov/nchs/fastats/lifexpec.htm CDC year-by-year life expectancy figures for USA]\n* [http://www.worldpolicy.org/globalrights/econrights/maps-life.html Map of life expectancy around the world]\n* [http://www.utexas.edu/depts/classics/documents/Life.html Life expectancy in Roman times]\n* [http://www.ac.wwu.edu/~stephan/Animation/expectancy.html The changing influence of sex and race on life expectancy in the US]\n\n[[de:Lebenserwartung]] \n[[fr:Espérance de vie]]\n[[he:תוחלת חיים]]\n[[ja:平均余命]]','',13,'Budhi','20040917032920','',0,0,0,0,0.753395029229,'20050103081414','79959082967079'); INSERT INTO cur VALUES (1491,0,'Model_linier','Dina [[statistik]] \'\'\'model linier\'\'\' bisa ditembongkeun ku nyebutkeun\n\n* Y = X \\beta + \\epsilon\n\ndimana Y ngarupakeun nx1 vektor kolom variabel random, X ngarupakeun matrik kuantitas nxp \"dipikanyaho\" (contona, bisa di-observasi sarta non-random), vektor baris pakait jeung [[statistical unit]], β ngarupakeun px1 vektor parameter (teu ka-observasi), sarta ε ngarupakeun nx1 vektor \"error\", nu teu pakait ka variabel random nu mibanda nilai ekspektasi 0 sarta varian σ2. Salawasna komponen vektor kasalahan nu dicokot bakal [[statistical independence|independent]] sarta [[sebaran normal|kasebar normal]]. Anggap nilai X sarta Y ka observasi, statistikawan kudu nga-estimate β sarta σ2. Sacara tipikal parameter β di-estimasi make metoda [[least squares]].\n\nTinimbang nyokot varian ε jadi σ2I, numana I ngarupakeun nxn matrik identitas, anggap varian ngarupakeun σ2M,\nnumana M ngarupakeun matrik sejen nu dipikanyaho salian ti matrik identitas, mangka estimate β make metoda \"generalized least squares\", numana, ku ngaminimalkeun kuadrat residu, minimalkeun bentuk beda kuadrat dina residu -- bentuk kuadrat diberekeun ku matrik M-1.\nLamun sakabeh diagonal dina matrik M sarua jeung 0, mangka estimasi normal β ku metoda \"weighted least squares\", nu mibanda beurat sarua jeung diagonal asupan.\n\n[[Linear regression]] ordiner ngarupakeun topik nu raket pakait.\n\n== Generalisasi ==\n\n=== Generalisasi model linier ===\n\n[[Generalized linear model]]s, tinimbang \n* E(Y)=Xβ,\nleuwih ilahar\n*f(E(Y))=Xβ,\ndimana f ngarupakeun \"fungsi pakait\". Contona \"model regresi Poisson\", ku nuliskeun \n*Yi ngabogaan sebaran Poisson nu mibanda nilai ekspektasi eγ+δxi.\nFungsi pakait ngarupakeun fungsi logaritma natural.\nObservasi nu dipiboga xi sarta Yi keur\ni=1,...,n, bisa nga-estimasi γ and δ ku metoda [[maximum likelihood]].\n\n=== Model linier general ===\n\n[[General linear model]] (atawa [[multivariate regression model]]) ngarupakeun model linier nu mibanda sababara ukuran dina unggal obyek.\nUnggal obyek diwakilan dina bentuk vektor.','',13,'Budhi','20040904011142','',0,0,0,0,0.780963533456,'20040904070038','79959095988857'); INSERT INTO cur VALUES (1492,0,'Prediksi_linier','\'\'\'Prediksi linier\'\'\' ngarupakeun operasi matematik dimana nilai kahareup tina [[digital]] [[signal]] ngarupakeun estimasi salaku [[linear transformation|fungsi linier]] sampel samemehna.\n\nDina [[digital signal processing]] prediksi linier ilahar disebut [[linear predictive coding]] (LPC) sarta bisa ditembongkeun salaku sub susunan [[filter theory]]. Dina [[system analysis]] (sub bagean [[matematik]]), prediksi linier bisa ditempo salaku bagian [[mathematical model|mathematical modelling]] atawa [[optimization]].\n\n== Model prediksi ==\n\nNu ilahar digambarkeun nyaeta\n\n:x\'(n) = \\sum_{i=1}^p a_i x(n-i)\n\nnumana \'\'x\'\'\'\'n\'\'′ ngarupakeun nilai prediksi tanda, \'\'x\'\'\'\'n\'\'−\'\'i\'\' nilai samemehna, sarta \'\'a\'\'\'\'i\'\' koefisien prediktor. Generat kasalahan ku estimasi ieu nyaeta\n\n:e(n) = x(n) - x\'(n)\n\nnumana \'\'x\'\'\'\'n\'\' ngarupakeun nilai tanda sabenerna.\n\nPersamaan ieu valid keur sakabeh tipe (hiji-dimensi) prediksi linier. Bedana kapanggih dina jalan parameter \'\'a\'\'\'\'i\'\' nu dipilih.\n\nKeur tanda multi-dimensi kasalahan biasana dihartikeun ku \n\n:e(n) = ||x(n) - x\'(n)||\n\nnumana ||.|| ngarupakeun vektor [[norm]] pilihan nu cocok.\n\n== Estimasi parameter ==\n\nNu ilahar dina optimasi parameter a_i nyaeta kriteri [[root mean square]] numana disebut oge kriteria [[autocorrelation]]. Dina metoda ieu ngaminimalkeun nilai ekspektasi tina kuadrat kasalahan E(e2\'\'n\'\', ngahasilkeun persamaan\n\n:\\sum_{i=1}^p a_i R(i-j) = -R(j),\n\nkeur 1 ≤ \'\'j\'\' ≤ \'\'p\'\', dimana \'\'R\'\' ngarupakeun tanda [[autocorrelation]] \'\'x\'\'\'\'n\'\', diartikeun salaku\n\n:R(i) = E\\{x(n)x(n-i)\\}\n\nDina kasus multi-dimensi pakait jeung ngaminimalkeun norma L2.\n\nPersamaan di luhur disebut persamaan normal atawa Yule-Walker. Dina bentuk matriks bisa sarua jeung \n\n:Ra = r,\n\nnumana matrix autokorelasi \'\'R\'\' ngarupakeun [[Toeplitz matrix]] nu mibanda elemen \'\'r\'\'\'\'i\'\',\'\'j\'\' = \'\'R\'\'(\'\'i\'\' − \'\'j\'\'), vektor \'\'r\'\' ngarupakeun vektor autokorelasi \'\'r\'\'j = \'\'R\'\'(\'\'j\'\'), sarta vektor \'\'a\'\' ngarupakeun vektor parameter.\n\nPendekatan nu leuwih umum nyaeta ngaminimalkeun\n\n:e(n) = \\sum_{i=0}^p a_i x(n-i)\n\nnumana umumna parameter konstrain a_i mibanda a_0=1 keur manggihkeun solusi trivial. Konstrain ieu ngahasilkeun prediktor nu sarua jeung di luhur ngan persamaan normal, mangka \n\n:Ra = [1, 0, ... , 0]^T\n\nnumana indeks \'\'i\'\' antara 0 ka \'\'p\'\' sarta ukuran \'\'R\'\' nyaeta matriks (\'\'p\'\'+1) × (\'\'p\'\'+1).\n\nOptimasi parameter ngarupakeun topik luas sarta angka nu gede ngarupakeun pendeketan sejen nu diusulkeun.\n\nMetoda autokorelasi leuwih ilahar sarta biasa digunakeun, contona, keur [[speech coding]] dina standar [[GSM]].\n\nSolusi persamaan matriks \'\'Ra\'\' = \'\'r\'\' ngarupakeun proses komputasi nu lumayan mahal. [[Gauss algorithm]] keur invers matrik bisa jadi ngarupakeun solusi heubeul tapi pendekatan ieu teu epektip dipake dina simetri \'\'R\'\' jeung \'\'r\'\'. Algoritma panggancangna ti [[Levinson recursion]] diusulkeun ku N. Levinson taun 1947, nu ngarupakeun solusi perhitungan bolak-balik. Pangahirna, Delsarte saparakanca ngusulkeun metoda algoritma sejen nyaeta [[split Levinson recursion]] nu merlukeun satengah jumlah perkalian jeung pembagian. Ieu dipake keur sipat simetri vektor parameter diana tingkatan sub perhitungan.\n\n==Tempo oge==\n\n[[prediction interval]].','',13,'Budhi','20040905043531','',0,0,0,0,0.341130715488,'20040905043531','79959094956468'); INSERT INTO cur VALUES (1493,0,'Parameter_lokasi','Dina [[statistik]], lamun kulawarga densiti sebaran diparameterisasi ku parameter nilai -skalar atawa -vektor μ ngarupakeun bentuk \n\n:\'\'f\'\'μ(\'\'x\'\') = \'\'f\'\'(\'\'x\'\' − μ)\n\nmangka μ disebut \'\'\'parameter lokasi\'\'\', sabab ieu nilai nangtukeun \"lokasi\" tina sebaran probabiliti.\n\n==Tempo oge==\n* [[numerical parameter]]\n* [[statistical dispersion]]\n* [[scale parameter]]','',13,'Budhi','20040905064631','',0,0,0,0,0.346177211193,'20040905064702','79959094935368'); INSERT INTO cur VALUES (1494,0,'Logit','The \'\'\'logit\'\'\' (pronounced with a long \"o\" and a soft \"g\") of a number \'\'p\'\' between 0 and 1 is\n\n:{\\rm logit}(p)=\\log\\left( \\frac{p}{1-p} \\right) =\\log(p)-\\log(1-p).\n\n[[Image:Logit.png|thumbnail|right|Plot of logit in the range 0 to 1, base is e]]\n\n(The base of the [[logarithm]] function used here is of little importance in the present article, as long as it is greater than 1.) The logit function is the inverse of the [[logistic curve|\"sigmoid\", or \"logistic\" function]].\nIf \'\'p\'\' is a probability then \'\'p\'\'/(1 − \'\'p\'\') is the corresponding [[odds]], and the logit of the probability is the logarithm of the odds; similarly the difference between the logits of two probabilities is the logarithm of the [[odds ratio|odds-ratio]], thus providing an additive mechanism for combining odds-ratios.\n\nLogits are used for various purposes by statisticians. In particular there is the \"logit model\" of which the simplest sort is\n:{\\rm logit}(p_i)=a+bx_i\nwhere \'\'xi\'\' is some quantity on which success or failure in the \'\'i\'\'th in a sequence of [[Bernoulli trial]]s may depend, and \'\'pi\'\' is the probability of success in the \'\'i\'\'th case. For example, \'\'x\'\' may be the age of a patient admitted to a hospital with a heart attack, and \"success\" may be the event that the patient dies before leaving the hospital (another instance of the reason why the words \"success\" and \"failure\" in speaking of Bernoulli trials should be taken with large doses of salt). Having observed the values of \'\'x\'\' in a sequence of cases and whether there was a \"success\" or a \"failure\" in each such case, a statistician will often estimate the values of the coefficients \'\'a\'\' and \'\'b\'\' by the method of [[maximum likelihood]]. The result can then be used to assess the probability of \"success\" in a subsequent case in which the value of \'\'x\'\' is known. Estimation and prediction by this method are called \'\'\'logistic regression\'\'\'.\n\nA logistic regression model is identical to a [[neural network]] with no hidden units.\nFor a neural network hidden units, \neach hidden unit computes a logistic regression (different for each hidden unit), \nand the output is therefore a weighted sum of logistic regression outputs.\n\nThe \'\'\'logit\'\'\' in logistic regression is a special case of a [[link function]] in [[generalized linear model]]s. Another example is the [[probit]] model, which is more concerned with the tails of the response curve.\n\nThe logit model was introduced by [[Joseph Berkson]] in [[1944]], who coined the term. [[G. A. Barnard]] in [[1949]] coined the commonly used term \'\'log-odds\'\'; the log-odds of an event is the logit of the probability of the event.\n\n== Tempo ogé ==\n* [[Daniel McFadden]], winner of the [[Nobel Prize in Economics]] for development of a particular logit model used in economics\n* [[Logit analysis (in marketing)|Logit analysis in marketing]]\n\n[[Category:Statistics]]','/* See also */',13,'Budhi','20050101221435','',0,0,0,0,0.934626708242,'20050101221435','79949898778564'); INSERT INTO cur VALUES (1495,0,'Kurva_Lorenz','Kurva Lorenz diwangun ku [[Max O. Lorenz]] salaku grapik nu ngagambarkeun kateusaruaan [[income]]. Kurva bisa dipake oge keur ngukur kateusaruaan [[asset]] atawa [[distribution]] sejenna.\n\nDina diskusi panghasilan pribadi, urang remen nyebutkeun yen, \"duapuluh persen sahandapeun sakabeh rumahtangga mibanda sapuluh persen total panghasilan\". Kurva Lorenz dumasar kana ieu \'\'pernyataan\'\'; unggal titik dina kurva ngagambarkeun unggal \'\'pernyataan\'\'.\n\n[[curve]] Lorenz ngarupakeun [[graph of a function|graph]] nu nembongkeun, di handap x% rumahtangga, persentase y% total panghasilan no dipibanda. Persentase rumah tangga di plot dina sumbu x, persentasi panghasilan dina sumbu y. \n\nSebaran panghasilan persis sarua di masarakat bakal jadi hiji dimana unggal jalma mibanda panghasilan nu sarua. Dina kasus ieu, handapeun N% masarakat bakal salawasna mibanda N% panghasilan. Mangka sebaran nu persis sarua digambarkeun ku garis lempeng y=x; bisa disebut yen ieu garis ngarupakeun garis persis sarua.\n\nSebaran nu persis teusarua, sacara jelas, nyaeta saurang boga kabeg penghasilan sarta nu sejenna teu boga nanaon. Dina kasus eta, kurva bakal dina y=0 keur sakabrh x<100, sarta y=100 waktu x=100. Garis dina kurva ieu disebut garis kateusaruaan sampurna.\n\nCatetan yen dumasar kana panghasilan (atawa naon bae nu bakal diukur) teu bisa negatip, mangka teu mungkin keur kurva Lorenz naek di saluhureun garis sarua sampurna, atawa nurun sahandapeun garis teusarua sampurna. Kurva kudu naek sarta [[concave]].\n\nKurva Lorenz dipeke keur ngitung [[koefisien Gini]], numana daerah antara garis sampurna jeung kurva, salaku persentasi daerah antara garis sarua sampurna jeung garis teu sarua sampurna. \n\nTipikal kurva Lorenz bisa ditempo di handap ieu:\n\n[[image:lorenz-curve1.png]]\n\n==See also==\n* [[Welfare economics]]\n* [[Income inequality metrics]]\n* [[Koefisien Gini]]\n* [[Social welfare (political science)]]\n* [[ROC analysis]]','',13,'Budhi','20040903223816','',0,0,0,0,0.538291272958,'20040903223845','79959096776183'); INSERT INTO cur VALUES (1496,0,'Loss_function','Dina [[statistik]], [[decision theory]] sarta [[ékonomi]], a \'\'\'loss function\'\'\' is a function that maps an [[event (probability theory)|event]] (technically an element of a [[sample space]]) onto a [[real number]] representing the economic cost or regret associated with the event.\n\n\'\'Loss functions\'\' are typically expressed in monetary terms though other measures of cost are possible, for example mortality or morbidity in the field of [[public health]].\n\n\'\'Loss functions\'\' are complementary to [[utility|utility functions]] which represent benefit and satisfaction. Typically, for [[utility]] \'\'U\'\', loss is equal to \'\'k\'\'-\'\'U\'\', where \'\'k\'\' is some arbitrary constant.\n\n==Expected loss==\n\n\'\'Loss function\'\' satisfies the definition of a [[random variable]] so we can establish a [[cumulative distribution function]] and an [[nilai ekspektasi]]. However, more commonly, the \'\'loss function\'\' is expressed as a function of some other [[random variable]]. For example, the time that a light bulb operates before failure is a [[random variable]] and we can specify the loss, arising from having to cope in the dark and/or replace the bulb, as a function of failure time. For a continuous [[random variable]], \'\'X\'\' with [[probability density function]] \'\'f\'\'(\'\'x\'\') and \'\'loss function\'\', λ(\'\'x\'\'), the \'\'expected loss\'\' is:\n\n:\\Lambda = \\int_{-\\infty}^\\infty \\lambda (x) f(x) dx.\n\nMinimum \'\'expected loss\'\' is widely used as a criterion for choosing between prospects. It is closely related to the criterion of maximum \'\'expected utility\'\'.\n\n==Loss functions in Bayesian statistics==\n\nOne of the consequences of [[Bayesian inference]] is that in addition to experimental data, the loss function does not in itself wholly determine a decision. What is important is the relationship between the loss function and the [[prior probability]]. So it is possible to have two different loss functions which lead to the same decision when the prior [[probability distribution]]s associated with each compensate for the details of each loss function.\n\nCombining the three elements of the prior probability, the data, and the loss function then allows decisions to be based on maximising the [[subjective expected utility]], a concept introduced by [[Leonard J. Savage]]. He also argued that using non-Bayesian methods such as [[minimax]], the loss function should be based on the idea of regret, i.e. the loss associated with a decision should be the difference between the consequences of the best decision that could have been taken had the underlying circumstances been known and the decision that was in fact taken before they were known.','',13,'Budhi','20040917062912','',0,0,0,0,0.989369635465,'20040917062912','79959082937087'); INSERT INTO cur VALUES (1497,6,'Lorenz-curve1.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040903220613','',0,0,0,1,0.411399066831357,'20040903223816','79959096779386'); INSERT INTO cur VALUES (1498,0,'Lorenz_curve','#REDIRECT [[Kurva Lorenz]]\n','Lorenz curve dipindahkeun ka Kurva Lorenz',13,'Budhi','20040903223845','',0,1,0,1,0.717448099253185,'20040903223845','79959096776154'); INSERT INTO cur VALUES (1499,0,'Design_of_experiments','#REDIRECT [[Desain percoban]]\n','Design of experiments dipindahkeun ka Desain percoban',13,'Budhi','20040903225422','',0,1,0,1,0.3530433265055,'20040903225422','79959096774577'); INSERT INTO cur VALUES (1500,0,'Desain_percoban','#REDIRECT [[Desain percobaan]]\n','Desain percoban dipindahkeun ka Desain percobaan',13,'Budhi','20040903225456','',0,1,0,1,0.61287236550159,'20040903225456','79959096774543'); INSERT INTO cur VALUES (1501,0,'Linear_model','#REDIRECT [[Model linier]]\n','Linear model dipindahkeun ka Model linier',13,'Budhi','20040904011217','',0,1,0,1,0.00523187872509647,'20040904011217','79959095988782'); INSERT INTO cur VALUES (1502,0,'Hukum_Zipf-Mandelbrot','\'\'\'Hukum Zipf-Mandelbrot\'\'\' (oge dipikanyaho salaku hukum [[Pareto]]-Zipf) \nnyaeta [[power-law]] [[distribution]] dina [[ranked data]], dipake sanggeus [[Harvard]] [[linguistic]] [[professor]] [[George Kingsley Zipf]] ([[1902]]-[[1950]]) \nnu ngusulkeun dina teks [[regularity]], sarta [[mathematician]] [[Benoit Mandelbrot]] (lahir [[November 20]], [[1924]]), no nga-generalisir.\n\n[[Distribution]] kecap dirangking ku [[frequency]]-na dina [[random]]\n[[corpus]] [[text]] ngarupakeun [[power-law]] [[distribution]] umum, dipikanyaho salaku [[Zipf\'s law]].\n\nLamun hiji plot rangking [[frequency]] kecap dikandung dina \n[[corpus]] nu gede tina data teks ka jumlah kajadian atawa [[frequencies]] sabenerna, meunangkeun [[power-law]] [[distribution]], mibanda [[exponent]] raket ka hiji (tapi tempo [[Gelbukh]] jeung [[Sidoro]] [[2001]]).\n\n==Tumbu kaluar==\n* [http://arxiv.org/PS_cache/physics/pdf/9901/9901035.pdf Z. K. Silagadze: Citations and the Zipf-Mandelbrot\'s law]\n* [http://www.nist.gov/dads/HTML/zipfslaw.html NIST: Zipf\'s law]\n* [http://linkage.rockefeller.edu/wli/zipf/ W. Li\'s References on Zipf\'s law]','',13,'Budhi','20040905111635','',0,0,0,0,0.462690714031,'20050208061849','79959094888364'); INSERT INTO cur VALUES (1503,0,'Yates\'_correction_for_continuity','\'\'\'Koreksi Yates keur kontinyu\'\'\', atawa \'\'tes chi-kuadrat Yates\'\', ngatur rumus keur [[uji kuadrat-chi Pearson]] nu ngurangan 0.5 tina unggal nilai dina tabel kontingensi 2 X 2. Rumus ieu dipake lamun dina hiji sel dina tabel ngabogaan nilai ekspektasi kurang ti 5.\n\n\nSumber sejen nyebutkeun yen koreksi ieu kudu dipake lamun ekspektasi frekuensi kurang ti 10.','',13,'Budhi','20041224204815','',0,0,1,0,0.634549614338,'20041224204815','79958775795184'); INSERT INTO cur VALUES (1504,0,'Vysochanskiï-Petunin_inequality','In [[probability]] theory, the \'\'\' Vysochanskiï-Petunin inequality \'\'\' gives a lower bound for the probability that a [[random variable]] with finite [[varian]] lies within a certain number of [[simpangan baku]]s of the variable\'s [[nilai ekspektasi|mean]]. The sole restriction on the [[random variable]] is that the [[probability distribution|distribution]] be [[monotonic function|unimodal]] (and the random variable continuous). The theorem applies even to heavily skewed distributions and puts bounds on how much of the data is, or is not, \"in the middle\".\n\n\'\'Theorem.\'\' Let \'\'X\'\' be a random variable with unimodal distribution, mean μ and finite variance σ2. Then, for any λ > √(8/3) = 1.63299... \n:P(\\left|X-\\mu\\right|\\geq \\lambda\\sigma)\\leq\\frac{4}{9\\lambda^2}.\n\nThe theorem refines [[Chebyshev\'s inequality]] by imposing the condition that the distribution be unimodal.\n\nIt is common in the construction of [[control chart]]s, and other statistical heuristics, to set λ = 3, corresponding to an upper probability bound of 4/81=0.04938..., and to construct \'\'3-sigma\'\' limits to bound \'\'nearly all\'\' (i.e. 95%) of the values of a [[process]] output. Without unimodality and a continuous random variable, Chebyshev\'s inequality would give a looser bound of 1/9=0.11111...\n\n==Reference==\n\n*Vysochanskiï, D F & Petunin, Y I (1980) Justification of the 3σ rule for unimodal distributions, \'\'Theory of Probability and Mathematical Statistics\'\' vol. 21 pp25-36','',13,'Budhi','20040917033244','',0,0,0,0,0.594814806988,'20040917033244','79959082966755'); INSERT INTO cur VALUES (1505,0,'VC_dimension','The \'\'\'VC dimension\'\'\' (for \'\'\'Vapnik Chervonenkis dimension\'\'\') is a measure of the [[capacity]] of a [[classification]] [[algorithm]]. It is one of the core concepts in [[statistical learning theory]]. It was originally defined by [[Vladimir Vapnik]] and [[Alexey Chervonenkis]].\n\nIntuitively, the capacity of a classification model is related to how complicated it can be. Think of [[Heaviside step function|threshold]]ing a high-[[Degree#Mathematics_and_Physics|degree]] [[polynomial]], where if the polynomial evaluates above zero, we classify that point into a positive class, negative otherwise. If we use a very high-degree polynomial, it can be very wiggly, and can fit a training set exactly. But, we should expect that outside of the training points, the classifier would not generalize well, because it is too wiggly. Such a polynomial has a high capacity. Alternatively, we can think about thresholding a linear polynomial. This polynomial may not fit the entire training set, because it has a low capacity. This notion of capacity can be made more rigorous. \n\nFirst, we need the concept of [[shatter]]ing. Consider a classification model f with some parameter vector \\theta. The model f can \'\'shatter\'\' a set of data points (x_1,x_2,\\ldots,x_n) if, for all assignments of labels to those data points, there exists a \\theta such that the model f makes no errors when evaluating that set of data points.\n\nNow, we are ready to define a mathematical notion of capacity, called the VC dimension. The VC dimension of a model f is the maximum h such that some data point set of [[cardinality]] h can be shattered by f.\n\nThe VC dimension has utility in statistical learning theory, because it can predict a [[probabilistic]] [[upper bound]] on the test error of a classification model.\n\nThe bound on the test error of a classification model (on data that is drawn [[i.i.d.]] from the same distribution as the training set) is given by\n:Training error+\\sqrt{h(\\log(2N/h)+1)-log(\\eta/4)\\over N}\nwith probability 1-\\eta, where h is the VC dimension of the classification model, and N is the size of the training set.\n\n== Rujukan jeung sumber ==\n\n* [[Andrew Moore]]\'s [http://www-2.cs.cmu.edu/~awm/tutorials/vcdim.html VC dimension tutorial]\n* V. Vapnik and A. Chervonenkis. \"On the uniform convergence of relative frequencies of events to their probabilities.\" \'\'Theory of Probability and its Applications\'\', 16(2):264--280, 1971. \n* A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. \"Learnability and the Vapnik-Chervonenkis dimension.\" \'\'Journal of the ACM\'\', 36(4):929--865, 1989.','/* References and sources */',13,'Budhi','20041224224510','',0,0,1,0,0.871926440332,'20041231122709','79958775775489'); INSERT INTO cur VALUES (1506,0,'Urn_problem','An \'\'\'urn problem\'\'\' is an idealized [[thought experiment]] in which some objects of real interest (such as atoms, people, cars, etc.) are represented as colored balls in an [[urn]] or other container.\nOne pretends to draw (remove) one or more balls from the urn;\nthe goal is to determine the probability of drawing one color or another, \nor some other properties.\n\n== Basic urn model ==\n\nIn this basic urn model in [[probability theory]], the urn contains \'\'x\'\' white and \'\'y\'\' black balls; one ball is drawn randomly from the urn and its color observed; it is then placed back in the urn, and the selection process is repeated.\n\nPossible questions that can be answered in this model are:\n* can I infer the proportion of white and black balls from n observations ? With what degree of confidence ?\n* knowing \'\'x\'\' and \'\'y\'\', what is the probability of drawing a specific sequence (e.g. one white followed by one black)?\n* if I only observe n white balls, how sure can I be that there is no black balls?\n\n== Other models ==\n\nMany other variations exist:\n* the urn could have numbered balls instead of colored ones\n* balls may not be returned to the urns once drawn.\n\n==Conto masalah urn==\n\n* Turunan [[sebaran binomial]]\n* Turunan [[hypergeometric distribution|sebaran hipergeometrik]]\n* [[Statistical physics|Statistik fisika]]: turunan tanaga sarta sebaran kecepatan\n\n==Historical remarks==\n\nUrn problems have been a part of the [[probability theory|theory of probability]] since at least the publication of the \'\'[[Ars conjectandi]]\'\' by [[Jakob Bernoulli]] ([[1713]]).\nBernoulli\'s inspiration may have been [[lottery|lotteries]], [[election|elections]], or [[games of chance]] which involved drawing balls from a container.\nIt has been asserted \n[http://mathforum.org/epigone/historia_matematica/sningzahzhil/3DEFCC9A.73AA528D@earthlink.net]\nthat \n\n:\'\'Elections in medieval and renaissance [[Venice]], including that of the [[Doge_of_Venice|doge]], often included the choice of electors by lot, using balls of different colors drawn from an urn.\'\'\n\nBernoulli himself, in \'\'Ars conjectandi\'\', considered the problem of determining, from a number of pebbles drawn from an urn, the proportions of different colors.\nThis problem was known as the \'\'[[inverse probability]]\'\' problem, and was a topic of research in the [[eighteenth century]],\nattracting the attention of [[Abraham de Moivre]] and [[Thomas Bayes]].\n\n==See also==\n\n* [[Coin-tossing problem]]s\n\n[[Category:Probability and statistics]]','/* Examples of urn problems */',13,'Budhi','20040907092844','',0,0,0,0,0.525124238117,'20040907092844','79959092907155'); INSERT INTO cur VALUES (1507,0,'Uncomfortable_science','\'\'\'\'\'Uncomfortable science\'\'\'\'\' is the term coined by [[statistician]] [[John Tukey]] for cases in which there is a need to draw an [[statistical inference|inference]] from a limited [[sampling (statistics)|sample]] of [[data]], where further [[sampling (statistics)|sample]]s influenced by the same [[cause system]] will not be available. More specifically, it involves the analysis of a [[finite]] [[natural]] [[phenomenon]] for which it is difficult to overcome the problem of using a common sample of [[data]] for both [[exploratory data analysis]] and [[confirmatory data analysis]]. This leads to the danger of [[statistics|statistical]] [[bias (statistics)|bias]] through [[testing hypotheses suggested by the data]].\n\nA typical example is [[Titius-Bode law|Bode\'s law]], which provides a simple numerical rule for the distances of the [[planet|planets]] in the [[solar system]] from the [[Sun]]. Once the rule has been derived, through the [[trial and error]] matching of various rules with the observed [[data]] ([[exploratory data analysis]]), there are not enough planets remaining for a rigorous and independent test of the [[hypothesis]] ([[confirmatory data analysis]]). We have exhausted the natural [[phenomenon|phenomena]]. The agreement between data and the numerical rule should be no surprise, as we have deliberately chosen the rule to match the data. If we are concerned about what Bode\'s law tells us about the cause system of planetary distribution then we demand confirmation which is not available.','',13,'Budhi','20040904014617','',0,0,0,1,0.82827679153,'20041225235727','79959095985382'); INSERT INTO cur VALUES (1508,0,'U_test','#redirect [[Mann-Whitney U]]','',13,'Budhi','20040904014729','',0,1,0,1,0.581160886949,'20040904014831','79959095985270'); INSERT INTO cur VALUES (1509,0,'Mann-Whitney_U','The \'\'\'Mann-Whitney U\'\'\' test is one of the best-known [[non-parametric statistics|non-parametric]] [[statistical significance]] tests. It is sometimes also called the \'\'\'Mann-Whitney-Wilcoxon\'\'\' test.\n\nThe test is appropriate to the case of two [[statistical independence|independent]] [[sampling (statistics)|samples]] of observations that are measured at least at an [[ordinal measurement|ordiinal]] level, i.e. we can at least say, of any two observations, which is the greater. The test assesses whether the degree of overlap between the two observed distributions is less than would be expected by chance, on the [[null hypothesis]] that the two samples are drawn from a single population.\n\nThe test involves the calculation of a statistic, usually called \'\'U\'\', whose distribution under the null hypothesis is known. In the case of small samples, the distribution is tabulated, but for samples above about 20 there is a good approximation using the [[normal distribution]]. Some books tabulate statistics other than \'\'U\'\', such as the sum of ranks in one of the samples, but this deviation from standard practice is unhelpful.\n\nThe \'\'U\'\' test is included in most modern [[statistical packages]]. However, it is easily calculated by hand especially for small samples. There are two ways of doing this:\n*For small samples, a direct method is recommended. It is very quick, and it also gives an insight into the meaning of the \'\'U\'\' statistic. Choose the sample for which the observations seem to be smaller (or the smaller sample - the choice is relevant only to ease of computation). Call this sample 1, and call the other sample sample 2. Taking each observation in sample 1, count the number of observations in sample 2 that are smaller than it. The total of these counts is \'\'U\'\'.\n*For larger samples, a formula can be used. Arrange all the observations into a single ranked series, and then add up the ranks in the smaller group. The sum of ranks in the other group follows by calculation, since the sum of all the ranks equals \'\'N\'\'(\'\'N\'\' + 1)/2 where \'\'N\'\' is the total number of observations. \'\'U\'\' is then given by the following formula:\n\n::U=n_1 n_2 +{n_1(n_2+1) \\over 2}-R_1\n\n:where \'\'n\'\'1 and \'\'n\'\'2 are the two sample sizes, and \'\'R\'\'1 is the sum of the ranks in sample 1.

\n\nNote that the maximum value of \'\'U\'\' is the product of the two sample sizes, and if the value obtained by either of the methods above is more than half of this maximum, it should be subtracted from the maximum to obtain the value to look up in tables. \n\nFor example, let us suppose that [[Aesop]] is dissatisfied with his classic experiment in which one [[tortoise]] was found to beat one [[hare]] in a race, and decides to carry out a significance test to discover whether the results could be extended to tortoises in general and hares in general. He collects a sample of 6 tortoises and 6 hares, and makes them all run his race. The order in which they reach the finishing post is as follows, writing T for a tortoise and H for a hare:\n\n
T H H H H H T T T T T H
\n\n(his original tortoise still goes at [[warp speed]], and his original hare is still lazy, but the others run truer to [[stereotype]]). What is the value of \'\'U\'\'? \n*Using the direct method, we take each tortoise in turn, and count the number of hares it beats, getting the following results: 6, 1, 1, 1, 1, 1. So \'\'U\'\' = 6 + 1 + 1 + 1 + 1 + 1 + 1 = 11. \n*Using the indirect method:\n::the sum of the ranks achieved by the tortoises is 1 + 7 + 8 + 9 + 1 0 + 11 = 46.\n::The sum of all the ranks will be 12·13/2 = 78.\n::Therefore the sum of the hares\' ranks = 78 − 46 = 32.\n::Therefore U = 6·6 + 6·7/2 − 46 = 36 + 21 − 46 = 11.\nConsulting the table referenced below, we find that this result does not confirm the greater speed of tortoises, though nor does it show any significant speed advantage for hares. It is left as an exercise for the reader to establish that statistical packages will give the same result, at rather greater expense.\n\nFor large samples, the normal approximation:\n\n:z=m_U/\\sigma_U\n\ncan be used, where \'\'z\'\' is a standard normal deviate whose significance can be checked in tables of the normal distribution. mU and σU are the mean and standard deviation of \'\'U\'\' if the null hypothesis is true, and are given by the following formulae:\n\n:m_U=n_1 n_2/2.\n\n:\\sigma_U=\\sqrt{n_1 n_2 (n_1+n_2+1) \\over 12}.\n\nAll the formulae given here are made more complicated in the presence of tied ranks, but if the number of these is small (and especially if there are no large tie bands) these can be ignored when doing calculations by hand. The computer statistical packages will use them as a matter or routine.\n\nThe \'\'U\'\' test is useful in the same situations as the independent samples [[Student\'s t-test]], and the question arises of which should be preferred. Before electronic calculators and computer packages made calculations easy, the \'\'U\'\' test was preferred on grounds of speed of calculation. It remains the logical choice when the data are inherently ordinal; and it is much less likely than the \'\'t\'\'-test to give a spuriously significant result because of one or two [[outlier]]s. On the other hand, the \'\'U\'\' test is often recommended for situations where the distributions of the two samples are very different. This is an error: it tests whether the two samples come from a common distribution, and [[Monte Carlo method]]s have shown that it is capable of giving erroneously significant results in some situations where they are drawn from distributions with the same mean and different variances. In that situation, the version of the \'\'t\'\'-test that allows for the samples to come from populations of different [[varian]] is likely to give more reliable results.\n\nThe \'\'U\'\' test is related to a number of other nonparametric statistical procedures. For example, it is equivalent to using [[Maurice Kendall|Kendall]]\'s τ correlation coefficient in a situation where one of the variables being correlated can only take two values.\n\nA statistic linearly related to \'\'U\'\', the ρ statistic proposed by [[Richard Herrnstein]], is widely used in studies of categorization ([[discrimination learning]] involving [[concept]]s) in birds (see [[animal cognition]]). ρ is calculated by dividing \'\'U\'\' by its maximum value for the given sample sizes, which is simply \'\'n\'\'1\'\'n\'\'2. ρ is thus a non-parametric measure of the overlap between two distributions; it can take values between 0 and 1. Both extreme values represent complete separation of the distributions, while a ρ of 0.5 represents complete overlap.\n\n==Tumbu kaluar==\n*[http://fsweb.berry.edu/academic/education/vbissonnette/tables/mwu.pdf Table of critical values of U]\n\n==Rujukan==\n*Herrnstein, R. J., Loveland, D. H., & Cable, C. (1976). Natural concepts in pigeons. \'\'Journal of Experimental Psychology: Animal Behavior Processes, 2\'\', 285-302.','',13,'Budhi','20040907230023','',0,0,0,0,0.098767989361,'20040907230023','79959092769976'); INSERT INTO cur VALUES (1510,0,'Margin_kasalahan','Dina [[statistik]], kaasup dina [[opinion poll|jajal pamanggih]] sarta survey mirip, \'\'\'margin kasalahan\'\'\' nyaeta jari-jari [[interval kapercayaan]] -- ilaharna 90% interval kapercayaan -- keur populasi nu saimbang.\n\n==Conto==\n\nContona, tempo jumlah nu resep ngarupakeun hal nu saimbang keur pamilih nu milu ngajawab \"enya\" dina referendum. Sampel random pamilih tina populasi dicokot sarta manggihkeun yen 60% pamilih dina sampel bakal milih \"enya\". Mangka estimasi saimbang tina sakabeh populasi nu bakal milih \"enya\" dicokot jadi 60%. Lamun 3% margin kasalahan dilaporkeun, hartina yen prosedur nu dipake bakal 3% sarimbang jeung nu bakal diestimasi, 90% kali. Akibatna interval ti 57% ka 63% ngarupakeun 90% interval kapercayaan keur proporsi pamilih tina sakabeh populasi bakal ngajawab \"enya\". Jari-jari interval nyaeta 3%; ieu nu disebut margin kasalahan.\n\n==Kumaha cara ngitung margin kasalahan==\n\nAnggap \'\'n\'\' ngarupakeun jumlah pamilih dina sampel. Anggap oge dicokot sacara random sarta bebas tina sakabeh pamilih. Ieu ngaharepkeun optimis, tapi angger kudu carincing dina nyokot sampel ngarah mere gambaran nu sabenerna. Anggap \'\'p\'\' ngarupakeun proporsi pamilih dina sakabeh populasi bakal ngajawab \"enya\". Mangka jumlah pamilih \'\'X\'\' dina \'\'sampel\'\' nu bakal milih \"enya\" ngarupakeun [[variabel acak]] nu mibanda [[sebaran binomial]] nu parameter-na \'\'n\'\' jeung \'\'p\'\'. Lamun \'\'n\'\' cukup gede, mangka \'\'X\'\' ngadeukeutan [[sebaran normal]] nu mibanda [[nilai ekspektasi]] \'\'np\'\' sarta [[varian]] \'\'np\'\'(1 - \'\'p\'\'). Mangka\n\n:Z=\\frac{X/n-p}{\\sqrt{np(1-p)}}\n\nngadeukeutan sebaran normal nu mibanda nilai ekspektasi 0 sarta varian 1. Nempo kana tabel persentase sebaran normal mangka nunjukeun yen P(-1.645 < Z < 1.645) = 0.9, atawa, dina basa sejen, didinya aya 90% kamungkinan kajadian. Mangka\n\n:P\\left(-1.645<\\frac{X/n-p}{\\sqrt{p(1-p)/n}}<1.645\\right)=0.9.\n\nIeu sarua jeung\n\n:P\\left(\\frac{X}{n}-1.645\\sqrt{\\frac{p(1-p)}{n}}\n\nGantikeun \'\'p\'\' dina anggota kahiji jeung katilu dina kateusaruaan ieu ku hasil nilai ekspektasi \'\'X\'\'/\'\'n\'\' sorangan dina kasalahan gede lamun \'\'n\'\' cukup gede. Hasil operasi ieu\n\n:P\\left(\\frac{X}{n}-1.645\\sqrt{\\frac{(X/n)(1-(X/n))}{n}}\n\nAnggota kahiji jeung katilu kateusaruaan ieu gumantung kana observasi \'\'X\'\'/\'\'n\'\' sarta henteu kana nu ka observasi \'\'p\'\', sarta titik tungtung interval kapercayaan. Dina basa sejen, margin kasalahan nyaeta\n\n:100%\\times 1.645\\sqrt{\\frac{(X/n)(1-(X/n))}{n}}.','',13,'Budhi','20041225044527','',0,0,1,0,0.885458320326,'20041225044527','79958774955472'); INSERT INTO cur VALUES (1511,0,'Marginal_distribution','Given two jointly distributed [[variabel acak]] \'\'X\'\' sarta \'\'Y\'\', the \'\'\'marginal distribution\'\'\' of \'\'X\'\' is simply the [[probability distribution]] of \'\'X\'\' ignoring information about \'\'Y\'\', typically calculated by summing or integrating the [[joint probability]] distribution over \'\'Y\'\'.\n\nFor [[discrete random variable]]s, the [[marginal probability]] mass function can be written as \'\'P\'\'(\'\'X\'\'=\'\'x\'\'). This is \n:P(X=x) = \\sum_{y} P(X=x,Y=y) = \\sum_{y} P(X=x|Y=y) P(Y=y)\nwhere \'\'P\'\'(\'\'X\'\'=\'\'x\'\',\'\'Y\'\'=\'\'y\'\') is the [[joint distribution]] of \'\'X\'\' and \'\'Y\'\', while \'\'P\'\'(\'\'X\'\'=\'\'x\'\'|\'\'Y\'\'=\'\'y\'\') is the [[conditional distribution]] of \'\'X\'\' given \'\'Y\'\'.\n\nSimilarly for [[continuous random variable]]s, the marginal [[probability density function]] can be written as \'\'p\'\'\'\'X\'\'(x). This is \n:p_{X}(x) = \\int_y p_{X,Y}(x,y) \\, dy = \\int_y p_{X|Y}(x|y) \\, p_Y(y) \\, dy \nwhere \'\'p\'\'\'\'X\'\',\'\'Y\'\'(x,y) gives the joint distribution of \'\'X\'\' and \'\'Y\'\', while \'\'p\'\'\'\'X\'\'|\'\'Y\'\'(\'\'x\'\'|\'\'y\'\') gives the conditional distribution for \'\'X\'\' given \'\'Y\'\'.\n\n[[Category:Probability distributions]]','',13,'Budhi','20041224115932','',0,0,1,0,0.011781380983,'20041231123439','79958775884067'); INSERT INTO cur VALUES (1512,0,'Simpangan_mean','#redirect [[simpangan mutlak]]','',13,'Budhi','20040905113437','',0,1,0,0,0.293084607596,'20040905113523','79959094886562'); INSERT INTO cur VALUES (1513,0,'Mean_kuadrat_kasalahan','Dina [[statistik]], \'\'\'mean kuadrat kasalahan\'\'\' tina [[estimator]] \'\'T\'\' dina parameter nu teu ka-observasi θ nyaeta\n\n:\\operatorname{MSE}(T)=\\operatorname{E}((T-\\theta)^2),\n\ndina hal ieu, ngarupakeun nilai ekspektasi kuadrat \"kasalahan\". \"Kasalahan\" nyaeta jumlah numana estimator beda jeung jumlah nu keur di-estimasi. Mean kuadrat kasalahan nyukupan identitas\n\n:\\operatorname{MSE}(T)=\\operatorname{var}(T)+(\\operatorname{bias}(T))^2\n\ndimana\n\n:\\operatorname{bias}(T)=\\operatorname{E}(T)-\\theta,\n\ndina hal ieu, the [[bias (statistics)|bias]] nyaeta lobana numana nilai ekspektasi tina estimator beda keur jumlah nu teu ka-observasi nu keur di-estimasi.\n\nConto kongkritna. Anggap\n\n:X_1,\\dots,X_n\\sim\\operatorname{N}(\\mu,\\sigma^2),\n\ndina hal ieu, ukran sampel random \'\'n\'\' tina populasi [[sebaran normal]]. Dua estimators σ2 kadangkala dipake (atawa nu sejenna):\n\n:\\frac{1}{n}\\sum_{i=1}^n\\left(X_i-\\overline{X}\\,\\right)^2\\ {\\rm and}\\ \\frac{1}\n{n-1}\\sum_{i=1}^n\\left(X_i-\\overline{X}\\,\\right)^2 \n\nnumana\n\n:\\overline{X}=(X_1+\\cdots+X_n)/n\n\nngarupakeun \"sampel mean\". Kahiji tina estimator ieu nyaeta estimator [[maximum likelihood]], sarta bias, dina hal ieu, bias teu sarua jeung nol, tapi ngabogaan varian nu leuwih leutik tinimbang nu kadua, anu teu bias. Varian leutik tina akibat sejen keur bias, mangka mean kuadrat kasalahan tina bias estimator leuwih leutik tinimbang estimator unbiased.','',13,'Budhi','20040907041447','',0,0,0,0,0.307359920026,'20040907041657','79959092958552'); INSERT INTO cur VALUES (1514,0,'Tes_nilai_tengah','Dina [[statistik]], \'\'\'tes nilai tengah\'\'\' atawa \'\'\'tes median\'\'\' ngarupakeun kasus husus dina [[uji kuadrat-chi Pearson]]. Tes [[null hypothesis]] nu [[median]] tina [[Statistical population|population]] tina dua [[Sampling (statistics)|samples]] digambarkeun identik. Data unggal sampe dibagi kana dua grup, hiji grup ngandung nilai data nu leuwih luhur tina median, sarta grup sejenna ngandung nilai data dina median atawa sahandapeunnana. Tes chi-kuadrat Pearson dipake keur nangtukeun frekuensi observasi dina unggal grup nu beda tina ekspektasi frekuensi nu asalna tina kombinasi dua grup [[sebaran frekuensi|sebaran]].\n\n[[Statistical power]] dina tes ieu kadangkala ditingkatkeun ku make nilai sejen tinimbang median nu dihartikeun tina grup - hal ieu, ku make nilai nu ngabagi grup kana nilai grup nu ampir sarua tinimbang median-na.\n\nTes kacida kapakena waktu sebaran data beda tina [[sebaran normal|normal]], contona waktu [[raw score]] dina klasifikasi teu teratur kana \'\'rentang pendekatan\'\' nu dijieun. Ku kitu, ieu biasa dipake salaku lengkah awal dina [[exploratory analysis]].','',13,'Budhi','20050104235030','',0,0,0,0,0.868391438792,'20050104235030','79949895764969'); INSERT INTO cur VALUES (1515,0,'Memorylessness','Dina [[probability theory|tiori probabiliti]], \'\'\'memorylessness\'\'\' nyaeta sipat penting [[probability distribution|sebaran probabiliti]]: [[sebaran eksponensial]] sarta [[geometric distribution|sebaran geometrik]].\n\n==Discrete memorylessness==\n\nSuppose \'\'X\'\' is a [[discrete random variable|discrete]] [[random variable]] whose values lie in the set { 0, 1, 2, ... } or in the set { 1, 2, 3, ... }.\nThe probability distribution of \'\'X\'\' is \'\'\'memoryless\'\'\' precisely if for any \'\'x\'\', \'\'y\'\' in { 0, 1, 2, ... } or in { 1, 2, 3, ... }, (as the case may be), we have\n\n:P(X>x+y \\mid X>x)=P(X>y).\n\nIt can readily be shown that the \'\'only\'\' probability distributions that enjoy this discrete memorylessness are [[geometric distribution]]s. These are the distributions of the number of [[statistical independence|independent]] [[Bernoulli trial]]s needed to get one \"success\", with a fixed probability \'\'p\'\' of \"success\" on each trial.\n\n==Example and motivation for the name \'\'memorylessness\'\'==\n\nFor example, suppose a die is thrown as many times as it takes to get a \"1\", so that the probability of \"success\" on each trial is 1/6, and the random variable \'\'X\'\' is the number of times the die must be thrown. Then \'\'X\'\' has a geometric distribution, and the [[conditional probability]] that the die must be thrown at least four more times to get a \"1\", given that it has already been thrown 10 times without a \"1\" appearing, is no different from the original probability that the die would be thrown at least four times. In effect, the random process does not \"remember\" how many failures have occurred so far.\n\n===A frequent misunderstanding===\n\nMemorylessness is often misunderstood by students taking courses on probability: the fact that P(\'\'X\'\' > 16 | \'\'X\'\' > 12) = P(\'\'X\'\' > 4) does \'\'not\'\' mean that the events \'\'X\'\' > 16 and \'\'X\'\' > 12 are [[statistical independence|independent]]; i.e., it does \'\'not\'\' mean that P(\'\'X\'\' > 16 | \'\'X\'\' > 12) = P(\'\'X\'\' > 16). To summarize: \"memorlessness\" of the probability distribution of the number of trials \'\'X\'\' until the first success means\n\n:\\mathrm{(Right)}\\ P(X>16 \\mid X>12)=P(X>4).\n\nIt does \'\'not\'\' mean\n\n:\\mathrm{(Wrong)}\\ P(X>16 \\mid X>12)=P(X>16).\n\n(That would be independence. These two events are \'\'not\'\' independent.)\n\n==Continuous memorylessness==\n\nSuppose that rather than considering the discrete number of trials until the first \"success\", we consider continuous waiting time \'\'T\'\' until the arrival of the first phone call at a switchboard. To say that the probability distribtuion of \'\'T\'\' is \'\'\'memoryless\'\'\' means that for any positive [[real number]]s \'\'s\'\' and \'\'t\'\', we have\n\n:P(T>t+s \\mid T>t)=P(T>s).\n\nThe only difference between this and the discrete version is that instead of requiring \'\'s\'\' and \'\'t\'\' to be positive (or, in some cases, nonnegative) [[integer]]s, thus achieving discreteness, we allow them to be real numbers that are not necessarily integers.\n\nIt can be shown that the only probability distributions that enjoy this continuous memorylessness are the [[sebaran eksponensial]].\n\n[[Category:Probability distributions]]','/* Continuous memorylessness */',13,'Budhi','20040918223654','',0,0,0,0,0.244370936996,'20041231123527','79959081776345'); INSERT INTO cur VALUES (1516,0,'Statistik_matematis','\'\'\'Statistik matematis\'\'\' migunakeun [[tiori probabiliti]] sarta cabang séjén [[matematik]] pikeun ngulik [[statistik]] tina jihat matematis murni.\n\nJadi, pikeun conto, hiji [[random sample|conto acak]] dituliskeun salaku runtuyan [[variabel acak]],\n:X_1, X_2, \\ldots, X_n\\,\\! \nnu masing-masing nuturkeun hiji [[probability distribution|sebaran probabiliti]] nu tangtu (biasana dianggap [[i.i.d. random variables|independent and identically distributed|kasebar bebas sarta identik]]).\n[[Sample mean]] digambarkeun salaku [[Fungsi (matematik)|fungsi]] tina variabel,\n:\\bar{X} = {1\\over n} \\sum_{i=1}^n X_i\\,\\! \nsarta ngarupakeun variabel acak tina hiji sebaran.\n\nKu migunakeun ieu cara, \'\'\'statistik matematik\'\'\' ngarupakeun salah sahiji usaha keur ngabuktikeun teori-teori nu loba dipake dina [[statistik terapan]].\n\n\n{{pondok}}\n\n[[Category:Statistik]]','',13,'Budhi','20041225130316','',0,0,0,0,0.958314386177,'20050303211247','79958774869683'); INSERT INTO cur VALUES (1517,0,'Meta-analysis','A \'\'\'meta-analysis\'\'\' is a [[statistics|statistical]] practice of combining the results of a number of studies. The first meta-analysis was performed by [[Karl Pearson]] in 1904, in an attempt to overcome the problem of reduced [[statistical power]] in studies with small sample sizes; analyzing the results from a group of studies can allow more accurate estimation of effects. \n\nMeta-analysis is a collection of systematic techniques for resolving apparent contradictions in research findings. Meta-analysts translate results from different studies to a common metric and statistically explore relations between study characteristics and findings. \n\nAlthough meta-analysis is widely used in [[evidence-based medicine]] today, a meta-analysis of a medical treatment was not published till 1955. In the 1970s more sophisticated analytical techniques were introduced in [[educational research]], starting with the work of [[Eugene V. Glass]].\n\nBecause the results from different studies investigating different [[dependent variable]]s are measured on different scales, the dependent variable in a meta-analysis is some standard measure of [[efek ukuran]], such as a [[skor standar]] equivalent to a difference between means (\'\'d\'\'), or an [[odds ratio]].\n\nA weakness of the method is that sources of bias are not controlled by the method. A good meta-analysis of badly designed studies will still result in bad statistics. \n\n==Tempo oge==\n* [[Simpson\'s paradox]]\n* [[Selection bias]]\n\n==Outspoken critics==\n* [[Ray Hyman]]\n\n==Tumbu kaluar==\n* [http://www.ericdigests.org/2003-4/meta-analysis.html Effect Size and Meta-Analysis]\n* [http://www.ericdigests.org/pre-922/meta.htm Meta-Analysis Research on Science Instruction]\n* [http://www.ericdigests.org/1992-5/meta.htm Meta-Analysis in Educational Research]\n\n[[da:metaanalyse]]\n[[es:metaanálisis]]','',13,'Budhi','20040908040817','',0,0,0,0,0.086181737988,'20040908040817','79959091959182'); INSERT INTO cur VALUES (1518,0,'Multidimensional_scaling','\'\'\'Multidimensional scaling (MDS)\'\'\' is a [[statistical]] technique often used in and [[data visualisation]]. It is a procedure for producing a lower-dimensional data suitable for graphing or [[3D visualisation]] from a [[high-dimensional]] data set, whilst preserving some of the most prominent \"distance\" relationships of the high-dimensional data set.\n\nApplications include [[scientific visualisation]] and [[data mining]] in fields such as [[cognitive science]], [[psychophysics]] and [[psychometrics]]. The technique is also used in [[marketing]].\n\nReferences:\n* [[J. B. Kruskal|Kruskal, J. B.]], and Wish, M. (1978), \'\'Multidimensional Scaling\'\', Sage University Paper series on Quantitative Application in the Social Sciences, 07-011. Beverly Hills and London: Sage Publications.\n\n\nSee also:\n* [[Multidimensional scaling (in marketing)]]\n\n== External links ==\n* [http://www.mathpsyc.uni-bonn.de/doc/delbeke/delbeke.htm An elementary introduction to multidimensional scaling]\n* [http://www.pavis.org/essay/multidimensional_scaling.html Evaluation of multidimensional scaling algorithms]','',13,'Budhi','20040904020221','',0,0,0,1,0.602267697734,'20041226002643','79959095979778'); INSERT INTO cur VALUES (1519,0,'Multiple_comparisons','Dina [[statistik], the \'\'\'multiple comparisons\'\'\' problem tests [[null hypothesis|null hypotheses]] stating that the averages of several disjoint populations are equal to each other. Typically one behaves as if the standard deviations of the several populations are equal to each other and the populations are [[sebaran normal|normally distributed]] unless the data give evidence to the contrary. It is one of many problems in applied statistics in which the usual test is an [[F-test]]. This problem is a special case of the [[analisa varian]].\n\nOther methods include:\n\n*[[Tukey-Cramer method]] (Tukey\'s HSD)\n*[[Bonferroni bound]]\n\n==Bibliography==\n\n*Miller, R G (1966) \'\'Simultaneous Statistical Inference\'\'\n\n{{msg:stub}}','',13,'Budhi','20040908003918','',0,0,0,0,0.548690162855,'20040908003918','79959091996081'); INSERT INTO cur VALUES (1520,0,'Negative_binomial_distribution','Dina [[probability theory|teori probabiliti]], \'\'\'sebaran negative binomial\'\'\' nyaeta anggota tina kulawarga [[probability distribution|sebaran probabiliti]] diskrit.\n\n==Two or three discrepant conventions==\n\nThree conventions are found in the literature, two of them conflicting with each other. The third generalizes the second rather than directly conflicting with it.\n\n* The \'\'\'negative binomial distribution\'\'\' is the probability distribution of the number of [[statistical independence|independent]] [[Bernoulli trial]]s needed to get a fixed number \'\'r\'\' of \"successses\" (see also [[Bernoulli process]].); or\n\n* The \'\'\'negative binomial distribution\'\'\' is the probability distribution of the number of \"failures\" in [[statistical independence|independent]] [[Bernoulli trial]]s \'\'before\'\' the \'\'r\'\'th \"success\" (see also [[Bernoulli process]]).\n\n* A third convention will be explained below. The third convention generalizes the second one, rather than actually conflicting with it. It allows \'\'r\'\' to be a non-integer.\n\nThe probability distributions called \"negative binomial\" according to the second and third conventions are [[infinite divisibility|infinitely divisible]]. The ones called \"negative binomial\" according to the first convenetion have the virtue that everyone\'s intuitive guess about their [[nilai ekspektasi]] is correct; for example, if you repeatedly throw an ordinary six-sided die until you get a \"1\", on average it takes six trials, if you keep trying until you get two \"1\"s, it takes 12 trials on average, and so on.\n\n==Example==\n\nSuppose we repeatedly throw a die, and consider a \"1\" to be a \"success\". The probability of success on each trial is 1/6. The number of trials needed to get three successes belongs to the infinite set { 3, 4, 5, 6, ... }. That number of trials is a negative-binomially distributed [[random variable]] according to the first convention. The number of failures before the third success belongs to the infinite set { 0, 1, 2, 3, ... }. That number of failures is a negative-binomially distributed random variable according to the second convention.\n\n==Parametrization==\n\nThe family of negative binomial distributions is parametrized by two parameters: the fixed number \'\'r\'\' of successes and the probability \'\'p\'\' of success on each trial. The first parameter \'\'r\'\' is a positive [[integer]]; the second parameter \'\'p\'\' is a [[real number]] between 0 and 1. If \'\'r\'\' = 1, then we have a [[geometric distribution]]. (In the \"third convention\" referred to above, \'\'r\'\' will not necessarily be an integer.)\n\n== Formulas ==\n\nIn this section we adhere to the first convention above: the negative binomial distribution is the number of independent trials needed to get \'\'r\'\' successes, with probability \'\'p\'\' of success on each trial.\n\n:Parameters : \'\'r\'\' (number of successes) is an [[integer]] where 1 ≤ \'\'r\'\'; the special case \'\'r\'\' = 1 is the [[geometric distribution]].\n\n: \'\'p\'\' = probability of success on each trial is a [[real number]] where 0 < \'\'p\'\' < 1.\n\n:Support (domain where probability mass > 0) = set of all integers ≥ \'\'r\'\'.\n\n:[[Probability mass function]] \'\'f\'\'(\'\'x\'\') = P(\'\'X\'\' = \'\'x\'\') = the probability that \'\'r\'\'th success occurs on the \'\'x\'\'th trial is given by\n\n:f(x)={x-1 \\choose r-1} p^r (1-p)^{x-r}\n\n(see [[binomial coefficient]]).\n\n:[[Cumulative distribution function|Fungsi kumulatif sebaran]] \'\'F\'\'(\'\'x\'\') = P(\'\'X\'\' ≤ \'\'x\'\') = probabiliti yen ka-\'\'r\'\' sukses kajadian dina atawa samemeh percobaan ka-\'\'x\'\': Taya bentuk solusi sederhana nu raket, tapi bisa diitung ku komputer ngaliwatan fungsi beta teu lengkep salaku [[sebaran binomial]].\n\n:[[Nilai ekspektasi]] E(\'\'X\'\') = \'\'r\'\'/\'\'p\'\'.\n\n:[[Varian]] var(\'\'X\'\') = σ2 = \'\'r\'\'(1 − \'\'p\'\')/\'\'p\'\'2.\n\n== Properties ==\n\nIf \'\'Xr\'\' is a random variable following the negative binomial distribution with parameters \'\'r\'\' and \'\'p\'\', then \'\'Xr\'\' is a sum of \'\'r\'\' [[statistical independence|independent]] variables following the [[geometric distribution]] with parameter \'\'p\'\'. As a result of the [[central limit theorem]], \'\'Xr\'\' is therefore approximately [[sebaran normal|normal]] for sufficiently large \'\'r\'\'.\n\nSaterusna, lamun \'\'Ys\'\' ngarupakeun variabel random nu nuturkeun [[sebaran binomial]] mibanda paramater \'\'s\'\' jeung \'\'p\'\', mangka\n\n:\\operatorname{Pr}\\left(X_r \\leq s\\right)\n= \\operatorname{Pr}\\left(Y_s \\geq r\\right)\n\n: = Pr(after \'\'s\'\' trials, there are at least \'\'r\'\' successes).\n\nIn this sense, the negative binomial distribution is the \"inverse\" of the binomial distribution.\n\nThe sum of independent negative-binomially distributed random variables with the same value of the parameter \'\'p\'\' but the \"\'\'r\'\'-values\" \'\'r\'\'1 and \'\'r\'\'2 is negative-binomially distributed with the same \'\'p\'\' but with \"\'\'r\'\'-value\" \'\'r\'\'1 + \'\'r\'\'2.\n\nThe negative binomial distribution also arises as a continuous mixture of [[Poisson distribution]]s for which the Poisson parameter λ was generated by a [[sebaran gamma]].\n\nIf we follow the convention that the negative binomial distribution is the probability distribution of the number of failures before the \'\'r\'\'th success, then any negative binomial distribution is [[infinite divisibility|infinitely divisible]], i.e., if \'\'X\'\' has a negative binomial distribution, then for any positive integer \'\'n\'\', there exist independent identically distributed random variables \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\' whose sum has the same distribution that \'\'X\'\' has. These will not be negative-binomially distributed in the sense defined above unless \'\'n\'\' is a divisor of \'\'r\'\', but see the \"third convention\" below.\n\n== Explanation of the name ==\n\nSuppose \'\'X\'\' is a random variable with a negative binomial distribution with parameters \'\'r\'\' and \'\'p\'\'.\nThe statement that the sum from \'\'x\'\' = \'\'r\'\' to infinity, of the probability Pr[\'\'X\'\' = \'\'x\'\'], is equal to 1, can be shown by a bit of algebra to be equivalent to the statement that (1 − \'\'p\'\')− \'\'r\'\' is what [[binomial series|Newton\'s binomial theorem]] says it should be.\n\nAnggap \'\'Y\'\' ngarupakeun variabel [[sebaran binomial]] mibanda parameter \'\'n\'\' sarta \'\'p\'\'.\n\'\'Pernyataan\'\' yen jumlah tina \'\'y\'\' = 0 ka \'\'n\'\', probabiliti Pr[\'\'Y\'\' = \'\'y\'\'], sarua jeung 1, sebutkeun yen 1 = (\'\'p\'\' + (1 − \'\'p\'\'))\'\'n\'\' nyaeta nuturkeun [[binomial theorem|teorema binomial]] saperti nu diajarkeun dina aljabar di SMA.\n\nThus the negative binomial distribution bears the same relationship to the negative-integer-exponent case of the binomial theorem that the binomial distribution bears to the positive-integer-exponent case.\n\n===Mathematical details===\n\nAssume \'\'p\'\' + \'\'q\'\' = 1. Then the [[binomial theorem]] of elementary algebra implies that\n\n:1=1^n=(p+q)^n=\\sum_{x=0}^n {n \\choose x} p^x q^{n-x}.\n\nThis can be written in a way that may at first appear to some to be incorrect, and perhaps perverse even if correct:\n\n:(p+q)^n=\\sum_{x=0}^\\infty {n \\choose x} p^x q^{n-x},\n\nin which the upper bound of summation is infinite. If the [[binomial coefficient]] is defined by\n\n:{n \\choose x}={n! \\over x!(n-x)!} \n\nthen it does not make sense when \'\'x\'\' > \'\'n\'\', since [[factorial]]s of negative numbers are not defined. But one may also read it as\n\n:{n \\choose x}={n(n-1)(n-2)\\cdots(n-x+1) \\over x!}.\n\nIn that case it is defined even when \'\'n\'\' is negative or is not an integer. But in our case of the binomial distribution it is zero when \'\'x\'\' > \'\'n\'\'. So \'\'why\'\' would we write the result in that form, with a seemingly needless sum of infinitely many zeros? The answer comes when we generalize the binomial theorem of elementary algebra to \'\'\'[[Newton\'s binomial theorem]]\'\'\'. Then we can say, for example\n\n:(p+q)^{8.3}=\\sum_{x=0}^\\infty {8.3 \\choose x} p^x q^{n-x}.\n\nNow suppose \'\'r\'\' > 0 and we use a negative exponent:\n\n:1=p^r p^{-r}=p^r (1-q)^{-r}=p^r\\sum_{x=0}^\\infty {-r \\choose x} (-q)^x.\n\nThen all of the terms are positive, and the term\n\n:p^r {-r \\choose x} (-q)^x\n\nis just the probability that the number of failures before the \'\'r\'\'th success is equal to \'\'x\'\', provided \'\'r\'\' is an integer. (If \'\'r\'\' is a negative non-integer, so that the exponent is a positive non-integer, then some of the terms in the sum above are negative, so we do not have a probability distribution on the set of all nonnegative integers.)\n\nThis brings us to the \"third convention\" mentioned above: Allow non-integer values of \'\'r\'\'. Then we have a generalized negative binomial distribution that coincides with the second convention above when \'\'r\'\' happens to be a positive integer.\n\nRecall from above that\n\n:The sum of independent negative-binomially distributed random variables with the same value of the parameter \'\'p\'\' but the \"\'\'r\'\'-values\" \'\'r\'\'1 and \'\'r\'\'2 is negative-binomially distributed with the same \'\'p\'\' but with \"\'\'r\'\'-value\" \'\'r\'\'1 + \'\'r\'\'2.\n\nThis property persists when the definition is thus generalized, and affords a quick way to see that the negative binomial distribution is infinitely divisible.\n\n== Example ==\n\n\'\'(After a problem by Dr. Diane Evans, professor of mathematics at [[Rose-Hulman Institute of Technology]])\'\'\n\nJohnny, a sixth grader at Honey Creek Middle School in [[Terre Haute, Indiana]], is required to sell candy bars in his neighborhood to raise money for the 6th grade field trip.\nThere are thirty homes in his neighborhood, and his father has told him not to return home until he has sold five candy bars.\nSo the boy goes door to door, selling candy bars. At each home he visits, he has an 0.4 probability of selling one candy bar and an 0.6 probability of selling nothing.\n\n=== What\'s the probability mass function for selling the last candy bar at the \'\'x\'\'th house? ===\n\n:\'\'f\'\'(\'\'x\'\') = C(\'\'x\'\' − 1, 4) · 0.45 · (1 − 0.4)\'\'x\'\' − 5\n\n=== What\'s the probability that he finishes on the tenth house? ===\n\n:\'\'f\'\'(10) = 0.100\n\n=== What\'s the probability that he finishes on or before reaching the eighth house? ===\n\nAnswer: To finish on or before the eighth house, he must finish at the fifth, sixth, seventh, or eighth house. Sum those probabilities:\n:f(5) = 0.0102; f(6) = .0307, f(7) = .0553; f(8) = .0774; sum(f(j), j=5..8) = 0.1737\n\n=== What\'s the probability that he exhausts all houses in the neighborhood, gives up, and then goes to [[homelessness|live on the streets]]? ===\n\n:1-\\sum_{j=5}^{30} f(j)=1-0.9985=0.0015\n\nMoral: Negative binomial distributions don\'t turn our children out on the streets; bad [[parenting]] does.\n\n\n[[Category:Probability distributions]]\n\n[[it:Variabile casuale Binomiale Negativa]]\n[[de:Negative Binomialverteilung]]','/* Properties */',13,'Budhi','20040918224434','',0,0,0,0,0.888970476058,'20040918224434','79959081775565'); INSERT INTO cur VALUES (1521,0,'Neyman-Pearson_lemma','Dina [[statistik]], \'\'\'Neyman-Pearson lemma\'\'\' nangtukeun yen waktu ngagawekeun [[tes hipotesa statistik|tes hipotesa]] antara dua titik hipotesa \'\'H\'\'0: \'\'θ\'\'=\'\'θ\'\'0 sarta \'\'H\'\'1: \'\'θ\'\'=\'\'θ\'\'1, mangka [[likelihood-ratio test]] nu nolak \'\'H\'\'0 dina ngadukung \'\'H\'\'1 waktu\n\n:\\Lambda(x)=\\frac{ L( \\theta _{0} \\mid x)}{ L (\\theta _{1} \\mid x)} \\leq k \\mbox{ where } Pr(\\Lambda(X)\\leq k|H_0)=\\alpha\n\nleuwih ilahar salaku tes [[statistical power|power]] [[Type I error|ukuran \'\'α\'\']].','',13,'Budhi','20050104070003','',0,0,0,0,0.694621472943,'20050104070003','79949895929996'); INSERT INTO cur VALUES (1522,0,'Statistik_non-parametrik','\'\'\'Métode kaputusan statistik\'\'\' \'\'\'Non-parametrik\'\'\' (atawa sebaran-bebas) ngarupakeun prosedur matematik keur [[tes hipotesa statistik]], teu siga dina [[statistik parametrik]], taya asumsi ngeunaan [[sebaran frekuensi]] tina variabel nu ditaksir. Pamakean nu ilahar ieu metoda nyaeta dina [[tes chi-kuadrat]]. Pamakean sejen nu make metoda non-parametrik kaasup [[Mann-Whitney U]], [[Kruskal-Wallis one-way analysis of variance]], [[median test]], [[Spearman\'s rank correlation coefficient|Spearman\'s ρ]], sarta estimasi sebaran make [[sebaran binomial]].\n\nKabehanna \'\'mungkin\'\' leuwih mibanda [[statistical power]] tinimbang tes parametrik waktu asumsi dina kaayaan tes parametrik teu nyugemakeun.\n\nTempo oge [[statistik parametrik]].','',13,'Budhi','20050105000109','',0,0,0,0,0.481416103189,'20050105000109','79949894999890'); INSERT INTO cur VALUES (1523,0,'Nonprobability_sampling','[[sampling (statistics)|Sampling]] is the use of a subset of the [[population (statistics)|population]] to represent the whole population. Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated. \'\'\'Nonprobability sampling\'\'\' does not meet this criterion and should be used with caution. Nonprobability sampling techniques cannot be used to infer from the sample to the general population. Any generalizations obtained from a nonprobability study must be filtered through one\'s knowledge of the topic being studied. Performing nonprobability sampling is considerably less expensive than doing probability sampling, but the results are of limited value.\n\nExamples of nonprobability sampling include:\n* \'\'\'Convenience sampling\'\'\' - members of the population are chosen based on their relative ease of access. To sample friends, co-workers, or shoppers at a single mall, are all examples of convience sampling.\n* \'\'\'Snowball sampling\'\'\' - The first respondent refers a friend. The friend also referes a friend, ect.\n* \'\'\'Judgmental sampling\'\'\' or \'\'\'Purposive sampling\'\'\' - The researcher chooses the sample based on who they think would be appropriate for the study. This is used primarily when there is a limited number of people that have expertise in the area being researched.\n* \'\'\'Case study\'\'\' - The research is limited to one group, often with a similar characteristic or of small size.\n* \'\'\'ad hoc quotas\'\'\' - A quota is established (say 65% women) and researchers are free to choose any respondent they wish as long as the quota is met.\n\nEven studies intended to be probability studies sometimes end up being non-probability studies due to unintentional or unplanned characteristics of the sampling method. In public opinion polling by private companies (or organizations unable to require response), the sample can be self-selected rather than random. This often introduces an important type of error: \'\'\'self-selection error\'\'\'. This error sometimes makes it unlikely that the sample will accurately represent the broader population. Volunteering for the sample may be determined by characteristics such as submissiveness or availability. The samples in such surveys should be treated as non-probability samples of the population, and the validity of the estimates of parameters based on them unknown. \n\n\n==See also==\n\n* [[statistics]]\n* [[marketing research]]\n* [[quantitative marketing research]]\n* [[sampling (statistics)|sampling]]\n* [[cluster sampling]]\n* [[multistage sampling]]\n* [[simple random sampling]]\n* [[systematic sampling]]\n* [[stratified sampling]]','',13,'Budhi','20040904021359','',0,0,0,1,0.523834751697,'20040904021359','79959095978640'); INSERT INTO cur VALUES (1524,0,'Rankit','Dina [[statistik]], \'\'\'rankits\'\'\' titik data tina susunan data nu ngandung jejer [[scalar|skalar]] sederhana nyaeta nilai ekspektasi tina [[order statistik]] dina standar [[sebaran normal]] corresponding to data points in a manner determined by the order in which the data points appear.\n\nThis is perhaps most readily understood by means of an example. If an [[i.i.d.]] sample of six items is taken from a [[sebaran normal|kasebar normal]] population with [[nilai ekspektasi]] 0 and [[varian]] 1 and then sorted into increasing order, the expected values of the resulting [[order statistic]]s are:\n\n:-1.2816,\\ \\ -0.64335,\\ \\ -0.20189,\\ \\ 0.20189,\\ \\ 0.64335,\\ \\ 1.2816\n\nSuppose the numbers in a data set are\n\n: 65, 75, 16, 22, 43, 40.\n\nThe corresponding ranks are\n\n: 5, 6, 1, 2, 4, 3,\n\ni.e., the number appearing first is the 5th-smallest, the number appearing second is 6th-smallest, the number appearing third is smallest, the number appearing fourth is 2nd-smallest, etc. One rearranges the expected normal order statistics accordingly, getting the \'\'\'rankits\'\'\' of this data set:\n\n:\\begin{matrix}\n\\mbox{data}\\ \\mbox{point} & & \\mbox{rankit} \\\\ \\\\\n65 & & 0.64335 \\\\\n75 & & 1.2816 \\\\\n16 & & -1.2816 \\\\\n22 & & -0.64335 \\\\\n43 & & 0.20189 \\\\\n40 & & -0.20189\\end{matrix}\n\nA graph ploting the rankits on the horizontal axis and the data points on the vertical axis is a \'\'\'rankit plot\'\'\' or \'\'\'normal probability plot\'\'\'. Such a plot is necessarily nondecreasing. In large samples from a normally distributed population, such a plot will approximate a straight line. Substantial deviations from straightness are considered evidence against normality of the distribution.\n\nThe word \'\'\'\'\'rankit\'\'\'\'\' was introduced by the statistician Chester Bliss (not to be confused with the politician Chester Bliss Bowles).','',13,'Budhi','20040917033431','',0,0,0,0,0.335842844721,'20040917033431','79959082966568'); INSERT INTO cur VALUES (1525,0,'Semivarian','Dina [[spatial statistics|statistik spasial]], \'\'\'semivarian\'\'\' dijelaskeun ku \n:\\gamma(h)=\\sum_{i=1}^{n(h)}\\frac{(z(x+h)-z(x))^2}{n(h)}\nnumana \'\'z\'\' ngarupakeun nilai data tina sabagian lokasi, \'\'h\'\' nyaeta jarak antara nilai data, sarta \'\'n\'\'(\'\'h\'\') dianggap angka pasangan nilai data diberekeun, spasi jarak tina bagian \'\'h\'\'.\n\nPot semivarian ka jarak antara data nilai dipikanyaho salaku [[semivariogram]], atawa keur gampang nyebutna [[variogram]].\n\nTopik pakait: [[géostatistik]]\n\nRujukan:\n# Shine, J.A., Wakefield, G.I.: A comparison of supervised imagery classification using analyst-chosen and geostatistically-chosen training sets, 1999, http://www.geovista.psu.edu/sites/geocomp99/Gc99/044/gc_044.htm','',13,'Budhi','20040908020151','',0,0,0,0,0.938130644587,'20040908020151','79959091979848'); INSERT INTO cur VALUES (1526,0,'Truncated_mean','A \'\'\'truncated mean\'\'\' is a [[statistical]] [[measure of central tendency]], much like the [[mean]] and [[median]]. It involves discarding given parts of a [[probability distribution]] or [[Sampling (statistics)|sample]] at the top or the bottom end, and typically involves discarding an equal amount at each end. \n\nThe scoring method used in many [[sport]]s that are evaluated by a panel of judges is a truncated mean: \'\'discard the lowest and the highest scores; calculate the mean value of the remaining scores\'\'. The [[interquartile mean]] is another example when the lowest 25% and the highest 25% are discarded, and the mean of the remaining scores are calculated.\n\nThe truncated mean is less sensitive to outliers than the mean, but uses more information from the distribution or sample than the median. Unless the underlying distribution is [[symmetric]], the truncated mean of a sample is unlikely to produce an [[unbiased estimator]] for either the mean or the median.','',13,'Budhi','20040904021711','',0,0,0,1,0.538057476533,'20040904021711','79959095978288'); INSERT INTO cur VALUES (1527,0,'Trend_estimation','A series of measurements of a [[process]] may be treated as a [[deret waktu]], and then \'\'\'trend estimation\'\'\' is the application of statistical techniques to make and justify statements about trends in the data. Assuming the underlying process is a physical system that is incompletely understood, one may thereby construct a model, independent of anything known about the physics of the process, to explain the behaviour of the measurement. In particular, one may wish to know if the measurements exhibit an increasing or decreasing trend, that can be statistically distinguished from random behaviour. For example, take daily average temperatures at a given location, from winter to summer; or the global temperature series over the last 100 years. \n\nParticularly in that latter case, issues of [[homogeneity]] (is the series equally reliable throughout its length?) are important. For the moment we shall simplify the discussion and neglect those points. This page does not attempt a full mathematical treatment, merely an exposition. \n\n== Fitting a trend: least-squares ==\n\nGiven a set of data, and the desire to produce some kind of \"model\" of that data (model, in this case, meaning a function fitted through the data) there are a variety of functions that can be chosen for the fit. But if there is no prior understanding of the data, the simplest function to fit is a straight line and thus this is the \"default\".\n\nContinuing, once it has been decided to fit a straight line, there are various ways to do so, but the overwhelming default is the least-squares fit, equivalent to minimisation of the \'\'L\'\'2 norm. See [[least squares]].\n\nThus, given a set of data points x_i, and data values y_i, one choses a and b so that \n\n:sum(((ax_i + b) - y_i)^2) \n\nis minimised. This can always be done, in closed form [http://mathworld.wolfram.com/LeastSquaresFitting.html].\n\nFor the rest of this article, \"trend\" will mean the least squares trend. It\'s what it means in 99% of cases everywhere else.\n\nNow, we have a trend. But is it significant? And what do we mean by significant?\n\n==Tren dina data random==\n\nSamemeh urang nempo kana tren data riil, kudu ngarti heula tren dina data random.\n\n[[Image:Random-trends-histogram.png|thumb|right|Red shaded values are greater than 99% of the rest; blue, 95%; red, 90%. In this case, the V values discussed in the text for (one-sided) 95% confidence is seen to be 0.2.]]\n\nIf we take a series which is known to be random - fair dice falls; or computer-generated random numbers - and fit a trend line through the data, the chances of a truly zero trend are negligible. But we would probably expect the trend to be \"small\". If we take a series with a given degree of noise, and a given length (say, 100 points), and generate a large number of such series (say, 100,000 series), we can then calculate the trends from these 100,000 series, and empirically establish a distribution of trends that are to be expected from such random data - see diagram. Such a distribution will be normal ([[Central limit theorem]] except in pathological cases, since (in a slightly non-obvious way of thinking about it) the trend is a linear combination of the y_i) and (if the series genuinely is random) centered on zero. We may now establish a level of statistical certainty, S, desired - 95% confidence is typical; 99% would be stricter, 90% rather looser - and say: what value, V, do we have to choose so that S% of trends are within V? (complication: we may be interested in positive and negative trends - 2-tailed - or may have prior knowledge that only positive, or only negative, trends are of interest).\n\nIn the above discussion the distribution of trends was calculated empirically, from a large number of trials. In simple cases (normally distributed random noise being a classic) the distribution of trends can be calculated exactly.\n\nSuppose we then take another series with approximately the same variance properties as our random series. We do not know in advance whether it \"really\" has a trend in it, so we calculate the trend, T, and discover that it is less than V. Then we may say that, at degree of certainty S, any trend in the data cannot be distinguished from random noise.\n\nHowever, note that whatever value of S we choose, then a given fraction, 1-S, of truly random series will be declared (falsely, by construction) to have a significant trend. Conversely, a certain fraction of series that \"really\" have a trend will not be declared to have a trend.\n\n== Data as trend plus noise ==\n\nTo analyse a (time) series of data, we assume that it may be represented as trend plus noise:\n\n:x_i = at_i + b + e_i\n\nwhere a and b are (usually unknown) constants and the e\'s are independent randomly distributed \"errors\". Unless something special is known about the e\'s, they will be assumed to have a [[normal distribution]]. It is simplest if the e\'s all have the same distribution, but if not (if some have higher variance, meaning that those data points are effectively less certain) then this can be taken into account during the least squares fitting, by weighting each point by the inverse of the variance of that point.\n\nIn most cases, where only a single time series exists to be analysed, the variance of the e\'s is estimated by fitting a trend, thus allowing at+b to be removed and leaving the e\'s as residuals, and calculating the variance of the e\'s from the residuals — this is often the only way of estimating the variance of the e\'s.\n\nOne particular special case of great interest, the (global) temperature time series, is known not to be homogeneous in time: apart from anything else, the number of weather observations has (generally) increased with time, and thus the error associated with estimating the global temperature from a limited set of observations has decreased with time. In fitting a trend to this data, this can be taken into account, as described above.\n\nOnce we know the \"noise\" of the series, we can then assess the significance of the trend by making the \'\'null hypothesis\'\' that the trend, a, is not significantly different from 0. From the above discussion of trends in random data with known variance, we know the distribution of trends to be expected from random (trendless) data. If the calculated trend, a, is larger than the value, V, then the trend is deemed significantly different from zero at significance level S.\n\n== Noisy time series, and an example ==\n\nIt is harder to see a trend in a noisy time series. For example, if the true series is 0, 1, 2, 3 all plus some independent normally distributed \"noise\" e of [[standard deviation]] E, and we have a sample series of length 50, then if E=0.1 the trend will be obvious; if E=100 the trend will probably be visible; but if E=10000 the trend will be buried in the noise.\n\nIf we consider a concrete example, the global surface temperature record of the past 140 years as presented by the [[IPCC]]: [http://www.grida.no/climate/ipcc_tar/wg1/figspm-1.htm], then the interannual variation is about 0.2°C and the trend about 0.6°C over 140 years, with 95% confidence limits of 0.2°C (by coincidence, about the same value as the interannual variation). Hence the trend is statistically different from 0. This alone, however, tells us nothing about the physical causes of the temperature change.\n\n\n== Goodness of fit (R-squared) and trend ==\n\n[[Image:Random-data-plus-trend-r2.png|thumb|right|Illustration of the variation of r2 with filtering whilst fit remains the same]]\n\nThe least-squares fitting process throws out a value - r-squared - which is the square of the residuals of the data after the fit. It says what fraction of the variance of the data is explained by the fitted trend line. Is does \'\'\'not\'\'\' relate to the significance of the trend line - see graph. A noisy series can have a very low r2 value but a very high significance of fit. Often, filtering a series increases r2 whilst making little difference to the fitted trend or significance.\n\n\n\n== Real data is auto-correlated ==\n\nThe above discussion assumed the data could be represented as trend + noise, with the noise at each data point being \'\'independent\'\'. This is important, as it makes an enormous difference to the ease with which the statistics can be analysed. Real (climate) data rarely fulfills this criterion.\n\n[\'\'This section in need of expansion: examples.\'\']','/* Trends in random data */',13,'Budhi','20041015010812','',0,0,0,0,0.141520272541,'20041015010812','79958984989187'); INSERT INTO cur VALUES (1528,0,'Rentang_tolérans','Ogé katelah wates toléran (Ing. \'\'tolerance limits\'\').\n\n==Pamakéan rentang toléran==\nRentang toléran patali jeung rékayasa wates toléran. Sacara husus, rékayasa wates toléran nangtukeun niléy maksimum jeung minimum pikeun hiji produk sangkan bisa lumaku. Rékayasa wates toléran bisa ditangtukeun maké \'\'[[Geometric Dimensioning and Tolerancing]]\'\'. Rentang tolérans ngarupakeun dasar keur [[control chart|chart kontrol]] dina sababaraha rupa.\nStatistik interval tolérans (atawa watés) dihasilekun tina mroses data.\nLobana ieu interval gumantung kana prosesna.\nRentang toléran dihartikeun salaku kamampuan proses keur nangtukeun nilai minimum jeung maksimum.\nNilai wates dina ieu wewengkon mibanda bagean nu sarimbag jeung sakabeh populasi sarta mibanda probabiliti atawa kapercayaan husus.\n\n==Rujukan kaluar==\n\nTempo [http://www.itl.nist.gov/div898/handbook/index.htm The NIST/SEMATECH e-Handbook of Statistical Methods], 2004 July 17.\n\nDina bagian \nSection 7.2.6.3 - \n[http://www.itl.nist.gov/div898/handbook/prc/section2/prc263.htm Tolerance intervals for a normal distribution]\n\nTempo \"Quality Control Handbook\", Juran.','/* Pamakéan rentang toléran */',13,'Budhi','20041224223839','',0,0,0,0,0.072570066002,'20041224223839','79958775776160'); INSERT INTO cur VALUES (1529,0,'Testing_hypotheses_suggested_by_the_data','Dina [[statistik]], \'\'\'hypotheses suggested by the data\'\'\' must be tested differently from hypotheses formed independently of the data.\n\n==How to do it wrong==\n\nFor example, suppose fifty different researchers, unaware of each other\'s work, run clinical trials to test whether Vitamin X is efficacious in preventing cancer. Forty-nine of them find no significant differences between measurements done on patients who have taken Vitamin X and those who have taken a placebo. The fiftieth study finds a difference so extreme that if Vitamin X has no effect then such an extreme difference would be observed in only one study out of fifty. When all fifty studies are pooled, one would say no effect of Vitamin X was found. But it would be reasonable for the investigators running the fiftieth study to consider it likely that they have found an effect, until they learn of the other forty-nine studies. Now suppose that one anomalous study was in Denmark. The data suggest a hypothesis that Vitamin X is more efficacious in Denmark than elsewhere. But Denmark was fortuitously the one-in-fifty in which an extreme value of a test statistic happened; one expects such extreme cases one time in fifty on average if no effect is present. It would therefore be fallacious to cite the data as evidence in favor of this particular \'\'\'hypothesis suggested by the data\'\'\'.\n\n==The general problem==\n\nSuch a process greatly inflates the [[probability]] of [[type I error]] as all but the data most favourable to the [[hypothesis]] is discarded. This is a risk, not only in [[tes hipotesa statistik|hypothesis testing]] but in all [[statistical inference]] as it is often problematic accurately to describe the process that has been followed in searching and discarding [[data]]. It is a particular problem in [[model statistik]], where many different models are rejected by [[trial and error]] before publishing a result (see also [[overfitting]].) [[Likelihood]] and [[Bayesian inference|Bayesian]] approaches are no less at risk owing to the difficulty in specifying the [[likelihood function]] without an exact description of the search and discard process.\n\nThe error is a particularly prevalent in [[data mining]] and [[machine learning]]. It also commonly occurs in [[academic publishing]] where only reports of positive, rather than negative, results tend to be accepted, resulting in the effect known as [[publication bias]].\n\n==Kumaha cara migawe nu bener==\n\nStrategi keur meupeuskeun masalah kaasup:\n*Ngumpulkeun [[confirmation sample|konfirmasi sampel]]\n*[[Cross-validation|Validasi silang]]\n*[[Multiple comparisons|Perbandingan bertingkat]]\n\nTes simultan Henry Scheffé\'s sakabehna jentre dina masalah [[multiple comparisons|perbandingan bertingkat]] nyaeta ulangan nu dipikanyaho sacara hade keur kasus dina [[analisa varian]]. It is a method designed for testing hypotheses suggested by the data while avoiding the fallacy described above. See his \'\'A Method for Judging All Contrasts in the Analysis of Variance\'\', Biometrika, 40, pages 87-104.','/* The general problem */',13,'Budhi','20050104070204','',0,0,0,0,0.820823869119,'20050104070204','79949895929795'); INSERT INTO cur VALUES (1530,0,'Métode_Taguchi','[[ja:品質工学]]\n\n\'\'\'Metoda Taguchi\'\'\' nyaeta metoda [[statistik]] nu diwangun ku [[Genichi Taguchi]] keur ningkatkeun kualitas produksi pabrik. \'\'Metoda Taguchi\'\' ngarupakeun hal nu kontroversi keur [[statistician|statistikawan]] urang kulon.\n\nPrinsip [[Genichi Taguchi|Taguchi]] nu mangaruhan kana [[statistik]] nyaeta\n\n#Taguchi loss-function;\n#Pilosopi \'\'off-line quality control\'\'; sarta\n#Hal anyar dina [[desain percobaan]].\n\n===Loss functions===\n\n[[Genichi Taguchi|Taguchi]]\'s reaction to the classical [[desain percobaan]] methodology of [[Ronald A. Fisher|R. A. Fisher]] was that it was perfectly adapted in seeking to improve the [[mean]] outcome of a [[process]]. As [[Ronald A. Fisher|Fisher]]\'s work had been largely motivated by programmes to increase [[agricultural]] production, this was hardly surprising. However, Taguchi realised that in much industrial production, there is a need to produce an outcome \'\'on target\'\', for example, to [[machine]] a hole to a specified [[diameter]] or to manufacture a [[electrochemical cell|cell]] to produce a given [[voltage]]. He also realised, as had [[Walter A. Shewhart]] and others before him, that excessive variation lay at the root of poor manufactured quality and that reacting to individual items inside and outside specification was counter-productive.\n\nHe, therefore, argued that quality engineering should start with an understanding of the [[cost of poor quality]] in various situations. In much conventional [[industrial engineering]] the [[cost of poor quality]] is simply represented by the number of items outside specification multiplied by the cost of rework or scrap. However, Taguchi insisted that manufacturers broaden their horizons to consided \'\'cost to society\'\'. Though the short-term costs may simply be those of non-conformance, any item manufactured away from nominal would result in some loss to the customer or the wider community through early wear-out; difficulties in interfacing with other parts, themselves probably wide of nominal; or the need to build-in safety margins. These losses are [[externalities]] and are usually ignored by manufacturers. In the wider economy the [[Coase Theorem]] predicts that they prevent markets from operating efficiently. [[Genichi Taguchi|Taguchi]] argued that such losses would inevitably find their way back to the originating corperation (in an effect similar to the [[tragedy of the commons]]) and that by working to minimise them, manufacturers would enhance brand reputation, win markets and generate profits.\n\nSuch losses are, of course, very small when an item is near to nominal. [[Donald J. Wheeler]] characterised the region within specification limits as where we \'\'deny that losses exist\'\'. As we diverge from nominal, losses grow until the point where \'\'losses are too great to deny\'\' and the specification limit is drawn. All these losses are, as [[W. Edwards Deming]] would describe them, ...\'\'unknown and unknowable\'\' but [[Genichi Taguchi|Taguchi]] wanted to find a useful way of representing them within [[statistics]]. Taguchi specified three situations:\n\n#Larger the better (for example, agricultural yield);\n#Smaller the better (for example, [[carbon dioxide]] emissions); and\n#On-target, minimum-variation (for example, a mating part in an assembly).\n\nThe first two cases are represented by simple [[monotonic function|monotonic]] [[loss function]]s. In the third case, Taguchi adopted a squared-error [[loss function]] on the grounds:\n\n*It is the first symmetric term in the [[Taylor series]] expansion of any reasonable, real-life [[loss function]], and so is a \"first-order\" approximation;\n*Total loss is measured by the [[varian]]. As [[varian]] is additive it is an attractive model of cost; and\n*There was an established body of [[statistical theory]] around the use of the [[least squares]] principle.\n\nThe squared-error [[loss function]] had been used by [[John von Neumann]] and [[Oskar Morgenstern]] in the [[1930s]]. \'\'There is a theorem I think - help appreciated\'\'\n\nThough much of this thinking is endorsed by [[statistician]]s and [[economist]]s in general, [[Genichi Taguchi|Taguchi]] extended the argument to insist that industrial experiments seek to maximise an appropriate \'\'signal to noise ratio\'\' representing the magnitude of the [[mean]] of a process, compared to its variation. Most [[statistician]]s believe [[Genichi Taguchi|Taguchi]]\'s \'\'signal to noise ratios\'\' to be effective over too narrow a range of applications and they are generally deprecated.\n\n===Off-line quality control===\n\n[[Genichi Taguchi|Taguchi]] realised that the best opportunity to eliminate variation is during design of a product and its manufacturing process ([[Taguchi\'s rule for manufacturing]]). Consequently, he developed a strategy for quality engineering that can be used in both contexts. The process has three stages:\n\n#System design;\n#Parameter design; and\n#Tolerance design.\n\n====System design====\n\nThis is design at the conceptual level involving [[creativity]] and [[innovation]].\n\n====Parameter design====\n\nOnce the concept is established, the nominal values of the various dimensions and design parameters need to be set, the [[detailed design]] phase of conventional engineering. In [[1802]], philosopher [[William Paley]] had observed that the [[inverse-square law]] of [[gravitation]] was the only law that resulted in stable orbits if the planets were perturbed in their motion. [[William Paley|Paley]]\'s understanding that [[engineering]] should aim at designs robust against variation led him to use the phenomenon of [[gravitation]] as an [[arguments for the existence of God|argument for the existence of God]]. [[William Sealey Gosset]] in his work at the [[Guinness]] brewery suggested as early as the beginning of the [[20th century]] that the company might breed strains of barley that not only yielded and malted well but whose characteristics were robust against variation in the different soils and climates in which they were grown. [[Genichi Taguchi|Taguchi]]\'s radical insight was that the exact choice of values required is under-specified by the performance requirements of the system. In many circumstances, this allows the parameters to be chosen so as to minimise the effects on performance arising from variation in manufacture, environment and cumulative damage. This approach is often known as \'\'robust design\'\'.\n\n====Tolerance design====\n\nWith a successfully completed \'\'parameter design\'\', and an understanding of the effect that the various parameters have on performance, resources can be focused on reducing and controlling variation in the critical few dimensions (see [[Pareto principle]]).\n\n===Design of experiments===\n\n[[Genichi Taguchi|Taguchi]] developed much of his thinking in isolation from the school of [[Ronald A. Fisher|R. A. Fisher]], only coming into direct contact in [[1954]]. His framework for [[design of experiments]] is idioyncratic and often flawed but contains much that is of enormous value. He made a number of innovations.\n\n====Outer arrays====\n\nIn his later work, [[Ronald A. Fisher|R. A. Fisher]] had started to consider the prospect of using [[design of experiments]] to understand variation in a \'\'wider inductive basis\'\'. [[Genichi Taguchi|Taguchi]] sought to understand the influence that parameters had on variation, not just on the mean. He contended, as had [[W. Edwards Deming]] in his discussion of [[analytic studies]], that conventional [[sampling (statistics)|sampling]] is inadequate here as there is no way of obtaining a [[simple random sample|random sample]] of future conditions. In conventional [[design of experiments]], variation between experimental replications is a nuisance that the experimenter would like to eliminate whereas, in [[Genichi Taguchi|Taguchi]]\'s thinking, it is a central object of investigation.\n\n[[Genichi Taguchi|Taguchi]]\'s innovation was to replicate each experiment by means of an [[outer array]], itself an [[orthogonal array]] that seeks deliberately to emulate the sources of variation that a product would encounter in reality. This is an example of [[judgement sampling]]. Though [[statistician]]s following in the Shewhart-Deming tradition have embraced outer arrays, many academics are still sceptical. An alternative approach proposed by [[Ellis R. Ott]] is to use a [[chunk variable]].\n\n====Management of interactions====\n\nMany of the [[orthogonal arrays]] that [[Genichi Taguchi|Taguchi]] has advocated are [[saturated]] allowing no scope for [[estimation]] of [[interaction (statistics)|interaction]]s. This is a continuing topic of controversy.\n\n*Followers of [[Genichi Taguchi|Taguchi]] argue that the designs offer rapid results and that [[interaction (statistics)|interaction]]s can be eliminated by proper choice of quality characteristic and by transforming the data. That notwithstanding, a [[confirmation experiment]] offers protection against any residual interactions.\n\n*Western statisticians argue that [[interaction (statistics)|interaction]]s are part of the real world and that Taguchi\'s arrays have complicated [[alias structure]]s that leave [[interaction (statistics)|interaction]]s difficult to disentangle. [[George Box]], and others, have argued that a more effective and efficient approach is to use [[sequential assembly]].\n\n====Analisa percobaan====\n\n[[Genichi Taguchi|Taguchi]] ngawanohkeun sababaraha metoda keur analisa hasil percobaan kaasup ngalarpkeun novel [[analisa varian]] sarta \'\'[[minute analysis|analisa menit]]\'\'. Saeutik tina pagaweanana geus di-validasai ku [[statistician|statistikawan]] urang Kulon.\n\n==Assessment==\n\n[[Genichi Taguchi]] has made seminal and valuable methodological innovations in [[statistics]] and [[engineering]], within the Shewhart-Deming tradition. His emphasis on \'\'loss to society\'\'; techniques for investigating variation in experiments and his overall strategy of system, parameter and tolerance design have been massively influential in improving manufactured quality worldwide. Much of his work was carried out in isolation from the mainstream of Western [[statistics]] and, while this may have facilitated his creativity, much of the technical detail of \'\'Taguchi methods\'\' is flawed.\n\n==Other statisticians working on \'\'Taguchi methods\'\'==\n\n*N. Logothetis\n*[[Madhav Phadke]]\n*[[Yuin Wu]]\n\n==Pustaka==\n\n*León, R V; Shoemaker, A C & Kacker, R N (1987) Performance measures independent of adjustment: an explanation and extension of Taguchi\'s signal-to-noise ratios (with discussion), \'\'Technometrics\'\' vol 29, pp253-285\n* Moen, R D; Nolan, T W & Provost, L P (1991) \'\'Improving Quality Through Planned Experimentation\'\' ISBN 0070426732\n*Nair, V N (\'\'ed.\'\') (1992) Taguchi\'s parameter design: a panel discussion, \'\'Technometrics\'\' vol34, pp127-161','/* Loss functions */',13,'Budhi','20041224105004','',0,0,1,0,0.15984751571,'20050316081936','79958775894995'); INSERT INTO cur VALUES (1531,0,'Outlier','Dina [[statistik]], \'\'\'outlier\'\'\' nyaeta hiji observasi nu jauh tina [[data set|data]] nu keur ditempo.\n\nHarti \"jauh tina\" di hal ieu nyaeta:\n:kurang ti \'\'Q1\'\' − 1.5 × \'\'IQR\'\' \'\'\'atawa\'\'\' leuwih ti \'\'Q3\'\' + 1.5 × \'\'IQR\'\'\nnumana \'\'Q1\'\' sarta \'\'Q3\'\' [[quartile|kuartil]] kahiji jeung katilu, sarta \'\'IQR\'\' [[interquartile range]] (sarua jeung \'\'Q3\'\' − \'\'Q1\'\').\n\nNilai ieu ngahartikeun yen hartina aya dina \"jero pager\", saluareun eta observasi bisa dingaranan\'\'\'mild outlier\'\'\'.\n\n\'\'\'Outliers ekstrim\'\'\' nyaeta observasi ayana \'\'saluareun pager\'\':\n:kurang ti \'\'Q1\'\' − 3 × \'\'IQR\'\' \'\'\'atawa\'\'\' leuwih ti \'\'Q3\'\' + 3 × \'\'IQR\'\'\n\nDina kasus data [[sebaran normal|kasebar normal]], make harti di luhur, ngan 1 tina 150 observasi bakal aya \'\'mild outlier\'\' sarta ngan 1 tina 425,000 aya \'\'outlier ekstrim\'\'.\n\n\'\'Outliers\'\' ilaharna merlukeun perhatian saprak nembongkeun masalah dina [[sampling (statistics)|sampling]] atawa kumpulan data atawa transkrip. Alternatipna, outlier bisa jadi hasil, contona, respon nu teu umum kana [[treatment|\'\'perlakuan\'\']] nu ditempo, nu jadi perhatian \'\'peneliti\'\'.\n\nTempo oge: [[box plot]], [[Studentized residual]]','',13,'Budhi','20040908031302','',0,0,0,0,0.710314113978,'20040908031302','79959091968697'); INSERT INTO cur VALUES (1532,0,'Taguchi_methods','#REDIRECT [[Métode Taguchi]]\n','Taguchi methods dipindahkeun ka Métode Taguchi',3,'Kandar','20040904035852','',0,1,0,1,0.187542327854356,'20040904035852','79959095964147'); INSERT INTO cur VALUES (1533,0,'Ahmad_H._Zewail','\'\'\'Ahmad Hassan Zewail\'\'\' ([[Basa Arab]]: أحمد زويل) (wedal [[26 Pébruari]] [[1946]]) [[kimia|kimiawan]] urang [[Mesir]], dileler [[Hadiah Nobel/Kimia|Hadiah Nobel widang Kimia]] taun [[1999]] pikeun karyana ngeunaan [[fémtokimia]]. Lahir di [[Damanhur]] (60 km kidul-wétaneun [[Iskandariah]]) sarta digedékeun di [[Disuq]], anjeunna nampa gelar kahijina ti [[Universitas Iskandariah]] méméh pindah ka [[United States|US]] pikeun ngaréngsékeun PhD-na di [[University of Pennsylvania]]. Sanggeus sababaraha karya posdoktorat di [[University of California, Berkeley|UC Berkeley]], anjeunna dileler a faculty appointment di [[Caltech]] taun 1976, where he has remained since. In 1990 he was made the first \"[[Linus Pauling]] Chair in Chemical Physics\".\n\nZewail\'s key work has been as the pioneer of femtochemistry - nyéta ulikan [[réaksi kimiawi]] na [[fémtodetik]]. Migunakeun téhnik [[laser]] nu cepet (consisting of ultrashort laser flashes), téhnik ieu bisa ngagambarkeun réaksi dina tingkat [[atom]]ik. It can be viewed as a highly sophisticated form of [[Flash (photo)|flash photography]].\n\nTaun 1999, Zewail jadi urnag Mesir katilu nu nampa Hadiah Nobel, nuturkeun [[Anwar Sadat]] (1978 in Peace) jeung [[Naguib Mahfouz]] (1988 widang Sastra). Pangleler internasional séjénna di antarana [[Wolf Prize in Chemistry|Wolf Prize]] (1993) jeung [[Robert A. Welch Award]] (1997). Taun 1999 anjeunna nampa panghargaan nagara pangluhurna, the [[Grand Collar of the Nile]].\n\n[[en: Ahmed H. Zewail]] [[fr:Ahmed H. Zewail]]\n\n[[Category:Nobel Prize in Chemistry winners|Zewail, Ahmed H.]]','',3,'Kandar','20040904042510','',0,0,0,0,0.520298764352,'20040904042510','79959095957489'); INSERT INTO cur VALUES (1534,0,'Ahmed_H._Zewail','#REDIRECT [[Ahmad H. Zewail]]\n','Ahmed H. Zewail dipindahkeun ka Ahmad H. Zewail',3,'Kandar','20040904042227','',0,1,0,1,0.922016033830136,'20040904042227','79959095957772'); INSERT INTO cur VALUES (1535,0,'Kalsium','\n\n\n\n \n\n\n\n \n\n\n\n\n\n\n\n \n \n \n\n \n\n \n\n \n\n \n\n\n\n \n\n \n\n \n \n\n \n\n \n\n\n\n \n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n \n\n \n\n\n\n \n\n\n\n\n\n\n\n
\n\n\n\n\n\n
[[potassium]] – \'\'\'calcium\'\'\' – [[scandium]]
[[Magnesium|Mg]]
\'\'\'Ca\'\'\'
[[Strontium|Sr]]  
 
 
[[Image:Ca-TableImage.png]]
\n
[[Tabel periodik (baku)|Tabel lengkep]]
\n
\'\'\'Umum\'\'\'
[[Daptar unsur dumasar ngaran|Ngaran]], [[Daptar unsur dumasar lambang|Lambang]], [[Daptar unsur dumasar wilangan|Wilangan]]Kalcium, Ca, 20
[[dérét tabel periodik|Dérét]] [[logam taneuh alkali]]
[[Golongan tabel periodik|Golongan]], [[periode tabel periodik|Periode]], [[Blok tabel periodik|Blok]][[unsur golongan 2|2 (IIA)]], [[unsure periode 4|4]], [[orbital atomik|s]]
[[Density]], [[Mohs hardness scale|Hardness]] 1550 [[kilogram per cubic meter|kg/m3]], 1.75
[[color|Appearance]] bodas pérak
[[Image:Ca,20.jpg|125px|]]
\'\'\'Sipat atomik\'\'\'
[[Beurat atomik]] [[1 E-26 kg|40.078 amu]]
[[Radius atomik]] (calc.) 180 (194) [[picometer|pm]]
[[Radius kovalén]] 174 pm
[[Radius van der Waals]] no information
[[Konfigurasi éléktron]] [[[Argon|Ar]]]4s2
[[éléktron|e]]- \'s per [[energy level]]2, 8, 8, 2
[[Oxidation state]]s ([[Oxide]]) 2 (strong [[Basa (kimia)|basa]])
[[Struktur kristal]] Cubic face centered
\'\'\'Sipat fisik\'\'\'
[[Wujud zat]] padet ([[magnetisme|paramagnetik]])
[[Titik lééh]] 1115 [[Kelvin|K]] (1548°[[Fahrenheit|F]])
[[Titik golak]] 1757 K (2703°F)
[[Volume molar]] 26.20 [[scientific notation|×]]10-6 [[cubic meter per mole|m3/mol]]
[[Panas nguap]] 153.6 [[kilojoule per mole|kJ/mol]]
[[Panas fusi]] 8.54 kJ/mol
[[Tekenan uap]] 254 [[Pascal (unit)|Pa]] at 1112 K
[[Speed of sound]] 3810 [[meter per second|m/s]] at 293.15 K
\'\'\'Rupa-rupa\'\'\'
[[Éléktronégativiti]] 1.00 ([[skala Pauling]])
[[Kapasitas panas spésifik]] 632 [[joule per kilogram-kelvin|J/(kg*K)]]
[[Konduktivitas listrik]] 29.8 106/(m·[[ohm]])
[[Konduktivitas panas]] 201 [[watt per meter-kelvin|W/(m*K)]]
1st [[poténsial ionisasi]] 589.8 kJ/mol
2nd ionization potential 1145.4 kJ/mol
3rd ionization potential 4912.4 kJ/mol
\'\'\'Most stable isotopes\'\'\'
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
[[Isotope|iso]][[natural abundance|NA]][[half-life]] [[decay mode|DM]][[decay energy|DE]] [[mega|M]][[electron volt|eV]][[decay product|DP]]
40Ca\'\'\'96.941%\'\'\'Ca is [[stable isotope|stable]] with 20 [[neutron]]s
41Ca[[synthetic radioisotope|{syn.}]][[1 E12 s|103,000 y]][[electron capture|ε]]0.42141[[Potassium|K]]
42Ca0.647%Ca is stable with 22 neutrons
43Ca0.135%Ca is stable with 23 neutrons
44Ca2.086%Ca is stable with 24 neutrons
46Ca0.004%Ca is stable with 26 neutrons
48Ca0.187%[[1 E19 s and more|>6×1018 y]][[beta emission|β-]]4.27248[[Titanium|Ti]]
\n
[[SI]] units & [[standard temperature and pressure|STP]] are used except where noted.
\n\'\'\'Kalsium\'\'\' ngarupakeun [[unsur kimiawi]] na [[tabel periodik]] nu lambangna \'\'\'Ca\'\'\' sarta [[wilangan atom]] 20. Kalsium is a soft grey [[alkaline earth metal]] nu dipaké salaku agén pang[[réduksi]] na ékstraksi [[thorium]], [[zirconium]], jeung [[uranium]]. Unsur ieu ogé mangrupa unsur kalima nu paling ngaleuyah na kulit Marcapada. Penting pikeun [[organisme]] hirup, utamana dina fisiologi sél.\n\n== Notable characteristics ==\nCalcium is a rather hard element that is purified by [[electrolysis]] from [[calcium fluoride]] that burns with a yellow-red flame and forms a white [[nitride]] coating when exposed to air. It reacts with water displacing hydrogen and forming calcium hydroxide.\n\n== Applications ==\nCalcium is an important component of a [[healthy diet]]. Its minor deficit can affect bone and teeth formation. Its excess can lead to [[kidney stone]]s. [[Vitamin D]] is needed to absorb calcium. [[Dairy product]]s are an excellent source of calcium. \n\nFor more information about Ca in living nature, see [[calcium in biology]].\n\nOther uses include:
\n*Reducing agent in the extraction of other metals such as uranium, zirconium, and thorium.\n*Deoxidizer, desulfurizer, or decarburizer for various [[Iron|ferrous]] and nonferrous [[alloy]]s. \n*Alloying agent used in the production of aluminum, beryllium, copper, lead, and magnesium alloys.\n\n== History ==\n([[Latin]] calx, [[calcium oxide|lime]]) Lime was prepared and used by the Romans as early as the [[1st century]], but calcium was not discovered until [[1808]]. After learning that [[Jons Jacob Berzelius|Berzelius]] and [[Magnus Martin Pontin|Pontin]] prepared calcium [[amalgam]] by electrolyzing lime in [[mercury (element)|mercury]], Sir [[Humphry Davy]] was able to isolate the impure metal.\n\n== Occurrence ==\nCalcium is the fifth most abundant element in the earth\'s crust (forming more than 3%) and is an essential part of leaves, bones, teeth, and shells. Due to its chemical reactivity with air and water, calcium is never found in nature unbound to other elements, except in living organisms where Ca2+ plays a key role in cell physiology. This metallic element is found in quantity in [[limestone]], [[gypsum]], and [[fluorite]]. [[Apatite]] is the fluorophosphate or chlorophosphate of calcium. [[Electrolysis]] of molten [[calcium chloride]] (CaCl2) can be used to isolate pure calcium.
\n\'\'Isolation\'\' (* follow):
\n[[cathode]]: Ca2+* + 2[[electron|e]]- --> Ca
\n[[anode]]: Cl-* --> ½Cl2 ([[gas]]) + e-\n\n== Compounds ==\n[[Quicklime]] (Ca[[oxygen|O]]) is used in many chemical refinery processes and is made by heating and carefully adding water to [[limestone]]. When CaO is mixed with sand it hardens into a [[Mortar (masonry)|mortar]] and is turned into [[plaster]] by [[carbon dioxide]] uptake. Mixed with other compounds, CaO forms an important part of [[Portland cement]]. \n\nWhen water percolates through limestone or other soluble [[carbonate]] rocks, it partially disolves part of the rock and causes cave formation and characteristic [[stalactite]]s and [[stalagmite]]s and also forms [[hard water]]. Other important calcium compounds are [[calcium nitrate|nitrate]], [[calcium sulfide|sulfide]], [[calcium chloride|chloride]], [[calcium carbide|carbide]], [[calcium cyanamide|cyanamide]], and [[calcium hypochlorite|hypochlorite]].\n\n== Isotop ==\nKalsium boga genep [[isotop]] stabil, dua di antarana aya di alam: Ca-40 stabil jeung Ca-41 [[radioaktif]] nu [[umur-satengah]]na = 103.000 taun. 97% unsur ieu aya dina wujud Ca-40. Ca-40 is one of the daughter products of K-40 decay, along with Ar-40. While [[K-Ar dating]] has been used extensively in the [[geology|geological]] sciences, the prevalence of Ca-40 in nature has impeded its use in dating. Techniques using [[mass spectrometry]] and a double spike isotope dilution have been used for [[Potassium|K]]-Ca age dating. Unlike cosmogenic isotopes that are produced in the [[Earth\'s atmosphere|atmosphere]], Ca-41 is produced by [[neutron]] activation of Ca-40. Most of its production is in the upper meter or so of the soil column where the cosmogenic neutron flux is still sufficiently strong. Ca-41 has received much attention in stellar studies because Ca-41 decays to K-41, a critical indicator of solar-system anomalies. \n\n\'\'Temp ogé\'\': [[disorders of calcium metabolism]]\n\n==Tumbu kaluar==\n*[http://www.webelements.com/webelements/elements/text/Ca/index.html WebElements.com – Kalsium]\n*[http://environmentalchemistry.com/yogi/periodic/Ca.html EnvironmentalChemistry.com – Kalsium]\n\n[[Category:Unsur kimiawi]]\n[[Category:Logam]]\n\n[[cs:V%C3%A1pn%C3%ADk]] [[de:Calcium]] [[en:Calcium]] [[es:Calcio]] [[eo:Kalcio]] [[et:Kaltsium]] [[fr:Calcium]] [[it:Calcio (metallo)]] [[nl:Calcium]] [[ja:カルシウム]] [[pl:Wapń]] [[ru:Кальций]] [[sl:kalcij]] [[sv:Kalcium]]','/* Isotopes */',3,'Kandar','20040904045404','',0,0,0,0,0.623244793445,'20050203153547','79959095954595'); INSERT INTO cur VALUES (1536,0,'Odds','In [[probability theory]] and [[statistics]] the \'\'\'odds\'\'\' in favor of an event or a proposition are the quantity \'\'p\'\'/(1 − \'\'p\'\'), where \'\'p\'\' is the probability of the event or proposition. The [[logarithm]] of the odds is the [[logit]] of the probability.\n\nOdds have long been the standard way of representing probability used by [[bookmaker]]s, though the method of presenting odds varies by location.\n\nTaking an event with a 1 in 5 probability of occurring (i.e. 0.2 or 20%), then the odds are 0.2/0.8=\'\'\'0.25\'\'\'. If you [[Fixed-odds gambling|bet]] 1 at fair odds and the event occurred, you would receive back 4 plus your original 1 stake. This would be presented by a British bookmaker as odds of 4 to 1 against (written as 4/1), by a European bookmaker as 5.0 to include the returned stake, and by an American bookmaker as +400 representing the gain from a 100 stake.\n\nBy contrast, for an event with a 4 in 5 probability of occurring (i.e. 0.8 or 80%), then the odds are 0.8/0.2=\'\'\'4\'\'\'. If you bet 4 at fair odds and the event occurred, you would receive back 1 plus your original 4 stake. This would be presented by a British bookmaker as odds of 4 to 1 on (written as 1/4), by a European bookmaker as 1.25 to include the returned stake, and by an American bookmaker as −400 representing the stake necessary to gain 100.\n\nThe odds are a [[ratio]] of probabilities; an [[odds ratio]] is a ratio of odds, that is, a ratio of ratios of probabilities. Odds-ratios are often used in analysis of [[clinical trial]]s.\n\n[[Category:Probability theory]]\n[[Category:Statistics]]','',13,'Budhi','20040904054642','',0,0,0,1,0.773730293742,'20040904054642','79959095945357'); INSERT INTO cur VALUES (1537,0,'Rasio_ganjil','\'\'\'Rasio ganjil\'\'\' nyaeta ukuran statistik, bagean penting dina [[Bayesian statistics|statistik Bayes]] sarta [[logistic regression|régrési logistik]].\n\nRasio ganjil diartikeun salaku rasio hiji kajadian [[odds|ganjil]] dina hiji grup kana kaganjilan nu kajadian dina grup sejen, atawa estimasi data dumasar kana rasio. Grup ieu bisa awewe jeung lalaki, grup percobaan sarta [[control group|grup kontrol]], atawa [[dichotomy|klasifikasi nu ngabingungkeun]]. Maka lamun kamungkinan kajadian unggal grup \'\'p\'\' jeung \'\'q\'\' mangka rasio-ganjil nyaeta\n\n:{ p/(1-p) \\over q/(1-q)}=\\frac{\\;p(1-q)\\;}{\\;(1-p)q\\;}.\n\n[[logarithm|Logaritma]] rasio ganjil ngarupakeun beda [[logit]] tina [[probability|probabiliti]].\n\n[[logistic regression|Logistic régrési]] loba dipake dina widang kadokteran jeung panalungtikan élmu sosial, hartina \'\'rasio-ganjil\'\' ilahar dipake geus ngagambarkeun sababaraha bentuk [[clinical trial|percobaan klinis]], saperti [[case-controlled trial]], sarta dina [[survey research]].','',13,'Budhi','20041224225922','',0,0,0,0,0.911659103311,'20041224230023','79958775774077'); INSERT INTO cur VALUES (1538,0,'Jajal_pamanggih','\'\'\'Jajal pamanggih\'\'\' ngarupakeun [[statistical survey|surveys]] pamanggih make [[sampling (statistics)|sampling]]. Hal ieu dijieun keur ngagambarkeun pamanggih tina populasi ku mere patarosan ka sajumlah leutik anggota populasi sarta nga-ekstrapolasi jawaban kana grup nu leuwih gede.\n\n==Potensi keur kateu-akuratan==\n\n===Margin kasalahan===\n\nSakabeh jajal ngabogaan [[margin kasalahan]], nu ngarupakeun fungsi tina jumlah anggota nu ngajajal. Margin kasalahan ngagambarkeun kamungkinan kasalahan dina proses sampling, tapi teu ngagambarkeun sumber kasalahan, saperti ukuran kasalahan atawa kasalahan dina proses data. Jajal nu mibanda sampel 500 anggota ngabogaan margi kasalahan 4.5% keur estimasi persentese tina sakabeh populasi. Margin kasalahan 4.5% hartina yen 95% tina waktu prosedur nu dipake bakal mere estimasi dina 4.5% persentase nu keur di-estimasi.\n\nSaprak anggota nu milu dina jajal nolak, sampel jajal teu ngagambarkeun sampel dina populasi, sarta karakter matematikna ditandaan ku beda tina populasi. Margin kasalahan beda jeung persentase estimasi, sarta persentase estimasi tanda beda tina populasi, margin kasalahan dina hasil jajal teu ngagambarkeun populasi nu sabenerna.\n\n===Kalimah patarosan===\n\nMilih kalimah sarta urutan patarosan dina jajal pamanggih kacida perlu, ieu bisa mangaruhan kana hasil jajal pamanggih. Thus comparisons between polls often boil down to the wording of the question.\nOne way in which pollsters attempt to minimize this effect is to ask the same set of questions over time, in order to track changes in opinion. The most effective controls, used by [[attitude]] researchers, are: \n\n* asking enough questions to allow all aspects of an issue to be covered and to control effects due to the form of the question (such as positive or negative wording), the adequacy of the number being established quantitatively with [[psychometrics|psychometric]] measures such as reliability coefficients, and\n\n* analyzing the results with psychometric techniques which synthesize the answers into a few reliable scores and detect ineffective questions.\n\nThese controls are not widely used in the polling industry.\n\n===Nonrepresentative samples===\n\nAnother source of error is the deliberate or accidental use of nonrepresentative samples. For example, when home telephones were rare, telephone sampling had a built-in error because most of those surveyed were well-to-do.\n\nPeople asked to participate in opinion polls also have the right to refuse; this means that the sample is self-selected and consequently a [[nonprobability sampling|non-probability sample]]. The validity of the results and of the statistical techniques used to derive characteristics of the sample such as the margin of error are therefore highly questionable.\n\n==Polling organizations==\n\nThere are many polling organizations. The most famous is the [[Gallup poll]], created by [[George Gallup]].\n\nOther major polling organizations in the United States include:\n:[[Quinnipiac Polls]], run by the University of Connecticut, and started as a student project.\n:The [[Pew Charitable Trusts]] conducts polls concentrating on media and political beliefs.\n:The [[Harris Poll]]\n:[[Nielsen Ratings]], virtually always for television.\n\nAll the major television networks, alone or in conjunction with the largest newspapers or magazines, in virtually every country with elections, operate polling operations, alone or in groups. \n\nThe best-known failure of opinion polling to date in the United States was the prediction that [[Thomas Dewey]] would defeat [[Harry S. Truman]] in the [[U.S. presidential election, 1948|1948 Presidential election]]. Major polling organizations, including Gallup and the [[Roper Center]], indicated a landslide victory for Dewey.\n\n==Tempo oge==\n* [[Exit poll]]\n* [[interval kapercayaan]]\n* [[push poll]]\n* [[VCIOM|All-Russia Center for the Study of Public Opinion]]\n\n[[Category:Psychometrics]]','/* Tempo oge */',13,'Budhi','20041225044335','',0,0,1,0,0.478027639202,'20041226002643','79958774955664'); INSERT INTO cur VALUES (1539,0,'Order_statistik','Dina [[statistik]], \'\'\'order statistik\'\'\' ka-\'\'n\'\' tina sampel saruna jeung nilai sampel ka-\'\'n\'\' pangleutikna.\n\nContona, lamun nilai sampe nyaeta:\n\n:6, 9, 3, 8\n\nmangka \'\'\'order statistik kadua\'\'\' nyaeta:\n\n:\'\'x\'\'(2) = 6.\n\n\'\'\'Order statistik kahiji\'\'\' (atawa \'\'order statistik pangleutikna\'\') salawasna \'\'minimum\'\' tina sampel. Keur ukuran sampel \'\'n\'\', \'\'\'order statistik ka-\'\'n\'\'\'\'\' (atawa \'\'order statistik panggedena\'\') nyaeta \'\'maximum\'\'.\n\nDina notasi konvensional, ditulis:\n\n:\'\'x\'\'1 = 6\n:\'\'x\'\'2 = 9\n:\'\'x\'\'3 = 3\n:\'\'x\'\'4 = 8\n\n\'\'\'teu make kurung()\'\'\' dina \'\'subscripts\'\', dumasar kana urutan data nu dikumpulkeun, sarta:\n\n:\'\'x\'\'(1) = 3\n:\'\'x\'\'(2) = 6\n:\'\'x\'\'(3) = 8\n:\'\'x\'\'(4) = 9\n\n\'\'\'make kurung ()\'\'\' dina \'\'subscripts\'\', dumasar kana order statistik, dina hal ieu, data disusun dumasar kana naekna order.\n\n\'\'Beda jeung [[quantile]]s....\'\'\n\n==Tempo oge== \n\n* [[Rankit]]\n* [[Box plot]]\n* [[Fisher-Tippett distribution]]','',13,'Budhi','20040906022720','',0,0,0,0,0.698727975925,'20040906022800','79959093977279'); INSERT INTO cur VALUES (1540,0,'Overfitting','Dina [[statistik]], \'\'\'overfitting\'\'\' is fitting a statistical model that has too many parameters. An absurd and false model may fit perfectly if the model has enough complexity by comparison to the amount of data available. Overfitting is generally recognized to be a violation of [[Occam\'s razor]].\n\nA field that has more recently adopted the concept of \'\'\'overfitting\'\'\' is [[machine learning]]. Usually a learning [[algorithm]] is trained using some set of training examples, i.e. exemplary situations for which the desired output is known. The learner is assumed to reach a state where it will also be able to predict the correct output for other examples, thus generalizing to situations not presented during training (based on its [[inductive bias]]). However, especially in cases where learning was performed too long or where training examples are rare, the learner may adjust to very specific random features of the training data, that have no causal relation to the target function. In this process of overfitting, the performance on the training examples still increases while the performance on unseen data becomes worse. \n\nBoh dina [[statistik]] jeung [[machine learning]], in order to avoid overfitting, it is necessary to use additional techniques (e.g. [[cross-validation]], [[early stopping]]), that can indicate when further training is not resulting in better generalization. In [[treatment learning]], a minimum best support value is used to avoid \'\'\'overfitting\'\'\' the model.\n\n[[Category:Statistics]]','',13,'Budhi','20040917065832','',0,0,0,0,0.219790717224,'20040917065832','79959082934167'); INSERT INTO cur VALUES (1541,0,'Page\'s_trend_test','Dina [[statistik]], the \'\'\'Page test\'\'\' for multiple comparisons between ordered alternatives is a generalisation of the test of the [[statistical significance]] of a correlation performed using [[Spearman\'s rank correlation coefficient]]. It is also known as \'\'\'Page\'s trend test\'\'\' or \'\'\'Page\'s \'\'L\'\' test\'\'\'.\n\nThe Page test is useful in the situation where:\n*there are three or more conditions, \n*a number of subjects (or other randomly sampled entities) are all observed in each of them\n*we predict that the observations will have a particular order. \n\nFor example, a number of subjects might each be given three trials at the same task, and we predict that performance will improve from trial to trial. A test of the significance of the trend between conditions in this situation was developed by Page (1963). More formally, the test considers the [[null hypothesis]] that, for \'\'n\'\' conditions, where \'\'m\'\'i is a measure of the [[central tendency]] of the \'\'i\'\'th condition,\n\n
\n\'\'m\'\'1 = \'\'m\'\'2 = \'\'m\'\'3 = ... = \'\'m\'\'n\n
\n\nagainst the [[alternative hypothesis]] that\n\n
\n\'\'m\'\'1 > \'\'m\'\'2 > \'\'m\'\'3 > ... > \'\'m\'\'n\n
\n\nAs such it is more [[statistical power|powerful]] than a test such as the [[Friedman test]] that uses the data in similar ways, but tests for the alternative hypothesis that the central tendencies of the observations under the \'\'n\'\' conditions are different, without specifying their order.\n\nThe procedure for carrying out the Page test, when there are \'\'k\'\' subjects each exposed to \'\'n\'\' conditions, is as follows:\n*Arrange the \'\'n\'\' conditions in the order implied by the alternative hypothesis, and assign each of them a rank \'\'Y\'\'i\n*For each of the \'\'k\'\' subjects separately, rank the \'\'n\'\' observations from 1 to \'\'n\'\'.\n*Add the ranks for each condition to give a total \'\'X\'\'i.\n*Multiply \'\'X\'\'i by \'\'Y\'\'i and add all the products together; this sum is called \'\'L\'\'.\n*To test whether there is a significant trend, values of \'\'L\'\' can be compared with those tabulated by Page (1963).\n*Alternatively, the quantity\n\n
\n(12\'\'L\'\' - 3\'\'kn\'\'(\'\'n\'\'+1)2)2/(\'\'kn\'\'2(\'\'n\'\'2-1)(\'\'n\'\'+1))\n
\n:may be compared with values of [[chi-square]]d with one [[degree of freedom]]. This gives a [[two-tailed test]]. The approximation is reliable for more than 20 subjects with any number of conditions, for more than 12 subjects when there are 4 or more conditions, and for any number of subjects when there are 9 or more conditions.\n*If a measure of the overall correlation between the conditions and the data is required, it can be calculated as\n\n
\nrho = 12\'\'L\'\'/\'\'k\'\'(\'\'n\'\'3-\'\'n\'\') - 3(\'\'n\'\'+1)/(\'\'n\'\'-1)\n
\n:if \'\'k\'\'=1, this reduces to the familiar Spearman coefficient.\n\nThe Page test is most often used with fairly small numbers of conditions and subjects. The minimum values of \'\'L\'\' for significance at the .05 level, one-tailed, with three conditions, are 56 for 4 subjects (the lowest number that is capable of giving a significant result at this level), 54 for 5 subjects, 91 for 7 subjects, 128 for 10 subjects, 190 for 15 subjects and 251 for 20 subjects.\n\nA corresponding extension of [[Kendall\'s tau correlation coefficient]] was developed by Jonckheere (1954). \n\n==References==\n*Jonckheere, A. R., (1954). A test of significance for the relation between \'\'m\'\' rankings and \'\'k\'\' ranked categories. \'\'British Journal of Statistical Psychology, 7\'\', 93-100.\n*Page, E. B. (1963). Ordered hypotheses for multiple treatments: A significance test for linear ranks. \'\'Journal of the American Statistical Association, 58\'\', 216-230.','',13,'Budhi','20050101220156','',0,0,1,0,0.96002426276,'20050101220156','79949898779843'); INSERT INTO cur VALUES (1542,0,'Percentile_rank','\'\'\'Rangking persentil\'\'\' tina skor nyaeta persentase skor panghandapna tina [[sebaran frekuensi]]na. Conto, skor uji leuwih ti 90% tina skor nu dicokot tina uju maka bakal disebutkeun dina persentil ka-90.\n\nRangking persentil ilaharna dipake keur ngajelaskeun interpretasi skor dina [[Standardized test|uji standar]]. Lamun sebaran ieu kasebar [[sebaran normal|normal]], rangking persentil bisa dicokot tina [[skor standar]].','',13,'Budhi','20050105000014','',0,0,0,0,0.82988293461,'20050105000014','79949894999985'); INSERT INTO cur VALUES (1543,0,'Paleostatistics','[[Paleontology]] often faces phenomena so vast and complex they can be described only through [[statistics]].\n\nFirst applied to the study of a population in 1662 statistics is today a basic tool for [[natural sciences]] pratictioners, and a solid acquaintance with methods and applications is essential for communication purposes within the scientific community.\n\nThanks to the diffusion of powerful low-cost computers and the availability of many software tools for statistical analysis, data elaboration is now open to a much wider users pool than before. \n\nStatistics offers to paleontology the tools needed to describe and summarize data (base statistics -- [[average]], [[simpangan baku]], [[distributions]]), to stress and characterize relations existing between two sets of data, with reference to one or more [[taxonomic groups]] ([[correlation]] analysis, [[multiple regression]], [[Cluster Analysis]]) and finally allows the testing of ipotheses and the development of new ipotheses from the available data ([[factor analysis]], [[correspondence analysis]]).\n\nA general skill in applying these few methods is enough to set up a basic analysis of both quantitative or semi-quantitative data , as a complement to a traditional palaeontological research.\nStatistical analysis alone on the other hand does not prove anything and its worth is directly dependent on the quality of the data used. Adopting a statistical approach to the data does not push back the paleontologist, and to the countrary turns the paleontologist\'s experience into the one essential component in a well-developed statistical analysis.','',13,'Budhi','20041224105323','',0,0,1,0,0.085015702567,'20041224105323','79958775894676'); INSERT INTO cur VALUES (1544,0,'Statistik_parametrik','\'\'\'Metoda kaputusan statistik parametrik\'\'\' ngarupakeun prosedur matematik keur [[tes hipotesa statistik]] nu nganggap yen sebaran variabel bakal bisa ditaksir ku karakter nu ditempo. [[Analisa varian]] nganggap yen dina kaayaan sebaran [[sebaran normal|normal]] sarta [[varian]] tina sebaran nu dibandingkeun dianggap sarua. [[Pearson product-moment correlation coefficient|Koefisien korelasi momen-produk Pearson]] dianggap normal.\n\nKadangkala tenknik parametrik ngarupakeun hal nu kuat – hal ieu, ku nahankeun tetempoan kana [[statistical power|power]] keur ngalacak beda atawa sarua waktu ieu asumsi kalanggar – sababaraha sebaran ngalanggar asumsi mangka ditandaan salaku [[statistik non-parametrik]], alternatip nu leuwih ilahar dipake keur ngalacak beda atawa sarua.','',13,'Budhi','20050104070246','',0,0,0,0,0.512492903747,'20050104070246','79949895929753'); INSERT INTO cur VALUES (1545,0,'Interpolasi_Pareto','\'\'\'Interpolasi Pareto\'\'\' ngarupakeun metoda [[interpolation|interpolasi]] nonlinier keur manggihkeun [[median]] tina susunan data. Ilahar dipake dina widang [[economics|ekonomi]] keur ngagambarkeun analisa panghasilan. Anggapan nu dipake yen data nuturkeun kurva nu disebut [[Pareto distribution|sebaran Pareto]].\n\nMedian dirumuskeun ku\n\n:{\\rm median}=\\kappa\\,2^{1/\\theta},\n\nnumana parameter κ jeung θ dirumuskeun ku:\n\n:\nK =\n\\left( \n\\frac{P_b - P_a}\n{ \\frac{1}{a^{\\theta}} - \\frac{1}{b^{\\theta}}} \n\\right) ^{ \\frac{1} {\\theta}}\n\n\nsarta\n\n:\n\\theta \\; = \\;\n\\frac{\\log(1-P_a) - \\log(1-P_b)}\n{\\log(b) - \\log(a)}\n\n\nnumana\n\n:\'\'a\'\' = wates handap kategori nu ngandung median \n\n:\'\'b\'\' = wates luhur kategori nu ngandung median \n\n:\'\'P\'\'\'\'a\'\' = proporsi sebaran nu katutup di handapeun wates handap \n\n:\'\'P\'\'\'\'b\'\' = proporsi sebaran nu katutup di handapeun wates handap','',13,'Budhi','20040906024720','',0,0,0,0,0.831668998502,'20040906024745','79959093975279'); INSERT INTO cur VALUES (1546,0,'Pearson_product-moment_correlation_coefficient','Dina [[matematik]], sarta dina sabagean [[statistik]], the \'\'\'[[Karl Pearson|Pearson]] product-moment correlation coefficient\'\'\' (\'\'r\'\') is a measure of how well a [[linear equation]] describes the relation between two variables \'\'X\'\' and \'\'Y\'\' measured on the same object or organism. It is defined as the sum of the products of the [[skor standard]] of the two measures divided by the [[degrees of freedom]]:\n\n: r = \\frac {\\sum z_x z_y}{N - 1}\n\nThe result obtained is equivalent to dividing the [[covariance]] between the two variables by the product of their [[standard deviation]]s. In general the quantity of a [[correlation coefficient]] is the [[square root]] of the [[coefficient of determination]] (\'\'r2\'\'), which is the ratio of explained variation to total variation:\n\n: r^2 = {\\sum (Y\' - \\overline Y)^2 \\over \\sum (Y - \\overline Y)^2}\n\nwhere: \n\n:Y = a score on a [[random variable]] \'\'Y\'\'\n:Y\' = corresponding predicted value of \'\'Y\'\', given the correlation of \'\'X\'\' and \'\'Y\'\' and the value of \'\'X\'\'\n:\\overline Y = [[mean]] of \'\'Y\'\'\n\nThe correlation coefficient adds a sign to show the direction of the relationship. The formula for the Pearson coefficient conforms to this definition, and applies when the relationship is linear.\n\nThe coefficient ranges from -1 to 1. A value of 1 shows that a linear equation describes the relationship perfectly and positively, with all data points lying on the same [[line]] and with \'\'Y\'\' increasing with \'\'X\'\'. A score of -1 shows that all data points lie on a single line but that \'\'Y\'\' increases as \'\'X\'\' decreases. A value of 0 shows that a linear model is inappropriate – that there is no linear relationship between the variables.\n\nThe Pearson coefficient is a statistic which estimates the [[correlation]] of the two given [[random variable]]s.\n\nThe linear equation that best describes the relationship between \'\'X\'\' and \'\'Y\'\' can be found by [[linear regression]]. If \'\'X\'\' and \'\'Y\'\' are both [[normal distribution|normally distributed]], this can be used to \"predict\" the value of one measurement from knowledge of the other. That is, for each value of \'\'X\'\' the equation calculates a value which is the best estimate of the values of \'\'Y\'\' corresponding the specific value of \'\'X\'\'. We denote this predicted variable by \'\'Y\'\'.\n\nAny value of \'\'Y\'\' can therefore be defined as the sum of \'\'Y\'\' and the difference between \'\'Y\'\' and \'\'Y\'\':\n\n:Y = Y^\\prime + (Y - Y^\\prime)\n\nThe [[varian]] of \'\'Y\'\' is equal to the sum of the variance of the two components of \'\'Y\'\':\n\n:s_y^2 = S_{y^\\prime}^2 + s^2_{y.x}\n\nSince the coefficient of determination implies that sy.x2 = sy2(1 − r2) we can derive the identity\n\n:r^2 = {s_{y^\\prime}^2 \\over s_y^2}\n\nThe square of \'\'r\'\' is conventionally used as a measure of the strength of the association between \'\'X\'\' and \'\'Y\'\'. For example, if the coefficient is .90, then 81% of the variance of \'\'Y\'\' is said to be explained by the changes in \'\'X\'\' and the linear relation between \'\'X\'\' and \'\'Y\'\'.\n\n\'\'r\'\' is a [[statistik parametrik]]. It assumes that the variables being assessed are normally distributed. If this assumption is violated, a [[non-parametric statistics|non-parametric]] alternative such as [[Spearman\'s rank correlation coefficient|Spearman\'s ρ]] \'\'may\'\' be more successful in detecting a linear relationship.','',13,'Budhi','20040918230233','',0,0,0,0,0.786918641434,'20040918230233','79959081769766'); INSERT INTO cur VALUES (1547,0,'Pitman-Koopman-Darmois_theorem','#REDIRECT[[exponential family]]','',13,'Budhi','20040904060328','',0,1,0,1,0.962585073878,'20040904060328','79959095939671'); INSERT INTO cur VALUES (1548,0,'Sebaran_Poisson','Dina [[statistik]] jeung [[probability theory]], \'\'\'sebaran Poisson\'\'\' nyaeta [[probability distribution]] [[discrete mathematics|discrete]] (dipanggihkeun ku [[Simeon Poisson|Siméon-Denis Poisson]] ([[1781]]-[[1840]]) sarta di-publikasi-keun, babarengan jeung teori probabiliti, taun [[1838]] dina paperna \'\'Recherches sur la probabilité des jugements en matières criminelles et matière civile\'\') dumasar kana [[variabel acak]] \'\'N\'\' nu diitung, diantara nu sejenna, wilangan kajadian diskrit (kadang kala disebut \"datang\") nu dicokot salila interval [[time]] nu panjang dibere. Probabiliti numana kajadian \'\'k\'\' pasti (\'\'k\'\' salila [[natural number]] kaasup 0, \'\'k\'\' = 0, 1, 2, ...) nyaeta:\n\n:P(N=k)=\\frac{e^{-\\lambda}\\lambda^k}{k!}.\n\nNumana:\n* {e^{}} nyaeta [[e (mathematical constant)|dumasar kana logaritma natural ]] ({e^{}} = 2.71828...),\n* {k!} nyaeta [[factorial]] of {k},\n* {\\lambda} nyaeta [[real number]] positip, sarua jeung wilangan ekspektasi kajadian nu kajadian salila dina interval waktu. Keur contona, lamun kajadian rata-rata unggal [[minute]], jeung anjeun museurkeun jumlah kajadian dina interval 10 menit , anjeun bisa make model sebaran Poisson ku {\\lambda}=5.\n\n==Proses Poisson==\n\nKadangkala {\\lambda} dijadikeun \'\'laju\'\', dina hal ieu, wilangan rata-rata kajadian per satuan waktu. Dina kasus eta, lamun \'\'Nt\'\' ngarupakeun jumlah kajadian samemeh waktu \'\'t\'\' mangka\n\n:P(N_t=k)=\\frac{e^{-\\lambda t}(\\lambda t)^k}{k!},\n\nsarta waktu tunggu \'\'T\'\' ti mimiti kajadian ngarupakeun variabel random \'\'kontinyu\'\' nu mibanda [[sebaran eksponensial]]; [[probability distribution]] ieu bisa disimpulkeun tina kanyataan yen \n\n:P(T>t)=P(N_t=0).\n\nMangsa waktu jadi kalibet, mangka urang mibanda 1-dimensi [[Poisson process]], nu kaasup boh sebaran-Poisson diskrit variabel random nu diitung tina nu datang unggal interval waktu, sarta [[Erlang distribution|Erlang-distributed]] kontinyu waktu tunggu. Mangka [[Poisson process]] dimensi-na leuwih luhur ti 1.\n\n== Kajadian ==\n\nSebaran Poisson diwangun dina pakait jeung [[Poisson process|proses Poisson]]. Ilahar dipake keur rupa-rupa hal nu pakait jeung diskrit alami (saperti hiji kajadian bisa aya dina 0, 1, 2, 3, ... kali salila periode waktu atawa daerah nu geus ditangtukeun) iraha wae kamungkinan eta kajadian bakal aya ngarupakeun hal anu konstan dina waktu atawa [[space|ruang]]. Contona nyaeta :\n* The number of unstable [[atomic nucleus|nuclei]] that decayed within a given period of time in a piece of [[radioactivity|radioactive substance]].\n* The number of cars that pass through a certain point on a road during a given period of time.\n* The number of spelling mistakes a secretary makes while typing a single page.\n* The number of phone calls you get per day.\n* The number of times your [[web server]] is accessed per minute.\n** For instance, the number of edits per hour recorded on Wikipedia\'s [[special:Recentchanges|Recent Changes]] page follows an approximately Poisson distribution.\n* The number of [[road fauna|roadkill]] you find per unit length of road.\n* The number of [[mutation]]s in a given stretch of [[DNA]] after a certain amount of radiation.\n* The number of pine trees per square mile of mixed forest.\n* The number of [[star]]s in a given volume of space.\n* The number of soldiers killed by horse-kicks each year in each corps in the Prussian cavalry (an example made famous by a book of [[Ladislaus Bortkiewicz|Ladislaus Josephovich Bortkiewicz]] ([[1868]]-[[1931]])).\n* The number of [[bomb]]s falling on each square mile of [[London]] during a German air raid in the early part of the [[World War II|Second World War]].\n\n== How does this distribution arise? -- The limit theorem ==\n\n[[Sebaran binomial]] mibanda parameter \'\'n\'\' sarta λ/\'\'n\'\', dina hal ieu, sebaran probabiliti tina jumlah sukses dina \'\'n\'\' percobaan, mibanda probabiliti λ/\'\'n\'\' tina sukses dina unggal percobaan, ngadeukeutan sebaran Poisson mibanda nilai ekspektasi λ salaku \'\'n\'\' ngadeukeutan tak hingga.\n\nHere are the details. First, recall from calculus that\n\n:\\lim_{n\\to\\infty}\\left(1-{\\lambda \\over n}\\right)^n=e^{-\\lambda}.\n\nLet \'\'p\'\' = λ/\'\'n\'\'. Then we have\n\n:\\lim_{n\\to\\infty} P(X=k)=\\lim_{n\\to\\infty}{n \\choose x} p^k (1-p)^{n-k}\n=\\lim_{n\\to\\infty}{n! \\over (n-k)!k!} \\left({\\lambda \\over n}\\right)^k \\left(1-{\\lambda\\over n}\\right)^{n-k}\n\n:=\\lim_{n\\to\\infty} \\underbrace{\\left({n \\over n}\\right)\\left({n-1 \\over n}\\right)\\left({n-2 \\over n}\\right) \\cdots \\left({n-k+1 \\over n}\\right)} \\underbrace{\\left({\\lambda^k \\over k!}\\right)}\\underbrace{\\left(1-{\\lambda \\over n}\\right)^n}\\underbrace{\\left(1-{\\lambda \\over n}\\right)^{-k}}.\n\n\nAs \'\'n\'\' approaches ∞, the expression over the first of the four \\underbrace{\\mathrm{underbraces}} approaches 1; the expression over the second underbrace remains constant since \"\'\'n\'\'\" does not appear in it at all; the expression over the third underbrace approaches \'\'e\'\'−λ; and the one over the fourth underbrace approaches 1.\n\nConsequently the limit is\n\n:{\\lambda^k e^{-\\lambda} \\over k!}.\n\n== Pasipatan ==\n\n[[Nilai ekspektasi]] variabel random nu kasebar Poisson sarua jeung λ sarta ngarupakeun [[varian]]-na. The higher [[moment (mathematics)|moments]] of the Poisson distribution are [[Touchard polynomials]] in λ, whose coefficients have a [[combinatorics|combinatorial]] meaning.\n\nThe most likely value (\"mode\") of a Poisson distributed random variable is equal to the largest integer ≤ λ, which is also written as [[floor function|floor]](λ).\n\nIf λ is big enough (λ > 1000 say), then the [[normal distribution]] with mean λ and standard deviation √ λ is an excellent approximation to the Poisson distribution. If λ > about 10, then the normal distribution is a good approximation if an appropriate [[continuity correction]] is done, i.e., P(\'\'X\'\' ≤ \'\'x\'\'), where (lower-case) \'\'x\'\' is a non-negative integer, is replaced by P(\'\'X\'\' ≤ \'\'x\'\' + 0.5).\n\nIf \'\'N\'\' and \'\'M\'\' are two [[statistical independence|independent]] random variables, both following a Poisson distribution with parameters λ and μ, respectively, then \'\'N\'\' + \'\'M\'\' follows a Poisson distribution with parameter λ + μ.\n\nThe [[moment-generating function]] of the Poisson distribution with expected value λ is\n\n:E\\left(e^{tX}\\right)=\\sum_{k=0}^\\infty e^{tk} P(X=k)=\\sum_{k=0}^\\infty e^{tk} {\\lambda^k e^{-\\lambda} \\over k!} =e^{\\lambda(e^t-1)}.\n\nAll of the [[cumulant]]s of the Poisson distribution are equal to the expected value λ. The \'\'n\'\'th [[factorial moment]] of the Poisson distribution is λ\'\'n\'\'.\n\nThe Poisson distributions are [[infinite divisibility|infinitely divisible]] probability distributions.\n\n==The \"law of small numbers\"==\n\nThe word \'\'\'law\'\'\' is sometimes used as a synonym of [[probability distribution]], and \'\'\'convergence in law\'\'\' means [[convergence in distribution]]. Accordingly, the Poisson distribution is sometimes called the \'\'\'law of small numbers\'\'\' because it is the probability distribution of the number of occurrences of an event that happens rarely but has very many opportunities to happen. \'\'The Law of Small Numbers\'\' is a book by [[Ladislaus Bortkiewicz]] about the Poisson distribution, published in [[1898]]. Some historians of mathematics have argued that the Poisson distribution should have been called the Bortkiewicz distribution.\n\n==Tempo oge==\n\n* [[Compound Poisson distribution]]\n* [[Poisson process]]\n* [[Erlang distribution]] nu ngajelaskeun waktu tunggu salila kajadian n geus kajadian. Keur [[time|temporally]] sebaran kajadian, sebaran Poisson ngarupakeun sebaran probabiliti wilangan kajadian nu bakal kajadian dina waktu nu ditangtukeun, sebaran Erlang nyaeta sebaran probabiliti antara waktu salila kajadian nu ka-\'\'n\'\'.\n\n[[Category:Probability distributions]]\n[[de:Poisson-Verteilung]]\n[[es:distribución de Poisson]]\n[[it:variabile casuale Poissoniana]]\n[[nl:Poissonverdeling]]\n[[pl:Rozk%C5%82ad Poissona]] \n[[zh:泊松分布]]','',0,'133.66.133.191','20041224044347','',0,0,0,0,0.877679089027,'20041224044347','79958775955652'); INSERT INTO cur VALUES (1549,0,'Poisson_process','A \'\'\'Poisson process\'\'\', one of a variety of things named after the French mathematician [[Siméon-Denis Poisson]] (1781 - 1840), is a [[stochastic process]] that assigns to each bounded interval of time or to each bounded region in some space (for example, a Euclidean plane or a 3-dimensional Euclidean space) a random number of \"arrivals\" or \"occurrences\" in such a way that\n\n* The number of arrivals in each interval of time or region in space is a [[random variable]] with a [[Poisson distribution]], and\n\n* The number of arrivals in one interval of time or region in space and the number of arrivals in another disjoint (\'\'non-overlapping\'\') interval of time or region in space are [[statistical independence|independent]] random variables.\n\nTechnically, and perhaps more precisely, one should say each set of finite [[measure (mathematics)|measure]] is assigned such a Poisson-distributed random variable.\n\n===Examples===\n\n* The number of telephone calls arriving at a switchboard during any specified time interval may have a Poisson distribution, and the number of calls arriving during one time interval may be [[statistical independence|statistically independent]] of the number of calls arriving during any other non-overlapping time interval. This is a one-dimensional Poisson process. In simple models, one may assume a constant average rate of arrival, e.g., λ = 12.3 calls per minute. In that case, the [[nilai ekspektasi]] of the number of calls in any time interval is that rate times the amount of time, λ\'\'t\'\'. In messier and more realistic problems, one uses a non-constant rate function λ(\'\'t\'\'). In that case, the expected value of the number of calls between time \'\'a\'\' and time \'\'b\'\' is\n\n::\\int_a^b \\lambda(t)\\,dt.\n\n* The number of bombs falling on a specified area of London in the early days of the Second World War may be a random variable with a Poisson distribution, and the number of bombs falling on two areas of the city that do not overlap may be statistically independent. This is a 2-dimensional Poisson process.\n\n* Astonomers may treat the number of stars in a given volume of space as a random variable with a Poisson distribution, and the numbers of stars in any two or more non-overlapping regions as statistically independent. This is a 3-dimensional Poisson process.\n\n==1-dimensional Poisson processes==\n\nA 1-dimensional Poisson process on the interval from 0 to ∞ (essentially this means that the clock starts at time 0; that is when we begin counting) may thus be viewed as an [[integer]]-valued nondecreasing random function of time \'\'N\'\'(\'\'t\'\') that counts the number of \"arrivals\" before time \'\'t\'\'. Just as a Poisson random variable is characterized by its scalar parameter λ, a Poisson process is characterized by its rate function λ(\'\'t\'\'), which is the [[nilai ekspektasi|expected]] number of \"events\" or \"arrivals\" that occur per unit time. A \'\'homogeneous\'\' Poisson process has a constant rate function λ(\'\'t\'\') = λ. If the rate remains constant, then the number \'\'N\'\'(\'\'t\'\') of arrivals before time \'\'t\'\' distribution has a [[Poisson distribution]] with expected value λ\'\'t\'\'.\n\nLet \'\'X\'\'\'\'t\'\' be the number of arrivals before time \'\'t\'\'. Let \'\'T\'\'\'\'x\'\' be the time of the \'\'x\'\'th arrival, for \'\'x\'\' = 1, 2, 3, ... . (We are using capital \'\'X\'\' and capital \'\'T\'\' for random variables, and lower-case \'\'x\'\' and lower-case \'\'t\'\' for constants, i.e., non-random quantities.) The random variable \'\'X\'\'\'\'t\'\' has a \'\'discrete\'\' probability distribution -- a Poisson distribution -- and the random variable \'\'T\'\'\'\'x\'\' has a \'\'continuous\'\' probability distribution.\n\nClearly the number of arrivals before time \'\'t\'\' is less than \'\'x\'\' if and only if the waiting time until the \'\'x\'\'th arrival is more than \'\'t\'\'. In symbols, the event [ \'\'X\'\'\'\'t\'\' < \'\'x\'\' ] occurs if and only if the event [ \'\'T\'\'\'\'x\'\' > \'\'t\'\' ]. Consequently the probabilities of these events are the same:\n\n:P(X_tt).\n\nThis fact plus knowledge of the Poisson distribution enables us to find the probability distribution of these continuous random variables. In case the rate, i.e., the expected number of arrivals per unit time, remains constant, this is fairly simple. In particular, consider the waiting time until the first arrival. Clearly that time is more than \'\'t\'\' if and only if the number of arrivals before time \'\'t\'\' is a 0. If the rate is λ arrivals per unit time, then we have\n\n:P(T_1>t)=P(X_t=0)=e^{-\\lambda t}.\n\nConsequently, the waiting time until the first arrival has a [[sebaran eksponensial]]. This exponential distribution has expected value 1/λ. In other words, if the average rate of arrivals is, for example 6 per minute, then the average waiting time until the first arrival is (unsurprisingly) 1/6 minute. This exponential distribution is [[memorylessness|memoryless]], i.e. we have\n\n:P(T_1>t+s \\mid T_1>t)=P(T_1>s).\n\nThis says that the [[conditional probability]] that we need to wait, for example, more than another 10 seconds before the first arrival, given that the first arrival has not yet happened after 30 seconds, is no different from the initial probability that we need to wait more than 10 seconds for the first arrival. This is often misunderstood by students taking courses on probability: the fact that P(\'\'T\'\'1 > 40 | \'\'T\'\'1 > 30) = P(\'\'T\'\'1 > 10) does \'\'not\'\' mean that the events \'\'T\'\'1 > 40 and \'\'T\'\'1 > 10 are independent. To summarize: \"memorylessness\" of the probability distribution of the waiting time \'\'T\'\'1 until the first arrival means\n\n:\\mathrm{(Right)}\\ P(T_1>40 \\mid T_1>30)=P(T_1>10).\n\nIt does \'\'not\'\' mean\n\n:\\mathrm{(Wrong)}\\ P(T_1>40 \\mid T_1>30)=P(T_1>40).\n\n(That would be independence. These two events are \'\'not\'\' independent.)\n\n==Characterization of Poisson processes==\n\nIn its most general form, the only two conditions for a 1-dimensional process to be a (not necessarily homogeneous) Poisson process are:\n\n* \'\'\'Orderliness\'\'\': which roughly means limΔ\'\'t\'\' → 0 Pr[\'\'X\'\'\'\'t\'\' + Δ\'\'t\'\' − \'\'X\'\'\'\'t\'\' >1| \'\'X\'\'t + Δ\'\'t\'\' − \'\'X\'\'\'\'t\'\' ≥ 1] = 0 which implies that events don\'t occur simultaneously (but is actually a stronger statement).\n* \'\'\'[[Memorylessness]]\'\'\' (also called evolution without aftereffects): the number of arrivals occurring in any bounded interval of time after time \'\'t\'\' is [[statistical independence|independent]] of the number of arrivals occuring before time \'\'t\'\'.\n\nThese seemingly unrestrictive conditions actually impose a great deal of structure in the Poisson process. In particular, they imply independent exponential (memoryless) interarrival times (with parameter λ for homogeneous processes). Because the interarrival times are [[sebaran eksponensial|exponentially distributed]], the time between the 4th and 9th arrival (for instance) is distributed as the sum of exponential random variables (i.e. 5th order [[sebaran gamma]]). Also, these conditions imply that the probability distribution of the number of events in the interval [a,b), which is also written as \'\'X\'\'\'\'b\'\' − \'\'X\'\'\'\'a\'\' is [[Poisson distribution|Poisson-distributed]], (with parameter λ(\'\'b\'\' − \'\'a\'\') for homogeneous processes).\n\nThis is a sample one-dimensional homogeneous Poisson process, \'\'X\'\'\'\'t\'\'; not to be confused with a density or distribution function.\n
[[image:Sampleprocess.png]]
\'\'Sample homogeneous Poisson process\'\'
\n\n==See also==\n\n[[Compound Poisson distribution]], [[Compound Poisson process]]\n\n[[Category:Stochastic processes]]\n[[es:Proceso de Poisson]]','/* Characterization of Poisson processes */',13,'Budhi','20040918224523','',0,0,0,0,0.754436944031,'20041231123527','79959081775476'); INSERT INTO cur VALUES (1550,0,'Dinamika_populasi','\'\'\'Dinamika Populasi\'\'\' nyaeta pangajaran watesan sarta lilana parobahan dina wilangan, beurat individu sarta komposisi umur individu dina hiji atawa sababaraha [[populasi]], [[biologi]] sarta pangaruh [[environment|lingkungan]] kana eta parobahan.\n\nDinamika populasi ngarupakeun utama utama dina [[mathematical biology|matematik biologi]], nu mibanda sajarah leuwih ti 200 taun. Periode mimiti di-dominasi ku pangajaran [[demography|demograpi]] saperti nu digawekeun ku [[Benjamin Gompertz]] ([[5 Maret]] [[1779]]-[[14 Juli]] [[1865]]) sarta [[Pierre François Verhulst]] ([[28 Oktober]] [[1804]]-[[15 Pébruari]] [[1849]]), nu ngaluskeun turta makekeun model demograpi [[Malthus]].\n\nModel rumusan nu leuwih umum diusulkeun ku [[F.J. Richards]] taun [[1959]], nu make model models Gompertz, Verhulst sarta [[Ludwig von Bertalanffy]] nu nerangkeun kasus husus dina rumusan nu umum.\n[[computer game|Kaulinan komputer]] [[SimCity]] nyoba [[computer simulation|simulasi]] tina sababaraha dinamika populasi.\nDinamika populasi oge dipake keur nalungtik topik saperti [[aging population|umur populasi]] atawa [[population decline|nurunna populasi]].\n\n\'\'Tempo oge\'\': [[System dynamics|dinamika sistim]], [[Volterra-Lotka equations|persamaan Volterra-Lotka]]\n\n[[Category:Fisheries science]]','Pébruari...',38,'Robin Patterson','20050215001904','',0,0,1,0,0.787083719758,'20050215001904','79949784998095'); INSERT INTO cur VALUES (1551,0,'Principal_components_analysis','In [[statistics]], \'\'\'principal components analysis (PCA)\'\'\' is a technique that can be used to simplify a dataset; more formally it is a [[transform]] that chooses a new coordinate system for the data set such that the greatest variance by any projection of the data set comes to lie on the first axis (then called the first principal component), the second greatest variance on the second axis, and so on. PCA can be used for reducing [[dimension]]ality in a dataset while retaining those characteristics of the dataset that contribute most to its [[varian]] by eliminating the later principal components (by a more or less heuristic decision). These characteristics may be the \'most important\', but this is not necessarily the case, depending on the application.\n\nPCA is also called the \'\'\'Karhunen-Loève transform\'\'\' or the \'\'\'Hotelling transform\'\'\' (in honor of [[Harold Hotelling]]). PCA has the speciality of being the optimal [[linear transformation]] for keeping the subspace that has largest variance. However this comes at the price of greater computational requirement, e.g. if compared to the [[discrete cosine transform]]. Unlike other linear transforms, the PCA does not have a fixed set of [[basis vector]]s. Its basis vectors depend on the data set.\n\nThe principal component \'\'\'w\'\'\'1 of a dataset \'\'\'x\'\'\' can be defined as (assuming zero empirical mean, i.e. the empirical mean of the distribution has been subtracted away from the data set).\n\n: \\mathbf{w}_1\n = \\arg\\max_{\\Vert \\mathbf{w} \\Vert = 1} E\\left\\{ \\left( \\mathbf{w}^T \\mathbf{x}\\right)^2 \\right\\}\n(See [[arg max]] for the notation.) With the first k - 1 components, the k-th component can be found by subtracting the first k - 1 principal components from \'\'\'x\'\'\':\n: \\mathbf{\\hat{x}}_{k - 1}\n = \\mathbf{x} -\n \\sum_{i = 1}^{k - 1}\n \\mathbf{w}_i \\mathbf{w}_i^T \\mathbf{x}\nand by substituting this as the new dataset to find a principal component in:\n: \\mathbf{w}_k\n = \\arg\\max_{\\Vert \\mathbf{w} \\Vert = 1} E\\left\\{\n \\left( \\mathbf{w}^T \\mathbf{\\hat{x}}_{k - 1}\n \\right)^2 \\right\\}.\n\nA simpler way to calculate the components \'\'\'w\'\'\'i uses the empirical [[covariance matrix]] of \'\'\'x\'\'\', the measurement vector. By finding the [[eigenvalue]]s and [[eigenvector]]s of the covariance matrix, we find that the eigenvectors with the largest eigenvalues correspond to the dimensions that have the strongest [[correlation]] in the dataset. The original measurements are finally projected onto the reduced [[vector space]]. Note that the eigenvectors X are actually the columns of the matrix V, where X=ULV ′ is the [[singular value decomposition]] of X.\n\nPCA is equivalent to [[empirical orthogonal functions]] (EOF).\n\nPCA is a popular technique in [[pattern recognition]]. However, PCA is not optimized for class separability. An alternative is the [[linear discriminant analysis]], which does take this into account. PCA optimally minimizes reconstruction error under the [[Lp_space | L2 norm]].\n\n== Pseudocode ==\n\n[[Pseudocode]] for PCA using the covariance method.\nSuppose you have \'\'n\'\' data vectors of \'\'d\'\' dimensions each. You want to project your data into a \'\'k\'\' dimensional subspace.\n\n\'\'\'Find the basis vectors\'\'\'\n# Organize your data into column vectors, so you end up with a d \\times n matrix, \'\'D\'\'.\n# Find the empirical mean along each dimension, so you end up with a d \\times 1 empirical mean vector, \'\'M\'\'.\n# Subtract the empirical mean vector \'\'M\'\' from each column of the data matrix \'\'D\'\'. Store mean-subtracted data matrix in \'\'S\'\'.\n# Find the empirical covariance matrix \'\'C\'\' of \'\'S\'\'. C = S \\cdot S^T.\n# Compute and sort by decreasing eigenvalue, the eigenvectors \'\'V\'\' of \'\'C\'\'.\n# Save the mean vector \'\'M\'\'. Save the first \'\'k\'\' columns of \'\'V\'\' as \'\'P\'\'. \'\'P\'\' will have dimension d \\times k. 1 \\leq k \\leq d\n\n== Projecting new data ==\n\nSuppose you have a \'\'d\'\'×1 data vector \'\'D\'\'. Then the \'\'k\'\'×1 projected vector is \'\'v\'\' = PT(D − M).\n\n== Derivation of PCA using the covariance method ==\n\nLet \'\'\'X\'\'\' be a \'\'d\'\'-dimensional random vector expressed as column vector. \nWithout loss of generality, assume \'\'\'X\'\'\' has zero empirical mean.\nWe want to find a d \\times d [[Orthonormal_basis | orthonormal projection matrix]] \'\'\'P\'\'\' such that\n\nY = P^\\top X\n\nwith the constraint that \n\n\\operatorname{cov}(Y) is a [[Diagonal_matrix | diagonal matrix]] and P^{-1} = P^\\top.\n\nBy substitution, and matrix algebra, we get\n\n\n\\begin{matrix}\n\\operatorname{cov}(Y) &=& \\operatorname{E}[YY^\\top]\\\\\n\\ &=& \\operatorname{E}[(P^\\top X) (P^\\top X)^\\top]\\\\\n\\ &=& \\operatorname{E}[(P^\\top X) (X^\\top P)]\\\\\n\\ &=& P^\\top \\operatorname{E}[X X^\\top] P\\\\\n\\ &=& P^\\top \\operatorname{cov}(X) P\n\\end{matrix}\n\n\nWe now have\n\n\n\\begin{matrix}\nP\\operatorname{cov}(Y) &=& P P^\\top \\operatorname{cov}(X) P\\\\\n\\ &=& \\operatorname{cov}(X) P\\\\\n\\end{matrix}\n\n\nRewrite \'\'\'P\'\'\' as d d \\times 1 column vectors, so\n\nP = [P_1, P_2, \\ldots, P_d]\n\nand \\operatorname{cov}(Y) as\n\n\n\\begin{bmatrix}\n\\lambda_1 & 0 & 0 \\\\\n0 & \\ddots & 0 \\\\\n0 & 0 & \\lambda_d\n\\end{bmatrix}\n\n\nSubstituting into equation above, we get\n\n[\\lambda_1 P_1, \\lambda_2 P_2, \\ldots, \\lambda_d P_d] =\n[\\operatorname{cov}(X)P_1, \\operatorname{cov}(X)P_2,\n\\ldots, \\operatorname{cov}(X)P_d]\n\nNotice that in \\lambda_i P_i = \\operatorname{cov}(X)P_i, \'\'\'Pi\'\'\' is an [[Eigenvector | eigenvector]] of \'\'\'X\'\'\'s covariance matrix. Therefore, by finding the eigenvectors of \'\'\'X\'\'\'s convariance matrix, we find a projection matrix \'\'\'P\'\'\' that satisfies the original constraints.\n\n==See also==\n* [[eigenface]]\n* [[transform coding]]\n* [[independent components analysis]]\n* [[singular value decomposition]]\n\n\n[[de:Hauptkomponentenanalyse]]','',13,'Budhi','20040907104438','',0,0,0,0,0.035748037992,'20040907104438','79959092895561'); INSERT INTO cur VALUES (1552,0,'Eror_probabiliti','==Error probabiliti dina tes hipotesis==\n\nDina [[hypothesis testing|tes hipotesis]] dina [[statistik]], dibedakan dua tipe \'\'[[error|eror]]\'\'.\n*[[Type I error|Tipe I eror]] nu nolak [[null hypothesis|null hipotesa]] lamun eta hipotesa bener; ieu ngagambarkuen hasil positip salah.\n*[[Type II error|Tipe II eror]] nu gagal keur nolak null hipotesa nu salah; ieu ngagambarkeun hasil negatip salah.\n\n\'\'\'Eror probabiliti\'\'\' dibedakeun ampir sarua. \n* Keur Tipe I eror, dilambangkeun ku α (alpha) sarta dipikanyaho salaku \'\'ukuran\'\' tina tes sarta 1 minus ngarupakeun [[specificity|husus]] tina tes.\n* Keur Tipe II eror, dilambangkeun ku β (beta) sarta 1 minus ngarupakeun [[Statistical power|power]] atawa 1 minus tina [[sensitivity (tests)|sensitip]] tina tes.\n\n==Eror probabiliti dina model statistik jeung ekonometrik==\n\nLoba [[model]] dina statistik sarta [[econometrics|ekonometrik]] bakal ilahar dipake keur ngurangan beda antara nilai panalungtikan jeung nilai prediksi atawa nilai teori. Beda ieu dipikanyaho salaku \'\'eror\'\', waktu panalungtikan bakal leuwih hade dijelaskeun salaku \'\'[[Errors and residuals in statistics|sesa]]\'\'. \n\nEror bakal jadi [[random variable|variabel random]] sarta mibanda [[probability distribution|distribusi probabiliti]].','/* Eror probabiliti dina model statistik jeung ekonometrik */',13,'Budhi','20041204022925','',0,0,0,0,0.668131993929,'20041204022949','79958795977074'); INSERT INTO cur VALUES (1553,0,'Prosecutor\'s_fallacy','The \'\'\'prosecutor\'s fallacy\'\'\' is a [[logical fallacy|fallacy]] commonly occurring in criminal trials and elsewhere. A [[prosecutor]] has collected some [[evidence]] (for instance a [[DNA]] match) and has an expert testify that the [[probability]] of finding this evidence if the accused were innocent is tiny. The fallacy is committed if one then concludes that the probability of the accused being innocent must be comparably tiny.\n\n==Why this is fallacious: several examples==\n\nA concrete example can make it clear why this reasoning is fallacious. Suppose there is a one-in-a-million chance of a match given that the accused is innocent. The prosector says that means there is only a one-in-a-million chance of innocence. But in a community of 10 million people, one expects about 10 matches by pure chance, and the accused is just one of those ten. That would indicate only a one-in-ten chance of guilt, if no other evidence is available.\n\nConsider for instance the case of [[Sally Clark]], who was accused in [[1998]] of having killed her first child at 11 weeks of age, then conceived another child and killed it at 8 weeks of age. The defense claimed that these were two cases of [[sudden infant death syndrome]]; neither prosecution nor defense offered any other explanations for the deaths. The prosecution had expert [[witness]] [[Roy Meadow|Sir Roy Meadow]] testify that the probability of two children in the same family dying from [[sudden infant death syndrome]] is about 1 in 73 million. To provide proper context for this number, the probability of a mother killing one child, conceiving another and killing that one too, should have been estimated and compared to the 1 in 73 million figure, but it wasn\'t. Ms. Clark was convicted in [[1999]], resulting in a press release by the [[Royal Statistical Society]] which pointed out the mistake. (See link at end of article.) A higher court later quashed Sally Clark\'s conviction, on other grounds, on 29 January 2003. \n\nIn another scenario, assume a rape has been committed in a town, and 20,000 men in the town have their DNA compared to a sample from the crime. One of these men has matching DNA, and at his trial, it is testified that the probability that two DNA profiles match by chance is only 1 in 10,000. This does \'\'not\'\' mean the probability that the suspect is innocent is 1 in 10,000. Since 20,000 men were tested, there were 20,000 opportunities to find a match by chance; the probability that there was at least one DNA match is\n:1 - \\left(1-\\frac{1}{10000}\\right)^{20000} \\approx 86\\%\nwhich is considerably more than 1 in 10,000. (The probability that \'\'exactly\'\' one of the 20,000 men has a match is about 27%, which is still rather high.)\n\nNow consider this case: you win the lottery jackpot. You are then charged with having cheated, for instance with having bribed lottery officials. At the trial, the prosecutor points out that winning the lottery without cheating is extremely unlikely, and that therefore your being innocent must be comparably unlikely. This reasoning is clearly faulty: the prosecutor failed to mention that cheating lottery winners are much more rare than honest winners. \n\nAnother instance of the prosecutor\'s fallacy is sometimes encountered when discussing the origins of [[life]]: the probability of life arising at random out of the physical laws is estimated to be tiny, and this is presented as evidence for a creator, without regard for the possibility that the probability of such a creator could be even tinier.\n\n== Mathematical analysis ==\n\nWe can view finding a person innocent or guilty in mathematical terms as a form of [[binary classification]]. \n\nWe start with a [[thought experiment]]. I have a big bowl with one thousand balls, some of them made of wood, some of them made of plastic. I know that 100% of the wooden balls are white, and only 1% of the plastic balls are white, the others being red. Now I pull a ball out at random, and observe that it is actually white. Given this information, how likely is it that the ball I pulled out is made of wood? Is it 99%? No! Maybe the bowl contains only 10 wooden and 990 plastic balls. Without that information (the \'\'a priori\'\' probability), we cannot make any statement. In this thought experiment, you should think of the wooden balls as \"accused is guilty\" or \"life originated from a creator\", the plastic balls as \"accused is innocent\" or \"life emerged without a creator\", and the white balls as \"the evidence is observed\" or \"life developed\".\n\nThe fallacy can be analyzed using [[conditional probability]]: Suppose E is the observed evidence, and I stands for \"accused is innocent\". We know that P(E|I) (the probability that the evidence would be observed if the accused were innocent) is tiny. The prosecutor wrongly concludes that P(I|E) (the probability that the accused is innocent, given the evidence E) is comparatively tiny. However, P(E|I) and P(I|E) are quite different; using [[Bayes\' theorem]] we see\n:P(I|E) = P(E|I) · P(I) / P(E)\nSo the \'\'a priori\'\' probability of innocence P(I) and the overall probability of the observed evidence P(E) need to be taken into account. If P(I) is much larger than P(E), then P(I|E) can be large as well.\n\nWe can also formulate Bayes\' theorem with [[odds]]:\n:Odds(I|E) = Odds(I) · P(E|I)/P(E|~I)\nWithout knowledge of the \'\'a priori\'\' odds of I, the small value of P(E|I) does not necessarily imply that Odds(I|E) is small. (P(E|~I), the probability that the evidence is observed given the accused is guilty, is assumed to be high.)\n\nThe fallacy lies in the fact that the \'\'a priori\'\' probability of guilt is not taken into account. If this probability is small, then the only effect of the presented evidence is to increase that probability somewhat, but not necessarily dramatically. (In the earlier example of a 10 million city, the presented evidence raises the \'\'a priori\'\' probability of guilt of 1 in 10 million to an \'\'a posteriori\'\' probability of guilt of 1 in 10.)\n\nThe prosecutor\'s fallacy is therefore no fallacy if the \'\'a priori\'\' odds of guilt are assumed to be 1:1. In an [[Bayesian probability|Bayesian]] approach to personal probabilities, where probabilities represent degrees of belief of reasonable persons, this assumption can be justified as follows: a completely unbiased person, without having been shown any evidence and without any prior knowledge, will estimate the \'\'a priori\'\' odds of guilt as 1:1.\n\nIn this picture then, the fallacy consists in the fact that the prosecutor claims an absolutely low probability of innocence, without mentioning that the information he conveniently omitted would have led to a different estimate. \n\nIn legal terms, the prosecutor is operating in terms of a presumption of guilt, something which is contrary to the normal [[presumption of innocence]] where a person is assumed to be innocent unless found guilty. A more reasonable value for the prior odds of guilt might be a value estimated from the overall frequency of the given crime in the general population.\n\n==Defendant\'s fallacy==\n\nThe defendant\'s fallacy (taking the earlier example) would be to say, \"We would expect 10 matches in this city of 10 million people, so this particular piece of evidence suggests there is 90% chance that the accused is innocent. So this evidence cannot be used to point to a conclusion of guilt, and should be excluded.\"\n\nThe problem with the defendant\'s argument is that there may be other available evidence which on its own is also not conclusive. For example if [[CCTV]] cameras surrounding the scene of the crime spotted all one hundred people there at the relevant time, one of which was the accused, then the defendant could claim: \"The photograph suggests a 99% chance that the defendant is innocent. The match suggested a 90% chance of innocence. So the conclusion should be a finding of innocence.\" \n\nWhen the photographic evidence is combined with the match, the two together point strongly towards guilt, since (assuming the chance of being in the photograph and having the match are independent) the chance that the accused is innocent falls to about 0.01%.\n\n==See also==\n\n* [[likelihood]]\n* [[Howland Will forgery trial]]\n* \'\'[[People v. Collins]]\n\n==External links==\n* Press release by the Royal Statistical Society about the Sally Clark case: http://www.rss.org.uk/archive/evidence/sclark.html\n* http://www.colchsfc.ac.uk/maths/dna/discuss.htm\n* http://dna-view.com/profile.htm\n\n[[Category:Logical fallacies]]','',13,'Budhi','20040904061005','',0,0,0,1,0.790611486319,'20041231123527','79959095938994'); INSERT INTO cur VALUES (1554,0,'Pythagorean_expectation','\'\'\'Ekspektasi phitagoras\'\'\' ngarupakeun rumus nu diwangun ku [[Bill James]] keur estimasi lobana \'\'game\'\' dina tim [[baseball]] \"kudu\" meunang dumasar kana jumlah skor jeung aturanna. Watesan ieu asalna tina kasaruaan rumus [[Pythagoras]] nu ngitung panjang \'\'hypotenuse\'\' [[triangle (geometry)|segitiga]] tina panjang dua sisi sejenna.\n\nRumus dasarna nyaeta:\n\n:Win% = \\frac{Runs Scored^2}{Runs Scored^2 + Runs Allowed^2}\n\n%meunang ngarupakeun persentase nu dihasilkeun tina rumus. Saterusna bisa ngalikeun ku jumlah \'\'game\'\' nu dimaenkeun ku unggal tim (kiwari, musim dina [[Major League Baseball|Liga Utama]] aya 162 \'\'game\'\') keur ngitung kudu sabaraha loba dikira-kira meunang dumasar kana nilai jeung aturanna.\n\nSacara empiris, rumus ieu pakait jeugn kumaha \'\'penampilan\'\' tim basebal, sanajan eksponen \'\'1.81\'\' ampir akurat. Hubungan ieu hiji kaputusan nu dipake keur [[runs (baseball statistics)|\'\'runs\'\']] salaku ukuran keur \'\'penampilan\'\' pamaen. Usaha nu geus digawekeun nyaeta manggihkeun eksponen ideal keur rumus, ilahar dipikanyaho ku rumus \'\'pythagenport\'\' (dikumpulkeun ku Clay Davenport) 1.5log((r+ra)/g)+.45 sarta anu kurang kawentar tapi ampir epektip: ((r+ra)/g)^.287, invented by David Smyth. \n\nSacara ilahar dipercaya yen simpangan tina hiji tim ekpektasi nyaeta gumantung kana nasib sarta kualitas [[bullpen]] tim oge kaayaan waktu eta \'\'game\'\' dimaenkeun.\n\n\'\'\'Tempo oge:\'\'\' [[Baseball statistics]], [[Sabermetrics]]\n\n==Tumbu kaluar==\n*[http://www.footballproject.com/story.php?storyid=122 Applying the pythagorean expectation to Football]: Includes a discussion of how the exponent in the formula should be larger the larger the number of points scored per game becomes.','',13,'Budhi','20040910020009','',0,0,0,0,0.252359281877,'20040910020009','79959089979990'); INSERT INTO cur VALUES (1555,0,'Q_test','To apply a \'\'\'Q test\'\'\' for bad data, arrange the data in order of increasing values and calculate Q as defined:\n\n:Q=\\frac{gap}{range}\n\nIf Qcalculated > Qtable then reject the questionable point.\n\n==Table==\nSomeone put the Q table here\n\n==Example==\nFor the data: \n\n:0.189, 0.169, 0.187, 0.183, 0.186, 0.182, 0.181, 0.184, 0.181, 0.177\n\nArranged in increasing order:\n\n:0.169, 0.177, 0.181, 0.181, 0.182, 0.183, 0.184, 0.186, 0.187, 0.189 \n\nOutlier is 0.169. Calculate Q:\n\n:Q=\\frac{gap}{range}=\\frac{(0.177-0.169)}{(0.189-0.169)}=0.400\n\nWith 10 observations at 90% confidence, Qcalculated < Qtable. Therefore keep 0.169 at 90% confidence.\n\n\'\'See also:\'\' [[List of statistical topics]]','',13,'Budhi','20040904061246','',0,0,0,1,0.424920563318,'20040904061246','79959095938753'); INSERT INTO cur VALUES (1556,0,'Panalungtikan_psikologi_kuantitatif','\'\'\'Quantitative psychological research\'\'\' is [[psychology|psychological]] research which performs [[statistical estimation]] or [[statistical inference]]. This definition distinguishes it from so-called [[qualitative psychological research]]; however, many psychologists do not acknowledge any real difference between quantitative and qualitative research. The validity of the distinction is discussed in the article about qualitative psychological research.\n\n[[Quantitative method|Quantitative methods]] are used in many social sciences.\n\n[[Category:Psikologi]]\n\n{{pondok}}','',3,'Kandar','20041129054148','',0,0,0,0,0.270506733223,'20050303211247','79958870945851'); INSERT INTO cur VALUES (1557,0,'Quantitative_research','\'\'\'Quantitative research\'\'\' is the numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect. It is used in a wide variety of natural and social sciences, including physics, biology, psychology, sociology and geology.\n\nQuantitative research begins with the collection of statistics, based on real data, observations or questionnaires. In the field of health, for example, researchers might measure and study the relationship between dietary intake and measurable physiological effects such as weight loss. Opinion surveys are a form of quantitative research in which respondents are asked a set of fixed questions and their responses are tallied. In the field of climate science, researchers compile and compare statistics such as temperature or atmospheric concentrations of carbon dioxide.\n\nSometimes quantitative research uses \'\'[[proxy|proxies]]\'\' as stand-ins for other quantities that cannot be directly measured. Tree-ring width, for example, is considered a reliable proxy of ambient environmental conditions such as the warmth of growing seasons or amount of rainfall. Although scientists cannot directly measure the temperature of past years, tree-ring width and other climate proxies have been used to provide a semi-quantitative record of [[Temperature record of the past 1000 years|average temperature in the Northern Hemisphere back to 1000 A.D.]] When used in this way, the proxy record (tree ring width, say) only reconstructs a certain amount of the variance of the original record. The proxy may be calibrated (for example, during the period of the instrumental record) to determine how much variation is captured, including whether both short and long term variation is revealed. In the case of tree-ring width, different species in different places may show more or less sensitivity to, say, rainfall or temperature: when reconstructing a temperature record there is considerable skill in selecting proxies that are well correlated with the desired variable.\n\nQuantitative research is often contrasted with [[qualitative research]], which is the non-numerical examination and interpretation of observations for the purpose of discovering underlying meanings and patterns of relationships. Qualitative research is generally considered to be exploratory and inductive in nature. It is used to get a general sense of what is happening and to form theories that can then be tested using quantitative research, which is viewed as confirmatory and deductive in nature.','',13,'Budhi','20040904061447','',0,0,0,1,0.03321155395,'20040904061447','79959095938552'); INSERT INTO cur VALUES (1558,0,'Adolphe_Quetelet','\'\'\'Lambert Adolphe Jacques Quételet\'\'\' ([[February 22]], [[1796]] - [[1874]]) was a [[Belgium|Belgian]] [[astronomer]], [[statistician]] and [[sociologist]]. He founded and directed the [[Brussels observatory]] and was influential in introducing statistical methods to the [[social science]]s. Some French-language sources give his last name as \'\'\'Quetelet\'\'\', with no accent.\n\nQuetelet received a doctorate in [[mathematics]] in [[1819]] from the [[University of Ghent]]. Shortly thereafter, the young man set out to convince government officials and private donors to build an astronomical observatory in [[Brussels]]; he succeeded in [[1828]].\n\nThe new science of [[probability]] and [[statistics]] was mainly used in astronomy at the time, to get a handle on measurement errors with the method of [[least squares]]. Quetelet was among the first who attempted to apply it to social science, planning what he called a \"social physics\". He was keenly aware of the overwhelming complexity of social phenomena, and the many variables that needed measurement. His goal was to understand the statistical laws underlying such phenomena as crime rates, marriage rates or suicide rates. He wanted to explain the values of these variables by other social factors. These ideas were rather controversial among other scientists at the time who held that it contradicted a concept of freedom of choice.\n\nHis most influential book was \'\'Sur l\'homme et le développement de se facultés, ou Essai de physique sociale\'\', published in [[1835]]. In it, he outlines the project of a social physics and describes his concept of the \"average man\" (\'\'l\'homme moyen\'\') who is characterized by the [[mean value]]s of measured variables that follow a [[normal distribution]]. He collected data about many such variables.\n\nQuetelet also founded several statistical journals and societies, and was especially interested in creating international cooperation among statisticians.\n\n== Reference ==\n* Stigler: \"Statistics on the Table\", Harvard University Press 1999, chapter 2\n\n[[it:Lambert-Adolphe-Jacques Quételet]]\n[[de:Adolphe Quetelet]]\n\n[[Category:Ahli Statistik|Quetelet, Adolphe]]\n[[Category:Astronom|Quetelet, Adolphe]]\n[[Category:Sosiolog|Quetelet, Adolphe]]','/* Reference */',20,'DiN','20050303205824','',0,0,1,0,0.84301179547,'20050303205824','79949696794175'); INSERT INTO cur VALUES (1559,0,'Quartile','Dina [[statistik déskriptif]], \'\'\'kuartil\'\'\' nyaeta hiji tina tilu nilai nu ngabagi [[data set|susunan data]] kana opat bagean.\n\nMangka:\n* \'\'\'kuartil kahiji\'\'\' = \'\'\'kuartil handap\'\'\' = motong data sahandapeun 25% = \'\'25th [[percentile|persentil]]\'\'\n* \'\'\'kuartil kadua\'\'\' = \'\'[[median]]\'\' = motong satengahna data = \'\'50th [[percentile|persentil]]\'\'\n* \'\'\'kuartil katilu\'\'\' = \'\'\'upper quartile\'\'\' = motong data 25% kaluhur, atawa handapeun 75% = \'\'75th [[percentile]]\'\'\n\nBeda antara kuartil luhur jeung handap disebut \'\'[[interquartile range]]\'\'.\n\nIlaharna penting keur [[Interpolation|interpolasi]] antara nilai keur ngalengkepan ieu, siga conto di handap ieu.\n\n i x[i]\n\n 1 102\n 2 105\n ------------- kuartil kahiji, Q1 = (105+106)/2 = 105.5\n 3 106\n 4 109\n ------------- kuartil kadua, Q2 = (109+110)/2 = 109.5\n 5 110\n 6 112\n ------------- kuartil katilu, Q3 = (112+115)/2 = 113.5\n 7 115\n 8 118\n\nNyokot nilai mean sisi sejen tina kuartil ngarupakeun kaputusan teu pasti: dina conto di luhur, nilai kuartil kudu aya dina rentang [105,106], [109,110] and [112, 115]. \n\nIf the [[sample size]] is not a multiple of four, some of the quartiles may be numbers in the original data set, as in this example:\n\n i x[i]\n\n 1 102\n 2 105 -- Q[1] = 105\n 3 106\n ------------- Q[2] = 107.5\n 4 109\n 5 110 -- Q[3] = 110\n 6 112\n\nIn both of the above cases, the first and third quartiles can be taken to be the [[median]] values of the lower and upper halves of the data, respectively. However, there is more than one school of thought on how to apply this definition when the overall median is one of the original data values. The next two examples are illustrations of some of the rules of thumb which have been adopted; neither always produces correct results, and it would be better to use a precise formulation as shown later. \n\nOne may include the median in both \"halves\" of the data:\n\n i x[i]\n\n 1 102\n 2 105\n 3 106 -- Q1 = 106\n 4 109\n 5 110 \n )- Q2 = 110 (note line 5 has been duplicated\n 5 110 to illustrate the point)\n 6 112\n 7 115 -- Q3 = 115\n 8 118\n 9 120\n\nOr \'\'not\'\' include the median in either \"half\":\n\n i x[i]\n\n 1 102\n 2 105\n ------------- Q1 = 105.5\n 3 106\n 4 109\n\n 5 110 -- Q2 = 110\n\n 6 112\n 7 115\n ------------- Q3 = 116.5\n 8 118\n 9 120\n\nMore precise mathematical formulations are possible: the quartiles of the distribution of a random variable \'\'X\'\' can be defined as the values \'\'x\'\' such that:\n\n:P(X\\leq x)\\geq \\frac{1}{4} \\ and \\ P(X\\geq x)\\geq \\frac{3}{4};\n:P(X\\leq x)\\geq \\frac{1}{2} \\ and \\ P(X\\geq x)\\geq \\frac{1}{2};\\ \\rm{ or }\n:P(X\\leq x)\\geq \\frac{3}{4} \\ and \\ P(X\\geq x)\\geq \\frac{1}{4}.\n\nWith these definitions the quartiles in the last example are 106, 110 and 115:\n P(\'\'X\'\' ≤ 106) = 1/3 and P(\'\'X\'\' ≥ 106) = 7/9;\n P(\'\'X\'\' ≤ 110) = 5/9 and P(\'\'X\'\' ≥ 110) = 5/9; and\n P(\'\'X\'\' ≤ 115) = 7/9 and P(\'\'X\'\' ≥ 115) = 1/3. \n\n\nSee also: \n\n*[[Interquartile range]]\n*[[Summary statistics]]\n*[[Quantile]]\n*[[Percentile]]','',13,'Budhi','20040908032750','',0,0,0,0,0.056548645281,'20040908032750','79959091967249'); INSERT INTO cur VALUES (1560,0,'Data_random','\'\'\'Data acak\'\'\' nyaéta data nu dihasilkeun maké prosés [[acak]] atawa data nu mibanda pola teu teratur. Data [[éntropi]] bisa dipaké keur ngukur sabaraha acak éta data.\n\n== Data acak jeung komprési ==\nSacara téoritis, data acak bakal ngahasilkeun suboptimal lamun dipaké salaku input dina algoritma [[lossless data compression]].\n\n\n{{pondok}}','',3,'Kandar','20041224072032','',0,0,0,0,0.519268068261,'20050303211247','79958775927967'); INSERT INTO cur VALUES (1561,0,'Random_sampling','#REDIRECT [[sampling (statistics)]]','',13,'Budhi','20040904061903','',0,1,0,1,0.783437081977,'20040904061903','79959095938096'); INSERT INTO cur VALUES (1562,0,'Sekuen_random','[[de:Zufallssequenz]]\n\'\'\'Sekuen random\'\'\' ngarupakeun salah sahiji tipe [[stochastic process|proses stokastik]]. Singkatna, sekuen [[random]] nyaeta [[sequence|sekuen]] [[variabel random variable]]. \n\nSekuen random penting dina [[statistik]]. Unggal analisa statistik tina [[experiment|percobaan]] umumna dimimitian ku \"anggap \'\'X\'\'1,...,\'\'Xn\'\' ngarupakeun variabel random ...\". Cara panggampangna keur nyebutkeun kaayaan dimana urang bisa milih ukuran anyar ku nganggap sekuen takhingga{\'\'Xi\'\'} diberekeun, sarta lengkah saterusna dina eksperimen ku nempo \'\'N\'\' kahiji dina watesan sekuen. Oge, pernyataa [[central limit theorem|teorema central limit]] (penting yen average jumlah observasi konvergen ka nilai mean) kaasup sekuen takhingga [[independent, identically distributed]] variabel random.\n\nTempo [[random number]], [[randomness]], [[pseudo-random number generator]], [[Halton_Sequences]]','',13,'Budhi','20040906042835','',0,0,0,0,0.879023477844,'20040906042902','79959093957164'); INSERT INTO cur VALUES (1563,0,'Randomized_controlled_trial','A \'\'\'randomized controlled trial\'\'\' (RCT) is a form of [[clinical trial]], or scientific procedure used in the testing of the efficacy of [[medicine]], used because of its record of reliability.\n\nSellers of medicines throughout the ages have had to convince their patients that the medicine works. As science has progressed, public expectations have risen, and government health budgets have become ever tighter, pressure has grown for a reliable system to prove this.\n\nAll new [[medication|medicines]] and [[surgery|surgical procedures]] must therefore undergo trials before use. Effects of a treatment may be small, and biological organisms (including [[human]]s) are complex, and do not react to the same stimulus in the same way. There is also a proven [[placebo effect]]. This effect can be marked and powerful. Some conditions will spontaneously go into full [[remission]]—doctors for hundreds of years have reported miraculous cures for no discernible reason. Finally, the simple process of administering the treatment may have direct effects on the patient. \n\nRandomized trials are employed to test efficacy while avoiding these factors. Trials may be \'\'open\'\', \'\'blind\'\' or \'\'double-blind\'\'.\n\n==== Open Trial ====\n\nIn an open trial, the researcher knows the full details of the treatment, and so does the patient. These trials are open to challenge for bias, and they do nothing to reduce the placebo effect. However, sometimes they are unavoidable, particularly in relation to surgical techniques, where it may not be possible to hide from the patient which treatment he or she received.\n\n==== Single Blind Trial ====\n\nIn a single blind trial, the researcher knows the details of the treatment but the patient does not. Because the patient does not know which treatment is being administered (the new treatment or another treatment) there should be no placebo effect. In practice, since the researcher knows, it is possible for them to treat the patient differently or to subconsciously hint to the patient important treatment-related details, thus influencing the outcome of the study.\n\n==== Double Blind Trial ====\n\nIn a [[double-blind]] trial, one researcher allocates a series of numbers to \'new treatment\' or \'old treatment\'. The second researcher is told the numbers, but not what they have been allocated to. Since the second researcher does not know, they cannot possibly tell the patient, directly or otherwise, and cannot give in to patient pressure to give them the new treatment. In this system, there is also often a more realistic distribution of sexes and ages of patients. Therefore double-blind (or randomized) trials are preferred, as they tend to give the most accurate results.\n\n==== Triple Blind Trial ====\n\nSome randomized controlled trials are considered triple-blinded, although the meaning of this may vary according to the exact study design. The most common meaning is that the subject, researcher and person administering the treatment (often a [[pharmacist]]) are blinded to what is being given. Alternatively, it may mean that the patient, researcher and [[statistician]] are blinded. These additional precautions are often in place with the more commonly accepted term \"double blind trials\", and thus the term \"triple-blinded\" is infrequently used. However, it connotes an additional layer of security to prevent undue influence of study results by anyone directly involved with the study.\n\n==== Controlled Aspect ====\n\nThe \'controlled\' aspect comes from three main sources. The first is another member of the research team, who will typically review the test to try to remove any factors which might skew the results. For example, it is important to have a test group which is reasonably balanced for ages and sexes of the subjects (unless this is a treatment which will never be used on a particular sex or age group). The second source of control is inherent in having a \'control\' group, that is, a group which is undergoing the same routine (seeing a doctor, taking pills at the same time, etc.) but is not receiving the same treatment. This control group will be receiving either no treatment (e.g., sugar pills) or will be receiving the current standard treatment (if, for example, it would be unethical not to treat their ailment at all). The third source of control is via peer review and/or review by government regulators, who will examine the trial when it is presented for publication or when the drug manufacturer applies for a licence for the drug.\n\nThe importance of having a control group cannot be understated. Merely being told that one is receiving a miraculous cure can be enough to cure a patient—even if the pill contains nothing more than sugar. Additionally, the procedure itself can produce ill effects. For example, in one study on [[rabbit]]s where these subjects were receiving daily injections of a drug, it was found that they were developing [[cancer]]. If this was a result of the treatment, it would obviously be unsuitable for testing in humans. Because this result was reflected equally between the control and test groups, the source of the problem was investigated and it was shown in this case that the administration of daily injections was the cancer risk—not the drug itself.\n\nThe analysis of the trial results is a great skill in itself, and pharmaceutical firms employ groups of [[statistics|statisticians]] to try to make sense of the data. Likewise, regulators pay keen attention to the statistics, which can be used to hide serious deficiencies in the effectiveness of a treatment. \n\n==== Difficulties ====\n\nA major difficulty in dealing with trial results comes from commercial, political and/or academic pressure. Most trials are expensive to run, and will be the result of significant previous research, which is itself not cheap. There may be a political issue at stake (cf. [[MMR vaccine]]) or vested interests (cf. [[homeopathy]]). In such cases there is great pressure to interpret results in a way which suits the viewer, and great care must be taken by researchers to maintain emphasis on clinical facts.\n\nMost studies start with a \'[[null hypothesis]]\' which is being tested (usually along the lines of \'Our new treatment \'\'x\'\' cures as many patients as existing treatment \'\'y\'\'\') and an [[alternative hypothesis]] (\'\'\'x\'\' cures more patients than \'\'y\'\'\'). The analysis at the end will give a statistical likelihood, based on the facts, of whether the null hypothesis can be safely rejected (saying that the new treatment does, in fact, result in more cures). Nevertheless this is only a statistical likelihood, so false negatives and false positives are possible. These are generally set an acceptable level (e.g., 1% chance that it was a false result). However, this risk is cumulative, so if 200 trials are done (often the case for contentious matters) about 2 will show contrary results. There is a tendency for these two to be seized on by those who need that proof for their point of view.\n\n== See also ==\n* [[Medicine]]\n* [[hypothesis testing]]\n* [[statistical inference]]\n* [[evidence-based medicine]]\n* [[double-blind]]\n\n== External links ==\n\n*[http://bmj.bmjjournals.com/cgi/content/full/327/7429/1459 A humorous look at problems with requiring randomized studies in medicine]','',13,'Budhi','20040904062101','',0,0,0,1,0.82163384595,'20041225235727','79959095937898'); INSERT INTO cur VALUES (1564,0,'Rentang_(statistik)','Dina [[statistik deskriptif]], \'\'\'rentang\'\'\' nyaeta panjang interval pangleutikna nu ngawengku sakabeh data. Rentang diitung ku cara ngurangan observasi panggedena ku nu pangleutikna. \n\nRentang ngarupakeun ukuran nu sarua salaku data. Rentang nu ngan gumantung kana dua observasi, ngarupakeun ukuran dispersi nu goreng, iwal ti lamun ukuran sampelna gede.. \n\nTempo ogé:\n\n*[[Interquartile range]]\n*[[Statistical dispersion]]','',13,'Budhi','20041224233459','',0,0,0,0,0.945828355824,'20041224233529','79958775766540'); INSERT INTO cur VALUES (1565,0,'Téoréma_Rao-Blackwell','Dina [[statistik]], \'\'\'téoréma Rao-Blackwell\'\'\' ngagambarkeun hiji téhnik nu bisa ngarubah bentuk estimator nu teu jelas jadi hiji estimator nu optimal ku kriteria mean-kasalahan kuadrat atawa kriteria sejen nu ampir sarupa. (Pronunciation: \'\'Rao\'\' rhymes with \"cow\".)\n\n==Sababaraha harti prasarat==\n\n*Hiji [[estimator]] nyaeta hiji variabel acak \'\'nu bisa diobservasi\'\' (upamana dina statistik) dipake keur ngira-ngira kuantita nu \'\'teu ka-observasi\'\'. For example, one may be unable to observe the average height of \'\'all\'\' male students at the University of X, but one may observe the heights of a random sample of 40 of them. The average height of those 40--the \"sample average\"--may be used as an estimator of the unobservable \"population average\".\n\n*A [[sufficiency (statistics)|sufficient statistic]] \'\'T\'\'(\'\'X\'\') is an \'\'observable\'\' [[random variable]] such that the [[conditional probability]] distribution of all observable data \'\'X\'\' given \'\'T\'\'(\'\'X\'\') does not depend on any of the \'\'unobservable\'\' quantities such as the mean or standard deviation of the whole population from which the data \'\'X\'\' was taken. In the most frequently cited examples, the \"unobservable\" quantities are parameters that parametrize a known family of [[probability distribution]]s according to which the data are distributed.\n\n*A \'\'\'Rao-Blackwell estimator\'\'\' δ1(\'\'X\'\') of an unobservable quantity θ is the [[conditional expectation]] E(δ(\'\'X\'\') | \'\'T\'\'(\'\'X\'\')) of some estimator δ(\'\'X\'\') given a sufficient statistic \'\'T\'\'(\'\'X\'\'). Call δ(\'\'X\'\') the \'\'\'\"original estimator\"\'\'\' and δ1(\'\'X\'\') the \'\'\'\"improved estimator\"\'\'\'. It is important that the improved estimator be \'\'observable\'\', i.e., that it not depend on θ. Generally, the conditional expected value of one function of these data given another function of these data \'\'does\'\' depend on θ, but the very definition of sufficiency given above entails that this one does not.\n\n*The \'\'mean squared error\'\' of an estimator is the expected value of the square of its deviation from the unobservable quantity being estimated.\n\n==The theorem==\n\nOne case of Rao-Blackwell theorem states:\n\n:The mean squared error of the Rao-Blackwell estimator does not exceed that of the original estimator.\n\nIn other words\n\n:E((\\delta_1(X)-\\theta)^2)\\leq E((\\delta(X)-\\theta)^2).\n\nA more general version of the theorem will be mentioned below.\n\nThe essential tools of the proof besides the definition above are the [[law of total expectation]] and the fact that for any random variable \'\'Y\'\', E(\'\'Y\'\'2) cannot be less than [E(\'\'Y\'\')]2. That inequality is a case of [[Jensen\'s inequality]], although in a statistics course it may be shown to follow instantly from the frequently mentioned fact that\n\n:0\\leq\\operatorname{var}(Y)=E((Y-E(Y))^2)=E(Y^2)-(E(Y))^2.\n\nThe more general version of the Rao-Blackwell theorem speaks of the \"expected loss\"\n\n:E(L(\\delta_1(X)))\\leq E(L(\\delta(X)))\n\nwhere the \"loss function\" \'\'L\'\' may be any [[convex]] function. For the proof of the more general version, Jensen\'s inequality cannot be dispensed with.\n\nThe improved estimator is [[bias (statistics)|unbiased]] if and only if the original estimator is unbiased, as may be seen at once by using the [[law of total expectation]]. The theorem holds regardless of whether biased or unbiased estimators are used.\n\nThe theorem seems very weak: it says only that the allegedly improved estimator is no worse than the original estimator. In practice, however, the improvement is often enormous, as an example can show.\n\n==Example==\n\nPhone calls arrive at a switchboard according to a [[Poisson process]] at an average rate of λ per minute. This rate is not observable, but the numbers of phone calls that arrived during \'\'n\'\' successive one-minute periods are observed. It is desired to estimate the probability \'\'e\'\'−λ that the next one-minute period passes with no phone calls. The answer given by Rao-Blackwell may perhaps be unexpected.\n\nA \'\'extremely\'\' crude estimator of the desired probability is\n\n\n:\\delta_0=\\left\\{\\begin{matrix}1 & \\mbox{if}\\ X_1=0 \\\\\n0 & \\mbox{otherwise}\\end{matrix}\\right\\},\n\ni.e., this estimates this probability to be 1 if no phone calls arrived in the first minute and zero otherwise.\n\nThe sum\n\n:X_1+\\cdots+X_n\n\ncan be readily shown to be a sufficient statistic for λ, i.e., the \'\'conditional\'\' distribution of the data \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\', given this sum, does not depend on λ. Therefore, we find the Rao-Blackwell estimator\n\n:\\delta_1=E(\\delta_0|X_1+\\cdots+X_n).\n\nAfter doing some algebra we have\n\n:\\delta_1=\\left(1-{1 \\over n}\\right)^{X_1+\\cdots+X_n}.\n\nSince the average number \'\'X\'\'1+ ... + \'\'X\'\'\'\'n\'\' of calls arriving during the first \'\'n\'\' minutes is \'\'n\'\'λ, one might not be surprised if this estimator has a fairly high probability (if \'\'n\'\' is big) of being close to\n\n:\\left(1-{1 \\over n}\\right)^{n\\lambda}\\approx e^{-\\lambda}.\n\nSo δ1 is clearly a very much improved estimator of that last quantity.\n\n==Idempotence of the Rao-Blackwell process==\n\nIn case the sufficient statistic is also a [[completeness (statistics)|complete statistic]], i.e., one which \"admits no unbiased estimator of zero\", the Rao-Blackwell process is [[idempotent]], i.e., using it to improve the already improved estimator does not do so, but merely returns as its output the same improved estimator.\n\n==When is the Rao-Blackwell estimator the best possible?==\n\nIf the improved estimator is both [[bias (statistics)|unbiased]] and [[completeness (statistics)|complete]], then the [[téoréma Lehmann-Scheffé]] implies that it is the unique \"best unbiased estimator.\"\n\n[[Category:Probability and statistics]] [[Category:Theorems]]','/* When is the Rao-Blackwell estimator the best possible? */',13,'Budhi','20041225233359','',0,0,1,0,0.104341554038,'20041231123527','79958774766640'); INSERT INTO cur VALUES (1566,0,'Receiver_operating_characteristic','In [[signal detection theory]], a \'\'\'receiver operating characteristic\'\'\' (\'\'\'ROC\'\'\') is a [[graph of a function|graph]]ical plot of the number of [[true positive]]s vs. the number of [[false positives]] for a [[binary classifier]] system as its discrimination threshold is varied. The usage \'\'\'receiver operator characteristic\'\'\' is also common. \n\nROC curves are used to evaluate the results of a [[prediction]] and were first employed in the study of discriminator systems for the detection of radio signals in the presence of noise in the [[1940s]]. In the [[1960s]] they began to be used in [[psychophysics]], to assess human (and occasionally animal) detection of weak signals. They also proved to be useful for the evaluation of [[machine learning]] results, such as the evaluation of Internet [[search engine]]s. They are also used extensively in [[epidemiology]] and [[medical research]].\n\nThe best possible prediction method would yield a graph that was a point in the upper left corner of the ROC space, i.e. 100% [[Sensitivity (tests)|sensitivity]] (all true positives are found) and 100% [[specificity]] (no false positives are found). A completely random predictor would give a straight line at an angle of 45 degrees from the horizontal, from bottom left to top right: this is because, as the threshold is raised, equal numbers of true and false positives would be let in. Results below this no-discrimination line would suggest a detector that gave wrong results consistently, and could therefore be simply used to make a detector that gave useful results by inverting its decisions.\n\nSometimes, the ROC is used to generate a summary statistic. Three common versions are:\n* the intercept of the ROC curve with the line at 90 degrees to the no-discrimination line\n* the area between the ROC curve and the no-discrimination line\n* \'\'d\'\'\' (pronounced \"d-prime\"), the distance between the mean of the distribution of activity in the system under noise-alone conditions and its distribution under signal plus noise conditions, divided by their [[standard deviation]], under the assumption that both these distributions are [[normal distribution|normal]] with the same standard deviation.\n\nHowever, any attempt to summarize the ROC curve into a single number loses information about the pattern of tradeoffs of the particular discriminator algorithm.\n\nIn engineering, the area between the ROC curve and the line is most frequently used statistic, because of its useful mathematical properties as a [[non-parametric statistic]]. This area is often simply known as the \'\'\'discrimination\'\'\'. In psychophysics, \'\'d\'\'\' is the commonest measure.\n\n[[Image:roc.png]]\n\nIllustration of the use of ROC graphs for discrimination. TP - true positives, FP - false p., TN - true negatives, FN - false n.. Starting from two distributions of positives (red) and negatives (blue) one can apply a threshold criterion (vertical line) to arbitrarily separate the two. For overlapping distributions, there is always a tradeoff between sensitivity (TP) and specificity (1-FN). TP and FN as well as TN and FP both add up to 1. Sliding the threshold line towards the distribution of positives will result in a decreased probability for true positive detection P(TP) and FPs, which is equivalent to moving the ROC curve (dashed) downwards. If the two distributions overlap completely, the ROC curve will be the diagonal shown as the dot-dashed curve.\n\n\'\'\'See also\'\'\':\n* [[Mann-Whitney U]] test\n* [[Fisher\'s linear discriminator]]\n\n== External links ==\n* [http://splweb.bwh.harvard.edu:8000/pages/ppl/zou/roc.html Receiver Operating Characteristic bibliography]\n* [http://gim.unmc.edu/dxtests/roc2.htm A simple example of a ROC curve]\n* [http://www.anaesthetist.com/mnm/stats/roc/ applets]\n* [http://sucia.stanford.edu/~lera/psych115s/notes/signal/ A more thorough treatment of ROC curves and signal detection theory]\n\n[[Category:Statistics]]','',13,'Budhi','20040904062515','',0,0,0,1,0.634052058511,'20040904062515','79959095937484'); INSERT INTO cur VALUES (1567,0,'Regression_toward_the_mean','In [[statistics]], \'\'\'regression toward the mean\'\'\' is a principle stating that of related measurements, the second is expected to be closer to the mean than the first.\n\n==Example ==\n\nConsider, for example, students who take a midterm and a final exam. Students who got an extremely high score on the midterm will probably get a good score on the final exam as well, but we expect their score to be closer to the average (i.e.: fewer [[standard deviation]]s above the average) than their midterm score was. The reason: it is likely that some [[luck]] was involved in getting the exceptional midterm score, and this luck cannot be counted on for the final. It is also true that among those who get exceptionally high final exam scores, the average midterm score will be fewer standard deviations above average than the final exam score, since some of those got high scores on the final due to luck that they didn\'t have on the midterm. Similarly, unusually low scores regress toward the mean.\n\n==History==\n\nThe principle was described and explained by [[Francis Galton]] in the [[1870s]] and [[1880s]]. Initially, he investigated [[genius]]es in various fields and noted that their children, while typically gifted, were almost invariably closer to the average than their exceptional parents. He later described the same effect more numerically by comparing fathers\' heights to their sons\' heights. Again, the son\'s height is typically closer to the mean height than the father\'s height.\n\n==Ubiquity==\n\nIt is important to realize that regression toward the mean is a ubiquitous statistical phenomenon and has nothing to do with biological inheritance. It is also unrelated to the progression of time: the \'\'fathers\'\' of exceptionally tall people also tend to be closer to the mean than their sons. The overall variability of height among fathers and sons is the same.\n\n== Mathematical derivation ==\n\nGiven two variables \'\'X\'\' and \'\'Y\'\' with mean 0, common variance 1, and [[correlation|correlation coefficient]] \'\'r\'\', the expected value of \'\'Y\'\' given that the value of \'\'X\'\' was measured to be \'\'x\'\' is equal to \'\'rx\'\', which is closer to the mean 0 than \'\'x\'\' since |\'\'r\'\'| < 1. If the variances of the two variable \'\'X\'\' and \'\'Y\'\' are different, and one measures the variables in \"normalized units\" of standard deviations, then the principle of regression toward the mean also holds true.\n\nThis example illustrates a general fact: regression toward the mean is the more pronounced the less the two variables are correlated, i.e. the smaller |\'\'r\'\'| is.\n\n== Regression fallacies ==\n\nMisunderstandings of the principle (known as \"\'\'\'regression fallacies\'\'\'\") have repeatedly led to mistaken claims in the scientific literature.\n\nAn extreme example is Horace Secrist\'s 1933 book \'\'The Triumph of Mediocrity in Business\'\', in which the statistics professor collected mountains of data to prove that the profit rates of competitive businesses tend towards the average over time. In fact, there is no such effect; the variability of profit rates is almost constant over time. Secrist had only described the common regression toward the mean. One exasperated reviewer likened the book to \"proving the multiplication table by arranging elephants in rows and columns, and then doing the same for numerous other kinds of animals\".\n\nA different regression fallacy occurs in the following example. We want to test whether a certain stress-reducing drug increases reading skills of poor readers. Pupils are given a reading test. The lowest 10% scorers are then given the drug, and tested again, with a different test that also measures reading skill. We find that the average reading score of our group has improved significantly. This however does not show anything about the effectiveness of the drug: even without the drug, the principle of regression toward the mean would have predicted the same outcome.\n\nThe calculation and interpretation of \"improvement scores\" on standardized educational tests in Massachusetts probably provides another example of the regression fallacy. In 1999, schools were given improvement goals. For each school, the Department of Education tabulated the difference in the average score achieved by students in 1999 and in 2000. It was quickly noted that most of the worst-performing schools had met their goals, which the Department of Education took as confirmation of the soundness of their policies. However, it was also noted that many of the supposedly best schools in the Commonwealth, such as Brookline High School (with 18 National Merit Scholarship finalists) were declared to have failed. As in many cases involving statistics and public policy, the issue is debated, but \"improvement scores\" were not announced in subsequent years and the findings appear to be a case of regression to the mean.\n\n== References ==\n\n* J.M. Bland and D.G. Altman. \"Statistic Notes: Regression towards the mean\", \'\'British Medical Journal\'\' 308:1499, 1994. \'\'(Article, including a diagram of Galton\'s original data, online at: [http://bmj.bmjjournals.com/cgi/content/full/308/6942/1499])\'\'\n\n* Francis Galton. \"Regression Towards Mediocrity in Hereditary Stature,\" \'\'Journal of the Anthropological Institute\'\', 15:246-263 (1886). \'\'(Facsimile at: [http://www.mugu.com/galton/essays/1880-1889/galton-1886-jaigi-regression-stature.pdf])\'\'\n\n* Stephen M. Stigler. \'\'Statistics on the Table\'\', Harvard University Press, 1999. \'\'(See Chapter 9.)\'\'\n\n==Tumbu kaluar==\n\n* Amanda Wachsmuth, Leland Wilkinson, Gerard E. Dallal. [http://www.spss.com/research/wilkinson/Publications/galton.pdf Galton\'s Bend: An Undiscovered Nonlinearity in Galton\'s Family Stature Regression Data and a Likely Explanation Based on Pearson and Lee\'s Stature Data] \'\'(A modern look at Galton\'s analysis.)\'\'\n\n* Massachusetts standardized test score regression: see [http://groups.google.com/groups?q=g:thl3845480903d&dq=&hl=en&lr=&ie=UTF-8&oe=UTF-8&safe=off&selm=93ikdr%24i20%241%40nnrp1.deja.com discussion in sci.stat.edu]\n\n[[Category:Statistics]]','/* External links */',13,'Budhi','20040908042638','',0,0,0,0,0.413315294969,'20040908042638','79959091957361'); INSERT INTO cur VALUES (1568,0,'Reliability_(psychometric)','In [[psychometrics]] \'\'\'reliability\'\'\' is the accuracy of the scores of a measure. Reliability does not imply [[validity (psychometric)|validity]]. That is, a reliable measure is measuring something accurately, but not necessarily what it is supposed to be measuring. For example, while there are many reliable tests, not all of them would validly predict job performance.\n\n==Estimation==\n\nReliability may be estimated through a variety of methods that fall into two types: Single-administration and multiple-administration. \nMultiple-administration methods require that two assessments are administered. In the \'\'test-retest\'\' method, reliability is estimated as the [[Pearson product-moment correlation coefficient]] between two administrations of the same measure. In the \'\'alternate forms\'\' method, reliability is estimated by the [[Pearson product-moment correlation coefficient]] of two different forms of a measure, usually administered together. Single-administration methods include \'\'split-half\'\' and \'\'internal consistency\'\'. The split-half method treats the two halves of a measure as alternate forms. This \"halves reliability\" estimate is then stepped up to the full test length using the [[rumus prediksi Spearman-Brown]]. The most common internal consistency measure is [[Cronbach\'s α]], which is usually interpreted as the mean of all possible split-half coefficients.\n\nEach of these estimation methods is sensitive to different sources of error and so might not be expected to be equal. Also, reliability is a property of the \'\'scores of a measure\'\' rather than the measure itself and are thus said to be \'\'sample dependent\'\'. Reliability estimates from one sample might differ from those of a second sample (beyond what might be expected due to sampling variations) if the second sample is drawn from a different population because the true reliability is different in this second population. (This is true of measures of all types--yardsticks might measure houses well yet have poor reliability when used to measure the lengths of insects.)\n\nReliability may be improved by clarity of expression (for written assessments), lengthening the measure, and other informal means. However, formal psychometric analysis is considered the most effective. Such analysis generally involves computation of item statistics such as the \'\'[[item-total correlation]]\'\' (the correlation between the item score and sum of the item scores of the entire test). These measures are inherently circular but in practice they work well if the test has been constructed carefully so that it\'s initial draft contains sufficient reliability.\n\n==Classical test theory==\n\nIn [[classical test theory]], reliability is defined mathematically as the ratio of the variation of the \'\'true score\'\' and the variation of the \'\'observed score\'\'. Or, equivalently, one minus the ratio of the variation of the \'\'error score\'\' and the variation of the \'\'observed score\'\':\n\n{\\rho}_{xx\'}=\\frac{{\\sigma}^2_T}{{\\sigma}^2_X}=1-\\frac{{{\\sigma}^2_E}}{{{\\sigma}^2_X}}\n\nwhere {\\rho}_{xx\'} is the symbol for the reliability of the observed score, X; {\\sigma}^2_X, {\\sigma}^2_T, and {\\sigma}^2_E are the variances of the observed, true and error scores, respectively.\n\n==Item response theory==\n\nIt was well-known to classical test theorists that measurement precision is not uniform across the scale of measurement. Tests tend to distinguish better for test-takers with moderate trait levels and worse among high- and low-scoring test-takers. [[Item response theory]] extends the concept of reliability from a single index to a function called the \'\'information function\'\'. The IRT information function is the inverse of the conditional observed score standard error at any given test score. Higher levels of IRT information indicate higher precision and thus greater reliability.\n\n[[Category:Psychometrics]]','/* Estimation */',13,'Budhi','20041226004641','',0,0,1,0,0.606279120132,'20041226004641','79958773995358'); INSERT INTO cur VALUES (1569,0,'Rothamsted_Experimental_Station','The \'\'\'Rothamsted Experimental Station\'\'\' is located at [[Harpenden]] in [[Hertfordshire]], [[England]]. [[John Bennett Lawes]] (1814-1900) founded the \'\'Rothamsted Agricultural Research Station\'\' after he inherited the Rothamsted Manor, dating from the [[16th century]]. He started the first experiments at Rothamsted in about [[1834]].\n\n[[Ronald Fisher]], [[Frank Yates]], [[William Cochran]] and [[John Wishart]] worked at Rothamsted, performing much pioneering work in [[20th century]] [[statistics]] and [[genetics]].\n\nIn [[2003]] the station is operated by a grouping of private organisations named Rothamsted Research and is mainly funded by the branches of the UK government through the [[Biotechnology and Biological Sciences Research Council|BBSRC]].\n\n==External links==\n\n* [http://www.rothamsted.bbsrc.ac.uk Rothamsted Research]\n* [http://www.rothamsted.bbsrc.ac.uk/res/corporate/meetingsfuncsaccommod/rothamstedmanor/trothamstedmanor.html Rothamsted Manor]','',13,'Budhi','20040904062904','',0,0,0,1,0.570067615979,'20050316081936','79959095937095'); INSERT INTO cur VALUES (1570,0,'Rule_of_succession','[[Category:Probability]]\n\nIn [[probability theory]], the \'\'\'rule of succession\'\'\' is a formula introduced in the 18th century by [[Pierre-Simon Laplace]] in the course of treating the [[sunrise problem]].\n\n==Statement of the rule of succession==\n\nAnggap \'\'p\'\' mangrupa [[sebaran seragam]] dina interval [0, 1]. Suppose \'\'X\'\'1, ..., \'\'X\'\'\'\'n\'\'+1 are [[conditional independence|conditionally independent]] [[random variable]]s given the value of \'\'p\'\', and [[conditional probability|conditional]] on \'\'p\'\' are [[Bernoulli distribution|Bernoulli-distributed]] with expected value \'\'p\'\', i.e., each has probability \'\'p\'\' of being equal to 1 and probability 1 − \'\'p\'\' of being equal to 0. Then\n\n:P(X_{n+1}=1 \\mid X_1+\\cdots+X_n=s)={s+1 \\over n+2}.\n\n==The probability that the sun will rise tomorrow==\n\nLet \'\'p\'\' be the long-run frequency of sunrises, i.e., the sun rises on 100 × \'\'p\'\'% of days. \'\'\'\'\'Prior\'\'\'\'\' to knowing of any sunrises, one is completely ignorant of the value of \'\'p\'\'. Laplace represented this prior ignorance by means of a [[sebaran seragam|uniform probability distribution]] on \'\'p\'\'. Thus the probability that \'\'p\'\' is between 20% and 50% is just 30%. This must not be interpreted to mean that in 30% of all cases, \'\'p\'\' is between 20% and 50%; that would be a [[frequentism|frequentist]] philosophy of applied probability. Rather, it means that one\'s state of knowledge (or ignorance) justifies one in being 30% sure that the sun rises between 20% of the time and 50% of the time -- that is a [[Bayesianism|Bayesian]] philosophy of applied probability. \'\'Given\'\' the value of \'\'p\'\', and no other information relevant to the question of whether the sun will rise tomorrow, the probability that the sun will rise tomorrow is \'\'p\'\'. But we are \'\'not\'\' \"given the value of \'\'p\'\'\". What we are given is the observed data: the sun has risen every day on record. Laplace inferred the number of days by saying that the universe was created about 6000 years ago, based on a literal construction of the [[Bible]]. To find the [[conditional probability]] distribution of \'\'p\'\' given the data, one uses [[Bayes theorem]], which some call the \'\'Bayes-Laplace rule\'\'. Having found the conditional probability distribution of \'\'p\'\' given the data, one may then calculate the conditional probability, given the data, that the sun will rise tomorrow. That conditional probability is given by the [[rule of succession]]. The probability that the sun will rise tomorrow increases with the number of days on which the sun has risen so far and would decrease as the number of days on which the sun has failed to rise increases.\n\n==Mathematical details==\n\nThe proportion \'\'p\'\' is treated as a uniformly distributed random variable. (Some who take an extreme Bayesian approach to applied probability insist that the word \'\'random\'\' should be banished altogether from probability theory, on the grounds of examples like this one. This proportion is not random, but uncertain. We assign a probability distribution to \'\'p\'\' to express our uncertainty, not to attribute randomness to \'\'p\'\'.)\n\nLet \'\'X\'\'\'\'i\'\' be the number of \"successes\" on the \'\'i\'\'th [[Bernoulli trial|trial]], with probability \'\'p\'\' of success on each trial. Thus each \'\'X\'\' is 0 or 1; each \'\'X\'\' has a [[Bernoulli distribution]]. Suppose these \'\'X\'\'s are [[conditional independence|conditionally independent]] given \'\'p\'\'.\n\n[[Bayes\' theorem]] says that in order to get the conditional probability distribution of \'\'p\'\' given the data \'\'X\'\'\'\'i\'\', \'\'i\'\' = 1, ..., \'\'n\'\', one multiplies the \"prior\" (i.e., marginal) probability measure assigned to \'\'p\'\' by the [[likelihood function]]\n\n:L(p)=P(X_1=x_1, \\cdots, X_n=x_n \\mid p)=\\prod_{i=1}^n p^{x_i}(1-p)^{1-x_i}=p^s (1-p)^{n-s}\n\nwhere \'\'s\'\' = \'\'x\'\'1 + ... + \'\'x\'\'\'\'n\'\' is the number of \"successes\" and \'\'n\'\' is of course the number of trials, and then [[normalizing constant|normalizes]], to get the \"posterior\" (i.e., conditional on the data) probablity distribution of \'\'p\'\'. (We are using capital \'\'X\'\' to denote a random variable and lower-case \'\'x\'\' either as the [[bound variable|dummy]] in the definition of a function or as the data actually observed.)\n\nThe prior [[probability density function]] is equal to 1 for 0 < \'\'p\'\' < 1 and equal to 0 for \'\'p\'\' < 0 or \'\'p\'\' > 1. To get the normalizing constant, we find\n\n:\\int_0^1 p^s(1-p)^{n-s}\\,dp={(s+1)!(n-s+1)! \\over (n+2)!}\n\n(tempo [[fungsi beta]] keur integral leuwih jentre dina bentuk ieu).\n\nThe posterior probability density function is therefore\n\n:f(p)={(n+2)! \\over (x+1)!(n-s+1)!}p^s(1-p)^{n-s}.\n\nIeu ngarupakeun [[sebaran beta]] nu [[nilai ekspektasi]]-na nyaeta\n\n:{s+1 \\over n+2}.\n\nSince the conditional probability of tomorrow\'s sunrise, given the value of \'\'p\'\', is just \'\'p\'\', the [[law of total probability]] tell us that the probability of tomorrow\'s sunrise is just the expected value of \'\'p\'\'. Since all of this is conditional on the observed data \'\'X\'\'\'\'i\'\' for \'\'i\'\' = 1, ..., \'\'n\'\', we have\n\n:P(X_{n+1}=1 \\mid X_i=x_i\\ \\mbox{for}\\ i=1,\\dots,n)={s+1 \\over n+2}.\n\nThus if the sun has risen every morning for 2,000,000 consecutive mornings, and no other data are available, Laplace would have us conclude that the probability of tomorrow\'s sunrise is\n\n:{2,\\!000,\\!001 \\over 2,\\!000,\\!002}.\n\nThe probability that the sun will \'\'not\'\' rise tomorrow would then be slightly less than one in two million.','/* The probability that the sun will rise tomorrow */',13,'Budhi','20041224032207','',0,0,1,0,0.69774309392,'20041231123527','79958775967792'); INSERT INTO cur VALUES (1571,0,'Simpson\'s_paradox','\'\'\'Simpson\'s paradox\'\'\' (or the \'\'Yule-Simpson effect\'\') is a [[statistics|statistical]] [[paradox]] described by E. H. Simpson in [[1951]] and G. U. Yule in [[1903]], in which the successes of several groups seem to be reversed when the groups are combined. This seemingly impossible result is encountered surprisingly often in social science and medical statistics.\n\nAs an example, suppose two people, Ann and Bob, are let loose on Wikipedia. In the first test, Ann improves 60 percent of the articles she edits while Bob improves 90 percent of the articles he edits. In the second test, Ann improves just 10 percent of the articles she edits, while Bob improves 30 percent.\n\nBoth times, Bob improved a much higher percentage of articles than Ann - yet when the two tests are combined, Ann has improved a much higher percentage than Bob!\n\nThe result comes about this way: In the first test, Ann edits 100 articles, improving 60 of them, while Bob edits just 10 articles, improving 9 of them. In the second test, Ann edits only 10 articles, improving 1 of them, while Bob edits 100 articles, improving 30 of them. When the two tests are added together, both edited 110 articles, yet Ann improved 61 of them (55 percent) while Bob improved only 39 of them (35 percent)!\n\nIt appears that the two sets of data separately support a certain hypothesis, but, considered together, support the opposite hypothesis. \n\nTo recap, introducing some notation that will be useful later:\n*In the first test, Ann improved 60% of the articles she edited (\'\'S\'\'A(1) = 60%), while Bob\'s success rate was 90% (= \'\'S\'\'B(1)) Success is associated with Bob.\n*In the second test Ann managed 10% (\'\'S\'\'A(2)) while Bob achieved 30% (\'\'S\'\'B(2)). On both occasions Bob\'s edits were more successful than Ann\'s. Success is again associated with Bob. \n*But if we combine the two tests, we see that Ann and Bob both edited 110 articles, and that Ann improved 61 (\'\'S\'\'A = 61/110) while Bob improved only 39 (\'\'S\'\'B = 39/110). \n*\'\'S\'\'B < \'\'S\'\'A. Success is now associated with Ann. Bob is better on every test but worse overall!\n\nThe arithmetical basis of the paradox is uncontroversial. If \'\'S\'\'B(1) > \'\'S\'\'A(1) and \'\'S\'\'B(2) > \'\'S\'\'A(2) we feel that \'\'S\'\'B \'\'must be greater\'\' than \'\'S\'\'A. However if \'\'different\'\' weights are used to form the overall score for each person then this feeling may be disappointed. Here the first test is weighted 100/110 for Ann and 10/110 for Bob while the weights are reversed on the second test. \n\n\'\'S\'\'A = 100/110\'\'S\'\'A(1) + 10/110\'\'S\'\'A(2).\n\n\'\'S\'\'B = 10/110\'\'S\'\'B(1) + 100/110\'\'S\'\'B(2). \n\nBy more extreme reweighting A\'s overall score can be pushed up to 60% and B\'s down to 30%.\n\nThe arithmetic allows us to see through the paradox but there is still the conflict between the individual performances and the overall performance: who is better, A or B? Ann and Bob\'s creator thought Ann was better--her overall success rate is higher. But it is possible to retell the story so that it appears obvious that B is better. A and B are now hospitals and the two tests have become two types of patient: mild and severe. The numerical data is as before: B is better at curing both types of patient but its overall success rate is worse because almost all (100/110) of its patients are severe cases while almost all of A\'s are mild (100/110). The association of success with A is misleading, even spurious. \n\nIn this retelling has something been added, or has a tacit assumption of the Ann and Bob story been changed? These issues are discussed in the modern literature on Simpson\'s paradox. Although statisticians have known about the Simpson\'s paradox phenomenon for over a century, there has lately been a revival of interest in it and philosophers, computer scientists, epidemiologists, economists and others have discussed it too. \n\n==Tempo ogé==\n* The [[low birth weight paradox]] is an example of Simpson\'s paradox in action.\n\n==Tumbu kaluar==\nFor a brief history of the origins of the paradox see the entries on Simpson\'s Paradox and Spurious Correlation in\n*[http://members.aol.com/jeff570/s.html Earliest known uses of some of the words of mathematics: S]\nFor a recent technical discussion with many references see\n*[http://singapore.cs.ucla.edu/R264.pdf Simpson\'s Paradox: An Anatomy by Judea Pearl]\n\n[[ja:シンプソンのパラドックス]]\n[[de:Simpson-Paradoxon]]\n[[Category:Paradoxes]]','/* See also */',13,'Budhi','20041224222127','',0,0,1,0,0.557453817948,'20041224222127','79958775777872'); INSERT INTO cur VALUES (1572,0,'Social_statistics','\'\'\'Statistik social\'\'\' nyaeta pamakean sistim ukuran [[statistik]] keur nalungtik paripolah [[manusa]] dina lingkungan [[social|sosial]]. Ieu bisa dipikanyaho ku cara [[poll|jajal pamanggih]] ti sabagian grup masarakat, evaluasi sabagian data ngeunaan grup masarakat, atawa ku panalungtikan jeung analisa statistik susunan data nu pakait jeung masarakat sarta paripolahna.\n\nBiasan, ahli sosial mateakeun dina [[Program evaluation|evaluasi]] kualitas [[service|palayanan]] sabagian grup organisasi, dina analisa paripolah grup masarakat dina lingkunganna, atawa dina nangtukeun naon nu butuh jeung kahayang masarakat ngaliwatan [[Sampling|sampling]] statistik.','',13,'Budhi','20040906043607','',0,0,0,0,0.81304382105,'20040906043607','79959093956392'); INSERT INTO cur VALUES (1573,0,'SPSS','[[Category:Software statistik]]\n\n[[Program komputer]] \'\'\'SPSS\'\'\' (Ing. \'\'\'\'\'S\'\'\'tatistical \'\'\'P\'\'\'ackage for the \'\'\'S\'\'\'ocial \'\'\'S\'\'\'ciences\'\') munggaran vérsi kahiji diwanohkeun dina taun 1960-an sarta ngarupakeun program ku loba dipaké pikeun [[statistik terapan|analisis statistik]] dina [[élmu sosial]]; ogé dipaké ku panalungtik pasar, panalungtik kaséhatan, pamaréntah, guu jeung nu séjénna.\n\nProgram SPSS dijual ku maskapé nu disebut ogé SPSS. Ieu rada ngabingungkeun, saprak parusahaan SPSS ngajual \'\'software\'\' keur analisis statistik - kaasup, teu sakadar ngan, program SPSS. Ngaran maskapéna singkatan tina \'\'\'\'\'S\'\'\'tatistical \'\'\'P\'\'\'roduct and \'\'\'S\'\'\'ervice \'\'\'S\'\'\'olutions\'\'. Sanajan kitu, hurup nu dipaké dina perangkat lunak ayeuna teu ngabogaan harti, saprak ngaluarkeun SPSS-x dina awal taun [[1980]]-an. \n\n\'\'SPSS Data Editor\'\' dipake keur mere gambaran ngeunaan [[uji statistik]], saperti tés keur [[correlation|korelasi]], [[multicollinearity|multicolinear]], sarta [[hypotheses|hipotesa]]; ieu bisa digawekeun ku panalungtik ku cara ngitung frekuensi, nyorir data, nyusun data sarta make data-asupan salaku alatm nu mibandan ngaran keur singgetan asupan. (Contona, ngaran asupan \"Richard\", sawaktu ngetik, sebutkeun, hurup R dina salah sahiji sel).\n\n\'\'SPSS Data Editor\'\' mibanda dua \"panémbong\" utama, \'\'Data View\'\' (tempat data asupan) sarta \'\'Variable View\'\', tempat keur milih ngaran, tipe, maksimum hurup per sél (\"width\"), jumlah titik désimal, ngaran, kandel sél (\"column\"), rataan dina sél (\"align\"), sarta aya atawa henteuna variabel nu mangrupa [[nominal]], [[ordinal]], atawa skala (\"measure\"). Dina \'\'Variable View\'\', bisa ogé ngararangkay asupan kana ngaran (ieu dipaké keur pasangan hurup tina kecap nu gedé, dina kolom \"Values\") sarta nandaan asupan nu salah (dina kolom \"Missing\").\n\n==Tumbu kaluar==\n*[http://www.spss.com SPSS Inc Homepage]\n*[http://www.spssusers.co.uk SPSS User Group Homepage]\n*[http://pages.infinit.net/rlevesqu/ Raynald Levesque\'s SPSS Tools] - support material for SPSS users\n*[http://www.gnu.org/software/pspp/pspp.html GNU PSPP] - a [[Free software|free software]] program that uses the SPSS language.\n\n[[de:SPSS]]\n[[en:SPSS]]\n[[es:SPSS]]\n[[pt:SPSS]]\n[[zh:社会科学统计包]]','warnfile Adding:de,en,pt',42,'Shizhao','20050303144010','',0,0,1,0,0.228652232899,'20050303144010','79949696855989'); INSERT INTO cur VALUES (1574,0,'Spurious_relationship','In [[statistics]], a \'\'\'spurious relationship\'\'\' (or, sometimes, \'\'\'spurious correlation\'\'\') is a [[mathematical relationship]] in which two occurrences have no logical connection, yet it may be implied that they do, due to a certain third, unseen factor (referred to as a \"confounding factor\" or \"lurking variable\"). The spurious relationship gives an impression of a worthy link between two groups that is invalid when objectively examined.\n\n==General example==\n\nAn example of a spurious relationship can be delineated by a city\'s [[ice cream]] sales. These sales are highest when the city\'s crime rate is highest. To allege that ice cream sales cause crime would be to imply a spurious relationship between the two. In reality, a [[heat wave]] may have caused both. The heat wave is an example of a hidden or unseen variable. \n\n==Statistics==\n\nThe term is commonly used in [[statistics]] and in particular in [[experimental techniques|experimental research]] techniques. Experimental research attempts to understand and predict causal relationships (X -> Y). A causal relationship can be contaminated by spurious variables (W -> X & Y), intervening variables (X -> W -> Y), and antecedent variables (W -> Y, X). Because of this, it is safest to present the conclusions of experimental research in terms of [[correlation]] instead of [[causation]].\n\n== See also ==\n\n*[[Logical fallacy]]\n*[[Joint effect]]\n\n==External links and references==\n\n* Burns, William C., \"\'\'[http://www.burns.com/wcbspurcorl.htm Spurious Correlations]\'\'\", 1997.','',13,'Budhi','20040904064735','',0,0,0,1,0.004556586502,'20040904064735','79959095935264'); INSERT INTO cur VALUES (1575,0,'St._Petersburg_paradox','In [[probability theory]] and [[decision theory]] the \'\'\'St. Petersburg paradox\'\'\' is a [[paradox]] that exhibits a [[random variable]] whose value is probably very small, and yet has an infinite [[nilai ekspektasi]]. This poses a situation where decision theory may superficially appear to recommend a course of action that no [[rationalism|rational]] person would be willing to take. That appearance evaporates when [[utility|utilities]] are taken into account. It was first ennunciated by [[Daniel Bernoulli]] in [[1738]].\n\nIn a [[game of chance]], you pay a fixed fee to enter, and then a coin will be tossed repeatedly until a \"head\" first appears. You win 1 cent if a head appears on the first toss, 2 cents if on the second, 4 cents if on the third, 8 cents if on the fourth, etc. It doubles with every toss. In short, you win\n2\'\'k\'\'−1 cents if the coin must be tossed \'\'k\'\' times.\n\nHow much would you be willing to pay to enter the game?\n\nThe [[probability]] that the first \'\'head\'\' occurs on the \'\'k\'\'th toss is:\n\n:p_k=\\frac{1}{2^k}.\n\nThe probability that you win more than $10.24 (i.e., 210 cents) is less than one in a thousand. The probability that you win more than $1 is less than one in a hundred. Nonetheless, the expected amount that you win is infinite! Here is how it is calculated:\n\n:E=\\sum_{k=1}^\\infty p_k 2^{k-1}\n=\\sum_{k=1}^\\infty {1 \\over 2}=\\infty.\n\nThis sum [[convergence|diverges]] to infinity. Thus, according to traditional [[nilai ekspektasi]] theory, no matter how much you pay to enter (imagine paying $1 billion each time, and winning only a few cents on nearly all occasions when you have paid that fee for the privilege) you will come out ahead in the long run, the idea being that on the very rare occasions when a large payoff comes along, it will far more than repay all the hundreds of trillions of dollars you have paid to play.\n\n[[Decision theory]] applied naively without taking utility into account would suggest that any fee, no matter how high, would be worth paying for this opportunity. In practice, no reasonable person would pay more than a few cents to enter.\n\nEncounter with the [[paradox]] leads to a deeper understanding of a variety of issues in [[economics]] and [[decision theory]], in particular:\n\n*[[Utility]];\n*Diminishing [[marginal utility]] of money;\n*[[Risk aversion]]; and\n*The \'\'gestalt\'\' of factors that are not simply represented in [[mathematical model]]s but which provide human decision-making with its context.\n\nFor example, according to diminishing marginal utility, 9 trillion dollars is not much more useful than 900 billion dollars, despite being ten times as large. Therefore, a one-in-900,000,000,000 chance of earning 900,000,000,000 cents is not worth even the one cent that naive decision theory says that it is.\n\nA way around that solution is to change the game so that it offers a quantity of utility (enough money, lifespan, knowledge, etc., arranged so that each prize is worth twice as much as the last) rather than money. In this case, the game should be worth an infinite amount. Possibly, however, there is a limit to the amount of utility that a person can have.\n\nIn addition, this does not take into account the fact that no person has the time and money necessary to play over the long run, or even a good approximation of it.\n\n==External link==\nFor a fuller treatment see:\n*[http://plato.stanford.edu/entries/paradox-stpetersburg/ \'\'St Petersburg Paradox\'\' - Stanford Encyclopaedia of Philosophy]\n\n==Reference==\nA translation of [[Daniel Bernoulli]]\'s original presentation is found in:\n*Bernoulli, Daniel: 1738, \"Exposition of a New Theory on the Measurement of Risk\", \'\'Econometrica\'\' vol 22 (1954), pp23-36.\n\n[[Category:Paradoxes]]','',13,'Budhi','20040917052127','',0,0,0,0,0.658421001238,'20040917052127','79959082947872'); INSERT INTO cur VALUES (1576,0,'Standar_kasalahan_(statistis)','Dina [[statistik]], ukuran \'\'\'standar kasalahan\'\'\', nilai atawa kuantitas ngarupakeun [[simpangan baku]] tina [[process|proses]] nu di-\'\'generate\'\'.\n\nSandar kasalahan nyaratkeun ukuran kateupastian sederhana dina nilai sarta remen dipake sabab:\n*Lamun standar kasalahan kuantitas sababaraha identitas dipikanyaho mangka standar kasalahan tina sababaraha [[Fungsi (matematik)|fungsi]] kuantitas bisa diitung sacara gampang di loba kasus;\n*Dimana [[probability distribution|sebaran probabiliti]] nilai nu dipikanyaho, bisa dipake keur ngitung [[interval kapercayaan]] sacara pasti; sarta\n*Dimana sebaran probabiliti teu dipikanyaho, kaitan saperti [[Chebyshev\'s inequality|Chebyshev]] atawa [[Vysochanskiï-Petunin inequality]] bisa dipake keur ngitung interval kapercayaan konservatif.\n\nStandar kasalahan sampel tina [[statistical population|populasi]] ngarupakeun [[simpangan baku]] tina [[sampling distribution|sebaran sampling]] sarta di-estimasi ku rumus:\n\n:\\frac{\\sigma}{\\sqrt{N}}\n\nnumana \\sigma ngarupakeun simpangan baku sebaran populasi sarta N nyaeta ukuran (jumlah barang) dina sampel.\n\nHal nu penting dina rumus ieu nyaeta kudu ngalikeun opat kali ukuran sampel (4X) ngarah ukuran kasalahanna jadi (1/2). Waktu rarangkay elmu statistik numana biaya ngarupakeun faktor, ieu ngarupakeun faktor nu kudu dipikaharti ngeunaan pentingna biaya.\n\n==Tempo oge==\n[[sampling distribution]], [[simpangan baku]]','',13,'Budhi','20041225044305','',0,0,1,0,0.716542911584,'20041225044305','79958774955694'); INSERT INTO cur VALUES (1577,0,'Statistical_arbitrage','\'\'\'Statistical arbitrage\'\'\', as opposed to (deterministic) [[arbitrage]], is the mispricing of one or more assets based on the expected value of these assets. For example, consider a game in which one flips a coin and collects $1 on heads or pays $0.50 on tails. In any single flip it is uncertain if one will win or lose money. However, in the statistical sense, there is an expected value of $1x50% - $0.50x50% = $0.25 for each flip. According to the [[law of large numbers]], the mean return on actual flips will approach this expected value as the number of flips increases. This is precisely the way in which casinos make their money.\n\n==Trading Strategy==\nAs a trading strategy, Statistical Arbitrage, or StatArb, is a heavily quantitative and computational approach to [[equity trading]]. It describes a variety of automated trading systems which commonly make use of [[data mining]], statisitical methods and [[artificial intelligence]] techniques. A popular strategy is [[pairs trading]], in which [[stocks]] are put into pairs by fundamental or market-based similarities. One stock in the pair is bought long, the other is sold short. This hedges risk from whole-market movements. [[Stephen N. P. Smith]] is one of the founders of this approach.\n\nReference:\nStatistical Arbitrage, by Stephen N. P. Smith, Wiley publications\n\n[[Category:Economics]]\n[[de:Statistical Arbitrage]]','',13,'Budhi','20040904065142','',0,0,0,1,0.397591576631,'20040904065142','79959095934857'); INSERT INTO cur VALUES (1578,0,'Statistical_assembly','A \'\'\'statistical assembly\'\'\' is a study of the relationships among the components in a [[statistical unit]] that is made of discrete components like organs or machine parts. Much of the observation for statistical assembly requires special preparation of the unit, which demands that the intervention must not prejudice the observations. A simple version of this kind of research uses the [[stimulus-response model]].','',13,'Budhi','20040904065241','',0,0,0,1,0.438294729422,'20040904070038','79959095934758'); INSERT INTO cur VALUES (1579,0,'Statistical_noise','\'\'\'Statistical noise\'\'\' is the [[colloquial term]] for recognized amounts of [[variation]] in a [[sample]].\n\n{{msg:Stub}}','',13,'Budhi','20040904065340','',0,0,0,1,0.175062720745,'20040904065340','79959095934659'); INSERT INTO cur VALUES (1580,0,'Paket_statistik','\'\'\'Paket statistik\'\'\' nyaeta salah sahiji tipe tina [[computer program|program komputer]] nu gede ngarupakeun hal husus keur [[applied statistics|analisa statistik]]. Hal ieu ngamungkinkeun keur jalma nu teu ngabogaan kamampuh dina program komputer keur nangtukeun hasil prosedur statistik standar sarta tes [[statistical significance|kasimpulan statistik]].\n\nConto paket statistik komersial nyaeta (dumasa kana urutan abjad):\n*[[GenStat]]\n*[[Macanova]]\n*[[Minitab]]\n*[[SAS inc|SAS]]\n*[[SPSS]]\n*[[StatView]]\n*[[Systat]]\n\nSanajan kitu, kiwari ngaran program make ngaran [[software company|parusahaan perangkat lunak]] nu dihasilkeunna (sarta perangkat lunak sejenna).\n\nAya oge sajumlah paket statistik gratis atawa nu kudu dibeuli, daptarna dina kaca tumbu di handap ieu.\n\n==Tumbu kaluar==\n*http://www.nag.co.uk/stats/tt_soft.asp (site [[Numerical Algorithms Group]], keur inpormasi leuwih jentre ngeunaan GenStat)\n*http://www.minitab.com\n*http://www.sas.com\n*http://www.statview.com\n*http://www.systat.com\n*http://www.spss.com\n* [http://gsociology.icaap.org/methods/soft.html Free Statistical Programs]\n* [http://members.aol.com/johnp71/javasta2.html John C. Pezzullo\'s list of free statistical software]\n* [http://freestatistics.altervista.org/Software.html Free Statistical Software]\n\n[[Category:Statistical software]]','',13,'Budhi','20040907060929','',0,0,0,0,0.176078898914,'20040907060955','79959092939070'); INSERT INTO cur VALUES (1581,0,'Fenomena_statistik','Ieu lain percobaan dina [[daptar jejer statistis]] nu lengkep; tempo artikel.\n\n==[[phenomena]] [[statistik]] nu bisa ditalungtik==\n\n* [[Regression toward the mean]]\n* [[Simpson\'s paradox]]\n* [[Statistical dispersion]]\n* [[Statistical independence]]\n* [[Correlation]]\n* [[Zipf-Mandelbrot law]]\n* [[Benford\'s law]]','',13,'Budhi','20040905114058','',0,0,0,0,0.03204702308,'20040905114141','79959094885941'); INSERT INTO cur VALUES (1582,0,'Populasi_statistik','Dina [[statistik]], \'\'\'populasi statistik\'\'\' nyaeta [[set|susunan]] nu bener-bener aya ngeunaan [[statistical inference|kaputusan statistik]] nu keur digambarkeun, ilaharna dumasar kana sampel random nu dicokot tina populasi. Contona, lamun urang kataji dina nalungtik ngeunaan manuk gagak, mangka urang bakal ngajelaskeun susunan manuk gagak nu keur ditalungtik. Perhatikeun lamun urang milih populasi upamana \'\'sakabeh manuk gagak\'\', urang bakal ngawatesan observasi manuk gagak nu aya ayeuna sarta nu bakal aya dina mangsa nu bakal datang. Kamungkinanna, [[géografi]] oge bakal ngawatesan kana sumberdaya urang keur nalungtik manuk gagak.\n\n\"Populasi\" ilahar oge dipake keur nuduhkeun susunan ukuran atawa nilai. Anggap, keur contona, urang museurkeun kana susunan sakabeh manuk gagak kolot nu aya di wewengkon Kent, sarta urang hayang nyaho kana mean beurat ieu manuk gagak. Keur unggal manuk dina populasi diukur beuratna, sarta susunan beurat ieu disebut \"populasi beurat\".\n\n\'\'\'Tempo ogé:\'\'\' [[populasi]], [[statistik]], [[statistical sample|sampel statistik]]\n\n[[da:Population (statistik)]] [[en:Population (statistics)]] [[es:población estadística]]','',3,'Kandar','20040907081423','',0,0,0,0,0.678371195997,'20040907081423','79959092918576'); INSERT INTO cur VALUES (1583,0,'Statistical_regularity','\'\'\'Statistical regularity\'\'\' is a notion in [[statistics]] that if we throw a thumbtack onto a table once, we would have a hard time predicting whether the point would touch the surface of the table or not. But if we repeat this experiment many times, we will see that the number of times the point touches the surface divided by the number of throws will eventually stabilize at a specific value. \n\nSimilar experiments with coins, dice, and roulette wheels reinforce the main idea. Repeating a series of trials will produce similar, but not identical, results for each series. This phenomenon is called \'\'\'statistical regularity\'\'\'.\n\nThe same idea occurs in [[games of chance]], [[demographic statistics]], [[quality control]] of a manufacturing process, and in many other parts of our lives.\n\nObservations of this phenomenon provided the initial motivation for the concept of what is now known as [[frequency probability]].','',13,'Budhi','20040904065839','',0,0,0,1,0.089061111719,'20041224120715','79959095934160'); INSERT INTO cur VALUES (1585,0,'Statistical_unit','In different [[statistical]] disciplines, the \'\'\'statistical unit\'\'\' is the source of a [[random variable]]. There are different ways to study a unit and different names applied \n\n#We may be interested in a \'\'unit\'\' because we intend to generalize from observations on a few units to a [[statistical assembly]] of units. [[Opinion polling]] and [[survey sampling]] provide well known examples of this type of research.\n#We may be interested in the dynamics of a \'\'unit\'\', how its observable characteristics change from time to time. Economic studies of business firms provide an example of this type of research. (See [[dynamic model]].) \n#We may be interested in the internal functioning of a \'\'unit\'\' which we can characterize as a [[statistical assembly]]. This kind of research often involves interference with the unit such as subjecting it to a treatment or even dissection, in some cases. Field experimentation and [[clinical trial]]s. are examples.\n\nTempo oge: [[model statistik]]','',13,'Budhi','20040908023516','',0,0,0,0,0.937174379796,'20040908023516','79959091976483'); INSERT INTO cur VALUES (1586,0,'Statistics_Belgium','\'\'\'Statistik Belgia\'\'\' kantor pusat lembaga statistik di [[Belgium | Belgian]] nyadikeun data dina gambar gede.\n\n==Tumbu kaluar==\n*[http://www.statbel.fgov.be/ Statistics Belgium website]\n\n{{msg:stub}}','',13,'Budhi','20040904070642','',0,0,0,0,0.092754809695,'20040904070642','79959095929357'); INSERT INTO cur VALUES (1587,0,'Statistics_New_Zealand','\'\'\'Statistik Selandia Baru\'\'\' (\'\'\'Te Tari Tatau\'\'\') ngarupakeun lembaga pamarentah [[New Zealand]], sarta sumber tina kantor [[statistik]]. Ti heula ngaranna \'\'Department of Statistics\'\'.\n\n\"Information obtained from Statistics New Zealand may be freely used, reproduced, or quoted unless otherwise specified. In all cases Statistics New Zealand must be acknowledged as the source.\"\n\n== Tumbu kaluar ==\n*[http://www.stats.govt.nz/ Statistics New Zealand Website]
\n\n\n{{pondok}}\n\n[[en:Statistics New Zealand]]','apostrophe and updated stub message, and copyright note',38,'Robin Patterson','20050209000424','',0,0,0,0,0.558320121168,'20050303211247','79949790999575'); INSERT INTO cur VALUES (1588,0,'Poisson_distribution','#REDIRECT [[Sebaran Poisson]]\n','Poisson distribution dipindahkeun ka Sebaran Poisson',3,'Kandar','20040904091906','',0,1,0,1,0.0474532163212571,'20040904091906','79959095908093'); INSERT INTO cur VALUES (1589,0,'Random_data','#REDIRECT [[Data random]]\n','Random data dipindahkeun ka Data random',13,'Budhi','20040904122831','',0,1,0,1,0.471218010849522,'20040904122831','79959095877168'); INSERT INTO cur VALUES (1590,0,'Fisher_information','#REDIRECT [[Informasi Fisher]]\n','Fisher information dipindahkeun ka Informasi Fisher',13,'Budhi','20040904135857','',0,1,0,1,0.213730436017486,'20040904135857','79959095864142'); INSERT INTO cur VALUES (1591,0,'Non-parametric_statistics','#REDIRECT [[Statistik non-parametrik]]\n','Non-parametric statistics dipindahkeun ka Statistik non-parametrik',13,'Budhi','20040904141004','',0,1,0,1,0.654998178272506,'20040904141004','79959095858995'); INSERT INTO cur VALUES (1592,0,'Summary_statistics','#REDIRECT [[Kasimpulan statistik]]\n','Summary statistics dipindahkeun ka Kasimpulan statistik',13,'Budhi','20040904143011','',0,1,0,1,0.63379961404372,'20040904143011','79959095856988'); INSERT INTO cur VALUES (1593,0,'Semivariance','#REDIRECT [[Semivarian]]\n','Semivariance dipindahkeun ka Semivarian',13,'Budhi','20040904144616','',0,1,0,1,0.204003566134724,'20040904144616','79959095855383'); INSERT INTO cur VALUES (1594,0,'Weibull_distribution','#REDIRECT [[Sebaran Weibull]]\n','Weibull distribution dipindahkeun ka Sebaran Weibull',13,'Budhi','20040904152509','',0,1,0,1,0.118619019276108,'20040904152509','79959095847490'); INSERT INTO cur VALUES (1595,0,'Algorithms_for_calculating_variance','#REDIRECT [[Algoritma keur ngitung varian]]\n','Algorithms for calculating variance dipindahkeun ka Algoritma keur ngitung varian',13,'Budhi','20040904233800','',0,1,0,1,0.98108442871001,'20040904233800','79959095766199'); INSERT INTO cur VALUES (1596,0,'Absolute_deviation','#REDIRECT [[Simpangan mutlak]]\n','Absolute deviation dipindahkeun ka Simpangan mutlak',13,'Budhi','20040904235031','',0,1,0,1,0.549565116455373,'20040904235031','79959095764968'); INSERT INTO cur VALUES (1597,6,'Accuracy_and_precision.png','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040904235649','',0,0,0,1,0.804572326880481,'20041229230152','79959095764350'); INSERT INTO cur VALUES (1598,0,'Linear_prediction','#REDIRECT [[Prediksi linier]]\n','Linear prediction dipindahkeun ka Prediksi linier',13,'Budhi','20040905043349','',0,1,0,1,0.374166315769932,'20040905043349','79959094956650'); INSERT INTO cur VALUES (1599,0,'Location_parameter','#REDIRECT [[Parameter lokasi]]\n','Location parameter dipindahkeun ka Parameter lokasi',13,'Budhi','20040905064702','',0,1,0,1,0.457114628941859,'20040905064702','79959094935297'); INSERT INTO cur VALUES (1600,0,'Median_test','#REDIRECT [[Tes nilai tengah]]\n','Median test dipindahkeun ka Tes nilai tengah',13,'Budhi','20040905113042','',0,1,0,1,0.163074228133144,'20040905113042','79959094886957'); INSERT INTO cur VALUES (1601,0,'Mean_deviation','#REDIRECT [[Simpangan mean]]\n','Mean deviation dipindahkeun ka Simpangan mean',13,'Budhi','20040905113523','',0,1,0,1,0.444027284573789,'20040905113523','79959094886476'); INSERT INTO cur VALUES (1602,0,'Statistical_phenomena','#REDIRECT [[Fenomena statistik]]\n','Statistical phenomena dipindahkeun ka Fenomena statistik',13,'Budhi','20040905114141','',0,1,0,1,0.730913769203158,'20040905114141','79959094885858'); INSERT INTO cur VALUES (1603,0,'Standard_error_(statistics)','#REDIRECT [[Standar kasalahan (statistis)]]\n','Standard error (statistics) dipindahkeun ka Standar kasalahan (statistis)',13,'Budhi','20040906003512','',0,1,0,1,0.322487023028067,'20040906003512','79959093996487'); INSERT INTO cur VALUES (1604,0,'Sampling_distribution','#REDIRECT [[Sebaran sampling]]\n','Sampling distribution dipindahkeun ka Sebaran sampling',13,'Budhi','20040906005613','',0,1,0,1,0.419693838264508,'20040906005613','79959093994386'); INSERT INTO cur VALUES (1605,0,'Order_statistic','#REDIRECT [[Order statistik]]\n','Order statistic dipindahkeun ka Order statistik',13,'Budhi','20040906022800','',0,1,0,1,0.131008152971983,'20040906022800','79959093977199'); INSERT INTO cur VALUES (1606,0,'Pareto_interpolation','#REDIRECT [[Interpolasi Pareto]]\n','Pareto interpolation dipindahkeun ka Interpolasi Pareto',13,'Budhi','20040906024745','',0,1,0,1,0.395959280800036,'20040906024745','79959093975254'); INSERT INTO cur VALUES (1607,0,'Density_estimation','#REDIRECT [[Estimasi densiti]]\n','Density estimation dipindahkeun ka Estimasi densiti',13,'Budhi','20040906025443','',0,1,0,1,0.586771975817878,'20040906025443','79959093974556'); INSERT INTO cur VALUES (1608,0,'Parametric_statistics','#REDIRECT [[Statistik parametrik]]\n','Parametric statistics dipindahkeun ka Statistik parametrik',13,'Budhi','20040906030159','',0,1,0,1,0.745982067422925,'20040906030159','79959093969840'); INSERT INTO cur VALUES (1609,0,'Analysis_of_variance','#REDIRECT [[Analisa varian]]\n','Analysis of variance dipindahkeun ka Analisa varian',13,'Budhi','20040906032631','',0,1,0,1,0.969594440394635,'20040906032631','79959093967368'); INSERT INTO cur VALUES (1610,0,'Margin_of_error','#REDIRECT [[Margin kasalahan]]\n','Margin of error dipindahkeun ka Margin kasalahan',13,'Budhi','20040906035454','',0,1,0,1,0.610026030438045,'20040906035454','79959093964545'); INSERT INTO cur VALUES (1611,0,'Point_estimation','#REDIRECT [[Titik estimasi]]\n','Point estimation dipindahkeun ka Titik estimasi',13,'Budhi','20040906040839','',0,1,0,1,0.141346861739966,'20040906040839','79959093959160'); INSERT INTO cur VALUES (1612,0,'Random_sequence','#REDIRECT [[Sekuen random]]\n','Random sequence dipindahkeun ka Sekuen random',13,'Budhi','20040906042902','',0,1,0,1,0.87665624811934,'20040906042902','79959093957097'); INSERT INTO cur VALUES (1613,0,'Opinion_poll','#REDIRECT [[Jajal pamanggih]]\n','Opinion poll dipindahkeun ka Jajal pamanggih',13,'Budhi','20040906051726','',0,1,0,1,0.959240686110445,'20040906051726','79959093948273'); INSERT INTO cur VALUES (1614,0,'Exponential_distribution','#REDIRECT [[Sebaran eksponensial]]\n','Exponential distribution dipindahkeun ka Sebaran eksponensial',13,'Budhi','20040906224105','',0,1,0,1,0.166234716927851,'20040906224105','79959093775894'); INSERT INTO cur VALUES (1615,0,'Statistical_model','#REDIRECT [[Model statistik]]\n','Statistical model dipindahkeun ka Model statistik',13,'Budhi','20040906225316','',0,1,0,1,0.953451557041566,'20040906225316','79959093774683'); INSERT INTO cur VALUES (1616,0,'Population_dynamics','#REDIRECT [[Dinamika populasi]]\n','Population dynamics dipindahkeun ka Dinamika populasi',13,'Budhi','20040907001936','',0,1,0,1,0.268553665157923,'20040907001936','79959092998063'); INSERT INTO cur VALUES (1617,0,'Hazard_ratio','#REDIRECT [[Rasio bencana]]\n','Hazard ratio dipindahkeun ka Rasio bencana',13,'Budhi','20040907010615','',0,1,0,1,0.482413685398562,'20040907010615','79959092989384'); INSERT INTO cur VALUES (1618,0,'Information_bottleneck_method','#REDIRECT [[Metoda inpormasi leherbotol]]\n','Information bottleneck method dipindahkeun ka Metoda inpormasi leherbotol',13,'Budhi','20040907011829','',0,1,0,1,0.606407462252683,'20040907011829','79959092988170'); INSERT INTO cur VALUES (1619,0,'Random_sample','#REDIRECT [[Sampel random]]\n','Random sample dipindahkeun ka Sampel random',13,'Budhi','20040907025242','',0,1,0,1,0.584796285801377,'20040907025242','79959092974757'); INSERT INTO cur VALUES (1620,0,'Square_root','#REDIRECT [[Akar kuadrat]]\n','Square root dipindahkeun ka Akar kuadrat',3,'Kandar','20040907034151','',0,1,0,1,0.104759072982482,'20040907034151','79959092965848'); INSERT INTO cur VALUES (1621,0,'Mean_squared_error','#REDIRECT [[Mean kuadrat kasalahan]]\n','Mean squared error dipindahkeun ka Mean kuadrat kasalahan',13,'Budhi','20040907041657','',0,1,0,1,0.769406538241922,'20040907041657','79959092958342'); INSERT INTO cur VALUES (1622,0,'Least_squares','#REDIRECT [[Kuadrat leutik]]\n','Least squares dipindahkeun ka Kuadrat leutik',13,'Budhi','20040907042944','',0,1,0,1,0.532755502995807,'20040907042944','79959092957055'); INSERT INTO cur VALUES (1623,0,'Statistical_dispersion','#REDIRECT [[Dispersi statistik]]\n','Statistical dispersion dipindahkeun ka Dispersi statistik',13,'Budhi','20040907045958','',0,1,0,1,0.355557930986917,'20040907045958','79959092954041'); INSERT INTO cur VALUES (1624,0,'Statistical_estimation','#REDIRECT [[Estimasi statistik]]\n','Statistical estimation dipindahkeun ka Estimasi statistik',13,'Budhi','20040907051555','',0,1,0,1,0.179523176680806,'20040907051555','79959092948444'); INSERT INTO cur VALUES (1625,0,'Inferential_statistics','#REDIRECT [[Kaputusan statistik]]\n','Inferential statistics dipindahkeun ka Kaputusan statistik',13,'Budhi','20040907053147','',0,1,0,1,0.830942121176927,'20040907053147','79959092946852'); INSERT INTO cur VALUES (1626,0,'Statistical_package','#REDIRECT [[Paket statistik]]\n','Statistical package dipindahkeun ka Paket statistik',13,'Budhi','20040907060955','',0,1,0,1,0.616141106575859,'20040907060955','79959092939044'); INSERT INTO cur VALUES (1627,0,'Statistical_parameter','#REDIRECT [[Parameter statistik]]\n','Statistical parameter dipindahkeun ka Parameter statistik',13,'Budhi','20040907062050','',0,1,0,1,0.58787920008216,'20040907062050','79959092937949'); INSERT INTO cur VALUES (1628,0,'Table_of_mathematical_symbols','#REDIRECT [[Daptar lambang matematis]]\n','Table of mathematical symbols dipindahkeun ka Daptar lambang matematis',3,'Kandar','20040907063023','',0,1,0,1,0.0909727114168673,'20040907063023','79959092936976'); INSERT INTO cur VALUES (1629,0,'Daptar_lambang_matematis','#REDIRECT [[Tabel lambang matematis]]\n','Daptar lambang matematis dipindahkeun ka Tabel lambang matematis',3,'Kandar','20040907064326','',0,1,0,1,0.691225987571502,'20040907064326','79959092935673'); INSERT INTO cur VALUES (1630,0,'Concrete_illustration_of_the_central_limit_theorem','#REDIRECT [[Gambaran kongkrit teorema central limit]]\n','Concrete illustration of the central limit theorem dipindahkeun ka Gambaran kongkrit teorema central limit',13,'Budhi','20040907065922','',0,1,0,1,0.183211834340554,'20040907065922','79959092934077'); INSERT INTO cur VALUES (1631,0,'Graphical_model','#REDIRECT [[Model grapik]]\n','Graphical model dipindahkeun ka Model grapik',13,'Budhi','20040907073019','',0,1,0,1,0.842381239721907,'20040907073019','79959092926980'); INSERT INTO cur VALUES (1632,0,'Statistical_population','#REDIRECT [[Populasi statistik]]\n','Statistical population dipindahkeun ka Populasi statistik',13,'Budhi','20040907080343','',0,1,0,1,0.662270726321517,'20040907080343','79959092919656'); INSERT INTO cur VALUES (1633,0,'Statistical_assumptions','#REDIRECT [[Asumsi statistik]]\n','Statistical assumptions dipindahkeun ka Asumsi statistik',13,'Budhi','20040908025655','',0,1,0,1,0.784209943175511,'20040908025655','79959091974344'); INSERT INTO cur VALUES (1634,0,'Farmasi','\'\'\'Farmasi\'\'\' sacara historis nyaéta [[pagawéan]] méré [[ubar]]. Kadieunakeun, istilah ieu jadi ngawengku fungsi séjén nu patali jeung [[mulasara pasén]] (fungsi klinis), nu kiwari sapalih ti antarana aya dina hukum féderal atawa nagara.\nThese include monitoring [[medical prescription]]s for appropriateness, for adverse drug [[interaction]]s and following the course of [[therapy]] to insure positive outcomes. \nPharmacy is thus distinct from [[pharmacology]], an academic [[discipline]] which includes the study of [[mechanism]]s of [[drug action]]. In most jurisdictions, [[pharmacist]]s are regulated separately from [[physician]]s hence the separate [[profession]]. \nIn other [[jurisdiction]]s, the [[doctor]] is allowed to dispense [[drug]]s themselves and the [[practice]] of pharmacy is integrated with that of the [[physician]]. \nWhere so regulated, only pharmacists may dispense certain [[pharmaceutical]]s, typically [[narcotic]]s and [[antibiotic]]s.\n\nIn the United States, a person must pass the [[Naplex]] examination before they can practice pharmacy.\n----\n\nA \'\'\'pharmacy\'\'\' (known also as a \'\'\'chemist\'s\'\'\' or in [[American English]] a \'\'\'drugstore\'\'\', or historically an \'\'\'[[Apothecary]]\'\'\') is also a place where pharmacists (chemists) practise the profession of pharmacy. \nMany [[retailer]]s (including [[grocery store]]s and [[mass merchandiser]]s) now include a pharmacy as department of their store. Many pharmacies also sell household items. Within pharmacies, the term \"dispensary\" is sometimes used to distinguish that part of the store which pharmacists practise pharmacy. \nThe dispensary is subject to pharmacy legislation. The rest of the pharmacy is simply a retail store.\n\nPharmacies are also located within [[hospital]]s and [[nursing home]]s and function as a department of these larger organizations. Such pharmacies are known within the pharmacy industry as \"hospital pharmacies\" to distinguish from \"retail\" or \"community\" pharmacies. \nPharmacists in hospital pharmacies often have more complex medications whereas pharmacists in community pharmacies often have more complex business and customer relations issues. \nIn [[medical building]]s where [[physician]]s and other medical professionals congregate, a small community pharmacy may be present as well for the convenience of [[patient]]s. Such a \"medical pharmacy\" is legally distinct from the other medical professionals, unlike the pharmacies integrated into [[hospital]]s. A medical pharmacy is in fact a [[community pharmacy]].\n\nThe [[icon]] most commonly associated with the practise of pharmacy in the [[United States]] is the [[mortar and pestle]]; in [[France]], it is a green [[Greek cross]].\n\n\n\n==See also==\n
  • [[List of pharmacies]]
    \n
  • [http://www.pharmacist.com Pharmacist.com] Very useful site for pharmacists and pharmacy students.
    \n
  • [http://www.nabp.net National association of Boards of Pharmacy] Home of the National association of Boards of Pharmacy\n\n[[de:Apotheke]]\n[[nds:Aftheiken]]\n[[zh:药学]]\n[[Category:Pharmacies]]','',3,'Kandar','20040908064414','',0,0,0,1,0.240738878604,'20040908064414','79959091935585'); INSERT INTO cur VALUES (1635,0,'Polynomial_interpolation','\'\'\'Téks kandel\'\'\'polinomial','',0,'202.72.207.195','20040909131712','',0,0,0,1,0.390247674375,'20040909131712','79959090868287'); INSERT INTO cur VALUES (1636,6,'Halton_seq_01.jpg','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040910002900','',0,0,0,1,0.93423756764665,'20050208235642','79959089997099'); INSERT INTO cur VALUES (1637,6,'Halton_seq_03.gif','Ti Wikipedia English','Ti Wikipedia English',13,'Budhi','20040910003142','',0,0,0,1,0.318558039440362,'20050208235642','79959089996857'); INSERT INTO cur VALUES (1638,0,'Halton_sequences','#REDIRECT [[Sekuen Halton]]\n','Halton sequences dipindahkeun ka Sekuen Halton',13,'Budhi','20040910010444','',0,1,0,1,0.790077524995504,'20040910010444','79959089989555'); INSERT INTO cur VALUES (1639,0,'System_dynamics','#REDIRECT [[Dinamika sistim]]\n','System dynamics dipindahkeun ka Dinamika sistim',13,'Budhi','20040910011930','',0,1,0,1,0.994713537390077,'20040910011930','79959089988069'); INSERT INTO cur VALUES (1640,0,'Expected_value','#REDIRECT [[Nilai ekspektasi]]\n','Expected value dipindahkeun ka Nilai ekspektasi',13,'Budhi','20040917002550','',0,1,0,1,0.60333514269752,'20040917002550','79959082997449'); INSERT INTO cur VALUES (1641,0,'Cochran\'s_theorem','#REDIRECT [[Teorema Cochran]]\n','Cochran\'s theorem dipindahkeun ka Teorema Cochran',13,'Budhi','20040917064007','',0,1,0,1,0.939727708204,'20040917064007','79959082935992'); INSERT INTO cur VALUES (1642,0,'Pseudo-random_number','','blank',0,'213.107.224.14','20041101010333','',0,0,0,0,0.080913006366,'20041101010333','79958898989666'); INSERT INTO cur VALUES (1643,8,'Categoriespagetext','Kategori-kategori di handap ieu aya na wiki.','',3,'Kandar','20040924071140','',0,0,0,1,0.429556127838,'20040924071140','79959075928859'); INSERT INTO cur VALUES (1645,2,'Davidcannon','{{NUMBEROFARTICLES}}','',21,'Davidcannon','20040928021312','',0,0,0,1,0.408012274377,'20040928021312','79959071978687'); INSERT INTO cur VALUES (1646,0,'Fisika_tioritis','\'\'\'Tiori Fisika\'\'\' nyoba mikaharti dunya kujalan nyieun model-model tina alam/zat nyata, dipake jang ngakalan, nerangkeun, nyawang phenomena fisika kucara \"\'\'tiori fisika\'\'\". Aya tilu tiori nu geus tangtu; teori \"mainstream\", tiori \"proposed\" sarta tiori \"fringe\" . \n\nSababarahahiji tiori dimimitian ku panalungtikan, whereas others are not. A physical theory is a model of physical events and cannot be proved from basic axioms. A physical theory is different from a mathematical theorem. Physical theories model reality and are a statement of what has been observed, and provide predictions of new observations.\n\nPhysical theories can become accepted if they are able to make correct predictions and avoid incorrect ones. Physical theories which are simpler tend to be accepted over theories which are complex. Physical theories are more likely to be accepted if they connect a wide range of phenomena. The process of testing a physical theory is part of the [[scientific method]]. \n\nTheoretical physics is just one important part of [[physics]]; the other part is [[experimental physics]]. The difference between theoretical physics and [[mathematical physics]] is that mathematical physics finds the mathematical rigor required in [[mathematics]] to be more important than the contact with experiments and observations.','',23,'Ruhe ruhe','20040928074140','',0,0,0,1,0.763837702928,'20040928074140','79959071925859'); INSERT INTO cur VALUES (1647,1,'Géologi','kuring teh mimitian masuk ka web ngeunaan geology tapi bahasa nu digunakeun basa Sunda, mani surpes urangmah. Tapi saha nu nyieun ieu web teh???','',0,'152.118.24.3','20040930031619','',0,0,0,1,0.531797651915,'20040930031619','79959069968380'); INSERT INTO cur VALUES (1648,0,'Time_series','#REDIRECT [[Deret waktu]]\n','Time series dipindahkeun ka Deret waktu',13,'Budhi','20041004003118','',0,1,0,1,0.476120740397,'20041004003118','79958995996881'); INSERT INTO cur VALUES (1650,0,'Bodor','Bodor nyaeta laku-lampah anu matak pikaseurieun. Laku-lampah di dieu bisa dihartikeun boh ucapan, gerak-gerik, atawa tulisan, anu dihaja ngondang pikaseurieun.','',0,'202.159.98.236','20041221023813','',0,0,0,0,0.326461339056,'20050207074124','79958778976186'); INSERT INTO cur VALUES (1651,0,'Nineteenth_century','#REDIRECT [[Abad ka-19]]\n','Nineteenth century dipindahkeun ka Abad ka-19',3,'Kandar','20041008033410','',0,1,0,1,0.823343451053,'20041008033410','79958991966589'); INSERT INTO cur VALUES (1653,0,'Lésitin','\'\'\'Lésitin\'\'\' biasana dipaké salaku sinonim pikeun \'\'\'fosfatidilkolin\'\'\', hiji [[fosfolipid]] nu ngarupakeun komponén utama fraksi fosfatida nu bisa diékstraksi tina [[konéng endog|konéng]] [[endog]] (dina [[basa Yunani]] lekithos - λεκιθος), atawa kacang [[kedelé]]. Lésitin sacara komersil aya nu didagangkeun dina kaayaan murni pikeun kaperluan suplemén dahareun jeung médis.\n\n==Na biologi==\nLésitin pikeun [[saraf]] jeung sirkulatoris dijieun na [[ati]] mun asupan dahareunana nyukupan. Lésitin dipikabutuh ku unggal [[sél]] na awak sarta ngarupakeun komponén konci [[mémbran sél]]; tanpa lésitin, mémbran bakal heuras. Lésitin ngajaga sél tina oxidasi sarta jadi taméng sabudeureun [[uteuk]]. Lésitin utamana diwangun ku [[Vitamin B]], [[asam fosfat]], [[kolin]], [[asam linoléat]], jeung [[inositol]]. Jadi, lésitin ngarojong [[sistim sirkulasi]].\n\n==Salaku aditif dahareun==\nLésitin dianggap salaku [[pangémulsi]] nu aman nu geus disatujuan ku [[Food and Drug Administration|FDA]] [[Amérika Sarikat|AS]] pikeun tujuan konsumsi manusa kalawan status sacara umum aman (\"Generally Recognized As Safe\"). Lésitin ngarupakeun bagian integral mémbran sél, sarta bisa [[métabolisme|diolah]] sagemblengna, sahingga écés amanna pikeun manusa. Pangémulsi séjén ngan bisa diékskrésikeun ngaliwatan [[ginjal]].\n\nLésitin dipigunakeun sacara komersil pikeun sarupaning nu merlukeun pangémulsi atawa \'\'[[lubricant]]\'\' alami, ti [[farmasi]] nepi ka protective coverings. Pikeun conto, lésitin dipaké pikeun ngajaga [[coklat]] jeung [[sari kalapa]] na permén sangkan tetep ngahiji.\n\nRupa-rupa panalungtikan (Brook \'\'et al.\'\' 1986, Spilburg \'\'et al.\'\' 2003) nunjukkeun yén lésitin turunan kadelé mangaruhan kadar [[kolésterol]] jeung [[trigliserida]] na getih sacara positif.\n\n==Tempo ogé==\n*[[biokimia]]\n*[[kolin]]\n*[[lipid]]\n*[[lapis ganda lipid]]\n\n==Rujukan==\n*Brook JG, Linn S, Aviram M. \'\'Dietary soya lecithin decreases plasma triglyceride levels and inhibits collagen-and ADP-induced platelet aggregation.\'\' Biochem Med Metab Biol 1986;35:31-9. PMID [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3778675&dopt=Abstract 3778675].\n* Spilburg CA, Goldberg AC, McGill JB, Stenson WF, Racette SB, Bateman J, McPherson TB, Ostlund RE Jr. \'\'Fat-free foods supplemented with soy stanol-lecithin powder reduce cholesterol absorption and LDL cholesterol\'\'. J Am Diet Assoc 2003;103:577-81. PMID [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12728215&dopt=Abstract 12728215].\n\n==Tumbu kaluar==\n*[http://www2.chemie.uni-erlangen.de/services/dissonline/data/dissertation/Christoph_Wabel/html/Chapter1.html Introduction to Lecithin] ([[University of Erlangen]])\n\n[[Category:Aditif dahareun]]\n[[Category:Fosfolipid]]\n[[Category:Produk kadelé]]\n\n[[en:Lecithin]]','/* Na biologi */',3,'Kandar','20041111101642','',0,0,0,0,0.50407228782,'20050302051215','79958888898357'); INSERT INTO cur VALUES (1654,14,'Probability_and_statistics','','',3,'Kandar','20041012085520','',0,0,0,0,0.222185959677,'20041225233359','79958987914479'); INSERT INTO cur VALUES (1656,0,'Golongan_tabel_periodik','\'\'\'Golongan tabel periodik\'\'\' ngarupakeun kolom vértikal na [[tabel periodik]]. Aya 18 golongan dina tabel periodik baku.\n\nLain teu ngahaja yén sababaraha tina béréndélan ieu saluyu jeung [[dérét kimia]]: tabel periodik mimitina dijieun pikeun nyusun béréndélan bahan kimia na skéma tunggal nu kohérén. \n\nDadaran modérn pikeun pola tabel periodik nyaéta yén unsur-unsur nu sagolongan mibanda konfigurasi [[kulit éléktron]] pangluarna nu sarupa dina atomna: kusabab sipat kimiawi lolobana ditangtukeun ku interaksi éléktron luarna, mangka unsur nu sagolongan bakal mibanda boh [[sipat fisik]] atawa [[sipat kimia|kimia]] nu sarupa.\n\n==Nomer golongan==\nAya tilu cara pikeun nganomeran golongan tabel periodik, nu hiji maké [[angka Arab]], sedengkeun dua nu séjénna migunakeun [[angka Romawi]]. Ngaran angka Romawi ngarupakeun ngaran tradisional asli golongan; angka Arab mangrupa ngaran nu dirujuk ku \'\'[[International Union of Pure and Applied Chemistry]]\'\' (IUPAC) pikeun ngaganti ngaran heubeul nu sok pajeulit.\n\nThere is considerable confusion surrounding the two old systems in use (old IUPAC and CAS) that combined the use of Roman numerals with letters. In the old IUPAC system the letters A and B were designated to the left (A) and right (B) part of the table, while in the CAS system the letters A and B were designated to main group elements (A) and transition elements (B). The former system was frequently used in Europe while the latter was most common in America. The new IUPAC scheme was developed to replace both systems as they confusingly used the same names to mean different things.\n\n\nGolongan tabel periodik nyaéta saperti di handap ieu (nu na jero kurung nunjukkeun sistim heubeul: Éropa jeung Amérika):\n\n* [[Unsur golongan 1|Golongan 1]] (IA,IA): [[Logam alkali]]\n* [[Unsur golongan 2|Golongan 2]] (IIA,IIA): [[Logam taneuh alkali]]\n* [[Unsur golongan 3|Golongan 3]] (IIIA,IIIB)\n* [[Unsur golongan 4|Golongan 4]] (IVA,IVAB)\n* [[Unsur golongan 5|Golongan 5]] (VA,VB)\n* [[Unsur golongan 6|Golongan 6]] (VIA,VIB)\n* [[Unsur golongan 7|Golongan 7]] (VIIA,VIIB)\n* [[Unsur golongan 8|Golongan 8]] (VIII)\n* [[Unsur golongan 9|Golongan 9]] (VIII)\n* [[Unsur golongan 10|Golongan 10]] (VIII)\n* [[Unsur golongan 11|Golongan 11]] (IB,IB): \'\'[[Coinage metal]]\'\' (Not an [[IUPAC]] recommended name)\n* [[Unsur golongan 12|Golongan 12]] (IIB,IIB)\n* [[Unsur golongan 13|Golongan 13]] (IIIB,IIIA): [[Golongan Boron]]\n* [[Unsur golongan 14|Golongan 14]] (IVB,IVA): the [[Golongan Karbon]]\n* [[Unsur golongan 15|Golongan 15]] (VB,VA): the [[Pnictogen]]s (Not an [[IUPAC]]-recommended name)(Ogé katelah [[Golongan Nitrogén]])\n* [[Unsur golongan 16|Golongan 16]] (VIB,VIA): [[Chalcogen]]\n* [[Unsur golongan 17|Golongan 17]] (VIIB,VIIA): [[Halogén]]\n* [[Unsur golongan 18|Golongan 18]] (Golongan 0): [[Gas Mulya]]\n\n----\nCatetan: \'\'Gaya Wikipédia sakuduna ngaganti ngaran golongan nu heubeul ku ngaran IUPAC, sarta mun perlu méré dadaran sajarah ngeunaan ngaran heubeulna.\'\'\n\n{{TabelPeriodik}}\n[[Category:Tabel periodik]]\n[[Category:Golongan unsur kimiawi]]\n\n[[bg:Група на периодичната система]]\n[[ca:Grup De La Taula Periòdica]]\n[[de:Gruppe des Periodensystems]]\n[[en:Periodic table group]]\n[[eo:Grupoj de la perioda tabelo]]\n[[es:Grupo de la tabla periódica]]\n[[ja:元素の族]]\n[[ro:Grupele tabelului periodic]]\n[[zh:族(化学)]]','',3,'Kandar','20041124054405','',0,0,0,0,0.469749493278,'20041222063441','79958875945594'); INSERT INTO cur VALUES (1657,10,'TabelPeriodik','
    \n{| style=\"margin:0 auto;\" align=center width=75% id=toc\n|align=center style=\"background:#ccccff\"| \n\'\'\'[[Tabel periodik]]\'\'\'\n|-\n|align=center| [[Tabel periodik (baku)|Tabel baku]] | [[Tabel periodik (pilihan)|Tabel vértikal]] | [[Tabel periodik (anti)|Tabel antizat]] | [[Tabel periodik (badag)|Tabel jeung ngaran]] | [[Tabel periodik (lega)|Ngaran jeung massa atom (badag)]] | [[Tabel periodik (mérélé)|Ngaran jeung massa atom (leutik)]] | [[Tabel periodik (lébar)|Blok-F satabel]] | [[Tabel periodik (dilegaan)|Unsur-unsur nepi ka-218]] | [[Tabel periodik (konfigurasi éléktron)|Konfigurasi éléktron]] | [[Tabel periodik (logam jeung nonlogam)|Logam jeung nonlogam]] | [[Tabel periodik (blok)|Tabel dumasar blok]] \n|-\n|align=center|Daptar Unsur\n|-\n|align=center| [[Daptar unsur dumasar ngaran|Ngaran]] | [[Daptar unsur dumasar lambang|Lambang atom]] | [[Daptar unsur dumasar wilangan atom|Wilangan atom]] | [[DAptar unsur dumasar titik golak|Titik golak]] | [[Daptar unsur dumasar titik lééh|Titik lééh]] | [[Daptar unsur dumasar dénsiti|Dénsiti]] | [[DAptar unsur dumasar massa atom|Massa atom]]\n\n|-\n|align=center style=\"background:#ccccff\"|[[Golongan tabel periodik|Golongan]] | [[Periode tabel periodik|Periode]] | [[Dérét kimia|Dérét]] | [[Blok tabel periodik|Blok]] \n|}','',3,'Kandar','20041015093617','',0,0,0,0,0.953317184445,'20041222063441','79958984906382'); INSERT INTO cur VALUES (1658,2,'Bgbot','\'\'\'Bgbot\'\'\' is a bot which is primarily active on [[:bg:|Bulgarian Wikipedia]]. Its main task on other wikipedias consists of making of bg: interwikis.\n\nThe bot was developed by [[:bg:Потребител:Borislav|User:Borislav]], so any possible complaints about it should be [[:bg:Потребител беседа:Borislav|directed]] to him :-).\n\n[[bg:Потребител:Bgbot]]','Bgbot\'s main task',22,'Bgbot','20041015140206','',0,0,1,1,0.340590221966,'20041016095422','79958984859793'); INSERT INTO cur VALUES (1660,0,'Periode_tabel_periodik','Dina [[tabel periodik]], \'\'\'periode\'\'\' nyaéta baris na tabel.\n\nJumlah [[kulit éléktron]] nangtukeun kaasup periode mana hiji atom. Unggal kulit dibagi kana subkulit nu béda-béda, di mana nalika [[wilangan atom]] nambahan, mangka subkulitna kaeusi nurutkeun susunan\n\n 1s \n 2s 2p \n 3s 3p \n 4s 3d 4p \n 5s 4d 5p \n 6s 4f 5d 6p \n 7s 5f 6d 7p \n 8s 5g 6f 7d 8p \n ... \n\nnu ngabentuk struktur tabel periodik. Ku sabab éléktron pangluarna nangtukeun sipat kimiawi, susunan ieu saluyu jeung [[golongan tabel periodik]]. \n\nUnsur-unsur nu patutur-tutur dina hiji golongan mibanda sipat fisik nu sarupa, sanajan béda massana kaitung loba. Unsur-unsur nu patutur-tutur dina hiji periode mibanda massa nu sarupa tapi sipatna béda.\n\nTempo ogé:\n* [[Unsur periode 1]]\n* [[Unsur periode 2]]\n* [[Unsur periode 3]]\n* [[Unsur periode 4]]\n* [[Unsur periode 5]]\n* [[Unsur periode 6]]\n* [[Unsur periode 7]]\n\n{{TabelPeriodik}}\n[[Category:Tabel periodik]]\n\n[[bg:Период на периодичната система]]\n[[ca:Període de la taula periòdica]]\n[[de:Periode des Periodensystems]]\n[[en:Periodic table period]]\n[[eo:Periodo de la perioda tabelo]]\n[[es:Periodo de la tabla periódica]]\n[[it:Periodo della tavola periodica]]\n[[ja:元素の周期]]\n[[nl:Periodieke tabel, periode]]\n[[ro:Perioadele tabelului periodic]]\n[[sv:Periodiska systemets perioder]]\n[[zh:周期 (化学)]]','warnfile Adding:eo,nl,de,sv Modifying:ja,ca',42,'Shizhao','20050303143859','',0,0,1,0,0.752143338207,'20050303143859','79949696856140'); INSERT INTO cur VALUES (1661,3,'Bgbot','
    Please, use the [[:bg:Потребител беседа:Bgbot|\'\'\'Bgbot\'s talk page on bg:\'\'\']].
    ','Bgbot\'s talk page on bg:',22,'Bgbot','20041016095422','',0,0,0,1,0.735553951811,'20041016095422','79958983904577'); INSERT INTO cur VALUES (1662,0,'Spésiés','Candida albicans','',0,'61.94.198.237','20041016135003','',0,0,0,1,0.965283721204,'20041016135003','79958983864996'); INSERT INTO cur VALUES (1663,0,'Cara...','','',0,'61.5.64.74','20041019032302','',0,0,0,0,0.023085508972,'20041019032302','79958980967697'); INSERT INTO cur VALUES (1665,6,'D-fruktosa.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041020062233','',0,0,0,1,0,'20041229052827','79958979937766'); INSERT INTO cur VALUES (1666,6,'D-glukosa.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041020062334','',0,0,0,1,0,'20041229052827','79958979937665'); INSERT INTO cur VALUES (1667,6,'Ribosa.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041020062630','',0,0,0,1,0,'20041229052827','79958979937369'); INSERT INTO cur VALUES (1668,0,'Ayip_Rosidi','\'\'\'Ajip Rosidi\'\'\' téh saurang budayawan sakaligus sastrawan kahot. Anjeunna nyipta karya sastra dina [[basa Sunda]] jeung [[basa Indonésia]], sarta loba ngawanohkeun sastra [[Sunda]] jeung [[Indonésia]] ka mancanagara.\n\nAjip lahir tanggal [[31 Januari]] [[1938]] di [[Jatiwangi]], [[Majaléngka]]. Aktif nulis, boh dina basa Indonésia atawa dina basa Sunda ti rumaja kénéh, umur 15 taun geus jadi Pamingpin Rumpaka Majalah [[Suluh Pelajar]] ([[1953]]-[[1955]]), sarta salajengna ngaluluguan sababaraha lembaga sastra, seni, pers, jeung budaya. Anjeunna ngadegkeun [[Yayasan Pusat Studi Sunda]] (2003) nu ngulik kabudayaan Sunda sarta [[Yayasan Kabudayaan Rancagé]] nu ngabobotohan tumuwuhna sastra lokal. Kungsi ngajar basa jeung kabudayaan Indonesia di [[Osaka Gaikokugo Daigaku]] (1981-2003), sagigireun ngajar ogé di [[Kyoto Sangyo Daigaku]] (1982-1996) jeung [[Tenri Daigaku]] (1982-1995), Jepang. Naratas dilembagakeunana [[Hadiah Sastra Rancagé]] ti taun 1989, sarta mokalan lumangsungna [[Konferensi Internasional Budaya Sunda]] (KIBS) 2001 di Bandung. Buku-buku karyana geus leuwih ti saratus judul, mangrupa [[roman]], kumpulan [[sajak]], kumpulan [[carita pondok]], mémoar, jeung biografi.\n\n[[Category:Sastrawan]] [[Category:Inohong Sunda]] [[Category:Budayawan]]\n[[id:Ajip Rosidi]]','',3,'Kandar','20041203164636','',0,0,0,0,0.504983249356,'20041203165036','79958796835363'); INSERT INTO cur VALUES (1669,1,'Litium','\'\'\'Téks kandel\'\'\'\'\'Tulisan déngdék\'\'[[Judul tumbu]][Judul tumbu http://www.conto.com][[Image:Conto.jpg]][[Media:Example.mp3]]Asupkeun rumus di dieuInsert non-formatted text here--[[User:202.176.254.35|202.176.254.35]] 04:20, 21 Oct 2004 (UTC)\n\n\'\'\'Téks kandel\'\'\'\'\'Tulisan déngdék\'\'[[Judul tumbu]][Judul tumbu http://www.conto.com][[Image:Conto.jpg]][[Media:Example.mp3]]Asupkeun rumus di dieuInsert non-formatted text here--[[User:202.176.254.35|202.176.254.35]] 04:20, 21 Oct 2004 (UTC)','',0,'202.176.254.35','20041021042011','',0,0,0,0,0.093187703329,'20041021042011','79958978957988'); INSERT INTO cur VALUES (1670,0,'Ajip_Rosidi','#REDIRECT [[Ayip Rosidi]]\n','Ajip Rosidi dipindahkeun ka Ayip Rosidi',3,'Kandar','20041021042241','',0,1,0,1,0.936812131636,'20041021042241','79958978957758'); INSERT INTO cur VALUES (1671,0,'Polisakarida','\'\'\'Polisakarida\'\'\' nyaéta [[karbohidrat]] \"teu amis\" nu kawilang pajeulit. Polisakarida ngarupakeun [[polimér]] nu diwangun ku loba [[monosakarida]] nu silihsambungkeun (nyaéta \'\'poli\'\'-sakarida). Ku kituna polisakarida mah kaasup molekul badag pisan, malah ngarangkadak. Sipatna teu leyur na cai sarta teu ngabentuk kristal, contona nyaéta [[aci]], [[sélulosa]], jeung [[glikogén]].\n\n\'\'\'Struktur\'\'\'\n\nPolisakarida mibanda rumus umum:\n\n:-[Cx(H2O)y)]n-\n\nnu mana \'\'y\'\' biasana = \'\'x\'\' - 1.\n\n=== Aci ===\nAci ngarupakeun polimér glukosa nu unit glukopiranosana kabeungkeut ku tumbu-\'\'alfa\'\'. [[Amilosa]] diwangun ku sababaraha ratus molekul glukosa ranté-lempeng. [[Amilopéktin]] nyaéta molekul rangkadak nu disusun ku sababaraha réwu unit glukosa.\n\n[[Aci]] teu leyur na [[cai]], bisa disiksik ku hidrolisis nu dikatalisan ku énzim nu disebut [[amilase]], nu bisa megatkeun tumbu-\'\'alfa\'\'. Manusa jeung sato séjénna boga amilase, sahingga bisa nyerna aci. [[Kentang]], [[béas]], [[gandum]], [[jagong]], jeung [[sampeu]] ngarupakeun sumber aci na dahareun manusa.\n\n=== Glikogén ===\n[[Glikogén]], polimér rangkadak glukosa, ngarupakeun bentuk simpenan glukosa dina [[sato]]. Glikogén bisa dibeulah jadi substrat pikeun réspirasi ngaliwatan prosés [[glikogénolisis]]. Ieu ngawengku megatkeun beungkeut C-O-C antarmolekul glukosa ku ditambahkeunana fosfat, gaganti cai na [[hidrolisis]]. Prosés ieu ngahasilkeun molekul glukosa kafosforilasi, nu métabolismena bisa ngahasilkeun hiji molekul [[Adénosin trifosfat|ATP]].\n\n=== Sélulosa ===\nKomponén struktural [[tutuwuhan]] diwangun utamana ku [[sélulosa]]. Kai diwangun ku sélulosa jeung [[lignin]], sedengkeun [[kertas]] jeung [[kapas]] méh murni sélulosa. Sélulosa ngarupakeun [[polimér]] nu dibentuk ku ulangan unit glukosa nu kabeungkeut ku tumbu-\'\'béta\'\'. Manusa sarta kalolobaan sato séjénna teu boga/kakurangan énzim pikeun megatkeun tumbu-\'\'béta\'\', sahingga teu bisa nyerna sélulosa. Sababaraha sato bisa nyerna sélulosa sabab boga [[sélulase]]na.\n\n==polisakarida asam==\nPolisakarida asam nyaéta sagolongan polisakarida nu ngandung [[gugus karboxil]] jeung/atawa [[gugus éster sulfat]].\n\n[[Category:Polimér organik]]\n[[Category:Polisakarida]]\n\n[[de:Polysaccharid]]\n[[en:Polysaccharide]]\n[[es:Polisacárido]]\n[[fr:Polysaccharide]]\n[[ja:多糖]]','warnfile Adding:fr',42,'Shizhao','20050303143908','',0,0,1,0,0.674489954335,'20050303143908','79949696856091'); INSERT INTO cur VALUES (1672,0,'Gajih','Na [[biokimia]], \'\'\'\'\'gajih\'\'\'\'\' (\'\'fat\'\') ngarupakeun istilah umum pikeun hiji golongan [[lipid|lemak]]. Gajih dihasilkeun tina prosés organik na [[sato]] jeung [[tutuwuhan]]. Sakabéh gajih teu leyur na [[cai]] sarta mibanda dénsiti sahandapeun cai (nu matak ngambang na cai).\nGajih nu [[cair]] dina [[suhu rohangan]] mimindengna disebut [[minyak]].\n\n== Wangunan kimiawi ==\nMost fats are composed primarily of [[triglyceride]]s; some monoglycerides and diglycerides are mixed in, produced by incomplete [[ester]]ification. These are extracted and used as an ingredient.\n\nProducts with a lot of saturated fats tend to be solid at room temperature, while products containing [[unsaturated fat]]s, which include [[monounsaturated fat]]s and [[polyunsaturated fat]]s, tend to be liquid at room temperature.\n\nPredominantly saturated fats (solid at [[room temperature]]) include all [[animal fat]]s (e.g. [[milk]] fat, [[lard]], [[tallow]]), as well as [[palm oil]], [[coconut]] oil, [[cocoa]] fat and [[hydrogenation|hydrogenated]] [[vegetable oil]] ([[shortening]]).\nAll other vegetable fats, such as those coming from [[olive]], [[peanut]], [[maize]] ([[corn oil]]), [[cottonseed oil|cottonseed]], [[sunflower]], [[safflower]], and [[soybean]], are predominantly unsaturated and remain liquid at room temperature. \nHowever, both vegetable and animal fats contain saturated and unsaturated fats. Some oils (such as olive oil) contain in majority monounsaturated fats, while others present quite a high percentage of polyunsaturated fats (sunflower, rape).\n\n== Utilization ==\nIn the ancient [[Minoan culture]], and in many of the other early [[Mediterranean]] [[culture]]s, [[olive oil]] was a very important commodity and at times used as a measure of [[wealth]].\n\nDifferent varieties of fat have seen, and indeed still see, much use as [[lubricant]]s, although recently various [[synthetic]] substances and [[petroleum]] derivatives has taken over in most industrial applications. \n\nIn [[cooking]], products with a high fat content are often used as enhancers of taste, for example [[butter]], [[milk]], [[cheese]] and other [[dairy]] products. \n\nAnimal fat or \"drippings\" are also used in the traditional [[cuisine]] of [[Europe]]an countries. In [[Denmark ]] [[pork]] \'\'fedt\'\' (the fat from the frying pan after the meat has been cooked) is drained and filtered to [[strain]] any large [[particles]]. It is then placed in a container and cooled down until solid. It can be kept for extremely long periods of time in a refrigerator. Often it is used as a more flavourful alternative to [[butter]] or [[margarine]], and is easily spread even when cold.\n\nIn traditional Jewish cuisine the fat from [[chicken]]s, known as \'\'schmaltz\'\', is used. \n\nAnother use of fat in cooking is as heat conductor in [[frying]].\n\n== Fats in nutrition ==\nFat is one of the three main classes of food and, at approximately 38 [[Joule|kJ]] (9 [[Calorie|Cal]]) per [[gram]], as compared to [[sugar]] with 17 kJ (4 Cal) per gram or [[ethanol]] with 29 kJ (7 Cal) per gram, the most concentrated form of [[metabolic energy]] available to humans. \n[[Vitamin]]s [[Vitamin A|A]], [[Vitamin D|D]], [[Vitamin E|E]], and [[Vitamin K|K]] are fat-soluble meaning they can only be digested, absorbed, and transported in conjunction with fats. Fats are sources of [[essential fatty acid]]s, an important dietary requirement.\n\nThey also serve as energy stores for the body. In [[food]], there are two types of fats: [[Saturated_fat|saturated]] and [[Unsaturated_fat|unsaturated]]. Fats are broken down in the body to release glycerol and free fatty acids. The glycerol can be converted to glucose by the liver and thus used as a source of energy. The fatty acids are a good source of energy for many tissues, especially heart and skeletal muscle.\n\n=== The biological imperative ===\nAll varieties of fat have an extraordinary [[energy]] content. In animals, fat acts as an energy reserve, and is stored in fatty tissue, normally located subcutaneously or surrounding organs. Fatty tissue consist of fat [[cell (biology)|cell]]s, designed to store energy in the form of fat.\n\nEnergy is stored as fatty tissue when the [[nutrition]]/energy content of the blood remains higher than is consumed by muscular and other activity. When the energy content in the blood lessens, the fatty tissue reacts by releasing a corresponding amount of energy from the fat [[cell (biology)|cell]]s. This activity is controlled by [[insulin]] and other [[hormone]]s in the [[body]]. \n\n===Adipose tissue===\n[[Adipose tissue|Adipose]], or fatty, tissue is the human body\'s means of storing metabolic energy over extended periods of time. The location of the tissue determines its metabolic profile: \"visceral fat\" (around the abdomen) is prone to lead to [[insulin resistance]], while \"peripheral fat\" (around the limbs) is much more harmless.\n\n==[[Metabolism]]==\n\n===[[Catabolism]]===\n\n===[[Anabolism]]===\nThe synthesis of fatty acids occurs by reactions almost reverse to fat catabolism.\n{{cookbookpar|Oil and fat}}\n\'\'See also:\'\' [[Carbohydrate]], [[protein]], [[lipid]], [[biodiesel]], [[brown fat]]\n\n[[de:Fett]]\n[[en:fat]]\n[[es:grasa]]\n[[fr:Graisse]]\n[[ja:脂肪]]\n[[nl:vet]]\n[[pl:T%C5%82uszcz]]\n[[fi:rasva]]\n\n[[Category:Lipids]]\n[[Category:Nutrition]]','fr',0,'209.90.162.112','20050221055002','',0,0,0,0,0.960143495798,'20050302051215','79949778944997'); INSERT INTO cur VALUES (1673,0,'Karbon','\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\" style=\"margin-left: 0.5em\"\n|-\n| colspan=\"2\" cellspacing=\"0\" cellpadding=\"2\" |\n{| align=\"center\" border=\"0\"\n|-\n| colspan=\"2\" align=\"center\" | [[boron]] – \'\'\'karbon\'\'\' – [[nitrogén]]\n|-\n| rowspan=\"3\" valign=\"center\" |  
    \'\'\'C\'\'\'
    [[Silikon|Si]]  
     
     \n|-\n| align=\"center\" | [[image:C-TableImage.png|250px|Klik pikeun dadaran]]
    [[Tabel periodik (baku)|Tabel lengkep]]
    \n|}\n|-\n! colspan=\"2\" align=center bgcolor=\"#a0ffa0\" | \'\'\'Umum\'\'\'\n|-\n| [[Daptar unsur dumasar ngaran|Ngaran]], [[Daptar unsur dumasar lambang|Lambang]], [[Daptar unsur dumasar wilangan|Wilangan]]\n| Karbon, C, 6\n|-\n| [[Dérét kimia]]\n| [[Nonlogam]]\n|-\n| [[golongan tabel periodik|Golongan]], [[periode tabel periodik|Periode]], [[blok tabel periodik|Blok]]\n| [[Unsur golongan 14|14 (IVA)]], [[unsur periode 2|2]], [[blok-p|p]]\n|-\n| [[Dénsiti]], [[skala teuas Mohs|Kateuasan]]\n| 2267 [[kilogram per méter kubik|kg/m3]],
    0.5 (grafit)
    10.0 (inten)\n|-\n| [[warna|Panémbong]] \n| align=\"center\" | hideung (grafit)
    tanpawarna (inten)
    [[Image:C,6.jpg|125px|]]\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#a0ffa0\" | \'\'\'Sipat atom\'\'\'\n|-\n| [[Beurat atom]]\n| 12.0107 [[unit beurat atom|amu]]\n|-\n| [[Radius atom]] (calc.)\n| 70 (67) [[picométer|pm]]\n|-\n| [[Radius kovalén]]\n| 77 pm\n|-\n| [[Radius van der Waals]]\n| 170 pm\n|-\n| [[konfigurasi éléktron]]\n| [[[Hélium|He]]]2[[orbital-s|s]]22p2\n|-\n| [[éléktron|e-]] per [[tingkat énergi]]\n| 2, 4\n|-\n| [[Wilangan oxidasi]] ([[Oxida]])\n| \'\'\'4\'\'\', 2 (mildly [[acid]]ic)\n|-\n| [[Struktur kristal]]\n| Héxagonal\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#a0ffa0\" | \'\'\'Sipat fisik\'\'\'\n|-\n| [[Wujud zat]]\n| padet ([[diamagnetik]])\n|-\n| [[Titik lééh]]\n| 3773 [[Kélvin|K]] (6332 °[[Fahrenheit|F]])\n|-\n| [[Titik golak]]\n| 5100 K (8721 °F)\n|-\n| [[Volume molar]]\n| 5.29 [[scientific notation|×]]10-6 [[cubic metre per mole|m3/mol]]\n|-\n| [[Panas panguapan]]\n| 355.8 [[kilojoule per mol|kJ/mol]] ([[sublimasi (kimia)|sublim]])\n|-\n| [[Panas fusi]]\n| N/A ([[sublimasi (kimia)|sublim]])\n|-\n| [[Tekenan uap]]\n| 0 [[Pascal|Pa]]\n|-\n| [[Speed of sound]]\n| 18350 [[méter per sekon|m/s]]\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#a0ffa0\" | \'\'\'Rupa-rupa\'\'\'\n|-\n| [[Éléktronégativiti]]\n| 2.55 ([[Skala Pauling]])\n|-\n| [[Kapasitas panas spésifik]]\n| 710 [[joule per kilogram-Kelvin|J/(kg*K)]]\n|-\n| [[Konduktiviti listrik]]\n| 0.061 × 106/(m·[[ohm]])\n|-\n| [[Konduktiviti panas]]\n| 129 [[watt per méter-kelvin|W/(m*K)]]\n|-\n| [[Poténsi ionisasi]] ka-1\n| 1086.5 kJ/mol\n|-\n| Poténsi ionisasi ka-2\n| 2352.6 kJ/mol\n|-\n| Poténsi ionisasi ka-3\n| 4620.5 kJ/mol\n|-\n| Poténsi ionisasi ka-4\n| 6222.7 kJ/mol\n|-\n| Poténsi ionisasi ka-5\n| 37831 kJ/mol\n|-\n| Poténsi ionisasi ka-6\n| 47277.0 kJ/mol\n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#a0ffa0\" | \'\'\'Isotop pangstabilna\'\'\'\n|-\n| colspan=\"2\" |\n{| border=\"1\" cellspacing=\"0\" cellpadding=\"2\" width=\"100%\"\n|-\n! [[Isotop|iso]]\n! [[natural abundance|NA]]\n! \'\'[[half-life]]\'\'\n! [[decay mode|DM]]\n! [[decay energy|DE]] [[mega|M]][[electron volt|eV]]\n! [[decay product|DP]]\n|-\n| [[Karbon-12|12C]]\n| \'\'\'98.9%\'\'\'\n| colspan=\"4\" | C [[isotop stabil|stabil]] mibanda 6 [[neutron]]\n|-\n| [[Karbon-13|13C]]\n| 1.1%\n| colspan=\"4\" | C stabil mibanda 7 neutron\n|-\n| [[Karbon-14|14C]]\n| [[trace radioisotope|trace]]\n| 5730 [[year|y]]\n| [[émisi béta|béta-]]\n| 0.156\n| [[Nitrogén|14N]] \n|-\n! colspan=\"2\" align=\"center\" bgcolor=\"#a0ffa0\" | Unit [[SI]] & [[standard temperature and pressure|STP]] dipaké iwal mun ditandakeun lain.\n|}\n\'\'\'Karbon\'\'\' ngarupakeun [[unsur kimia]] na [[tabel periodik]] nu boga lambang \'\'\'C\'\'\' sarta [[nomer atom]] 6. An abundant [[nonmetal]]lic, tetravalent element, carbon has several [[Allotropes of carbon|allotropic forms]]:\n\n* [[inten]] ([[mineral]] pangteuasna). Struktur beungkeutan: 4 éléktron na orbital-sp3 3-diménsi\n* [[grafit]] (salasahiji zat panglemesna). Struktur beungkeutan: 3 éléktron na orbital-sp2 2-diménsi jeung 1 éléktron na orbital-s.\n* Orbital sp1 nu kabeungkeut kovalén mangrupa hiji-hijina interés kimia.\n\nFullerit ([[fullerin]]) nyaéta molekul dina skala-[[nanométer]]. Dina bentuk nu basajan, 60 atom karbon ngabentuk lapisan grafit nu ngagulung jadi hiji struktur 3-dimensi nu sarupa jeung bal maénbal. \n\nLamp black consists of small graphitic areas. These areas are randomly distributed, so the whole structure is isotropic.\n\nSo-called \'glassy carbon\' is isotropic and as strong as glass. Unlike normal graphite, the graphitic layers are not arranged like pages in a book, but are crumpled like crumpled paper.\n\nCarbon fibers are similar to glassy carbon. Under special treatment (stretching of organic fibers and carbonization) it is possible to arrange the carbon planes in direction of the fiber. Perpendicular to the fiber axis there is no orientation of the carbon planes. The result are fibers with a higher specific strength than steel.\n\nKarbon aya dina sadaya bahan organik sarta mangrupa dasar pikeun [[kimia organik]]. Nonlogam ieu ogé mibanda sipat kimia nu ahéng ku bisana kabeungkeut ku atom karbon jeung rupa-rupa unsur séjénna, ngabentuk ampir 10 yuta sanyawa nu geus kanyahoan. Nalika ngahiji jeung [[oxigén]], karbon jadi [[karbon dioxida]] nu kacida pentingna pikeun [[tutuwuhan]]. Nalika ngahiji jeung [[hidrogén]], karbon jadi rupa-rupa sanyawa nu disebut [[hidrokarbon]] nu penting pikeun industri dina bentuk [[minyak bumi]] (Ing. \'\'fossil fuel\'\'). Nalika ngahiji jeung oxigén lan hidrogén, karbon bisa jadi rupa-rupa golongan sanyawa kayaning [[asam lemak]], nu penting pikeun mahluk hirup, jeung [[éster]], nu méré rasa kana bungbuahan. [[Isotop]] [[karbon-14]] ilahar dipaké pikeun [[pananggalan radioaktif]].\n\n==Ciri penting== \nCarbon is a remarkable element for many reasons. Its different forms include one of the softest (graphite) and one of the hardest (diamond) substances known to man. Moreover, it has a great affinity for [[chemical bond|bond]]ing with other small [[atom]]s, including other carbon atoms, and its small size makes it capable of forming multiple bonds. Because of these properties, carbon is known to form nearly ten million different compounds. Carbon compounds form the basis of all life on [[Earth]] and the [[carbon-nitrogen cycle]] provides some of the energy produced by the [[sun]] and other [[star]]s. \n\nCarbon was not created in the [[big bang]] due to the fact that it needs a triple collision of alpha particles ([[helium]] nuclei) to be produced. The universe initially expanded and cooled too fast for that to be possible. It is produced, however, in the interior of [[star]]s in the [[H-R diagram|horizontal branch]], where stars transform a [[helium]] core into carbon by means of the [[triple-alpha process]].\n\n== Applications == \nCarbon is a vital component of all known living systems, and without it life as we know it could not exist (see [[carbon chauvinism]]). The major economic use of carbon is in the form of hydrocarbons, most notably the [[fossil fuel]]s [[methane]] gas and [[crude oil]]. Crude oil is used by the [[petrochemical industry]] to produce, amongst others, [[petroleum]], [[gasoline]] and [[kerosene]], through a [[distillation]] process, in so-called [[refinery|refineries]]. Crude oil forms the raw material for many synthetic substances, many of which are collectively called [[plastic]]s.\n\n===Mangpaat séjén===\n* Isotop [[karbon-14|14C]], kapanggih [[27 Pébruari]] [[1940]], dipaké dina [[pananggalan radiokarbon]].\n* Sababaraha detéktor haseup migunakeun sajumlah ménél isotop radioaktif karbon salaku sumber [[radiasi pangionan]] (Most smoke detectors of this type use an isotope of [[Americium]])\n* Graphite is combined with [[clay]]s to form the \'lead\' used in [[pencil]]s. \n* Diamond is used for decorative purposes, and also as drill bits and other applications making use of its hardness. \n* Carbon is added to [[iron]] to make [[steel]].\n* Carbon is used for [[control rod]]s in [[nuclear reactor]]s.\n* Graphite carbon in a powdered, caked form is used as [[charcoal]] for [[cooking]], [[art]]work and other uses. \n* Charcoal pills are used in medicine in pill or powder form to [[adsorption|adsorb]] toxins or poisons from the digestive system.\n\nSipat fisik jeung kimiawi fulerin, dina bentuk [[nanotabung karbon]], mibanda poténsi nu ngajangjikeun pikeun widang nanotéhnologi.\n\n== Sajarah == \nKarbon (tina [[basa Latin]] \'\'carbo\'\' nu hartina \"areng\", \'\'charcoal\'\') kapendakna sarta geus dipikawanoh ti jaman prasajarah kénéh, dijieun ku jalan ngaduruk bahan organik dina kaayaan kurang oksigén (nyieun [[areng]]). [[Inten]] geus ti baheula dipikawanoh salaku barang nu jarang sarta éndah. Alotrop karbon nu pangahirna nu kapanggih, [[fulerin]], kapanggih salaku hasil gigir (\'\'byproduct\'\') percobaan \'\'molecular beam\'\' taun 1980-an.\n\n== Alotrop == \nOpat [[alotrop]] karbon nu dipikanyaho di antarana: amorf, [[grafit]], [[inten]], jeung [[fulerin]]. Bentuk nu kalima diumumkeun [[22 Maret]] [[2004]].\n\nIn its amorphous form, carbon is essentially [[graphite]] but not held in a crystalline macrostructure. It is, rather, present as a powder which is the main constituent of substances such as [[charcoal]] and [[lamp black]] ([[soot]]).\n\nAt normal pressures carbon takes the form of [[graphite]], in which each atom is bonded to three others in a plane composed of fused [[hexagon]]al rings, just like those in [[aromatic hydrocarbon]]s. The two known forms of graphite, alpha (hexagonal) and beta ([[rhombohedron|rhombohedral]]), both have identical physical properties, except for their crystal structure. Graphites that naturally occur have been found to contain up to 30% of the beta form, when synthetically-produced graphite only contains the alpha form. The alpha form can be converted to the beta form through mechanical treatment and the beta form reverts back to the alpha form when it is heated above 1000 °[[Celsius|C]]. \n\nBecause of the delocalization of the [[pi-cloud]], graphite conducts [[electricity]]. The material is soft and the sheets, frequently separated by other atoms, are held together only by [[van der Waals force]]s, so easily slip past one another. \n\nAt very high pressures carbon has an allotrope called [[diamond]], in which each atom is bonded to four others. Diamond has the same cubic structure as [[silicon]] and [[germanium]] and, thanks to the strength of the carbon-carbon [[chemical bond|bond]]s, is together with the [[isoelectronic]] [[boron nitride]] (BN) the hardest substance in terms of resistance to scratching. The transition to [[graphite]] at room temperature is so slow as to be unnoticeable. Under some conditions, carbon crystallizes as [[Lonsdaleite]], a form similar to diamond but hexagonal. \n\nFullerenes have a graphite-like structure, but instead of purely hexagonal packing, also contain pentagons (or possibly heptagons) of carbon atoms, which bend the sheet into spheres, ellipses or cylinders. The properties of fullerenes (also called \"buckyballs\" and \"buckytubes\") have not yet been fully analyzed. All the names of fullerenes are after [[Buckminster Fuller]], developer of the [[geodesic]] [[dome]], which mimics the structure of \"buckyballs\".\n\nA nanofoam allotrope has been dicovered which is [[ferromagnetic]].\n\n== Occurrence == \nThere are nearly ten million carbon compounds that are known to [[science]] and many thousands of these are vital to life processes and very economically important organic-based reactions. This element is abundant in the [[sun]], [[star]]s, [[comet]]s, and in the [[celestial body\'s atmosphere|atmosphere]]s of most [[planet]]s. Some [[meteorite]]s contain microscopic diamonds that were formed when the [[solar system]] was still a [[protoplanetary disk]]. In combination with other elements, carbon is found the earth\'s atmosphere and dissolved in all bodies of water. With smaller amounts of [[calcium]], [[magnesium]], and [[iron]], it is a major component of very large masses [[carbonate]] [[Rock (geology)|rock]] ([[limestone]], [[dolomite]], [[marble]] etc.). When combined with [[hydrogen]], carbon form [[coal]], [[petroleum]], and [[natural gas]] which are called hydrocarbons. \n\nGraphite is found in large quantities in [[New York]] and [[Texas]], the [[United States]]; [[Russia]]; [[Mexico]]; [[Greenland]] and [[India]]. \n\nNatural diamonds occur in the mineral [[kimberlite]] found in ancient [[volcano|volcanic]] \"necks,\" or \"pipes\". Most diamond deposits are in [[Africa]], notably in [[South Africa]], [[Namibia]], [[Botswana]], the [[Republic of the Congo]] and [[Sierra Leone]]. There are also deposits in [[Canada]], the Russian [[Arctic]], [[Brazil]] and in Northern and Western [[Australia]].\n\n== Sanyawa anorganik ==\n(Tempo ogé [[kimia organik]]) \n\nOksida karbon nu penting nyéta [[karbon dioxida]], CO2, nu ngarupakeun salasahiji komponén minor [[atmosfir Marcapada]], dihasilkeun sarta dipigunakeun ku mahluk hirup, nu mibanda sipat volatil. Na [[cai (molekul)|cai]], oksida karbon ieu ngabentuk sajumlah renik [[asam karbonat]], H2CO3, but as most compounds with multiple single-bonded oxygens on a single carbon it is unstable. Through this intermediate, though, resonance-stabilized [[carbonate]] [[ion]]s are produced. Some important minerals are carbonates, notably [[calcite]]. [[Carbon disulfide]], CS2, is similar. \n\nThe other oxides are [[carbon monoxide]], CO, and the uncommon carbon suboxide, C3O2. Carbon monoxide is formed by incomplete combustion, and is a colorless, odorless gas. The molecules each contain a triple bond and are fairly [[polar molecule|polar]], resulting in a tendency to bind permanently to [[hemoglobin]] molecules, so that the gas is highly poisonous. [[Cyanide]], CN-, has a similar structure and behaves a lot like a [[halide]] ion; the nitride [[cyanogen]], (CN)2, is related. \n\nWith strong [[metal]]s carbon forms either carbides, C-, or acetylides, C22-; these are associated with [[methane]] and [[acetylene]], both incredibly pathetic [[acid]]s. All in all, with an electronegativity of 2.5, carbon prefers to form [[covalent bond]]s. A few carbides are covalent lattices, like [[carborundum]], SiC, which resembles [[diamond]].\n\n== Ranté karbon ==\nIt´s the atomic structure of hydrocarbons in which a series of carbon atoms, saturated by hydrogen atoms, form a chain. Volatile oils have shorter chains. Fats have longer chain lengths, and waxes have extremely long chains.\n\n== Daur karbon ==\nThe continuous process of combining and releasing carbon and oxygen thereby storing and emitting heat and energy. [[Catabolism]] + [[anabolism]] = [[metabolism]]. See [[carbon cycle]].\n\n== Isotop == \nIn [[1961]] the [[International Union of Pure and Applied Chemistry]] adopted the [[isotope]] carbon-12 for basis for [[atomic weight]]s. \n*[[Carbon-14]] is a [[radioisotope]] with a [[half-life]] of 5715 years and has been used extensively for [[radiocarbon dating]] wood, [[archeology|archaeological]] sites and specimens. \n\nCarbon has two stable, naturally-occurring isotopes: C-12 (98.89%) and C-13 (1.11%). Ratios of these isotopes are reported in ? relative to the standard VPDB (Vienna Pee Dee Belemnite from the Peedee Formation of South Carolina). The [[delta (letter)|d]]C-13 of the [[Earth\'s atmosphere|atmosphere]] is -7?. During [[photosynthesis]], the carbon that becomes [[carbon fixation|fixed]] in [[plant]] tissue is significantly depleted in C-13 relative to the atmosphere. \n\nThere is two mode distribution in the dC-13 values of terrestrial plants resulting from differences in the photosynthetic reaction used by the plant. Most terrestrial plants are [[C3 pathway plant]]s and have dC-13 values range from -24 to -34?. A second category of plants ([[C4 pathway plants]]), composed of aquatic plants, desert plants, salt marsh plants, and tropical grasses, have dC-13 values that range from -6 to -19. An intermediate group ([[CAM plant]]s) composed of algae and lichens has dC-13 values range from -12 to -23?. The dC-13 of plants and organisms can provide useful information about sources of [[nutrient]]s and food web relations.\n\n== Kawaspadaan == \nSanyawaan karbon mibanda rupa-rupa peta toxik. [[Karbon monoxida]] (C[[oxygen|O]]), nu aya dina haseup durukan mesin, sarta [[sianida]] (CN-), nu mindeng kapanggih dina polusi patambangan, toxik pisan pikeun [[mamalia]]. Sanyawaan karbon séjénna teu toxik sarta malah penting pisan pikeun hirup. [[Gas]] organik kayaning [[éténa]] (CH2=CH2), [[étuna]] (HCCH), jeung [[métana]] (CH4) pibahyaeun alatan gampang ngabeledug sarta kaduruk nalika dicampurkeun jeung hawa.\n\n== Tumbu kaluar ==\n* [http://periodic.lanl.gov/elements/6.html Los Alamos National Laboratory – Carbon]\n* [http://www.nature.com/NSU/040322/040322-5.html][http://www.nature.com/nsu/040322/040322-5.html]\n* [http://www.webelements.com/webelements/elements/text/C/index.html WebElements.com – Carbon]\n* [http://environmentalchemistry.com/yogi/periodic/C.html EnvironmentalChemistry.com – Carbon]\n* [http://education.jlab.org/itselemental/ele006.html It\'s Elemental – Carbon]\n* [http://www.vincentherr.com/cf/ – Carbon Fullerene and other Allotropes] models by Vincent Herr\n* {{wia}}\n\n\n\n[[Category:Unsur kimia]]\n\n[[ca:Carboni]] [[cs:Uhlík]] [[cy:Carbon]] [[da:Carbon]] [[de:Kohlenstoff]] [[en:carbon]] [[et:Süsinik]] [[es:Carbono]] [[eo:Karbono]] [[io:Karbo]] [[fr:Carbone]] [[it:Carbonio]] [[la:Carbonium]] [[hu:Szén]] [[nl:Koolstof]] [[ja:炭素]] [[mi:Waro]] [[no:Karbon]] [[nds:Kohlenstoff]] [[pl:Węgiel]] [[pt:Carbono]] [[ru:Углерод]] [[simple:Carbon]] [[sl:Ogljik]] [[fi:Hiili]] [[sv:Kol]] [[th:คาร์บอน]] [[zh:碳]]','',3,'Kandar','20050217033203','',0,0,0,0,0.116587697117,'20050228103131','79949782966796'); INSERT INTO cur VALUES (1674,2,'Romanm','[[sl:Uporabnik:romanm]]\n[[en:User:romanm]]','',25,'Romanm','20041025200630','',0,0,0,1,0.957134816776,'20041025200630','79958974799369'); INSERT INTO cur VALUES (1675,0,'Monosakarida','\'\'\'Monosakarida\'\'\' nyaéta [[karbohidrat]] na wujud [[gula]] basajan.\n\nMonosakarida, kawas [[disakarida]], sipatna amis, [[leyur]] na [[cai]] sarta [[kristal]]in.\n\nMonosakarida digolongkeun dumasar jumlah atom [[karbon]] nu dikandungna ([[triosa]], [[tetrosa]], [[pentosa]], [[héxosa]], jeung [[héptosa]]) sarta dumasar gugus aktifna, [[aldehid]] atawa [[keton]]. Kombinasina bisa jadi rupa-rupa, misalna aldohéxosa, ketotriosa.\n\nSalajengna, unggal atom karbon nu boga gugus hidroksil (iwal nu tungtung) sipatna [[optik aktif]], sahingga bisa aya sababaraha karbohidrat nu struktur dasarna sarua. Misal, [[galaktosa]] kaasup aldohéxosa, tapi mibanda sipat béda ti glukosa sabab susunan atom-atomna béda.\n\nConto séjénna:\n*[[triosa]]: [[gliseraldehid]] jeung [[dihidroxiaséton]]\n*[[tétrosa]]: [[éritrosa]]\n*[[péntosa]]: [[lixosa]], [[ribosa]], jeung [[déoxiribosa]]\n*[[héxosa]]: [[idosa]], [[glukosa]], [[fruktosa]], jeung [[galaktosa]]\n*[[héptosa]]:\n\n==Sipat fisik==\nLolobana teu warnaan, padet kristalin (amis).\n\n==Struktur==\nIwal ti sabagian leutik nu béda, (misalna déoxiribosa atawa [[gula amino]]), monosakarida mibanda [[rumus kimia]] umum:\n\n:(CH2O)n\n\nMonosakarida ngandung boh [[gugus fungsi]] [[keton]] atawa [[aldehid]].\n\n===Struktur siklik===\nCara umum pikeun mintonkeun struktur siklik monosakarida nyaéta ku [[proyéksi Haworth]].\n\n===Isomérisme===\n[[Sistim D,L]] biasana digunakeun.\n\n==Tata ngaran==\nMonosakarida nu ngandung hiji gugus [[aldehid]] digolongkeun kana [[aldosa]], sedengkeun nu ngandung gugus [[keton]] digolongkeun kana [[ketosa]].\n\n==Réaksi==\n#Ngabentuk [[asétal]].\n\n==Tempo ogé==\n*[[Karbohidrat]]\n*[[Disakarida]]\n*[[Oligosakarida]]\n*[[Polisakarida]]\n\n==Tumbu kaluar==\n[http://www.chem.qmul.ac.uk/iupac/2carb/app.html Nomenclature of Carbohydrates] \n\n[[Category:Monosakarida]]\n\n[[de:Einfachzucker]]\n[[en:Monosaccharide]]\n[[eo:Monosakarido]]\n[[es:Monosacárido]]\n[[fr:Monosaccharide]]\n[[id:Monosakarida]]\n[[ja:単糖]]\n[[nl:Monosacharide]]\n[[pt:Monossacarídeos]]\n[[zh:單糖]]','',0,'63.249.98.145','20050125074556','',0,0,0,0,0.802368940228,'20050125074556','79949874925443'); INSERT INTO cur VALUES (1676,0,'Hidrolisis','\'\'\'Hidrolisis\'\'\' nyaéta prosés kimia nalika hiji [[molekul]] dibeulah jadi dua bagian ku nambahkeun hiji molekul [[cai]]. \nIeu béda jeung [[réaksi hidrasi]], nalika molekul cai ditambahkeun kana hiji zat tanpa ayana prosés meulah.\n\n==Tipe==\n\n\'\'\'Hidrolisis tumbu éster\'\'\'\n\nDina hidrolisis nu megatkeun tumbu [[éster]], hiji produk hidrolisis ngandung [[gugus fungsi]] [[hidroxil]], sedengkeun nu hiji deui ngandung [[asam karboksilat]]. \n\nPopotongan molekul indung nu asalna gugus [[karboksilat]] narima hiji [[ion]] [[hidrogén]] ti molekul cai nu ditambahkeun, sedengkeun popotongan nu asalna gugus [[alkil]] narima gugus hidroksil sésana.\n\nJadi éster sacara éféktif balik deui jadi komponén-komponénna, nyéta [[alkohol]] jeung [[asam karboksilat]].\n\n\n\'\'\'Hidrolisis tumbu péptida asam amino\'\'\'\n\nDina réaksi hidrolisis séjénna kayaning hidrolisis [[tumbu péptida]] asam amino, ukur salasahiji produk, produk asam karboxilat, nu boga gugus hidroxida nu diturunkeun ti cai. Produk amin nampa ion hidrogén sésana.\n\nHidrolisis bisa dianggap salaku sabalikna ti [[réaksi kondensasi|kondensasi]], nalika dua popotongan disambungkeun pikeun tiap molekul cai nu dihasilkeun. Kusabab hidrolisis réaksina bisa malik, kondensasi jeung hidrolisis bisa lumangsung sakaligus dina kaayaan kasatimbangan.\n\n===Kateubisamalikan hidrolisis dina kaayaan fisiologis===\n\nDina kaayaan fisiologis (misalna dina leyuran éncér cai), réaksi meulah hidrolitik, nalika konsentrasi prékursor métabolikna rendah (ti 10-3 nepi ka 10-6 molar), sacara prinsip [[térmodinamik]] teu bisa malik. Pikeun conto,\n\n:A + H2O → X + Y\n\n:K_d = \\frac{\\left[X\\right] \\left[Y\\right]} {\\left[H_2O\\right] \\left[A\\right]}\n\nAssuming that \'\'x\'\' is the final concentration of products, and that \'\'C\'\' is the initial concentration of A, and W = [H2O] = 55.5 molar, then \'\'x\'\' can be calculated with the equation:\n\n:\\frac{x \\times x}{W\\left(C - x\\right)} = K_d\n\nlet Kd×W = k\n\nthen x = \\frac {-k + \\sqrt {k^2 + 4kC} } {2} \n\nFor a value of C = 0.001 molar, and k = 1 molar, \'\'x\'\'/C > 0.999. Less than 0.1% of the original reactant would be present once the reaction is complete.\n\nThis theme of physiological irreversibility of hydrolysis is used consistently in metabolic pathways, since many biological processes are driven by the cleavage of [[anhydride|anhydrous]] [[pyrophosphate]] bonds.\n\n==Tempo ogé==\n*[[adénosin trifosfat]]\n*[[biopolimér]]\n*[[polimér kondensasi]]\n*[[oléokimia]]\n\n[[cs:Hydrolýza]]\n[[de:Hydrolyse]]\n[[en:Hydrolysis]]\n[[eo:Hidrolizo]]\n[[fr:Hydrolyse]]\n[[ja:加水分解]]\n[[nl:Hydrolyse]]\n[[pl:Hydroliza]]\n[[Category:Prosés kimia]]','',0,'210.169.65.109','20050128165847','',0,0,0,0,0.849983395007,'20050303210134','79949871834152'); INSERT INTO cur VALUES (1677,0,'Asam_karboksilat','Dina [[kimia]], \'\'\'asam karboksilat\'\'\' (ogé disebut \'\'\'asam alkanoat\'\'\') nyaéta [[asam organik]] nu dicirikeun ku ayana [[gugus karboxil]]. Strukturna\n\n:[[image:carboxy.png|Struktur asam karboksilat]]\n\nR mangrupa hidrogén atawa gugus organik. Dina [[rumus kimia]], ieu ogé biasa ditulis R[[karbon|C]][[oxigén|OO]][[hidrogén|H]]). \n\n== Kaasaman, sebaran éléktron, jeung résonans ==\n\nAsam karboksilat ngarupakeun asam lemah, sabab disosiasi molekul RCOOH ngan kira 1% nu jadi [[kation]] H+ jeung [[anion]] RCOO- na suhu rohangan dina leyuran [[cai]].\n\nDua atom oxigén [[éléktronégativiti|éléktronégatif]] cenderung metot éléktron ngajauhan hidrogén na gugus [[hidroxil]], sedengkeun [[proton]] H+ sésana bisa leupas kalawan gampang. Muatan négatif sésana salajengna nyebar simétris di antara dua atom oxigén, sarta [[beungkeut kimia|beungkeut]] karbon–oxigén mibanda ciri beungkeut ganda parsial (délokalisasi). \n\nIeu ngarupakeun hasil tina struktur résonans nu kaciptakeun ku ayana komponén [[karbonil]] na asam karboksilat, nu mun teu kitu gugus OH-na moal gampang kaleungitan H+-na (tempo [[alkohol]]). \n\nAyana gugus éléktronégatif (kayaning -[[gugus hidroxil|OH]] atawa -[[Klorin|Cl]]) nuturkeun gugus karboksilat bakal ngaronjatkeun kaasaman. Sahingga, pikeun conto, [[asam trikloroasétat]] (tilu gugus -Cl) ngarupakeun asam nu leuwih kuat batan [[asam laktat]] (hiji gugus -OH) nu leuwih kuat batan [[asam asetat]] (teu boga gugus séjén).\n\n==Réaksi==\n\nAsam karboksilat bisa dijieun ku jalan [[oxidasi]] lengkep [[alkohol|alkohol primér]]. \n\nAsam karboksilat meta jeung [[basa (kimia)|basa]] piekun ngahasilkeun [[uyah]] karboksilat, nalika hidrogén gugus -OH diganti ku [[ion]] logam.\nAsam étanoat (sarua jeung asam asetat) meta jeung [[natrium bikarbonat]] (\'\'baking soda\'\') jadi natrium étanoat (natrium asetat), [[karbon dioxida]], jeung cai:\n\n:CH3COOH + NaHCO3 → CH3COONa + CO2 + H2O\n\nGugus karboxil ogé meta jeung gugus [[amina]] jadi [[beungkeut péptida]] sarta jeung [[alkohol]] jadi [[éster]].\n\nAsam karboksilat bisa [[réduksi|diréduksi]] ku [[Litium aluminum hidrida|LiAlH4]] jadi [[alkohol]] primér:\n\n:[[Image:COOH_reduced_by_LAH.png]]\n\n== Conto ==\n\nSababaraha asam karboksilat di antarana:\n\n* HCOOH [[asam format]] (kapanggih dina panyeureud serangga, \'\'format\'\' nujul ka [[sireum]])\n* sadaya [[asam lemak]], nu R-na mangrupa [[alkana]] dina asam jenuh atawa [[alkéna]] mun asamna teu jenuh\n** CH3COOH [[asam asétat]] atawa asam étanoat (aya na [[cuka]])\n** CH3CH2COOH [[asam propanoat]]\n** C6H5COOH [[asam bénzoat]] (natrium bénzoat, uyah natrium asam bénzoat dipaké salaku pangawét pangan)\n** [[asam butirat]]\n** CH2=CHCOOH [[asam akrilat]]\n* [[asam laktat]], aya na susu murni\n* [[asam oksalat]]\n* [[asam malonat]]\n* [[asam suksinat]]\n* [[asam glutarat]]\n* [[asam adipat]]\n* sadaya [[asam amino]]\n\n==Tempo ogé==\n* [[anhidrida asam]]\n* [[éster]]\n\n[[Category:Asam]]\n[[Category:Asam karboksilat]]\n\n[[da:Carboxylsyre]]\n[[de:Carbonsäure]]\n[[en:carboxylic acid]]\n[[es:Grupo carboxilo]]\n[[et:Karboksüülhape]]\n[[fr:Acide carboxylique]]\n[[ja:カルボン酸]]\n[[nl:Carbonzuur]]\n[[pl:Kwas karboksylowy]]','',20,'DiN','20050303210507','',0,0,1,0,0.279251168612,'20050303210507','79949696789492'); INSERT INTO cur VALUES (1678,0,'Asam_amino','Dina [[kimia]], \'\'\'asam amino\'\'\' nyaéta [[molekul]] naon baé nu ngandung boh [[gugus fungsi]] [[amino]] jeung [[asam karboxilat]].\nDina [[biokimia]], harti nu pondok sarta umum ieu mimindengna digunakeun pikeun nujul asam amino alfa: asam amino nu gugus fungsi amino jeung asam karboxilatna kabeungkeut na atom [[karbon]] nu sarua. \n\n\'\'\'Résidu asam amino\'\'\' nyaéta naon nu nyésa na hiji asam amino nalika hiji molekul [[cai]] leungit (hiji [[ion hidrogén]], H+, ti sisi [[nitrogén]] sarta hiji [[ion hidroxil]], OH-, ti sisi karboxilat) dina ngawujudna [[beungkeut péptida]] .\n\n\n==Ihtisar==\n\nAsam amino ngarupakeun batubata biokimia, nu ngabentuk [[polimér]] pondok nu disebut [[polipéptida]] atawa [[péptida]] nu salajengna ngawangun struktur nu disebut [[protéin]] (tempo di handap). \n\nDua puluh asam amino disandikeun ku [[sandi genetik]] baku sarta disebut [[protéinogénik]]. Asam amino nu leuwih jarang jeung leuwih pajeulit bisa dijieun dumasar kaperluan ku awak. [[Prolin]] is the only proteinogenic amino acid whose side group is cyclic and links to the a-amino group, forming a secondary amino group. Strictly speaking, this makes proline an [[imino acid]]. Other amino acids contained in proteins are usually formed by modification after [[translation (biology)|translation]] (protein synthesis). These modifications are often essential for the function of the protein. At least two amino acids other than the standard 20 are sometimes incorporated into proteins during translation:\n* [[Selenocysteine]] is incorporated into some proteins at a UGA [[codon]], which is normally a stop codon.\n* [[Pyrrolysine]] is used by some [[methanogen]]s in enzymes that they use to produce [[methane]]. It is coded for similarly to selenocysteine but with the codon UAG instead.\n\nOver 500 amino acids have been found in nature. Some of them have also been found in meteoritic material. Microorganisms and plants often produce very uncommon amino acids, which can be found in peptidic [[antibiotics]] (for example [[nisin]] or [[alamethicin]]). [[Lanthionine]] is a sulfide bridged alanine dimer which is found together with [[unsaturated]] amino acids in [[lantibiotics]] (antibiotic peptides from microbial origin). 1-Aminocycloproane-1-carboxylic acid ([[1-Aminocyclopropane-1-carboxylic acid|ACC]]) is a small disubstituted cyclic amino acid and a key intermediate in the production of the plant [[hormone]] [[ethylene]].\n\nLian ti asam amino pikeun sintésis protéin, aya asam amino séjén nu sacara biologis penting, kayaning neurotransmitter [[glisin]], [[GABA]] jeung [[glutamat]], ogé [[karnitin]] (dipaké na angkutan lipid jeroeun sél), [[ornitin]], [[sitrulin]], [[homosistéin]], [[hidroxiprolin]], [[hidroxilisin]], jeung [[sarkosin]].\n\nSababaraha ti 20 asam amino na sandi genetik katelah [[asama amino ésénsil]], sabab teu bisa disintésis na jero [[awak]] tina [[sanyawa kimia|sanyawa]] séjén ku [[réaksi kimia]], tapi kudu diasupan tina dahareun. Pikeun [[manusa]], nu kaasup asam amino ésénsil nyaéa [[lisin]], [[leusin]], [[isoleusin]], [[métionin]], [[fénilalanin]], [[tréonin]], [[triptofan]], [[valin]], sarta (pikeun barudak) [[histidin]] jeung [[arginin]].\n\n==Mangpaat asam amino==\n\n[[Monosodium glutamat]] ngarupakeun additif pangan pikeun ngaronjatkeun rasa.
    \n[[L-DOPA]] (L-dihidroxifénilalanin) ngarupakeun ubar nu dipaké pikeun [[Parkinsonisme]].
    \n5-HTP (5-hidroxitriptofan) dipaké pikeun mulasara masalah neurologis nu patali jeung [[PKU]] (fénilketonuria).\n\n==Struktur umum asam amino==\n\nStruktur umum asam amino alfa protéinogénik nyaéta:\n\n COOH\n |\n H-C-R\n |\n NH2\n\ndi mana \"R\" nunjukkeun \'\'ranté gigir\'\' nu husus pikeun unggal asam amino. Asam amino biasana digolongkeun dumasar sipat ranté gigirna jadi opat golongan: [[asam]], [[basa (kimia)|basa]], [[hidrofilik]] ([[molekul polar|polar]]), jeung [[hidrofobik]] ([[nonpolar]]).\n\n===Isomérisme===\nIwal [[glisin]], R = H, asam amino aya dina dua kamungkinan [[isomérisme optik|isomér optik]], nu disebut D (tina déxtro) jeung L (tina lévo). Asam amino L ngarupakeun mayoritas asam amino nu aya na [[protéin]]. Asam amino D aya na protéin nu dihasilkeun ku \'\'exotic sea-dwelling organisms\'\', kayaning \'\'[[cone snail]]\'\'. Ogé loba pisan ayana dina [[dinding sél]] [[baktéri]].\n\n==Réaksi==\nProtéin diwangun ku [[polimérisasi]] asam amino dumasar [[beungkeut péptida]] dina prosés nu disebut [[translasi (biologi)|translasi]].\n\n[[image:amino_acids_1.png|none|Dibentukna beungkeut péptida]]\n
    \'\'Dibentukna beungkeut péptida
    1. Asam amino; 2, struktur [[zwitterion]]; 3, dua asam amino ngabentuk hiji beungkeut péptida (tempo ogé [[beungkeut kimia]]).\'\'
    \n\n==Daptar asam amino==\n\n===Struktur===\nTabel di handap ieu mintonkeun struktur jeung lambang 20 asam amino nu aya na [[sandi genetik]].\n\n[[image:amino_acids_2.png]]\n\n===Sipat kimia===\nTabel di handap ieu ngadaptar lambang saaksara, lambang tilu aksara, sarta sipat kimia ranté gigir asam aminona. Asam amino nu can kanyahoan dibéré lambang \'\'X\'\' (saaksara) atawa \'\'asx\'\' (tilu aksara) nu ngandung harti yén éta asam amino téh [[asparagin]] atawa [[asam aspartat]].\n\n{| border=\"1\" cellpadding=\"2\" cellspacing=\"0\"\n|-\n! colspan=\"2\" | Singget. \n! Ngaran lengkep \n! Tipe ranté gigir \n! Massa \n! [[titik isolistrik|pI]] \n! pK1(α-COOH) \n! pK2(α-+NH3) \n! pKr (R) \n! Catetan\n|-\n| A\n| Ala\n| [[Alanin]]\n| [[hidrofobik]]\n| 89.09\n| 6.11\n| 2.35\n| 9.87\n|\n|\n|-\n| C\n| Cys\n| [[Sistéin]]\n| [[hidrofilik]]\n| 121.16\n| 5.05\n| 1.92\n| 10.70\n| 8.37\n| Under oxidizing conditions, two cysteines can join together by a [[disulfide bond]] to form the amino acid [[cystine]]. When cysteines are part of a protein, [[insulin]] for example, this enforces tertiary structure.\n|-\n| D\n| Asp [[Asam aspartat]]\n| [[asam]]\n| 133.10\n| 2.85\n| 1.99\n| 9.90\n| 3.90\n|\n|-\n| E\n| Glu [[Asam glutamat]]\n| asam\n| 147.13\n| 3.15\n| 2.10\n| 9.47\n| 4.07\n|\n|-\n| F\n| Phe\n| [[Fenilalanin]]\n| hidrofobik\n| 165.19\n| 5.49\n| 2.20\n| 9.31\n|\n|\n|-\n| G\n| Gly\n| [[Glisin]]\n| hidrofilik\n| 75.07\n| 6.06\n| 2.35\n| 9.78\n|\n| Because of the two hydrogen atoms at the α carbon, glycine is not [[optical isomerism|optically active]].\n|-\n| H\n| His\n| [[Histidin]]\n| [[basa (kimia)|basa]]\n| 155.16\n| 7.60\n| 1.80\n| 9.33\n| 6.04\n|\n|-\n| I\n| Ile\n| [[Isoleusin]]\n| hidrofobik\n| 131.17\n| 6.05\n| 2.32\n| 9.76\n|\n|\n|-\n| K\n| Lys\n| [[Lisin]]\n| basa\n| 146.19\n| 9.60\n| 2.16\n| 9.06\n| 10.54\n|\n|-\n| L\n| Leu\n| [[Leusin]]\n| hidrofobik\n| 131.17\n| 6.01\n| 2.33\n| 9.74\n|\n|\n|-\n| M\n| Met\n| [[Métionin]]\n| hidrofobik\n| 149.21\n| 5.74\n| 2.13\n| 9.28\n|\n| Always the first amino acid to be incorporated into a protein; sometimes removed after translation.\n|-\n| N\n| Asn\n| [[Asparagin]]\n| hidrofilik\n| 132.12\n| 5.41\n| 2.14\n| 8.72\n|\n|\n|-\n| P\n| Pro\n| [[Prolin]]\n| hidrofobik\n| 115.13\n| 6.30\n| 1.95\n| 10.64\n|\n| Can disrupt protein folding structures like [[alpha helix|α helix]] or [[beta sheet|β sheet]].\n|-\n| Q\n| Gln\n| [[Glutamin]]\n| hidrofilik\n| 146.15\n| 5.65\n| 2.17\n| 9.13\n|\n|\n|-\n| R\n| Arg\n| [[Arginin]]\n| basa\n| 174.20\n| 10.76\n| 1.82\n| 8.99\n| 12.48\n|\n|-\n| S\n| Ser\n| [[Serin]]\n| hidrofilik\n| 105.09\n| 5.68\n| 2.19\n| 9.21\n|\n|\n|-\n| T\n| Thr\n| [[Tréonin]]\n| hidrofilik\n| 119.12\n| 5.60\n| 2.09\n| 9.10\n|\n|\n|-\n| V\n| Val\n| [[Valin]]\n| hidrofobik\n| 117.15\n| 6.00\n| 2.39\n| 9.74\n|\n|\n|-\n| W\n| Trp\n| [[Triptofan]]\n| hidrofobik\n| 204.23\n| 5.89\n| 2.46\n| 9.41\n|\n|\n|-\n| Y\n| Tyr\n| [[Tirosin]]\n| hidrofilik\n| 181.19\n| 5.64\n| 2.20\n| 9.21\n| 10.46\n|\n|}\n\n{| border=\"1\" bordercolor=\"black\" cellspacing=\"0\" cellpadding=\"2\"\n|-\n! Asam
    Amino\n! hidrofobik \n! positif\n! négatif \n! polar\n! muatan \n! small\n! tiny \n! aromatik \n! alifatik\n! [[Induced-dipole attraction|van der Waals]] volume\n|- align=\"center\"\n| align=\"left\" | Ala\n| X\n| -\n| -\n| -\n| -\n| X\n| X\n| -\n| -\n| align=\"left\" | 67\n|- align=\"center\"\n| align=\"left\" | Cys\n| X\n| -\n| -\n| -\n| -\n| X\n| -\n| -\n| -\n| align=\"left\" | 86\n|- align=\"center\"\n| align=\"left\" | Asp\n| -\n| -\n| X\n| X\n| X\n| X\n| -\n| -\n| -\n| align=\"left\" | 91\n|- align=\"center\"\n| align=\"left\" | Glu\n| -\n| -\n| X\n| X\n| X\n| -\n| -\n| -\n| -\n| align=\"left\" | 109\n|- align=\"center\"\n| align=\"left\" | Phe\n| X\n| -\n| -\n| -\n| -\n| -\n| -\n| X\n| -\n| align=\"left\" | 135\n|- align=\"center\"\n| align=\"left\" | Gly\n| X\n| -\n| -\n| -\n| -\n| X\n| X\n| -\n| -\n| align=\"left\" | 48\n|- align=\"center\"\n| align=\"left\" | His\n| X\n| X\n| -\n| X\n| X\n| -\n| -\n| X\n| -\n| align=\"left\" | 118\n|- align=\"center\"\n| align=\"left\" | Lys\n| X\n| X\n| -\n| X\n| X\n| -\n| -\n| -\n| -\n| align=\"left\" | 135\n|- align=\"center\"\n| align=\"left\" | Ile\n| X\n| -\n| -\n| -\n| -\n| -\n| -\n| -\n| X\n| align=\"left\" | 124\n|- align=\"center\"\n| align=\"left\" | Leu\n| X\n| -\n| -\n| -\n| -\n| -\n| -\n| -\n| X\n| align=\"left\" | 124\n|- align=\"center\"\n| align=\"left\" | Met\n| X\n| -\n| -\n| -\n| -\n| -\n| -\n| -\n| -\n| align=\"left\" | 124\n|- align=\"center\"\n| align=\"left\" | Asn\n| -\n| -\n| -\n| X\n| -\n| X\n| -\n| -\n| -\n| align=\"left\" | 96\n|- align=\"center\"\n| align=\"left\" | Pro\n| -\n| -\n| -\n| -\n| -\n| X\n| -\n| -\n| -\n| align=\"left\" | 90\n|- align=\"center\"\n| align=\"left\" | Gln\n| -\n| -\n| -\n| X\n| -\n| -\n| -\n| -\n| -\n| align=\"left\" | 114\n|- align=\"center\"\n| align=\"left\" | Arg\n| -\n| X\n| -\n| X\n| X\n| -\n| -\n| -\n| -\n| align=\"left\" | 148\n|- align=\"center\"\n| align=\"left\" | Ser\n| -\n| -\n| -\n| X\n| -\n| X\n| X\n| -\n| -\n| align=\"left\" | 73\n|- align=\"center\"\n| align=\"left\" | Thr\n| X\n| -\n| -\n| X\n| -\n| X\n| -\n| -\n| -\n| align=\"left\" | 93\n|- align=\"center\"\n| align=\"left\" | Val\n| X\n| -\n| -\n| -\n| -\n| X\n| -\n| -\n| X\n| align=\"left\" | 105\n|- align=\"center\"\n| align=\"left\" | Trp\n| X\n| -\n| -\n| X\n| -\n| -\n| -\n| X\n| -\n| align=\"left\" | 163\n|- align=\"center\"\n| align=\"left\" | Tyr\n| X\n| -\n| -\n| X\n| -\n| -\n| -\n| X\n| -\n| align=\"left\" | 141\n|}\n\n[[Category:Asam amino]]\n\n[[ca:Aminoàcid]]\n[[da:Aminosyre]]\n[[de:Aminosäure]]\n[[en:amino acid]]\n[[es:Aminoácido]][[he:חומצת אמינו]]\n[[eo:Aminoacido]]\n[[fa:اسیدهای آمینه]]\n[[fr:Acide aminé]]\n[[it:Amminoacidi]] \n[[ko:아미노산]]\n[[nl:Aminozuur]]\n[[ja:アミノ酸]]\n[[pl:Aminokwas]]\n[[ru:Аминокислоты]]\n[[sv:Aminosyra]]','/* Ihtisar */',3,'Kandar','20050307092327','',0,0,1,0,0.232090194352,'20050307092327','79949692907672'); INSERT INTO cur VALUES (1679,0,'Amanat_Galunggung','\'\'\'Amanat Galunggung\'\'\' ngarupakeun ngaran nu dibér pikeun sakumpulan naskah nu kapanggih di [[Kabuyutan]] [[Ciburuy]], salasahiji naskah pangkolotna di Kabupaten [[Garut]]. Naskah ieu ditulis dina abad ka-15 na daun lontar jeung nipah, migunakeun basa jeung aksara [[Sunda]] Kuna. Naskah ngunggelkeun papagon ngeunaan étika jeung budi pangarti Sunda baheula, nu ditepikeun ku Prabu Guru [[Darmasiksa]], nu ngawasa [[Galunggung]], ka putrana [[Ragasuci]] (Sang Lumahing Taman). Lian ti naskah ieu, aya sababaraha naskah séjén nu disusun dina abad ka-18 migunakeun aksara Arab-pegon, Jawa-Cirebon, jeung Jawa-Sunda.\n\n\n{{Pondok}}\n\n[[Category:Sunda]] [[Category:Sajarah Sunda]]\n\n[[id:Amanat Galunggung]]','',3,'Kandar','20041203175308','',0,0,0,0,0.451787832403,'20050315084342','79958796824691'); INSERT INTO cur VALUES (1680,0,'Polimérisasi','\'\'\'Polimérisasi\'\'\' nyaéta prosés ngawujudna ranté [[polimér]] organik ulangan nu panjang. Aya sababaraha rupa polimérisasi, sarta sistimna gé béda-béda. Kategorisasina ngawengku \'\'sistim adisi-kondensasi\'\' jeung \'\'chain growth-step growth system\'\'. Rupa polimérisasi nu séjénna nyaéta [[polimérisasi muka cingcin]] (Ing. \'\'ring-opening polymerization\'\'), nu sarupa jeung polimérisasi ranté.\n\n==Ihtisar==\nPolimérisasi adisi ngawengku numbukeun molekul-molekul nu mibanda [[beungkeut kimia]] rangkep dua atawa tilu. \'\'Monomér\'\' (molekul idéntik nu nyusun polimér) nu teu jenuh ieu mibanda kaleuwihan beungkeut internal nu bisa dipegatkeun sarta ditumbukeun jeung monomér séjén pikeun ngawangun ranté ulangan. Polimérisasi adisi dilarapkeun kana produksi polimér kayaning poliéténa, [[polipropilén]], jeung [[polivinilklorida]] (PVC).\n\nPolimérisasi kondensasi lumangsung nalika monomér kabungkeut ngaliwatan [[réaksi kondensasi]]. Réaksi ieu bisa dihasilkeun ku jalan metakeun molekul-molekul nu ngandung gugus fungsi [[alkohol]], [[amina]], atawa [[asam karboxilat]] (atawa turunan karboxil séjénna). Nalika amina meta jeung asam karboxilat, bakal kawangun [[amida]] atawa beungkeut péptida, kalawan ngaleupaskeun cai (jadina polimérisasi \'\'kondensasi\'\'). Nya ku prosés ieu asam-asam amino numbu sarta ngagabung jadi protéin, sakumaha dijieunna kevlar.\n\nSistim tumuwuh hambalan ranté-tumuwuh (Ing. \'\'chain growth-step growth system\'\') ngagolongkeun polimér dumasar mékanismena. Najan lolobana polimér kaasup kana golongan métode adisi-kondensasi, tapi aya sababaraha iwal.\n\nPolimér ranté-tumuwuh diwatesan salaku polimér nu kabentuk ku réaksi [[monomér]] jeung hiji [[puseur réaktif]]. Polimér ieu tumuwuh nepi ka badag dina laju nu gancang pisan. Penting dicatet yén the overall conversion rates between chain and step growth polymers are similar, but that high molecular weight polymers are formed in addition reactions much more quickly than with step polymerizations.\n\nStep growth polymers are defined as polymers formed by the stepwise reaction between functional groups of monomer. Most step growth polymers are also classified as condensation polymers, but not all step growth polymers (like polyurethanes formed from isocyanate and alcohol bifunctional monomers) release condensates. Step growth polymers increase in molecular weight at a very slow rate at lower conversions and only reach moderately high molecular weights at very high conversion (i.e. >95%).\n\nTo alleviate inconsistencies in these naming methods, adjusted definitions for condensation and addition polymers have been developed. A condensation polymer is defined as a polymer that involves elimination of small molecules during its synthesis, or contains functional groups as part of its [[backbone chain]], or it [[repeat unit]] does not contain all the atoms present in the hypothetical monomer to which it can be degraded.\n\n== Polimérisasi adisi ==\n\nPolimérisasi adisi majeujeutkeun pegatna beungkeut ganda atawa rangkep tilu, nu dipaké pikeun nyambungkeun monomér-monomér kana ranté. Dina polimérisasi éténa (gbr. 1), beungkeut pi-na pegat nu salajengna dua éléktronna disusun ulang pikeun nyiptakeun a new propagating center like the one that attacked it. The form this propagating center takes depends on the specific type of addition mechanism. Aya sababaraha mékanisme cara naratasna (inisiasi). Mékanisme [[radikal bébas]] ngarupakeun métode nu pangmunggaranna dipaké. Radikal bébas ngarupakeun atom/molekul nu réaktif pisan nu mibanda éléktron nyorangan (teu boga pasangan). Misalna dina polimérisasi éténa, mékanisme radikal bébas bisa dibagi kana tilu hambalan: inisiasi, propagasi, jeung terminasi.\n\n[[image:polimérisasi éténa.png|right]]\n\nInisiasi nyaéta prosés nyipta radikal bébas nu dipikabutuh pikeun propagasi. Radikal bisa dijieun tina molekul péroksida organik, molekul nu mibanda beungkeut tunggal O-O, ku ngaréaksikeun [[oxigén]] jeung [[éténa]]. Hasilna mangrupa molekul nu teu stabil nu gampang pisan dibeulah jadi dua radikal. In an ethene monomer, one electron pair is held securely between the two carbons in a sigma bond. The other is more loosely held in a pi bond. The free radical uses one electron from the pi bond to form a more stable bond with the carbon atom. The other electron returns to the second carbon atom, turning the whole molecule in to another radical.\n\nPropagation is the rapid reaction of this radicalised ethene molecule with another ethene monomer, and the subsequent repetition to create the repeating chain.\n\nTermination occurs when a radical reacts in a way that prevents further propagation. The most common method of termination is by coupling where two radical species react with each other forming a single molecule. Another, less common method of termination is disproportionation where two radicals meet, but instead of coupling, they exchange a proton, which gives two terminated chains, one saturated and the other with a terminal double bond.\n\nFree radical addition polymerization of ethylene must take place at high temperatures and pressures, approximately 300°C and 2000 At. While most other free radical polymerizations do not require such extreme temperatures and pressures, they do tend to lack control. One effect of this lack of control is a high degree of branching. Also, as termination occurs randomly, when two chains collide, it is impossible to control the length of individual chains. \nA newer method of polymerization similar to free radical, but allowing more control involves the [[Ziegler-Natta catalyst]].\n\nThe problem of branching occurs during propagation, when a chain curls back on itself and breaks - leaving irregular chains sprouting from the main carbon backbone. Branching makes the polymers less dense and results in low tensile strength and melting points. Developed by Karl Ziegler and Giulio Natta in the 1950s, Ziegler-Natta catalysts (triethylaluminium in the presence of a metal (IV) chloride) largely solved this problem. Instead of a free radical reaction, the initial ethene monomer inserts between the aluminium atom and one of the ethyl groups in the catalyst. The polymer is then able to grow out from the aluminium atom and results in almost totally unbranched chains. With the new catalysts, the [[tacticity]] of the polypropene chain, the alignment of alkyl groups, was also able to be controlled. Different metal chlorides allowed the selective production of each form i.e., syndiotactic, isotactic and atactic polymer chains could be selectively created.\n\nHowever there were further complications to be solved. If the Ziegler-Natta catalyst was poisoned or damaged then the chain stopped growing. Also, Ziegler-Natta monomers have to be small, and it was still impossible to control the molecular mass of the polymer chains. Again new catalysts, the [[metallocene]]s, were developed to tackle these problems. Due to their structure they have less premature chain termination and branching.\n\nOther forms of addition polymerization include cationic and anionic polymerization. While not used to a large extent in industry yet due to stringent reaction conditions such as lack of water and oxygen, these methods provide ways to polymerize some monomers that cannot be polymerized by free radical methods such as polypropylene. Cationic and anionic mechanisms are also more ideally suited for living polymerizations, although free radical living polymerizations have also been developed.\n\n== Polimérisasi kondensasi ==\n\nPolimérisasi nu lumangsungna ku prosés [[réaksi kondensasi]].\n\n==Sajarah==\nPolimérisasi bisa dilacak nepi ka munggaran kahirupan nu dumasar [[DNA]], sabab boh DNA atawa [[protéin]] bisa dianggap salaku polimér. Polimér \'sintétik\' munggaran na abad ka-19 sabenerna dijieun ku jalan ngarombak polimér alam. Pikeun conto, [[nitrosélulosa]] dijieun ku jalan ngaréaksikeun [[sélulosa]] jeung [[asam nitrat]]. Polimér munggaran nu asli jieunan manusa, [[bakelit]], disintésis taun 1872, ngan laju panalungtikan ngeunaan polimér jeung polimérisasi ngaronjatna mah taun 1930-an, waktu papanggihan [[poliéténa]] ku pausahaan kimia [[Imperial Chemical Industries PLC|ICI]].\n\n== Tempo ogé ==\n*[[Polimérisasi plasma]]\n*[[Polimér]]\n*[[Katalis Zieglar-Natta]]\n*[[Métallosin]]\n\n[[de:Polymerisation]]\n[[en:polymerization]]\n[[pt:Polimerização]]\n[[ja:重合反応]]\n[[Category:Prosés kimia]]','/* Ihtisar */',3,'Kandar','20050216032507','',0,0,0,0,0.240113861039,'20050216032507','79949783967492'); INSERT INTO cur VALUES (1682,0,'Vagina','#REDIRECT [[Heunceut]]\n','Vagina dipindahkeun ka Heunceut',3,'Kandar','20041029095456','',0,1,0,1,0.038879031799,'20041029095456','79958970904543'); INSERT INTO cur VALUES (1683,6,'Aktivasi.png','ti méta','ti méta',3,'Kandar','20041101042330','',0,0,0,1,0,'20050208084918','79958898957669'); INSERT INTO cur VALUES (1684,0,'Katalis','[[image:profil_éntalpi.png|frame|\'\'\'Gambar 1\'\'\' Profil [[éntalpi]] pikeun réaksi nu maké jeung teu maké katalis. \'\'AU\'\' mangrupa énergi aktivasi pikeun réaksi tanpa katalis, \'\'AC\'\' mangrupa énergi aktivasi nu dikurangan pikeun réaksi nu sarua nalika dikatalisan. \'\'I\'\' salaku titik nalika \'\'chemical intermediate\'\' kabentuk, nu salajengna meta jadi produk.]]\n\'\'\'Katalis\'\'\' nyaéta hiji zat nu ngaronjatkeun [[laju]] hiji [[réaksi kimia]], dina suhu nu tangtu, tanpa teu kabawa robah atawa kahakan ku réaksina (tempo ogé [[katalisis]]). Katalis aub na réaksi, tapi lain mangrupa réaktan atawa produk kimia.\n\nKatalis ngajadikeun réaksi bisa lumangsung leuwih gancang atawa bisa lumangsung dina suhu nu leuwih handap alatan parobahan nu dipicuna dina réaktan. Katalis nyadiakeun jalur séjén nu [[énergi aktivasi]]na leuwih handap pikeun lumangsungna réaksi. Molekul nu teu mibanda énergi pikeun meta atawa énergina handap teuing sahingga réaksina bakal lila pisan jadi bisa meta ku ayana katalis. Katalis ngurangan énergi nu dipikabutuh pikeun lumangsungna réaksi.\n\nDua kategori utama katalis nyaéta katalis homogén jeung hétérogén. Katalis hétérogén aya dina fase nu béda ti réaktan dina réaksi nu dikatalisanana, sedengkeun katalis homogén aya dina fase nu sarua. Conto pikeun katalis hétérogén nyaéta katalis nu nyadiakeun beungeut sangkan réaktan (atawa [[substrat]]) samentara bisa kajerap. Beungkeut na substrat jadi lemah sahingga produk anyar bisa dihasilkeun. Beungkeut antara produk jeung katalis leuwih lemah, sahingga salajengna produkna lésot.\n\nKatalis homogén umumna meta jeung hiji atawa leuwih réaktan pikeun ngabentuk sarupaning panengah kimiawi (\'\'chemical intermediate\'\') nu salajengna meta pikeun ngabentuk produk réaksi ahir, dina prosés nu ngalahirkeun deui katalisna. Di handap ieu hiji skéma réaksi katalitik, C nunjukkeun katalisna:\n\n:A + C → AC (1)\n\n:B + AC → AB + C (2)\n\nNajan katalisna (C) kahakan ku réaksi 1, salajengna kaluar deui dina réaksi 2, sahingga réaksi gemblengna jadi:\n\n:A + B + C → AB + C\n\nkatalis teu kahakan atawa dihasilkeun. [[Énzim]] ngarupakeun biokatalis. Mangpaat \"katalis\" dina jihat budaya nu leuwih lega sacara kasarna mah analog sarupa/analog jeung nu dipedar di dieu.\n\nSababaraha katalis nu kawentar nu kungsi dikembangkeun nyaéta [[katalis Ziegler-Natta]] nu dipaké ngahasilkeun sacara massal [[poliétilén]] jeung [[polipropilén]]. Réaksi katalitik nu pangdipikawanohna di antarana [[prosés Haber]] pikeun sintésis [[amonia]], nu maké [[beusi]] salaku katalis.\n[[Konvérter katalitik]] ngancurkeun sababaraha produk gigir pembakaran dina mobil, dijieunna tina [[platinum]] jeung [[rhodium]].\n\n==Tempo ogé==\n*[[Énzim]]\n*[[Katalis koordinasi]]\n\n\n[[Category:Kimia]]\n\n[[da:Katalysator]]\n[[de:Katalysator]]\n[[en:catalyst]]\n[[et:Katalüsaator]]\n[[es:Catalizador]]\n[[fr:Catalyseur]]\n[[id:katalis]]\n[[nl:Katalysator]]\n[[ja:触媒]]\n[[pt:Catalisador]]\n[[zh:催化剂]]','',3,'Kandar','20041125101914','',0,0,0,0,0.055924306184,'20041125101914','79958874898085'); INSERT INTO cur VALUES (1686,6,'Profil_éntalpi.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041101070950','',0,0,0,1,0,'20041125101914','79958898929049'); INSERT INTO cur VALUES (1687,0,'Sél_(biologi)','[[Image:Sél épitél.jpeg|thumb|right|160px|Sél na kultur, diwarnaan [[keratin]]na]]\n\n\'\'\'Sél\'\'\' ngarupakeun unit struktural jeung fungsional sadaya [[organisme]] [[hirup]]. Sababaraha organisme, kayaning baktéri, unisélular, ngan diwangun ku sél nunggal. Organisme séjén, kayaning [[manusa]], kaasup [[multisélular]], (manusa mibanda kira 100 triliun sél). \n[[Tiori sél]], munggaran dikembangkeun [[abad ka-19]], ngunikeun yén sadaya organisme diwangun ku hiji atawa leuwih sél; sadaya sél datangna ti sél nu saméméhna geus aya; sadaya fungsi vital hiji organisme lumangsung jeroeun sél sarta yén sél ngandung [[genetik|informasi turunan]] nu dipikabutuh pikeun ngatur fungsi sél sarta pikeun neruskeun informasi ka sél wedalan salajengna.\n\nKecap \'\'[[sél]]\'\' asalna tina [[basa Latin]] \'\'cella\'\', rohangan leutik. Ngaran ieu dipilih ku [[Robert Hooke]] sabab anjeunna nempo kamiripan antara sél \'\'[[cork]]\'\' jeung rohangan leutik.\n\n==Ihtisar==\n===Pasipatan sél===\n[[Image:ukuran_sél.jpg|thumb|right|190px|Kultur sél beurit émbrionik. Sél nu ditémbongkeun kira 10 μ across.]]\n\nUnggal sél mangrupakeun éntitas nu mulasara diri: bisa ngasupkeun [[gizi]], ngarobah gizi jadi [[énergi]], migawé pungsi husus, sarta baranahan sakumaha perluna. Unggal sél neundeun paréntah-paréntah sorangan pikeun migawé tiap kagiatan-kagiatanana.\n\nSadaya sél mibanda sababaraha kabisa:\n*Réproduksi ku [[cell division]].\n*[[Métabolisme sél|Métabolisme]], kaasup ngasupkeun bahan kasar, ngawangun komponén sél, \"nyiptakeun\" [[énergi]], sarta ngaluarkeun \'\'[[byproduct]]\'\'. Lumangsungna fungsi sél gumantung kana kabisana pikeun nyerep jeung migunakeun énergi kimia nu diteundeun dina molekul organik. Énergi ieu diturunkeun tina [[jalur métabolik]].\n*[[Biosintésis protéin]], mesin sél kayaning [[énzim]]. Sawatara sél [[mamalia]] ngandung nepi ka 10.000 rupa [[protéin]].\n*Némbal kana [[transduksi sinyal|stimuli]] internal atawa éxternal kayaning parobahan temperatur, [[pH]], atawa kadar gizi.\n*[[traffic (locational)|Patali marga]] [[vésikel]].\n\n===Tipe sél===\nHiji cara pikeun ngagolongkeun sél, nyaéta naha maranéhna hirup nyorangan atawa ngagorombol. Aya rupa-rupa [[organisme]], ti mimiti sél tunggal (disebut organisme \'\'\'unisélular\'\'\') that function and survive more or less independently, through \'\'colonial\'\' forms with cells living together, to \'\'\'multicellular\'\'\' forms in which cells are specialized and do not generally survive once separated. 220 types of cells and tissues make up the multicellular [[human]] body.\n\n[[Image:celltypes.png|thumbnail|350px|\'\'\'The cells of eukaryotes and prokaryotes.\'\'\' - This figure illustrates a typical human cell (\'\'eukaryote\'\') and a typical bacterium (\'\'prokaryote\'\'). The drawing on the \'\'left\'\' highlights the internal structures of eukaryotic cells, including the nucleus (\'\'light blue\'\'), the nucleolus (\'\'intermediate blue\'\'), mitochondria (\'\'orange\'\'), and ribosomes (\'\'dark blue\'\'). The drawing on the \'\'right\'\' demonstrates how bacterial DNA is housed in a structure called the nucleoid (\'\'very light blue\'\'), as well as other structures normally found in a prokaryotic cell, including the cell membrane (\'\'black\'\'), the cell wall (\'\'intermediate blue\'\'), the capsule (\'\'orange\'\'), ribosomes (\'\'dark blue\'\'), and a flagellum (also \'\'black\'\').]]\n\nCells can also be classified into two categories based on their internal structure.\n\n* \'\'\'\'\'[[prokaryote|Prokaryotic]]\'\'\'\'\' cells are structurally simple. They are found only in single-celled and [[Colony (biology)|colonial]] organisms. In the [[three-domain system]] of [[scientific classification]], prokaryotic cells are placed in the domains [[Archaea]] and [[Eubacteria]].\n\n*\'\'\'\'\'[[eukaryote|Eukaryotic]]\'\'\'\'\' cells have [[organelle]]s with their own membranes. Single-celled eukaryotic organisms are very diverse, but many colonial and multicellular forms also exist. (The multicellular [[kingdom (biology)|kingdom]]s, i.e., [[Animal|Animalia]], [[Plant|Plantae]] and [[Fungi]], are all eukaryotic.)\ntest\n\n==Komponén sél==\n\n[[image:sél_biologis.png|thumb|400px|Skéma umum sél sato. [[Organél]]: (1) [[nukléolus]] (2) [[nukleus]] (3) [[ribosom]] (4) [[vésikel]],(5) [[rétikulum éndoplasma]] (RÉ) kasar, (6) [[awak Golgi]], (7) [[Mikrotubul]], (8) RÉ lemes, (9) [[mitokondria]], (10) [[vakuola]], (11) [[sitoplasma]], (12) [[lisosom]], (13) [[séntriol]]]]\n\nSadaya sél boh prokariot atawa eukariot mibanda [[mémbran sél|mémbran]], nu ngabungkus sél, misahkeun interiorna tina lingkungan sabudeureunana, sacara ketat ngontrol naon nu asup jeung kaluar sarta mulasara [[poténsial sél|poténsi listrik sél]]. Di jero mémbran aya [[sitoplasma]] (zat nu ngeusian ampir sakabéh eusi sél) nu [[uyah|asin]]. Sadaya sél mibanda [[DNA]], bahan wawarisan [[gén]], jeung [[RNA]], nu ngandung informasi nu dipikabutuh pikeun [[éxprési gén|ngéxprésikeun]] rupa-rupa [[protéin]] kayaning [[énzim]], mesin utama sél. Sajeroeun sél dina rupa-rupa wanci aya rupa-rupa [[biomolekul]] séjén. Artikel ieu bakal ngabahas sacara ringkes komponén-komponén utama ieu lajeng diteraskeun ku dadaran ringkes pungsina.\n\n===Mémbran sél - jakét panyalindung sél===\n\'\'Artikel utama:\'\' [[mémbran sél]]\n\nWates luar sél eukariot disebut \'\'mémbran plasma\'\', sedengkeun di prokariot ilahar disebut \'\'mémbran sél\'\'. Mémbran ieu pikeun misahkeun sarta panyalindungan pikeun sél ti lingkungan sabudeureunana, diwangun utamana tina [[lapis ganda lipid]] (molekul sarupa lemak) jeung [[protéin]]. Nu narapel na éta mémbran nyaéta rupa-rupa molekul nu meta salaku torowongan jeung kompa, nu mindahkeun molekul-molekul ka jeung ti sél.\n\n===Sitoskeleton - rorongkong sél===\n\'\'Artikel utama:\'\' [[Sitoskeleton]]\n\nSitoskeleton nyaéta komponén sél nu penting, pajeulit, sakaligus dinamis, nu meta pikeun nyusun/ngatur sarta mertahankeun bentuk sél; nyangsangkeun organél dina tempat samistina; mantuan nalika [[éndositosis]], ngasupkeun bahan luar ku sél; sarta mindahkeun bagian-bagian sél dina prosés tumuwuh jeung motiliti. Aya loba pisan protéin nu patali jeung sitoskeleton, nu masing-masing ngatur struktur sél ku ngarahkeun, ngagulungkeun, sarta nyambungkeun filamén.\n\n===Sitoplasma - rohangan jero sél===\n\'\'Artikel utama:\'\' [[Sitoplasma]]\n\nJeroeun sél aya rohangan badag nu dieusi cairan nu disebut sitoplasma, kadang disebut sitosol. Na prokariot, rohangan ieu rélatif teu kabagi-bagi. Na eukariot, sitosol mangrupa \"sop\" tempat pagalona sagala organél. It is also the home of the cytoskeleton. The cytosol contains dissolved nutrients, helps break down waste products, and moves material around the cell through a process called \'\'cytoplasmic streaming\'\'. The nucleus often flows with the cytoplasm changing its shape as it moves. The cytoplasm also contains many salts and is an excellent conductor of electricity, creating the perfect environment for the mechanics of the cell. The function of the cytoplasm, and the organelles which reside in it, are critical for a cell\'s survival.\n\n===Bahan genetik===\n \nAya dua rupa bahan genetik: [[DNA|asam déoxiribonukléat]] (DNA) jeung [[RNA|asam ribonukléat]] (RNA). Organisme lolobana diwangun tina DNA, tapi aya sababaraha virus nu mibanda RNA salaku bahan genetikna. Informasi biologis nu dikandung ku organisme disandikeun dina runtuyan DNA atawa RNAna.\n \nBahan genetik prokariot diatur dina struktur sirkular basajan nu aya na sitoplasma. Bahan genetik eukariot leuwih pajeulit sarta dibagi kana unit diskrét nu disebut [[gén]]. Bahan genetik manusa dijieun tina dua komponén béda: [[génom|génom inti]] jeung [[génom mitokondria]]. Génom inti kabagi kana 24 molekul DNA liniér, nu masing-masing dikandung dina [[kromosom]] nu béda. Génom mitokondria nyaéta molekul DNA sirkular nu misah ti DNA inti. Najan génom mitokondria leutik pisan, tapi nyandi sababaraha protéin nu penting pisan.\n\n===Organél===\n\'\'Artikel utama:\'\' [[Organél]]\n\nAwak manusa ngandung pirang-pirang organ, kayaning [[jantung]], [[burih]], [[ginjal]], nu masing-masing ngajalankeun pungsi nu béda. Sél ogé mibanda sakumpulan \"organ leutik\" nu disebut [[organél]], nu diluyukeun atawa dihususkeun mibanda hiji atawa leuwih pungsi penting. Organél ngan aya na eukariot jeung salawasna dikuriling ku mémbran panyalindung. \n\n*\'\'\'Inti sél - puseur sél\'\'\': [[Inti sél]] is the most conspicuous organelle found in a eukaryotic cell. It houses the cell\'s chromosomes and is the place where almost all DNA replication and RNA synthesis occur. The nucleus is spheroid in shape and separated from the cytoplasm by a membrane called the [[nuclear envelope]]. The nuclear envelope isolates and protects a cell\'s DNA from various molecules that could accidentally damage its structure or interfere with its processing. During processing, DNA is [[transcribed]], or synthesized, into a special RNA, called mRNA. This mRNA is then transported out of the nucleus, where it is translated into a specific protein molecule. In prokaryotes, DNA processing takes place in the cytoplasm.\n\n*\'\'\'Ribosom - mesin produksi protéin\'\'\': [[Ribosom]]s are found in both prokaryotes and eukaryotes. The [[ribosome]] is a large complex composed of many molecules, including RNAs and proteins, and is responsible for processing the genetic instructions carried by an mRNA. The process of converting an mRNA\'s genetic code into the exact sequence of amino acids that make up a protein is called [[translation (genetics)|translation]]. Protein synthesis is extremely important to all cells, and therefore a large number of ribosomes—sometimes hundreds or even thousands—can be found throughout a cell.\n\n*\'\'\'Mitokondria jeung kloroplas - generator\'\'\': [[Mitokondria]] are self-replicating organelles that occur in various numbers, shapes, and sizes in the cytoplasm of all eukaryotic cells. As mentioned earlier, mitochondria contain their own genome that is separate and distinct from the nuclear genome of a cell. Mitochondria play a critical role in generating energy in the eukaryotic cell, and this process involves a number of complex [[metabolic pathway]]s. [[Chloroplasts]] are similar to mitochondria but are found only in plants.\n\n*\'\'\'Rétikulum éndoplasma jeung awak Golgi - ménéjer makromolekul:\'\'\': The [[endoplasmic reticulum]] (ER) is the transport network for molecules targeted for certain modifications and specific destinations, as compared to molecules that will float freely in the cytoplasm. The ER has two forms: the rough ER and the smooth ER. The rough ER is labeled as such because it has ribosomes adhering to its outer surface, whereas the smooth ER does not. Translation of the mRNA for those proteins that will either stay in the ER or be \'\'exported\'\' (moved out of the cell) occurs at the ribosomes attached to the rough ER. The smooth ER serves as the recipient for those proteins synthesized in the rough ER. Proteins to be exported are passed to the [[Golgi apparatus]], sometimes called a \'\'Golgi body\'\' or \'\'Golgi complex\'\', for further processing, packaging, and transport to a variety of other cellular locations.\n \n*\'\'\'Lisosom jeung peroxisom - the cellular digestive system\'\'\': [[Lysosome]]s and [[peroxisome]]s are often referred to as the garbage disposal system of a cell. Both organelles are somewhat spherical, bound by a single membrane, and rich in digestive [[enzyme]]s, naturally occurring proteins that speed up biochemical processes. For example, lysosomes can contain more than three dozen enzymes for degrading proteins, nucleic acids, and certain sugars called polysaccharides. Here we can see the importance behind compartmentalization of the eukaryotic cell. The cell could not house such destructive enzymes if they were not contained in a membrane-bound system.\n\n==Anatomi sél==\n=== Sél prokariot ===\n[[Prokariot]] dibédakeun ti eukariot dumasar susunan intina, hususna ku teu ayana mémbran inti. Prokariot ogé teu boga organél-organél nu has sél eukariot. Fungsi organélna lolobana, kayaning mitokondria, kloroplas, jeung awak Golgi, diwengku ku mémbran plasma prokariot. Svl prokariot mibanda tilu wewengkon arsitéktural: appendages called [[flagella]] and [[pili]]—proteins attached to the cell surface; a [[cell envelope]] consisting of a capsule, a [[cell wall]], and a [[plasma membrane]]; and a [[cytoplasmic region]] that contains the [[cell genome]] (DNA) and ribosomes and various sorts of inclusions. Other differences include:\n*The \'\'cytoplasm\'\' of prokaryotes (the liquid which makes up most of the cell volume) is diffuse and granular due to \'\'ribosomes\'\' (protein factories) floating in the cell.\n*The \'\'plasma membrane\'\' (a phospholipid bilayer) separates the interior of the cell from its environment and serves as a filter and communications beacon.\n*Most prokaryotes have a \'\'[[cell wall]]\'\' (some exceptions are \'\'Mycoplasma\'\' (a bacterium) and \'\'Thermoplasma\'\' (an archaeon)). It consists of \'\'[[peptidoglycan]]\'\' in bacteria, and acts as an additional barrier against exterior forces. It also prevents the cell from \"exploding\" from [[osmotic pressure]] against a hypotonic environment.\n*A prokaryotic chromosome is usually a circular molecule (an exception is that of the bacterium \'\'Borrelia burgdorferi\'\', which causes [[Lyme disease]]). Even without a real \'\'nucleus\'\', the DNA is somehow condensed in a \'\'nucleoid\'\'. Prokaryotes can carry extrachromosomal DNA elements called \'\'[[plasmid]]s\'\', which are usually circular. Plasmids can carry additional functions, such as antibiotic resistance.\n*Some prokaryotes have \'\'[[flagellum|flagella]]\'\' which enable them to move actively instead of passively drifting.\n\n=== Sél eukariot ===\nSél [[eukariot]] ukuranana kurang leuwih sapuluh kalieun sél prokariot sarta eusina bisa nepi ka 1000 kalieunana. Bébéda utama antara prokariot jeung eukariot nyaéta sél eukariot mah ngandung kompartemén nu napel na mémbran tempat lumangsungna kagiatan métabolik husus. Utamana [[inti]], a membrane-delineated compartment that houses the eukaryotic cell’s DNA. It is this nucleus that gives the eukaryote—literally, true nucleus—its name.\nEukaryotic organisms also have other specialized structures, performing dedicated functions, the aforementioned [[organelles]].. \nOther differences include:\n*The cytoplasm of eukaryotes does not appear as granular as that of prokaryotes, since an important part of the ribosomes are bound to the \'\'[[endoplasmic reticulum]]\'\'.\n*The plasma membrane resembles that of prokaryotes in function, with minor differences in the setup. Cell walls may or may not be present.\n*The eukaryotic DNA is organized in one or more linear molecules, called [[chromosome]]s, which are highly condensed (e.g. folded around [[histone]]s). All chromosomal DNA is stored in the \'\'[[cell nucleus]]\'\', separated from the cytoplasm by a membrane. Some eukaryotic [[organelle]]s can contain some DNA.\n*Eukaryotes can become mobile using \'\'cilia\'\' or \'\'flagella\'\'. The flagella are more complex than those of prokaryotes.\n\n{| align=\"center\" border=\"1\" \n|+\'\'\'Table 1: Babandingan antara sél prokariot jeung eukariot\'\'\'\n|- \n| \n!Prokariot\n!Eukariot\n|-\n!typical organisms\n|[[bacterium|bacteria]]\n|[[protist]]s, [[fungus|fungi]], [[plant]]s, [[animal]]s\n|-\n!typical size\n|~ 1-10 µm\n|~ 10-100 µm ([[sperm]] cells, apart from the tail, are smaller)\n|-\n!type of [[cell nucleus|nucleus]]\n|[[nucleoid region]]; no real nucleus\n|real nucleus with double membrane\n|-\n!DNA\n|circular (usually)\n|linear molecules ([[chromosome]]s) with [[histone]] [[protein|proteins]]\n|-\n!RNA-/protein-synthesis\n|coupled in [[cytoplasm]]\n|RNA-synthesis inside the nucleus
    protein synthesis in cytoplasm\n|-\n![[ribosome]]s\n|50S+30S\n|60S+40S\n|-\n!cytoplasmatic structure\n|very few structures\n|highly structured by intercellular membranes and a [[cytoskeleton]]\n|-\n![[chemotaxis|cell movement]]\n|[[flagellum|flagella]] made of [[flagellin]]\n|flagella and [[cilium|cilia]] made of [[tubulin]]\n|-\n![[mitochondrium|mitochondria]]\n|none\n|one to several dozen (though some lack mitochondria)\n|-\n![[chloroplast]]s\n|none\n|in [[algae]] and [[plant]]s\n|-\n!organization\n|usually single cells\n|single cells, colonies, higher organisms with specialized cells\n|-\n![[cell division]]\n|[[Binary fission]] (simple division)\n|[[Mitosis]] (core division)
    [[Cytokinesis]] (cytoplasmatic division)\n|}\n\n{|align=\"center\" border=\"1\" \n|+\'\'\'Table 2: Comparison of structures between animal and plant cells\'\'\'\n|-\n|\n!Typical animal cell\n!Typical plant cell\n|-\n!Organelles\n|\n* [[Nucleolus]]\n* [[Cell nucleus|Nucleus]]\n* [[Ribosome]]\n* [[Vesicle]] \n* Rough [[endoplasmic reticulum]] (ER)\n* [[Golgi apparatus]]\n* [[Microtubule]]\n* Smooth ER\n* [[Mitochondrion|Mitochondria]]\n* [[Vacuole]]\n* [[Cytoplasm]]\n* [[Lysosome]] \n* [[Centriole]]s\n|\n*[[Tonoplast]]\n*[[Central vacuole]]\n*[[Cell nucleus|Nucleus]]\n*[[Rough endoplasmic reticulum]]\n*[[Smooth endoplasmic reticulum]]\n*[[Peroxisome]]\n*[[Golgi apparatus]]\n*[[Ribosomes]]\n*[[Chloroplast]]\n*[[Microfilament]]s\n*[[Microtubule]]s\n*[[Mitochondrion]]\n|-\n!Additional structures\n|\n*[[Cilium]]\n*[[Cytoplasm]]\n*[[Flagellum]]\n*[[Plasma membrane]]\n|\n*[[Plasma membrane]]\n*[[Cell wall]]\n*[[Plasmodesma]]\n|}\n\n==Fungsi sél==\n===Pertumbuhan jeung métabolisme sél===\n\'\'Artikel utama:\'\' [[Pertumbuhan sél]], [[Métabolisme sél]]\n\nBetween successive cell divisions cells grow through the functioning of cellular metabolism.\nCell metabolism is the process by which individual [[cell (biology)|cell]]s process nutrient molecules. Metabolism has two distinct divisions; [[catabolism]], in which the cell breaks down complex molecules to produce energy and reducing power, and [[anabolism]], where the cell uses energy and reducing power to construct complex molecules and perform other biological functions.\nComplex sugars consumed by the organism can be broken down into a less chemically complex sugar molecule called [[glucose]]. Once inside the cell, glucose is broken down to make adenosine triphosphate ([[ATP]]), a form of energy, via two different pathways.\n\nThe first pathway, [[glycolysis]], requires no oxygen and is referred to as [[anaerobic metabolism]]. Each reaction is designed to produce some hydrogen ions that can then be used to make energy packets ([[ATP]]). In prokaryotes, glycolysis is the only method used for converting energy.\nThe second pathway, called the Kreb\'s cycle, or [[citric acid cycle]], occurs inside the mitochondria and is capable of generating enough ATP to run all the cell functions. \n\n===Nyieun sél anyar===\n\'\'Main article:\'\' [[Cell division]]\n\n[[Image:proteinsynthesis.png|frame|An overview of protein synthesis.
    Within the [[cell nucleus|nucleus]] of the cell (\'\'light blue\'\'), [[gene]]s (DNA, \'\'dark blue\'\') are [[transcription (genetics)|transcribed]] into [[RNA]]. This RNA is then subject to post-transcriptional modification and control, resulting in a mature [[mRNA]] (\'\'red\'\') that is then transported out of the nucleus and into the [[cytoplasm]] (\'\'peach\'\'), where it undergoes [[translation (genetics)|translation]] into a protein. mRNA is translated by [[ribosome]]s (\'\'purple\'\') that match the three-base [[codon]]s of the mRNA to the three-base anti-codons of the appropriate [[transfer RNA|tRNA]]. Newly synthesized proteins (\'\'black\'\') are often further modified, such as by binding to an effector molecule (\'\'orange\'\'), to become fully active.]]\n\nCell division involves a single cell (called a \'\'mother cell\'\') dividing into two daughter cells. This leads to growth in [[multicellular organism]]s (the growth of [[biological tissue|tissue]]) and to procreation ([[vegetative reproduction]]) in [[unicellular organism]]s.\n[[Prokaryote|Prokaryotic]] cells divide by [[binary fission]]. [[Eukaryote|Eukaryotic]] cells usually undergo a process of nuclear division, called [[mitosis]], followed by division of the cell, called [[cytokinesis]]. A [[diploid]] cell may also undergo [[meiosis]] to produce haploid cells, usually four. [[Haploid]] cells serve as [[gamete]]s in multicellular organisms, fusing to form new diploid cells.\n[[DNA replication]], or the process of duplicating a cell\'s genome, is required every time a cell divides. Replication, like all cellular activities, requires specialized proteins for carrying out the job. \n\n===Sintésis protéin===\n\'\'Artikel utama:\'\' [[Biosintésis protéin]]\n\nSintésis protéin nyaéta prosés nalika sél ngawangun [[protéin]]. [[transkripsi (genetik)|Transkripsi]] DNA nujul ka sintésis molekul [[RNA utusan]] (Ing. \'\'messenger RNA\'\', mRNA) tina citakan DNA. Prosés ieu mirip pisan jeung réplikasi DNA. Sanggeus mRNA dijieun, molekul protéin anyar mitembeyan disintésis ngaliwatan prosés [[translasi (genetik)|translasi]].\n\nMesin sélular nu boga tanggung jawab dina sintésis protéin nyaéta [[ribosom]], nu diwangun ku RNA struktural jeung kira 80 rupa protéin. Nalika ribosom tepung jeung mRNA, mangka prosés [[translasi (genetik)|translasi]] mRNA jadi protéin dimimitian. Ribosom nampa a new [[transfer RNA]], or tRNA—the adaptor molecule that acts as a translator between mRNA and protein—bearing an [[amino acid]], the building block of the protein. Another site binds the tRNA that becomes attached to the growing chain of amino acids, forming the a polypeptide chain that will eventually be processed to become a protein.\n\n==Sasakala sél==\nSasakala sél nu patali pisan jeung [[sasakala hirup]], kungsi jadi salasahiji hambalan pangpentingna dina [[évolusi]] hirup. Lahirna sél nandaan jalan ti [[kimia prébiotik]] ka [[hirup|kahirupan]] biologis.\n\n===Sasakala sél munggaran===\n\nMun hirup disawang tina jihat [[réplikator]], nyaéta molekul [[DNA]] dina organisme, sél nyumponan dua kaayaan fundaméntal: pangjaga ti lingkungan luar sarta ngawadahan aktivitas biologis. The former condition is needed to maintain the fragile [[DNA]] chains stable in a varying and sometimes aggressive environment, and may have been the main reason for which cells evolved. The latter is fundamental for the evolution of [[biological complexity]]. If freely-floating DNA molecules that code for [[enzyme|enzymes]] that are not enclosed into cells, the enzymes that advantage a given DNA molecule (for example, by producing nucleotides) will automatically advantage the neighbouring DNA molecules. This might be viewed as \"[[parasitism]] by default\". Therefore the [[natural selection|selection pressure]] on DNA molecules will be much lower, since there is not a definitive advantage for the \"lucky\" DNA molecule that produces the better enzyme over the others: all molecules in a given neighbourhood are almost equally advantaged. \n\nIf all the DNA molecule is enclosed in a cell, then the enzymes coded from the molecule will be kept close to the DNA molecule itself. The DNA molecule will directly enjoy the benefits of the enzymes it codes, and not of others. This means other DNA molecules won\'t benefit from a positive mutation in a neighbouring molecule: this means that positive mutations give immediate and selective advantage to the replicator bearing it, and not on others. This is thought to have been the one of the main driving force of evolution of life as we know it.\n(Note. This is more a metaphor given for simplicity than complete accuracy, since the earliest molecules of life, probably up to the stage of cellular life, were most likely [[RNA]] molecules, acting both as replicators and enzymes: see [[RNA world hypothesis]] . But the core of the reasoning is the same.)\n\nBiochemically, cell-like spheroids formed by [[proteinoid|proteinoids]] are observed by heating [[amino acid|amino acids]] with [[phosphoric acid]] as a catalyst. They bear much of the basic features provided by [[cell membrane|cell membranes]]. Proteinoid-based protocells enclosing RNA molecules could (but not necessarily should) have been the first cellular life forms on Earth.\n\n===Sasakala sél eukariot===\nÉvolusi sél eukariot sigana ngaliwatan prosés [[simbiosis]] sél-sél prokariot. It is almost certain that DNA-bearing organelles like the [[mitochondria]] and the [[chloroplasts]] are what remains of ancient symbiotic oxygen-breathing [[bacteria]] and [[cyanobacteria]], respectively, where the rest of the cell seems to be derived from an ancestral [[archaea|archaean]] prokaryote cell. There is still considerable debate on if organelles like the [[hydrogenosome]] predated the origin of [[mitochondria]], or viceversa : see the [[hydrogen hypothesis]] for the origin of eukaryotic cells.\n\n==Sajarah==\n*1632-1723: [[Antony van Leeuwenhoek]] kalawan otodidak nyieun [[Lénsa (optik)|lénsa]] jeung [[mikroskop]], sarta ngagambar [[protozoa]], kayaning \'\'[[Vorticella]]\'\' tina cihujan jeung [[baktéri]] tina bahamna sorangan.\n*1665 : [[Robert Hooke]] manggih sél dina \'\'cork\'\', lajeng dina jaringan tutuwuhan migunakeun mikroskop.\n::\'\'...I could exceedingly plainly perceive it to be all perforated and porous, much like a Honeycomb...these [[pore]]s or cells, were not very deep, but consisted of a great many little boxes...\'\' – Hooke describing his observations on a thin slice of cork.\n*1839 : [[Theodor Schwann]] jeung [[Matthias Jakob Schleiden]] nu ngabuktikeun prinsip yén tutuwuhan jeung sato diwangun ku sél-sél, jinek yén sél mangrupakeun unit struktur jeung tumuwuh nu ilahar, salajengna ngedalkeun \'\'\'Tiori sél\'\'\'.\n*Kapercayaan yén bentuk kahirupan bisa lumangsung sacara ngadadak kitu baé (spontan, \'\'generatio spontanea\'\') dibantah ku [[Louis Pasteur]] (1822-1895).\n*[[Rudolph Virchow]] nyebutkeun yén sél salawasna borojol tina [[pameulahan sél]] (\'\'omnis cellula ex cellula\'\').\n*1931: [[Ernst Ruska]] nyieun [[mikroskop transmisi éléktron]] di [[Universitas Berlin]]. Taun 1935 anjeunna geus nyieun mikroskop éléktron nu résolusina dua kalieun mikroskop cahaya, revealing previously unresolvable organelles.\n*1953: [[James D. Watson|Watson]] jeung [[Francis Crick|Crick]] munggaran ngawawarkeun struktur [[hélix]] ganda DNA ([[Pébruari 28]]).\n*1981: [[Lynn Margulis]] medalkeun \'\'Symbiosis in Cell Evolution\'\' nu ngadadarkeun [[tiori éndosimbiosis]].\n\n==Jejer nu patali==\n*[[Biologi]] \n*[[Biologi sél]] \n*[[Cell division]]\n**[[Mitosis]]\n**[[Sitokinesis]]\n**[[Fisi binér]]\n*[[Cariology]], nyaéta ulikan ngeunaan [[inti]] sél.\n*[[Sitotoxisiti]]\n*[[Sél tutuwuhan]]\n*[[Sél sato]]\n*[[sél fungi|Sél supa]]\n*[[Sél prokariot]]\n*[[Eukariot|Sél eukariot]]\n*[[Sél manusa]]\n*[[How to prepare an onion cell slide]]\n*[[Tipe sél]]\n*[[Syncytium]]\n*[[Kultur sél]]\n\n==Rujukan==\n===Sumber===\n*{{NCBI-scienceprimer}}\n===Tumbu kaluar===\n*[http://wikibooks.org/wiki/Cell_Biology Wikibooks Cell Biology Textbook]\n*[http://www.ericdigests.org/2004-1/cells.htm Teaching about the Life and Health of Cells.]\n*[http://www.biopic.co.uk/cellcity/cell.htm The cell like a city].\n\n[[Category:Biologi sél]]\n[[Category:Biologi]]\n\n[[cy:Cell]]\n[[da:Celle (biologi)]]\n[[de:Zelle (Biologie)]]\n[[en:Cell (biology)]]\n[[es:Célula (biología)]]\n[[eo:Biologia ĉelo]]\n[[fa:یاخته]]\n[[fr:Cellule]]\n[[id:Sel (Biologi)]]\n[[is:Fruma]]\n[[it:Cellula]]\n[[la:Cellula]]\n[[ms:Sel]]\n[[nl:Cel]]\n[[ja:細胞]]\n[[ku:şane]]\n[[pl:Komórka organizmów żywych]]\n[[pt:Célula]]\n[[simple:Cell]]\n[[sv:Cell]]\n[[zh:细胞]]\n[[he:תא]]','/* Genetic material */',3,'Kandar','20050201073352','',0,0,0,0,0.816347506743,'20050228103131','79949798926647'); INSERT INTO cur VALUES (1688,0,'Adénosin_trifosfat','\'\'\'Adénosin trifosfat\'\'\' (\'\'\'ATP\'\'\') nyaéta [[nukléotida]] nu dipiwanoh na [[[biokimia]] salaku \"\'\'[[molekul|molecular]] currency\'\'\" alih [[énergi]] intrasélular; maksudna, ATP mampuh piekun nyimpen sarta ngangkut énergi kimiawi jeroeun [[sél (biologi)|sél]]. ATP ogé nyepeng peran nu penting dina sintésis [[asam nukléat]].\n\n== Sifat kimia ==\n[[Image:atp.png|thumb|right|350px|\'\'Adénosin trifosfat (ATP)\'\']]\n\nSacara kimiawi, ATP diwangun ku [[adénosin]] jeung tilu gugus [[fosfat]]. Rumus émpirisna C10H16N5O13P3, sedengkeun rumus kimiana C10H8N4O2NH2(OH)2(PO3H)3H, nu mibanda massa molekul [[1 E-25 kg|507.184]] [[unit massa atom|u]].\n\n== Fungsi ==\nMolekul ATP dipaké pikeun nyimpen énergi nu dihasilkeun tina [[réspirasi sélular]].\n\n== Posisi fosforil ==\n\nGugus fosforil mun dimimitian ti [[AMP]] kaasup fosfat alfa, béta, jeung gamma.\n\n== Sintésis ==\n[[Image:ATP_space-filling_image.jpg|200px|left]]\nATP bisa dihasilkeun tina rupa-rupa prosés sélular, hususna [[mitokondria]] dina prosés [[fosforilasi oxidatif]] dina pangaruh katalitik [[ATP sintase]] atawa mun dina tutuwuhan dina [[kloroplas]] dina prosés [[fotosintésis]].\n\n\"Béngsin\" utama pikeun sintésis ATP nyaéta [[glukosa]] jeung [[asam lemak]]. Mimitina glukosa direcah jadi [[piruvat]] na [[sitosol]]. Dua molekul ATP dihasilkeun tina unggal hiji molekul glukosa. Hambalan ahir sintésis ATP lumangsung dimna mitokondria nu bisa ngahasilkeun nepi ka 34 molekul ATP.\n\n== ATP na awak manusa ==\n\nATP na awak manusa jumlah-jamléh kira 0.1 [[mol (unit)|mol]]. Énergi nu dipikabutuh ku sél manusa pikeun [[hidrolisis]] nyaéta 200 nepi ka 300 mol ATP unggal poé. Ieu ngandung harti yén unggal molekul ATP didaur ulang 2000 nepi ka 3000 kali dina sapoéna. ATP teu bisa disimpen, sahingga sintésisna kudu reureujeungan jeung pamakéanana.\n\n== Trifosfat séjén ==\n\nSél hirup ogé boga [[nukléosida]] trifosfat \"énergi luhung\" séjén, kayaning [[guanin trifosfat]]. Antara molekul-molekul éta, énergi kalawan gampang bisa dialihkeun dina réaksi sarupa nu di[[katalis]]an ku [[nukléosida difosfokinase]]: énergi dileupaskeun nalika [[hidrolisis]] beungkeut [[fosfat énergi luhung|fosfat-fosfat]] lumangsung. Énergi ieu bisa dipaké ku rupa-rupa [[énzim]], [[protéin motor]], jeung [[protéin angkutan]] pikeun ngalaksanakeun gawé sél. Ogé, hidrolisis tadi ngahasilkeun fosfat anorganik bébas jeung [[adénin difosfat]], nu salajengna bisa direcah deui jadi ion fosfat jeung [[adénosin monofosfat]]. ATP ogé bisa langsung direcah jadi [[adénosin monofosfat]], ngahasilkeun [[pirofosfat]]. Réaksi nu ieu nguntungkeun sabab sacara éféktif prosésna teu bisa malik na [[leyuran]] [[cai]].\n\n=== Réaksi ADP jeung GTP ===\n\n:[[adénosin difosfat|ADP]] + [[GTP]] \\to ATP + [[guanosin difosfat|GDP]]\n\nKiwari aya padungdengan pikeun ngamangpaatkeun ATP pikeun sumber [[tanaga (fisika)|tanaga]] pikeun [[nanotéhnologi]] jeung cangkok. \'\'[[Artificial pacemaker]]\'\' bisa jadi teu kudu maké [[batré (listrik)|batré]].\n\n== Tempo ogé ==\n\n* [[daur asam sitrat]] (ogé katelah daur Krebs)\n* [[adénosin difosfat]] (ADP)\n* [[adénosin monofosfat siklik]] (cAMP)\n* [[fosfagén]]\n* [[Tioéster]] nu patali jeung ATP\n\n== Tumbu kaluar ==\n\n*[http://www.emc.maricopa.edu/faculty/farabee/BIOBK/BioBookATP.html ATP and biological energy]\n\n[[Category:Nukléotida]]\n\n[[da:ATP (kemi)]]\n[[de:Adenosintriphosphat]]\n[[en:adenosine triphosphate]]\n[[es:Adenosín trifosfato]]\n[[fr:Adénosine triphosphate]]\n[[nl:Adenosinetrifosfaat]]\n[[ja:アデノシン三リン酸]]\n[[pl:ATP]]','/* Sifat kimia */',3,'Kandar','20041105114005','',0,0,0,0,0.442415353117,'20041105114005','79958894885994'); INSERT INTO cur VALUES (1689,6,'Atp.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041103100202','',0,0,0,1,0,'20041105114006','79958896899797'); INSERT INTO cur VALUES (1690,0,'Mitokondria','Dina [[biologi sél]], \'\'\'mitokondria\'\'\' nyaéta hiji [[organél]] nu aya na [[sél (biologi)|sél]] kalolobaan [[eukariot]]. Mitokondria kadang didadarkeun salaku \"[[pembangkit listrik]] sélular\" sabab tujuan utamana pikeun nga[[rancang wangun]] [[adénosin trifosfat]] (ATP), nu dipikabutuh salaku sumber [[énergi]].\n\nJumlah mitokondria béda dina unggal tipe sél. [[Protozoa]] [[Trypanosome]] mibanda hiji mitokondria tunggal nu badag; sél [[ati]] [[manusa]] hijina ilaharna mibanda antara sarébu nepi ka dua rébu. Mitokondria bisa ngeusian nepi ka 25% [[sitosol]] sél.\n\n==Struktur==\n\n[[image:mitokondria.png|frame|\'\'\'Keureutan nyilang mitokondria, némbongkeun:\'\'\' (1) mémbran jero, (2), mémbran luar, (3) krista, (4) matrix]]\n\nMitokondria mibanda dua sistim mémbran: mémbran luar, nu ngabungkus organélna; sarta mémbran jero, nu karejut tulap-tilep ka lebah jero. tilepan nu ka jero disebut [[krista]]. Jumlah jeung bentuk kristae dina mitokondria béda-béda, gumantung jaringan jeung organismena. Krista ieu nyadiakeun raray mémbran nu leuwih lega.\n\n* Mémbran luar mungkus sakabéh [[organél]] sarta ngandung kanal nu dijieun tina kompléx [[protéin]] nu disebut [[porin]] tempat [[molekul]] jeung [[ion]] bisa asup jeung kaluar mitokondria. Mémbran luar diwangun ku 50%-an lipid jeung 50%-an protéin. Molekul badag teu bisa nembus mémbran ieu.\n* Mémbran jero, narilep jadi krista, mungkus \'\'[[matrix (biologi)|matrix]]\'\' (cairan jero mitokondria). Mémbran jero ngandung sababaraha kopléx protéin, kandunganana 20%-an lipid jeung 80%-an protéin. Aya \'\'stalked particles\'\' nu kapanggih na krista, nu taya lian ti molekul énzim [[ATP sintase]] nu ngahasilkeun ATP téa.\n* \'\'Rohangan antarmémbran\'\' antara dua mémbran ngandung énzim-énzim nu migunakeun ATP pikeun [[fosforilasi|mosforilasi]] [[nukléotida]] séjén nu ngatalisan réaksi séjén.\n\n\"Mitokondria\" sacara harfiah ngandung harti \'thread granule\', sakumaha katémbongna dina [[mikroskop]] cahya: struktur \'\'tiny rod-like\'\' na [[sitoplasma]] sadaya sél. Matrixna ngandung énzim [[bisa leyur]] nu [[catalisis|ngatalisan]] oxidasi [[asam piruvat|piruvat]] jeung molekul organik leutik séjénna. Sapalih ti [[daur asam sitrat|daur Krebs]] lumangsung jero mitokondria. Matrixna ogé ngandung sababaraha salinan [[DNA mitokondria]] (biasana 5-10 molekul DNA sirkular per mitokondria), [[ribosom]] husus mitokondria, [[tRNA]], sarta protéin-protéin nu dipikabutuh pikeun [[réplikasi DNA]].\n\nNalika sél meulah manéh, mitokondria ngayakeun réplikasi ku cara [[Binary fission|fisi]]. Réplikasi ogé lumangsung nalika pangabutuh énergi sél ningkat. Pikeun conto, sél panyimpen [[lemak]], nu mikabutuh énergi saeutik, mitokondriana ngan saeutik. Bandingkeun jeung sél [[otot]] nu mikabutuh énergi, mitokondriana loba pisan.\n\nProtéin mitokondria ayana di mémbran luar, mémbran jero, sarta na rohangan anrarmémbran. Runtuyan stop-transfer anchor proteins to the outer membrane. Matrix-targeting sequences [[protein targeting|target]] the protein for the mitochondrial matrix.\n\n==Konversi énergi==\nMitokondria ngarobah énergi poténtial molekul dahareun jadi ATP. Produksi ATP kahontal ku daur Krebs (tempo [[daur asam sitrat]]), [[ranté alih éléktron|alih éléktron]], jeung [[fosforilasi oxidatif]]. Mun euweuh [[oxigén]], prosés ieu moal bisa lumangsung.\n\nÉnergi tina molekul [[dahareun]] (nyaéta [[glukosa]]) dipaké pikeun ngahasilkeun molekul NADH jeung FADH2 ngaliwatan [[glikolisis]] jeung daur Krebs. Énergi ieu dialihkeun ka oxigén (O2) dina sababaraha hambalan nu ngawengku ranté alih éléktron. Kompléx protéin na mémbran jero ([[NADH déhidrogénase]], [[Koénzim Q - sitokrom c réduktase| sitokrom c réduktase]], [[sitokrom c oxidase]]) nu ngalaksanakeun alihanana migunakeun énergi nu dileupaskeun pikeun ngompa [[proton]] (H+) ngalawan [[gradién]] (konsentrasi proton na rohangan antarmémbran leuwih luhur batan na matrix). Sistim [[alih aktif]] (merlukeun énergi) ngompa proton ngalawan téndénsi fisikna (dina arah nu \"salah\") ti matrix ka rohangan antarmémbran.\n\nNalika kosentrasi proton ngaronjat na rohangan antarmémbran, a strong \'\'diffusion gradient\'\' is built up. Jalan kaluar pikeun proton ieu nya ngaliwatan kompléx \'\'[[ATP sintase]]\'\'. Ku cara ngalihkeun proton ti rohangan antarmémbran balik deui ka matrix, kompléx ATP sintase bisa nyieun [[Adénosin trifosfat|ATP]] tina ADP jeung fosfat anorganik (Pi). Prosés ieu disebut [[kémiosmosis]] nu ngarupakeun hiji conto \'\'[[facilitated diffusion]]\'\'. [[Peter Mitchell]] dipaparin [[Hadiah Nobel]] Kimia taun 1978 pikeun karyana ngeunaan kémiosmosis. Salajengna, Hadiah Nobel Kimia taun 1997 dipaparinkeun ka [[Paul D. Boyer]] jeung [[John E. Walker]] pikeun klarifikasi mékanisme peta ATP sintase.\n\n==Fungsi séjén==\n\nMitokondria mibanda sababaraha fungsi penting séjén di sagigireun produksi ATP. Rupa-rupa fungsi ieu patali jeung rupa-rupa [[kasakit mitokondria]].\n\nSababaraha fungsi mitokondria ngan lumangsung dina tipe sél nu tangtu. Pikeun conto, mitokondria na sél ati ngandung énzim-énzim nu bisa ngadétoksifikasi amonia, pamiceunan métabolisme protéin. Énzim-énzim ieu teu dijieun na mitokondria sél \'\'cardiac\'\'. \n\nMitokondria ogé maénkeun peran dina\n* [[apoptosis]]\n* [[glutamate]]-mediated excitotoxic [[neuron|neuronal]] injury\n* proliferasi sélular\n* regulation of the cellular [[redox]] state\n* sintésis [[hémé]]\n* sintésis [[stéroid]]\n* produksi panas (sangkan organisme bisa tetep haneut)\n\n==Larapan dina ngulik genetik populasi==\n\nKu sabab [[Ovum|endog]] ngancurkeun mitokondria [[spérma]] nu [[fertilization|ngabuahan]] them, the [[mitochondrial DNA]] of an individual derives exclusively from the mother. Individuals inherit the other kinds of genes and DNA from both parents jointly. Because of the unique matrilineal transmission of mitochondrial DNA, scientists in [[population genetics]] and [[evolutionary biology]] often use data from mitochondrial DNA sequences to draw conclusions about [[genealogy]] and [[evolution]]. See: [[mitochondrial Eve]].\n\nRecent studies have, however, cast doubt on this hypothesis. Kraytsberg et al. showed that mitochondrial recombination is possible in humans (\'\'[[Science (journal)|Science]]\'\' \'\'\'304\'\'\':981, May 2004, [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15143273 pubmed #15143273]).\n\n==Tiori éndosimbiotik==\n\nMitokondria mahiwal sorangan ti antara organél-organél séjén sabab ngandung [[ribosom]] sarta bahan genetikna sorangan. [[DNA]] mitokondria bentukna sirkular sarta mibanda [[sandi genetik]] béda ti eukariotik baku.\n\nThese and similar pieces of evidence motivate the endosymbiotic theory — that mitochondria originated as prokaryotic [[endosymbiont]]s. \nEssentially this widely accepted hypothesis postulates that the ancestors of modern mitochondria were independent bacteria that colonized the interior of the ancient [[common descent|precursor]] of all eukaryotic life.\n\n==Tempo ogé==\n* [[Tiori éndosimbiotik]]\n* [[Hipotésis kémiosmotik]]\n* [[Kloroplas]]\n* [[Partikel submitokondria]]\n* [[Kasakit mitokondria]]\n* [[DNA mitokondria]]\n* [[Poténsi éléktrokimia]]\n* [[Glikolisis]]\n\n{{organél}}\n{{NCBI-scienceprimer}}\n\n[[Category:Réspirasi sélular]] [[Category:Organél]]\n\n[[de:Mitochondrium]]\n[[en:mitochondrion]]\n[[es:Mitocondria]]\n[[eo:Mitokondrio]]\n[[fr:Mitochondrie]]\n[[he:מיטוכונדריה]]\n[[nl:Mitochondrion]]\n[[ja:ミトコンドリア]]\n[[pl:Mitochondrium]]\n[[pt:Mitocôndria]]\n[[sv:Mitokondrie]]','/* Use in population genetic studies */',3,'Kandar','20041109100331','',0,0,0,0,0.096075454772,'20050315112136','79958890899668'); INSERT INTO cur VALUES (1691,10,'Organél','{| style=\"margin:0 auto;\" align=\"center\" id=\"toc\"\n!align=center style=\"background:#ccccff\"| [[Organél]] [[sél (biologi)|sél]]\n|-\n|align=center style=\"font-size:90%;\"| [[Kloroplas]] | [[Mitokondria]] | [[Séntriol]] | [[Rétikulum éndoplasma]] | [[Awak Golgi]] | [[Lisosom]] | [[Miofibril]] | [[Nukleus sél|Nukleus]] | [[Peroxisom]] | [[Ribosom]] | [[Vakuol]] | [[Vésikel]]\n|}','',3,'Kandar','20041104083932','',0,0,0,1,0.385402570192,'20041104083932','79958895916067'); INSERT INTO cur VALUES (1692,0,'Agama','Sakabeh umat manusa ngagaduhan Agama boh rek Islam, Nasoro, jeng sajabana, Agama lamun di Indonesia diartikeunna kirang langkung aturan anu kudu ditaati ku sakabeh insyan / manusa jeung kedah dimumule ku anu nganut eta Agama. Di iyeu kaca nyobaan ngarewong sugan aya hartosna jeung mangfaatna keur balarea.\nDina danget-danget iyeu Agama loba anu ngarecokeun diantawisna dina widang hukum perkawina sareng waris anu teusesuai jeung hukum islam anu geus aya dina Alqur,an jeung hadis, ngan sementawis iyeu para pemikir ngadopsi kana perasaan hate dina istilah agama islam disebut Ro,yu, anu pohara jadi bahayana ka umat anu nganut agama islam diantawisna anu kurang cocok dilarapkaeun sapopoe keu urang diantawisna :\n1. Awewe bisa kawin tanpa wali \n2. Awewe bisa nalak lalaki \n3. Perkawinan poligami ditentang ku kaum awewe \n4. Bagi waris kudu sarua awewe jeung lalaki \nKumaha uarang balarea nyikapi perkawis agama iyeu anu di sodorkeun ku para pemikir aheng malah nyimpang tina tatanan / aturan agama jeung budaya Islam jeung budaya Indonesia anu kacida anehna can bisa kapikir kunu jalmi bodo saperti kuring sorangan. ngan untung undang undang Agama anu anyar di tolak ku memntri Agama, patut acungan jempol ker mentri agama anu kacida tegasna. Kuring ngarasa reueus pisan ka pamarentah anu geus merenahkeun eta undang-undang / hukum islam dina wewengkon di Indonesia jeung ngarasa daria khususnya ka MUI oge ngarasa tegas jeung teu aya tendeng aling-aling','Agama kedah di mumule',0,'202.162.212.40','20041105031551','',0,0,0,1,0.388378157461,'20041105031551','79958894968448'); INSERT INTO cur VALUES (1693,0,'Parahyangan','==Etimologi==\n\'\'\'Priangan\'\'\' atawa \'\'\'Parahyangan\'\'\' hartina tempat para \'\'rahyang atawa \'\'hyang\'\'.\n\n==Géografis==\nPriangan ayeuna nyaéta wewengkong di Propinsi Jawa Barat nu ngawengku Kabupatén [[Cianjur]], [[Bandung]], [[Sumedang]], [[Garut]], [[Tasikmalaya]], jeung [[Ciamis]], nu gedéna kira-kira sapergenep ti luas wewengkon Pulo Jawa (kurang leuwih 21.524 km persegi). Di beulah kalér watesna jeung [[Karawang]], [[Purwakarta]], [[Subang]] jeung [[Indramayu]]; beulah wétan watesna jeung [[Majaléngka]], [[Kuningan]]. Jeung [[Jawa Tengah]] diwatesanan ku [[Citanduy]]; beulah kidul diwatesan ku [[Samodra Indonésia]]; beulah kulon watesna wewengkon [[Sukabumi]] jeung [[Bogor]].\n\nLahan daérah Priangan: dataran rendah, pasir-pasir, gunung-gunung nu jumlahna kaitung loba, di antarana: [[Gunung Gedé]], [[Gunung Kancana]], [[Gunung Masigit]] (Cianjur); [[Gunung Tangkuban Parahu]], [[Gunung Burangrang]], [[Gunung Malabar]], [[Gunung Bukit Tunggul]] (Bandung); [[Gunung Tampomas]], [[Gunung Calancang]], [[Gunung Cakra Buana]] (Sumedang); [[Gunung Guntur]], [[Gunung Haruman]], [[Gunung Talagabodas]], [[Gunung Karacak]], [[Gunung Galunggung]] (Garut); [[Gunung Cupu]], [[Gunung Cula Badak]], [[Gunung Bongkok]] (Tasikmalaya); [[Gunung Syawal]] (Ciamis). Dilingkung ku gunung, Priangan kawentar subur sabab loba ogé walunganana.\n\n==Sajarah==\nDaérah Priangan mimitina disebut Tatar Ukur sabab diparéntah ku [[Dipati Ukur]]. Sanggeus Karajaan [[Sunda]] runtuh (1578/1580), éta wewengkon (iwal [[Galuh]]) mangrupa wilayah kakuasaan [[Sumedanglarang]] (nepi ka 1620). Ti taun 1621, daérah Priangan nu puseurna Sumedang, dipangaruhan ku [[Mataram]]. Numutkeun salasahiji sumber tradisional, ti saprak harita, éta wewengkon disebut Priangan. Akibat tina baruntakna Dipati Ukur ka Mataram, daerah Priangan di luar Sumedang jeung Galuh dibagi deui jadi Kabupatén [[Bandung]], [[Parakanmuncang]], jeung [[Sukapura]], dumasar kana Piagem [[Sultan Agung]] titimangsa 9 Muharam taun Alip. Ceuk F. de Haan (élmuwan Walanda), taun Alip téh sami jeung taun 1641 Maséhi, tapi aya sawatara katerangan séjén yén taun Alip idéntik jeung taun 1633 Maséhi. Salajengna, dumasar kana \'perjanjian\' Mataram jeung Kumpeni ([[VOC]]), daérah Priangan kacekel ku Kumpeni nya dibagi dua. Nu kahiji, Priangan kulon jeung tengah (taun 1677); kadua Priangan wétan (taun 1705). Dina mangsa harita, mangsa pamaréntah Hindia Walanda (1808-1942), status Priangan nyaéta karésidénan, nu munggaran ibukotana di Cianjur, salajengna ibukota karésidénan Priangan pindah ka Bandung (ti taun 1864). Ku asupna Galuh (awal abad ka-20), wilayah Karésidénan Priangan nambahan. Priangan jadi 6 kabupatén; Cianjur, Bandung, Sumedang, [[Limbangan]] (Garut), Sukapura (Tasikmalaya), jeung Galuh (Ciamis).','',3,'Kandar','20050315075129','',0,0,1,0,0.121961615571,'20050315084342','79949684924870'); INSERT INTO cur VALUES (1694,14,'Kimia','\'\'\'Kimia\'\'\' ngarupakeun [[élmu]] ngeunaan struktur, sipat, wangunan, jeung [[réaksi kimiawi|réaksi]] [[unsur kimiawi|unsur]] jeung [[sanyawa kimiawi]].\n{{artikelutama}}\n[[Category:Sains]]\n[[Category:Élmu alam]]','',20,'DiN','20050303194342','',0,0,0,0,0.886844611208,'20050315142334','79949696805657'); INSERT INTO cur VALUES (1695,0,'Glikolisis','\'\'\'Glikolisis\'\'\' ngarupakeun awal [[alur métabolik]] [[katabolisme]] [[karbohidrat]]. Bentuk glikolisis nu pangilaharna dipikawanoh nyaéta alur [[Gustav Embden|Embden]]-[[Otto Meyerhof|Meyerhof]]. Istilah glikolisis bisa ogé ngawengku alur pilihan séjén kayaning alur Entner-Doudoroff. Ngan, \'\'\'glikolisis\'\'\' nu dipedar di dieu salaku sinonim pikeun [[alur Embden-Meyerhof]]. \n\nGlikolisis ngarupakeun prosés universal nalika sagala rupa sél nurunkeun énergi ti gula. Najan lain nu pang éfisiénna, glikolisis perlu sabab anaérob; nyéta, teu merlukeun [[oxigén]].\n\n==Kaluaran==\nGlikolisis ngarobah hiji [[molekul]] [[glukosa]] jadi dua molekul [[piruvat]] sarta \"ékivalén pangréduksi\" (\'\'reducing equivalents\'\') dina ujud [[koénzim]] [[NADH]].\n\nRéaksi umum glikolisis:\n\n:Glukosa + 2 NAD+ + 2 ADP + 2 Pi → 2 NADH + 2 piruvat + 2 ATP + 2 H2O + 4 H+\n\nJadi, for simple fermentations, métabolisme hiji molekul glukosa ngahasilkeun dua molekul [[Adénosin trifosfat|ATP]]. Cells performing [[cellular respiration|respiration]] synthesize much more ATP but this is not considered part of glycolysis. Eukaryotic aerobic respiration produces an additional 34 molecules (approximately) of ATP for each glucose molecule oxidized.\n\n==Location==\nIn [[eukaryote]]s glycolysis takes place within the [[cytosol]] of the [[cell (biology)|cell]] (as opposed to the [[mitochondrion|mitochondria]], where reactions more closely connected to [[aerobic organism|aerobic]] metabolism occur). Glucose gets into the cell through [[facilitated diffusion]]. In some tissues, skeletal muscle for instance, [[insulin]] stimulates this process.\n\n==Follow up==\nThe ultimate fate of the pyruvate and [[NADH]] produced in glycolysis depends upon the organism and the conditions, most notably the presence or absence of [[oxygen]] or other external electron acceptors. \n\nIn [[fermentation]], the pyruvate and [[NADH]] are anerobically metabolized to yield any of a variety of products. For example, the [[bacteria]] involved in making yogurt simply reduce the pyruvate to [[lactic acid]], whereas [[yeast]] produce [[ethanol]] and [[carbon dioxide]]. \n\nIn [[aerobic organism]]s, the pyruvate typically enters the [[citric acid cycle]], and the [[NADH]] is ultimately oxidized by oxygen during [[oxidative phosphorylation]]. Although human metabolism is primarily aerobic, under anerobic conditions, for example in over-worked muscles that are starved for oxygen, pyruvate is converted to lactate, as in many microorganisms.\n\n==Evolution==\nGlycolysis is the only metabolic pathway common to nearly all living organisms, suggesting great antiquity; it may have originated with the first [[prokaryote]]s, 3.5 billion years ago or more.\n\n==Pathway==\nThe first step in glycolysis is [[phosphorylation]] of glucose by [[hexokinase]] (in liver the most important hexokinase is [[glucokinase]] which has slightly different properties than the hexokinases in most other cells). This reaction consumes 1 [[Adenosine triphosphate|ATP]] molecule, but the energy is well spent: although the [[plasma membrane|cell membrane]] is permeable to glucose because of the presence of glucose transport proteins, it is impermeable to glucose 6-phosphate. Glucose 6-phosphate is then rearranged into [[fructose]] 6-phosphate by phosphoglucose [[isomerase]]. (Fructose can also enter the [[glycolytic pathway]] at this point.) \n\n[[Phosphofructokinase]]-1 then consumes 1 ATP to form fructose 1,6-bisphosphate. The energy expenditure in this step is justified in 2 ways: the glycolytic process (up to this step) is now irreversible, and the energy supplied to the molecule allows the ring to be split by [[aldolase]] into 2 molecules - dihydroxyacetone phosphate and glyceraldehyde 3-phosphate. (Triosephosphate isomerase converts the molecule of dihydroxyacetone phosphate into a molecule of glyceraldehyde 3-phosphate.) Each molecule of glyceraldehyde 3-phosphate is then oxidized by a molecule of NAD+ in the presence of glyceraldehyde 3-phosphate dehydrogenase, forming 1,3-bisphosphoglycerate.\n\nIn the next step, phosphoglycerate kinase generates a molecule of ATP while forming 3-phosphoglycerate. At this step glycolysis has reached the break-even point: 2 molecules of ATP were consumed, and 2 new molecules have been synthesized. This step, one of the two substrate-level phosphorylation steps, requires ADP; thus, when the cell has plenty of ATP (and little ADP) this reaction does not occur. Because ATP decays relatively quickly when it is not metabolized, this is an important regulatory point in the glycolytic pathway.\nPhosphoglyceromutase then forms 2-phosphoglycerate; enolase then forms phosphoenolpyruvate; and another substrate-level phosphorylation then forms a molecule of pyruvate and a molecule of ATP by means of the enzyme [[pyruvate kinase]]. This serves as an additional regulatory step.\n\nAfter the formation of fructose 1,6 bisphosphate, many of the reactions are energetically unfavorable. The only reactions that are favorable are the 2 substrate-level phosphorylation steps that result in the formation of ATP. These two reactions pull the glycolytic pathway to completion.\n\n==Etymology==\nFrom [[Greek language|Greek]] \'\'glyk\'\' meaning sweet and \'\'lysis\'\' meaning dissolving.\n\n==tempo ogé==\n*[[Glukonéogenesis]]\n*[[Daur Krebs]]\n\n==External links==\n*[http://nist.rcsb.org/pdb/molecules/pdb50_1.html The Glycolytic enzymes in Glycolysis: Protein Data Bank]\n*[http://www.wdv.com/CellWorld/Biochemistry/Glycolytic Glycolytic cycle with animations]\n\n[[Category:Cellular respiration]]\n\n[[de:Glykolyse]]\n[[ja:解糖系]]\n[[es:glucólisis]]\n[[eo:glikolizo]]\n[[en:glycolysis]]','/* See also */',3,'Kandar','20041109102747','',0,0,0,0,0.223562981106,'20041109102747','79958890897252'); INSERT INTO cur VALUES (1696,0,'Ngaran_anak_sasatoan','Dina basa Sunda, aya sesebutan husus pikeun rupa-rupa anak sasatoan. Di antarana,\n*[[anak]] [[anjing]] = kirik/kicik\n*anak [[bagong]] = begu\n*anak [[bandeng]] = nanar/nénér\n*anak [[banteng]] = bangkanang\n*anak [[bangbung]] = kuuk\n*anak [[bangkong]] = buruy\n*anak [[belut]] = kuntit\n*anak [[bogo]] = cingok\n*anak [[boncél]] = bayong\n*anak [[buhaya]] = bocokok\n*anak [[deleg|deleg/gabus]] = boncél/kocolan/kokocolan\n*anak [[éntog]] = titit\n*anak [[embé]] = cémé\n*anak [[gajah]] = ménél\n*anak [[hayam]] = ciak/pitik\n*anak [[japati]] = piyik\n*anak [[keuyeup]] = boncérét\n*anak [[kuda]] = belo\n*anak [[kukupu]] = hileud\n*anak [[kutu]] = kuar\n*anak [[lancah]] = aom\n*anak [[lauk]] = kebul/burayak\n*anak [[lélé]] = nanahaon\n*anak [[lubang]] = leungli\n*anak [[maung]] = juag/aum\n*anak [[meri]] = titit\n*anak [[monyét]] = begog\n*anak [[munding]] = énéng\n*anak [[reungit]] = utek-utek\n*anak [[sapi]] = pedet\n*anak [[ucing]] = bilatung','',3,'Kandar','20041106061234','',0,0,0,0,0.886128296557,'20041106061234','79958893938765'); INSERT INTO cur VALUES (1697,0,'Sajak','Cacarakan\nsajak\nIndung\n\nIndung kuring anu dipikacinta\nkuring ngahaturkeun nuhun pisan\njasa indung nu dibikeun\nkuring jadi bisa nincak ieu dunya\nkuring jadi nempo kaayaanana\nhanjakal kuring can bisa \nmulang tarima ka indung\nkuring ngan bisa nyiksa\nkuring ngan bisa jadi kapusing\ntaya maksud kuring\nnganyenyeri nu jadi indung\nhampura... hampura kuring indung','',0,'202.143.100.65','20041105235155','',0,0,0,1,0.092499234757,'20041105235155','79958894764844'); INSERT INTO cur VALUES (1699,6,'Peta_tilu_karajaan_koréa.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041106052740','',0,0,0,1,0,'20041107112202','79958893947259'); INSERT INTO cur VALUES (1700,0,'Tilu_Karajaan_Koréa','{| border=\"1\" cellpadding=\"2\" cellpadding=\"2\" cellspacing=\"0\" align=\"right\"\n! colspan=\"2\" bgcolor=\"#FFCCCC\" | Tilu Karajaan Koréa\n|-\n| colspan=\"2\" | [[Image:Peta tilu karajaan koréa.png|250px]]\n|-\n| colspan=\"2\" | Peta Tilu Karajaan Koréa ahir abad ka-5\n|-\n! colspan=\"2\" style=\"background:#ffdead;\" | Ngaran Koréa\n|-\n| width=\"150\" | [[Révisi Romanisasi Koréa|Révisi Romanisasi]]\n| Samguk\n|-\n| width=\"150\" | [[McCune-Reischauer]]\n| Samguk\n|-\n| width=\"150\" | [[Hangul]]\n| 삼국\n|-\n| width=\"150\" | [[Hanja]]\n| 三國\n|}\n\'\'\'Tilu Karajaan Koréa\'\'\' ngarupakeun karajaan [[Goguryeo]], [[Baekje]], jeung [[Silla]], nu ngawasa [[Bojong Koréa]] jeung [[Manchuria]] salila dalapan abad nepi ka abad ka-7 M. Karajaan-karajaan séjén nu leuwih leutik aya saméméh nepi ka mangsana Tilu Karajaan, kayaning [[Gaya]], [[Dongye]], [[Okjeo]], [[Fuyu|Buyeo]], [[Usan]], [[Tamna]], jsb.\n\nMangsa tradisional geus aya ti [[57 BC]], nalika karajaan Saro (salajengna Silla) di béh kidul-wétaneun bojong meunangkeun otonomi ti kakawasaan [[dinasti Han]] [[Cina]]. Goguryeo di béh kalér jeung kidul [[walungan Yalu]] (na basa Koréa walungan Amnok) merdika ti Cina dina [[37 BC]]. Dina [[18 BC]], dua pangéran Goguryeo nu kawarisan kakawasaan, ngadegkeun Beaekje di kidul-kuloneun bojong (ayeuna Seoul), nu dayeuhna Ungjin (ayeuna Gongju atawa Chongju) salajengna Sabi (ayeuna Puyo) di kidul-kuloneun Seoul. Karajaan Gaya misah ti Beakje dina [[abad ka-1]] M.\n\nPamungkasan dinasti Han, awal [[abad ka-3]], ngantepkeun tilu Karajaan éta terus tumuwuh. Tiluanana mibanda budaya nu sarua. [[Confucianisme]] sumebar di masarakat kelas luhur Koréa ti [[abad ka-1]], ngan kadieunakeun mah kalindih ku [[Buddhisme]] sagemblengna.\n\nGoguryeo, nu pangbadagna ti nu tilu, boga dua ibukota piligenti. Nangnang (ayeuna [[Pyongyang]]) jeung Kungae peuntaseun walungan Yalu. At the beginning the state located at the border of China, it conquered little by little vast territories of [[Manchuria]]. and finally chased Chinese from Nangnang in [[313]]. The cultural influence of Chinese remained till Buddhism was adopted as the official religion in [[372]].\n\nDina [[abad ka-4]] Baekje jaya kumawasa sarta ngungkulan ampir satengah ti bojongna, nyéta bojong beulah kidul.\n\nRenaming Silla in [[503]], it is known the kingdom of Silla absorbed the whole kingdom of Kaya or Gaya on their border in the first half of the [[4th Century]]. Ibukota Silla nyaéta Gumsong (ayeuna Gyeongju atawa [[Kyongju]]). Buddhisme dijadikeun ageman resmi taun [[528]].\n\nKu ayana kongsi jeung [[dinasti Tang]] Cina, Silla meruhkeun Goguryeo taun [[668]], satutasna ngawasa Baekje taun [[660]], thus ushering in the [[Unified Silla]] period and effectively putting an end to the \"Three Kingdoms.\"\n\nNgaran \"Samguk\", atawa \"Tilu Karajaan\" dipaké dina naskah kuna Koréa \'\'[[Samguk Sagi]]\'\' jeung \'\'[[Samguk Yusa]].\'\'\n\n==Tempo ogé==\n*[[Pangawasa Koréa]]\n*[[Daptar jejer nu patali jeung Koréa]]\n\n[[Category:Sajarah Koréa]]\n\n\n[[als:Drei Reiche von Korea|Drüü Choreanischi Chönigrych]]\n[[ang:Þréo Coreaniscu Cynerícu]]\n[[bg:Три царства (Корея)]]\n[[de:Drei Reiche von Korea]]\n[[en:Three Kingdoms of Korea]]\n[[fr:Trois Royaumes de Corée]]\n[[fy:Trije keninkryken fan Korea]]\n[[he:שלושת הממלכות של קוריאה]]\n[[it:Tre regni di Corea]]\n[[ko:삼국시대]]\n[[la:Tria Regna Coreae]]\n[[lb:Dräi Kinnekräicher vu Korea]]\n[[lv:Korejas trīs karaļvalstis]]\n[[ms:Tiga Kerajaan Korea]]\n[[nl:Drie Koninkrijken van Korea]]\n[[nv:Kolíya T%C3%A1%C3%A1%27 Bik%C3%A9yah%C4%85%CC%81%C4%85]]\n[[ro:Cele Trei Regate ale Coreei]]\n[[simple:Three Kingdoms of Korea]]\n[[fi:Korean kolme kuningaskuntaa]]\n[[sk:Tri královstvá (Kórea)]]\n[[sv:Koreas tre kungariken]]\n[[tl:Tatlong Kaharian ng Korea]]\n[[zh:朝鲜三国时代]]','',0,'80.78.69.178','20041107112201','',0,0,0,0,0.626373244741,'20041107112201','79958892887798'); INSERT INTO cur VALUES (1701,0,'Johann_Sebastian_Bach','\'\'\'Johann Sebastian Bach\'\'\' ([[21 Maret]] [[1685]]–[[28 Juli]] [[1750]]) ngarupakeun saurang [[komposer]] jeung [[organ (musik)|organis]] Jérman mangsa [[Baroque]], nu geus diaku salaku salasahiji lulugu komposer sapanjang jaman. Karyana, nu jero ajén kaélmuanana, kamampuhan téknisna, sarta kaéndahan artistikna, geus jadi inspirasi pikeun ampir sakabéh musisi dina tradisi [[Éropah]], ti [[Wolfgang Amadeus Mozart|Mozart]] nepi ka [[Arnold Schoenberg|Schoenberg]]. \n\n[[Image:JSBach.jpg|thumb|250px|right|Johann Sebastian Bach]]\n\n== Formative years ==\nJ. S. Bach was born in [[Eisenach]], [[Germany]], in [[1685]] and died in 1750 at the age of 65. His father, [[Johann Ambrosius Bach]], was the town piper in [[Eisenach]], a post that entailed organizing all the secular music in town as well as participating in church music at the direction of the church organist, and his uncles were also all professional musicians ranging from church organists and court chamber musicians to composers, although Bach would later surpass them all in his art. In an era when sons were expected to assist in their fathers\' work, we can assume J. S. Bach began copying music and playing various instruments at an early age. \n\nBach\'s mother died when he was still a young boy and his father suddenly passed away when J. S. Bach was 9, at which time J. S. Bach moved in with his older brother [[Johann Christoph Bach]], who was the organist of [[Ohrdruf]] in Germany. While in his brother\'s house, J. S. Bach continued copying, studying, and playing music. According to one popular legend of the young composer\'s curiosity, late one night, when the house was asleep, he retrieved a manuscript (which may have been a collection of works by Johann Christoph\'s former mentor, [[Johann Pachelbel]]) from his brother\'s music cabinet and began to copy it by the moonlight. This went on nightly until Johann Christoph heard the young Sebastian playing some of the distinctive tunes from his private library, at which point the elder brother demanded to know how Sebastian had come to learn them.\n\n[[Image:Young Bach2.jpg|left|thumb|200px|Bach as a young man]]\n\nIt was at Ohrdruf that Bach began to learn about [[organ (music)|organ]] building. The Ohrdruf church\'s instrument, it seems, was in constant need of minor repairs, and young J. S. Bach was often sent into the belly of the old organ to tighten, adjust, or replace various parts. Realizing that in the seventeenth and eighteenth centuries the church organ, with its moving bellows, manifold stops, and complicated mechanical linkages from the keys and pedals to the many actual pipes, was the most complex machine in any European town, we can imagine that Sebastian may have been awed by it much as modern boys are fascinated by cars, trucks, and planes. This hands-on experience with the innards of the instrument would provide a unique [[counterpoint]] to his unequalled skill at playing the instrument; J. S. Bach was equally at home talking with organ builders and performers. \n\nWhile in school and as a young man, Bach\'s curiosity compelled him to seek out great organists of Germany such as [[Georg Böhm]], [[Dietrich Buxtehude]] and [[Johann Adam Reinken]], often taking journeys of considerable length to hear them play. He was also influenced by the work of [[Nicholas Bruhns]]. Shortly after graduation (Bach completed Latin school when he was 18, an impressive accomplishment in his day, especially considering that he was the first in his family to finish school), Bach took a post as organist at [[Arnstadt]] in Germany in [[1703]]. He apparently felt cramped in the small town and began to seek his fortune elsewhere. Owing to his virtuosity, he was soon offered a more lucrative organist post in [[Muhlhausen]]. Some of Bach\'s earliest extant compositions date to this period (including, according to some scholars, his famous [[Toccata and Fugue in D Minor]]), but owing to the general immaturity of this \"early\" Bach music, much of the music Bach wrote during this time has unfortunately been lost.\n\n== Professional life ==\nStill not content as organist of Muhlhausen, in [[1708]], Bach took a position as court organist and [[concert master]] at the ducal court in [[Weimar, Germany|Weimar]]. Here he had opportunity to not only play the organ but also compose for it and play a more varied repertoire of concert music with the dukes\' ensemble. A devotee of [[counterpoint|contrapuntal]] music, Bach\'s steady output of [[Fugue (music)|fugue]]s begins in Weimar. The best known example of his fugal writing is probably \'\'[[The Well-Tempered Clavier]]\'\', which comprises 48 preludes and fugues, two for each major and minor key, a monumental work not only for its masterful use of counterpoint but also for exploring, for the first time, the full glory of keys--and the means of expression made possible by their slight differences from each other--available to keyboard musicians when their instruments are tuned according to [[Andreas Werckmeister]]\'s system of [[well temperament]] or similar system.\n\nAlso during his tenure at Weimar, Bach began work on the Orgelbüchlein for Wilhelm Friedemann. This \"little book\" of organ music contains traditional [[Lutheran]] church hymns harmonized by Bach and compiled in a way to be instructive to organ students. This incomplete work introduces two major themes into Bach\'s corpus: Firstly, his dedication to teaching, and secondly, his love of the traditional [[chorale]] as a form and source of inspiration. Bach\'s dedication to teaching is especially remarkable. There was hardly any period in his life when he did not have a full-time apprentice studying with him, and there were always numerous private students studying in Bach\'s house, including such 18th century notables as [[Johann Friedrich Agricola]]. Still today, students of nearly every instrument encounter Bach\'s works early and revisit him throughout their careers.\n\n[[image:Jsbach3.jpg|right|framed|The St. Thomas church in Leipzig]]\n\nSensing increasing political tensions in the ducal court of Weimar, Bach began once again to search out a more stable job conducive to his musical interests. Prince Leopold of Anhalt-Cöthen hired Bach to serve as his [[Kapellmeister]], that is, director of music. Prince Leopold, himself a musician, appreciated Bach\'s talents, compensated him well, and gave him considerable latitude in composing and performing. However, the prince was [[Calvinist]] and did not use elaborate music in his worship, so that most of Bach\'s work from this period is secular in nature. The [[Brandenburg concerti]], as well as many other instrumental works, including the [[suite]]s for solo cello, the sonatas and [[partita]]s for solo [[violin]], and the orchestral suites, date to this period. \n\nIn [[1723]], J. S. Bach was appointed [[Cantor]] and Musical Director of [[St. Thomas church]] in [[Leipzig]] in Germany. This post required him to not only instruct the students of the St. Thomas school in singing but also to provide weekly music at the two main churches in Leipzig. Rising above and beyond the call of duty, Bach endeavored to compose a new church piece, or [[cantata]], every week. This challenging schedule, which basically amounted to writing an hour\'s worth of music every week, in addition to his more menial duties at the school, produced some genuinely sublime music, most of which has been preserved. Most of the cantatas from this period expound upon the Sunday readings from the Bible for the week in which they were originally performed; some were written using traditional church hymns, such as \'\'Wachet auf! Ruft uns die Stimme\'\' and \'\'Nun komm, der Heiden Heiland\'\', as inspiration for the music. \n\nOn holy days such as [[Christmas]], [[Good Friday]], and [[Easter]], Bach produced cantatas of particular brilliance, most notably the [[Magnificat]] for Christmas and [[St. Matthew Passion (Bach)|St. Matthew Passion]] for Good Friday. The composer himself considered the monumental St. Matthew Passion among his greatest masterpieces; in his correspondence, he referred to it as his \"great Passion\" and carefully prepared a calligraphic manuscript of the work, which required every available musician in town for its performance. Bach\'s representation of the essence and message of Christianity in his religious music is considered by many to be so powerful and beautiful that in Germany he is sometimes referred to as the Fifth Evangelist.\n\n== Family life ==\nBach married his second cousin, Maria Barbara Bach, on [[October 17]], [[1707]] after receiving a small inheritance. They had 7 children, 4 of whom survived to adulthood. Little is known of Maria Barbara. She died suddenly on [[July 7]], [[1720]] while Bach was travelling with Prince Leopold.\n\nWhile at [[Cöthen]], Bach met Anna Magdalena Wilcke, a young [[soprano]]. They married on [[December 11]], [[1721]]. Despite the age difference (she was 17 years his junior), the couple seem to have had a very happy marriage. Anna supported Johann\'s composing (many final scores are in her hand) while he encouraged her singing. Together they had 13 children.\n\nAll the Bach children were musically inclined, which must have given the aging composer much pride. His sons [[Wilhelm Friedemann Bach]], [[Johann Gottfried Bernhard Bach]], [[Johann Christoph Friedrich Bach]], [[Johann Christian Bach]], and [[Carl Philipp Emanuel Bach]] all became accomplished musicians, with C. P. E. Bach winning the respect of [[Wolfgang Amadeus Mozart]]. Although the barriers to women having professional careers were great, all of Bach\'s daughters most likely sang and possibly played in their father\'s ensembles. The only one of the Bach daughters to marry, Elisabeth Juliana Friederica, choose as husband Bach\'s student Johann Christoph Altnickol. Most of the music we have from Bach was passed on through his children, who preserved much of what C. P. E. Bach called the \"Old Bach Archive\" after his father\'s death. \n\nAt Leipzig, Bach seems to have fit in amongst the professoriate of the university, with many professors standing as god-parents for his children, and some of the university\'s men of letters and theology providing many of the [[libretto]]s for his cantatas. In this last capacity Bach enjoyed a particularly fruitful relationship with the poet [[Picander]]. Sebastian and Anna Magdalena also welcomed friends, family, and fellow musicians from all over Germany into their home; court musicians at Dresden and Berlin as well as musicians including [[George Philipp Telemann]] (one of Carl Philipp Emanuel\'s godfathers) made frequent visits to Bach\'s house and may have kept up frequent correspondence with him. Interestingly, [[George Friedrich Handel]], who was born in the same year as Bach, made several trips to Germany, but Bach was unable to meet him, a fact he regretted. \n\n[[Image:Jsbach.jpg|right|170px|thumb|Johann Sebastian Bach]]\n\n== Later life and legacy ==\nHaving spent much of the [[1720]]s composing weekly cantatas, Bach assembled a sizable repertoire of church music that, with minor revisions and a few additions, allowed him to continue performing impressive Sunday music programs while pursuing other interests in secular music, both vocal and instrumental. Many of these later works were collaborations with Leipzig\'s [[Collegium Musicum]], but some were increasingly introspective and abstract compositional masterpieces that represent the pinnacle of Bach\'s art. These erudite works start with the four volumes of his Clavier-Übung (\"Keyboard Practice\") a set of keyboard works to inspire and challenge organists and lovers of music that includes the 6 Partitas for keyboard (Vol. I), the Italian Concerto, the French Overture (Vol. II), and the [[Goldberg variations]] (Vol. IV). \n\nAt the same time, Bach wrote a complete [[Mass in B Minor (Bach)|Mass in B Minor]], which incorporated newly composed movements with portions from earlier works. Although the mass was never performed during the composer\'s lifetime, it is considered to be among the greatest of his choral works.\n\nAfter meeting King [[Frederick II of Prussia]] in [[Potsdam]] in [[1747]], who played a [[theme (music)|theme]] for Bach and challenged the famous musician to improvise a six-part [[fugue]] based on his theme, Bach presented the king with a [[Musical Offering]] including several fugues and canons based on the \"royal theme.\" Later, using a theme of his own design, Bach produced \'\'[[The Art of Fugue]]\'\'. These 14 fugues (called Contrapuncti by Bach), are all based on the same theme, demonstrating the versatility of a simple melody. During his life time he composed over 1,000 pieces. \n\nJohann Sebastian Bach\'s contributions to music, or to borrow a term popularized by his student Lorenz Christoph Mizler, \"musical science\" are frequently compared to the \"original geniuses\" of [[William Shakespeare]] in English literature and [[Isaac Newton]] in physics.\n\nJohann Sebastian Bach died in 1750.\n\n== The BWV numbering system==\n[[Image:BWV1001-cropped.jpg|right|thumb|200px|Violin Sonata #1 in G minor (BWV 1001) in Bach\'s handwriting]]\nJohann Sebastian Bach pieces are indexed with BWV numbers, where BWV is \'\'Bach Werke Verzeichnis\'\' . The catalog was compiled by Wolfgang Schmieder and the BWV numbers are sometimes referred to as Schmieder Numbers. An obsolete system uses S, instead of BWV, for Schmieder.\n\n== Further reading ==\n*The early biography by [[Johann Nikolaus Forkel]], from 1808, reprinted in \'\'The Bach Reader\'\' (W. W. Norton, 1966), is of considerable value, as Forkel was able to correspond directly with people who had known Bach.\n*The \'\'Bach Reader\'\', edited by [[Hans T. David]] and [[Arthur Mendel]], also contains much other interesting material, such as a large selection of contemporary documents, some by Bach himself.\n*An early groundbreaking study of Bach\'s life and music is by Philipp Spitta: \'\'Johann Sebastian Bach: Sein Leben etc...\'\', Dover, 1951, ISBN 0-486-22278-0\n*Another famous study of his life and music is \'\'J. S. Bach\'\' by the versatile scholar and organist [[Albert Schweitzer]], in two volumes (1908).\n*[[Christoph Wolff]]\'s more recent works (\'\'Johann Sebastian Bach: The Learned Musician\'\' and \'\'Johann Sebastian Bach: Essays\'\'), include a discussion of Bach\'s \"original genius\" in German aesthetics and music.\n*\'\'[[Gödel, Escher, Bach]]\'\'\n\n==See also==\n*[[Johann Sebastian Bach/Compositions|Compositions]]\n*[[Johann Sebastian Bach/Recordings|Recordings]]\n*[[Bach family]]\n\n==External links==\n{{Wikisource author}}\n* [http://www.mckeeth.org/wikilinks/bach1911.html 1911 Encyclopedia Britannica entry]\n* [http://www.jsbach.org/ J.S. Bach Home Page]\n* [http://www.bach-leipzig.de/ Bach-Archiv Leipzig]\n* [http://www.music.qub.ac.uk/~tomita/bachbib J. S. Bach bibliography on the web]\n* [http://jan.ucc.nau.edu/~tas3/life.html J. S. Bach\'s Education and Career]\n* [http://www.bach-cantatas.com/ J.S.Bach cantatas] extensive references including cantatas by BWV number.\n* [http://jan.ucc.nau.edu/~tas3/wtc.html Online recordings of Bach\'s Well-Tempered Clavier]\n* [http://hebb.mit.edu/FreeMusic/Bach/ Free recordings of Bach\'s Cantata 140 and other audio examples]\n* [http://hebb.mit.edu/FreeMusic/Pandora/vorbis/piano/Hokanson/Master_Works/index.html Free recordings of Bach\'s 15 Three-Part Inventions (Sinfonias) for keyboard]\n\n[[ca:Johann Sebastian Bach]] [[cy:Johann Sebastian Bach]] [[da:Johann Sebastian Bach]] [[de:Johann Sebastian Bach]] [[en:Johann Sebastian Bach]] [[et:Johann Sebastian Bach]] [[es:Johann Sebastian Bach]] [[eo:Johann Sebastian BACH]] [[fr:Johann Sebastian Bach]] [[ko:요한 제바스티안 바흐]] [[it:Johann Sebastian Bach]] [[he:יוהאן סבסטיאן באך]] [[ka:იოჰან სებასტიან ბახი]] [[la:Iohannes Sebastianus Bach]] [[lb:Johann Sebastian Bach]] [[ms:Johann Sebastian Bach]] [[nah:Johann Sebastian Bach]] [[nl:Johann Sebastian Bach]]\n[[ja:ヨハン・セバスティアン・バッハ]] [[no:Johann Sebastian Bach]] [[pl:Jan Sebastian Bach]]\n[[pt:Johann Sebastian Bach]] [[ro:Johann Sebastian Bach]] [[simple:Johann Sebastian Bach]] [[sl:Johann Sebastian Bach]] [[fi:Johann Sebastian Bach]] [[sv:Johann Sebastian Bach]]\n[[zh:约翰·塞巴斯蒂安·巴赫]]\n\n[[Category:medal 1685]] [[Category:pupus 1750]] [[Category:komposer Baroque]] [[Category:Lutherans]] [[Category:Komposer klasik]]','',3,'Kandar','20041106070958','',0,0,0,1,0.930794671146,'20041106070958','79958893929041'); INSERT INTO cur VALUES (1702,0,'Asia','{{otheruses}}\n[[Image:Fotograf_satelit_asia.jpg|thumb|300px|Gambar komposit satelit Asia]]\n[[Benua]] \'\'\'Asia\'\'\' is defined by subtracting [[Europe]] and [[Africa]] from the great land mass of [[Africa-Eurasia]]. The boundaries are vague, especially between Asia and Europe: Asia and Africa meet somewhere near the [[Suez Canal]]. The boundary between Asia and Europe runs via the [[Dardanelles]], the [[Sea of Marmara]], the [[Bosphorus]], the [[Black Sea]], the ridges of the [[Caucasus]] (according to others, through the [[Kuma-Manych Depression]]), the [[Caspian Sea]], the [[Ural River]] (according to others, the [[Emba River]]) and the [[Ural Mountains]] to [[Novaya Zemlya]]. About 60% of the world\'s population live in Asia. See also [[Eurasia]].\n\nThe region of \'\'\'Asia\'\'\' is the continent of Asia plus nearby [[island]]s in the [[Indian Ocean|Indian]] and [[Pacific Ocean]]s.\n\n==Subwilayah==\n[[Image:Peta_Asia.png|thumb|Peta Asia]]\n\nSakumaha nu geus disebutkeun yén Asia bisa dianggap salaku subwilayah [[Eurasia]] nu leuwih gedé. Pikeun babagian nurutkeun istilah ieu, tempo [[Eurasia Kalér]] jeung [[Eurasia Tengah]].\n\nAsia mindeng dibagi jadi sababaraha subwilayah:\n\n===[[Asia Kalér]]===\nIstilah ieu jarang dipaké ku ahli géografi, tapi biasana nujul ka bagian Asia wewengkon [[Rusia]], nu ogé katelah [[Sibéria]]. Kadang nagara-nagara Asia di béh kalér kayaning [[Kazakhstan]] ogé kaasup Asia Kalér.\n\n===[[Asia Tengah]]===\nTaya konsénsus There is no absolute consensus in the usage of this term. Usually, Central Asia includes:\n* the [[Central Asian Republics]] of [[Kazakhstan]], [[Uzbekistan]], [[Tajikistan]], [[Turkmenistan]] and [[Kyrgyzstan]].\n* [[Afghanistan]], [[Mongolia]], and the western regions of [[China]] are also sometimes included.\n\n===[[Asia Wétan]]===\nThis term includes:\n* The [[Pacific Ocean|Pacific]] islands of [[Taiwan]] and [[Japan]].\n* [[North Korea|North]] and [[South Korea]] on the [[Korean Peninsula]].\n* [[China]], but sometimes only the eastern regions\n\nSometimes the nation of [[Mongolia]] is also included with East Asia.\n\n===[[Asia Kidul-wétaneun]]===\nThis region contains the [[Malay Peninsula]], [[Indochina]] and islands in the [[Indian Ocean]] and [[Pacific Ocean]]. The countries it contains are:\n\n* In [[Mainland Southeast Asia]], the countries of [[Myanmar]], [[Thailand]], [[Laos]], [[Cambodia]] and [[Vietnam]]. \n\n* In [[Maritime Southeast Asia]], the countries of [[Malaysia]], the [[Philippines]], [[Singapore]], [[Indonesia]], [[Brunei]] and [[East Timor]].\n\nThe country of [[Malaysia]] is divided in two by the [[South China Sea]], and thus has both a mainland and island part.\n\n===[[Asia Kidul]]===\nSouth Asia is also referred to as the [[Indian Subcontinent]]. It includes:\n* the [[Himalayan States]] of [[India]], [[Pakistan]], [[Nepal]], [[Bhutan]] and [[Bangladesh]]\n* the [[Indian Ocean]] nations of [[Sri Lanka]] and the [[Maldives]].\n\n===[[Asia Kidul-kuloneun]]===\nIt can also be called the [[Middle East]], although that term is occasionally used to also refer to countries in [[North Africa]]. Southwest Asia can be further divided into:\n\n* [[Anatolia]], which includes the nation of [[Turkey]] \n* The island nation of [[Cyprus]] in the [[Mediterranean Sea]].\n* The [[Levant]] or [[Near East]], which includes [[Syria]], [[Israel]], [[Jordan]], [[Lebanon]] and [[Iraq]].\n* The [[Arabian peninsula]], including [[Saudi Arabia]], [[United Arab Emirates]], [[Bahrain]], [[Qatar]], [[Oman]], [[Yemen]] and occasionally [[Kuwait]].\n* The [[Caucasus]] region, including the nations of [[Georgia (country)|Georgia]], [[Azerbaijan]] and [[Armenia]].\n* The [[Iranian Plateau]], containing [[Iran]] and parts of other nations.\n\nAlso see [[Gulf States]], for a different grouping involving several of the above countries.\n\n==Population density== \n\nThis is a list of countries/dependencies by [[population density]] in inhabitants/km2.\n\nUnlike the figures in the country articles, the figures in this table are based on areas including inland water bodies (lakes, reservoirs, rivers) and may therefore be lower here.\n\nThe whole of Russia, Egypt, and Turkey are referred to in the table, although they are only partly in Asia. Georgia, Armenia and Azerbaijan have been included, although they can also be considered part of Europe.\n\nWest Bank and Gaza Strip are not listed separately, but combined as Palestinian territories.\n\n{| style=\"text-align:right\";\n|- bgcolor=\"#F0EBAA\" style=\"text-align:center\";\n! country\n! pop. dens.\n! area\n! population\n|- bgcolor=\"#F0EBAA\" style=\"text-align:center\";\n!  \n! (/km2)\n! (km2)\n! (2002-07-01 est.)\n|-\n| align=\"left\" | [[Macau]] (PRC)\n| 18,000\n| 25\n| 461,833\n|-\n| align=\"left\" | [[Hong Kong]] (PRC)\n| 6,688\n| 1,092\n| 7,303,334\n|-\n| align=\"left\" | [[Singapore]]\n| 6,430\n| 693\n| 4,452,732\n|-\n| align=\"left\" | [[Maldives]]\n| 1,070\n| 300\n| 320,165\n|-\n| align=\"left\" | [[Bahrain]]\n| 987\n| 665\n| 656,397\n|-\n| align=\"left\" | [[Bangladesh]]\n| 926\n| 144,000\n| 133,376,684\n|-\n| align=\"left\" | [[Republic of China]] ([[Taiwan]], [[Quemoy]], [[Matsu Islands|Matsu]])\n| 627\n| 35,980\n| 22,548,009\n|-\n| align=\"left\" | [[Palestinian territories]]\n| 545\n| 6,220\n| 3,389,578\n|-\n| align=\"left\" | [[South Korea]]\n| 491\n| 98,480\n| 48,324,000\n|-\n| align=\"left\" | [[Lebanon]]\n| 354\n| 10,400\n| 3,677,780\n|-\n| align=\"left\" | [[Japan]]\n| 336\n| 377,835\n| 126,974,628\n|-\n| align=\"left\" | [[India]]\n| 318\n| 3,287,590\n| 1,045,845,226\n|-\n| align=\"left\" | [[Sri Lanka]]\n| 298\n| 65,610\n| 19,576,783\n|-\n| align=\"left\" | [[Israel]]\n| 290\n| 20,770\n| 6,029,529\n|-\n| align=\"left\" | [[Philippines]]\n| 282\n| 300,000\n| 84,525,639\n|-\n| align=\"left\" | [[Vietnam]]\n| 246\n| 329,560\n| 81,098,416\n|-\n| align=\"left\" | [[North Korea]]\n| 184\n| 120,540\n| 22,224,195\n|-\n| align=\"left\" | [[Nepal]]\n| 184\n| 140,800\n| 25,873,917\n|-\n| align=\"left\" | [[Pakistan]]\n| 184\n| 803,940\n| 147,663,429\n|-\n| align=\"left\" | [[People\'s Republic of China]] ([[Mainland China|Mainland]])\n| 134\n| 9,596,960\n| 1,284,303,705\n|-\n| align=\"left\" | [[Thailand]]\n| 121\n| 514,000\n| 62,354,402\n|-\n| align=\"left\" | [[Indonesia]]\n| 121\n| 1,919,440\n| 231,328,092\n|-\n| align=\"left\" | [[Kuwait]]\n| 118\n| 17,820\n| 2,111,561\n|-\n| align=\"left\" | [[Armenia]]\n| 112\n| 29,800\n| 3,330,099\n|-\n| align=\"left\" | [[Syria]]\n| 93\n| 185,180\n| 17,155,814\n|-\n| align=\"left\" | [[Azerbaijan]]\n| 90\n| 86,600\n| 7,798,497\n|-\n| align=\"left\" | [[Turkey]]\n| 86\n| 780,580\n| 67,308,928\n|-\n| align=\"left\" | [[Georgia (country)|Georgia]]\n| 71\n| 69,700\n| 4,960,951\n|-\n| align=\"left\" | [[Cambodia]]\n| 71\n| 181,040\n| 12,775,324\n|-\n| align=\"left\" | [[Egypt]]\n| 71\n| 1,001,450\n| 70,712,345\n|-\n| align=\"left\" | [[Qatar]]\n| 69\n| 11,437\n| 793,341\n|-\n| align=\"left\" | [[Malaysia]]\n| 69\n| 329,750\n| 22,662,365\n|-\n| align=\"left\" | [[East Timor]]\n| 63\n| 15,007\n| 952,618\n|-\n| align=\"left\" | [[Myanmar]]\n| 62\n| 678,500\n| 42,238,224\n|-\n| align=\"left\" | [[Brunei]]\n| 61\n| 5,770\n| 350,898\n|-\n| align=\"left\" | [[Jordan]]\n| 58\n| 92,300\n| 5,307,470\n|-\n| align=\"left\" | [[Uzbekistan]]\n| 57\n| 447,400\n| 25,563,441\n|-\n| align=\"left\" | [[Iraq]]\n| 55\n| 437,072\n| 24,001,816\n|-\n| align=\"left\" | [[Tajikistan]]\n| 47\n| 143,100\n| 6,719,567\n|-\n| align=\"left\" | [[Bhutan]]\n| 45\n| 47,000\n| 2,094,176\n|-\n| align=\"left\" | [[Afghanistan]]\n| 43\n| 647,500\n| 27,755,775\n|-\n| align=\"left\" | [[Iran]]\n| 40\n| 1,648,000\n| 66,622,704\n|-\n| align=\"left\" | [[Yemen]]\n| 35\n| 527,970\n| 18,701,257\n|-\n| align=\"left\" | [[United Arab Emirates]]\n| 30\n| 82,880\n| 2,445,989\n|-\n| align=\"left\" | [[Laos]]\n| 24\n| 236,800\n| 5,777,180\n|-\n| align=\"left\" | [[Kyrgyzstan]]\n| 24\n| 198,500\n| 4,822,166\n|-\n| align=\"left\" | [[Oman]]\n| 13\n| 212,460\n| 2,713,462\n|-\n| align=\"left\" | [[Saudi Arabia]]\n| 12\n| 1,960,582\n| 23,513,330\n|-\n| align=\"left\" | [[Turkmenistan]]\n| 9.6\n| 488,100\n| 4,688,963\n|-\n| align=\"left\" | [[Russia]]\n| 8.5\n| 17,075,200\n| 144,978,573\n|-\n| align=\"left\" | [[Kazakhstan]]\n| 6.2\n| 2,717,300\n| 16,741,519\n|-\n| align=\"left\" | [[Mongolia]]\n| 1.7\n| 1,565,000\n| 2,694,432\n|}\n\n{{Benua}}\n[[Category:Benua]]\n[[Category:Asia|Asia]]\n\n\n[[af:Asië]] [[bg:Азия]] [[ca:Àsia]] [[cy:Asia]] [[da:Asien]] [[de:Asien]] [[en:Asia]] [[et:Aasia]] [[es:Asia]] [[eo:Azio]] [[eu:Asia]] [[fa:قاره‌ی آسیا]] [[fr:Asie]] [[ko:아시아]] [[hi:एशिया]] [[id:Asia]] [[it:Asia]] [[he:אסיה]] [[la:Asia]] [[io:Azia]] [[lt:Azija]] [[ms:Asia]] [[zh-min-nan:A-chiu]] [[nl:Azië]] [[ja:アジア]] [[no:Asia]] [[nds:Asien]] [[pl:Azja]] [[pt:Ásia]] [[ro:Asia]] [[ru:Азия]] [[simple:Asia]] [[fi:Aasia]] [[sv:Asien]] [[tl:Asya]] [[tokipona:ma Asija]] [[uk:Азія]] [[zh-cn:亚洲]] [[zh-tw:亚洲]]','/* Subwilayah */',3,'Kandar','20050223155638','',0,0,0,0,0.383936581846,'20050223155638','79949776844361'); INSERT INTO cur VALUES (1703,14,'Sunda','\'\'\'Sunda\'\'\' téh budaya, bangsa, katut alamna. Di handap ieu daptar artikel nu patali jeung Kasundaan, boh \'\'\'budaya\'\'\', \'\'\'jalma\'\'\', \'\'\'sajarah\'\'\', \'\'\'alam\'\'\', jeung sajabana.','',3,'Kandar','20041110042242','',0,0,0,0,0.231974823974,'20050309114449','79958889957757'); INSERT INTO cur VALUES (1704,0,'Gagak_Lumayung','\'\'\'Gagak Lumayung\'\'\' ngarupakeun sebutan lain pikeun [[Rajasangara]] atawa Kéansantang, putra [[Sri Baduga Maharaja]] (Ratu Jayadéwata, salasaurang raja Pajajaran nu pangmashurna, nu katelah Prabu Siliwangi).\n\n===Tempo ogé===\n*[http://wikisource.org/wiki/Wawacan_Gagak_Lumayung Wawacan Gagak Lumayung]\n\n\n{{pondok}}\n\n[[Category:Sunda]]','',3,'Kandar','20041218001841','',0,0,0,0,0.298180726961,'20050303211247','79958781998158'); INSERT INTO cur VALUES (1705,10,'Pondok','
    \n\'\'Artikel ieu pondok kénéh, perelu dilengkepan deui. Upami sadérék terang langkung paos perkawis ieu, dihaturan kanggo ngalengkepan.\'\'\n
    ','',20,'DiN','20050303211247','',0,0,1,0,0.123888374364,'20050303211247','79949696788752'); INSERT INTO cur VALUES (1706,10,'Téhnologi','{| style=\"margin:0 auto;\" align=center width=100% id=toc\n|align=center style=\"background:#ccccff\"| \n\'\'\'Widang utama [[téhnologi]]\'\'\'\n|align=\"center\" style=\"background:#ccccff\" |[http://su.wikipedia.org/wiki/Template:Téhnologi édit]\n|-\n|align=center| [[Biotéhnologi]] | [[Téhnologi komputer]] | [[Rékayasa listrik]] | [[Éléktronik]] | [[Téhnologi mikro]] | [[Téhnologi nano]] | [[Rékayasa biomédis]] | [[Panyimpen énergi]] | [[Mesin]] | [[Téhnologi angkasa]] | [[Téhnologi nuklir]] | [[Téhnologi visual]] | [[Téhnologi jeung alat militér|Téhnologi pakarang]] | [[Telekomunikasi]] | [[Angkutan]] \n|-\n|}','',3,'Kandar','20041111054938','',0,0,0,1,0.327999240872,'20041111054938','79958888945061'); INSERT INTO cur VALUES (1707,0,'Kabuyutan','Istilah \'\'\'kabuyutan\'\'\' dina budaya [[Sunda]] sahanteuna geus aya ti munggaran abad ka-11 M. [[Prasasti Cibadak]] nu dijieun kira taun 1006-1016 M, ngunggelkeun yén Prabu [[Sri Jayabupati]] (salaku Raja Sunda) geus netepkeun sawaréh ti wewengkon walungan [[Sanghyang Tapak]] (waktu harita) salaku kabuyutan, nyaéta tempat nu mibanda pantangan nu kudu diturut ku sakabéh rahayatna. Unina kieu,\n\n:\"\'\'Salamet, dina taun Saka 952 bulan Kartika tanggal 12 bagian terang poé Hariyang-Kliwon-Ahad wuku Tambir. Ieu nalika raja Sunda Maharaja Sri Jayabhupati Jayamanahen Wisnumurti Samarawijaya Sakalabuanamandaleswaranindita Harogowardana Wikramotunggadewa nyieun tanda di wétaneun sanghyang tapak, dijieun ku Sri Jayabhupati Raja Sunda jeung ulah aya nu ngarumpak katangtuan di walungan ieu. Ulah aya nu néwak lauk di walungan belah dieu ti wates wewengkon kabuyutan sanghyang tapak béh hulu…………\'\'\"\n\nIstilah kabuyutan salajengna aya dina naskah kuna Sunda titinggal abad ka-13 M, nyaéta naskah [[Ciburuy]] atawa Naskah Galunggung nu katelah [[Amanat Galunggung]] atawa Amanat Prabu Guru [[Darmasiksa]].\n\n\n{{pondok}}\n\n[[Category:Sunda]] [[Category:Sajarah Sunda]]','',3,'Kandar','20050125053830','',0,0,0,0,0.625421213743,'20050303211247','79949874946169'); INSERT INTO cur VALUES (1708,0,'Qur\'an','{{Islam}}\n\'\'\'Qur\'an\'\'\' ([[basa Arab]] \'\'al-qurʾān\'\' \'\'\'أَلْقُرآن\'\'\'; ogé di[[tarjamah]]keun jadi \'\'\'Quran\'\'\', \'\'\'Koran\'\'\', atawa \'\'\'Alcoran\'\'\') ngarupakeun kitab suci [[Islam]].\n\n[[Muslim]] percaya yén Qur\'an ngarupakeun kekecapan Gusti Alloh, nu nungtutan didugikeun ka Nabi [[Muhammad]] salila 22 taun. Qur\'an ngandung 114 [[surat]] (bab) nu total eusina aya 6.236 [[ayat]]. Qur\'an nyaritakeun kajadian-kajadian picontoeun dina sajarah manusa, utamana ngeunaan para nabi saméméh Muhammad kayaning [[Nuh]], [[Adam]], [[Ibrahim]], [[Musa]], [[Isa]], jeung nu séjénna.\n\n==Asal-usul Qur\'an ==\n\nMuslim percaya yén kekecapan dina téks Qur\'an nu aya kiwari persis sarua jeung nu dikedalkeun ku Muhammad; firman Pangéran nu didugikeun ka [[Muhammad]] ngalangkungan [[Jibril]]. Muhammad is supposed to have only delivered the Qur\'an in spoken form during his lifetime (although his [[Sahaba|companions]] are said to have written it down piecemeal); the word \'\'Qur\'an\'\' (repertoire) is suitably translated as \"recital\", indicating that it cannot exist as a mere text. To be able perform [[salat]] (prayer), a religious obligation in Islam five times daily, a person is required to learn at least some [[sura]]s of the Qur\'an (typically starting with the shorter ones at the end); and the more of the Qur\'an learned, the better. A person whose recital repertoire encompasses the whole Qur\'an is called a [[Qari\']] (قَارٍئ) or [[Hafiz]] (which translates as \"protector\" or \"memorizer\".)\n\nMuhammad\'s companions began recording all the suras in writing before Muhammad died in [[632]] CE; written copies of various suras during his lifetime are frequently alluded to in the traditions. For instance, in the story of the conversion of [[Umar ibn al-Khattab]] (when Muhammad was still at [[Mecca]]), his sister is said to have been reading a text of surat [[Ta-Ha]], and at [[Medina]], about 65 [[sahaba|Companions]] are said to have acted as scribes for him at one time or another, and he would regularly call upon them to write down revelations immediately after they came. \n\nAccording to Islamic tradition, the first complete compilation of the Qur\'an in one volume was made in the first [[Caliph]] [[Abu Bakr]]\'s time by [[Zayd ibn Thabit]], who \"gathered the Qur\'an from various parchments and pieces of bone, and from the chests (ie memories) of men.\" This copy was kept in [[Hafsa bint Umar]] house. However, during the caliphate of [[Uthman ibn Affan]], a dispute developed about the use of various dialects ([[ahruf]]) that the Qur\'an was being recited. Some were also alarmed by the reported divergences in the recitation of the revelation, especially among new Muslims. In response, Uthman made the decision of codifying and standardizing the text. According to conflicting Islamic traditions, he had a committee, that included Zayd and several prominent members of Quraysh, to produce a standard copy of the text, based on the compilation in the keeping of Hafsah. \n\nWhen finished, Uthman sent out copies of it to the various corners of the Islamic empire, and ordered the destruction of all copies that differed from it. Several manuscripts, including the [[Samarkand manuscript]], are claimed to be one of the original copies Uthman sent out[http://www.islamic-awareness.org/Quran/Text/Mss/]; however, many scholars dispute that Samarkand is Uthmanic copy. Among the recently discovered [[Sanaa]] Qur\'an manuscripts, at least three are dated to before 50 AH. Inscriptional evidence begins somewhat later; the earliest dated inscriptions containing portions of the Qur\'an other than the [[basmala]] are dated to around 70 AH[http://www.islamic-awareness.org/History/Islam/Dome_Of_The_Rock/Estwitness.html][http://www.islamic-awareness.org/History/Islam/Inscriptions/].\n\nBeside the known earlier versions from Abdallah Ibn Masud and Ubay Ibn Ka\'b, there exist also some reports about a Shiite version which was allegedly compiled by [[Ali ibn Abi Talib|Ali]], Muhammad\'s son-in-law, which he gave up in favor of Uthman\'s collection. Muslim scholars assume that the differences between the versions consisted mostly of orthographical and lexical variants and differing count of verses. All three of the mentioned people (Ibn Masud, Ubay Ibn Ka\'b & Ali) were in positions of authority that would allow them to oppose any variations that existed between their collection and that of Uthman\'s. But to the contrary they all supported Uthamic version and continued to serve under the Caliph\'s rule.\n\nSince Uthman\'s version contained no diacritical marks, and could thus be read in various ways by those who had not memorised it, around the year 700 the development of a vocalized version started. Today the Qur\'an is published in fully vocalized versions.\n\nToday seven canonical readings of the Qur\'an and several uncanonical exist. This sevener-system was laid down by [[Ibn Mujahid]] who tried to find the special characteristics of each reading and thus derived common rules by analogical reasoning (\'\'qiyas\'\'). They are:\n\n# [[Nafi\']] of [[Madina]] (169/[[785]]), transmitted by [[Warsh]] (197/[[812]])\n# [[Ibn Kathir]] of [[Makka]] (120/[[737]])\n# [[Ibn \'Amir]] of [[Damascus]] (118/[[736]])\n# [[Abu \'Amr]] of [[Basra]] (148/[[770]]) \n# [[\'Asim]] of [[Kufa]] (127/[[744]]), transmitted by [[Hafs]] (180/[[796]])\n# Hamza of [[Kufa]] (156/[[772]])\n# [[Al-Kisa\'i]] of [[Kufa]] (189/[[804]]), transmitted by [[Duri]] (246/[[860]])\n\nThese readings differ in the vocalization (\'\'tashkil\'\' تشكيل) of a few words. By far the two best-known readings of the Qur\'an are the [[Warsh]] (ورش) and [[Hafs]] (حفص) readings; the others are almost never used.\n\n== Textual Criticism and the Qur\'an == \n\nHigher biblical criticism revolutionized Judaism and Christianity by calling into question long-held assumptions about the origins of the Bible; some ambitious textual critics are attempting to do the same for the Qur\'an. They claim that parts of the Qur\'an are based on stories of the [[Tanakh]] ([[Hebrew Bible]]), the [[New Testament]] of the [[Christianity|Christian]] Bible, and other non-canonical Christian works; differences of the biblical to the Qur\'anic versions indicate that these stories were not taken directly from written texts but seem rather to have been part of the oral traditions of the Arab peninsula at Muhammad\'s time. To Muslims, however, this explanation is topsy-turvy: the \"non-canonical\" Jewish and Christian stories are simply further textual corruptions of an otherwise nearly lost divine original reflected in the Qur\'an.\n\nThese critics also seek to find evidence of text evolution and transcription disputes in early Islam; the results have been meager, but some have expressed hopes that recent discoveries of \"Qur\'an Graveyards\" in Yemen will throw more light on the subject.\n\n==Tapsir Qur\'an==\n\nPitulung pangpentinga dina [[tapsir|napsirkeun]] harti ayat-ayat Qur\'an nyaéta [[Hadis]] - kumpulan tradisi Islam (kagiatan jeung sasanggeman Nabi Muhammad). Élmu [[isnad]] tumuwuh dina mangsa munggaran abad Hijriyah, nu usaha ngagolongkeun sasanggeman/béja hadis dumasar bisa henteu dipercayana jalma nu nepikeun hadis. Tapsir Qur\'an salajengna tumuwuh jadi hiji élmu mandiri nu disebut \'\'élmu tapsir\'\'. Di antaran élmuwan nu kawentar nyaéta [[Tabari]], [[Zamakhshari]], [[Turmudhi]], [[Ibn Kathir]].\n\nBelief in the Qur\'an\'s direct, uncorrupted divine origin is fundamental to Islam; this of course entails believing that the Qur\'an has neither errors nor inconsistencies. (\"This is the book in which there is no doubt, a guide to the believers\": Surat [[al-Baqarah]], verse 2.) However, it is well-known that certain chronologically later verses supersede earlier ones - the banning of wine, for instance, was accomplished gradually rather than immediately - and certain scholars have argued that some verses which discourage certain practices (for instance, [[polygamy]]) without banning them altogether should be understood as part of a similar process, though others argue that this contradicts \"This day have I perfected your religion for you, completed My favor upon you, and chosen for you Islam as your religion\" ([[sura 5|5]].3).\n\n\n----\n[[\'\'\'Naha quran teh mahluk atanapi lain (abadi) ?\'\'\']]\n\n----\n\nKaseueuran ulama tauhid ngayakinkeun yen al-quran teh kalam allah nu tangtos sanes mahluk jeung moal ruksak (abadi),sabab al-quran teh dawuhan Allah, jeueng ari ngadawuh teh eta salah sahiji sifat Allah. Lamun sifat Allah teu abadi, tangtu dzat Allah ge teu abadi, sedengken lamun Alla teu abadi eta mustahil. kulantaran kitu kaharti ku akal yen sifat Allah nu ieu (ngadawuhna Allah)mustahil ruksak, kulantaran mustahil ruksak, atuh jelas yen al-quran teh lain mahluk. Ngenaan ieu pendapat kantos dibabarkeun ka ahli filsafatna Yunani, utamina teori-teori Plato yen sadaya kanyataan jeung kabeneran anu teu kawates tangtos abadi jeung moal matak robah.\nGiven that Muslims believe that Biblical figures such as [[Moses]] and [[Jesus]] all preached Islam, the doctrine of an unchanging, uncreated revelation implies that contradictions between their statements according to the Qur\'an and the Bible must be the result of human corruption of the earlier divine revelations.\n\nHowever, some, notably including the [[Mu\'tazili]] and [[Ismaili]] sects, dispute this doctrine of the uncreated Qur\'an. Various [[liberal movements within Islam]] implicitly or explicitly question the doctrine of the uncreated Qur\'an when they question the continuing applicability and validity of [[Islamic law]], as their justifications for doing so are often based on a belief that such laws were created by God to meet the particular needs and circumstances of Muhammad\'s community. A Qur\'an created by God for a particular context might also account for differences between the Bible without requiring humans to have corrupted divine texts.\n\n==Tempo ogé==\n* [[Allah]]\n* [[Islam]]\n* [[Muhammad]]\n* [[Maaz bin jabal]]\n* [[Ngabandingkeun Bibel jeung Qur\'an]]\n\n==Pustaka==\n\n* A. J. Arberry, \'\'The Koran Interpreted\'\', Touchstone Books, 1996. ISBN 0684825074\n* M. M. Al-Azami, \'\'The History of the Qur\'anic Text from Revelation to Compilation\'\', UK Islamic Academy: Leicester 2003.\n* Fazlur Rahman, \'\'Major Themes in the Qur\'an\'\', Bibliotheca Islamica, 1989. ISBN 0882970461 \n* W. M. Watt and R. Bell, \'\'Introduction to the Qur\'an\'\', Edinburgh University Press, 2001. ISBN 0748605975\n* J. D. McAuliffe (ed.), \'\'Encyclopaedia of the Qur\'an\'\', Brill, 2002-2004. \n* Don Richardson, \'\'Secrets of the Koran\'\', Regal Books, 2003. ISBN 0830731245\n* [[Ibn Warraq]] (ed.), \'\'The Origins of the Koran\'\', Prometheus Books, 1998. ISBN 157392198X \n* Muhammad ibn Jarir at-Tabari, \'\'Jami al-bayan `an ta\'wil al-Qur\'an\'\', Cairo [[1955]]-[[1969|69]], transl. J. Cooper (ed.), \'\'The Commentary on the Qur\'an\'\', Oxford University Press, 1987. ISBN 0199201420\n\n==Tumbu kaluar==\n{{Wikisource}}\n*[http://www.haqaonline.com/multimedia/audio/Quran/ Listen to the Holy Quran, available to listen in Realplayer, Windows Media Player and available to download as a MP3]\n*[http://www.haqaonline.com/multimedia/video/quran/ Watch the Holy Quran being recited.]\n*[http://www.quran.org.uk Holy Qur\'an Resources on the Internet]\n*[http://faculty.washington.edu/wheelerb/quran/quran_index.html Qur\'an Manuscripts]\n* [http://www.islamic-awareness.org/Quran/ Examining The Qur\'an] Orginal articles responding to textual criticism. \n* [http://www.quranicstudies.com/ The Qur\'anic Studies] \n*[http://www.SureGuidance.org Sure Guidance]\n*[http://www.usc.edu/dept/MSA/quran/ The Noble Qur\'an] - three translations and [[Sayyid Abul Ala Maududi]]\'s chapter introductions to the Qur\'an\n*[http://www.al-quran.org.uk/ The Qur\'an Browser]\n*[http://answering-islam.org/Quran/Text/ Textual Variants of the Qur\'an]\n*[http://www.altway.freeuk.com/Answers/00-Content.htm A Muslim Response to \"Answering Islam\"]\n*[http://theatlantic.com/issues/99jan/koran.htm What is the Koran?]\n*[http://www16.brinkster.com/weichertech/Quran.html Quranic Concordance Engine] - Proof of Miracle of Quranic Concordance - \'\'Requires IE5+, takes time to load\'\'\n*[http://members.aol.com/silence004/ The Koran and Nature\'s Testimony]\n*[http://playandlearn.org/ramadhan/Ghamidi.htm Holy Quran Recitation]\n*[http://www.islam101.com/science/bucaille.html The Bible, the Qur\'an and Science]\n*[http://www.skepticsannotatedbible.com/quran/index.html The Skeptic\'s Annotated Qur\'an] - a version of the Qur\'an annotated from a skeptical point of view.\n*[http://syrcom.cua.edu/Hugoye/Vol6No1/HV6N1PRPhenixHorn.html Review] of \'\'Die syro-aramaeische Lesart des Koran; Ein Beitrag zur Entschlüsselung der Qur\'ānsprache\'\' by Christoph Luxenberg (ps.), a controversial work of textual criticism.\n* [http://www.islamic-awareness.org/Quran/Text/luxreview1.html More] [http://www.islamic-awareness.org/Quran/Text/luxreview2.html reviews] of \'\'Die syro-aramaeische Lesart des Koran; Ein Beitrag zur Entschlüsselung der Qur\'ānsprache\'\' by Christoph Luxenberg (ps.).\n* [http://www.witness-pioneer.org/vil/Books/Denffer_uaq/Ch5S5.htm The Various Readings] - a summary of the 7 ahruf\n* [http://www.altafsir.com/ Tafsir.com]\n\n[[ar:القران]]\n[[da:Koran]]\n[[de:Koran]]\n[[en:Qur\'an]]\n[[es:Corán]]\n[[eo:Korano]]\n[[fa:قرآن]]\n[[fr:Coran]]\n[[id:Al-Qur\'an]]\n[[it:Corano]]\n[[ms:Al Quran]]\n[[nl:Koran]]\n[[ja:クルアーン]]\n[[pl:Koran]]\n[[pt:Corão]]\n[[ro:Coran]]\n[[simple:Qur\'an]]\n[[sv:Koranen]]\n[[zh-cn:古兰经]]\n\n[[Category:Quran]] [[Category:Islam]] [[Category:Naskah suci]]','/* Interpretation of the Qur\'an */',3,'Kandar','20050301055150','',0,0,1,0,0.837960885297,'20050303024849','79949698944849'); INSERT INTO cur VALUES (1709,10,'Islam','{| class=\"WSerieV\" id=\"WSerie_Islam\" tableborder=\"1\" cellspacing=\"0\" style=\"padding: 0.3em; float:right; margin: 5px 5px 1em 1em; border:1px solid #999; background:#99CC99; text-align:center;\"\n|[[image:shahadah.PNG|200px|Sahadat, atawa panyaksén Islam]]
    Artikel ieu salasahiji ti séri
    \'\'\'[[Islam]]\'\'\'\n|-\n|[[Daptar istilah Islam|Kosakecap Islam]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Lima Pangadeg\'\' \n|-\n|[[Sahadat|Panyaksén kaimanan]]\n|-\n|[[Solat]] – [[Zakat]]\n|-\n|[[Saum]]\n|-\n|[[Haji|Munggah ka Mekah]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Kota Suci\'\'\n|-\n|[[Mekah]] – [[Madinah]]\n|-\n|[[Darussalam]] \n|-\n|[[Najaf]] – [[Karbala]] – [[Kufah]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Kajadian\'\'\n|-\n|[[Hijrah]] – [[Kalénder Islam]] – [[Idul Fitri]]\n|-\n|[[Idul Adha]] – [[Aashura]] – [[Arba\'in]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Wangunan\'\'\n|-\n|[[Masjid]] – [[Munara]]\n|-\n|[[Mihrob]] – [[Ka\'bah]]\n|-\n| [[Arsitéktur Islam]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Functional Religious Roles\'\'\n|-\n|[[Muezzin]] – [[Imam]] – [[Mullah]]\n|-\n|[[Ayatollah]] – [[Mufti]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Interpretive Texts & Practices\'\'\n|-\n|[[Qur\'an]] – [[Hadith]] – [[Sunnah]]\n|-\n| [[Fiqh]] – [[Fatwa]] – [[Sharia]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Sects\'\'\n|-\n|[[Sunni Islam|Sunni]] ([[Madhhab|Schools of thought]]:
    [[Hanafi]], [[Hanbali]], [[Maliki]], [[Shafi\'i]])\n|-\n| [[Shi\'a Islam|Shi\'a]]: [[Twelvers|Ithna Asharia]], [[Ismaili|Ismailiyah]],
    [[Zaiddiyah]]\n|-\n|Others: [[Mu\'tazili]] – [[Kharijites|Kharijite]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Movements\'\'\n|-\n| [[Sufism]]\n|-\n|[[Wahhabism]] – [[Salafi|Salafism]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Non-Mainstream Sects/Movements\'\'\n|-\n| [[Ahmadiyya Muslim Community|Ahmadiyyah]]\n|-\n|style=\"background:#F6E6AE\"|\'\'Related Faiths\'\'\n|-\n|[[Druze]]; [[Bahá\'í Faith]]\n|}\n\n\n[[en:Template:Islam]]','',3,'Kandar','20041112040213','',0,0,0,1,0.698648267751,'20041112040213','79958887959786'); INSERT INTO cur VALUES (1710,10,'Wikisource','{| border=\"0\" width=\"35%\" align=\"right\" cellpadding=\"5\" class=\"noprint\" style=\"float:right; clear:both; border:solid #008 2px; margin:0em 0em 0.5em 0.5em; width:35%;\" \n|-\n|[[Image:Sourceberg.jpg|50px|none|Wikisource|]]\n| width=\"100%\" | \n;[[Wikisource]] mibanda tulisan nu patali jeung artikel ieu:\n:
    \'\'\'\'\'[[Wikisource:{{PAGENAME}}|{{PAGENAME}}]]\'\'\'\'\'
    \n|}','',3,'Kandar','20041112040636','',0,0,0,1,0.265187448014,'20041112040636','79958887959363'); INSERT INTO cur VALUES (1711,0,'2004','*[[Abad ka-20]] [[1999]] [[2000]]\n*[[Abad ka-21]] [[2001]] [[2002]] [[2003]] \'\'\'2004\'\'\' [[2005]] [[2006]] [[2007]] [[2008]] [[2009]]\n\n[[5 Juli]] Pamilihan présidén Indonésia\n\n[[28 Agustus]] Gelar [[Budaya]] jeung Wisata Kontémplatif NYIAR LUMAR 4 Situs Astana Gedé [[Kawali]] \n\n[[en:2004]]\n[[id:2004]]\n[[mi:2004]]\n[[sm:2004]]','',3,'Kandar','20041123094656','',0,0,0,0,0.225701178995,'20050208111611','79958876905343'); INSERT INTO cur VALUES (1712,0,'Musik','jazz','',0,'217.184.220.51','20041116221825','',0,0,0,1,0.613626297849,'20041116221825','79958883778174'); INSERT INTO cur VALUES (1713,1,'Logarithmic_integral','x','',0,'142.103.168.121','20041117193219','',0,0,0,1,0.101800170774,'20041117193219','79958882806780'); INSERT INTO cur VALUES (1714,0,'Klaipéda','[[Image:Dramaga_Klaipeda.jpg|thumb|right|250px|Labuan Klaipėda nguruskeun nepi ka 20 yuta ton kargo unggal taunna]]\n\n\'\'\'Klaipėda\'\'\', ([[basa Jėrman]]na \'\'Memel\'\' atawa \'\'Memelburg\'\'; [[basa Polandia]]na \'\'Kłajpeda\'\'), ngarupakeun [[labuan]] hiji-hijina [[Lituania]] di [[Laut Baltik]]. Pangeusina aya 194,400 urang ([[2002]]), nurun ti 202,900 dina taun [[1989]]. Klaipėda ayeuna jadi dramaga [[fėri]] utama nu ngahubungkeun jeung [[Swėdia]], [[Dėnmark]], jeung [[Jėrman]]. Tempatna deukeut ka muara [[walungan Neman]].\n\nKlaipėda mibanda arsitėktur \'\'picturesque\'\' nu sarupa jeung nu kapanggih di Jėrman, [[Inggris]], jeung [[Dėnmark]]. \'\'Resort\'\' gigir laut gaya Lituania popular sabudeureun Klaipėda aya di [[Neringa]] jeung [[Palanga]].\n\n==Sajarah==\n\nKlaipėda diadegkeun ku suku Baltik [[abad ka-12]], nu salajengna pikeun jangka waktu nu cukup lila dikawasa ku [[Prusia Wėtan]], nyėta nalika katelah Memel.\n\nDayeuh labuan Laut Baltik ieu diadegkeun ku \'\'[[Teutonic Knights]]\'\' taun [[1252]] sarta kacatetkeun salaku \'\'Castrum Memele\'\' (basa Jėrman \'\'Memelburg\'\', atawa \'\'Mimmelburg\'\'). Taun [[1254]] Klaipėda dipaparin [[Lübeck City Right]]. Wewengkon ieu [[kristenisasi|dikristenkeun]] ku \'\'Teutonic Knights\'\'. Perjangjian \'\'[[Daméi di Laut Melno]]\'\' taun [[1422]] nangtukeun wates antara [[Provinsi Prusia]] jeung [[Lituania]]. Memel asup ka Prusia; perjangjian ieu lumaku nepi ka taun [[1919]]. Ieu ngarupakeun wates nu panglilana teu robah di [[Éropa]].\n\nMunggaran taun [[1474]] Memel diatur ku [[Hukum Culm]] dayeuh Tatar Prusia. Taun [[1525]], Ménak Memel, nu ditangtayungan ku [[Albert ti Prussia]] (Albrecht von Brandenburg-Ansbach-Prussia), ngadopsi [[Luteranisme]]. Mangsa ieu dayeuh jeung labuan pinanggih jeung karaharjaan, sabab [[Ducal Prussia]] ngarupakeun tanah injeuman [[Polandia]] sarta salajengna jadi bagian [[Persemakmuran Polandia-Lituania]]. Dayeuh ieu ogé jadi labuan pikeun Lituania, sabab lokasina nu deukeut muara walungan Nemen nguntungkeun pisan. Mangsa raharja kalindih nalika antara [[1629]] jeung [[1635]] Memel diserang, diruksak, sarta dikawasa ku Swédia. Diropéa sababaraha kali, 75 taun salajengna loba pisan pangeusi Memel maot alatan [[cacar]]. Ku ngadegna nagara Uni Jérman taun [[1871]], Memel jadi dayeuh paling kalér-wétaneun wewengkon Jérman.\n\nTaun [[1919]] Klaipėda ditempatkeun dina [[protėktorat]] Nagara Entente. Satutasna [[Perjangjian Versailles]] wewengkon sabudeureun Memel dipisahkeun ti Jėrman sarta ngadeg otonom dina kakawasaan Prancis. Soldadu Lituania nu dipingpin ku [[Kolonėl Budrys]] nyerang Memel taun [[1923]] nepi ka ditinggalkeun ku soldadu Prancis. Memel direbut ku \'\'German Reich\'\' [[22 Maret]] [[1939]] satutasna ngarebut [[Austria]], [[Sudetenland]], jeung [[Cėkoslowakia]].\n\nNalika [[Perang Dunya ka-2]], mimiti ahir taun [[1944]] nepi ka [[1945]], pangeusina loba nu kalabur ngungsi. Dayeuh ieu salajengna direbut ku [[Soldadu Beureum]] Januari 1945 sarta dipulangkeun deui ka [[Lituania|Rėpublik Soviėt Lituania]].\n\nLoba pangeusi Klaipéda nu dikirim ka [[Sibéria]], sedengkeun sésana dibuang ka Jérman.\n\n==Nu wedal di Klaipėda ==\n* [[Simon Dach]] (1605 - 1659), panyajak\n* [[Michael Wohlfahrt|Rev. Michael Wohlfahrt]] (1687 - 1741), pamingpin agamis di Amėrika\n* [[Friedrich Wilhelm Argelander]] (1799 - 1875), ahli astronomi\n* [[George Adomeit]] (1879 - 1967), seniman (lukis) Amérika\n\n==Tempo ogė==\n*[[Labuan di Laut Baltik]]\n\n==Tumbu kaluar==\n* [http://www.klaipeda.lt/ Loka resmi Dayeuh Klaipeda]\n* [http://worldatwar.net/nations/other/memel/ Kaca ngeunaan sajarah Memel/Klaipeda] ku Richard Doody\n\n[[da:Klaipeda]]\n[[de:Klaipėda]]\n[[en:Klaipeda]]\n[[lt:Klaipėda]]\n[[nl:Klaipeda]]\n[[nds:Klaipeda]]\n[[pl:Kłajpeda]]\n[[sv:Klaipeda]]\n[[tt:Klaipėda]]\n\n[[Category:Dayeuh Lituania]]','/* Sajarah */',3,'Kandar','20041122072031','',0,0,0,0,0.170327897263,'20050208191941','79958877927968'); INSERT INTO cur VALUES (1715,6,'Dramaga_Klaipeda.jpg','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041122064535','',0,0,0,1,0,'20041122072032','79958877935464'); INSERT INTO cur VALUES (1716,0,'Gangnihessou','Nurutkeun carita, \'\'\'Gangnihessou\'\' ngarupakeun [[raja]] munggaran ti dua welas nu ngawasa [[Dahomey]] di [[Afrika]], kurang leuwih taun [[1620]]. Salasahiji lambangna mangrupa [[manuk gangnihessou]] jalu. Lambang séjénna mangrupa sarupaning kendang jeung tongkat nu dipaké pikeun malédog atawa moro. Nu sabenerna ngeunaan ieu masih mangrupa tanda tanya, sabab bisa waé anjeunna ukur salasahiji pamingpin nu boga pangaruh. Anjeunna boga adi nu ngaranna [[Dakodonou]], nu kungsi jadi raja. Sigana mah Gangnihessou mingpin rahayat sangkan nurut ka adina ieu.\n\n\n{{pondok}}\n\n[[ar:جانجنيهيسو]]\n[[bg:Гангнихесу]]\n[[ca:Gangnihessou]]\n[[cs:Gangnihessou]]\n[[cy:Gangnihessou]]\n[[da:Gangnihessou]]\n[[de:Gangnihessou]]\n[[el:Γκανγκνιχέσσου]]\n[[en:Gangnihessou]]\n[[es:Gangnihessou]]\n[[eo:Gangnihessou]]\n[[fr:Gangnihessou]]\n[[fy:Gangnihessou]]\n[[ko:가니니헤소]]\n[[hi:गेंगनीहेस्सू]]\n[[id:Gangnihessou]]\n[[it:Gangnihessou]]\n[[he:גנגניהסו]]\n[[kn:ಗಂಗ್ನಿಹೆಸ್ಸೊ]]\n[[la:Gangnihessou]]\n[[hu:Gangnihessou]]\n[[ms:Gangnihessou]]\n[[nl:Gangnihessou]]\n[[ja:ガングニヘソ]]\n[[no:Gangnihessou]]\n[[pl:Gangnihessou]]\n[[pt:Ganiehéssu]]\n[[ro:Gangnihessou]]\n[[simple:Gangnihessou]]\n[[sq:Gangnihessou]]\n[[fi:Gangnihessou]]\n[[sv:Gangnihessou]]\n[[tl:Gangnihessou]]\n[[tt:Gangnihessou]]\n[[th:กังนีเฮซซู]]\n[[vi:Gangnihessou]]\n[[zh:岡尼何梭]]\n[[ang:Gangnihessou]]','',3,'Kandar','20041122075834','',0,0,0,0,0.945696688698,'20050303211247','79958877924165'); INSERT INTO cur VALUES (1717,0,'Mathematical_statistics','#REDIRECT [[Statistik matematis]]\n','Mathematical statistics dipindahkeun ka Statistik matematis',3,'Kandar','20041122085146','',0,1,0,1,0.763849469723,'20041122085146','79958877914853'); INSERT INTO cur VALUES (1718,0,'Indonesia','#REDIRECT [[Indonésia]]\n','Indonesia dipindahkeun ka Indonésia',3,'Kandar','20041122091748','',0,1,0,1,0.672318843972,'20041122091748','79958877908251'); INSERT INTO cur VALUES (1719,0,'Flag_of_Indonesia','#REDIRECT [[Bandéra Indonésia]]\n','Flag of Indonesia dipindahkeun ka Bandéra Indonésia',3,'Kandar','20041122093602','',0,1,0,1,0.708969680923,'20041122093602','79958877906397'); INSERT INTO cur VALUES (1720,10,'Indonésia','
    \n
    \n{| id=\"toc\" style=\"margin: 0 2em 0 2em;\"\n! style=\"background:#ccccff\" align=\"center\" width=\"100%\" | [[Provinsi di Indonésia]]\'\'\' || [[Image:Indonesia flag large.png|50px|Bandéra Indonésia]]\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Sumatra]] (Sumatera):\'\'\'\n[[Acéh|DI Aceh]] |\n[[Sumatra Kalér]] (Sumatera Utara) |\n[[Sumatra Kulon]] (Sumatera Barat) |\n[[Bengkulu]] |\n[[Riau]] |\n[[Pulo Riau]] (Kepulauan Riau) |\n[[Jambi]] |\n[[Sumatra Kidul]] (Sumatera Selatan) |\n[[Lampung]] |\n[[Bangka-Belitung]]\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Jawa (pulo)|Jawa]] (Jawa):\'\'\'\n[[Jakarta|DKI Jaya]] |\n[[Jawa Kulon]] (Jawa Barat) |\n[[Banten]] |\n[[Jawa Tengah]] |\n[[Jogjakarta|DI Yogyakarta]] |\n[[Jawa Wétan]] (Jawa Timur)\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Kalimantan]]:\'\'\'\n[[Kalimantan Kulon]] (Kalimantan Barat) |\n[[Kalimantan Tengah]] |\n[[Kalimantan Kidul]] (Kalimantan Selatan) |\n[[Kalimantan Wétan]] (Kalimantan Timur)\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Pulo Sunda alit]] (Nusa Tenggara):\'\'\'\n[[Bali]] |\n[[Nusa Tenggara Kulon]] (Nusa Tenggara Barat) |\n[[Nusa Tenggara Wétan]] (Nusa Tenggara Timur)\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Sulawesi]]:\'\'\'\n[[Sulawesi Kulon]] (Sulawesi Barat) |\n[[Sulawesi Kalér]] (Sulawesi Utara) |\n[[Sulawesi Tengah]] |\n[[Sulawesi Kidul]] (Sulawesi Selatan) |\n[[Sulawesi Tenggara]] |\n[[Gorontalo]]\n|-\n| align=\"center\" style=\"font-size: 90%;\" colspan=\"2\" | \'\'\'[[Maluku (provinsi)|Pulo Maluku]] jeung [[Papua]] (Irian):\'\'\'\n[[Maluku (provinsi)|Maluku]] |\n[[Maluku Kalér]] (Maluku Utara) |\n[[Irian Jaya Kulon]] (Irian Jaya Barat) | \n[[Papua (provinsi)|Papua]]\n|}\n
    ','',3,'Kandar','20041122095828','',0,0,0,1,0.07396081885,'20050208043350','79958877904171'); INSERT INTO cur VALUES (1721,0,'Ahli_Astronomi','kumaha atuh etateh','',0,'203.130.226.203','20041122140147','',0,0,0,1,0.026213590999,'20041122140147','79958877859852'); INSERT INTO cur VALUES (1722,0,'Wikipédia:Cara_ngédit_kaca','#REDIRECT [[Wikipédia: Cara ngédit kaca]]\n','Wikipédia:Cara ngédit kaca dipindahkeun ka Wikipédia: Cara ngédit kaca',3,'Kandar','20041123034713','',0,1,0,1,0.524714198208,'20041123034713','79958876965286'); INSERT INTO cur VALUES (1725,0,'Bandung_purba','Palebah imah sim kuring (lamun dianggap rata sarua jeung di pintu tol Buah Batu) jerona teh 49 meter lamun dianggap beungeut cai 725 m.dpl, atuh di pintu tol Kopo 54 meter jerona.\nIeu kayaan teh 35 rebu taun anu geus kaliwat, dina mangsa talaga Bandung keur meujeuhna ngeplak caina.\n\n== Talaga Bandung ==\n\nTalaga Bandung panjangna kira kira 50 km, lebarna 30 km, mimiti ti [[Cicalengka]] beulah wetan, nepi ka [[Rajamandala]] beulah kulon jeung ti [[Majalaya]], [[Banjaran]] beulah kidul nepi ka [[Dago]] beulah kaler. Ditilik sacara [[geomorfologi]] talaga Bandung teh rada dengdek ka beulah kulon jeung kira beh tengah aya galengan saolah olah talaga teh dibagi dua nyeta beulah wetan jeung beulah kulon, ieu galengan teh perenahna aya di Curug Jompong.dina rangkaian gunung kuno diantarana Gunung Puncaksalam,Pasir Kamuning, Pasir Kalapa, Gunung Lalakon,Pasir Malang, Gunung Selacau, Lagadar, Padakasih,Jatinunggal nepi ka Gunung Bohong di beulah kidul Cimahi.\nTalaga Bandung beulah kulon mimiti ngorotan kira kira 6000 taun nu geus kaliwat, nu pangheulana bobol teh nyaeta didaerah Pasir Kiara (aya oge nu nyebatkeun di Sanghyang Tikoro) beulah kidul Rajamandala.\n \nDi jaman kuartier kala [[pleistosen]], kira kira 500.000 taun nu geus kaliwat [[Gunung Sunda]] (purba) mimiti mucunghul, gunung api raksasa anu rohaka, dibeulah wetana aya gunung Bukittunggul jeung beulah kulona aya gunung Burangrang. Gunung Sunda ngajegir, jangkungna kira kira antara 3000-4000 meter, [[Gunung Tangkuban Parahu]] harita can aya.\nKira kira 375 rebu taun lilana Gunung Sunda ngajegir, nangtawing jadi tanda Tatar Sunda, nepi ka 125 rebu taun nu geus kaliwat Gunung Sunda mimiti bitu, sagala material gunung mancawura, bukti anu masih keneh katingal tug nepi ka kiwari nyaeta ayana \"Patahan Lembang\" anu panjangna kira-kira 22 km ngulon-ngetan, upami hoyong antra mah cobi tingali ti Maribaya beulah kidul, atawa di beulah kidul Pasar Lembang, tidinya atra katingal patahan Lembang. Tina metrial bituna Gunung Sunda teh diantarana nya ngajadikeun Talaga Bandung sok sanajan harita mah caina can pinuh pisan.\n\nSanggeus Gunung Sunda bitu, dina tengah tengah urut bituna mimiti bijil gunung anyar, nyaeta pisan cikal bakal Gunung Tangkuban Parahu, jadi Gunung Tangkuban Parahu teh anakna Gunung Sunda (purba).\nGunung T.Parahu bitu 70 rebu taun nu geus kaliwat, tah material tina bitu gunung T.Parahu tea nu leuwih numpuk ngajadikeun Talaga Bandung beuki ngalegaan nya nepi ka 35 rebu taun kaliwat nu dianggap panggedena cai Talaga Bandung.\n(Dina mangsa kiwari ge aya nu disebut Gunung Sunda di beulah kaler Gunung Tangkuban Parahu, ngan Gunung Sunda (kiwari) mah teu jangkung ngan ukur 1000 meteran.)\n \nDina mangsa kiwari lamun tea mah Gunung Tangkuban Parahu bitu deui ( da nepi ka ayeuna ge G.Tangkuban Parahu teh tetep dianggap gunung nu aktip), naha Talaga Bandung bakal kajadian deui...?\n\n== Bacaan salajengna ==\n* \'\'\'Bachtiar, T. & D. Syafriani.\'\'\' 2004. \'\'Bandung Purba\'\'. Masyarakat Geologi Indonesia. ISBN ....','/* Bacaan salajengna */',3,'Kandar','20041222042641','',0,0,0,0,0.969886177205,'20041222042641','79958777957358'); INSERT INTO cur VALUES (1726,10,'Wiktionary','{| border=\"0\" width=\"35%\" cellpadding=\"5\" class=\"noprint\" style=\"font-weight:none; float:right; border:solid #008 2px;margin-left:5px;margin-bottom:5px\" \n|-\n|[[Image:Wiktionary.png|50px|none|Wiktionary|]]\n|Tempo \'\'[http://su.wiktionary.org/wiki/{{PAGENAME}} {{PAGENAME}}]\'\' na kamus bébas [[Wiktionary]].\n|}','',3,'Kandar','20050225084322','',0,0,1,0,0.47690104436,'20050225084322','79949774915677'); INSERT INTO cur VALUES (1727,0,'Gamma_function','#REDIRECT [[Fungsi gamma]]\n','Gamma function dipindahkeun ka Fungsi gamma',3,'Kandar','20041124053134','',0,1,0,1,0.509120528823,'20041124053134','79958875946865'); INSERT INTO cur VALUES (1728,0,'Fungsi_beta','#REDIRECT [[Fungsi béta]]\n','Fungsi beta dipindahkeun ka Fungsi béta',3,'Kandar','20041124053220','',0,1,0,1,0.772929759125,'20041124053220','79958875946779'); INSERT INTO cur VALUES (1729,0,'Simple_random_sample','#REDIRECT [[Sampel acak basajan]]\n','Simple random sample dipindahkeun ka Sampel acak basajan',3,'Kandar','20041124054722','',0,1,0,1,0.858759927032,'20041124054722','79958875945277'); INSERT INTO cur VALUES (1730,6,'Sél_épitél.jpeg','ti Wikipédia Inggris\n\n[[en:Image:Epithelial-cells.jpg]]','',3,'Kandar','20041124055553','',0,0,0,0,0,'20041201104310','79958875944446'); INSERT INTO cur VALUES (1731,0,'Fullerin','\'\'[[image:bucky-c60.gif|right|Buckminsterfullerene (C60)]]\'\'\n\'\'\'Fullerin\'\'\' nyaéta [[molekul]] nu diwangun sagemblengna ku [[karbon]], nu ngabentuk bal \'\'[[sphere]]\'\', [[élipsoid]], solobong, cingcin, atawa [[planar (matematik)|planar]]. Dina basa Inggris katelah ogé \'\'buckyballs\'\'.\n\nNgaranna dicokot ti ngaran [[Richard Buckminster Fuller]], inohong arsiték nu nyiptakeun [[kubah géodésik]]. Kusabab \'\'buckminsterfullerenes\'\' mibanda bentuk nu sarupa jeung kubah éta, jadi baé diaranan kitu.\n\nFullerin sarupa bentukna jeung struktur [[grafit]], nu diwangun ku salambar cingcin héxagonal numbu, tapi cingcinnna péntagonal (atawa kadang héptagonal) nu nyegah lambaranana jadi planar. Fullerin nyolobong mindengna disebut [[tabungnano karbon|tabungnano]] (\'\'nanotubes\'\'). The smallest fullerene in which no two pentagons share an edge (which is destabilizing — see [[pentalene]]) is C60 (\'\'\'buckminsterfullerene\'\'\'), and as such it is also the most common.\n\nThe structure of C60 is that of a [[truncated icosahedron]], which resembles a round [[football (soccer)|soccerball]] of the type made of hexagons and pentagons, with a carbon atom at the corners of each hexagon and a bond along each edge. A polymerized single-walled nanotubule ([[P-SWNT]]) is a substance composed of polymerized fullerenes in which carbon atoms from one buckytube bond with carbons in other buckytubes. \n\nUntil the late [[twentieth century]], [[graphite]] and [[diamond]] were the only known [[allotrope]]s of [[carbon]]. Then, in molecular beam experiments, discrete peaks were observed corresponding to molecules with the exact mass of 60, 70, or greater numbers of carbon atoms. [[Harold Kroto]], from the [[University of Sussex]], [[James Heath]], [[Sean O\'Brien]], [[Robert Curl]] and [[Richard Smalley]], from [[Rice University]], discovered C60 and the fullerenes. Kroto, Curl, and Smalley were awarded the [[1996]] [[Nobel Prize]] in Chemistry for their roles in the discovery of this class of compounds. C60 and other fullerenes were later noticed occurring outside of a laboratory environment (e.g. in normal [[candle]] soot). By [[1991]] it was relatively easy to produce grams of fullerene powder using the techniques of [[Donald Huffman]] and [[Wolfgang Krätschmer]]. As of the early twenty-first century, the chemical and physical properties of fullerenes are still under heavy study, in both pure and applied research labs. In [[April]] [[2003]], fullerenes were under study for potential medicinal use — binding specific antibiotics to the structure to target resistant [[bacteria]] and even target certain cancer cells such as [[melanoma]]. In [[October]] [[2004]], researchers at the [[University of Manchester]]\nand [[Institute of Microelectronics Technology and High Purity Materials]][http://www.ipmt-hpm.ac.ru/] at [[Chernogolovka]] discovered the first two-dimensional fullerene, called [[graphene]].\n\nFullerenes are not very reactive due to the stability of the graphite-like bonds, and are also fairly insoluble in many [[solvent]]s. Researchers have been able to increase the reactivity by attaching active groups to the surfaces of fullerenes.\n\nOther atoms can be trapped inside fullerenes, and indeed recent evidence for a meteor impact at the end of the [[Permian]] period was found by analysing [[noble gas]]es so preserved. \n\n[[Superconductivity]] is one of the more recently explored properties.\n\nA common method used to produce fullerenes is to send a large current between two nearby graphite electrodes in an inert atmosphere. The resulting carbon plasma arc between the electrodes cools into sooty residue from which many fullerenes can be isolated.\n\n== Possible dangers ==\n\nAlthough buckyballs have been thought in theory to be relatively inert, a presentation given to the [[American Chemical Society]] in [[March]] [[2004]] and described in an article in [[New Scientist]] on [[April 3]] [[2004]], suggests the molecule is injurious to organisms. An experiment by Eva Oberdörster at the [[Southern Methodist University in Dallas]] which introduced fullerenes into water at concentrations of 0.5 parts per million found that largemouth bass suffered a 17-fold increase in cellular damage in the brain tissue after 48 hours. The damage was of the type [[lipid peroxidation]], which is known to impair the functioning of [[cell membrane]]s. There were also inflammatory changes in the liver and activation of genes related to the making of repair enzymes. At the time of presentation, the SMUD work had not been peer reviewed.\n\n==Tempo ogé==\n*[[Tabungnano karbon]]\n*[[grafin]]\n\n==Tumbu kaluar==\n* [http://cnst.rice.edu/ Center for Nanoscale Science and Technology]\n* [http://www.nobel.se/chemistry/laureates/1996/smalley-autobio.html Dr. Smalley\'s brief autobiography]\n* [http://www.chem.rice.edu/CHEM_faculty_dtl.cfm?FDSID=437 Dr. Smalley\'s webpage] \n* [http://www.sciencedaily.com//releases/2003/04/030418081522.htm Potential use of fullerenes in medicine]\n* [http://www.vincentherr.com/cf/ Carbon Fullerene & Nanotube Models ] Vincent Herr, Houston, TX\n* [http://www.physorg.com/news1667.html Discovery of graphene]\n\n[[Category:Unsur kimia|Karbon, Fullerin]]\n\n[[de:Fulleren]]\n[[en:Fullerene]]\n[[es:Fullereno]]\n[[fr:Fullerène]]\n[[ja:フラーレン]]\n[[pl:Fuleren]]\n[[ro:Fulerene]]\n[[fi:Fullereeni]]\n[[zh:富勒烯]]\n[[sv:Fulleren]]','/* External links */',3,'Kandar','20041124083503','',0,0,0,0,0.916979378051,'20050208111611','79958875916496'); INSERT INTO cur VALUES (1732,6,'Bucky-c60.gif','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041124083330','',0,0,0,1,0,'20041124083505','79958875916669'); INSERT INTO cur VALUES (1733,0,'Lisénsi_Dokumén_Bébas_GNU','\'\'\'Lisénsi Dokumén Bébas GNU\'\'\' (\'\'GNU Free Documentation License\'\', GFDL) nyaéta [[lisénsi]] \'\'[[copyleft]]\'\' pikeun eusi nu bébas. Disusun ku [[Free Software Foundation]] (FSF) pikeun proyék [[GNU]]. Téks resmi lisénsi vérsi 1.2 bisa ditingal di http://www.gnu.org/copyleft/fdl.html.\n\nLisénsi ieu dipaké pikeun sarupaning nu ditulis ngeunaan cara migunakeun \'\'software\'\', ogé pikeun tulisan séjén nu dipaké salaku acuan atawa pikeun nulungan anjeun dina naon baé.\n\nLisénsi ieu nyebutkeun yén anjeun diwidian pikeun nyalin atawa ngarubah tulisanana, sarta anjeun bisa ngajual salinan ieu. Mun anjeun ngajual dina jumlah nu réa, you have to make it easy for people make changes to it as well.\n\n[[Wikipédia]] migunakeun lisénsi ieu, sarta ngarupakeun proyék pangbadagna nu migunakeun lisénsi ieu.\n\nThe [[Debian]]-legal group thinks that the GFDL is not always free. It does not meet their Free Software Guidelines. \n\nYou have to add the [[copyright]] notice and you have to say it is GFDL if you want to copy it.\n\n\'\'Tempo ogé\'\': [[Text Of The GNU Free Documentation License]] and the simplified version of it at [[Simple English GFDL]].\n\n=== Tumbu kaluar ===\n\n*[http://www.gnu.org/copyleft/fdl.html Téks lisénsi resmi]\n\n\'\'\'Catetan: Wikipédia teu ngalayanan advis hukum\'\'\'\n\n[[ca:GNU Free Documentation License]]\n[[cy:GNU FDL]]\n[[da:GNU Free Documentation License]]\n[[de:GNU Freie Dokumentationslizenz]]\n[[en:GNU Free Documentation License]]\n[[eo:GFDL]]\n[[es:Licencia de Documentación Libre GNU]]\n[[fr:Licence de documentation libre GNU]]\n[[fy:GNU/FDL]]\n[[hu:GFDL v1.1]]\n[[id:GFDL]]\n[[it:GNU Free Documentation License]]\n[[ja:GNU FDL]]\n[[ku:Lîsansa Belgekirina Azada GNU]]\n[[nl:GNU Vrije Documentatie Licentie]]\n[[oc:Licéncia de documentacion liura GNU]]\n[[pl:GNU Free Documentation License]]\n[[pt:GNU FDL]]\n[[ro:GNU FDL]]\n[[simple:GNU Free Documentation License]]\n[[sl:GNU FDL]]\n[[sr:ГНУ-ова ЛСД]]\n[[sv:GNU FDL]]\n[[vi:GNU FDL]]\n[[zh-cn:GNU自由文档协议证书]]\n[[zh-tw:GNU自由文檔許可證書]]','',3,'Kandar','20041124093928','',0,0,0,1,0.624266663391,'20041124093928','79958875906071'); INSERT INTO cur VALUES (1735,0,'Model_grapik','#REDIRECT [[Modél grafik]]\n','Model grapik dipindahkeun ka Modél grafik',3,'Kandar','20041124105044','',0,1,0,1,0.178943626666,'20041124105044','79958875894955'); INSERT INTO cur VALUES (1736,0,'Probability_theory','#REDIRECT [[Tiori probabiliti]]\n','Probability theory dipindahkeun ka Tiori probabiliti',3,'Kandar','20041124105943','',0,1,0,1,0.230110107097,'20041124105943','79958875894056'); INSERT INTO cur VALUES (1737,0,'Deret_waktu','#REDIRECT [[Dérét waktu]]\n','Deret waktu dipindahkeun ka Dérét waktu',3,'Kandar','20041125020505','',0,1,0,1,0.175844182342,'20041125020505','79958874979494'); INSERT INTO cur VALUES (1738,0,'Politik','#REDIRECT [[Pulitik]]\n','Politik dipindahkeun ka Pulitik',3,'Kandar','20041125033057','',0,1,0,1,0.879682421628,'20041125033057','79958874966942'); INSERT INTO cur VALUES (1739,0,'Province','#REDIRECT [[Propinsi]]\n','Province dipindahkeun ka Propinsi',3,'Kandar','20041125035840','',0,1,0,1,0.926164199564,'20041125035840','79958874964159'); INSERT INTO cur VALUES (1740,0,'Kolmogorov-Smirnov_tes','#REDIRECT [[Uji Kolmogorov-Smirnov]]\n','Kolmogorov-Smirnov tes dipindahkeun ka Uji Kolmogorov-Smirnov',3,'Kandar','20041125042350','',0,1,0,1,0.730683511463,'20041125042350','79958874957649'); INSERT INTO cur VALUES (1741,0,'Daptar_istilah','Di handap ieu ngarupakeun daptar istilah [[Sunda]] nu dilarapkeun pikeun narjamahkeun istilah-istilah nu can ilahar dipikawanoh/aya dina [[basa Sunda]]. Pami sadérék mendak istilah nu langkung cocog/payus nu sawanda sareng istilah aslina (nu na [[basa Inggris]]), mangga sawalakeun di dieu: langsung robih eusina atanapi simpen catetan na rohangan \'\'\'sawala\'\'\'na (klik tumbu \'\'sawala\'\' di luhur).\n\n* [[Kantétan]] = lampiran, \'\'attachment\'\'\n* [[Koropak]] = \'\'file\'\'\n* [[Jalaloka]] = \'\'website\'\'\n* [[Sungsi]], nyungsi, panyungsi = \'\'browse\'\', \'\'browsing\'\', \'\'browser\'\'\n* [[Surélék]], surat éléktronik = \'\'e-mail\'\', \'\'electronic mail\'\'\n* [[Tumbu]] = \'\'pranala\'\', \'\'link\'\'\n\n[[Category:Sunda]]','',3,'Kandar','20041203180453','',0,0,0,0,0.278871331494,'20041203180453','79958796819546'); INSERT INTO cur VALUES (1742,0,'Unsur_kimiawi','#REDIRECT [[Unsur kimia]]\n','Unsur kimiawi dipindahkeun ka Unsur kimia',3,'Kandar','20041125062245','',0,1,0,1,0.600184484664,'20041125062245','79958874937754'); INSERT INTO cur VALUES (1743,0,'Sanyawa_kimiawi','#REDIRECT [[Sanyawa kimia]]\n','Sanyawa kimiawi dipindahkeun ka Sanyawa kimia',3,'Kandar','20041125062326','',0,1,0,1,0.979353109365,'20041125062326','79958874937673'); INSERT INTO cur VALUES (1744,0,'Zat_kimiawi','#REDIRECT [[Zat kimia]]\n','Zat kimiawi dipindahkeun ka Zat kimia',3,'Kandar','20041125062724','',0,1,0,1,0.160910455585,'20041125062724','79958874937275'); INSERT INTO cur VALUES (1745,0,'Beungkeut_kimiawi','#REDIRECT [[Beungkeut kimia]]\n','Beungkeut kimiawi dipindahkeun ka Beungkeut kimia',3,'Kandar','20041125062856','',0,1,0,1,0.643700357826,'20041125062856','79958874937143'); INSERT INTO cur VALUES (1746,0,'Bahan_kimiawi','#REDIRECT [[Bahan kimia]]\n','Bahan kimiawi dipindahkeun ka Bahan kimia',3,'Kandar','20041125062904','',0,1,0,1,0.209155619242,'20041125062904','79958874937095'); INSERT INTO cur VALUES (1747,0,'Réaksi_kimiawi','\'\'\'Réaksi kimiawi\'\'\' ogé dipiwanoh salaku [[parobahan]] [[zat kimia|kimiawi]], nu maksudna nyaéta parobahan dina [[struktur]] [[molekul]]. Réaksi ieu bisa mangrupa napelna hiji molekul kanu séjén ngahasilkeun molekul nu leuwih gedé, molekul beulah jadi dua atawa leuwih molekul nu leuwih leutik, atawa [[wangun ulang]] [[atom]]-atom jeroeun molekul. Réaksi kimiawi salawasna ngalibetkeun dibentuk atawa dipegatkeunana [[beungkeut kimia]].\n\n==Rupa-rupa==\nAya sababaraha rupa réaksi kimiawi dasar:\n*\'\'Sintésis\'\' nu diwangun ku dua atawa leuwih atom, ion, atawa molekul mandiri nu ngahiji jadi hiji zat anyar.
    \n
    A + B → AB
    \n*\'\'Dékomposisi\'\' nu sabalikna ti sintésis, nalika hiji sanyawa beulah jadi dua atawa leuwih atom, ion, atawa molekul mandiri.
    \n
    AB → A + B
    \n*Dina réaksi nukeuran tunggal, salasahiji atom diganti ku atom séjén.
    \n
    A + BC → B + AC
    \n*Dina réaksi nukeuran ganda (ogé katelah [[métatésis]]), atom-atom nu kabeungkeut na sakabéh réaktan silih tukeurkeun.
    \n
    AB + CD → AD + CB
    \n*Dina réaksi oksidasi-réduksi (ogé katelah [[réaksi rédoks]]), hiji réaktan ngaleupaskeun éléktron (molekulna dioksidasi), sedengkeun réaktan nu séjénna narima éléktron (molekulna diréduksi). Réaktan nu dioksidasi ngarupakeun [[agén pangréduksi]], sedengkeun réaktan nu diréduksi salaku [[agén pangoksidasi]].
    \n
    A + B → A+ + B-
    \n\nRéaksi kimiawi teu ngarobah [[inti atom]], nu robah ukur interaksi awan [[éléktron]] na atom-atom nu kalibet (parobahan wangunan inti atom disebutna [[réaksi inti]], jeung teu dianggap salaku réaksi kimiawi, sanajan réaksi kimiawi bisa nuturkeun transformasi inti).\n\nRéaksi kimiawi ampir salawasna ngalibetkeun parobahan [[énergi]], nu pangmerenahna/panggampangna diukur dina parobahan [[panas]]. Béda énergi antara kaayaan \"méméh\" jeung \"sanggeus\" réaksi kimia bisa diitung sacara téoritis maké tabel data (atawa komputer). Pikeun conto, misalkeun réaksi CH4 + 2 O2 → CO2 + 2 H2O (ngadurukan [[métan]] dina [[oksigén]]). Ku jalan ngitung jumlah énergi nu diperlukeun pikeun megatkeun sakabéh beungkeut nu beulah kénca (\"méméh\") jeung katuhu (\"sanggeus\") \'\'persamaan\'\', urang bisa ngitung béda énergi antara réaktan jeung produkna. Ieu disebutna ΔH, di mana Δ (Délta) ngandung harti béda, sedengkeun H salaku [[éntalpi]], ukuran énergi nu sarua jeung panas nu dipindahkeun dina kaayaan \'\'tekanan\'\' angger (konstan). ΔH biasana ditunjukkeun dina unit kJ (rebuan [[joule]]) atawa dina kkal ([[Kalori|kilokalori]]). Mun réaksi ΔH-na négatip, mangka énergi dileupaskeun. Réaksi rupa kieu disebutna [[éksotérmik]] (hartina panas luar atawa miceun panas). Réaksi éksotérmik leuwih dipikaresep sahingga leuwih gampang lumangsung. Conto réaksi nu tadi éksotérmik, nu geus biasa urang manggihan sapopoé, sabab ngaduruk gas dina hawa ngaluarkeun panas.\n\nRéaksi bisa boga ΔH positip, hartina, sangkan bisa lumangsung, réaksi butuh asupan énergi ti luar. Réaksi rupa kieu disebut [[éndotérmik]] (hartina panas jero atawa nyerep panas).\n\n==[[Laju réaksi]]==\nLaju réaksi kimiawi gumantung ka:\n*[[Konséntrasi]] [[réaktan]]\n*[[Énergi aktivasi]]\n*[[Temperatur]]\n*Aya henteuna [[katalis]].\n\n==Kabisamalikan==\nUnggal réaksi kimiawi sacara téoritis bisa malik (\'\'reversible\'\').\nDina hiji \'\'réaksi maju\'\' [[réaktan]] dirobah jadi [[produk]], kitu ogé sabalikna. [[Kasatimbangan kimiawi]] ngarupakeun kaayaan nalika laju réaksi maju jeung sabalikna sarua, sahingga nahan jumlah réaktan jeung produkna.\n\nSanajan sakabéh réaksi bisa malik, sababaraha réaksi bisa kagolongkeun teu bisa malik (\'\'irreversible\'\'). \'\'Réaksi teu bisa malik\'\' bisa lumaku mun dina kasatimbangan ampir sakabéh molekul réaktan geus robah jadi produk.\n\n==[[Hukum polah massa]]==\nKonséntrasi réaktan jeung produk nangtukeun laju boh réaksi maju jeung malik.\n\n==Katalis==\nKatalis teu ruksak dina réaksi kimiawi, tapi nulung pikeun nurunkeun énergi nu dipikabutuh pikeun aktivasi sahingga ningkatkeun laju réaksi.\n\n==Tempo ogé==\n[[Sintésis kimiawi]], \'\'[[Persamaan kimiawi]]\'\'\n\n[[ca:Reacció química]] [[de:Chemische Reaktion]] [[en:Chemical reaction]] [[es:Reacción química]] [[fr:Réaction chimique]] [[ja:化学反応]] [[nds:Chemisch Reaktschonen]] [[nl:Chemische reactie]] [[pl:Reakcja chemiczna]]','',3,'Kandar','20041125063113','',0,0,0,0,0.843181888966,'20041125063113','79958874936886'); INSERT INTO cur VALUES (1748,0,'Wanci','Méméh aya sistim poé nu kabagi kana 24 [[jam]], masarakat [[Sunda]] migunakeun istilah-istilah \'\'\'wanci\'\'\' minangka tanggara dina sapoé sapeuting. Kiwari, sanajan geus wanoh jeung ukuran wanci dina jam-jaman, di lembur masih kénéh diparaké. Istilah-istilahna di antarana:\n*tengah peuting kira-kira tabuh 24.00\n*usum tumorék kira-kira tabuh 24.30\n*janari leutik kira-kira tabuh 01.30\n*janari gedé kira-kira tabuh 02.00\n*disada rorongkéng (kongkorongok hayam sakali) kira-kira tabuh 02.30\n*haliwawar kira-kira tabuh 03.00\n*kongkorongok hayam dua kali kira-kira 03.30\n*janari kira-kira 04.00\n*subuh kira-kira tabuh 04.30\n*balébat kira-kira tabuh 05.00\n*carangcang tihang kira-kira tabuh 05.30\n*isuk-isuk kira-kira tabuh 06.00\n*murag ciibun kira-kira tabuh 07.00\n*pecat sawed kira-kira tabuh 09.00\n*haneut moyan kira-kira tabuh 10.00\n*rumangsang kira-kira tabuh 11.00\n*tengah poé/lohor kira-kira tabuh 12.00\n*mengok kira-kira tabuh 13.00\n*lingsir ngulon kira-kira tabuh 14.00\n*asar kira-kira tabuh 15.00\n*paososoré kira-kira tabuh 16.00\n*ngampih laleur kira-kira tabuh 17.00\n*tunggang gunung kira-kira tabuh 17.30\n*sariak layung kira-kira tabuh 18.00\n*sareupna/magrib kira-kira tabuh 18.15\n*harieum beungeut kira-kira tabuh 18.30\n*isa kira-kira tabuh 19.00\n*sareureuh budak kira-kira 21.00\n*sareureuh kolot kira-kira tabuh 21.30\n*peuting kira-kira tabuh 23.00\n\n[[Category:Sunda]]','',3,'Kandar','20050309112905','',0,0,1,0,0.617855018758,'20050309112905','79949690887094'); INSERT INTO cur VALUES (1749,10,'Bukuwiki','{| border=\"0\" width=\"35%\" cellpadding=\"5\" class=\"noprint, floatright\" style=\"float: right; border:solid #008 2px; margin:0em 0em 0.5em 0.5em; width:35%;\" \n|-\n|[[Image:Wiki-textbook.png|50px|none|Bukuwiki|]]\n|\'\'\'[[Wikibooks|Bukuwiki]] boga buku téks [[wikibooks:{{PAGENAME}}|ngeunaan \'\'{{PAGENAME}}\'\']].\'\'\'\n|}','',3,'Kandar','20041125094015','',0,0,0,1,0.389846519749,'20041125094015','79958874905984'); INSERT INTO cur VALUES (1750,0,'Formula','#REDIRECT [[Rumus]]\n','Formula dipindahkeun ka Rumus',3,'Kandar','20041125094331','',0,1,0,1,0.77891279607,'20041125094331','79958874905668'); INSERT INTO cur VALUES (1751,0,'Regression','#REDIRECT [[Régrési]]\n','Regression dipindahkeun ka Régrési',3,'Kandar','20041125100125','',0,1,0,1,0.073331223835,'20041125100125','79958874899874'); INSERT INTO cur VALUES (1752,0,'Rao-Blackwell_theorem','#REDIRECT [[Téoréma Rao-Blackwell]]\n','Rao-Blackwell theorem dipindahkeun ka Téoréma Rao-Blackwell',3,'Kandar','20041125100417','',0,1,0,1,0.808298929505,'20041125100417','79958874899582'); INSERT INTO cur VALUES (1753,0,'Lehmann-Scheffé_theorem','#REDIRECT [[Téoréma Lehmann-Scheffé]]\n','Lehmann-Scheffé theorem dipindahkeun ka Téoréma Lehmann-Scheffé',3,'Kandar','20041125100552','',0,1,0,1,0.512350741547,'20041125100552','79958874899447'); INSERT INTO cur VALUES (1754,0,'Sunda','Kecap \'\'\'Sunda\'\'\' bisa nujul ka rupa-rupa harti nu sacara umum patali jeung wewengkon bagian kulon kapuloan [[Indonésia]]. Catetan sajarah pangheubeulna nu nyebut-nyebut kecap Sunda nyaéta [[prasasti]] [[prasasti Kebonkopi|Kebonkopi 2]] nu dijieun taun [[536]] M (atawa 458 [[Saka]]) (aya ogé nu boga pamanggih yén prasasti ieu dijieun taun [[932]] M, atawa 854 Saka) nu nujul ka [[karajaan Sunda]].\n\nKecap ieu sigana asalna tina [[basa Sangsakerta]] nu bisa ngandung harti \'cahya\' atawa \'cai\'.\n \n* [[urang Sunda]]\n* [[Tatar Sunda]]\n* [[Basa Sunda]]\n* [[Daratan Sunda]]\n* [[Karajaan Sunda]]\n\n===Tempo ogé===\n* [[Kisunda]]\n* [[Kapuloan Sunda Gedé]]\n* [[Kapuloan Sunda Leutik]]\n\n==Tumbu kaluar==\n{{Wiktionary}}\n* [http://www.urang-sunda.or.id Jalaloka KUSnét (Komunitas Urang Sunda di Internét)]\n* [http://www.sundanet.com/ SundaNet.Com: portal komunitas Sunda]\n\n\n{{pondok}}\n\n[[Category:Sunda]]','/* Tumbu kaluar */',3,'Kandar','20050309113904','',0,0,1,0,0.584474579238,'20050309113904','79949690886095'); INSERT INTO cur VALUES (1755,2,'Andre_Engels','I am an Interwiki-user from the Dutch Wikipedia.\n\n[[nl:Gebruiker:Andre Engels]]','',28,'Andre Engels','20041126160415','',0,0,0,1,0.120220120121,'20041126160415','79958873839584'); INSERT INTO cur VALUES (1756,2,'Robbot','Robbot is a Robot, programmed by [[User:Rob Hooft|Rob Hooft]] and others and operated by [[User:Andre Engels|Andre Engels]]. It is mostly used for adding and correcting Interwiki-links.','',28,'Andre Engels','20041126160537','',0,0,0,1,0.318442227467,'20041126160537','79958873839462'); INSERT INTO cur VALUES (1757,0,'Quantitative_psychological_research','#REDIRECT [[Panalungtikan psikologi kuantitatif]]\n','Quantitative psychological research dipindahkeun ka Panalungtikan psikologi kuantitatif',3,'Kandar','20041129054255','',0,1,0,1,0.686110209993,'20041129054255','79958870945744'); INSERT INTO cur VALUES (1758,1,'Linear_programming','max z=2x+3y\n4x+5y<2\nx,y>=0','',0,'217.218.36.111','20041130101142','',0,0,0,1,0.528982057482,'20041130101142','79958869898857'); INSERT INTO cur VALUES (1759,6,'Panonpoé.jpeg','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20041201062759','',0,0,0,1,0,'20041201070151','79958798937240'); INSERT INTO cur VALUES (1760,6,'Panonpoé_SOHO.gif','salinan foto panonpoé ti SOHO','salinan foto panonpoé ti SOHO',3,'Kandar','20041201063855','',0,0,0,1,0,'20041201070151','79958798936144'); INSERT INTO cur VALUES (1761,0,'Kadaharan','#REDIRECT [[Pangan]]\n','Kadaharan dipindahkeun ka Pangan',3,'Kandar','20041201075450','',0,1,0,1,0.713644005691,'20041201075450','79958798924549'); INSERT INTO cur VALUES (1762,0,'Achdiat_Karta_Mihardja','\'\'\'Achdiat Karta Mihardja\'\'\' sastrawan nu ngarang [[novél]] kawentar [[Athéis]], lahir di [[Garut]], [[6 Maret]] [[1911]]. Ti taun [[1961]] matuh di [[Australia]].\n\n\n{{pondok}}\n[[Category:Sastrawan]]','',3,'Kandar','20050125054712','',0,0,0,0,0.01870150865,'20050315084342','79949874945287'); INSERT INTO cur VALUES (1763,0,'Onom','\'\'\'Onom\'\'\' nyaéta salasahiji sebutan pikeun sarupaning bangsa [[lelembut]], utamana nu ngageugeuh wewengkon [[ranca]]/[[Rawa Lakbok|rawa]] [[Lakbok]], [[Ciamis]].\n\n\n{{pondok}}\n\n[[Category:Sunda]]','',3,'Kandar','20041203031919','',0,0,0,0,0.37648332835,'20050303211247','79958796968080'); INSERT INTO cur VALUES (1764,0,'Rawa_Lakbok','\'\'\'Rawa Lakbok\'\'\' nyaéta ngaran hiji [[ranca|rawa]] nu aya di wewengkon [[Lakbok]], Ciamis, deukeut [[Banjar]], [[Jawa Barat]], dina koordinat 7°24\' Kidul, 108°31\' Wétan. Rawa Lakbok ngarupakeun rawa [[gambut]], legana nepi ka 3000 héktar, nu meureun panglegana di [[Indonésia]] di antara nu satipe, jerona antara 6 nepi ka 10 méter. [[Réklamasi]] rawa Lakbok geus kungsi dipigawé ti taun [[1924]] kénéh.\n\nRawa Lakbok baheulana dieusi ku rupa-rupa spésiés jujukutan nu kiwari geus langka di pulo [[Jawa]], kayaning \'\'Ficus retusa\'\', \'\'Elaeocarpus littoralis\'\', \'\'Nephralepis radicans\'\', \'\'Scirpodendron ghaeni\'\', \'\'Flascopa scand ens\'\', \'\'Stenochlaena palustris\'\', jeung \'\'Licuala sp\'\'.\n\n\n{{pondok}}','',3,'Kandar','20041203040720','',0,0,0,0,0.454505247276,'20050303211247','79958796959279'); INSERT INTO cur VALUES (1766,0,'Kérod_salawé','[[image:parabot_lalaki.png|thumb|300px|\'Parabot lalaki\']]\n\n\'\'\'Kérod salawé\'\'\' atawa \'\'\'bool\'\'\' (Ing. \'\'anus\'\'), na [[anatomi]], nyaéta palawangan [[réktum]], nu dikadalikeun ku [[otot]] \'\'[[sphincter]]\'\'. [[Tai]] (Ing. \'\'feces\'\') dikaluarkeun tina awak ngaliwatan kérod salawé nalika [[ngising]] (\'\'defecation\'\'), nu ngarupakeun fungsi utamana. \n\n== Anatomi jeung fungsi kérod salawé ==\n\nKérod salawé aya di antara [[bujur|imbit]], tukangeun [[perineum]]. Kérod salawé mibanda dua \'\'[[anal sphincter]]\'\', hiji di jero, hiji deui di luar, nu fungsina ngajaga sangkan anus tetep nutup nepi ka waktuna ngising.\n\nNalika [[réktum]] pinuh, naékna tekenan intraréktal ngadorong dinding torowongan anus ngabadagan sahingga kaasupan pitaieun. Nalika pitaieun didorong kana torowongan, réktum mondokan sarta gelombang peristaltis ngadorong tai kaluar réktum. \'\'Sphincter\'\' luar jeung jero anus salajengna metot otot ngaluarkeun taina.\n\n== Patologi anal ==\n\n* [[Anal fissure]]\n* [[Ambéien]] (\'\'Hemorrhoids\'\')\n* [[Kangker anal]]\n* [[Fecal incontinence]]\n* [[Anal fistula]]\n* [[Anal abscess]]es\n\n==Tempo ogé==\n\n* [[enema]]\n* [[kloaka]]\n* [[suppository]]\n* [[flatulence]]\n\n{{digestive system}}\n\n[[Category:Digestive system]]\n\n[[de:Anus]]\n[[en:Anus]]\n[[fr:Anus]]\n[[he:פי הטבעת]]\n[[ja:肛門]]\n[[nl:Anus]]\n[[pl:Odbyt]]\n[[zh:肛门]]','/* Tempo ogé */',3,'Kandar','20041203131837','',0,0,0,0,0.02937920067,'20041203131837','79958796868162'); INSERT INTO cur VALUES (1767,0,'31_Januari','* [[Ajip Rosidi]], sastrawan-budayawan Sunda kahot lahir taun [[1938]] di [[Jatiwangi]], [[Majalngka]].','',3,'Kandar','20041203165032','',0,0,0,1,0.183328616518,'20041203165032','79958796834967'); INSERT INTO cur VALUES (1768,0,'Moment_(mathematics)','#REDIRECT [[Momen (matematik)]]\n','Moment (mathematics) dipindahkeun ka Momen (matematik)',3,'Kandar','20041203173307','',0,1,0,1,0.515013502219,'20041203173307','79958796826692'); INSERT INTO cur VALUES (1769,0,'P-value','#REDIRECT [[Ajén-P]]\n','P-value dipindahkeun ka Ajén-P',3,'Kandar','20041203175641','',0,1,0,1,0.847026023011,'20041203175641','79958796824358'); INSERT INTO cur VALUES (1770,0,'Compositional_data','#REDIRECT [[Komposisi data]]\n','Compositional data dipindahkeun ka Komposisi data',13,'Budhi','20041203234705','',0,1,0,1,0.707551995622,'20041203234705','79958796765294'); INSERT INTO cur VALUES (1772,0,'Ergodic_hypothesis','#REDIRECT [[Hipotesa ergodik]]\n','Ergodic hypothesis dipindahkeun ka Hipotesa ergodik',13,'Budhi','20041204015414','',0,1,0,1,0.720110702664,'20041204015414','79958795984585'); INSERT INTO cur VALUES (1773,0,'Probability_of_error','#REDIRECT [[Eror probabiliti]]\n','Probability of error dipindahkeun ka Eror probabiliti',13,'Budhi','20041204022949','',0,1,0,1,0.453467346008,'20041204022949','79958795977050'); INSERT INTO cur VALUES (1774,0,'Tolerance_interval','#REDIRECT [[Rentang tolérans]]\n','Tolerance interval dipindahkeun ka Rentang tolérans',3,'Kandar','20041218130845','',0,1,0,1,0.046034343096,'20041218130845','79958781869154'); INSERT INTO cur VALUES (1776,0,'Incomplete_beta_function','#REDIRECT [[Fungsi béta teu lengkep]]\n','Incomplete beta function dipindahkeun ka Fungsi béta teu lengkep',3,'Kandar','20041221110755','',0,1,0,1,0.709746191609,'20041221110755','79958778889244'); INSERT INTO cur VALUES (1777,0,'Markov_chain','#REDIRECT [[Ranté Markov]]\n','Markov chain dipindahkeun ka Ranté Markov',3,'Kandar','20041222033612','',0,1,0,1,0.939069099696,'20041222033612','79958777966387'); INSERT INTO cur VALUES (1778,0,'Stochastic_process','#REDIRECT [[Prosés stokastik]]\n','Stochastic process dipindahkeun ka Prosés stokastik',3,'Kandar','20041222033842','',0,1,0,1,0.072904205449,'20041222033842','79958777966157'); INSERT INTO cur VALUES (1779,0,'Variabel_random','#REDIRECT [[Variabel acak]]\n','Variabel random dipindahkeun ka Variabel acak',3,'Kandar','20041222033901','',0,1,0,1,0.087429120712,'20041222033901','79958777966098'); INSERT INTO cur VALUES (1780,0,'Function_(mathematics)','#REDIRECT [[Fungsi (matematik)]]\n','Function (mathematics) dipindahkeun ka Fungsi (matematik)',3,'Kandar','20041222034958','',0,1,0,1,0.965895600601,'20041222034958','79958777965041'); INSERT INTO cur VALUES (1781,0,'Brownian_motion','#REDIRECT [[Gerak Brown]]\n','Brownian motion dipindahkeun ka Gerak Brown',3,'Kandar','20041222035517','',0,1,0,1,0.40245025484,'20041222035517','79958777964482'); INSERT INTO cur VALUES (1782,0,'Tabel_periodik_(baku)','{|style=\"width: 100%\"\n|-\n|[[Golongan tabel periodik|\'\'\'Golongan\'\'\' →]]\n|[[Unsur golongan 1|\'\'\'1\'\'\']]\n|[[Unsur golongan 2|\'\'\'2\'\'\']]\n| \n|[[Unsur golongan 3|\'\'\'3\'\'\']]\n|[[Unsur golongan 4|\'\'\'4\'\'\']]\n|[[Unsur golongan 5|\'\'\'5\'\'\']]\n|[[Unsur golongan 6|\'\'\'6\'\'\']]\n|[[Unsur golongan 7|\'\'\'7\'\'\']]\n|[[Unsur golongan 8|\'\'\'8\'\'\']]\n|[[Unsur golongan 9|\'\'\'9\'\'\']]\n|[[Unsur golongan 10|\'\'\'10\'\'\']]\n|[[Unsur golongan 11|\'\'\'11\'\'\']]\n|[[Unsur golongan 12|\'\'\'12\'\'\']]\n|[[Unsur golongan 13|\'\'\'13\'\'\']]\n|[[Unsur golongan 14|\'\'\'14\'\'\']]\n|[[Unsur golongan 15|\'\'\'15\'\'\']]\n|[[Unsur golongan 16|\'\'\'16\'\'\']]\n|[[Unsur golongan 17|\'\'\'17\'\'\']]\n|[[Unsur golongan 18|\'\'\'18\'\'\']]\n|-\n|[[Periode tabel periodik|\'\'\'Periode\'\'\' ↓]]\n|colspan=\"20\"|
    \n|-\n|[[Unsur periode 1|\'\'\'1\'\'\']]\n|style=\"text-align:center;background-color:#a0ffa0;color:red;border:1px solid black;\"|1
    [[Hydrogen|H]]\n|colspan=\"17\"|
    \n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px solid black;\"|2
    [[Helium|He]]\n|-\n|[[Unsur periode 2|\'\'\'2\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px solid black;\"|3
    [[Lithium|Li]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px solid black;\"|4
    [[Beryllium|Be]]\n|colspan=\"11\"|
    \n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|5
    [[Boron|B]]\n|style=\"text-align:center;background-color:#a0ffa0;color:black;border:1px solid black;\"|6
    [[Carbon|C]]\n|style=\"text-align:center;background-color:#a0ffa0;color:red;border:1px solid black;\"|7
    [[Nitrogen|N]]\n|style=\"text-align:center;background-color:#a0ffa0;color:red;border:1px solid black;\"|8
    [[Oxygen|O]]\n|style=\"text-align:center;background-color:#ffff99;color:red;border:1px solid black;\"|9
    [[Fluorine|F]]\n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px solid black;\"|10
    [[Neon|Ne]]\n|-\n|[[Unsur periode 3|\'\'\'3\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px solid black;\"|11
    [[Sodium|Na]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px solid black;\"|12
    [[Magnesium|Mg]]\n|colspan=\"11\"|
    \n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|13
    [[Aluminium|Al]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|14
    [[Silicon|Si]]\n|style=\"text-align:center;background-color:#a0ffa0;color:black;border:1px solid black;\"|15
    [[Phosphorus|P]]\n|style=\"text-align:center;background-color:#a0ffa0;color:black;border:1px solid black;\"|16
    [[Sulfur|S]]\n|style=\"text-align:center;background-color:#ffff99;color:red;border:1px solid black;\"|17
    [[Chlorine|Cl]]\n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px solid black;\"|18
    [[Argon|Ar]]\n|-\n|[[Unsur periode 4|\'\'\'4\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px solid black;\"|19
    [[Potassium|K]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px solid black;\"|20
    [[Calcium|Ca]]\n|
    \n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|21
    [[Scandium|Sc]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|22
    [[Titanium|Ti]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|23
    [[Vanadium|V]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|24
    [[Chromium|Cr]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|25
    [[Manganese|Mn]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|26
    [[Iron|Fe]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|27
    [[Cobalt|Co]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|28
    [[Nickel|Ni]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|29
    [[Copper|Cu]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|30
    [[Zinc|Zn]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|31
    [[Gallium|Ga]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|32
    [[Germanium|Ge]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|33
    [[Arsenic|As]]\n|style=\"text-align:center;background-color:#a0ffa0;color:black;border:1px solid black;\"|34
    [[Selenium|Se]]\n|style=\"text-align:center;background-color:#ffff99;color:green;border:1px solid black;\"|35
    [[Bromine|Br]]\n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px solid black;\"|36
    [[Krypton|Kr]]\n|-\n|[[Unsur periode 5|\'\'\'5\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px solid black;\"|37
    [[Rubidium|Rb]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px solid black;\"|38
    [[Strontium|Sr]]\n|
    \n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|39
    [[Yttrium|Y]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|40
    [[Zirconium|Zr]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|41
    [[Niobium|Nb]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|42
    [[Molybdenum|Mo]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dashed black;\"|43
    [[Technetium|Tc]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|44
    [[Ruthenium|Ru]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|45
    [[Rhodium|Rh]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|46
    [[Palladium|Pd]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|47
    [[Silver|Ag]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|48
    [[Cadmium|Cd]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|49
    [[Indium|In]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|50
    [[Tin|Sn]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|51
    [[Antimony|Sb]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px solid black;\"|52
    [[Tellurium|Te]]\n|style=\"text-align:center;background-color:#ffff99;color:black;border:1px solid black;\"|53
    [[Iodine|I]]\n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px solid black;\"|54
    [[Xenon|Xe]]\n|-\n|[[Unsur periode 6|\'\'\'6\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px solid black;\"|55
    [[Caesium|Cs]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px solid black;\"|56
    [[Barium|Ba]]\n|style=\"vertical-align: top; text-align:center;background-color:#ffbfff;\"|*
    \n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|71
    [[Lutetium|Lu]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|72
    [[Hafnium|Hf]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|73
    [[Tantalum|Ta]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|74
    [[Tungsten|W]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|75
    [[Rhenium|Re]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|76
    [[Osmium|Os]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|77
    [[Iridium|Ir]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|78
    [[Platinum|Pt]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px solid black;\"|79
    [[Gold|Au]]\n|style=\"text-align:center;background-color:#ffc0c0;color:green;border:1px solid black;\"|80
    [[Mercury (element)|Hg]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|81
    [[Thallium|Tl]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|82
    [[Lead|Pb]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px solid black;\"|83
    [[Bismuth|Bi]]\n|style=\"text-align:center;background-color:#cccc99;color:black;border:1px dashed black;\"|84
    [[Polonium|Po]]\n|style=\"text-align:center;background-color:#ffff99;color:black;border:1px dashed black;\"|85
    [[Astatine|At]]\n|style=\"text-align:center;background-color:#c0ffff;color:red;border:1px dashed black;\"|86
    [[Radon|Rn]]\n|-\n|[[Unsur periode 7|\'\'\'7\'\'\']]\n|style=\"text-align:center;background-color:#ff6666;color:black;border:1px dashed black;\"|87
     [[Francium|Fr]]\n|style=\"text-align:center;background-color:#ffdead;color:black;border:1px dashed black;\"|88
    [[Radium|Ra]]\n|style=\"vertical-align: top; text-align:center;background-color:#ff99cc;\"|**
    \n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|103
    [[Lawrencium|Lr]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|104
    [[Rutherfordium|Rf]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|105
    [[Dubnium|Db]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|106
    [[Seaborgium|Sg]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|107
    [[Bohrium|Bh]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|108
    [[Hassium|Hs]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|109
    [[Meitnerium|Mt]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|110
    [[Darmstadtium|Ds]]\n|style=\"text-align:center;background-color:#ffc0c0;color:black;border:1px dotted black;\"|111
    [[Roentgenium|Rg]]\n|style=\"text-align:center;background-color:#ffc0c0;color:green;border:1px dotted black;\"|112
    [[Ununbium|Uub]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px dotted black;\"|113
    [[Ununtrium|Uut]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px dotted black;\"|114
    [[Ununquadium|Uuq]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px dotted black;\"|115
    [[Ununpentium|Uup]]\n|style=\"text-align:center;background-color:#cccccc;color:black;border:1px dotted black;\"|116
    [[Ununhexium|Uuh]]\n|style=\"text-align:center;background-color:#fcfecc;color:#cccccc;\"|117
    [[Ununseptium|Uus]]\n|style=\"text-align:center;background-color:#ecfefc;color:#cccccc;\"|118
    [[Ununoctium|Uuo]]\n|-\n|colspan=\"21\"|
    \n|-\n|colspan=\"4\" style=\"text-align:right\"|* \'\'\'[[Lanthanide]]s\'\'\'\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|57
    [[Lanthanum|La]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|58
    [[Cerium|Ce]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|59
    [[Praseodymium|Pr]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|60
    [[Neodymium|Nd]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px dashed black;\"|61
    [[Promethium|Pm]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|62
    [[Samarium|Sm]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|63
    [[Europium|Eu]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|64
    [[Gadolinium|Gd]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|65
    [[Terbium|Tb]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|66
    [[Dysprosium|Dy]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|67
    [[Holmium|Ho]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|68
    [[Erbium|Er]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|69
    [[Thulium|Tm]]\n|style=\"text-align:center;background-color:#ffbfff;color:black;border:1px solid black;\"|70
    [[Ytterbium|Yb]]\n|-\n|colspan=\"4\" style=\"text-align:right\"|** \'\'\'[[Actinide]]s\'\'\'\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dashed black;\"|89
    [[Actinium|Ac]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px solid black;\"|90
    [[Thorium|Th]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dashed black;\"|91
    [[Protactinium|Pa]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px solid black;\"|92
    [[Uranium|U]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dashed black;\"|93
    [[Neptunium|Np]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px solid black;\"|94
    [[Plutonium|Pu]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|95
    [[Americium|Am]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|96
    [[Curium|Cm]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|97
    [[Berkelium|Bk]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dashed black;\"|98
    [[Californium|Cf]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|99
    [[Einsteinium|Es]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|100
    [[Fermium|Fm]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|101
    [[Mendelevium|Md]]\n|style=\"text-align:center;background-color:#ff99cc;color:black;border:1px dotted black;\"|102
    [[Nobelium|No]]\n|}\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    [[Periodic table series|Deret Kimia Tabel Periodik]]
    [[Alkali metal]]s[[Alkaline earth metal]]s[[Lanthanide]]s[[Actinide]]s[[Transition metal]]s
    [[Poor metal]]s[[Metalloid]]s[[Nonmetal]]s[[Halogen]]s[[Noble gas]]es
    \n\n\'\'\'Wujud dina [[suhu jeung tekenan baku]] (Ing. \'\'standard temperature and pressure\'\')\n* nu beureum mangrupa gas\n* nu hejo mangrupa cairan\n* nu hideung mangrupa padet\n\n\'\'\'Ayana di alam\'\'\'\n*
    nu kotakanana garis leuwih kolot batan [[Marcapada]] ([[unsur primordial]])
    \n*
    nu kotakanana pegat-pegat mucunghul sacara alami tina \'\'decay\'\' unsur kimia sejen
    \n*
    nu kotakanana titik-titik teu aya sacara alami ([[unsur sintetik]])
    \n*
    nu teu make kotakan can kapanggih/disintesis
    \n\n== Tumbu kaluar ==\n*[http://www.webelements.com WebElements.com]\n\n{{TabelPeriodik}}\n[[Category:Tabel periodik]]\n\n[[en:Periodic table (standard)]]','/* Tumbu kaluar */',3,'Kandar','20041222063847','',0,0,0,0,0.1489404571,'20050203153547','79958777936152'); INSERT INTO cur VALUES (1783,0,'Surili','[[Image:Surili.jpeg|right|thumb|120px|Surili]]\n\'\'\'Surili\'\'\' (\'\'\'\'\'Presbytis comata\'\'\'\'\', génus \'\'[[Presbytis]]\'\', golongan [[Langur]], subfamili [[Colobinae]], famili [[Cercopithecidae]], superfamili [[Cercopithecoidea]]) ngarupakeun [[spésiés]] [[monyét]] éndemik wewengkon Tatar Sunda (Jawa Kulon-Tengah), utamana di wewengkon [[Ujung Kulon]], [[Leuweung Sancang]], [[Gunung Gedé]], [[Gunung Halimun]], [[Gunung Tilu]], jeung [[Gunung Patuha]]. Kusabab éndemik Jawa Kulon (wewengkon administratif [[Jawa Barat|Jabar]] jeung [[Banten]]), surili ieu dijadikeun salasahiji ikon [[sato]]/fauna Jabar.\n\n\n{{pondok}}\n\n[[Category:Sasatoan]]','',3,'Kandar','20041224021055','',0,0,0,0,0.284817014488,'20050303211247','79958775978944'); INSERT INTO cur VALUES (1784,0,'Water_cycle','#REDIRECT [[Daur cai]]\n','Water cycle dipindahkeun ka Daur cai',3,'Kandar','20041222101305','',0,1,0,1,0.12640571507,'20041222101305','79958777898694'); INSERT INTO cur VALUES (1785,0,'Factor_analysis','#REDIRECT [[Analisis faktor]]\n','Factor analysis dipindahkeun ka Analisis faktor',3,'Kandar','20041222101748','',0,1,0,1,0.353561351706,'20041222101748','79958777898251'); INSERT INTO cur VALUES (1786,8,'1movedto2_redir','$1 dipindahkeun ka $2','',3,'Kandar','20041229053135','sysop',0,0,0,0,0,'20041229053135','79958770946864'); INSERT INTO cur VALUES (1787,8,'Aboutsite','Ngeunaan {{SITENAME}}','',3,'Kandar','20041229053151','sysop',0,0,0,0,0,'20041229053151','79958770946848'); INSERT INTO cur VALUES (1788,8,'Addgroup','Tambahkeun Golongan','',3,'Kandar','20041229053217','sysop',0,0,0,0,0,'20041229053217','79958770946782'); INSERT INTO cur VALUES (1789,8,'Allarticles','Sadaya artikel','',3,'Kandar','20041229053228','sysop',0,0,0,0,0,'20041229053228','79958770946771'); INSERT INTO cur VALUES (1790,8,'Alllogstext','Témbongan gabungan log muatan, hapusan, koncian, peungpeukan, jeung kuncén. Bisa dipondokkeun ku cara milih tipe log, ngaran pamaké, atawa kaca nu dimaksud.','',3,'Kandar','20050221110522','sysop',0,0,1,0,0,'20050221110522','79949778889477'); INSERT INTO cur VALUES (1791,8,'AllmessagesnotsupportedDB','Special:AllMessages teu dirojong sabab wgUseDatabaseMessages pareum.','',3,'Kandar','20041229054034','sysop',0,0,0,0,0,'20041229054034','79958770945965'); INSERT INTO cur VALUES (1792,8,'AllmessagesnotsupportedUI','Basa \'\'interface\'\' anjeun kiwari $1 teu dirojong ku Special:AllMessages na loka ieu.','',3,'Kandar','20041229054144','sysop',0,0,0,0,0,'20041229054144','79958770945855'); INSERT INTO cur VALUES (1793,8,'Allpagesformtext1','Témbongkeun kaca mimiti $1','',3,'Kandar','20041229054207','sysop',0,0,0,0,0,'20041229054207','79958770945792'); INSERT INTO cur VALUES (1794,8,'Allpagesformtext2','Pilih spasingaran: $1 $2','',3,'Kandar','20041229054223','sysop',0,0,0,0,0,'20041229054223','79958770945776'); INSERT INTO cur VALUES (1795,8,'Allpagesnamespace','Sadaya kaca ($1 spasingaran)','',3,'Kandar','20041229054339','sysop',0,0,0,0,0,'20041229054339','79958770945660'); INSERT INTO cur VALUES (1796,8,'Allpagesnext','Salajengna','',3,'Kandar','20041229054300','sysop',0,0,0,0,0,'20041229054300','79958770945699'); INSERT INTO cur VALUES (1797,8,'Allpagesprev','Saméméhna','',3,'Kandar','20041229054310','sysop',0,0,0,0,0,'20041229054310','79958770945689'); INSERT INTO cur VALUES (1798,8,'Allpagessubmit','Jung','',3,'Kandar','20041229054314','sysop',0,0,0,0,0,'20041229054314','79958770945685'); INSERT INTO cur VALUES (1799,8,'Apr','Apr','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1800,8,'April','April','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1801,8,'Articlenamespace','(artikel)','',3,'Kandar','20041229054524','sysop',0,0,0,0,0,'20041229054524','79958770945475'); INSERT INTO cur VALUES (1802,8,'Asksqlpheading','asksql level','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1803,8,'Aug','Agu','',3,'Kandar','20041229054839','sysop',0,0,0,0,0,'20041229054839','79958770945160'); INSERT INTO cur VALUES (1804,8,'August','Agustus','',3,'Kandar','20041229054848','sysop',0,0,0,0,0,'20041229054848','79958770945151'); INSERT INTO cur VALUES (1805,8,'Block_compress_delete','Teu bisa ngahapus artikel ieu sabab ngandung block-compressed revisions. Ieu ngarupakeun kaayaan samentawis nu dipikanyaho ku developer, sarta bakal dilereskeun dina sabulan atawa dua bulan. Mangga tandaan yén artikel ieu rék dihapus, salajengna mah antosan baé developerna ngalereskeun \'\'software\'\'na.','',3,'Kandar','20041229055500','sysop',0,0,0,0,0,'20041229055500','79958770944499'); INSERT INTO cur VALUES (1806,8,'Blockpheading','hambalan peungpeuk','',3,'Kandar','20041229055622','sysop',0,0,0,0,0,'20041229055622','79958770944377'); INSERT INTO cur VALUES (1807,8,'Categoryarticlecount1','Aya $1 artikel na kategori ieu.','',3,'Kandar','20041229055727','sysop',0,0,0,0,0,'20041229055727','79958770944272'); INSERT INTO cur VALUES (1808,8,'Copyrightwarning2','Catet yén sadaya sumbangsih ka {{SITENAME}} bisa diédit, dirobah, atawa dihapus ku kontributor séjén. Mun anjeun teu hoyong tulisan anjeun dirobah, ulah ngintunkeun ka dieu.
    \nAnjeun ogé mastikeun yén ieu téh pituin tulisan anjeun, atawa salinan ti domain umum atawa sumberdaya bébas séjénna (tempo $1 pikeun écésna).\nULAH NGINTUNKEUN KARYA NU MIBANDA HAK CIPTA TANPA WIDI!','',3,'Kandar','20041229060451','sysop',0,0,0,0,0,'20041229060451','79958770939548'); INSERT INTO cur VALUES (1809,8,'Createaccountpheading','hambalan nyieun rekening','',3,'Kandar','20050203192416','sysop',0,0,0,0,0,'20050203192416','79949796807583'); INSERT INTO cur VALUES (1810,8,'Creditspage','Page credits','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1811,8,'Currentevents-url','Lumangsung kiwari','',3,'Kandar','20050204083910','sysop',0,0,0,0,0,'20050204083910','79949795916089'); INSERT INTO cur VALUES (1812,8,'Currentrevisionlink','Témbongkeun révisi kiwari','',3,'Kandar','20041229060812','sysop',0,0,0,0,0,'20041229060812','79958770939187'); INSERT INTO cur VALUES (1813,8,'Data','Data','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1814,8,'Dec','Dés','',3,'Kandar','20041229060711','sysop',0,0,0,0,0,'20041229060711','79958770939288'); INSERT INTO cur VALUES (1815,8,'December','Désémber','',3,'Kandar','20041229060819','sysop',0,0,0,0,0,'20041229060819','79958770939180'); INSERT INTO cur VALUES (1816,8,'Default','default','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1817,8,'Deletedrevision','Révisi heubeul nu dihapus $1.','',3,'Kandar','20041229060859','sysop',0,0,0,0,0,'20041229060859','79958770939140'); INSERT INTO cur VALUES (1818,8,'Deletepheading','hambalan hapus','',3,'Kandar','20041229061048','sysop',0,0,0,0,0,'20041229061048','79958770938951'); INSERT INTO cur VALUES (1819,8,'Editgroup','Édit Golongan','',3,'Kandar','20041229061120','sysop',0,0,0,0,0,'20041229061120','79958770938879'); INSERT INTO cur VALUES (1820,8,'Editingcomment','Ngédit $1 (pamanggih)','',3,'Kandar','20041229061207','sysop',0,0,0,0,0,'20041229061207','79958770938792'); INSERT INTO cur VALUES (1821,8,'Editingsection','Ngédit $1 (bagian)','',3,'Kandar','20041229061436','sysop',0,0,0,0,0,'20041229061436','79958770938563'); INSERT INTO cur VALUES (1822,8,'Editusergroup','Édit Golongan Pamaké','',3,'Kandar','20041229061452','sysop',0,0,0,0,0,'20041229061452','79958770938547'); INSERT INTO cur VALUES (1823,8,'Feb','Péb','',3,'Kandar','20050208085321','sysop',0,0,0,0,0,'20050208085321','79949791914678'); INSERT INTO cur VALUES (1824,8,'February','Pébruari','',3,'Kandar','20050208085335','sysop',0,0,0,0,0,'20050208085335','79949791914664'); INSERT INTO cur VALUES (1825,8,'Filemissing','Koropak leungit','',3,'Kandar','20041229061527','sysop',0,0,0,0,0,'20041229061527','79958770938472'); INSERT INTO cur VALUES (1826,8,'Friday','Jumaah','',3,'Kandar','20041229061409','sysop',0,0,0,0,0,'20041229061409','79958770938590'); INSERT INTO cur VALUES (1827,8,'Geo','Koordinat GEO','',3,'Kandar','20041229061606','sysop',0,0,0,0,0,'20041229061606','79958770938393'); INSERT INTO cur VALUES (1828,8,'History_copyright','-','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1829,8,'Imagemaxsize','Limit images on image description pages to: ','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1830,8,'Info_short','Iber','',3,'Kandar','20050223043314','sysop',0,0,1,0,0,'20050223043314','79949776956685'); INSERT INTO cur VALUES (1831,8,'Jan','Jan','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1832,8,'January','Januari','',3,'Kandar','20041229063932','sysop',0,0,0,0,0,'20041229063932','79958770936067'); INSERT INTO cur VALUES (1833,8,'Jul','Jul','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1834,8,'July','Juli','',3,'Kandar','20041229063936','sysop',0,0,0,0,0,'20041229063936','79958770936063'); INSERT INTO cur VALUES (1835,8,'Jun','Jun','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1836,8,'June','Juni','',3,'Kandar','20041229063945','sysop',0,0,0,0,0,'20041229063945','79958770936054'); INSERT INTO cur VALUES (1837,8,'Listingcontinuesabbrev',' cont.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1838,8,'Log','Log','',3,'Kandar','20050221093837','sysop',0,0,1,0,0,'20050221093837','79949778906162'); INSERT INTO cur VALUES (1839,8,'Mar','Mar','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1840,8,'March','Maret','',3,'Kandar','20041229064645','sysop',0,0,0,0,0,'20041229064645','79958770935354'); INSERT INTO cur VALUES (1841,8,'Markaspatrolleddiff','Tandaan salaku geus diriksa','',3,'Kandar','20041229064700','sysop',0,0,0,0,0,'20041229064700','79958770935299'); INSERT INTO cur VALUES (1842,8,'Markaspatrolledlink','
    [$1]
    ','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1843,8,'Markaspatrolledtext','Tandaan artikel ieu salaku geus diriksa','',3,'Kandar','20041229064720','sysop',0,0,0,0,0,'20041229064720','79958770935279'); INSERT INTO cur VALUES (1844,8,'Markedaspatrolled','Tandaan salaku geus diriksa','',3,'Kandar','20041229064731','sysop',0,0,0,0,0,'20041229064731','79958770935268'); INSERT INTO cur VALUES (1845,8,'Markedaspatrolledtext','Révisi nu dipilih geus ditandaan salaku geus diriksa.','',3,'Kandar','20041229065133','sysop',0,0,0,0,0,'20041229065133','79958770934866'); INSERT INTO cur VALUES (1846,8,'May','Méi','',3,'Kandar','20041229065225','sysop',0,0,0,0,0,'20041229065225','79958770934774'); INSERT INTO cur VALUES (1847,8,'May_long','Méi','',3,'Kandar','20041229065229','sysop',0,0,0,0,0,'20041229065229','79958770934770'); INSERT INTO cur VALUES (1848,8,'Monday','Senén','',3,'Kandar','20041229065333','sysop',0,0,0,0,0,'20041229065333','79958770934666'); INSERT INTO cur VALUES (1849,8,'Mw_math_html','Mun bisa HTML, mun henteu PNG','',3,'Kandar','20041229065610','sysop',0,0,0,0,0,'20041229065610','79958770934389'); INSERT INTO cur VALUES (1850,8,'Mw_math_mathml','Mun bisa MathML (uji coba)','',3,'Kandar','20041229065630','sysop',0,0,0,0,0,'20041229065630','79958770934369'); INSERT INTO cur VALUES (1851,8,'Mw_math_modern','Dianjurkeun pikeun panyungsi modérn','',3,'Kandar','20041229065650','sysop',0,0,0,0,0,'20041229065650','79958770934349'); INSERT INTO cur VALUES (1852,8,'Mw_math_png','Always render PNG','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1853,8,'Mw_math_simple','Mun basajan HTML, mun henteu PNG','',3,'Kandar','20041229065717','sysop',0,0,0,0,0,'20041229065717','79958770934282'); INSERT INTO cur VALUES (1854,8,'Mw_math_source','Antep salaku TeX (pikeun panyungsi tulisan)','',3,'Kandar','20041229065745','sysop',0,0,0,0,0,'20041229065745','79958770934254'); INSERT INTO cur VALUES (1855,8,'Newbies','anyaran','',3,'Kandar','20041229065759','sysop',0,0,0,0,0,'20041229065759','79958770934240'); INSERT INTO cur VALUES (1856,8,'Newimages','Galeri gambar anyar','',3,'Kandar','20041229065817','sysop',0,0,0,0,0,'20041229065817','79958770934182'); INSERT INTO cur VALUES (1857,8,'Nextdiff','Ka béda salajengna, jung→','',3,'Kandar','20041229070018','sysop',0,0,0,0,0,'20041229070018','79958770929981'); INSERT INTO cur VALUES (1858,8,'Nextrevision','Révisi nu leuwih anyar→','',3,'Kandar','20041229065940','sysop',0,0,0,0,0,'20041229065940','79958770934059'); INSERT INTO cur VALUES (1859,8,'Nocredits','There is no credits info available for this page.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1860,8,'Noimages','Taya nanaon.','',3,'Kandar','20041229070400','sysop',0,0,0,0,0,'20041229070400','79958770929599'); INSERT INTO cur VALUES (1861,8,'Nonunicodebrowser','WARNING: Your browser is not unicode compliant, please change it before editing an article.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1862,8,'Nosuchusershort','Taya pamaké nu ngaranna \"$1\", pariksa éjahanana!','',3,'Kandar','20041229070350','sysop',0,0,0,0,0,'20041229070350','79958770929649'); INSERT INTO cur VALUES (1863,8,'Nov','Nop','',3,'Kandar','20050126043208','sysop',0,0,0,0,0,'20050126043208','79949873956791'); INSERT INTO cur VALUES (1864,8,'November','Novémber','',3,'Kandar','20041229070316','sysop',0,0,0,0,0,'20041229070316','79958770929683'); INSERT INTO cur VALUES (1865,8,'Numauthors','Jumlah pangarang nu béda (artikel): $1','',3,'Kandar','20050126043225','sysop',0,0,0,0,0,'20050126043225','79949873956774'); INSERT INTO cur VALUES (1866,8,'Numedits','Jumlah éditan (artikel): $1','',3,'Kandar','20050126043243','sysop',0,0,0,0,0,'20050126043243','79949873956756'); INSERT INTO cur VALUES (1867,8,'Numtalkauthors','Jumlah pangarang nu béda (kaca sawala): $1','',3,'Kandar','20050126043311','sysop',0,0,0,0,0,'20050126043311','79949873956688'); INSERT INTO cur VALUES (1868,8,'Numtalkedits','Jumlah éditan (kaca sawala): $1','',3,'Kandar','20050126043325','sysop',0,0,0,0,0,'20050126043325','79949873956674'); INSERT INTO cur VALUES (1869,8,'Numwatchers','Jumlah nu ngawaskeun: $1','',3,'Kandar','20050126043336','sysop',0,0,0,0,0,'20050126043336','79949873956663'); INSERT INTO cur VALUES (1870,8,'Oct','Okt','',3,'Kandar','20041229070543','sysop',0,0,0,0,0,'20041229070543','79958770929456'); INSERT INTO cur VALUES (1871,8,'October','Oktober','',3,'Kandar','20041229070534','sysop',0,0,0,0,0,'20041229070534','79958770929465'); INSERT INTO cur VALUES (1872,8,'Previousdiff','← Ka béda saméméhna','',3,'Kandar','20050224110622','sysop',0,0,0,0,0,'20050224110622','79949775889377'); INSERT INTO cur VALUES (1873,8,'Previousrevision','←Révisi leuwih heubeul','',3,'Kandar','20050224110619','sysop',0,0,0,0,0,'20050224110619','79949775889380'); INSERT INTO cur VALUES (1874,8,'Protectmoveonly','Konci tina dipindahkeun wungkul','',3,'Kandar','20050221110731','sysop',0,0,1,0,0,'20050221110731','79949778889268'); INSERT INTO cur VALUES (1875,8,'Pubmedurl','http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=$1','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1876,8,'Randompage-url','Special:Randompage','Reverted edit of Kandar, changed back to last version by MediaWiki default',3,'Kandar','20050126055536','sysop',0,0,1,0,0,'20050126055536','79949873944463'); INSERT INTO cur VALUES (1877,8,'Rcpatroldisabled','Recent Changes Patrol disabled','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1878,8,'Rcpatroldisabledtext','The Recent Changes Patrol feature is currently disabled.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1879,8,'Recentchanges-url','Special:Recentchanges','Reverted edit of Kandar, changed back to last version by MediaWiki default',3,'Kandar','20050126055550','sysop',0,0,1,0,0,'20050126055550','79949873944449'); INSERT INTO cur VALUES (1880,8,'Revisionasofwithlink','Révisi nurutkeun $1; $2
    $3 | $4','',3,'Kandar','20050223075411','sysop',0,0,1,0,0,'20050223075411','79949776924588'); INSERT INTO cur VALUES (1881,8,'Saturday','Saptu','',3,'Kandar','20050126044030','sysop',0,0,0,0,0,'20050126044030','79949873955969'); INSERT INTO cur VALUES (1882,8,'Savegroup','Simpen Grup','',3,'Kandar','20050126052329','sysop',0,0,0,0,0,'20050126052329','79949873947670'); INSERT INTO cur VALUES (1883,8,'Saveusergroups','Simpen Grup Pamaké','',3,'Kandar','20050126052415','sysop',0,0,0,0,0,'20050126052415','79949873947584'); INSERT INTO cur VALUES (1884,8,'Sectionlink','→','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1885,8,'Sep','Sép','',3,'Kandar','20050126052421','sysop',0,0,0,0,0,'20050126052421','79949873947578'); INSERT INTO cur VALUES (1886,8,'September','Séptémber','',3,'Kandar','20050126052525','sysop',0,0,0,0,0,'20050126052525','79949873947474'); INSERT INTO cur VALUES (1887,8,'Sharedupload','Koropak ieu mangrupa muatan babarengan sarta bisa waé dipaké na proyék séjén.','',3,'Kandar','20050224111335','sysop',0,0,1,0,0,'20050224111335','79949775888664'); INSERT INTO cur VALUES (1888,8,'Showbigimage','Buka vérsi résolusi alus ($1x$2, $3 KB)','',3,'Kandar','20050224111226','sysop',0,0,1,0,0,'20050224111226','79949775888773'); INSERT INTO cur VALUES (1889,8,'Siteadminpheading','hambalan kuncén loka','',3,'Kandar','20050224111535','sysop',0,0,1,0,0,'20050224111535','79949775888464'); INSERT INTO cur VALUES (1890,8,'Sitenotice','','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1891,8,'Sitesettings','Pangaturan Loka','',3,'Kandar','20050126052515','sysop',0,0,0,0,0,'20050126052515','79949873947484'); INSERT INTO cur VALUES (1892,8,'Sitesettings-caching','Page caching','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1893,8,'Sitesettings-cookies','Cookies','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1894,8,'Sitesettings-debugging','Debugging','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1895,8,'Sitesettings-features','Fitur','',3,'Kandar','20050224111642','sysop',0,0,1,0,0,'20050224111642','79949775888357'); INSERT INTO cur VALUES (1896,8,'Sitesettings-images','Gambar','',3,'Kandar','20050126052939','sysop',0,0,0,0,0,'20050126052939','79949873947060'); INSERT INTO cur VALUES (1897,8,'Sitesettings-memcached','Memcache Daemon','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1898,8,'Sitesettings-performance','Kinerja','',3,'Kandar','20050126053141','sysop',0,0,0,0,0,'20050126053141','79949873946858'); INSERT INTO cur VALUES (1899,8,'Sitesettings-permissions','Widi','',3,'Kandar','20050126053157','sysop',0,0,0,0,0,'20050126053157','79949873946842'); INSERT INTO cur VALUES (1900,8,'Sitesettings-permissions-banning','User banning','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1901,8,'Sitesettings-permissions-miser','Pangaturan kinerja','',3,'Kandar','20050126053208','sysop',0,0,0,0,0,'20050126053208','79949873946791'); INSERT INTO cur VALUES (1902,8,'Sitesettings-permissions-readonly','Maintenance mode: Disable write access','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1903,8,'Sitesettings-permissions-whitelist','Whitelist mode','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1904,8,'Sitesettings-wgAllowExternalImages','Allow to include external images into articles','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1905,8,'Sitesettings-wgDefaultBlockExpiry','By default, blocks expire after:','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1906,8,'Sitesettings-wgDisableQueryPages','When in miser mode, disable all query pages, not only \"expensive\" ones','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1907,8,'Sitesettings-wgHitcounterUpdateFreq','Hit counter update frequency','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1908,8,'Sitesettings-wgMiserMode','Enable miser mode, which disables most \"expensive\" features','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1909,8,'Sitesettings-wgReadOnly','Readonly mode','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1910,8,'Sitesettings-wgReadOnlyFile','Readonly message file','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1911,8,'Sitesettings-wgShowIPinHeader','Show IP in header (for non-logged in users)','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1912,8,'Sitesettings-wgSysopRangeBans','kuncén wenang meungpeuk alamat IP','',3,'Kandar','20050208084303','sysop',0,0,0,0,0,'20050208084303','79949791915696'); INSERT INTO cur VALUES (1913,8,'Sitesettings-wgSysopUserBans','kuncén wenang meungpeuk pamaké nu geus asup og','',3,'Kandar','20050221095339','sysop',0,0,1,0,0,'20050221095339','79949778904660'); INSERT INTO cur VALUES (1914,8,'Sitesettings-wgUseCategoryBrowser','Enable experimental dmoz-like category browsing. Outputs things like: Encyclopedia > Music > Style of Music > Jazz','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1915,8,'Sitesettings-wgUseCategoryMagic','Enable categories','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1916,8,'Sitesettings-wgUseDatabaseMessages','Use database messages for user interface labels','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1917,8,'Sitesettings-wgUseWatchlistCache','Generate a watchlist once every hour or so','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1918,8,'Sitesettings-wgWLCacheTimeout','The hour or so mentioned above (in seconds):','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1919,8,'Sitesettings-wgWhitelistAccount-developer','Developer bisa mangnyieunkeun rekening pikeun pamaké','',3,'Kandar','20050203191733','sysop',0,0,0,0,0,'20050203191733','79949796808266'); INSERT INTO cur VALUES (1920,8,'Sitesettings-wgWhitelistAccount-sysop','Kuncén bisa mangnyieunkeun rekening pikeun pamaké','',3,'Kandar','20050203191935','sysop',0,0,0,0,0,'20050203191935','79949796808064'); INSERT INTO cur VALUES (1921,8,'Sitesettings-wgWhitelistAccount-user','Pamaké bisa nyieun rekening sorangan','',3,'Kandar','20050203191849','sysop',0,0,0,0,0,'20050203191849','79949796808150'); INSERT INTO cur VALUES (1922,8,'Sitesettings-wgWhitelistEdit','Pamaké kudu asup log pikeun ngédit','',3,'Kandar','20050126053052','sysop',0,0,0,0,0,'20050126053052','79949873946947'); INSERT INTO cur VALUES (1923,8,'Sitesettings-wgWhitelistRead','Pamaké anonim ukur bisa maca kaca-kaca ieu:','',3,'Kandar','20050126053149','sysop',0,0,0,0,0,'20050126053149','79949873946850'); INSERT INTO cur VALUES (1924,8,'Sitesupport-url','Project: ngarojong loka','',3,'Kandar','20050223073138','sysop',0,0,1,0,0,'20050223073138','79949776926861'); INSERT INTO cur VALUES (1925,8,'Spamprotectionmatch','The following text is what triggered our spam filter: $1','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1926,8,'Spamprotectiontext','The page you wanted to save was blocked by the spam filter. This is probably caused by a link to an external site.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1927,8,'Spamprotectiontitle','Spam protection filter','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1928,8,'Special_version_postfix',' ','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1929,8,'Special_version_prefix',' ','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1930,8,'Subcategorycount1','Aya $1 subkategori na kategori ieu.','',3,'Kandar','20041231061515','sysop',0,0,0,0,0,'20041231061515','79958768938484'); INSERT INTO cur VALUES (1931,8,'Sunday','Minggu','',3,'Kandar','20041231061420','sysop',0,0,0,0,0,'20041231061420','79958768938579'); INSERT INTO cur VALUES (1932,8,'Tagline','Ti {{SITENAME}}','',3,'Kandar','20041231061411','sysop',0,0,0,0,0,'20041231061411','79958768938588'); INSERT INTO cur VALUES (1933,8,'Templatesused','Citaka nu dipaké na kaca ieu:','',3,'Kandar','20041231061405','sysop',0,0,0,0,0,'20041231061405','79958768938594'); INSERT INTO cur VALUES (1934,8,'Thursday','Kemis','',3,'Kandar','20041231061351','sysop',0,0,0,0,0,'20041231061351','79958768938648'); INSERT INTO cur VALUES (1935,8,'Tog-editondblclick','Édit kaca ku klik ganda (JavaScript)','',3,'Kandar','20041231061204','sysop',0,0,0,0,0,'20041231061204','79958768938795'); INSERT INTO cur VALUES (1936,8,'Tog-editsection','Enable section editing via [edit] links','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1937,8,'Tog-editsectiononrightclick','Enable section editing by right clicking
    on section titles (JavaScript)','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1938,8,'Tog-editwidth','Edit box has full width','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1939,8,'Tog-hideminor','Sumputkeun éditan minor na parobahan anyar','',3,'Kandar','20041231061143','sysop',0,0,0,0,0,'20041231061143','79958768938856'); INSERT INTO cur VALUES (1940,8,'Tog-highlightbroken','Format broken links like this (alternative: like this?).','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1941,8,'Tog-hover','Show hoverbox over wiki links','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1942,8,'Tog-justify','Lempengkeun alinéa','',3,'Kandar','20041231061123','sysop',0,0,0,0,0,'20041231061123','79958768938876'); INSERT INTO cur VALUES (1943,8,'Tog-minordefault','Tandaan sadaya éditan salaku minor \'\'by default\'\'','',3,'Kandar','20041231061113','sysop',0,0,0,0,0,'20041231061113','79958768938886'); INSERT INTO cur VALUES (1944,8,'Tog-nocache','Disable page caching','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1945,8,'Tog-numberheadings','Auto-number headings','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1946,8,'Tog-previewonfirst','Témbongkeun sawangan dina éditan munggaran','',3,'Kandar','20041231061036','sysop',0,0,0,0,0,'20041231061036','79958768938963'); INSERT INTO cur VALUES (1947,8,'Tog-previewontop','Témbongkeun sawangan méméh kotak édit (lain sanggeusna)','',3,'Kandar','20041231061013','sysop',0,0,0,0,0,'20041231061013','79958768938986'); INSERT INTO cur VALUES (1948,8,'Tog-rememberpassword','Inget sandi liwat sési','',3,'Kandar','20041231060922','sysop',0,0,0,0,0,'20041231060922','79958768939077'); INSERT INTO cur VALUES (1949,8,'Tog-showtoc','Témbongkeun daptar eusi
    (pikeun kaca nu leuwih ti tilu subjudul)','',3,'Kandar','20041231060910','sysop',0,0,0,0,0,'20041231060910','79958768939089'); INSERT INTO cur VALUES (1950,8,'Tog-showtoolbar','Show edit toolbar','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1951,8,'Tog-underline','Garis-handapan tumbu','',3,'Kandar','20041231060809','sysop',0,0,0,0,0,'20041231060809','79958768939190'); INSERT INTO cur VALUES (1952,8,'Tog-usenewrc','Enhanced recent changes (not for all browsers)','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1953,8,'Tog-watchdefault','Tambahkeun kaca nu diédit ku anjeun kana awaskeuneun anjeun','',3,'Kandar','20041231060750','sysop',0,0,0,0,0,'20041231060750','79958768939249'); INSERT INTO cur VALUES (1954,8,'Tuesday','Salasa','',3,'Kandar','20041231060258','sysop',0,0,0,0,0,'20041231060258','79958768939741'); INSERT INTO cur VALUES (1955,8,'Uncategorizedcategories','Kategori nu can dikategorikeun','',3,'Kandar','20041231060320','sysop',0,0,0,0,0,'20041231060320','79958768939679'); INSERT INTO cur VALUES (1956,8,'Uncategorizedpages','Kaca nu can dikategorikeun','',3,'Kandar','20041231060334','sysop',0,0,0,0,0,'20041231060334','79958768939665'); INSERT INTO cur VALUES (1957,8,'Undeletedrevisions','$1 revisions restored','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1958,8,'Uploadcorrupt','The file is corrupt or has an incorrect extension. Please check the file and upload again.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1959,8,'Usenewcategorypage','1\n\nSet first character to \"0\" to disable the new category page layout.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1960,8,'Userlevels','Ngokolakeun hambalan pamaké','',3,'Kandar','20041231060001','sysop',0,0,0,0,0,'20041231060001','79958768939998'); INSERT INTO cur VALUES (1961,8,'Userlevels-addgroup','Tambahkeun grup','',3,'Kandar','20041231055903','sysop',0,0,0,0,0,'20041231055903','79958768944096'); INSERT INTO cur VALUES (1962,8,'Userlevels-editgroup','Édit grup','',3,'Kandar','20041231055849','sysop',0,0,0,0,0,'20041231055849','79958768944150'); INSERT INTO cur VALUES (1963,8,'Userlevels-editgroup-description','Dadaran grup (paling loba 255 aksara):
    ','',3,'Kandar','20041231055840','sysop',0,0,0,0,0,'20041231055840','79958768944159'); INSERT INTO cur VALUES (1964,8,'Userlevels-editgroup-name','Ngaran grup:','',3,'Kandar','20041231055809','sysop',0,0,0,0,0,'20041231055809','79958768944190'); INSERT INTO cur VALUES (1965,8,'Userlevels-editusergroup','Édit grup pamaké','',3,'Kandar','20041231055800','sysop',0,0,0,0,0,'20041231055800','79958768944199'); INSERT INTO cur VALUES (1966,8,'Userlevels-group-edit','Grup nu aya:','',3,'Kandar','20041231055739','sysop',0,0,0,0,0,'20041231055739','79958768944260'); INSERT INTO cur VALUES (1967,8,'Userlevels-groupsavailable','Kelompok nu sadia:','',3,'Kandar','20050224111849','sysop',0,0,1,0,0,'20050224111849','79949775888150'); INSERT INTO cur VALUES (1968,8,'Userlevels-groupshelp','Select groups you want the user to be removed from or added to.\nUnselected groups will not be changed. You can unselect a group by using CTRL + Left Click','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1969,8,'Userlevels-groupsmember','Anggota ti:','',3,'Kandar','20050224111906','sysop',0,0,1,0,0,'20050224111906','79949775888093'); INSERT INTO cur VALUES (1970,8,'Userlevels-lookup-group','Kokolakeun hak grup','',3,'Kandar','20041231055507','sysop',0,0,0,0,0,'20041231055507','79958768944492'); INSERT INTO cur VALUES (1971,8,'Userlevels-lookup-user','Kokolakeun grup pamaké','',3,'Kandar','20041231055458','sysop',0,0,0,0,0,'20041231055458','79958768944541'); INSERT INTO cur VALUES (1972,8,'Userlevels-user-editname','Asupkeun ngaran pamaké:','',3,'Kandar','20041231055437','sysop',0,0,0,0,0,'20041231055437','79958768944562'); INSERT INTO cur VALUES (1973,8,'Userrightspheading','hambalan hak pamaké','',3,'Kandar','20041231055419','sysop',0,0,0,0,0,'20041231055419','79958768944580'); INSERT INTO cur VALUES (1974,8,'Val_article_lists','Daptar artikel nu geus divalidasi','',3,'Kandar','20041231054903','sysop',0,0,0,0,0,'20041231054903','79958768945096'); INSERT INTO cur VALUES (1975,8,'Val_clear_old','Hapus data validasi kuring nu séjén pikeun $1','',3,'Kandar','20041231054847','sysop',0,0,0,0,0,'20041231054847','79958768945152'); INSERT INTO cur VALUES (1976,8,'Val_form_note','Hint: Merging your data means that for the article\nrevision you select, all options where you have specified no opinion\nwill be set to the value and comment of the most recent revision for which you\nhave expressed an opinion. For example, if you want to change a single option\nfor a newer revision, but also keep your other settings for this article in\nthis revision, just select which option you intend to change, and\nmerging will fill in the other options with your previous settings.','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1977,8,'Val_merge_old','Use my previous assessment where selected \'No opinion\'','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1978,8,'Val_no_anon_validation','Anjeun kudu asup \'\'log\'\' pikeun ngavalidkeun artikel.','',3,'Kandar','20041231054759','sysop',0,0,0,0,0,'20041231054759','79958768945240'); INSERT INTO cur VALUES (1979,8,'Val_noop','No opinion','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1980,8,'Val_page_validation_statistics','Kaca statistik validasi pikeun $1','',3,'Kandar','20041231054657','sysop',0,0,0,0,0,'20041231054657','79958768945342'); INSERT INTO cur VALUES (1981,8,'Val_percent','$1%
    ($2 of $3 points
    by $4 users)','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1982,8,'Val_percent_single','$1%
    ($2 of $3 points
    by one user)','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1983,8,'Val_stat_link_text','Statistik validasi pikeun artikel ieu','',3,'Kandar','20041231054641','sysop',0,0,0,0,0,'20041231054641','79958768945358'); INSERT INTO cur VALUES (1984,8,'Val_tab','Validkeun','',3,'Kandar','20041231054619','sysop',0,0,0,0,0,'20041231054619','79958768945380'); INSERT INTO cur VALUES (1985,8,'Val_table_header','Class$1Opinion$1Comment\n','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1986,8,'Val_this_is_current_version','ieu mangrupa vérsi ahir','',3,'Kandar','20041231054607','sysop',0,0,0,0,0,'20041231054607','79958768945392'); INSERT INTO cur VALUES (1987,8,'Val_total','Jumlah-jamléh','',3,'Kandar','20041231054549','sysop',0,0,0,0,0,'20041231054549','79958768945450'); INSERT INTO cur VALUES (1988,8,'Val_user_validations','Pamaké ieu geus ngavalidkeun $1 kaca.','',3,'Kandar','20041231054539','sysop',0,0,0,0,0,'20041231054539','79958768945460'); INSERT INTO cur VALUES (1989,8,'Val_validate_article_namespace_only','Ukur artikel nu bisa divalidasi. Kaca ieu teu dina spasingaran artikel.','',3,'Kandar','20041231040859','sysop',0,0,0,0,0,'20041231040859','79958768959140'); INSERT INTO cur VALUES (1990,8,'Val_validate_version','Validasi vérsi ieu','',3,'Kandar','20041231040817','sysop',0,0,0,0,0,'20041231040817','79958768959182'); INSERT INTO cur VALUES (1991,8,'Val_validated','Validasi geus réngsé.','',3,'Kandar','20041231040807','sysop',0,0,0,0,0,'20041231040807','79958768959192'); INSERT INTO cur VALUES (1992,8,'Val_version','Vérsi','',3,'Kandar','20041231040754','sysop',0,0,0,0,0,'20041231040754','79958768959245'); INSERT INTO cur VALUES (1993,8,'Val_version_of','Vérsi $1','',3,'Kandar','20041231040747','sysop',0,0,0,0,0,'20041231040747','79958768959252'); INSERT INTO cur VALUES (1994,8,'Val_view_version','Témbongkeun vérsi ieu','',3,'Kandar','20041231040742','sysop',0,0,0,0,0,'20041231040742','79958768959257'); INSERT INTO cur VALUES (1995,8,'Validate','Validasi kaca','',3,'Kandar','20041231040725','sysop',0,0,0,0,0,'20041231040725','79958768959274'); INSERT INTO cur VALUES (1996,8,'Variantname-zh','zh','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1997,8,'Variantname-zh-cn','cn','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1998,8,'Variantname-zh-hk','hk','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (1999,8,'Variantname-zh-sg','sg','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (2000,8,'Variantname-zh-tw','tw','',0,'MediaWiki default','20041223055404','sysop',0,0,0,1,0,'20041223055404','79958776944595'); INSERT INTO cur VALUES (2001,8,'Wednesday','Rebo','',3,'Kandar','20041231040427','sysop',0,0,0,0,0,'20041231040427','79958768959572'); INSERT INTO cur VALUES (2002,8,'Yourlanguage','Basa \'\'interface\'\'','',3,'Kandar','20041231040401','sysop',0,0,0,0,0,'20041231040401','79958768959598'); INSERT INTO cur VALUES (2003,8,'Yourvariant','Varian basa','',3,'Kandar','20041231040344','sysop',0,0,0,0,0,'20041231040344','79958768959655'); INSERT INTO cur VALUES (2004,6,'Surili.jpeg','Fotograf surili (\'\'Presbytis comata\'\') di Kebon Sato Ragunan kénging Markus Kappeler.','Fotograf surili (\'\'Presbytis comata\'\') di Kebon Sato Ragunan kénging Markus Kappeler.',3,'Kandar','20041223065314','',0,0,0,1,0,'20041224021055','79958776934685'); INSERT INTO cur VALUES (2005,0,'Kuiper\'s_test','#REDIRECT [[Uji Kuiper]]\n','Kuiper\'s test dipindahkeun ka Uji Kuiper',3,'Kandar','20041224015004','',0,1,0,1,0.356854812884,'20041224015004','79958775984995'); INSERT INTO cur VALUES (2006,0,'Ajag','[[Image:Asian red dog.jpg|right|300px]]\n\'\'\'Ajag\'\'\' (\'\'Cuon alpinus\'\') nyaéta [[anjing]] leuweung nu hirup di [[Asia]], utamana wewengkon kidul jeung wétan. Di wewengkon Asia séjénna sarta di [[Amérika]] jeung [[Éropa]], anjing ieu disebut [[srigala]].\n\nAjag ngarupakeun anjing asli [[Nusantara]], aya di Pulo [[Sumatra]] jeung [[Pulo Jawa|Jawa]], cicing utamana di wewengkon pagunungan jeung [[leuweung]]. Anjing kampung jeung nu séjénna nu ilahar jadi ingon-ingon urang, sabenerna mah anjing impor nu asalna ti wewengkon séjén. Pangawakan ajag sedeng, warnana coklat semu beureum. Lebah handapeun gado, beuheung, nepi ka tungtung beuteung warnana bodas, sedengkeun bulu buntutna kandel semu hideung.\n\nAjag biasana hirup ngagorombol lima nepi ka dua welas, tapi gumantung lingkunganana ogé. Misalna di [[Taman Nasional Gunung Leuser]], ajag téh hirupna nyorangan.\n\n\n{{pondok}}\n\n[[Category:Sasatoan]]\n\n[[bg:Азиатско диво куче]]\n[[de:Rothund]]\n[[en:Dhole]]\n[[fr:Dhole]]\n[[id:Ajag]]\n[[nl:Dhole]]\n[[ms:Anjing Hutan]]','',0,'130.88.171.12','20050304014221','',0,0,0,0,0.466028590313,'20050304014221','79949695985778'); INSERT INTO cur VALUES (2007,14,'Sasatoan','\'\'\'Sasatoan\'\'\' hartina sabangsaning sato (Ing. \'\'animal\'\').\n{{artikelutama}}\n[[Category:Alam]]','category',0,'83.129.203.1','20050304061424','',0,0,0,0,0.042801799367,'20050304061424','79949695938575'); INSERT INTO cur VALUES (2008,0,'Interval_estimation','#REDIRECT [[Interval estimasi]]\n','Interval estimation dipindahkeun ka Interval estimasi',13,'Budhi','20041224024928','',0,1,0,1,0.009220946935,'20041224024928','79958775975071'); INSERT INTO cur VALUES (2009,0,'Pearson\'s_chi-square_test','#REDIRECT [[Uji kuadrat-chi Pearson]]\n','Pearson\'s chi-square test dipindahkeun ka Uji kuadrat-chi Pearson',3,'Kandar','20041224062528','',0,1,0,1,0.303791752586,'20041224062528','79958775937471'); INSERT INTO cur VALUES (2010,0,'Empirical_Bayes_method','#REDIRECT [[Métode émpiris Bayes]]\n','Empirical Bayes method dipindahkeun ka Métode émpiris Bayes',3,'Kandar','20041224072442','',0,1,0,1,0.471172791078,'20041224072442','79958775927557'); INSERT INTO cur VALUES (2011,0,'Measurable_function','Dina [[matematik]], \'\'\'measurable functions\'\'\' are [[well-behaved]] [[Fungsi (matematik)|function]]s between [[measurable space]]s. Functions studied in [[mathematical analysis|analysis]] that are \'\'not\'\' measurable are generally considered pathological.\n\nIf \'\'X\'\' is a [[sigma-algebra|σ-algebra]] over \'\'S\'\' and \'\'Y\'\' is a σ-algebra over \'\'T\'\', then a function \'\'f\'\' : \'\'S\'\' → \'\'T\'\' is \'\'measurable\'\' if the preimage of every set in \'\'Y\'\' is in \'\'X\'\'.\n\nBy convention, if \'\'T\'\' is some [[topological space]], such as the space of [[real number]]s \'\'\'R\'\'\' or the [[complex number]]s \'\'\'C\'\'\', then the [[Borel algebra|Borel σ-algebra]] generated by the open sets on \'\'T\'\' is used, unless otherwise specified.\n\nThe composition of two measurable functions is measurable. \n\nOnly measurable functions can be [[Lebesgue integration|integrated]]. [[Random variable]]s are by definition measurable functions defined on [[probability space]]s. \n\nIf a function from one topological space to another is measurable with respect to the Borel σ-algebras on the two spaces, the function is also known as a \'\'\'Borel function\'\'\'.\n[[Continuous]] functions are Borel, however, not all Borel functions are continuous.\n\n\'\'See also:\'\' [[sigma-algebra|σ-algebra]]\n\n[[Category:Measure theory]]','',13,'Budhi','20041224214052','',0,0,1,0,0.57006461178,'20041224214052','79958775785947'); INSERT INTO cur VALUES (2012,0,'Probability_space','[[fr:espace probabilisé]]\n[[ja:確率空間]]\nIn [[mathematics]], a \'\'\'probability space\'\'\' is a [[set]] \'\'S\'\', together with a [[sigma-algebra|σ-algebra]] \'\'X\'\' on \'\'S\'\' and a [[measure (mathematics)|measure]] \'\'P\'\' on that σ-algebra such that \'\'P\'\'(\'\'S\'\') = 1.\nThe set \'\'S\'\' is called the [[sample space]] and the elements of \'\'X\'\' are called the [[Event (probability theory)|events]].\nThe measure \'\'P\'\' is called the \'\'probability measure\'\', and \'\'P\'\'(\'\'E\'\') is the [[probability]] of the event \'\'E\'\'.\n\nThe above is a compact form of stating the [[probability axioms]].\n\nNote that not all subsets of a probability space are events.','',13,'Budhi','20041224091813','',0,0,1,1,0.382764960135,'20041225235944','79958775908186'); INSERT INTO cur VALUES (2014,0,'Measurable_space','#REDIRECT [[Sigma-algebra]]','',13,'Budhi','20041224092052','',0,1,0,1,0.883123356611,'20041224092143','79958775907947'); INSERT INTO cur VALUES (2015,0,'Sigma-algebra','In [[mathematics]], a \'\'\'σ-algebra\'\'\' (or \'\'\'σ-field\'\'\') \'\'X\'\' over a [[set]] \'\'S\'\' is a family of [[subset|subsets]] of \'\'S\'\' which is closed under [[countable]] set operations; σ-algebras are mainly used in order to define [[measure (mathematics)|measures]] on \'\'S\'\'. The concept is important in [[mathematical analysis]] and [[probability theory]].\n\nFormally, \'\'X\'\' is a σ-algebra if and only if it has the following properties:\n\n# The [[empty set]] is in \'\'X\'\',\n# If \'\'E\'\' is in \'\'X\'\' then so is the [[complement (set theory)|complement]] of \'\'E\'\'.\n# If \'\'E\'\'1, \'\'E\'\'2, \'\'E\'\'3, ... is a sequence in \'\'X\'\' then their (countable) union is also in \'\'X\'\'.\n\nFrom 1 and 2 it follows that \'\'S\'\' is in \'\'X\'\'; from 2 and 3 it follows that the σ-algebra is also closed under countable intersections (via [[De Morgan\'s laws]]).\n\n\nAn ordered pair (\'\'S\'\', \'\'X\'\'), where \'\'S\'\' is a set and \'\'X\'\' is a σ-algebra over \'\'S\'\', is called a \'\'\'measurable space\'\'\'.\n\n== Examples ==\n\nIf \'\'S\'\' is any set, then the family consisting only of the empty set and \'\'S\'\' is a σ-algebra over \'\'S\'\', the so-called \'\'trivial σ-algebra\'\'. Another σ-algebra over \'\'S\'\' is given by the full [[power set]] of \'\'S\'\'.\n\nIf {\'\'X\'\'a} is a family of σ-algebras over \'\'S\'\', then the intersection of all \'\'X\'\'a is also a σ-algebra over \'\'S\'\'.\n\nIf \'\'U\'\' is an arbitrary family of subsets of \'\'S\'\' then we can form a special σ-algebra from \'\'U\'\', called the \'\'σ-algebra generated by U\'\'. We denote it by σ(\'\'U\'\') and define it as follows.\nFirst note that there is a σ-algebra over \'\'S\'\' that contains \'\'U\'\', namely the power set of \'\'S\'\'.\nLet Φ be the family of all σ-algebras over \'\'S\'\' that contain \'\'U\'\' (that is, a σ-algebra \'\'X\'\' over \'\'S\'\' is in Φ if and only if \'\'U\'\' is a subset of \'\'X\'\'.)\nThen we define σ(\'\'U\'\') to be the intersection of all σ-algebras in Φ. σ(\'\'U\'\') is then the smallest σ-algebra over \'\'S\'\' that contains \'\'U\'\'.\n\nThis leads to the most important example: the [[Borel algebra]] over any [[topological space]] is the σ-algebra generated by the [[open set]]s (or, equivalently, by the [[closed set]]s).\nNote that this σ-algebra is not, in general, the whole power set.\nFor a non-trivial example, see the [[Vitali set]].\n\nOn the [[Euclidean space]] \'\'\'R\'\'\'\'\'n\'\', another σ-algebra is of importance: that of all [[Lebesgue measure|Lebesgue measurable]] sets. This σ-algebra contains more sets than the Borel algebra on \'\'\'R\'\'\'\'\'n\'\' and is preferred in [[Integral|integration]] theory.\n\nSee also [[measurable function]].\n\n[[de:Σ-Algebra]]\n[[fr:Tribu (mathématiques)]]\n[[ja:完全加法族]]\n[[pl:Ciało zbiorów]]\n[[pt:Sigma-álgebra]]\n[[sk:Sigma algebra]]\n[[ru:Сигма-алгебра]]\n\n[[Category:Aljabar]]','kategori',20,'DiN','20050303205343','',0,0,1,0,0.020974347895,'20050303205343','79949696794656'); INSERT INTO cur VALUES (2016,0,'Borel_algebra','[[Category:Topology]]\nDina [[matematik]], \'\'\'aljabar Borel\'\'\' (atawa \'\'\'Borel σ-aljabar\'\'\') dina [[topological space|ruang topologi]] nyaeta dua [[sigma-algebra|σ-aljabar]] sejen dina topologi ruang \'\'X\'\': \n* The minimal σ-algebra containing the open sets.\n* The minimal σ-algebra containing the compact sets.\nThe minimal σ-algebra on a set \'\'X\'\' containing\na subset \'\'T\'\' of the [[power set]] \'\'2X\'\' of \'\'X\'\' is the smallest σ-algebra containing \'\'T\'\'. The existence and uniqueness of the minimal σ-algebra is shown by noting that the [[set theoretic intersection|intersection]] of all σ-algebras containing \'\'T\'\' is itself a σ-algebra containing \'\'T\'\'. The elements of the Borel algebra are called \'\'\'Borel sets\'\'\'.\n\nIn general topological spaces, even locally compact ones, the two structures are different. They are however identical whenever the topological space is a locally compact separable metric space.\n\nIn the case \'\'X\'\' is a metric space, the Borel algebra in the first sense may be described \'\'generatively\'\' as follows: First define for any collection \'\'A\'\' of subsets of \'\'X\'\' (that is, for any subset of the power set P(\'\'X\'\') of \'\'X\'\'),\n: A_\\sigma = \\mbox{ countable unions of elements of } A \\quad\n: A_\\delta = \\mbox{ countable intersections of elements of } A \\quad \nThen define by transfinite recursion a sequence \'\'Gm\'\', \'\'m\'\' an ordinal number, as follows:\n* For the base case of the definition,\n: G^0 = \\mbox{ open subsets of } X\n* If \'\'i\'\' is not a [[limit ordinal]], then \'\'i\'\' has an immediately preceding ordinal \'\'i-1\'\':\n: G^i = [G^{i-1}]_{\\delta \\sigma}\n* If \'\'i\'\' is a limit ordinal,\n: G^i = \\bigcup_{j < i} G^j\nThen the Borel algebra is \'\'Gm\'\' for the first uncountable ordinal number \'\'m\'\'. \n\nTo prove this fact, note that any open set in a metric space is the union of an increasing sequence of closed sets. In particular, it is easy to show\nthat complementation of sets maps \'\'Gm\'\' into itself for any limit ordinal; moreover if \'\'m\'\' is an uncountable limit ordinal, \'\'Gm\'\' is closed under countable unions. \n\nThis alternate definition is useful for some set-theoretic considerations, but the minimalist definition is preferred by analysts.\n\n== Examples ==\n\nA particularly important example is the Borel sigma algebra (or just \'\'Borel algebra\'\') on the set of [[real number]]s. It is the algebra on which the [[Borel measure]] is defined. Given a real random variable defined on a probability space, its [[probability distribution]] is by definition, also a measure on the Borel algebra. The Borel algebra on the reals is the smallest sigma algebra on \'\'\'R\'\'\' which contains all the [[interval (mathematics)|intervals]]. \n\nThe following is one of a number of [[Kuratowski]] theorems on Borel spaces:\nA \'\'\'Borel space\'\'\' is just another name for a set equipped with a σ-algebra. Borel spaces form a [[category]] in which the maps are Borel measurable mappings between Borel spaces, where \'\'f:X\'\' -> \'\'Y\'\' is Borel measurable iff \'\'f-1(B)\'\' is Borel in \'\'X\'\' for any Borel subset \'\'B\'\' of \'\'Y\'\'.\n\n\'\'\'Theorem\'\'\'. Let \'\'X\'\' be a [[Polish space]], that is a topological space such that there is a [[metric]] \'\'d\'\' on \'\'X\'\' which defines the topology of \'\'X\'\' and which makes \'\'X\'\' a complete separable metric space. Then \'\'X\'\' as a Borel space is isomorphic to one of\n(1) \'\'\'R\'\'\', (2) \'\'\'Z\'\'\' or (3) a finite space.\n\nIt should be noted that as Borel spaces \'\'\'R\'\'\' and \'\'\'R\'\'\' union with a countable set, are isomorphic. \n\nFor subsets of Polish spaces, Borel sets can be characterized as those sets which are the ranges of continuous injective maps defined on Polish spaces. Note however, that the range of a continuous noninjective map may fail to be Borel. See [[analytic set]].\n\n==See also==\n\n[[Baire set]]\n\n== References ==\n\nAn excellent exposition of the machinery of \'\'Polish topology\'\' is given in Chapter 3 of the following reference:\n\n* [[William Arveson]], \'\'An Invitation to C*-algebras\'\', Springer-Verlag, 1981\n\n* [[Richard Dudley]], \'\' Real Analysis and Probability\'\'. Wadsworth, Brooks and Cole, 1989\n\n* [[Paul Halmos]], \'\'Measure Theory\'\', D.van Nostrand Co., 1950\n\n* [[Halsey Royden]], \'\'Real Analysis\'\', Prentice Hall, 1988\n\n[[de:Borelsche σ-Algebra]]\n[[fr:Tribu borélienne]]\n[[ru:Борелевская сигма-алгебра]]','',13,'Budhi','20050218063152','',0,0,0,0,0.007218114303,'20050218063152','79949781936847'); INSERT INTO cur VALUES (2017,0,'Deming_regression','#REDIRECT [[Régrési Deming]]\n','Deming regression dipindahkeun ka Régrési Deming',13,'Budhi','20041224100348','',0,1,0,1,0.451839794304,'20041224100348','79958775899651'); INSERT INTO cur VALUES (2018,0,'Correlation_ratio','#REDIRECT [[Rasio korelasi]]\n','Correlation ratio dipindahkeun ka Rasio korelasi',13,'Budhi','20041224102814','',0,1,0,1,0.292695649664,'20041224102814','79958775897185'); INSERT INTO cur VALUES (2019,0,'Continuous','#REDIRECT [[Continuous function]]','',13,'Budhi','20041224114058','',0,1,1,1,0.13962778139,'20050303214455','79958775885941'); INSERT INTO cur VALUES (2020,0,'Continuous_function','Dina [[matematik]], a \'\'\'continuous\'\'\' [[Fungsi (matematik)|function]] is one in which arbitrarily small [[change]]s in the [[input]] produce arbitrarily small changes in the [[output]]. If small changes in the input can produce a broken jump in the changes of the output, the function is said to be \'\'\'discontinuous\'\'\' (or to have a \'\'\'discontinuity\'\'\'). \n\nAs an example, consider the function \'\'h\'\'(\'\'t\'\') which describes the [[height]] of a growing flower at time \'\'t\'\'. This function is continuous (unless the flower is cut). As another example, if \'\'T\'\'(\'\'x\'\') denotes the air temperature at height \'\'x\'\', then this function is also continuous. In fact, there is a dictum of [[classical physics]] which states that \'\'in nature everything is continuous\'\'. By contrast, if \'\'M\'\'(\'\'t\'\') denotes the amount of money in a bank account at time \'\'t\'\', then the function jumps whenever money is deposited or withdrawn, so the function \'\'M\'\'(\'\'t\'\') is discontinuous.\n\nThere are also some more special usages of continuity in some mathematical disciplines. Probably the most common one, found in [[topology]], is described in the article on [[continuity (topology)]]. In [[order theory]], especially in [[domain theory]], one considers a notion derived from this basic definition, which is known as [[Scott continuity]].\n\n== Real-valued continuous functions ==\n\nSuppose we have a function that maps [[real number]]s to real numbers and is defined on some [[interval (mathematics)|interval]], like the three functions \'\'h\'\', \'\'T\'\' and \'\'M\'\' from above. Such a function can be represented by a [[graph of a function|graph]] in the [[Cartesian coordinate system|Cartesian plane]]; the function is continuous if, roughly speaking, the graph is a single unbroken [[curve]] with no \"holes\" or \"jumps\": if it can be drawn by hand without lifting the pencil from the paper.\n\nTo be more precise, we say that the function \'\'f\'\' is continuous at some [[point (geometry)|point]] \'\'c\'\' when the following two requirements are satisfied:\n* \'\'f\'\'(\'\'c\'\') must be defined (i.e. \'\'c\'\' must be an element of the [[domain (mathematics)|domain]] of \'\'f\'\').\n* If \'\'c\'\' is an [[accumulation point]] of the domain, then the [[limit (mathematics)|limit]] of \'\'f\'\'(\'\'x\'\') as \'\'x\'\' approaches \'\'c\'\' must exist and be equal to \'\'f\'\'(\'\'c\'\').\n\nWe call the function \'\'\'everywhere continuous\'\'\', or simply \'\'\'continuous\'\'\', if it is continuous at every point of its [[domain (mathematics)|domain]]. More generally, we say that a function is continuous on some [[subset]] of its domain if it is continuous at every point of that subset.\n\n=== Epsilon-delta definition ===\n\nWithout resorting to limits, one can define continuity of real functions as follows.\n\nAgain consider a function \'\'f\'\' that maps a set of [[real numbers]] to another set of real numbers, and suppose \'\'c\'\' is an element of the domain of \'\'f\'\'. The function \'\'f\'\' is said to be continuous at the point \'\'c\'\' if (and only if) the following holds: For any number ε > 0 however small, there exists some number δ > 0 such that for all \'\'x\'\' in the domain with \'\'c\'\' - δ < \'\'x\'\' < \'\'c\'\' + δ, the value of \'\'f\'\'(\'\'x\'\') will satisfy \'\'f\'\'(\'\'c\'\') - ε < \'\'f\'\'(\'\'x\'\') < \'\'f\'\'(\'\'c\'\') + ε. This \"epsilon-delta definition\" of continuity was first given by [[Augustin-Louis Cauchy|Cauchy]]. \n\nMore intuitively, we can say that if we want to get all the \'\'f\'\'(\'\'x\'\') values to stay in some small [[topological neighbourhood|neighborhood]] around \'\'f\'\'(\'\'c\'\'), we simply need to choose a small enough neighborhood for the \'\'x\'\' values around \'\'c\'\', and we can do that no matter how small the \'\'f\'\'(\'\'x\'\') neighborhood is.\n\n=== Examples ===\n\n* All [[polynomial|polynomials]] are continuous, and so are the [[exponential function|exponential functions]], [[logarithm|logarithms]], [[square root|square root function]] and [[trigonometric function|trigonometric functions]].\n* The [[absolute value]] function is also continuous.\n* The real function \'\'f\'\' of non-zero real numbers such that \'\'f(x) = 1/x\'\' is continuous. However, if the function is extended by assigning some value to \'\'f(0)\'\', the extension will not be continuous.\n* An example of a discontinuous function is the function \'\'f\'\' defined by \'\'f\'\'(\'\'x\'\') = 1 if \'\'x\'\' > 0, \'\'f\'\'(\'\'x\'\') = 0 if \'\'x\'\' ≤ 0. Pick for instance ε = 1/2. There is no δ-neighborhood around \'\'x\'\'=0 that will force all the \'\'f\'\'(\'\'x\'\') values to be within ε of \'\'f\'\'(0). Intuitively we can think of a discontinuity as a sudden jump in function values.\n* Another example of a discontinuous function is the [[sign function]].\n\n=== Facts about continuous functions ===\n\nIf two functions \'\'f\'\' and \'\'g\'\' are continuous, then \'\'f\'\' + \'\'g\'\' and \'\'fg\'\' are continuous. If \'\'g\'\'(\'\'x\'\') ≠ 0 for all \'\'x\'\' in the domain, then \'\'f/g\'\' is also continuous. \n\nThe composition \'\'f\'\' o \'\'g\'\' of two continuous functions is continuous.\n\nThe [[intermediate value theorem]] is an [[existence theorem]], based on the real number property of [[completeness]], and states: \"If the real-valued function \'\'f\'\'(\'\'x\'\') is continuous on the [[interval (mathematics)|closed interval]] [\'\'a\'\', \'\'b\'\'] and \'\'k\'\' is some number between \'\'f\'\'(\'\'a\'\') and \'\'f\'\'(\'\'b\'\'), then there is some number \'\'c\'\' in [\'\'a\'\', \'\'b\'\'] such that \'\'f\'\'(\'\'c\'\') = \'\'k\'\'. For example, if a child undergoes continuous growth from 1[[metre|m]] to 1.5m between the ages of 2 years and 6 years, then, at some time between 2 years and 6 years of age, the child\'s height must have equalled 1.25m. \n\nAs a consequence, if \'\'f\'\'(\'\'x\'\') is continuous on [\'\'a\'\', \'\'b\'\'] and \'\'f\'\'(\'\'a\'\') and \'\'f\'\'(\'\'b\'\') differ in [[sign]], then, at some point \'\'c\'\', \'\'f\'\'(\'\'c\'\') must equal [[zero]]. \n\nIf a function \'\'f\'\' is defined on a closed interval [\'\'a\'\',\'\'b\'\'] and is continuous there, then the function attains its maximum, i.e. there exists \'\'c\'\'∈[\'\'a\'\',\'\'b\'\'] with \'\'f\'\'(\'\'c\'\') ≥ \'\'f\'\'(\'\'x\'\') for all \'\'x\'\'∈[\'\'a\'\',\'\'b\'\']. The same is true for the minimum of \'\'f\'\'. (Note that these statements are false if our function is defined on an open interval (\'\'a\'\',\'\'b\'\'). Consider for instance the continuous function \'\'f\'\'(\'\'x\'\') = 1/\'\'x\'\' defined on the open interval (0,1).)\n\nIf a function is [[derivative|differentiable]] at some point \'\'c\'\' of its domain, then it is also continuous at \'\'c\'\'. The converse is not true: a function that\'s continuous at \'\'c\'\' need not be differentiable there. Consider for instance the [[absolute value]] function at \'\'c\'\'=0.\n\n== Continuous functions between metric spaces ==\n\nNow consider a function \'\'f\'\' from one [[metric space]] (\'\'X\'\', d\'\'X\'\') to another metric space (\'\'Y\'\', d\'\'Y\'\'). Then \'\'f\'\' is continuous at the point \'\'c\'\' in \'\'X\'\' if for any positive real number ε, there exists a positive real number δ such that all \'\'x\'\' in \'\'X\'\' satisfying d\'\'X\'\'(\'\'x\'\', \'\'c\'\') < δ will also satisfy d\'\'Y\'\'(\'\'f\'\'(\'\'x\'\'), \'\'f\'\'(\'\'c\'\')) < ε.\n\nThis can also be formulated in terms of [[sequence]]s and [[mathematical limit|limits]]: the function \'\'f\'\' is continuous at the point \'\'c\'\' if for every sequence (\'\'x\'\'\'\'n\'\') in \'\'X\'\' with limit lim \'\'x\'\'\'\'n\'\' = \'\'c\'\', we have lim \'\'f\'\'(\'\'x\'\'\'\'n\'\') = \'\'f\'\'(\'\'c\'\'). \'\'Continuous functions transform limits into limits.\'\'\n\nThis latter condition can be weakened as follows: \'\'f\'\' is continuous at the point \'\'c\'\' if and only if for every convergent sequence (\'\'x\'\'\'\'n\'\') in \'\'X\'\' with limit \'\'c\'\', the sequence (\'\'f\'\'(\'\'x\'\'\'\'n\'\')) is a [[Cauchy sequence]]. \'\'Continuous functions transform convergent sequences into Cauchy sequences.\'\'\n\n== Continuous functions between topological spaces ==\n\'\'Main article: [[continuity (topology)]]\'\'\n\nThe above definitions of continuous functions can be generalized to functions from one [[topological space]]s to another in a natural way; a function \'\'f\'\' : \'\'X\'\' → \'\'Y\'\', where \'\'X\'\' and \'\'Y\'\' are topological spaces, is continuous [[iff]] for every [[open set]] \'\'V\'\' ⊆ \'\'Y\'\', \'\'f\'\' -1(\'\'V\'\') is open in \'\'X\'\'.\n\n== See also ==\n\n* [[uniform continuity]]\n* [[bounded linear operator]]\n* [[absolute continuity]]\n* [[semicontinuity]]\n* [[normal function]]\n* [[equicontinuity]]\n* [[limit (category theory)|continuous functor]]\n* [[Lipschitz continuity]]\n\n==References==\n*[http://archives.math.utk.edu/visual.calculus/ Visual Calculus] by [[Lawrence S. Husch]], [[University of Tennessee]] ([[2001]])\n\n[[da:Kontinuitet]]\n[[de:Stetigkeit]]\n[[es:Continuidad (matemáticas) ]][[ja:連続]][[pl:funkcja ciągła]][[ru:Непрерывное отображение]]\n[[fi:Jatkuva funktio]]\n[[sv:kontinuerlig]]\n[[he:רציפות]]\n[[Category:Calculus]][[Category:Topology]][[Category:General topology]]','',13,'Budhi','20041224214201','',0,0,1,0,0.060731427486,'20041229225327','79958775785798'); INSERT INTO cur VALUES (2021,0,'Variable','In [[computer science]] and [[matematik]], a \'\'\'variable\'\'\' is a symbol denoting a [[quantity]] or [[symbol|symbolic representation]]. In mathematics, a variable often represents an \'\'unknown\'\' quantity; in computer science, it represents a place where a quantity can be stored. Variables are often contrasted with [[constant]]s, which are known and unchanging.\n\nIn other scientific fields such as [[biology]], [[chemistry]], and [[physics]], the word \'\'\'variable\'\'\' is used to refer to a measureable factor, characteristic, or attribute of an individual or a system. In a scientific experiment, so called \"independent variables\" are factors that can be altered by the scientist. For example, [[temperature]] is a common environmental factor that can be controlled in laboratory experiments. \"Dependent variables\" or \"response variables\" are those that are measured and collected as [[data]]. \n\nFor Wikipedia\'s usages of special variables, see [[Help:Variable]].\n\n==General overview==\nVariables are used in [[open sentence]]s. For instance, in the formula: \'\'\'x\'\'\' + 1 = 5, \'\'\'x\'\'\' is a variable which represents an \"unknown\" [[number]]. In mathematics, variables are usually represented by [[letter]]s of the [[Roman alphabet]], but are also represented by letters of other [[alphabet]]s; as well as various other [[symbol]]s. In [[computer programming]], variables are usually represented by either single letters or [[alphanumeric]] [[string#Computing|string]]s.\n\n==Why are variables useful?==\nVariables are useful in mathematics and [[computer programming]] because they allow instructions to be specified in a general way. If one were forced to use actual values, then the instructions would only apply in a more narrow, and specific, set of situations. For example:\nspecify a mathematical definition for finding the [[square (algebra)|square]] of ANY number: square(\'\'\'x\'\'\') = \'\'\'x\'\'\' * \'\'\'x\'\'\'.\n\nNow, all we need to do to find the square of a number is replace \'\'\'x\'\'\' with any number we want. \n\n*square(x) = x * x = y\n*square(1) = 1 * 1 = 1\n*square(2) = 2 * 2 = 4\n*square(3) = 3 * 3 = 9\netc...\n\nIn the above example, the variable \'\'\'x\'\'\' is a \"[[placeholder]]\" for ANY number. One important thing we are assuming is that the value of each occurrence of \'\'\'x\'\'\' is the same -- that \'\'\'x\'\'\' does not get a new value between the first \'\'\'x\'\'\' and the second \'\'\'x\'\'\'. \nIn [[computer]] [[programming language]]s without [[referential transparency]], such changes can occur.\n\nAlso, among mathematicians and students. The inverse variable, -x, raised to any power would represent (-x) raised to that power, not -(x*).\n\n==Computer programming==\nIn programming languages, a \'\'variable\'\' can be thought of as a place to store a \'\'[[value (computer science)|value]]\'\' in [[computer memory]]. Variables are convinent ways to mimic mathematics.\n\nIn general, a variable binds an [[object (computer science)|object]] to a name so that the object could be accessed later, much like a person has a name and people could refer to him by that name. This is analogous to the use of variables in the mathematics and varaibles in computer programming work usually in the similar manner. Put in another way, an object could exist without it being bound to a certain variable.\n\nTypically, the name of a variable is bound to a particular address of some bytes on the memory, and any operations on the variable would manipulate that block. This is called \'\'[[name binding]]\'\'. If the space is way too large or its size is unknown beforehand, the use of [[reference (computer science)|referencing]] is more common, in which a value is not directly stored in the variable but a location information for it is.\n\nImportation questions about variables are twofold: its life-time and scope. For space efficiency, a memory space needed for a variable is allocated when first used and freed if no longer needed. The scope helps determine the life-time of variables. Usually, a variable is set to reside in some [[scope (programming)|scope]] in program code, and entrance and leave of the scope coincides with the beginning and ending of a varible life, respectively. Put in conceptual terms, a variable is \'\'visible\'\' in its scope, and computers could assume the varible is needed only when it is visible. In this way, however, unused variables might be given a space, which is going to be never used. Because of this, a compiler often warns programmers when a variable is declared but not used at all.\n\nWhile a variable stores simple data like integers and literal strings, some languages allow a variable to store [[datatype]] as well. They enable [[type polymorphism|parametric polymorphic]] functions to be written. They operate like variables, in that they can represent any type. For example, with the function length -- to determine the length of a list, it is only necessary to know the amount of elements in the list -- the type of the elements does not count, so the [[type signature]] can be represented with a type variable and thus is parametric polymorphic.\n\nVariables could be either mutable or immutable. Mutable variables could be thought of ones having l-value while immutable ones having r-value. One characterstic of functional programming is that a variable is immutable. Because immutable variables are semantically the same as constants given a name or constant functions, when one talks about variables, they usually mean mutable variables.\n\nSee [[name (computer science)|name]] for naming rules and convention of variable names.\n\n\n----\n\n\nIn programming languages, a \'\'\'variable\'\'\' can be thought of as a place to store a \'\'value\'\' in [[computer memory]]. More precisely, a variable associates a \'\'name\'\' (sometimes called an \'\'identifier\'\') with the location of the value; the value in turn is stored as a \'\'data object\'\' in this location. The specifics of variable allocation and the representation of values vary widely, both among languages and among implementations of any given language.\n\n=== The names of variables ===\n\nThe naming of variables is a matter of syntax, convention, and taste. Each language has lexical requirements for what may be used as a variable name. In addition, programming communities have informal conventions on the naming of variables -- as do individual programmers.\n\nFor instance, in [[C programming language|C]] and related languages, variable names must be made of letters, numbers, and underscores, and must begin with a letter. However, the language does not spell out whether a variable should be named x_coordinate or xCoordinate or simply x.\n\nIn other languages, the name of a variable might tell you what kind of value it might contain. For instance, in [[Fortran]], the first letter in a variable\'s name indicates whether by default it is created as an [[integer]] or [[floating point]] variable. In [[BASIC programming language|BASIC]], the suffix $ on a variable name indicates that its value is a [[string]]. [[Perl]] uses the prefixes $, @, %, and & to indicate scalar, array, hash, and subroutine variables.\n\nInternally, names are mapped to memory in a [[symbol table]]. In [[Lisp programming language|Lisp]] languages, the symbol table is exposed: the names of variables are not strings but \'\'symbols\'\', a special data type which can be manipulated by the program.\n\nIn many languages, such as [[Java programming language|Java]], [[Common Lisp]], and [[Python programming language|Python]], variable names can be arranged into \'\'[[namespace]]s\'\' or \'\'packages\'\'. Each namespace can be considered a separate symbol table, so a given name can occur in different namespaces without collision: thus, if there are packages myutils and app in a Common Lisp program, each can contain a variable called *mode* without conflict. A portion of a program (such as a \'\'module\'\') may use a given namespace as its default, and refer to variables from other namespaces only by mentioning the namespace explicitly — e.g. as myutils:*mode*.\n\n=== Scope and extent ===\n\nThe \'\'scope\'\' and \'\'extent\'\' (or \'\'lifetime\'\') of a variable describe where in the program\'s text it may be used, and when in the program\'s execution it has a value.\n\nIn most languages, variables can have different \'\'[[scope]]s\'\'. The scope of a variable is the portion of the program code for which the variable\'s name has meaning. For instance, a variable with \'\'lexical scope\'\' is meaningful only within a certain block of statements or [[subroutine]]. A \'\'global variable\'\', or one with \'\'indefinite scope\'\', may be referred to anywhere in the program. When a variable has gone out of scope, it is erroneous or meaningless to refer to it. [[Lexical analysis]] of a program can determine whether variables are used out of scope.\n\nLikewise, the [[binding (computer science)|binding]]s of variables to values can have different \'\'extent\'\'. The extent of a binding is the length of time -- part of the course of the program\'s execution -- during which the variable continues to refer to the same value or place. A running program may enter and leave a given extent many times, as in the case of a [[closure]]. A variable can be \'\'unbound\'\', meaning that it is in scope but has never been given a value, or its value has been destroyed; in many languages, it is an error to try to use the value of an unbound variable, or may yield unpredictable results.\n\nIn other words, scope is a lexical fact, but extent a runtime (dynamic) fact. If a variable name is out of scope, then it is an error for that name to be used in the program code. In compiled languages, this error can be detected statically at compile-time. If a variable is out of extent, its value cannot be referred to (since it doesn\'t have one; it is unbound) but it may be given a value, which gives it a new extent.\n\nWhen a variable binding extends (in time) as the program\'s execution passes out of the variable\'s scope, this is no bug. It is a Lisp closure or a C static variable: when execution passes back into the variable\'s scope, the variable may be referred to again. But when a variable\'s extent ends, it becomes unbound -- if it is still in scope, referring to it is an error (or, in C, gets you a nice arbitrary value).\n\n=== Memory allocation ===\n\nBound variables have values. A value, however, is an abstraction, an idea; in implementation, a value is represented by some \'\'data object\'\', which is stored somewhere in computer memory. The program, or the runtime environment, must set aside memory for each data object and, since memory is finite, ensure that this memory is yielded for re-use when the object is no longer needed to represent some variable\'s value.\n\nThe handling of memory for variables is highly dependent on the programming language environment. Many language implementations handle the simplest cases easily by distinguishing those variables whose extent lasts no longer than a single function call. Space for these \'\'local variables\'\' are allocated on the \'\'execution stack\'\', where their memory is automatically reclaimed when the function returns.\n\nSpace for other objects must be allocated on the \'\'heap\'\', or pool of unused memory. These must be reclaimed specially when the objects are no longer needed. In a \'\'[[garbage collection (computer science)|garbage-collected]]\'\' (gc) language such as Java or Lisp, the runtime environment automatically \"reaps\" objects when it can be proven that no extant variable refers to them. In a \'\'non-gc\'\' language such as C, it is up to the program (and thus the programmer) to explicitly [[malloc|allocate]] memory; and in turn to state when memory can be reclaimed, by explicitly freeing it. Failure to do so leads to [[memory leak]]s, in which the heap is depleted over the program\'s run. If the program runs long enough, it will exhaust available memory and fail.\n\nMemory allocation goes beyond single variables. A variable may refer to a [[data structure]] created dynamically, where many structure components are not \'\'directly\'\' named by variables, but are reachable from a variable by traversing the structure. For this reason, garbage collectors (and programs in languages which lack them) must deal with the case where a \'\'portion\'\' of the memory reachable from a variable needs to be reclaimed.\n\n=== Typed and untyped variables ===\n\nIn [[static typing|statically-typed]] languages such as [[Java programming language|Java]] or [[ML programming language|ML]], a variable also has \'\'type\'\', meaning that only values of a given sort can be stored in it. In [[dynamic typing|dynamically-typed]] languages such as [[Python programming language|Python]] or [[Lisp programming language|Lisp]], it is values and not variables which carry type. \'\'See [[type system]].\'\'\n\nTyping of variables also allows [[polymorphism]]s to be resolved at compile time.\n\n=== Parameters ===\n\nThe \'\'arguments\'\' or \'\'formal parameters\'\' of functions are also referred to as variables. For instance, in these equivalent functions in Python and Lisp \n\n def addtwo(x):\n return x + 2\n\n (defun addtwo (x) (+ x 2))\n\nthe variable named x is an argument. It is given a value when the function is called. In most languages, function arguments have local scope; this specific variable named x can only be referred to within the addtwo function, though of course other functions can also have variables called x.\n\n==External link==\n\n*[http://www.legislation.hmso.gov.uk/acts/acts2003/30042--b.htm Example of the use of variables (persons A and B) in a law]\n\n[[Category:Aljabar]]\n\n[[de:Variable]]\n[[eo:Variablo]]\n[[es:Variable (programación)]]\n[[et:Muutuja]]\n[[fr:Variable]]\n[[ja:変数]]\n[[nl:Variabele]]\n[[pl:Zmienna (informatyka)]]\n[[ru:Переменная]]\n[[sv:Variabel]]\n[[zh:變數]]','/* External link */',20,'DiN','20050303205538','',0,0,1,0,0.621228602823,'20050303205538','79949696794461'); INSERT INTO cur VALUES (2022,0,'Epistemic_probability','#REDIRECT [[Bayesian probability]]','',13,'Budhi','20041224120303','',0,1,1,1,0.613037831196,'20050303214455','79958775879696'); INSERT INTO cur VALUES (2023,0,'Bayesianism','#REDIRECT [[Bayesian probability]]','',13,'Budhi','20041224120548','',0,1,1,1,0.02940549134,'20050303214455','79958775879451'); INSERT INTO cur VALUES (2024,0,'Frequentism','#REDIRECT [[Frequency probability]]','',13,'Budhi','20041224120634','',0,1,1,1,0.114186239027,'20041224120715','79958775879365'); INSERT INTO cur VALUES (2025,0,'Frequency_probability','[[pl:Prawdopodobie%C5%84stwo_obiektywne]]\n\n[[Statistical regularity]] has motivated the development of the [[relative frequency]] [[Probability interpretations|concept of probability]]. \n\nMost of the procedures commonly used to make statistical estimates or tests were developed by statisticians who used this concept exclusively. They are usually called \'\'\'frequentists\'\'\', and their position is called \'\'\'frequentism\'\'\'. \n\nThis school is often associated with the names of [[Jerzy Neyman]] and [[Egon Pearson]] who described the logic of [[tes hipotesa statistik]]. Other influential figures of the frequentist school include [[John Venn]], [[Ronald Aylmer Fisher|R.A. Fisher]], and [[Richard von Mises]].\n\nSince the [[18th century]], there has been a [[Probability interpretations|debate]] between frequentists and [[Bayesian probability|Bayesian]]s. The former insisted that statistical procedures only made sense when one uses the [[relative frequency]] concept. The Bayesians supported the use of degrees of belief as a basis for statistical practice.\n\nThe frequentist position is the one you probably heard at school: perform an experiment lots of times, and measure the proportion where you get a positive result - this proportion, if you perform the experiment enough times, is the probability.\n\nThe problem comes in those cases where we haven\'t performed an experiment yet, or where there\'s no possible way an experiment could be performed - in these cases, frequentism can\'t help us. To solve this, Bayesians assume a hypothetic \'\'reference class\'\' from which random selection is made. The [[sunrise problem]] illustrates this. \n\n==Tempo ogé==\n\n[[probability interpretations]] -- [[Bayesian probability]] -- [[pilihan probabiliti]] -- [[kamungkinan|probability]] -- [[statistik]] -- [[statistical regularity]] -- [[probability axioms]] -- [[games of chance]]\n\n==Tumbu kaluar==\n\n*http://curry.edschool.virginia.edu/teacherlink/math/probability/history/contributors/vonMises.html','',13,'Budhi','20050104070422','',0,0,0,0,0.065247381251,'20050104070422','79949895929577'); INSERT INTO cur VALUES (2026,0,'Bruno_de_Finetti','\'\'\'Bruno de Finetti\'\'\' ([[Innsbruck]], [[June 13]], [[1906]] - [[Rome]], [[July 20]], [[1985]]) was an [[Italy|Italian]] [[list of probabilists | probabilist]] and [[statistician]], noted for the \"operational subjective\" conception of [[probability]]. The classic exposition of his distinctive theory is the 1937 \"La prévision: ses lois logiques, ses sources subjectives,\" \'\'Annales de l\'Institute Henri Poincaré\'\', 7, 1-68, which discussed probability founded on the coherence of betting odds and the consequences of exchangeability.\n\nDe Finetti proposed a [[thought experiment]] along the following lines (described in great detail at [[coherence (philosophical gambling strategy)]]): \'\'\'You\'\'\' must set the price of a promise to pay $1 if there was life on Mars 1 billion years ago, and $0 if there was not, and tomorrow the answer will be revealed. You know that \'\'\'your opponent\'\'\' will be able to choose either to buy such a promise from you at the price you have set, or require you to buy such a promise from your opponent, still at the same price. In other words: you set the odds, but your opponent decides which side of the bet will be yours. The price you set is the \"operational subjective probability\" that you assign to the proposition on which you are betting. This price has to obey the probability axioms if you are not to face certain loss, as you would if you set a price above $1 (or a negative price). By considering bets on more than one event de Finetti could justify additivity. Prices, or equivalently [[odds]], that do not expose you to certain loss through a \'\'[[Dutch book]]\'\' are called \'\'coherent\'\'.\n\nDe Finetti is also noted for [[de Finetti\'s theorem]] on [[de Finetti\'s theorem|exchangeable]] sequences of [[random variable]]s. De Finetti was not the first to study exchangeability but he put the subject on the map. He started publishing on exchangeability in the late 1920s but the 1937 article is his most famous treatment.\n\nIn 1929, de Finetti introduced the concept of [[infinitely divisible probability distribution]]s.\n\nDe Finetti studied mathematics at Milan University. After graduation, he did not pursue an academic career but worked as an actuary and a statistician. He published extensively (17 papers in 1930 alone, according to Lindley) and acquired an international reputation in the small world of probability mathematicians. He won a chair in Financial Mathematics at Trieste University (1939). In 1954 he moved to the University of Rome, first to another chair in Financial Mathematics and then, from 1961 to 1976, one in the Calculus of Probabilities. De Finetti developed his ideas on subjective probability in the 1920s independently of [[Frank P. Ramsey]]. He only became known in the Anglo-American statistical world in the 1950s when [[L. J. Savage]], who had independently adopted [[Bayesian inference|subjectivism]], drew him into it.\n\n==Bibliography==\n\n=== De Finetti in English===\n(The following are translations of works originally published in Italian or French.)\n*\"Probabilism: A Critical Essay on the Theory of Probability and on the Value of Science,\" (translation of 1931 article) in \'\'Erkenntnis,\'\' volume 31 September 1989. The entire double issue is devoted to de Finetti\'s philosophy of probability.\n*\"Foresight: its Logical Laws, Its Subjective Sources,\" (translation of 1937 article) in H. E. Kyburg and H. E. Smokler (eds), \'\'Studies in Subjective Probability,\'\' New York: Wiley, 1964.\n*\'\'Theory of Probabilty\'\', (translation of 1970 book) 2 volumes, New York: Wiley, 1974-5.\n\n=== Discussions===\n*D. V. Lindley, \"Bruno de Finetti, 1906-1985 (Obituary)\" \'\'Journal of the Royal Statistical Society, Series A\'\', \'\'\'149\'\'\', p. 252 (1986).\nThe following books have a chapter on de Finetti and references to further literature.\n*Jan von Plato, \'\'Creating Modern Probability Theory\'\', Cambridge: Cambridge University Press, 1994\n*Donald Gillies, \'\'Philosophical Theories of Probability\'\', London: Routledge, 2000.\n\n==External links==\n*[http://plato.stanford.edu/archives/sum2003/entries/probability-interpret/ Interpretations of Probability] from the Stanford Encyclopedia of Philosophy. De Finetti\'s views are discussed in Section 3.5 of this article.\n\n[[Category:1906 births|Finetti, Bruno de]]\n[[Category:1985 deaths|Finetti, Bruno de]]\n[[Category:Statisticians|Finetti, Bruno de]]\n[[it:Bruno de Finetti]]','',13,'Budhi','20041224120805','',0,0,1,1,0.359118838273,'20050303214455','79958775879194'); INSERT INTO cur VALUES (2027,0,'Tail_sigma-field','#REDIRECT[[Kolmogorov\'s zero-one law]]','',13,'Budhi','20041224120855','',0,1,0,1,0.694207823853,'20050303214455','79958775879144'); INSERT INTO cur VALUES (2028,0,'Kolmogorov\'s_zero-one_law','In [[probability theory]], \'\'\'Kolmogorov\'s zero-one law\'\'\', named in honor of [[Andrey Nikolaevich Kolmogorov]], specifies that a certain type of event, called a \'\'tail event\'\', will either certainly happen or certainly not happen; that is, the probability of such an event occurring is zero or one.\n\nTail events are defined in terms of infinite sequences of [[random variable]]s. Suppose\n:X_1,X_2,X_3,\\dots\nis an infinite sequence of [[statistical independence|independent]] random variables (not necessarily identically distributed). Then, a \'\'\'tail event\'\'\' is an event whose occurrence or failure is determined by the values of these random variables but which is [[statistical independence|probabilistically independent]] of each finite subsequence of these random variables. For example, the event that the series\n\n:\\sum_{k=1}^\\infty X_k\n\nconverges, is a tail event. The event that the sum to which it converges is more than 1 is \'\'not\'\' a tail event, since, for example, it is not independent of the value of \'\'X\'\'1. In an infinite sequence of coin-tosses, the probability that a sequence of 100 consecutive heads \'\'eventually\'\' occurs, is a tail event.\n\nIn a book published in [[1909]], [[Émile Borel]] stated that if a [[Infinite monkey theorem|dactylographic monkey]] hits typewriter keys randomly forever, it will eventually type every book in [[France|France\'s]] National Library. That is a special case of this zero-one law: since there is a positive, though tiny, chance that the monkey \"gets it right\" the first time he tries, the probability of the tail event that he \"gets it right\" given an infinite amount of time cannot be zero. Therefore, that probability must be 1 by the zero-one law.\n\n[[Category:Theorems]]','',13,'Budhi','20041224120923','',0,0,0,1,0.572611440044,'20050303214455','79958775879076'); INSERT INTO cur VALUES (2029,0,'Geometric_Dimensioning_and_Tolerancing','\'\'\'Geometric dimensioning and tolerancing\'\'\' is a method for explicitly describing a [[geometry]] and the allowable variation in the size and position of its features. It is often referred to by the abbreviation, GD&T.\n\nGD&T is used most often on [[engineering drawing]]s.\n\nThere are many standards available world-wide that describe the symbols and define the rules used in GD&T. One such standard is [[ASME]] [[Y14.5M-1994]]. This document will be based on that standard. Other standards may vary slightly.\n\n==Fundamental Rules==\nAs the purpose of GD&T is to describe the engineering intent of the item, there are some fundamental rules that need to be applied:\n*All dimensions must have a tolerance. Nothing can be made to perfection; therefore, an appropriate tolerance must be available. Tolerances may come in the form of limits of size applied to basic dimensions, with +- sytle tolerance applied directly to dimensions as a tolerance block or a general note. The only exception is when a dimension is marked as minimum, maximum, stock or reference.\n*All dimensions necessary to exactly reproduce the shown geometry must by present. Measurement and scaling should not be required.\n*In order to avoid ambiguities, only the minimum dimensions required should be present. If additional dimensions would be helpful but not required, they should be marked as reference.\n*Dimension should be applied to features and arranged in such a way as to represent the function of the individual features.\n*Descriptions of manufacturing methods should be avoided. The geometry should be described without expicitly defining the method of manufacture.\n*If certain sizes are required during the processing, but are not required in the final geometry (due to shrinkage or other causes) they should be marked as NON-MANDATORY.\n*All symbols should be arranged for maximum readability. They should be applied to visible lines in true profiles whenever possible.\n*When geometry is normally controlled by gage sizes or by code, the dimensions should still be included but should with the gauge or code number in parentheses following or below the dimension.\n*Angles of 90 degrees are assumed when basic dimensions or centerlines are used but no angular dimension is explicitly shown.\n*Dimensions and tolerances are valid at 20 degrees [[Celsius]] unless stated otherwise.\n*Unless explicitly stated, all dimensions and tolerances are valid when the item is in a free, unconstrained state.\n*Dimensions and tolerances apply to the full length, width, and depth of a feature.\n*Dimensions only apply at the level of the drawing where they are placed. If the intention is for them to apply at multiple levels, this must be stated.\n\n==Symbols==\n==External References==','',13,'Budhi','20041224223052','',0,0,0,1,0.224536426367,'20050303214455','79958775776947'); INSERT INTO cur VALUES (2030,0,'Odds-ratio','#REDIRECT [[Rasio ganjil]]\n','Odds-ratio dipindahkeun ka Rasio ganjil',13,'Budhi','20041224230023','',0,1,0,1,0.280915176761,'20041224230023','79958775769976'); INSERT INTO cur VALUES (2032,0,'Range_(statistics)','#REDIRECT [[Rentang (statistik)]]\n','Range (statistics) dipindahkeun ka Rentang (statistik)',13,'Budhi','20041224233529','',0,1,0,1,0.4796179851,'20041224233529','79958775766470'); INSERT INTO cur VALUES (2033,0,'Statistically_significant','#REDIRECT [[statistical significance]]','',13,'Budhi','20041225002921','',0,1,1,1,0.426200927586,'20050303214455','79958774997078'); INSERT INTO cur VALUES (2034,0,'Confidence_interval','#REDIRECT [[Interval kapercayaan]]\n','Confidence interval dipindahkeun ka Interval kapercayaan',13,'Budhi','20041225044122','',0,1,0,1,0.202269716195,'20041225044122','79958774955877'); INSERT INTO cur VALUES (2035,0,'Philosophical','#REDIRECT [[Philosophy]]','',13,'Budhi','20041225124840','',0,1,1,1,0.026247906016,'20050303214455','79958774875159'); INSERT INTO cur VALUES (2036,0,'Philosophy','\'\'\'Philosophy\'\'\' literally means \'love of wisdom\', from the Greek \'philo\' and \'sofia\'. It is now widely used to designate the pursuit of knowledge or wisdom about fundamental matters concerning life, death, meaning, reality, being and truth. The term may also refer to the collective works of major [[philosophers]]; it can mean the academic exploration of various questions raised by philosophers; it can also mean a certain critical, creative way of thinking. Western academic \'philosophy\' has two broad traditions, \'analytic\' and \'continental\' philosophy. The former tradition is commonly focused on conceptual analysis. The latter tradition is distinctive for its associations with particular movements. Eastern philosophy is another, discrete discipline. Each of these can be considered individually or in how it differs from the others. Philosophy, in brief, has several connotations in common speech, but this article will focus on philosophy as a field of study.\n\n== Philosophical topics ==\n\nPhilosophers are usually concerned with concepts such as [[existence]] or [[being]], [[morality]] or [[Goodness and value theory|goodness]], [[knowledge]], [[truth]], and [[beauty]]; historically most philosophy has also centred on [[religious belief]]s, or coincided with [[science]]. Philosophers may ask critical questions about the nature of these concepts, questions typically outside the scope of science, and several major works of post-medieval philosophy begin by asking what philosophy itself should or does mean. Asking \'\'what philosophy is\'\' is itself a philosophical activity, though philosophers are more often motivated by specific questions such as:\n\n*What is truth? How or why do we identify a statement as correct or false, and how do we reason?\n*Is knowledge possible? How do we know what we know?\n*Is there a difference between morally right and wrong actions (or values, or institutions)? If so, what is that difference? Which actions are right, and which wrong? Are values absolute, or relative? In general or particular terms, how should I live?\n*What is reality, and what things can be described as real? What is the nature of those things? Do some things exist independently of our perception? What is the nature of space and time? What is the nature of thought and thinking? What is it to be a person?\n*What is it to be beautiful? How do beautiful things differ from the everyday? What is [[Art]]? \n\nIn Ancient [[Greek philosophy]], these five broad types of questions were respectively called analytical or [[logic|logical]], [[epistemology|epistemological]], [[ethics|ethical]], [[metaphysics|metaphysical]], and [[aesthetics|aesthetic]]. They are not the only ones, and [[Aristotle]], who was the first to use this classification, also considered [[politics]], modern day [[physics]], [[geology]], [[biology]], [[meteorology]], and [[astronomy]] some of the other branches of philosophical investigation. The Greeks, through the influence of [[Socrates]] and [[Socratic method|his method]], developed a tradition of [[Analysis (philosophy)|analysis]], dividing a subject into its components to understand it better.\n\nOther traditions did not always use such labels, or emphasize the same themes. Though [[Hindu philosophy]] has similarities with [[Western philosophy]], there was no word for \'\'philosophy\'\' in [[Japanese language|Japanese]], [[Korean language|Korean]] or [[Chinese language|Chinese]] until the [[19th century]], despite the presence of philosophy there over millennia. [[Chinese philosophy|Chinese philosophers]] in particular had a different conception of categories from the Greeks, and their definitions were not based on common features, but were usually metaphorical and referred to several subjects at once [http://www.rep.routledge.com/article/G001]. However, there are no distinct boundaries between categories even in Western philosophy, and since at least the 19th century, Western philosophical works have more often addressed a nexus of questions without sorting them into distinct areas.\n\n== Motives, goals and methods ==\n\nThe word \"philosophy\" is derived from the ancient Greek (\'\'Φιλοσοφία\'\', \'\'philosophia\'\') which roughly means \"love of wisdom\". It suggests a vocation for questioning, learning, and spreading knowledge. Many philosophers are curious about the world, humanity, existence, values, understanding, and the nature of things.\n\nPhilosophy can be distinguished from other disciplines by its methods of inquiry. Philosophers often frame their questions as problems or puzzles, in order to give clear examples of their doubts about a subject they find interesting, wonderful or confusing. Often these questions are about the assumptions behind a belief, or about methods by which people reason.\n\nPhilosophers typically frame problems in a logical manner, historically using [[syllogism]]s of [[traditional logic]], since [[Gottlob Frege|Frege]] and [[Bertrand Russell|Russell]] increasingly using [[formal system]]s, such as [[predicate calculus]], and then work towards a solution based on critical reading and reasoning. Like Socrates, they search for answers through discussion, or by responding to the arguments of others, or through careful personal contemplation. Philosophers debate the relative merits of these methods, asking whether or not, for example, philosophical \"solutions\" are objective, definitive, and say something informative about reality; or rather whether these solutions just give more clarity or insight on the logic of our language, or even act as personal therapy. Philosophers seek justification for the answers to their questions.\n\nLanguage is the philosopher’s primary tool. In the [[Analytic philosophy|Analytic tradition]], debates about philosophical method have been closely connected to debates about the relationship between philosophy and language. There is a similar concern in [[Continental philosophy]]. [[Meta-philosophy]], the \"philosophy of philosophy\", studies the nature of philosophical problems, philosophical solutions, and the proper method for getting from one to another (cf. [[Pataphysics]]). These debates are also connected to debates over language and interpretation. \n\nThese debates are not \'\'less\'\' relevant to philosophy as a whole, since the nature and role of philosophy itself has always been an essential part of philosophical deliberations. On the contrary, the existence of fields like Pataphysics indicates a lengthy debate beyond the scope of this article. Such questions are discussed at greater length [[Meta-philosophy|elsewhere]].\n\nPhilosophy is also approached through relationships between components, as in [[Structuralism]] and [[Recursionism]]. There is, furthermore, the [[philosophy of science]] in general, and [[Biophilosophy|biophilosophy]], in particular.\n\n== Non-academic uses of the word ==\n\nPopularly, the word \'\'philosophy\'\' is often used to mean any form of assimilated knowledge, or any person\'s perspective on life (as in \"philosophy of life\") or basic principles behind or method of achieving something (as in \"my philosophy about driving on highways\"). This is also commonly referred to as a \'\'[[worldview]]\'\'.\n\nTo take another example, reacting to a tragedy \'\'philosophically\'\' might mean abstaining from passionate reactions in favour of intellectualized detachment. That particular definition arose from the example of [[Socrates]], who calmly discussed the nature of the soul with his followers before consuming the hemlock used to execute him on the orders of an Athenian jury. The [[Stoic]]s followed Socrates in seeking freedom from their passions, hence the modern use of \'\'stoic\'\' to refer to calm fortitude.\n\n==Philosophical traditions==\n\nMembers of many societies have considered philosophical questions, and built philosophic traditions based upon each other\'s works. The term \"philosophy\" in a Euro-American [[academia|academic]] context may misleadingly refer solely to the philosophic traditions of [[Western civilization|Western European civilization]]. This is also called \'\'\"[[Western philosophy]]\"\'\', especially when contrasted with \'\'\"[[Eastern philosophy]]\"\'\', which broadly subsumes the philosophic traditions of [[Asia]]. Both terms group together diverse, even incompatible schools of thought.\n\nEastern and Middle Eastern philosophical traditions have influenced Western philosophers. Russian, Jewish, Islamic and recently Latin American philosophical traditions have contributed to, or been derivative of Western philosophy, yet retain a unique identity.\n\nIt is convenient to divide contemporary Western academic philosophy into two traditions, since applications of the term \'\'\"Western philosophy\"\'\' over the past century frequently reveal a bias towards one or the other.\n\n\'\'[[Analytic philosophy]]\'\' is characterized by a precise approach to analysing the language of philosophical questions. The purpose is to lay bare any underlying conceptual confusion. It dominates Anglo-American philosophy, but has some roots in continental Europe, where it is also practiced. The tradition of Analytic philosophy began with [[Gottlob Frege]] at the turn of the twentieth-century, passing on to [[Bertrand Russell]], [[G. E. Moore]] and [[Ludwig Wittgenstein]].\n\n\'\'[[Continental philosophy]]\'\' is a label for various dissimilar schools, predominant in continental Europe, but also at home in many English-speaking Humanities departments, that may examine language, metaphysical approaches, [[political theory]], perspectivalism, or various aspects of the [[arts]] and [[culture]]. One of the highlights of recent continental philosophical schools is the attempt to reconcile academic philosophy with issues that appear non-philosophical, subverting common expectations of what philosophy is meant to be.\n\nThe divisions between all of these traditions are arbitrary. The differences between traditions are often based on their favored historical philosophers, favored emphases on ideas, and styles or languages of writing. The subject matter and dialogues of each can be studied using methods derived from the others, and there have been significant commonalities and exchanges between them.\n\nOther philosophical traditions, such as in Africa, are rarely considered in foreign academia. On account of the widespread emphasis on Western philosophy as a reference point, the study, preservation and dissemination of valuable but not widely known non-Western philosophical works faces many obstacles. \n\nLanguages can also be a barrier or a vehicle to ideas. The question of what and whether specific languages can be considered essential to philosophizing is a theme in the works of many recent philosophers.\n\n===Western philosophy===\n\nThe Western philosophic tradition began with the [[Greek philosophy|Greeks]] and continues to the present day. Famous Western [[philosopher]]s include [[Socrates]], [[Plato]], [[Aristotle]], [[Augustine of Hippo]], [[Thomas Aquinas]], [[Michel de Montaigne]], [[Francis Bacon]], [[René Descartes]], [[Baruch Spinoza]], [[George Berkeley]], [[John Locke]], [[David Hume]], [[Jean-Jacques Rousseau]], [[Immanuel Kant]], [[Georg Wilhelm Friedrich Hegel]], [[Arthur Schopenhauer]], [[Søren Kierkegaard]], [[Friedrich Nietzsche]], [[Gottlob Frege]], [[Bertrand Russell]], [[Henri Bergson]], [[Edmund Husserl]], [[Ludwig Wittgenstein]], [[Martin Heidegger]], [[Jean-Paul Sartre]], [[Theodor Adorno]], [[Jacques Derrida]], [[W. V. Quine|Willard van Orman Quine]] and [[Karl Popper]].\n\nSeveral other more contemporary, famous Western [[philosopher]]s include [[Hilary Putnam]], [[David Wiggins]], [[John Rawls]], [[Bernard Williams]], [[Saul Kripke]], [[Donald Davidson (philosopher)|Donald Davidson]], [[Thomas Nagel]], [[Jerry A. Fodor]] and [[Frank Jackson]].\n\nWestern philosophy is sometimes divided into several branches for study, based on the questions addressed by people working in different parts of the field. The most common categories are [[metaphysics]], [[epistemology]], [[ethics]] and [[aesthetics]]. Some of the other disciplines include [[logic]], [[philosophy of language]] and [[political philosophy]]. For more information, see [[Western philosophy]].\n\n===Eastern philosophy===\n\nEastern philosophy follows the broad traditions that originated from or were popular within ancient India and China. Famous Eastern philosophers include [[Kapila]], [[Yajnavalkya]], [[Gautama Buddha]], [[Akshapada Gotama]], [[Nagarjuna]], [[Confucius]], [[Lao Zi]] (Lao Tzu), [[Zhuang Zi]] (Chuang Tzu), [[Mencius]], [[Xun Zi]], [[Zhu Xi]], [[Wang Yangming]], [[Dharmakirti]], [[Adi_Sankara|Sankara]], [[Ramanuja]], [[Vivekananda]], [[Aurobindo]] and [[Sarvepalli Radhakrishnan]].\n\nIndian philosophy is perhaps the most comparable to Western philosophy. For instance, the ancient [[Hindu_philosophy#Nyaya|Nyaya]] school of [[Hindu philosophy]] explores [[logic]] as some modern Analytic philosophers do; but there are important differences - e.g. ancient Indian philosophy traditionally emphasized the teachings of schools or ancient texts, rather than individual philosophers, most of whom either wrote anonymously or whose names were simply not transmitted or recorded. For more information on Eastern philosophies, see [[Eastern philosophy]].\n\nOther philosophical traditions are linked below.\n\n==Applied philosophy==\n\nThough often seen as a wholly abstract field, philosophy is not without practical applications. The most obvious applications are those in [[ethics]] -- [[applied ethics]] in particular -- and in [[political philosophy]]. The political philosophies of [[Confucius]], [[Kautilya]], [[Sun Tzu]], [[John Locke]], [[Jean-Jacques Rousseau]], [[Karl Marx]], [[John Stuart Mill]], [[Mahatma Gandhi]], and [[John Rawls]] have shaped and been used to justify governments and their actions. \n\n[[Philosophy of education]] deserves special mention, as well; progressive education as championed by [[John Dewey]] has had a profound impact on educational practices in the [[United States]] in the twentieth century. It could be argued that some [[New Age]] philosophies, such as the \"[[Celestine Prophecy]]\", inadvertently educate people about human psychology and power relationships through the use of spiritual metaphor.\n\nOther important applications can be found in [[epistemology]], which might help one to regulate one\'s notions of what knowledge, evidence, and justified belief are. Two useful ways that epistemology and [[logic]] can inform the real world are through the fields of [[journalism]] and police investigation. [[Informal logic]] has fantastic applications, helping citizens to be critical in reading [[rhetoric]] and in everyday discussion. [[Philosophy of science]] discusses the underpinnings of the [[scientific method]]. [[Aesthetics]] can help to interpret discussions of [[art]]. Even [[ontology]], surely the most abstract and least practical-seeming branch of philosophy, has had important consequences for logic and [[computer science]].\n\nIn general, the various \"philosophies of,\" such as [[philosophy of law]], can provide workers in their respective fields with a deeper understanding of the theoretical or conceptual underpinnings of their fields. \n\nOften, philosophy is seen as an investigation into an area not understood well enough to be its own branch of knowledge. What were\nonce mearly philosophical pursuits have evolved into the modern day fields of [[psychology]], [[sociology]], [[linguistics]], and\n[[economics]] (among others). [[Computer science]], [[cognitive science]] and [[artificial intelligence]] are modern areas of research that philosophy has played a role in developing.\n\nMoreover, a burgeoning profession devoted to applying philosophy to the problems of ordinary life has recently developed, called [[philosophical counseling]]. Moreover, many Eastern philosophies can and do help millions of people with anxiety problems through their emphasis on meditation for calming the mind and the connection between the health of the body and the health of the soul.\n\n==See also==\n \n*[[Western philosophy]] \n*[[History of western philosophy]] \n*[[Eastern philosophy]] \n*[[Chinese philosophy]] \n*[[Buddhist philosophy]] \n*[[Hindu philosophy]] \n*[[Islamic philosophy]]\n*[[Jewish philosophy]]\n*[[Russian philosophy]]\n*[[Czech philosophy]]\n*[[Japanese philosophy]]\n*[[List of philosophers]]\n*[[Analytic philosophy]]\n*[[Continental philosophy]]\n*[[Critical theory]]\n*[[Meta-philosophy]]\n*[[List of philosophical topics]]\n*[[List of philosophies]]\n\n== Bibliography ==\n\n=== Introductions ===\n==== For beginners ====\n*\'\'Philosophy: A Very Short Introduction\'\' by [[Edward Craig]]\n*\'\'The Complete Idiot\'s Guide to Philosophy (2nd Edition)\'\' by Jay Stevenson \n*\'\'Sophie\'s World\'\' by [[Jostein Gaarder]]\n*\'\'Philosophy Now\'\' magazine\n*\'\'Big Questions: A Short Introduction to Philosophy\'\' by [[Robert Solomon|Robert C. Solomon]]\n*\'\'A Short History of Philosophy\'\' by Robert C. Solomon, Kathleen M. Higgins\n* \'\'[http://philosophy.hku.hk/think/phil/russell/ The Problems of Philosophy]\'\' by Bertrand Russell\n*\'\'Philosophy: The Basics\'\' by Nigel Warburton.\n*Sober, E. (2001). \'\'Core Questions in Philosophy: A Text with Readings\'\'. Upper Saddle River, Prentice Hall.\n*[http://www.philosophicalsociety.com/What%20Philosophy%20Is.htm What Philosophy Is]\n\n==== Topical introductions ====\n\n*\'\'A Short History of Modern Philosophy\'\' by [[Roger Scruton]]\n*\'\'World Philosophies\'\' by Ninian Smart\n*\'\'Indian Philosophy: a Very Short Introduction\'\' by Sue Hamilton\n*\'\'A Brief Introduction to Islamic Philosophy\'\' by Oliver Leaman\n*\'\'Eastern Philosophy For Beginners\'\' by Jim Powell, Joe Lee\n*\'\'An Introduction to African Philosophy\'\' by Samuel Oluoch Imbo\n*\'\'Philosophy in Russia: From Herzen to Lenin and Berdyaev\'\' by [[Frederick Copleston]]\n*\'\'Continental Philosophy: A Very Short Introduction\'\' by Simon Critchley\n*\'\'Complete Idiot\'s Guide to Eastern Philosophy\'\' by Jay Stevenson\n*\'\'Classic Asian Philosophy: A Guide to the Essential Texts\'\' by Joel J. Kupperman\n\n==== Anthologies ====\n\n*\'\'Philosophic Classics: From Plato to Derrida (4th Edition)\'\' by Forrest E. Baird\n*\'\'Classics of Philosophy (Vols. 1 & 2, 2nd edition)\'\' by Louis P. Pojman\n*\'\'Classics of Philosophy: The 20th Century (Vol. 3)\'\' by Louis P. Pojman \n*\'\'The English Philosophers from Bacon to Mill\'\' by Edwin Arthur Burtt\n*\'\'European Philosophers from Descartes to Nietzsche\'\' by Monroe Beardsley\n*\'\'Contemporary Analytic Philosophy: Core Readings\'\' by James Baillie \n*\'\'Existentialism: Basic Writings (Second Edition)\'\' by Charles Guignon, Derk Pereboom \n*\'\'The Phenomenology Reader\'\' by Dermot Moran, Timothy Mooney \n*\'\'Medieval Islamic Philosophical Writings\'\' edited by Muhammad Ali Khalidi \n*\'\'A Source Book in Indian Philosophy\'\' by [[Sarvepalli Radhakrishnan]], Charles A. Moore \n*\'\'A Source Book in Chinese Philosophy\'\' by [[Wing-Tsit Chan]]\n*Kim, J. and Ernest Sosa, Ed. (1999). \'\'Metaphysics: An Anthology\'\'. Blackwell Philosophy Anthologies. Oxford, Blackwell Publishers Ltd.\n\n=== Reference works ===\n*\'\'The Oxford Companion to Philosophy\'\' edited by [[Ted Honderich]]\n*\'\'The Cambridge Dictionary of Philosophy\'\' by Robert Audi\n*\'\'[[The Routledge Encyclopedia of Philosophy]]\'\' (10 vols.) edited by Edward Craig, Luciano Floridi (also available online by subscription); or \n*\'\'The Concise Routledge Encyclopedia of Philosophy\'\' edited by Edward Craig (an abridgement)\n*\'\'Routledge History of Philosophy\'\' (10 vols.) edited by John Marenbon\n*\'\'History of Philosophy\'\' (9 vols.) by Frederick Copleston\n*\'\'A History of Western Philosophy\'\' (5 vols.) by W. T. Jones\n*\'\'Encyclopaedia of Indian Philosophies\'\' (8 vols.), edited by Karl H. Potter et al (\'\'\'first 6 volumes out of print\'\'\')\n*\'\'Indian Philosophy\'\' (2 vols.) by Sarvepalli Radhakrishnan\n*\'\'A History of Indian Philosophy\'\' (5 vols.) by [[Surendranath Dasgupta]]\n*\'\'History of Chinese Philosophy\'\' (2 vols.) by [[Fung Yu-lan]], Derk Bodde\n*\'\'Encyclopedia of Chinese Philosophy\'\' edited by Antonio S. Cua \n*\'\'Encyclopedia of Eastern Philosophy and Religion\'\' by Ingrid Fischer-Schreiber, Franz-Karl Ehrhard, Kurt Friedrichs\n*\'\'Companion Encyclopedia of Asian Philosophy\'\' by Brian Carr, Indira Mahalingam\n*\'\'A Concise Dictionary of Indian Philosophy: Sanskrit Terms Defined in English\'\' by John A. Grimes\n*\'\'History of Islamic Philosophy\'\' edited by Seyyed Hossein Nasr, Oliver Leaman \n*\'\'History of Jewish Philosophy\'\' edited by Daniel H. Frank, Oliver Leaman\n*\'\'A History of Russian Philosophy: From the Tenth to the Twentieth Centuries\'\' by Valerii Aleksandrovich Kuvakin\n*Ayer, A. J. et al. Ed. (1994) \'\'A Dictionary of Philosophical Quotations\'\'. Blackwell Reference Oxford. Oxford, Basil Blackwell Ltd.\n*Blackburn, S., Ed. (1996)\'\'The Oxford Dictionary of Philosophy\'\'. Oxford, Oxford University Press. \n*Mauter, T., Ed. \'\'The Penguin Dictionary of Philosophy\'\'. London, Penguin Books.\n*Runes, D., ED. (1942). \'\'The Dictionary of Philosophy\'\'. New York, The Philosophical Library, Inc.\n*Angeles, P. A., Ed. (1992). \'\'The Harper Collins Dictionary of Philosophy\'\'. New York, Harper Perennial.\n*Bunnin, N. et. al.,Ed.(1996) \'\'The Blackwell Companion to Philosophy\'\'. Blackwell Companions to Philosophy. Oxford, Blackwell Publishers Ltd.\n*Popkin, R. H. (1999). \'\'The Columbia History of Western Philosophy\'\'. New York, Columbia University Press.\n\n== External links ==\n{{wikiquote}}\n{{wikiversity}}\n{{Wikisource}}\nSome of these websites contain links to online texts of philosophy, as do many related articles on Wikipedia.\n\n===Resources===\n*[http://epistemelinks.com/ EpistemeLinks.com : philosophy resources on the internet]\n*[http://www.erraticimpact.com/default.htm Erratic Impact: The Philosophy Research Base]\n*[http://www.earlham.edu/~peters/philinks.htm Guide to Philosophy on the Internet]\n*[http://www.galilean-library.org/philosophy.html/ Introducing Philosophy Series] by Paul Newall, aimed at beginners.\n*[http://www.iceion.com/philo/philo.php Introduction to Philosophy (abridgement of other sources)]\n*[http://melbournephilosophy.com/index.shtml Melbourne Philosophy: Philosophy in Melbourne, Australia (noncommercial, variety of resources, wiki)]\n*[http://www.liv.ac.uk/pal/ Philosophy @ large, A webguide for the philosophy community provided by Liverpool University]\n*[http://www-personal.monash.edu.au/~dey/phil/ Philosophy in Cyberspace]\n*[http://www.philosophicalsociety.com/ Philosophical Society.com]\n*[http://www.rep.routledge.com/signpost-articles Routledge Encyclopedia of Philosophy - \'\'Signpost articles free, others require subscription\'\']\n*[http://plato.stanford.edu/ Stanford Encyclopedia of Philosophy]\n*[http://www.utm.edu/research/iep/ The Internet Encyclopedia of Philosophy]\n\n===Forums===\n*[http://www.philosophyforums.com Philosophy Forums] -- a place to discuss Philosophy with a discursive library on Philosophical topics.\n*[http://www.talkphilosophy.org Talk Philosophy] -- A place to discuss topics in all areas of philosophy from ethics to aesthetics.\n*[http://www.galilean-library.org The Galilean Library] -- a place to discuss philosophy from basic to advanced levels, with a library of introductory essays for beginners.\n*[http://www.philiwiki.com PhiliWiki] -- the Internet\'s first online Wiki for the development of multiple points of view on a range of philosophical topics.\n\n===Organizations, Websites and Associations===\n*[http://philosophy.kitoba.com Columbus Philosophers]\n*[http://philosophy.meetup.com Philosophy Meetup]\n*[http://www.philosophicalsociety.com/ Philosophical Society.com]\n*[http://philosopher.org The Society for Philosophic Inquiry (Socrates Cafe)]\n*[http://www.trianglephilosophy.com Triangle Philosophy]\n\n\n\n[[af:Filosofie]]\n[[ar:فلسفة]]\n[[an:Filosofía]]\n[[ast:Filosofía]]\n[[bg:Философия]]\n[[bs:Filozofija]]\n[[ca:Filosofia]]\n[[cs:Filosofie]]\n[[da:Filosofi]]\n[[de:Philosophie]]\n[[et:Filosoofia]]\n[[el:Φιλοσοφία]]\n[[es:Filosofía]]\n[[eo:Filozofio]]\n[[fa:فلسفه]]\n[[fr:Philosophie]]\n[[fy:Filosofy]]\n[[gd:Feallsanachd]]\n[[gl:Filosofía]]\n[[ko:철학]]\n[[hi:दर्शनशास्त्र]]\n[[hr:Filozofija]]\n[[io:Filozofio]]\n[[id:Filsafat]]\n[[ia:Philosophia]]\n[[it:Filosofia]]\n[[he:פילוסופיה]]\n[[ku:Felsefe]]\n[[la:Philosophia]]\n[[lv:Filozofija]]\n[[lt:Filosofija]]\n[[lb:Philosophie]]\n[[hu:Filozófia]]\n[[ms:Falsafah]]\n[[nl:Filosofie]]\n[[ja:哲学]]\n[[no:Filosofi]]\n[[pl:Filozofia]]\n[[pt:Filosofia]]\n[[ro:Filozofie]]\n[[ru:Философия]]\n[[simple:Philosophy]]\n[[sk:Filozofia]]\n[[sl:Filozofija]]\n[[sr:Филозофија]]\n[[fi:Filosofia]]\n[[sv:Filosofi]]\n[[tl:Pilosopiya]]\n[[tr:Felsefe]]\n[[uk:Філософія]]\n[[vo:Filosop]]\n[[zh-cn:哲学]]\n[[zh-tw:哲學]]\n\n[[Category:Culture]]\n[[Category:Philosophy]]','',13,'Budhi','20041225124914','',0,0,0,1,0.015620302928,'20041229235111','79958774875085'); INSERT INTO cur VALUES (2037,0,'Bayes_theorem','#redirect [[Bayes\' theorem]]','',13,'Budhi','20041225125053','',0,1,0,1,0.440480857177,'20050303214455','79958774874946'); INSERT INTO cur VALUES (2038,0,'I.i.d._random_variables','Hiji \'\'sekuen\'\' atawa koleksi [[variabel acak]] is \'\'\'independent and identically distributed (i.i.d.)\'\'\' if each has the same [[probability distribution]] as any of the others and all are mutually [[statistical independence|independent]]. From the point of view of the [[sample space]] \'\'X\'\', this means that \'\'n\'\' trials correspond on \'\'X\'\'\'\'n\'\' to the \'\'n\'\'-fold product of the [[probability measure]] for one trial.\n\n{{msg:stub}}','',13,'Budhi','20050104072504','',0,0,0,0,0.023643017313,'20050104072504','79949895927495'); INSERT INTO cur VALUES (2039,0,'Frequentist','#REDIRECT [[Frequency probability]]','',13,'Budhi','20041225130851','',0,1,0,1,0.151617454649,'20050303214455','79958774869148'); INSERT INTO cur VALUES (2040,0,'Bukti','\'\'\'Bukti\'\'\' nyaéta,\n\n*[[Kajadian]] naon baé nu bisa ngabuktikeun atawa ngabantah hiji proposisi, tempo [[kanyataan]].\n*[[Kasaksian]] naon baé nu ku [[pangadilan]] bisa dipaké pikeun [[dispute resolution|judicial or administrative proceeding]].\n\n==Evidence in the United States federal courts==\nPrior to the 1975 enactment of the Federal Rules of Evidence (FRE), the [[Rules of evidence|rules of evidence]] were governed primarily by a chaotic body of [[case law]] at both the federal and state levels. The FRE and its state counterparts were mostly inspired by the California Evidence Code, which had been enacted in 1872.\n\nThe success of the CEC stimulated the [[U.S. Supreme Court]] into promulgating drafts of the FRE in 1969, 1971 and 1972; Congress then exercised its right under the Rules Enabling Act to suspend implementation of the FRE until it could study them further. After a long delay blamed on the [[Watergate]] scandal, Congress finally allowed the FRE to become federal law in 1974. \n\nFRE 102 includes the following elements in the \"Purpose and Construction\" of the [[Federal Rules of Evidence]]: \"These rules shall be construed to...\"\n*secure fairness in administration\n*eliminate unjustifiable expense and delay\n*promote growth and development of the law of evidence to the end that the truth may be ascertained, and proceedings justly determined\n\nThe following is the table of contents of the FRE:\n\nI. General Provisions\n*Rule 101: Scope\n*Rule 102: Purpose and Construction\n*Rule 103: Rulings on Evidence\n*Rule 104: Preliminary Questions\n*Rule 105: Limited Admissibility\n*Rule 106: Remainder of or Related Writings or Recorded Statements\nII. Judicial Notice\n*Rule 201: Judicial Notice of Adjudicative Facts\nIII. Presumptions in Civil Actions and Proceedings\n*Rule 301: Presumptions in General Civil Actions and Proceedings\n*Rule 302: Applicability of State Law in Civil Actions and Proceedings\n\'\'(to be cont.)\'\'\n\n\'\'See also:\'\' [[Law]], [[Affidavit]], [[Circumstantial evidence]], [[Corroborating evidence]], [[Rebuttal]], [[chain of custody]], [[Forensic evidence]]\n\n----\n\'\'\'Evidence\'\'\' is also the [[enlightenment]] file-manager for [[Linux]]\n\n----\n\'\'\'Evidence\'\'\' is also the title of a [[science fiction]] [[short story]] by [[Isaac Asimov]]. See: [[Evidence (Asimov)]].\n\n[[simple:Evidence]]\n[[Category:Evidence]][[Category:Law]]','',3,'Kandar','20050128043511','',0,0,0,0,0.433983160368,'20050128043511','79949871956488'); INSERT INTO cur VALUES (2041,0,'Bayes_factors','#redirect [[Bayes factor]]','',13,'Budhi','20041225131037','',0,1,0,1,0.419971280117,'20050303214455','79958774868962'); INSERT INTO cur VALUES (2042,0,'Sufficient_statistic','#REDIRECT [[Sufficiency_(statistics)]]','',13,'Budhi','20041225131128','',0,1,0,1,0.035704108244,'20041225131128','79958774868871'); INSERT INTO cur VALUES (2043,0,'Limit','A \'\'\'limit\'\'\' can be:\n\n* [[Limit (mathematics)]], including:\n** [[Limit of a function]]\n** [[Limit of a sequence]]\n** [[Net (topology)]]\n** [[Limit (category theory)]]\n* A [[constraint]] (mathematical, physical, economical, legal, etc.) in the form of an [[inequality]], such as:\n** [[Chandrasekhar limit]]\n** [[Greisen-Zatsepin-Kuzmin limit]]\n** [[Budget constraint]]\n** [[Speed limit]]\n** [[Age of consent]]\n* An [[extreme value]] or [[boundary]], such as:\n** [[High frequency limit]]\n* [[Limit (music)]] in [[just intonation]]\n\n{{disambig}}','',13,'Budhi','20041225232058','',0,0,0,1,0.572672954365,'20050303214455','79958774767941'); INSERT INTO cur VALUES (2044,0,'Generalised_f-mean','Dina [[matematik]] jeung [[statistik]], the \'\'\'generalised f-[[mean]]\'\'\' is the natural generalisation of the more familar means such as the [[arithmetic mean]] and the [[geometric mean]], using a function f(x).\n\nIf \'\'f\'\' is a function which maps a [[connected]] subset \'\'S\'\' of the real line to the [[real number]]s, and is both [[continuous]] and [[injective function|injective]] then we can define the \'\'\'f-mean of two numbers\'\'\' \n\n:\'\'x\'\'1, \'\'x\'\'2 in \'\'S\'\' \n\nas\n\n:\\overline{x}=f^{-1}( (f(x_1)+f(x_2))/2 ).\n\nFor \'\'n\'\' numbers \n\n:\'\'x\'\'1, ..., \'\'x\'\'\'\'n\'\' in \'\'S\'\', \n\nthe \'\'\'f-mean\'\'\' is\n\n:\\overline{x}=f^{-1}( (f(x_n)+ \\cdots + f(x_n))/n ).\n\nWe require \'\'f\'\' to be injective in order for the [[inverse function]] \'\'f\'\' -1 to exist. Continuity is required to ensure \n\n:(\'\'f\'\'(\'\'x\'\'1) + \'\'f\'\'(\'\'x\'\'2))/2 \n\nlies within the domain of \'\'f\'\' -1.\n\nSince \'\'f\'\' is injective and continuous, it follows that \'\'f\'\' is [[Monotonic function|strictly increasing]]; and therefore that the \'\'f\'\'-mean is neither larger than the largest number in {\'\'x\'\'\'\'i\'\'} nor smaller than the smallest number in {\'\'x\'\'\'\'i\'\'}.\n\nIf we take \'\'S\'\' to be the real line and \n\n:\'\'f(x) = x\'\', \n\nthen the \'\'f\'\'-mean corresponds to the arithmetic mean.\n\nIf we take \'\'S\'\' to be the set of positive real numbers and \n\n:\'\'f(x) = log x\'\' \n\n(the result does not depend on the base of the [[logarithm]]), then the \'\'f\'\'-mean corresponds to the geometric mean.\n\nIf we take \'\'S\'\' to be the set of positive real numbers and \n\n:\'\'f(x) = 1/x\'\', \n\nthen the \'\'f\'\'-mean corresponds to the [[harmonic mean]].\n\nSee also: [[Jensen\'s inequality]].','',13,'Budhi','20041225232228','',0,0,1,0,0.52064858652,'20041225232228','79958774767771'); INSERT INTO cur VALUES (2045,0,'Ecological_fallacy','#REDIRECT [[Ekologi kaliru]]\n','Ecological fallacy dipindahkeun ka Ekologi kaliru',13,'Budhi','20041225235440','',0,1,0,1,0.04056065182,'20041225235440','79958774764559'); INSERT INTO cur VALUES (2046,0,'Statistician','#REDIRECT [[statistik]]','',13,'Budhi','20041225235724','',0,1,0,1,0.533306415984,'20050303214455','79958774764275'); INSERT INTO cur VALUES (2047,0,'Personal_probability','#REDIRECT [[Bayesian probability]]','',13,'Budhi','20041225235843','',0,1,0,1,0.02235541235,'20050303214455','79958774764156'); INSERT INTO cur VALUES (2048,0,'Probability_axioms','[[kamungkinan|Probabiliti]] P tina sababaraha [[event (probability theory)|kajadian]] E (dilambangkeun ku P(E)) is defined with respect to a \"universe\" or [[sample space]] \\Omega of all possible [[elementary event]]s in such a way that P must satisfy the Kolmogorov axioms.\n\nAlternatively, a probability can be interpreted as a [[measure (mathematics)|measure]] on a [[sigma-algebra|σ-algebra]] of subsets of the sample space, those subsets being the events, such that the measure of the whole set equals 1. This property is important, since it gives rise to the natural concept of [[conditional probability]]. Every set A with non-zero probability defines another probability\n\n: P(B \\vert A) = {P(B \\cap A) \\over P(A)}\n\non the space. This is usually read as \"probability of B given A\". If the conditional probability of B given A is the same as the probability of B, then B and A are said to be [[statistical independence|independent]].\n\nIn the case that the sample space is [[finite]] or [[countable|countably]] infinite, a probability function can also be defined by its values on the elementary events \\{e_1\\}, \\{e_2\\}, ... where \\Omega = {e_1, e_2, ...}.\n\n== Kolmogorov axioms ==\n\nThe following three axioms are known as the \'\'\'Kolmogorov axioms\'\'\', after [[Andrey Kolmogorov]] who developed them.\n\n=== First axiom ===\n\n: For any set E, 0 \\leq P(E) \\leq 1.\n\nThat is, the probability of an event set is represented by a real number between 0 and 1.\n\n=== Second axiom ===\n\n: P(\\Omega) = 1\n\nThat is, the probability that some elementary event in the entire sample set will occur is 1. More specifically, there are no elementary events outside the sample set.\n\nThis is often overlooked in some mistaken probability calculations; if you cannot precisely define the whole sample set, then the probability of any subset cannot be defined either.\n\n=== Third axiom ===\n\n: Any [[countable]] sequence of mutually disjoint events E_1, E_2, ... satisfies P(E_1 \\cup E_2 \\cup \\cdots) = \\sum P(E_i).\n\nThat is, the probability of an event set which is the union of other disjoint subsets is the sum of the probabilities of those subsets. This is called σ-additivity. If there is any overlap among the subsets this relation does not hold.\n\nFor an algebraic alternative to Kolmogorov\'s approach, see [[algebra of random variables]].\n\n== Lemmas in probability ==\n\nFrom the Kolmogorov axioms one can deduce other useful rules for calculating probabilities:\n\n: P(A \\cup B) = P(A) + P(B) - P(A \\cap B)\n\nThat is, the probability that A \'\'or\'\' B will happen is the sum of the\nprobabilities that A will happen and that B will happen, minus the\nprobability that A \'\'and\'\' B will happen. This can be extended to the [[inclusion-exclusion principle]].\n\n: P(\\Omega - E) = 1 - P(E)\n\nThat is, the probability that any event will \'\'not\'\' happen is 1 minus the probability that it will.\n\nUsing conditional probability as defined above, it also follows immediately that\n\n: P(A \\cap B) = P(A) \\cdot P(B \\vert A)\n\nThat is, the probability that A \'\'and\'\' B will happen is the probability\nthat A will happen, times the probability that B will happen \'\'given\'\'\nthat A happened; this relationship gives [[Bayes\' theorem]]. It then follows that A and B are independent if and only if\n\n: P(A \\cap B) = P(A) \\cdot P(B).\n\n== See also ==\n\n* [[frequency probability]]\n* [[personal probability]]\n* [[pilihan probabiliti]]\n* [[statistical regularity]]\n\n[[Category:Probability theory]]\n[[fr:Axiomes des probabilités]]\n[[de:Wahrscheinlichkeitsaxiome]]\n[[es:Axiomas de probabilidad]]\n[[nl:axioma\'s van de kansrekening]] \n[[pl:aksjomaty Kołmogorowa]]\n[[ro:Axiomele probabilităţii]]\n[[ja:確率空間]]','',13,'Budhi','20050107023034','',0,0,0,0,0.158383712696,'20050107023034','79949892976965'); INSERT INTO cur VALUES (2049,0,'Philosophers','#REDIRECT [[Philosopher]]','',13,'Budhi','20041226000036','',0,1,0,1,0.29688373882,'20050303214455','79958773999963'); INSERT INTO cur VALUES (2050,0,'Philosopher','A \'\'\'philosopher\'\'\' is a person devoted to studying and producing results in [[philosophy]]. The word, \"philosopher,\" literally means \"lover of wisdom.\"\n\n==Popular Western philosophers in (approximate) historical order==\n\n
    \n
    \n{| id=\"toc\" style=\"margin: 0 2em 0 2em;\"\n|-\n| style=\"background:#ccccff\" align=\"center\" | This article is part of the \'\'\'[[Influential Western Philosophers]]\'\'\' series\n|-\n| align=\"center\" style=\"font-size: 90%;\" | [[Pre-Socratic philosophy|Presocratics]] | [[Socrates]] | [[Plato]] | [[Aristotle]] | [[Epicureans]] | [[Stoics]] | [[Plotinus]] | [[Augustine of Hippo]] | [[Anicius Manlius Severinus Boëthius|Boëthius]] | [[Al-Farabi]] | [[Anselm of Canterbury|Anselm]] | [[Peter Abelard]] | [[Averroes|Averroës]] | [[Maimonides]] | [[Thomas Aquinas]] | [[Albertus Magnus]] | [[Duns Scotus]] | [[Ramon Llull]] | [[William of Ockham|Occam]] | [[Giovanni Pico della Mirandola]] | [[Marsilio Ficino]] | [[Michel de Montaigne]] | [[René Descartes]] | [[Thomas Hobbes]] | [[Blaise Pascal]] | [[Baruch Spinoza]] | [[John Locke]] | [[Nicolas Malebranche]] | [[Gottfried Leibniz]] | [[Giambattista Vico]] | [[Julien Offray de La Mettrie]] | [[George Berkeley]] | [[Charles de Secondat, Baron de Montesquieu|Baron de Montesquieu]] | [[David Hume]] | [[Voltaire]] | [[Jean-Jacques Rousseau]] | [[Denis Diderot]] | [[Johann Gottfried Herder|Johann Herder]] | [[Immanuel Kant]] | [[Jeremy Bentham]] | [[Friedrich Schleiermacher]] | [[Johann Gottlieb Fichte]] | [[Georg Wilhelm Friedrich Hegel|G. W. F. Hegel]] | [[Friedrich Wilhelm Joseph von Schelling|Friedrich von Schelling]] | [[Karl Wilhelm Friedrich von Schlegel|Friedrich von Schlegel]] | [[Arthur Schopenhauer]] | [[Søren Kierkegaard]] | [[Henry David Thoreau]] | [[Ralph Waldo Emerson]] | [[John Stuart Mill]] | [[Karl Marx]] | [[Mikhail Bakunin]] | [[Friedrich Nietzsche]] | [[Vladimir Soloviev]] | [[William James]] | [[Wilhelm Dilthey]] | [[Charles Sanders Peirce|C. S. Peirce]] | [[Gottlob Frege]] | [[Edmund Husserl]] | [[Henri Bergson]] | [[Ernst Cassirer]] | [[John Dewey]] | [[Benedetto Croce]] | [[José Ortega y Gasset]] | [[Alfred North Whitehead]] | [[Bertrand Russell]] | [[Ludwig Wittgenstein]] | [[Ernst Bloch]] | [[Georg Lukács]] | [[Martin Heidegger]] | [[Rudolf Carnap]] | [[Simone Weil]] | [[Maurice Merleau-Ponty]] | [[Jean-Paul Sartre]] | [[Simone de Beauvoir]] | [[Georges Bataille]] | [[Theodor Adorno]] | [[Max Horkheimer]] | [[Hannah Arendt]] | [[Cornelius Castoriadis]]\n|}\n
    \n\n\n
    \n{| id=\"toc\" style=\"margin: 0 2em 0 2em;\"\n|-\n| style=\"background:#ccccff\" align=\"center\" | This article is part of \'\'\'The [[Contemporary Philosophers]]\'\'\' series\n|-\n| align=\"left\" style=\"background:#ccccff; font-size: 85%;\" | [[Analytic philosophy|Analytic]] philosophers:\n|-\n| align=\"center\" style=\"font-size: 90%;\" | [[Simon Blackburn]] | [[Ned Block]] | [[David Chalmers]] | [[Patricia Churchland]] | [[Paul Churchland]] | [[Donald Davidson (philosopher)| Donald Davidson]] | [[Daniel Dennett]] | [[Jerry Fodor]] | [[Susan Haack]] | [[Olly Hewitt]] [[Jaegwon Kim]] | [[Saul Kripke]] | [[Thomas Samuel Kuhn]] | [[Bryan Magee]] | [[Ruth Barcan Marcus]] | [[Colin McGinn]] | [[Thomas Nagel]] | [[Robert Nozick]] | [[Martha Nussbaum]] | [[Alvin Plantinga]] | [[Karl Popper]] | [[Hilary Putnam]] | [[W. V. Quine]] | [[John Rawls]] | [[Richard Rorty]] | [[Roger Scruton]] | [[Peter Singer]] | [[John Searle]] | [[Charles Taylor (philosopher) | Charles Taylor]]\n|-\n| align=\"left\" style=\"background:#ccccff; font-size: 85%;\" | [[Continental philosophy|Continental]] philosophers:\n|-\n| align=\"center\" style=\"font-size: 90%;\" | [[Louis Althusser]] | [[Giorgio Agamben]] | [[Roland Barthes]] | [[Jean Baudrillard]] | [[Isaiah Berlin]] | [[Maurice Blanchot]] | [[Pierre Bourdieu]] | [[Hélène Cixous]] | [[Guy Debord]] | [[Gilles Deleuze]] | [[Jacques Derrida]] | [[Michel Foucault]] | [[Hans-Georg Gadamer]] | [[Jürgen Habermas]] | [[Werner Hamacher]] | [[Julia Kristeva]] | [[Henri Lefebvre]] | [[Claude Lévi-Strauss]] | [[Emmanuel Levinas]] | [[Jean-François Lyotard]] | [[Paul de Man]] | [[Jean-Luc Nancy]] | [[Antonio Negri]] | [[Paul Ricoeur]] | [[Michel Serres]] | [[Paul Virilio]] | [[Slavoj Zizek|Slavoj Žižek]]\n|}\n
    \n\n\nNot listed above: (some of) [[The Presocratics]] -- [[Epicurus]] place after Aristotle --[[Hellenistic]] Philosophers -- [[Cicero]] -- [[Avicenna]] -- [[Sir Thomas Browne]] -- [[Francis Bacon]] -- [[Thomas Reid]] -- [[Dugald Stewart]] -- [[James Mill]] -- [[Rudolf Steiner]] -- [[Albert Schweitzer]] -- [[G. E. Moore]] -- [[Albert Camus]] -- [[Georg Henrik von Wright]] -- [[Mortimer Adler]] -- [[Nelson Goodman]] -- [[Imre Lakatos]] -- [[Ayn Rand]] -- [[Paul Feyerabend]] -- [[Mario Bunge]] -- [[Douglas Hofstadter]] -- [[Pierre Teilhard de Chardin]]\n\n==Eastern philosophers in approximate historical order:==\n[[Gautama Buddha]] -- [[Confucius]] -- [[Lao Zi]] -- [[Rhazes]] -- [[Mencius]] -- [[Zhuang Zi]] -- [[Xun Zi]] -- [[Nagarjuna]] -- [[Bodhidharma]] -- [[Shankara]] -- [[Dogen]] -- [[Zhu Xi]] -- [[Feng Youlan]] -- [[Sarvepalli Radhakrishnan]]\n\n==Philosophers: listed by philosophical school==\n\nSee [[Philosophical Movements]].\n\n==Nicknames of Medieval Philosophers==\nSeveral medieval philosophers have been given [[Latin]] nicknames -- some by their contemporaries, others by historians. For example:\n*[[Francis Mayron]] - \'\'Doctor acutus\'\', the acute doctor, or \'\'Doctor illuminatus\'\'\n*St. [[Thomas Aquinas]] - \'\'Doctor Angelicus\'\', the angelic doctor, or \'\'Doctor Communis\'\'\n*[[William of Ockham]] - \'\'Doctor Invincibilis\'\'\n*[[Alexander of Hales]] - \'\'Doctor Irrefragibilis\'\'\n*[[Roger Bacon]] - \'\'Doctor Mirabilis\'\', the wonderful doctor\n*[[John Bassol]] - \'\'Doctor Ordinatissimus\'\', the most methodical doctor\n*St. [[Bonaventure]] - \'\'Doctor Seraphicus\'\'\n*[[Henry Goethals]] (\'\'[[Hendricus Bonicollius]]\'\') - \'\'Doctor Solemnis\'\', the solemn doctor\n*[[Richard Middleton (Lord Chancellor)|Richard Middleton]] - the solid doctor, or the profound doctor\n*[[Duns Scotus]] - \'\'Doctor Subtilis\'\', the discriminating doctor, or \'\'Doctor Marianus\'\'\n*[[Albertus Magnus]] - \'\'Doctor Universalis\'\'\n*[[Durandus de Sancto Portiano]] - the most resolute doctor\n*[[Thomas Bradwardine]] - the profound doctor\n*[[Jean Ruysbroeck]] (\'\'Joannes Ruysbrokius\'\') - the divine doctor\nSee Also the articles at: [[Philosophy]], [[Eastern philosophy]], [[Epistemology]], [[Ethics]], [[Metaphysics]], [[Aesthetics]], [[Ontology]], [[Logic]], [[Reason]], [[Mathematician]]s, [[Scientist]]s, [[List of philosophers]], and a fuller listing at [[:Category:Philosophers]].\n\n----\n\'\'\'\'\'The Philosopher\'\'\'\'\' is also the nickname of [[Joseph Haydn]]\'s \'\'[[Symphony No. 22 (Haydn)|Symphony No. 22]]\'\'.\n\n[[Category:Philosophy]]\n[[Category:Humanities occupations]]\n[[de:Philosoph]][[eo:Filozofo]][[es:Filosofos A-Z]][[fr:Philosophe]][[gd:Feallsanachd]][[nl:Filosoof]][[pt:Filósofos]][[sl:filozof]][[sv:Filosof]][[uk:Філософ]]','',13,'Budhi','20041226000107','',0,0,0,1,0.174150236473,'20041229235111','79958773999892'); INSERT INTO cur VALUES (2051,0,'Eclectic_probability','#REDIRECT [[Pilihan probabiliti]]\n','Eclectic probability dipindahkeun ka Pilihan probabiliti',13,'Budhi','20041226001803','',0,1,0,1,0.187306484847,'20041226001803','79958773998196'); INSERT INTO cur VALUES (2052,0,'Psychometric','#REDIRECT [[Psychometrics]]','',13,'Budhi','20041226002617','',0,1,0,1,0.083691683237,'20050303214455','79958773997382'); INSERT INTO cur VALUES (2053,0,'Psychometrics','\'\'\'Psychometrics\'\'\' is the [[science]] of measuring \"psychological\" aspects of a person such as knowledge, skills, abilities, or [[personality]]. Measurement of these unobservable phenomena is difficult and much of the research and accumulated art of this discipline is designed to reliably define and then quantify. Critics, including \"hard science\" practitioners and social activists, have argued that such definition and quantification is impossibly difficult and that such measurements are very often misused (although users of psychometric techniques can reply that their critics often misuse data by not assessing them with psychometric criteria). Significant psychometricians include [[Karl Pearson]], [[L. L. Thurstone]], and [[Arthur Jensen]]. Significant critics include the late [[Stephen Jay Gould]].\n\nMuch of the early work in psychometrics was developed in order to measure intelligence. More recently psychometric theory has been used in measurement of [[personality]], attitudes and beliefs, academic achievement, and in health related fields, to measure quality of life.\n\nThere are two branches to psychometric theory - [[classical test theory]] (CTT), and the more recent [[item response theory]] (IRT).\n\nThe key concepts of classical test theory are [[Reliability (psychometric)|reliability]] and [[Validity (psychometric)|validity]]. A reliable measure is measuring something consistently, while a valid measure is measuring what it is supposed to measure. A reliable measure may be consistent without necessarily being valid, .e.g., a measurement instrument like a broken ruler may always under-measure a quantity by the same amount each time (consistently), but the resulting quantity is still wrong, that is, invalid. \n\nBoth reliability and validity may be assessed mathematically. Internal consistency may be assessed by correlating performance on two halves of a test (split-half reliability); the value of the [[Pearson product-moment correlation coefficient]] is adjusted with the [[rumus prediksi Spearman-Brown]] to correspond to the correlation between two full-length tests. A commonly used measure is [[Cronbach\'s α]], which is equivalent to the mean of all possible split-half coefficients. Stability over repeated measures is assessed with the Pearson coefficient, as is the equivalence of different versions of the same measure (different forms of an intelligence test, for example). Other measures are also used.\n\nValidity may be assessed by correlating measures with a criterion measure known to be valid. When the criterion measure is collected at the same time as the measure being validated the goal is to establish \'\'[[concurrent validity]]\'\'; when the criterion is collected later the goal is to establish \'\'[[predictive validity]]\'\'. A measure has \'\'[[construct validity]]\'\' if it is related to other variables as required by theory. \'\'[[Content validity]]\'\', or face validity, is simply a demonstration that the items of a test are drawn from the domain being measured; it does not guarantee that the test actually measures phenomena in that domain.\n\nPredictive or concurrent validity cannot exceed the square of the [[correlation]] between two versions of the same measure.\n\nItem response theory models the relationship between [[latent trait|latent traits]] and responses to test items. Among other advantages, it has the ability to provide a reliable estimate of the exact score of a test-taker on the latent trait. For example, a university student\'s knowledge of history can be deduced from his or her score on a university test and then be compared reliably with a high school student\'s knowledge deduced from a less difficult test. Scores derived by classical test theory do not have this characteristic, and assessment of actual ability (rather than ability relative to other test-takers) must be assessed by comparing scores to those of a [[norm|norm group]] randomly selected from the population. In fact, all measures derived from classical test theory are dependent on the sample tested, while those derived from item response theory are not.\n\nSee also [[standardized test]].\n\n=== External Links ===\n\n* [http://www.majon.com/cgi-bin/IQ?Q=newtest IQ Test]\n* [http://www.psychometrics.co.uk/test.htm Information About Psychometric Tests]\n\n[[Category:Psychometrics]]\n\n[[es:Psicometría]]\n[[nl:Psychometrie]]','',13,'Budhi','20041226004712','',0,0,1,0,0.785647029094,'20050104235933','79958773995287'); INSERT INTO cur VALUES (2054,0,'Item_response_theory','==Overview==\n\n\'\'\'Item response theory\'\'\' designates a body of related [[psychometric]] theory that predict outcomes of psychological [[test|testing]] such as the difficulty of items or the ability of test-takers. Generally speaking, the aim of item response theory is to understand and improve the [[Reliability (psychometric)|reliability]] of psychological tests.\n\nItem response theory is very often referred to by its acronym, \'\'IRT\'\'. IRT may be regarded as roughly synonymous with \'\'latent trait theory\'\'. It is sometimes referred to using the word \'\'strong\'\' as in \'\'strong true score theory\'\' or \'\'modern\'\' as in \'\'modern mental test theory\'\' because IRT is a more recent body of theory and makes stronger assumptions as compared to [[classical test theory]].\n\n==IRT models==\nMuch of the literature on IRT revolves around item response models. These models relate a \'\'person parameter\'\' (or, in the case of \'\'multidimensional item response theory\'\', a vector of person parameters) to one or more item parameters. For example:\n\n\np_i({\\theta})=c_i + \\frac{(1-c_i)}{1+e^{-Da_i({\\theta}-b_i)}}\n\n\nwhere {\\theta} is the person parameter and a_i, b_i, and c_i are item parameters. This logistic model relates the level of the person parameter and item parameters to the probability of responding correctly. The constant D has the value 1.702 which rescales the logistic function to closely approximate the [[cumulative normal]] [[ogive]]. (This model was originally developed using the normal ogive but the logistic model with the recaling provides virtually the same model while simplifying the computations greatly.)\n\nThe line that traces the probability for a given item across levels of the trait is called the \'\'item characteristic curve\'\' (ICC) or, less commonly, \'\'item response function\'\'.\n\nThe person parameter indicates the individual\'s standing in the \'\'latent trait\'\'. The estimate of the person parameter is the individual\'s test score. The latent trait is the human capacity measured by the test. It might be a cognitive ability, physical ability, skill, knowledge level, attitude, personality characteristic, etc. In a unidimensional model such as the one above, this trait is considered to be a single factor (as in [[factor analysis]]). Individual items or individuals might have secondary factors but these are assumed to be mutually independent and collectively othogonal.\n\nThe item parameters simply determine the shape of the ICC and in some cases may not have a direct interpretation. In this case, however, the parameters are commonly interpreted as follows. The b parameter is considered to index an item\'s difficulty. Note that this model scales the items\'s difficulty and the person\'s trait onto the same metric. Thus, it is valid to talk about an item being about as hard as Person A\'s trait level or of a person\'s trait level being about the same as Item Y\'s difficulty. The a parameter controls how steeply the ICC rises and thus indicates the degree to which the item distinguishes individuals with trait levels above and below the rising slope of the ICC. This parameter is thus called the item discrimination and is correlated with the item\'s loading on the underlying factor, with the item-total correlation, and with the index of discrimination. The final parameter, c, is the asympotote of the ICC on the left-hand side. Thus it indicates the probability that very low ability individuals will get this item correct by chance. \n\nThis model assumes a single trait dimension and a binary outcome; it is a dichotomous, unidimensional model. Another class of models preduct polytomous outcomes. And a class of models exist to predict response data that arise from multiple traits.\n\n\'\'\'Note to reader: Below here, this article is still very much under construction\'\'\'\n\n==Information==\n\nOne of the major contributions of item response theory is the extension or the concept of [[reliability]]. Traditionally, reliability refers to the precision of measurement (i.e., the degree to which measurement is free of error). And traditionally, it is measured using a single index defined in various ways, such as the ratio of true and observed score variance. This index is helpful in characterizing a test\'s average reliability, for example in order to compare two tests. But it is clear that reliability cannot be uniform across the entire range of test scores. Scores at the endges of the test\'s range, for example, are known to have more error than scores closer to the middle.\n\nItem response theory advances the concept of item and test information to replace reliability. Information is a \'\'function\'\' that varies across the scale. In general, information functions tend to look \"bell-shaped\"--although test information functions are much more variable than item information functions. Information is the reciprocal of the standard error of measurement at a given trait level. Thus more information implies less error of measurement. Plots of item information can be used to see how much information an item contributes and to what portion of the scale score range. Highly discriminating items have tall, narrow information functions; they contribute greatly but over a narrow range. Less discriminating items provide less information but over a wider range. Because of local independence, item information functions are additive. Thus, the test information function is simply the sum of the information functions of the items on the exam. Using this property with a large item bank, test information functions can be shaped to control measurement error very precisely.\n\n==Estimation==\n\n==A Comparison of classical and modern test theory==\n\n===Scoring===\nAfter the model is fit to data, each person has a theta estimate. This estimate is their score on the exam. This \"IRT score\" is computed and interpreted in a very different manner as compared to traditional scores like number or percent correct. However, for most tests, the (linear) [[correlation]] between the theta estimate and a traditional score is very high (e.g., .95). A graph of IRT scores against traditional scores shows an ogive shape implying that the IRT score is somewhat better at separating individuals with low or high trait standing.\n\n\n\nIt is worth noting the implications of IRT for test-takers. Tests are imprecise tools and the score achieved by an individual (the \'\'observed score\'\') is always the true score occluded by some degree of error. This error may push the observed score higher or lower.\n\nAlso, nothing about these models refutes human development or improvement. A person may learn skills, knowledge or even so called \"test-taking skills\" which may translate to a higher true-score.\n\nSee also [[psychometrics]], [[standardized test]], [[classical test theory]]\n\n==A brief list of references==\n\nMany books have been written that address item response theory or contain IRT or IRT-like models. This is a partial list, focusing on texts that provide more depth.\n\n*Lord, F.M. (1980). \'\'Applications of item response theory to practical testing problems.\'\' Mahwah, NJ: Erlbaum. \nThis book summaries much of Lord\'s IRT work, including chapters on the relationship between IRT and clasical methods, fundamentals of IRT, estimation, and several advanced topics. Its estimation chapter is now dated in that it primarily discusses joint maximum liklihood method rather than the [[marginal maximum liklihood]] method implemented by [[Darrell Bock]] and his colleages.\n*Embretson, S. and Reise, S. (2000). \'\'Item response theory for psychologists.\'\' Mahwah, NJ: Erlbaum.\nThis book is an accessible introduction to IRT, aimed, as the title says, at psychologists.\n\n==External links==\n\n[[Category:Psychometrics]]','',13,'Budhi','20041226002745','',0,0,0,1,0.293661445037,'20050303214455','79958773997254'); INSERT INTO cur VALUES (2055,0,'Spearman-Brown_prediction_formula','#REDIRECT [[Rumus prediksi Spearman-Brown]]\n','Spearman-Brown prediction formula dipindahkeun ka Rumus prediksi Spearman-Brown',13,'Budhi','20041226004545','',0,1,0,1,0.231580396358,'20041226004545','79958773995454'); INSERT INTO cur VALUES (2056,0,'Measurement','\'\'\'Measurement\'\'\' is the determination of the size or magnitude of something. Measurement is not limited to physical quantities, but can extend to quantifying almost anything imaginable. Examples of measurement range from, degrees of [[uncertainty]], to the [[Index of Consumer Confidence|consumer confidence]], to the rate of increase in the fall in the price of [[beanie baby|beanie babies]]. It is important to know, however, that different kinds of quantity should be measured with different [[levels of measurement]].\n\nIn [[academic research]], measurement is essential. It includes the proces of collecting data which can be used to make claims about learning. Measurement is also used to [[Evaluation|evaluate]] the effectiveness of a program or product (known as an [[evaluand]]). \n\nIn [[physics]] and [[engineering]], measurement is the [[process]] of comparing [[physical quantity|physical quantities]] of real-world [[object (philosophy)|objects]] and [[event]]s. Established standard objects and events are used as [[units of measurement|units]], and the measurement results in at least two [[number]]s for the relationship between the item under study and the referenced unit of measurement, where at least one number estimates the \'\'[[statistics|statistical]] [[uncertainty]]\'\' in the measurement, also referred to as \'\'measurement error\'\' (in a philosophical distinction). [[Measuring instrument]]s are the means by which this translation is made.\n\nFor example, the unit for length might be a well-known person\'s foot, and the length of a boat can be given as the number of times that person\'s foot would fit the length of the boat.\n\n:\'\'A measurement is a comparison to a standard.\'\' -- [[William Shockley]]\n\n==Metrology==\n\'\'\'Metrology\'\'\' is the study of measurement. A [[metric]] is a standard for measurement. The quantification of phenomena through the process of measurement relies on the existence of an explicit or implicit metric, which is the standard to which the measure is referenced. If I say \'\'I am 5\'\', I am indicating a measurement without supplying an applicable standard. I may mean \'\'I am 5 years old\'\' or \'\'I am 5 feet high\'\', however the implicit metric is that I mean \'\'I am 5 years old\'\'.\n\n==History==\n[[Law]]s to regulate measurement were originally developed to prevent [[fraud]]. However, units of measurement are now generally defined on a scientific basis, and are established by international treaties. In the [[United States]], commercial measurements are regulated by the National Institute of Standards and Technology [[NIST]], a division of the [[United States Department of Commerce]].\n\nThe history of measurements is a topic within the [[History of Science and Technology]]. The [[metre]] (us: meter) was standardized as the unit for length after the [[French revolution]], and has since been adopted throughout most of the world. The United States and the UK are in the process of converting to the SI system. This process is known as [[metrication]].\n\n===Systems of measurement===\n* [[SI]], also known as the metric system\n* [[Chinese unit]]s\n* [[Imperial unit]]s\n* [[U.S. customary unit]]s\n\n==Difficulties in measurement==\nMeasurement of many quantities is very difficult and prone to large [[error]]. Part of the difficulty is due to [[Uncertainty]], and part of it is due to the limited [[time]] available in which to make the measurement.\n\nExamples of things that are very difficult to measure in some respects and for some purposes include social related items such as:\n* a person\'s knowledge (as in [[test]]ing, see also [[assessment]])\n* a person\'s feelings, [[emotion]]s, or beliefs.\n* a person\'s senses ([[qualia]]).\n\n==See also==\n* [[units of measurement]]\n* [[conversion of units]]\n* [[dimensional analysis]]\n* [[dimensionless number]]\n* [[ancient weights and measures]]\n* [[medieval weights and measures]], for historical terms such as [[league]]\n* [[levels of measurement]]\n* [[measurement in quantum mechanics]]\n* [[orders of magnitude]]\n* [[timeline of temperature and pressure measurement technology]]\n* [[timeline of time measurement technology]]\n* [[uncertainty]] in measurement\n* [[uncertainty principle]]\n* [[weights and measures]]\n* [[econometrics]]\n\n==External links==\n* [http://www.unc.edu/~rowlett/units/index.html A Dictionary of Units of Measurement]\n\n==Miscellaneous==\nMeasuring the ratios between physical quantities is an important sub-field of [[physics]]. \n\nSome important physical quantities include:\n* the [[speed of light]]\n* the [[fine-structure constant]]\n* the charge of an [[electron]]\n\n[[Category:Measurement]]\n\n[[ca:Metrologia]]\n[[de:Messung]]\n[[eo:Mezuro]]\n[[fr:Métrologie]]\n[[it:metrologia]]\n[[la:Mensura]]\n[[nl:Meettechnieken]]\n[[ja:測定]]\n[[pl:Pomiar]]\n[[simple:Measurement]]','',13,'Budhi','20041226005019','',0,0,0,1,0.773595606538,'20050303214455','79958773994980'); INSERT INTO cur VALUES (2057,0,'Reliability','Dina [[rékayasa]] sacara umum, \n\'\'\'reliabiliti\'\'\' nyaeta kamampuh hiji komponen atawa [[system|sistim]] dina eta komponen keur ditembongkeun salaku hasil disain. \nTempo [[reliability theory|teori reliabiliti]] sarta [[reliable system design|disain sistim nu reliable]]. Program komputer dijieun keur ngitung sistim reliabiti nu kompleks migunakeun teknik [[reliability modelling|pemodelan reliabiliti]].\n\nDina widang [[telecommunication|telekomunikasi]], watesan \'\'\'reliabiliti\'\'\' nyaeta: \n\n#The ability of an item to perform a required function under stated conditions for a specified period of [[time]]. \n#The probability that a [[functional unit]] will perform its required function for a specified interval under stated conditions. \n#The continuous [[availability]] of communication services to the general public, and emergency [[response]] activities in particular, during normal operating conditions and under emergency circumstances with minimal disruption.\n\nSource: from [[Federal Standard 1037C]] in support of [[MIL-STD-188]]\n\nSee also: [[ilities]]\n-------------------------------------\n\nIn [[psychometrics]], \'\'\'reliability\'\'\' is the precision (i.e., freedom from error) of the scores of a measure, see [[Reliability (psychometric)]].\n-------------------------------------\n\nIn [[testing]], \'\'\'reliability\'\'\' is the extent to which the measurements resulting from a test are the result of characteristics of those being measured. See [http://www.ericdigests.org/2002-2/reliability.htm Reliability] for a fuller description.\n\n\n[[de:Reliabilität]]\n[[ru:Надёжность]]','',13,'Budhi','20041228002618','',0,0,0,1,0.129136243013,'20050303214455','79958771997381'); INSERT INTO cur VALUES (2058,0,'Reliability_theory','\'\'\'Reliability theory\'\'\' developed apart from the mainstream of [[probability]] and [[statistics]], and was used originally as a tool to help nineteenth century \n[[maritime insurance]] and [[life insurance]] companies compute profitable rates to charge their customers. \nEven today, the terms \"failure rate\" and \"hazard rate\" are often \nused interchangeably.\n\nThe failure of mechanical devices such as ships, trains, cars, and so on, is similar in many ways to the life or death of biological organisms. \nStatistical models appropriate for any of these topics are generically called \"time-to-event\" models.\nDeath or failure is called an \"event\", and the goal is to project or forecast the rate of events for a given population or probability of an event for an individual.\n\nComputer software exists to quantify complex system reliability.\nSee also:\n* [[reliability]]\n* [[survival analysis]]\n* [[extreme value theory]]\n* [[Gompertz law]]\n* [[Weibull law]]\n* [[availability]]\n* [[MTBF]]\n* [[fault tree]]\n\n{{msg:stub}}\n\n== Tumbu kaluar ==\n* [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11742523&dopt=Abstract Reliability theory applied to aging and death]','',13,'Budhi','20041228002738','',0,0,1,1,0.044599904789,'20050303214455','79958771997261'); INSERT INTO cur VALUES (2059,0,'Reliable_system_design','\'\'\'Reliable system design\'\'\' is the design of systems with high levels of [[reliability]] and [[availability]].\n\nIt should be noted that there is no such thing as a perfectly reliable system, and that reliable systems engineering cannot engineer out failure modes which are not anticipated by modelling. For this reason, reliable systems are generally engineered to a designed failure rate, not to a zero failure rate.\n\nTypical reliable system design failure rates include \"five nines\" (99.999% availability) and \"six nines\" (99.9999% availability). Some [[life-critical system]]s are designed to even higher levels of performance.\n\nReliable system design attempts to create reliable systems by design, rather than by blindly over-engineering systems. The analytical tools for reliable systems design are [[root cause analysis]] and [[threat tree analysis]]. These allow real-world system failures to be investigated, and the failure modes of new systems modelled.\n\nThe main engineering approaches of reliable systems design are\n* eliminating \'\'\'single points of failure\'\'\'\n* engineering any remaining single points of failure to whatever level is necessary to reach the system specification\n* adding extra system safety margins to allow for errors in modelling or implementation\n\nThe term \"single point of failure\" describes \'\'any\'\' part of the system that can, if it fails, cause an interruption of required service from that system. This can be as simple as a process failure or as catastrophic as a computer system crash.\n\nMost non-critical real-world systems have \'\'many\'\' single points of failure: for example, a typical desktop computer has only one processor, one power supply, one keyboard, one screen, and so on, the failure of any of which will render that computer unusable.\n\nHowever, a business as a whole generally conducts its affairs so that the failure of any single desktop PC will not bring the business down. \nThus, the components mentioned above are single points of failure for the PC, but not for the larger system of which the PC is a component.\nSimilar techniques of using duplicated systems and backup systems are used to create resilient systems for critical applications such as [[database]]s, [[communications network]]s and [[air traffic control]] systems.\n\nHowever, mere use of massive redundancy does not make a system reliable, so long as there is even one single point of failure left in the system.\nFor example, a network where power feeds, network connections, routers, and router interconnections have all been correctly made redundant can still have a single point of failure if both routers are housed in a single rack, allowing a single spilled cup of coffee to take out both routers at once.\n\n\nNote that even eliminating every conceivable single point of failure is not by itself enough to make a system truly resilient, as the extra redundancy may make the system vulnerable to [[Byzantine failure]] modes.\n\nTempo oge: [[extreme value theory]]','',13,'Budhi','20041228002836','',0,0,1,1,0.069203226094,'20050303214455','79958771997163'); INSERT INTO cur VALUES (2060,0,'System',':\'\'For the Macintosh operating system, which was called \'\'\'System\'\'\' up to version 7.5.5, see [[Mac OS]].\'\'\n\nA \'\'\'system\'\'\' is an assemblage of inter-related elements comprising a unified whole. From the Latin and Greek, the term \"system\" meant to combine, to set up, to place together. A \'\'\'sub-system\'\'\' is a system which is part of another system.\nA system typically consists of [[component]]s (or [[element]]s) which are connected together in order to facilitate the flow of [[information]], [[matter]] or [[energy]]. The term is often used to describe a set of entities which interact, and for which a [[mathematical model]] can often be constructed.\n\n==Background==\nAt arbitrary boundaries, a collection of interrelated components may be declared a system and may further be abstracted to be declared a component of a larger system. Systems enable \"activities\" to be performed. (It is tempting to say that systems enable \"things\" to be done—but that is confusing in this context.) An [[engineering]] example of a system is often a [[circuit]] or a physical series.\n\nDepending on the type of system, a system can often be distinguished from individual \'\'[[machine]]s\'\', \'\'elements\'\' or \'\'[[process]]es\'\' of that system by the number, arrangements and complexity of those elements. For example, a [[pulley]] is a \'\'machine\'\', but an [[elevator]], which incorporates pulleys (amongst other components), is a \'\'system\'\'. Going to the [[doctor]] is a \'\'process\'\', but [[health care]] is a \'\'system\'\'.\n\nIn the natural world, we say that there are systems. For example, the [[solar system]] of nine planets orbiting the sun. In the human body, we refer to such systems as the [[nervous system]], the [[circulatory system]], the [[digestive system]], the [[reproductive system]], and the [[respiratory system]].\n\nIn addition, all so-called \"things\" ([[object|Objects]]) are actually systems. For example, a cup is an object, but it is also a system for holding hot or cold liquid, or other material. The cup has a certain shape and a handle, it is made of non-porous material and so on, and it is put together in such a way as to provide a useful function. Describing this thing makes up information, and defines a system.\n\n==Types of systems==\n\nAn \'\'\'[[open system]]\'\'\' can be influenced by events outside of the declared boundaries of a system. A \'\'\'[[closed system]]\'\'\' is self-contained: outside events can have no influence upon the system. In practice many things are a mixture of the two. For example a prison is a closed system because the prisoners can\'t get out, and the wardens spend most of their time at the prison. However it is also an open system, because it depends on outside factors and the prisoners and wardens do go outside. \'\'\'[[Dynamic system]]s\'\'\' have components or flows or both, that change over time.\n\nAnother distinction is the relation of [[physical system]]s to [[conceptual system]]s. Physical systems are systems of matter and energy. Conceptual systems are made up of ideas. Conceptual systems generally exist to aid in the accomplishment of specific goals or may be used to model physical systems.\n\n==Systems in information and computer science==\n\nIn [[computer science]] and [[information science]], \'\'\'system\'\'\' could also be a [[method]] or an [[algorithm]]. Again, an example will illustrate: There are systems of counting, as with [[Roman numerals]], and various systems for filing papers, or catalogues, and various library systems, of which the [[Dewey Decimal System]] is an example. This still fits with the definition of components which are connected together (in this case in order to facilitate the flow of information).\n\nSystem can also be used referring to a framework, be it software or hardware, designed to allow software to run, see [[platform (computing)|platform]].\n\n==Systems in operations research and management science==\n\nIn [[operations research]] and [[organizational development]] (OD), organizations are viewed as human \'\'\'systems\'\'\' (conceptual systems) of interacting components such as sub-systems, processes and organizational structures. Organizational development theorist [[Peter Senge]] developed the notion of organizations as systems in his book \'\'The Fifth Discipline\'\'.\n[[Systems thinking]] has been identified as an important leadership competency where an individual thinks globally when acting locally. Such person takes into account the potential consequences of a decision on other parts of the organization.\n\n==Elements which can also be called systems==\n\nMany of the systems mentioned previously are related to [[science]] and [[technology]]. There are other systems\n*In [[sport]], there is what\'s called a scoring system. Examples are:\n**In [[rugby union]], a try is worth 5 points, a goal which is not a conversion is worth 3 points, and a conversion is worth 2 points.\n**In [[rugby league]], a try is worth 4 points, a goal which is not a drop-goal is worth 2 points, and a drop-goal is worth 1 point.\n**In [[soccer]], [[netball]], [[waterpolo]], [[lacrosse]], [[korfball]], and [[field hockey]], scoring is based solely on the number of goals scored.\n**In [[ice hockey]], you can also score points by helping a team-mate to score a goal.\n**[[Buzkashi]] scores are solely dependent on how many [[goats]] have been thrown in the goal.\n**In [[baseball]] and [[cricket]], scoring is based on the number of runs completed.\n**In [[basketball]], 1 point is scored for a free throw, 2 points for a lay-up or a shot scored by someone in the circle, and 3 points for a shot scored by someone outside the circle.\n**In [[archery]], your score depends on how accurate your shot was.\n**In [[tennis]] and [[volleyball]], you score a point if the ball goes right past your opponents.\n**In [[American football]], a touchdown is worth 6 points, a field goal is worth 3 points, a conversion can be worth 1 or 2 points, and a safety is worth 1 point. The same system applies in [[Canadian football]].\n**In [[hurling]] and [[Gaelic football]], a goal is worth 3 points and if the ball goes over the goal but through the posts, you score 1 point.\n**In [[Australian rules football]], a goal is worth 6 points and a behind is worth 1 point.\n**The scoring system of [[International rules]] is a combination of Australian rules and Gaelic football. A goal is worth 6 points, an [[over (sport)|over]] (which is when the ball misses the goal but goes through the post) is worth 3 points, and a behind is worth 1 point.\n**In [[golf]], where you have to aim for a lower score instead of a higher score, the score can be based solely on the number of strokes taken, or that number minus a \"par\" which changes from hole to hole.\n*Scoring systems also apply in [[card games]]. Click on the link for more.\n*Families can also introduce discipline systems for their children. This might include [[Child time-out|time-out]], [[grounding]], removal of priveleges, etc.\n\n==Tempo oge==\n*[[Chaos theory]]\n*[[Complex system]]s\n*[[Computer system]]\n*[[Cybernetics]]\n*[[Donella Meadows\' twelve leverage points to intervene in a system]]\n*[[General semantics]]\n*[[Holarchy]]\n*[[Meta-systems]]\n*[[Socio-Technical Systems]]\n*[[Solar System]]\n*[[Systems theory]]\n*[[Systems thinking]]\n\n== Tumbu kaluar ==\n*[http://www.worldtrans.org/whole.html An introduction to \'\'Whole Systems\'\']\n*[http://ratjed.com/?systems Conceptual Systems vs. Physical Systems]\n*[http://www.platinumsolutions.bravehost.com business solutions systems]\n[[Category:Systems theory]]\n[[bg:Система]]\n[[da:System]]\n[[de:System]]\n[[es:Sistema]]\n[[fa:سامانه]]\n[[ja:系]]\n[[pl:Układ]]\n[[ru:Система]]','',13,'Budhi','20041228003002','',0,0,1,1,0.377228027445,'20050303214455','79958771996997'); INSERT INTO cur VALUES (2061,0,'Reliability_modelling','In [[engineering]], [[reliability modelling]] is the process of predicting or understanding the [[reliability]] of a component or system.\n\nTwo separate fields of investigation are common.\n\nThe [[physics of failure]] approach uses an understanding of the failure mechanisms involved, such as [[crack propagation]] or chemical [[corrosion]].\n\nThe [[parts stress modelling]] approach is an empirical method for prediction based on counting the number and type of components of the system, and the stress they undergo during operation.\n\n{{stub}}','',13,'Budhi','20041228003102','',0,0,1,1,0.547953744434,'20050303214455','79958771996897'); INSERT INTO cur VALUES (2062,0,'Model_statistik','#REDIRECT [[Modél statistik]]\n','Model statistik dipindahkeun ka Modél statistik',3,'Kandar','20041229073051','',0,1,0,1,0.144151208489,'20041229073051','79958770926948'); INSERT INTO cur VALUES (2063,0,'Desain_percobaan','#REDIRECT [[Rancangan percobaan]]\n','Desain percobaan dipindahkeun ka Rancangan percobaan',3,'Kandar','20041229073253','',0,1,0,1,0.019864316729,'20041229073253','79958770926746'); INSERT INTO cur VALUES (2064,0,'Calibration_(statistics)','#REDIRECT [[Kalibrasi (statistik)]]\n','Calibration (statistics) dipindahkeun ka Kalibrasi (statistik)',3,'Kandar','20041229081406','',0,1,0,1,0.850636237869,'20041229081406','79958770918593'); INSERT INTO cur VALUES (2066,1,'Régrési_liniér','#REDIRECT [[Talk:Analisis régrési]]\n','Talk:Régrési liniér dipindahkeun ka Talk:Analisis régrési',3,'Kandar','20041229082021','',0,1,0,1,0.128477965824,'20041229082021','79958770917978'); INSERT INTO cur VALUES (2067,0,'Linear_regression','#REDIRECT [[Régrési liniér]]\n','Linear regression dipindahkeun ka Régrési liniér',3,'Kandar','20041229084817','',0,1,0,1,0.538187947128,'20041229084817','79958770915182'); INSERT INTO cur VALUES (2068,0,'Réaksi_kondensasi','\'\'\'Réaksi kondensasi\'\'\' (ogé katelah \'\'\'réaksi dehidrasi\'\'\') nyaéta [[réaksi kimia]] nalika dua [[molekul]] atawa \'\'[[moiety|moieties]]\'\' meta bari ngaleupaskeun [[cai]] atawa [[amonia]]. Ieu bisa dianggap sabalikna ti réaksi [[hidrolisis]], nyaéta meulah hiji zat kimia jadi dua bagian ku ayana cai.\n\n==Mékanisme==\nRéaksi kondensasi lumangsung dina dua hambalan:\n#[[adisi nukléofilik]]\n#Éliminasi\n\n==Larapan==\nRéaksi kieu dijadikeun dasar pikeun nyipta rupa-rupa polimér penting kayaning: [[nilon]], [[poliéster]], sarta rupa-rupa [[époxi|elém]]. Ieu ogé dijadikeun dasar pikeun nyipta [[silikat]] jeung [[polifosfat]] di laboratorium. Dina biologi, dibentukna [[adénosin difosfat]] jeung [[adénosin trifosfat]] prékursor jeung [[fosfat anorganik]] ogé mangrupa réaksi kondensasi.\n\nRéaksi nu ngahasilkeun [[anhidrida]] asam tina asam panyusunna biasana mangrupa réaksi kondensasi.\n\n[[de:Kondensationsreaktion]]\n[[en:condensation reaction]]\n\n[[Category:Prosés kimia]]','',3,'Kandar','20041229091954','',0,0,0,1,0.166125195685,'20050303214455','79958770908045'); INSERT INTO cur VALUES (2069,0,'Tree',':\'\'This article is about the biological organisms known as trees. For other meanings of the word see [[tree (disambiguation)]].\'\'\n\n[[Image:Raunkiaer.jpg|250px|right|thumb|An [[oak]] tree in [[Denmark]]]]\nA \'\'\'tree\'\'\' can be defined as a large [[perennial]] woody [[plant]]. Though there is no set definition of size, it is generally at least 6 m (20 ft) high at maturity, and with branches supported on a single main stem. Compared with most other forms of plants, trees are long-lived. A few species of trees grow to over 100 m (300 ft) tall and some live for several millennia. Trees are important components of the natural landscape and significant elements in [[landscaping]].\n\nTrees also play an important role in many of the world\'s [[mythology|mythologies]]. See [[Tree (mythology)]] for more information.\n\n==Classification==\nTrees occur in many diverse [[order (biology)|orders]] and [[family (biology)|families]] of plants, and thus show a wide variety of growth form, leaf types and shapes, bark, reproductive organs, etc. The earliest trees were [[tree fern]]s and [[horsetail]]s, which grew in vast forests in the [[Carboniferous]] Period; tree ferns still survive, but the only surviving horsetails are not of tree form. Later, in the [[Triassic]] Period, [[Pinophyta|conifers]], [[ginkgo]]s, [[cycad]]s and other [[gymnosperm]]s appeared, and subsequently [[flowering plant]]s in the [[Cretaceous]] Period. Most species of trees today are [[flowering plant]]s and conifers. The list below gives some examples of well known trees and how they are typically classified.\n\n==Morphology==\n[[Image:Tree in Chile.jpg|thumb|A (type?) tree in the slopes of the [[Andes]], in [[Santiago de Chile|Santiago]], [[Chile]]]]\n\nThe component parts of a tree are the [[root]]s, [[trunk (botany)|trunk]](s), [[branch]]es, [[twig]]s and [[leaf|leaves]]. Tree stems consist mainly of support and transport tissues ([[xylem]] and [[phloem]]). [[Wood]] consists of \'\'xylem\'\' cells, and [[bark]] is primarily made of \'\'phloem\'\'.\n \nTrees may be broadly grouped into \'\'exogenous\'\' and \'\'endogenous\'\' trees according to the way in which their stem diameter grows. Exogenous trees, which comprise the great majority of modern trees (all [[conifer]]s, and all [[dicotyledon|broadleaf]] trees), grow by the addition of new wood outwards, immediately under the bark. Endogenous trees, mainly in the [[monocotyledon]]s (e.g. [[palm tree|palms]]), grow by addition of new material inwards.\n\nAs an exogenous tree grows, it creates [[growth ring]]s. In temperate climates, these are commonly visible due to changes in the rate of growth with the temperature variation over the year. These can be counted to determine the age of the tree, and used to date cores or even wood taken from trees in the past; this is known as the science of [[dendrochronology]]. In tropical climates with near-constant climate, growth is continuous and does not form distinct rings, so age determination is impossible. Age determination is also impossible in endogenous trees.\n\nThe roots of a tree are generally embedded in earth, providing anchorage for the above-ground biomass and absorbing [[water]] and [[nutrients]] from the [[soil]]. Above ground, the trunk gives height to the leaf-bearing branches, aiding in competition with other plant species for [[sunlight]]. In many trees the arrangement of the branches optimizes exposure of the leaves to sunlight.\n\nNot all trees have all the plant organs mentioned above. For examples: most palm trees are not branched, the [[Saguaro|saguaro cactus]] of North America has no functional leaves, [[tree fern]]s do not have bark, etc. Based on their rough shape and size, all of these are nonetheless generally regarded as trees. Indeed, sometimes size is the most important consideration. A plant form that is similar to a tree, but generally having smaller, multiple trunks and/or branches that arise near the ground, is called a [[shrub]]. However, no sharp differentiation between shrubs and trees is possible. Given their small size, [[bonsai]] plants would not technically be \'trees\', but one should not confuse reference to the form of a species with the size or shape of individual specimens. A spruce seedling does not fit the definition of a tree, but all spruces are trees. [[Bamboo]]s by contrast, \'\'do\'\' show most of the characteristics of trees, yet are perhaps strangely rarely called trees.\n\nA small group of trees growing together is called a [[grove (nature)|grove]] or copse, and a landscape covered by a large area of trees is called a [[forest]]. Several [[biotope]]s are defined largely by the trees that inhabit them, for example, [[rainforest]] and [[taiga]]; see [[ecozone]]s. Large, but scattered trees with grassland (usually grazed or burned over periodically) in between is called [[savanna]].\n\n==Major tree genera==\n=== [[Flowering plant]]s (Magnoliophyta) ===\n====[[Dicotyledon]]s (Magnoliopsida; broadleaf or hardwood trees)====\n* [[Anacardiaceae]] ([[Cashew]] family)\n** [[Cashew]], \'\'Anacardium occidentale\'\'\n** [[Mango]], \'\'Mangifera indica\'\'\n** [[Pistachio]], \'\'Pistacia vera\'\'\n** [[Toxicodendron|Lacquer tree]], \'\'Toxicodendron verniciflua\'\'\n* [[Aquifoliaceae]] ([[Holly]] family)\n**[[Holly]], \'\'Ilex\'\' species\n* [[Araliaceae]] ([[Hedera|Ivy]] family)\n** [[Kalopanax]], \'\'Kalopanax pictus\'\'\n[[image:birchandmaple.jpg|thumb|[[Birch]] tree (foreground) and [[maple]] tree (background) in fall]]\n* [[Betulaceae]] ([[Birch]] family)\n** [[Alder]], \'\'Alnus\'\' species\n** [[Birch]], \'\'Betula\'\' species\n* [[Cactaceae]] ([[Cactus]] family)\n** [[Saguaro]], \'\'Carnegiea gigantea\'\'\n* [[Cornaceae]] ([[Dogwood]] family)\n** [[Dogwood]], \'\'Cornus\'\' species\n* [[Corylaceae]] ([[Hazel]] family)\n** [[Hornbeam]], \'\'Carpinus\'\' species\n** [[Hazel]], \'\'Corylus\'\' species\n* [[Dipterocarpaceae]] family\n** [[Garjan]] \'\'Dipterocarpus\'\' species\n** [[Sal]] \'\'Shorea\'\' species \n* [[Ericaceae]] ([[Heath]] family)\n** [[Arbutus]], \'\'Arbutus\'\' species\n* [[Fabaceae]] ([[Pea]] family)\n** [[Honey locust]], \'\'Gleditsia triacanthos\'\'\n** [[Black locust]], \'\'Robinia pseudoacacia\'\'\n** [[Laburnum]], \'\'Laburnum\'\' species\n** [[Caesalpinia echinata|Pau Brasil]], Brazilwood, \'\'Caesalpinia echinata\'\'\n* [[Fagaceae]] ([[Beech]] family )\n** [[Chestnut]], \'\'Castanea\'\' species\n** [[Beech]], \'\'Fagus\'\' species\n** [[Southern beech]], \'\'Nothofagus\'\' species\n** [[Tanoak]], \'\'Lithocarpus densiflorus\'\'\n** [[Oak]], \'\'Quercus\'\' species\n* [[Fouquieriaceae]] ([[Boojum tree|Boojum]] family)\n** [[Boojum tree|Boojum]], \'\'Fouquieria columnaris\'\'\n* [[Hamamelidaceae]] ([[Witch-hazel]] family)\n** [[Sweetgum]], \'\'Liquidambar\'\' species\n** [[Persian ironwood]], \'\'Parrotia persica\'\'\n* [[Juglandaceae]] ([[Walnut]] family)\n** [[Walnut]], \'\'Juglans\'\' species\n** [[Hickory]], \'\'Carya\'\' species\n* [[Lauraceae]] ([[Bay laurel|Laurel]] family)\n** [[Cinnamon]] \'\'Cinnamomum zeylanicum\'\'\n** [[Bay laurel]] \'\'Laurus nobilis\'\'\n** [[Avocado]] \'\'Persea americana\'\'\n* [[Lecythidaceae]] ([[Lecythidaceae|Paradise nut]] family)\n** [[Brazil Nut]] \'\'Bertholletia excelsa\'\'\n* [[Lythraceae]] [[Loosestrife]] family\n** [[Crape-myrtle]] \'\'Lagerstroemia\'\' species\n* [[Magnoliaceae]] ([[Magnolia]] family)\n** [[Liriodendron|Tulip tree]], \'\'Liriodendron\'\' species\n** [[Magnolia]], \'\'Magnolia\'\' species\n* [[Malvaceae]] ([[Mallow]] family; including [[Tilia|Tiliaceae]] and [[Bombacaceae]]) [[Image:Baobab.jpg|right|thumb|Baobab tree in South-Africa]]\n** [[Baobab]], \'\'Adansonia\'\' species\n** [[Silk-cotton tree]], \'\'Bombax\'\' species\n** [[Kapok]], \'\'Ceiba pentandra\'\'\n** [[Durian]], \'\'Durio zibethinus\'\'\n** [[Balsa]], \'\'Ochroma lagopus\'\'\n** [[Tilia|Linden]] (Basswood, Lime), \'\'Tilia\'\' species\n* [[Meliaceae]] ([[Mahogany]] family)\n** [[Neem]], \'\'Azadirachta indica\'\'\n** [[Bead tree]], \'\'Melia azedarach\'\'\n** [[Mahogany]], \'\'Swietenia mahagoni\'\'\n* [[Moraceae]] ([[Mulberry]] family)\n** [[Fig]], \'\'Ficus\'\' species\n** [[Mulberry]], \'\'Morus\'\' species\n* [[Myristicaceae]] ([[Nutmeg]] family)\n** [[Nutmeg]], \'\'Mysristica fragrans\'\'\n* [[Myrtaceae]] ([[Myrtle]] family)\n** [[Eucalyptus]], \'\'Eucalyptus\'\' species\n** [[Myrtle]], \'\'Myrtus\'\' species\n** [[Guava]], \'\'Psidium guajava\'\'[[Image:Davidia1.jpg|right|thumb|250px|[[Nyssaceae]]: \'\'a [[Dove tree]] in flower\'\']]\n* [[Nyssaceae]] ([[Tupelo]] family; sometimes included in [[Cornaceae]])\n** [[Nyssa|Tupelo]], \'\'Nyssa\'\' species\n** [[Dove tree]], \'\'Davidia involucrata\'\'\n* [[Oleaceae]] ([[Olive]] family)\n** [[Olive]], \'\'Olea europaea\'\'\n** [[Ash tree|Ash]], \'\'Fraxinus\'\' species\n* [[Platanaceae]] ([[Platanus|Plane]] family)\n** [[Platanus|Plane]], \'\'Platanus\'\' species\n* [[Rhizophoraceae]] ([[Mangrove]] family)\n** Red Mangrove, \'\'Rhizophora mangle\'\'\n* [[Rosaceae]] ([[Rose]] family)\n** [[Rowan]], \'\'Sorbus\'\' species\n** [[Hawthorn]], \'\'Crataegus\'\' species\n** [[Pear]], \'\'Pyrus\'\' species\n** [[Apple]], \'\'Malus\'\' species\n** [[Almond]], \'\'Prunus dulcis\'\'\n** [[Peach]], \'\'Prunus persica\'\'\n** [[Plum]], \'\'Prunus domestica\'\'\n** [[Cherry]], \'\'Prunus\'\' species\n* [[Rubiaceae]] ([[Bedstraw]] family)\n** [[Coffee]], \'\'Coffea arabica\'\'\n* [[Rutaceae]] ([[Rue]] family)\n** [[Citrus]], \'\'Citrus\'\' species\n** [[Cork-tree]], \'\'Phellodendron\'\' species\n** [[Tetradium|Euodia]], \'\'Tetradium\'\' species\n* [[Salicaceae]] ([[Willow]] family)\n** [[Aspen]], \'\'Populus\'\' species\n** [[Poplar]], \'\'Populus\'\' species\n** [[Willow]], \'\'Salix\'\' species\n[[image:yellowmaple.jpg|thumb|Yellow [[maple]] in fall]]\n* [[Sapindaceae]] (including [[Aceraceae]], [[Aesculus|Hippocastanaceae]]) ([[Soapberry]] family)\n** [[Maple]], \'\'Acer\'\' species\n** [[Aesculus|Buckeye, Horse-chestnut]], \'\'Aesculus\'\' species\n** [[Mexican Buckeye]], \'\'Ungnadia speciosa\'\'\n** [[Lychee]], \'\'Litchi sinensis\'\'\n** [[Golden rain tree]], \'\'Koelreuteria paniculata\'\'\n* [[Sapotaceae]] family\n** [[Tambalacoque]], or \'\'dodo tree\'\', \'\'Sideroxylon grandiflorum\'\', previously \'\'Calvaria major\'\'\n* [[Simaroubaceae]] family\n** [[Ailanthus|Tree of heaven]], \'\'Ailanthus\'\' species\n* [[Sterculiaceae]] family\n** [[Cacao]] ([[cocoa]]), \'\'Theobroma cacao\'\'\n* [[Ulmaceae]] ([[Elm]] family)\n** [[Hackberry]], \'\'Celtis\'\' species\n** [[Elm]], \'\'Ulmus\'\' species\n* [[Verbenaceae]] family\n** [[Teak]], \'\'Tectona\'\' species\n\n====[[Monocotyledon]]s (Liliopsida)====\n* [[Agavaceae]] ([[Agave]] family)\n** [[Cabbage tree]], \'\'Cordyline australis\'\'\n** [[Dragon tree]], \'\'Dracaena draco\'\'\n** [[Joshua tree]], \'\'[[Yucca]] brevifolia\'\'\n* [[Arecaceae]] (Palmae) ([[Arecaceae|Palm]] family)\n** [[Areca]] Nut, \'\'Areca catechu\'\'\n** [[Coconut]] \'\'Cocos nucifera\'\'\n** [[Date (fruit)|Date]] Palm, \'\'Phoenix dactylifera\'\'\n** [[Chusan Palm]], \'\'Trachycarpus fortunei\'\'\n* [[Poaceae]] ([[grass]] family)\n** [[Bamboo]]s Poaceae subfamily Bambusoideae\n* Note that [[Banana]] \'trees\' are not actually trees, as they are not woody nor perennial.\n\n=== [[Pinophyta|Conifer]]s (Pinophyta; softwood trees)===\n[[Image:coastredwood.jpg|right|thumb|250px|The [[conifer]]ous [[Coast Redwood]], the tallest tree species on earth]]\n* [[Araucariaceae]] ([[Araucaria]] family)\n** [[Araucaria]], \'\'Araucaria\'\' species\n** [[Kauri]], \'\'Agathis\'\' species\n* [[Cupressaceae]] ([[Cypress]] family)\n** [[Cupressus|Cypress]], \'\'Cupressus\'\' species\n** [[Chamaecyparis|Cypress]], \'\'Chamaecyparis\'\' species\n** [[Juniper]], \'\'Juniperus\'\' species\n** [[Alerce]] or Patagonian cypress, \'\'Fitzroya cupressoides\'\'\n** [[Sugi]], \'\'Cryptomeria japonica\'\'\n** [[Coast Redwood]], \'\'Sequoia sempervirens\'\'\n** [[Giant Sequoia]], \'\'Sequoiadendron giganteum\'\'\n** [[Dawn Redwood]], \'\'Metasequoia glyptostroboides\'\'\n** [[Taxodium|Bald Cypress]], \'\'Taxodium distichum\'\'\n* [[Pinaceae]] ([[Pine]] family)\n** [[Pinus classification|White pine]], \'\'Pinus\'\' species\n** [[Pinus classification|Pinyon pine]], \'\'Pinus\'\' species\n** [[Pine]], \'\'Pinus\'\' species\n** [[Spruce]], \'\'Picea\'\' species\n** [[Larch]], \'\'Larix\'\' species\n** [[Douglas-fir]], \'\'Pseudotsuga\'\' species\n** [[Fir]], \'\'Abies\'\' species\n** [[Cedar]], \'\'Cedrus\'\' species\n* [[Podocarpaceae]] ([[Yellowwood]] family)\n** African Yellowwood, \'\'Afrocarpus falcatus\'\'\n** [[Totara]], \'\'Podocarpus totara\'\'\n* [[Taxaceae]] ([[Yew]] family)\n** [[Yew]], \'\'Taxus\'\' species\n\n=== [[Ginkgo]]s (Ginkgophyta)===\n* [[Ginkgo|Ginkgoaceae]] ([[Ginkgo]] family)\n** [[Ginkgo]], \'\'Ginkgo biloba\'\'\n\n=== [[Cycad]]s (Cycadophyta)===\n* [[Cycadaceae]] family\n** Ngathu [[cycad]], \'\'Cycas angulata\'\'\n* [[Zamiaceae]] family\n** Wunu [[cycad]], \'\'Lepidozamia hopei\'\'\n\n=== [[Fern]]s (Pterophyta)===\n* [[Cyatheaceae]] and [[Dicksoniaceae]] families\n** [[Tree fern]]s, \'\'Cyathea\'\', \'\'Alsophila\'\', \'\'Dicksonia\'\' (not a monophyletic group)\n\n== Life stages ==\nThe life cycles of trees, especially conifers, are divided into the following stages in [[forestry]] for survey and documentation purposes:\n# [[Seed]]\n# Seedling: the above ground part of the embryo that sprout from the seed\n# Sapling: After the seedling reaches 1m tall, and until it reaches 7cm in stem diameter\n# Pole: young trees from 7-30cm diameter\n# Mature tree: over 30cm diameter, reproductive years begin\n# Old tree: dominate old growth forest; height growth slows greatly, with majority of productivity in seed production\n# Overmature: dieback and decay become common\n# Snag: standing dead wood\n# Log/debris: fallen dead wood\n\nTree diameters are measured at height of between 1.3-1.5m above the highest point on the ground at its base. The 7cm diameter definition is economically based, from the smallest saleable stem size (for paper production, etc), and the 30cm diameter is the smallest base diameter for sawlogs. Each stage may be uniquely perceptive to different pathogens and suitable for especially adapted arboreal animals.\n\n\n\n== See also ==\n{{commons|Trees}}\n* [[Trees of the world]]\n** [[Trees of Britain and Ireland]]\n** [[Trees of Canada]]\n** [[Trees of The Caribbean Basin]]\n** [[Trees of Iran]]\n** [[List of trees of New Zealand]]\n* [[Tree (mythology)]]\n* [[Christmas tree]]\n* [[List of famous trees]]\n* [[List of U.S. state trees]]\n* [[Fruit trees]]\n* [[Forestry]]\n* [[Deforestation]]\n* [[Tree farm]]\n* [[Wood]]\n** [[List of woods]]\n* [[Woodland management]]\n* [[Bonsai]]\n* [[Arboretum|Arboreta]]\n* [[Pinetum]]\n* [[List of garden plants]]\n* [[Lightning]]\n\n[[Category:Plants]]\n[[Category:Forestry]]\n[[Category:Trees|*]]\n\n[[cy:Coeden]]\n[[da:Træ (organisme)]]\n[[de:Baum]]\n[[eo:Arbo]]\n[[es:Árbol]]\n[[fa:درخت]]\n[[fr:Arbre]]\n[[ja:木]]\n[[la:Arbor]]\n[[nl:boom]]\n[[nds:Boom]]\n[[pl:Drzewo (biologia)]]\n[[simple:Tree]]\n[[fi:Puu]]\n[[sv:Träd]]\n[[zh-cn:树 (生物)]]\n[[zh-tw:樹 (生物)]]','',13,'Budhi','20041229220052','',0,0,0,1,0.245333419768,'20041229220220','79958770779947'); INSERT INTO cur VALUES (2070,0,'Dendrochronology','[[Image:Pinus_taeda_crossx7358.JPG|framed|right|\'\'Pinus taeda\'\'
    Cross section showing annual rings
    [[Cheraw, South Carolina]]]]\n\n\'\'\'Dendrochronology\'\'\' or tree-ring dating is the method of scientific dating based on the analysis of [[tree]] ring patterns. This technique was invented and developed during the 20th century originally by [[Andrew E. Douglass|A.E. Douglass]], the founder of the Laboratory of Tree-Ring Research which resides at the University of Arizona. This dating technique can give dates in exact calendar years for wood.\n\n==Overview==\nSimply stated, trees in temperate zones grow one [[growth ring]] each year. Trees develop annual rings of different properties depending on [[weather]], [[rain]], [[temperature]], etc. in different years. These variations may be used to infer past climate variations - see [[proxy (climate)|proxy]]. For the entire period of a tree\'s life, a year-by-year record or ring pattern is formed that in some way reflects the climatic conditions in which the tree grew. Adequate moisture and a long growing season results in a wide ring. A drought year may result in a very narrow one. Trees from the same region will tend to develop the same patterns of width for a given period. These patterns can be compared and matched ring for ring with trees growing in the same geographical zone and under similar climatic conditions. Following these tree-ring patterns from living trees back through time, chronologies can be built up. We can thus compare wood from old or ancient structures to our known chronologies, match the ring patterns (a technique called cross-dating), and determine precisely the age of the wood used by the ancient builder.\n\n== More detail ==\n\nInitial work focussed on measuring the tree ring width - this is simple to measure and can be related to climate parameters. But the annual growth of the tree leaves other traces, and in particular \'\'maximum latewood density\'\' is generally found to be a better proxy for temperature than ring width. It is, however, harder to measure.\n\nRecently, the established connection between tree rings and climate appears to be breaking down. Briffa et al report in Nature, 1998:\n\n: \'\'During the second half of the twentieth century, the decadal-scale trends in wood density and summer temperatures have increasingly diverged as wood density has progressively fallen. The cause of this increasing insensitivity of wood density to temperature changes is not known...\'\' [http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/journal/v391/n6668/abs/391678a0_fs.html&dynoptions=doi1103576918]. \n\nLaboratory analysis of timber core samples measures the width of annual rings. By taking samples from different sites and different [[rock strata|strata]] within a particular region, researchers can build a comprehensive historical sequence that becomes a part of the scientific record; for example, ancient timbers found in buildings can be dated to give an indication of when the source tree was alive and growing, setting an upper limit on the age of the wood. Some trees are more suitable than others for this type of analysis. Likewise, in areas where trees grew in marginal conditions such as aridity or semi-aridity, the techniques of dendrochronology are more consistent than in humid areas. These tools have been important in archaeological dating of timbers of the cliff dwellings of [[Native Americans]] in the arid Southwest.\n\n== Scientific value ==\n\nThe main use of dendrochronology is in [[climate]] studies to reconstruct past temperature variations. See-also [[temperature record of the past 1000 years]].\n\nA benefit of dendrochronology is that it makes available specimens of once-living material accurately dated to a specific year to be used as a [[kalibrasi]] and check of [[radiocarbon dating]]. The [[bristlecone pine]], being exceptionally long-lived and slow growing, has been used for this purpose, with still-living and dead specimens providing tree ring patterns going back thousands of years. For dating purposes, in some regions sequences of more than 10,000 years are available.\n\nThe dendrochronologist faces many obstacles, however, including some [[species]] of [[ant]] which inhabit [[tree]]s and extend their galleries into the wood, thus destroying ring structure.\n\nSimilar seasonal patterns also occur in [[ice core]]s and in [[Varve|varves]] (layers of [[sediment]] deposition). These are used for dating in a matter similar to dendrochronology, and such techniques are used in combination with dendrochronology, to plug gaps and to extend the range of the seasonal data available to archeologists.\n\n==External links==\n*[http://www.ltrr.arizona.edu The Laboratory of Tree-Ring Research]\n*[http://www.arts.cornell.edu/dendro/ Wiener Laboratory for Aegean and Near Eastern Dendrochronology at Cornell University website]\n*[http://www.dr-beuting.de/index_en.php Dendrochronology on musical instruments and art objects]\n\n[[Category:Geochronology]]\n[[Category:Anthropology]]\n\n[[da:Dendrokronologi]] \n[[de:Dendrochronologie]] \n[[eo:Dendrokronologio]] \n[[fr:Dendrochronologie]] \n[[nl:Dendrochronologie]] \n[[sv:Dendrokronologi]]','/* Scientific value */',13,'Budhi','20041229230443','',0,0,1,0,0.041026941149,'20041229230443','79958770769556'); INSERT INTO cur VALUES (2071,0,'Carbon-14','\'\'\'Carbon-14\'\'\' is the [[radioactive]] [[isotope]] of [[carbon]] discovered [[February 27]], [[1940]], by [[Martin Kamen]] and [[Sam Ruben]]. Its presence in organic materials is used in [[radiocarbon dating]].\n\nThe [[half-life]] of \'\'\'carbon-14\'\'\' is 5730 years. It decays into [[nitrogen-14]] through [[beta-decay]].\n\n
    \n\n
    \n
    \'\'\'[[Isotope]]s of [[Carbon]]\'\'\'\n\'\'\'[[Carbon-13]]\'\'\'\n\'\'\'[[Carbon-15]]\'\'\'\n
    \'\'\'[[Decay chain]]\'\'\'\nProduced from:
    \'\'\'[[Nitrogen-18]]\'\'\'
    \'\'\'[[Boron-14]]\'\'\'\n
    Decays to:
    \'\'\'[[Nitrogen-14]]\'\'\'\n
    \n
    \n\n\n==See also==\n* [[Carbon]]\n* [[Carbon-12]]\n* [[isotope]]\n* [[Radiocarbon_dating]]\n\n{{stub}}\n\n\n\n[[Category:Chemical isotope]]\n\n\n\n[[fr:Carbone 14]]\n[[zh:碳14]]','',13,'Budhi','20041229220349','',0,0,0,1,0.162199559308,'20050303214455','79958770779650'); INSERT INTO cur VALUES (2072,0,'Radiometric_dating','\'\'\'Radiometric dating\'\'\' is a technique used to date materials based on a knowledge of the decay rates of naturally occurring isotopes, and the current abundances.\n\nVarious methods exist differing in accuracy, cost and applicable time scale\n\n==Types of radiometric dating==\n*[[radiocarbon dating]]\n*[[Rubidium-Strontium dating|rubidium-strontium]]\n*[[samarium-neodymium dating|samarium-neodymium]]\n*[[potassium-argon dating|potassium-argon]]\n*[[argon-argon dating|argon-argon]]\n*[[uranium-thorium dating|uranium-thorium]]\n*[[optically stimulated luminescence dating]]\n*[[uranium-lead dating|uranium-lead]]\n\n==Fundamentals of radiometric dating==\n\nAll ordinary [[matter]] is made up of combinations of [[chemical element]]s, each with its own [[atomic number]], indicating the number of [[proton]]s in the [[atomic nucleus]]. Additionally, elements may exist in different [[isotope]]s, with each isotope of an element differing only in the number of [[neutron]]s in the nucleus. A particular isotope of a particular element is called a nuclide. Some nuclides are inherently unstable. That is, at some [[random]] point in time, an atom of such a nuclide will be transformed into a different nuclide by the process known as [[radioactive decay]]. This transformation is accomplished by the emission of particles such as [[electron]]s (known as [[beta decay]]) or [[alpha particle]]s. \n\nWhile the moment in time at which a particular nucleus decays is random, a collection of atoms of a radioactive nuclide decays [[exponential decay|exponentially]] at a rate described by a parameter known as the [[half-life]], usually given in units of years when discussing dating techniques. After one half-life has elapsed, one half of the atoms of the substance in question will have decayed. Many radioactive substances decay from one nuclide into a final, stable [[decay product]] (or \"daughter\") through a series of steps known as a [[decay chain]]. In this case, the half-life is usually given is for the entire chain, rather than just one step in the chain. Nuclides useful for radiometric dating have half-lives ranging from a few thousand to a few billion years.\n\nThe half-life of a nuclide depends solely on its nuclear properties; it is not affected by [[temperature]], chemical environment, [[magnetic field|magnetic]] and [[electric field]]s, or any other external factors. The half-life of any nuclide is also believed to be constant through time. Although decay can be accelerated by radioactive bombardment, such bombardment tends to leave evidence of its occurrence. Therefore, in any material containing a radioactive nuclide, the proportion of the original nuclide to its decay product(s) changes in a predictable way as the original nuclide decays. This predictability allows the relative abundances of related nuclides to be used as a [[clock]] that measures the time from the incorporation of the original nuclide(s) into a material to the present.\n\nThe processes that form specific materials are often conveniently selective as to what elements they incorporate during their formation. In the ideal case, the material will incorporate a parent nuclide and reject the daughter nuclide. In this case, the only daughter nuclides to be found through examination of a sample must have created since the sample was formed. When a material incorporates both the parent and daughter nuclides at the time of formation, it may be necessary to assume that the initial proportions of a radioactive substance and its daughter are known. The daughter product should not be a small-molecule gas that can leak out of the material, and it must itself have a long enough half-life that it will be present in significant amounts. In addition, the initial element and the decay product should not be produced or depleted in significant amounts by other reactions. The procedures used to isolate and analyze the reaction products must be straightforward and reliable.\n\nIf a material that selectively rejects the daughter nuclide is heated, any daughter nuclides that have been accumulated over time will be lost through [[diffusion]], setting the isotopic \"clock\" to zero. The temperature at which this happens is known as the \"blocking temperature\" and is specific to a particular material. \n\nIn contrast to most radiometric dating techniques, [[isochron dating]] using the [[Rubidium-Strontium dating|rubidium-strontium]] decay sequence does not require knowledge of the initial proportions.\n\n===Limitation of techniques===\n\nAlthough radiometric dating is accurate in principle, the accuracy is very dependent on the care with which the procedure is performed. The possible confounding effects of initial contamination of parent and daughter isotopes have to be considered, as do the effects of any loss or gain of such isotopes since the sample was created. Accuracy is enhanced if measurements are taken on different samples taken from the same rock body but at different locations. This permits some compensation for variations. \n\nThe precision of a method of dating depends in part on the half-life of the radioactive isotope involved. For instance, carbon-14 has a half-life of less than 6000 years. After an organism has been dead for 60,000 years, so little carbon-14 is left in it that accurate dating becomes impossible. On the other hand, the concentration of carbon-14 falls off so steeply that the age of relatively young remains can be determined precisely to within a few decades. The isotope used in [[uranium-thorium dating]] has a longer half-life, but other factors make it more accurate than radiocarbon dating.\n\n==Modern dating techniques==\n\nRadiometric dating can be performed on samples as small as a billionth of a gram using a [[mass spectrometer]]. The mass spectrometer was invented in the [[1940s]] and began to be used in radiometric dating in the [[1950s]]. The mass spectrometer operates by generating a beam of [[ion|ionized atoms]] from the sample under test. The ions then travel through a magnetic field, which diverts them into different sampling sensors, known as \"Faraday cups\", depending on their mass and level of ionization. On impact in the cups, the ions set up a very weak current that can be measured to determine the rate of impacts and the relative concentrations of different atoms in the beams. \n\nThe uranium-lead radiometric dating scheme is one of the oldest available, as well as one of the most highly respected. It has been refined to the point that the error in dates of rocks about three billion years old is no more than two million years. \n\nUranium-lead dating is best performed on the [[mineral]] \"[[zircon]]\" (ZrSiO4), though it can be used on other materials. Zircon incorporates uranium atoms into its crystalline structure as substitutes for zirconium, but strongly rejects lead. It has a very high blocking temperature, and is very chemically inert. \n\nOne of its great advantages is that any sample provides two clocks, one based on uranium-235\'s decay to lead-207 with a half-life of about 4.5 billion years, and one based on uranium-238\'s decay to lead-206 with a half-life of about 700 million years, providing a built-in crosscheck that allows accurate determination of the age of the sample even if some of the lead has been lost. \n\nTwo other radiometric techniques are used for long-term dating. Potassium-argon dating involves the beta decay of potassium-40 to argon-40. Potassium-40 has a half-life of 1.3 billion years, and so this method is applicable to the oldest rocks. Radioactive potassium-40 is common in micas, feldspars, and hornblendes, though the blocking temperature is fairly low in these materials, about 125C. \n\nRubidium-strontium dating is based on the beta decay of rubidium-87 to strontium-87, with a half-life of 50 billion years. This scheme is used to date old igneous and metamorphic rocks, and has also been used to date lunar samples. Blocking temperatures are so high that they are not a concern. Rubidium-strontium dating is not as precise as the uranium-lead method, with errors of 30 to 50 million years for a 3-billion-year-old sample.\n\n==Short-range dating techniques==\nThere are a number of other dating techniques that have short ranges and are so used for historical or archaelogical studies. One of the best-known is the [[Radiocarbon dating|carbon-14 (C14) radiometric technique]]. \n\nCarbon-14 is a radioactive isotope of carbon-12, with a half-life of 5,730 years (very short compared with the above). In other radiometric dating methods, the heavy parent isotopes were synthesized in the explosions of massive stars that scattered materials through the Galaxy, to be formed into planets and other stars. The parent isotopes have been decaying since that time, and so any parent isotope with a short half-life should be extinct by now. \n\nCarbon-14 is an exception. It is continuously created through collisions of neutrons generated by cosmic rays with nitrogen in the upper atmosphere. The carbon-14 ends up as a trace component in atmospheric [[carbon dioxide]] (CO2). \n\nAn organism acquires carbon from carbon dioxide during its lifetime. Plants acquire it through respiration and [[photosynthesis]], and animals acquire it from consumption of plants and other animals. When the organism dies, the carbon-14 begins to decay, and the proportion of carbon-14 left when the remains of the organism are examined provides an indication of the date of its death. Carbon-14 radiometric dating has a range of about 50,000 years. \n\nThe rate of creation of carbon-14 appears to be roughly constant, as cross-checks of carbon-14 dating with other dating methods show it gives consistent results. However, local eruptions of volcanoes or other events that give off large amounts of carbon dioxide can reduce local concentrations of carbon-14 and give inaccurate dates. \nThe releases of carbon dioxide into the biosphere as a consequence of industrialization have also depressed the proportion of carbon-14 by a few percent; conversely, the amount of carbon-14 was increased by above-ground nuclear bomb tests that were conducted into the early [[1960s]]. \n\nAnother relatively short-range dating technique is based on the decay of uranium-238 into thorium-230, a process with a half-life of 80,000 years It is accompanied by a sister process, in which uranium-235 decays into protactinium-231, which has a half-life of 34,300 years. \n\nWhile [[uranium]] is water-soluble, [[thorium]] and [[protactinium]] are not, and so they are selectively precipitated into ocean-floor [[sediment]]s, from which their ratios are measured. The scheme has a range of several hundred thousand years. \n\n[[Archaeologist]]s use tree-ring dating ([[dendrochronology]]) to determine the age of old pieces of wood. Trees grow rings on a yearly basis, with the spacing of rings being wider in good growth years than in bad growth years. These spacings can be used to help pin down the age of old wood samples, and also give some hints to climate change. The technique is only useful to about 4,000 years in the past, however, because it requires overlapping tree ring series. \n\nAlthough determining geologic time by measuring the rate of deposition of sediments is not reliable over the large scale, it is still useful for certain scenarios, such as the deposition of layers of sediment on the bottom of a stable lake. The approach is now known as \"varve analysis\" (the term \"varve\" means a layer or layers of sediment). \n\nAnother technique used by archaelogists is to inspect the depth of penetration of water vapor into chipped [[obsidian]] (volcanic glass) artifacts. The water vapor creates a \"hydration rind\" in the obsidian, and so this approach is known as \"hydration dating\" or \"obsidian dating\", and is useful for determining dates as far back as 200,000 years. \n\nNatural sources of radiation in the environment knock loose electrons in, say, a piece of pottery, and these electron accumulate in defects in the material\'s crystal lattice structure.\nWhen the sample is heated, at a certain temperature it will glow from the emission of electrons released from the defects, and this glow can be used to estimate the age of the sample to a threshold of a few hundred thousand years. \n\nFinally, \"fission track dating\" involves inspection of a polished slice of a material to determine the density of \"track\" markings left in it by radioactive decay of uranium-238 impurities. \n\nThe uranium content has to be understood, but that can be determined by placing a plastic film over the polished slice of the material, and then bombarding it with slow neutrons. This causes induced fission of U-235, as opposed to [[spontaneous fission]] of U-238. The fission tracks produced by this process are recorded by a thin plastic film placed against the surface of the sample. The uranium content of the material can then be calculated so long as the neutron dose is known. \n\nThis scheme has a maximum range of about a million years and works best with [[mica]]s, [[tektite]]s (glass fragments from volcanic eruptions), and meteorites. However, the dates may be inaccurate if the sample was heated to high temperatures in the past as blocking temperatures are generally low, or if the sample was exposed on the surface of the Earth where it was bombarded with cosmic rays.\n\n== See also ==\n* [[age of the Earth]]\n* [[exponential decay]]\n* [[half-life]]\n* [[radioactive decay]]\n* [[radioactivity]]\n* [[radiocarbon dating]]\n* [[thermoluminescence dating]]\n\n[[Category:Radiometric dating| ]]\n[[Category:Chemical isotope]]\n[[es:Datación radiométrica]]\n[[fr:Datation radioactive]]\n[[ja:放射線年代測定]]','',13,'Budhi','20041229220433','',0,0,0,1,0.362819353554,'20050126082014','79958770779566'); INSERT INTO cur VALUES (2073,0,'Causality','The [[Philosophy|philosophical]] concept of \'\'\'Causality\'\'\' or \'\'\'Causation\'\'\' refers to the set of all particular \"causal\" or \"cause-and-effect\" relations.\n\nThe [[Genus-differentia_definition|Differentia]] (distinguishing properties/characteristics) of Causality which all causal relations have in common:\n\n*The [[relationship|relationships]] hold between events, objects or [[state (physics)|states of affairs]].\n*The first event \'\'A\'\' (the \'\'cause\'\') is a [[reason]] that brings about the second event \'\'B\'\' (the \'\'effect\'\')\n*The first event \'\'A\'\' chronologically precedes the second event \'\'B\'\'\n*Events like \'\'A\'\' are consistently followed by events like \'\'B\'\'\n\nExamples decribing causal relationships:\n\n*\"The cue ball \'\'causes\'\' the eight ball to roll into pocket.\"\n*\"Heat \'\'causes\'\' water to boil.\"\n*\"The Moon\'s gravity \'\'causes\'\' the Earth\'s tides.\"\n*\"A hard blow to the arm causes a bruise.\"\n*\"My pushing the accelerator \'\'caused\'\' the [[Automobile|car]] to go faster.\"\n\nBut this [[definition]] is somewhat [[circular_reasoning|circular]]; what does it then \'\'really\'\' mean to say that \'\'A\'\' is a reason that \'\'B\'\' occurs? An important [[question]] in [[philosophy]] and other fields is to clarify the relationship between causes and effects, as well as how (and even if!) causes can bring about effects.\n\nA causal relation between heat and water boiling:\n\n*The heating came before the boiling\n*Whenever water is heated sufficiently, then it boils\n\nSo sufficient heating is always, or consistently, followed by boiling.\n\nWhile the perceived observance of causality is quite possibly the most basic pattern in human experience, [[David Hume]] held that causes and effects are not [[reality|real]] (or at least not knowable), but [[imagination|imagined]] by our [[mind]] to make sense of the [[observation]] that \'\'A\'\' often occurs together with or slightly before \'\'B\'\'. All we can observe are [[correlation]]s, not causations.\n\nSee also [[Categorical imperitive]]; [[Causality loop]]; [[Chance]]; [[Chaos theory]]; [[Consequentialism]]; [[Dependency]]; [[Determinism]]; [[Free will]]; [[Global warming controversy]]; [[Initiative]]; [[Interaction]]; [[Linear regression]]; [[Logic]]; [[post hoc ergo propter hoc]]; [[Randomness]]; [[Synchronicity]];\n\n==Attribution==\n\n[[Attribution Theory]] is the [[theory]] concerning how people explain individual occurrences of causation. [[Attribution]] can be external (assigning causality to an outside agent or force - claiming that some outside thing motivated the event) or internal (assigning causality to factors within the person - taking personal [[responsibility]] or [[accountability]] for one\'s actions and claiming that the person was directly responsible for the event). Taking causation one step further, the type of attribution a person provides influences their future behavior.\n\nThe intention behind the cause or the effect can be covered by the subject of [[action (philosophy)]]. See also [[Accident]]; [[Blame]];[[Intent]]; [[Responsibility]];\n\n==Law==\nAccording to [[law]] and [[jurisprudence]], \'\'\'legal cause\'\'\' must be demonstrated in order to hold a [[defendant]] liable for a [[crime]] or a [[tort]] (ie. a civil wrong such as negligence or trespass). It must be proven that causality, or a \'sufficient causal link\' relates the defendant\'s actions to the [[criminal event]] or damage in question.\n\n==Philosophy==\nIn a strict reading, if \'\'A\'\' causes \'\'B\'\', then \'\'A\'\' must \'\'always\'\' be followed by \'\'B\'\'. In this sense, [[sex]] does not cause [[pregnancy]], nor does [[smoking]] cause [[cancer]]. In everyday usage, we therefore often take \"\'\'A\'\' causes \'\'B\'\'\" to mean \"\'\'A\'\' causes an increase in the [[probability]] of \'\'B\'\'\".\n\nThe establishing of cause and effect, even with this relaxed reading, is notoriously difficult, expressed by the widely accepted statement \"[[Correlation implies causation (logical fallacy)|correlation does not imply causation]]\". For instance, the observation that smokers have a dramatically increased lung cancer rate does not establish that smoking must be a \'\'cause\'\' of that increased cancer rate: maybe there exists a certain genetic defect which both causes cancer and a yearning for nicotine.\n\nAlternatively, \'\'A\'\' may be:\n* one of many possible causes of \'\'B\'\',\n* a single step along a causal chain (sex often leads to release of sperm, which can lead to the combination of sperm and egg, and the combination sperm and egg leads to pregnancy)\n* one of many factors which, when combined, lead to \'\'B\'\' \n\nAnother complication is typified by the example of the moon\'s gravity. It isn\'t accurate to say, \"the moon exerts a gravitic pull and then the tides rise.\" Gravity, rather, is a law expressing a constant observable relationship among masses, and the movement of the tides is an example of that relationships. There are no discrete events, \"pulls\" that can be said to precede those other events, high tides! \n\n=== Aristotle ===\n\n[[Aristotle]] suggested four types of cause for a thing which exists: Material, Efficient, Final and Formal.\n\nTake for example the causality involved in creating a silver chalice used in a religious ceremony (this example is from [[Martin Heidegger]]). The four causes of the event of its creation are:\n\n*The \'\'material\'\' cause would be the [[silver]] used to create the chalice; the raw matter required by the event.\n*The \'\'formal\'\' cause would be the [[chalice]] design itself—the shape in which to form the silver; the design for the use of the raw matter.\n*The \'\'efficient\'\' cause would be the [[silversmith]] who took the silver and formed it into shape of the chalice; the actual agent required in turning the raw matter into the desired form.\n*The \'\'final\'\' cause would be the [[religion|religious ceremony]] which required a silver chalice in the first place; the ultimate reason behind the event, what compels the agent to make the raw matter into its form.\n\nNote that cause here does not imply a [[temporal]] relation between the cause and the effect. See [[supervenience]].\n\n===Nihilism and Causality===\n\nAlso see, Causality and Structuralist Theory \n\n[[Nihilist]]s subscribe to a world-view in which the [[universe]] is nothing but a chain of meaningless events following one after another according to the law of cause and effect. According to this [[worldview]] there is no such thing as \"[[free will]]\", and therefore, no such thing as [[morality]] of a moral [[God]]. Learning to bear the burden of a meaningless universe, and justify one\'s own existence, is the first step toward becoming the \"overman\" that [[Nietzsche]] speaks of extensively in his philosophical writings. \n\nAs an appropriate \"response\" to the meaningless causality of the universe, nihilists recommend: courage and disillusion. Nietzsche\'s life provides an object lesson for those who are wary of nihilism, who maintain that such lives end quite typically in madness and chaos.\n\n===Hume===\n\nThe philosopher who produced the most striking analysis of causality was [[David Hume]]. He asserted that it was impossible to \'\'know\'\' that certain laws of cause and effect always apply - no matter how many times one observe them occurring. Just because the sun has risen every day since the begining of the Earth does not mean that it will rise again tomorrow. However, it is impossible to go about one\'s life without assuming such connections and the best that we can do is to maintain an open mind and never presume that we know any laws of causality for certain. This was used as an argument against [[metaphysics]], [[ideology]] and attempts to find theories for everything. [[A.J. Ayer]] claimed that his [[law of verification]] was an application of Hume\'s teaching, yet it was, in fact, exactly what [[Hume]] argued against - assuming that empirical observation could lead to definite knowledge. [[Karl Popper]] clarified matters with his [[law of falsification]], which is more in line with Hume\'s teachings that any new experience could disprove a law that had been previously thought to be certain.\n\n==Programming==\n\nThe classic IF/THEN [[statement]] in most [[programming languages]] is a perfect example of simplified causality: If \'\'A\'\' is true, then \'\'B\'\' will occur. This can be expanded using [[Boolean algebra]]: If \'\'A\'\' \'\'\'and\'\'\' \'\'B\'\' are both true, then \'\'C\'\' will occur; If either \'\'A\'\' \'\'\'or\'\'\' \'\'B\'\' is true, then \'\'C\'\' will occur.\n\n==Religion and Theology== \n===The existence of God===\nOne of the classic [[arguments for the existence of God]] is known as the \"[[Cosmological argument]]\" or \"[[First cause]]\" argument. It works from the premise that every natural event is the effect of a cause. If this is so, then the events that caused today\'s events must have had causes themselves, which must have had causes, and so forth. If the chain never ends, then one must uphold the hypothesis of an \"actual infinite,\" which is often regarded as problematic, see [[Hilbert\'s paradox of the Grand Hotel]]. If the chain does end, it must end with a non-natural or supernatural cause at the start of the natural world -- e.g. a creation by God. \n\nSometimes the argument is made in [[eternity|non-temporal]] terms. The chain doesn\'t go back in time, it goes downward into the ever-more enduring facts, and thus toward the [[eternity|timeless]].\n\nTwo questions that can help to focus the argument are:\n\n1) What is an event without cause?\n\n2) How does an event without a cause occur?\n\nCritics of this argument point out [[Cosmological_argument#Critique_of_the_cosmological_argument|problems]] with it.\n\n===Karma===\n[[Karma]] is the belief held by some major [[religion]]s that a person\'s actions cause certain effects in future [[reincarnation|incarnations]], positively or negatively.\n\n===Reversed causality===\nSome [[new religious movement|modern religious movements]] have postulated along the lines of philosophical [[idealism]] that causality is actually reversed from the direction normally presumed. According to these groups, causality does not proceed inward, from external random causes toward effects on a perceiving individual, but rather outward, from a perceiving individual\'s causative mental requests toward responsive external physical effects that only seem to be independent causes. These groups have accordingly developed new causality principles such as the doctrine of [[responsibility assumption]].\n\n==Science==\nUsing the [[Scientific method]], scientists set up [[Experiment|experiments]] to determine causality in the physical world. Certain elemental forces such as [[Gravity|gravity]], the strong and weak nuclear forces, and electromagnetism are said to be the causes of all other actions in the universe.\n\nSee also [[Conditioning]]; [[Placebo]]; [[Placebo effect]]; \n\n=== Physics ===\nFor a discussion of how causality resonates in the field of [[physics]], see [[causality (physics)]]\n\n==Statistics==\nIn [[statistics]], it is generally accepted that observational studies (like counting cancer cases among smokers) can give hints, but can never \'\'establish\'\' cause and effect. The gold standard for causation here is the \'\'randomized experiment\'\': take a large number of randomly selected people, divide them into two groups, force one group to smoke and prohibit the other group from smoking (ideally in a [[double-blind]] setup), then determine whether one group develops a significantly higher lung cancer rate. Obviously, for ethical reasons this [[experiment]] cannot be performed, but the method is widely applicable for less damaging experiments.\n\nThat said, under certain [[assumption]]s, parts of the causal structure among several variables \'\'can\'\' be learned from full [[covariance]] or [[case data]] by the techniques of [[Path analysis]] and more generally, [[Bayesian network]]s. Generally these [[inference algorithm]]s search through the \'\'many\'\' possible causal structures among the [[variable]]s, and remove ones which are strongly incompatible with the observed [[correlation]]s. In general this leaves a set of possible [[causal relation]]s, which should then be tested by designing appropriate [[experiment]]s. If experimental data is already available, the [[algorithm]]s can take advantage of that as well.\n\nSee also: [[Supply and demand]]\n\n== Symbolism and Causality ==\nWhile the names we give objects often refer to their appearance, they can also refer to an object\'s \'\'causal powers\'\' - what that object can \'\'do\'\', the effects it has on other objects or people. David Sobel and Alison Gopnik from the Psychology Department of UC Berkeley designed a device known as \'\'the blicket detector\'\' which suggests that \"when causal property and perceptual features are equally evident, children are equally as likely to use causal powers as they are to use perceptual properties when naming objects\". [http://ihd.berkeley.edu/res-sobel.htm More Info]\n\n== External links == \n===Stanford Encyclopedia of Philosophy: ===\n* [http://plato.stanford.edu/entries/causation-probabilistic/ Probabilistic Causation]\n* [http://plato.stanford.edu/entries/causation-mani/ Causation and Manipulability]\n* [http://plato.stanford.edu/entries/causation-counterfactual/ Counterfactual Theories of Causation]\n* [http://plato.stanford.edu/entries/causation-process/ Causal processes]\n===General===\n* [http://etext.lib.virginia.edu/cgi-local/DHI/dhi.cgi?id=dv1-37 \'\'Dictionary of the History of Ideas\'\':] Causation\n* [http://etext.lib.virginia.edu/cgi-local/DHI/dhi.cgi?id=dv1-40 \'\'Dictionary of the History of Ideas\'\':] Causation in Law\n* [http://etext.lib.virginia.edu/cgi-local/DHI/dhi.cgi?id=dv1-38 \'\'Dictionary of the History of Ideas\'\':] Causation in History\n\n== References ==\n* Judea Pearl: \'\'Causality\'\', Cambridge University Press, ISBN 0521773628\n* Peter Spirtes, Clark Glymour and Richard Scheines: \'\'Causation, Prediction, and Search\'\', MIT Press, ISBN 0262194406\n\n[[de:Kausalität]] \n[[el:Αιτιότητα]]\n[[ja:因果]]\n[[nl:Oorzakelijkheid]]\n[[Category:Epistemology]]\n\n Fundamental\n Academia\n Academic disciplines\n Humanities and art\n Philosophy\n Metaphysics\n Epistemology\n Relationship\n Causation/Causality','',13,'Budhi','20041229220516','',0,0,0,1,0.145648870696,'20050303214455','79958770779483'); INSERT INTO cur VALUES (2074,0,'Extrapolation','[[de:Extrapolation]]\n[[ja:外挿]]\n\nIn [[mathematics]], \'\'\'extrapolation\'\'\' is a type of [[interpolation]]. When a tabulated [[function (mathematics)|function]] is interpolated not \'\'between\'\' given values, but \'\'outside\'\' of the given range, this is called extrapolation. Extrapolation often looks sensible at first glance, but its results are often invalid or subject to substantial [[uncertainty]].\n\n: {{stub}}\n\n==See also==\n*[[Richardson extrapolation]]','',13,'Budhi','20041229220728','',0,0,0,1,0.015078723936,'20041229220728','79958770779271'); INSERT INTO cur VALUES (2075,0,'Kalibrasi','\'\'\'Kalibrasi\'\'\' nyaeta nangtukeun, ku ngukur atawa ngabandingkeun jeung standar, nilai nu bener keur unggal bacaan dina alat ukur. Standarna dirawat ku organisasi nasional atawa internasional.\n\nKeur konstanta fisik, beurat, jeung ukuran, nilaina dipikanyaho sarta dipake dina [[SI|Sistim Satuan Internasional(SI)]]. Saperti konstanta panjang nyaeta [[méter]], beurat dina the [[kilogram]], sarta eusi dina [[litre|liter]].\n\nDi Amerika, [[National Institute of Standards and Technology]], bagian tina pamarentah federal, ngarawat standar sarta ngarupakeun lembaga nu boga wewenang keur satuan SI jeung standar industri. NIST oge [[traceability|menelusuri]], kaakuratan alat nu pakait jeung karusakan alat ukur make standar turunan nu dirawat ku [[NIST]], keur ngurangan [[uncertainty|kateupastian]].\n\n==Tempo ogé==\n*[[Kalibrasi (statistik)]]\n\n[[en:Calibration]]\n[[nl:Calibratie]]\n\n{{pondok}}','',3,'Kandar','20050316024646','',0,0,1,0,0.468635490133,'20050316024646','79949683975353'); INSERT INTO cur VALUES (2076,0,'SI','\'\'\'Sistim Internasional\'\'\' (lambangna \'\'\'SI\'\'\', sarua jeung tina asal hartina dina [[basa Prancis]] \'\'Système International d\'Unités\'\'), nyaéta [[sistim unit]] nu pangumumna dipaké. Iwal di As jeung Inggris, sistim ieu dipaké dina kahirupan sapopoé (utamana dagang) di sakuliah dunya, ogé dina widang ilmiah. SI was selected as a specific subset of the existing [[Metre]]-[[Kilogram]]-[[Second]] systems of units (MKS), rather than the older [[Centimetre gram second system of units|Centimetre-Gram-Second system of units (CGS)]]. Various new units were added with the introduction of the SI and at later times. SI is sometimes referred to as the \'\'\'metric system\'\'\' (especially [[Metric system in the United States|in the United States]], which has not widely adopted it, although it has been used more commonly in recent years, and the [[United Kingdom|UK]], where conversion is incomplete). \'\'Metric system\'\' is a broader term which includes SI; however, not all metric units of measurement are accepted as \'\'\'SI\'\'\' units.\n\nThere are seven [[SI base unit|base units]] and several [[SI derived unit|derived units]], together with a set of [[SI prefix|prefix]]es. Non-SI units can be converted to SI units (or \'\'vice versa\'\') according to the [[conversion of units]].\n\n==Asal-usul==\n\nThe units of the SI are decided by a series of international conferences organised by the [[standards organization]] [[Bureau International des Poids et Mesures]] (International Bureau of Weights and Measures). The SI was first given its name in [[1960]], and last added to in [[1971]].\n\nThe true origins of the SI or metric system date back to approximately [[1640]]. It was invented by French scientists, and was given a huge boost in popularity by the [[French Revolution]] of [[1789]]. The metric system tried to choose units which were non-arbitrary, merging well with the revolution\'s official ideology of \"Pure Reason\". The layout of the metric system may have been based on the idealistic world-view of ancient Greeks, who theorized that there were four basic elements: earth, water, fire and air.\n\nThe most important unit is that of length: one metre was intended to be equal to 1/10,000,000thof the distance from the pole to the equator along the meridian through Paris. This is approximately 10% longer than one [[yard]]. Later on, a platinum rod with a rigid, X-shaped cross section was produced to serve as the easy-to-check standard for one metre\'s length. However, due to the difficulty of actually measuring the length of a meridian quadrant in the [[18th century]], the first platinum prototype was short by 0.2 millimetres. Then a multiple of a specific radiation wavelength was introduced to abstractly define the (unchanged) length of the metre unit, and finally the metre was defined as the distance travelled by light in a vacuum in a specific period of time.\n\nThe unit of mass is the kilogram, which was defined by a cube filled with distilled pure water at its densest (+4° Celsius) and having sides equal to 1/10th of a metre. This volume contains one kilogram of water. One kilogram is about 2.2 [[pound]]s. This cubic space was also known as one [[litre]] (since slightly revised) so volumes of different liquids could be compared. Later on, a platinum-iridium metal cylinder was manufactured to serve as the one kilogram weight standard and remained so ever since.\n\nThe unit of temperature became the centigrade or inverted Celsius grade, which means the mercury scale is divided into 100 equal length parts between the water-ice mixture and the boiling point of pure, distilled water. Boiling water thus becomes one hundred degrees Celsius and freezing is zero degrees Celsius. This is the metric unit of temperature in everyday use. A hundred years later, scientists discovered [[absolute zero]]. This prompted the establishment of a new temperature scale, called the absolute scale or [[Kelvin]] scale, which relocates the zero place but still uses 100 kelvins between the freezing point and boiling point of water.\n\nThe metric unit of time remained the second. One definition of day is 86,400 seconds. The formal definition of the second has been changed several times for enhanced scientific requirements (astronomic observations, tuning fork clock, quartz clock and then [[caesium]] [[atomic clock]]) but wristwatch users remain relatively unaffected.\n\nThe swift worldwide adoption of the metric system as a tool of economy and everday commerce was based mainly on the lack of customary systems in many countries to adequately describe some concepts, or as a result of an attempt to standardize the many regional variations in the customary system. International politics also factored into the choice as many countries made the industrial shift when Britain still had empire status, and had various feelings related to its position in the world. Scientifically, it provides ease when dealing with very large and small quantities because it lines up so well with our [[numeral system]].\n\nCultural differences can be represented in the local everyday uses of metric units. For example, bread is sold in one-half, one or two kilogram sizes in many countries, but you buy them by multiples of one hundred grams in the former USSR.\n\nNon-scientific people should not be put off by the fine-tuning that has happened to the metric base units over the past two hundred years, as experts regularly tried to refine the metric system to fit the best scientific researcher (e.g. MKG to CGS to SI system changes or the invention of Kelvin scale). These changes seldom affect the everyday use of metric units. The presence of these adjustments has been one reason advocates of the [[U.S. customary units]] have used against metrication.\n\n== Basis ==\n\nSI is built on seven [[SI base unit]]s, the [[kilogram]], [[metre]], [[second]], [[ampere]], [[kelvin]], [[mole (unit)|mole]], and [[candela]]. These are used to define various [[SI derived unit]]s. \n\nSI also defines a number of [[SI prefix]]es to be used with the units: these combine with any unit name to give subdivisions and multiples. For example, the prefix \'\'kilo\'\' denotes a multiple of a thousand, so the \'\'kilo\'\'metre is 1 000 metres, the \'\'kilo\'\'gram 1 000 grams, and so on. Note that a millionth of a kilogram is a milligram, not a microkilogram.\n\n==Gaya nulis SI==\n\n*Symbols are written in [[lower case]], except the symbols that are derived from the name of a person. This means that the [[symbol]] for the SI unit for pressure, named after [[Blaise Pascal]], is [[Pascal|Pa]], whereas the [[unit]] itself is written [[pascal]]. The official SI brochure lists the symbol for the litre as an allowed exception to the capitalization rules: either capital or lowercase L is acceptable.\n*Symbols are written in singular, e.g. 25 kg (not \"25 kgs\").\n*Symbols, unlike abbreviations, do not have a period (.) at the end.\n*It is preferable to keep the symbol in upright Roman type (for example, m for metres, L for litres), so as to differentiate from mathematical and physical variables (for example, \'\'m\'\' for mass, \'\'l\'\' for length).\n*A space is left between the numbers and the symbols: 2.21 kg, 7.3·102 m2\n*SI uses spaces to separate decimal digits in sets of three. e.g. 1 000 000 or 342 142 (in contrast to the commas or dots used in other systems, e.g. 1,000,000 or 1.000.000).\n*SI used only a comma as the separator for decimal fractions until [[1997]]. The number \"twenty four and fifty one hundredths\" would be written as \"24,51\". In 1997 the [[CIPM]] decided that the British full stop (the \"dot on the line\", or period) would be the decimal separator in text whose main language is English (\"24.51\"); the comma remains the decimal separator in all other languages.\n*Symbols for derived units formed from multiple units by multiplication are joined with a space or centre dot (·), e.g. N m or N·m.\n*Symbols formed by division of two units are joined with a [[slash (punctuation)|solidus]] (/), or given as a negative [[exponent]], e.g. m/s, m s-1, m·s-1 or \\frac{\\mbox{m}}{\\mbox{s}}. A solidus should not be used if the result is ambiguous, e.g. kg·m-1·s-2, not \"kg/m/s2\".\n\nThe system can legally be used in every country in the world, and many countries do not maintain definitions of other units. Those countries that still give official recognition to non-SI units (e.g. the [[United States|US]] and [[United Kingdom|UK]]) have defined the modern [[conversion of units|in terms of SI units]]; for example, the common [[inch]] is defined to be exactly 0.0254 metres. Survey distances have, however, not been redefined due to the accumulation of error it would entail. It was adopted by the 11th [[Conférence Générale des Poids et Mesures|General Conference on Weights and Measures]] (CGPM) in [[1960]]. (See [[weights and measures]] for a history of the development of units of measurement.)\n\n==Unit==\n\n===Unit dasar===\n\nDi handap ieu unit-unit dasar ti mana nu séjén diturunkeun, they are dimensionally independent. The definitions stated below are widely accepted.\n\n{{SI_base_units}}\n\n=== Dimensionless derived units ===\n\nThe following SI units are derived from the base units and are dimensionless.\n\n{{SI_dimensionless_units}}\n\n=== Derived units with special names ===\nBase units can be put together to derive units of measurement for other quantities. Some have been given names.\n\n{{SI_special_units}}\n\n=== Non-SI units accepted for use with SI===\n\nThe following units are not SI units but are \"accepted for use with the International System.\"\n\n{{SI_acceptable_units}}\n\n=== SI prefixes===\nThe following SI prefixes can be used to prefix any of the above units to produce a multiple or submultiple of the original unit.\n\n\n{{SI prefixes}}\n\n=== Obsolete SI prefixes===\nThe following SI prefixes are no longer in use.\n\n{{Obsolete SI prefixes}}\n\n== Spelling variations ==\n\nSeveral nations, notably the [[United States]], typically use the spellings \'meter\' and \'liter\' instead of \'metre\' and \'litre\'. This is in keeping with standard [[American English]] spelling (for example, Americans also use \'center\' rather than \'centre,\' using the latter on mostly office buildings; see also [[American and British English differences]]). In addition, the official US spelling for the [[SI prefix]] \'deca\' is \'deka\'.\n\nThe US government has approved these spellings for official use, but the [[Bureau International des Poids et Mesures|BIPM]] only recognizes the [[British English]] spellings as official names for the units. In scientific contexts only the symbols are used; since these are universally the same, the differences do not arise in practice in scientific use.\n\nThe unit \'gram\' is also sometimes spelled \'gramme\' in English-speaking countries other than the United States, though that is an older spelling and use is declining.\n\n== See also ==\n\n*[[Weights and measures]]\n*Other measurement systems: \n**[[Imperial unit|Imperial units]]\n**[[U.S. customary units]]\n**[[Metre-tonne-second system of units]]\n**[[Chinese unit|Chinese system of units]]\n**[[Planck units]]\n*[[CODATA]]\n*[[Metrication]]\n*[[Metric system in the United States]]\n*[[Metrology]]\n*[[UTC]] (Coordinated Universal Time)\n*[[Binary prefix|Binary Prefixes]] - used to quantify large amounts of computer [[data]]\n*[[Orders of magnitude]]\n*[[ISO 31]]\n\n== External links ==\n\n\'\'Official\'\'\n*[http://www.bipm.fr/en/si/ BIPM (SI maintenance agency)] (home page)\n*[http://www.bipm.org/en/publications/brochure/ BIPM reference] (SI reference)\n\n\'\'Information\'\'\n*[http://physics.nist.gov/cuu/Units/index.html US NIST reference on SI]\n**[http://ts.nist.gov/ts/htdocs/200/202/pub814.htm#chart chart]\n*[http://www.aticourses.com/international_system_units.htm SI - Its history and use in science and industry]\n*[http://www.unc.edu/~rowlett/units/ A Dictionary of Units of Measurement]\n*[http://www.sengpielaudio.com/Calculations03.htm Calculation of many metric and American and English units]\n\n==Further reading==\n\n*I. Mills, Tomislav Cvitas, Klaus Homann, Nikola Kallay, IUPAC: \'\'Quantities, Units and Symbols in Physical Chemistry\'\', 2nd ed., Blackwell Science Inc 1993, ISBN 0632035838.\n\n[[Category:SI units]]\n[[Category:Systems of units]]\n\n\n[[bg:Международна система единици]]\n[[ca:Sistema Internacional]]\n[[cs:Soustava SI]]\n[[da:SI-enhed]]\n[[de:SI-Einheitensystem]]\n[[es:Sistema Internacional de Unidades]]\n[[eo:Sistemo Internacia de Unuoj]]\n[[fi:SI-järjestelmä]]\n[[fr:Système international]]\n[[he:SI]]\n[[hu:SI mértékegységrendszer]]\n[[ia:Systema International de Unitates]]\n[[id:SI (satuan ukur)]]\n[[is:SI]]\n[[it:SI]]\n[[nl:SI]]\n[[no:SI-enhetene]]\n[[ja:国際単位系]]\n[[pl:Układ SI]]\n[[pt:SI]]\n[[ro:SI]]\n[[ru:СИ]]\n[[simple:SI]]\n[[sl:Mednarodni sistem enot]]\n[[th:หน่วยเอสไอ]]\n[[zh:国际单位制]]','/* Units */',3,'Kandar','20050216061756','',0,0,0,0,0.021545903807,'20050216061756','79949783938243'); INSERT INTO cur VALUES (2077,0,'Méter','\'\'\'Méter\'\'\' nyaéta [[unit dasar SI|unit dasar]] [[panjang]] dina [[SI|Sistim Internasional pikeun Unit]], diwatesan salaku panjang lintasan nu kaliwatan ku [[cahaya]] dina [[vakum]] absolut dina selang [[waktu]] 1/299,792,458 [[detik]]. Saméter sarua jeung 10000/254 [[inci]], kurang-leuwih 39,37 inci. Méter dilambangan ku aksara \'\'\'m\'\'\'.\n\n[[miliméter]] << [[séntiméter]] << [[désiméter]] << \'\'\'méter\'\'\' << [[dékaméter]] << [[héktométer]] << [[kilométer]]\n\n==Sajarah==\n\nKecap ieu asalna tina [[Basa Yunani]] \'\'metron\'\' (μετρον), \"[[ukuran]]\" nu ngaliwatan [[basa Prancis]] \'\'mètre\'\'. Dina [[basa Inggris]] munggaran dipaké taun [[1797]].\n\nDina abad ka-18, aya dua \'\'pendekatan\'\' kana watesan ngeunaan unit baku panjang. Aya nu nyarankeun watesan méter salaku panjang [[pendulum]] nu satengah-[[periode]]na sadetik. Nu séjén nyarankeun watesan méter salaku sapersapuluh yuta panjang méridian Bumi sapanjang kuadran (saparapat jarak-kuriling Bumi). Taun [[1791]], [[Akademi Élmu-élmu Prancis]] milih watesan méridian, migunakeun méridian Paris, batan watesan pendulum kusabab ayana béda gaya [[graviti]] di unggal tempat di Bumi, nu bakal mangaruhan periode pendulum. Taun [[1795]], Prancis ngadopsi méter salaku unit panjang resmina. Najan prototipe watang méteran leuwih pondok saperlima miliméter alatan salah itung, panjang ieu jadi baku. Jadi, jarak-kuriling [[Marcapada|Bumi]] ngaliwatan kutub kurang leuwih opat puluh yuta méter.\n\nTaun [[1870-an]] saluyu jeung kamajuan présisi modern, runtuyan sawala internasional lumangsung pikeun ngabaru baku métrik. [[Konvénsi Méter|Perjangjian Méter]] ([[1875]]) ngukuhkeun Biro Internasional Timbangan jeung Ukuran ([[\'\'Bureau International des Poids et Mesures\'\']], BIPM) nu maneuh nu ditempatkeun di [[Sèvres]], Prancis. Organisasi anyar ieu bakal nyieun sarta nyimpen prototipe méter jeung [[kilogram]] anyar, sarta bakal mertahankeun babandinganana katut unit dasar séjénna, nonmétrik, timbangan, jeung ukuran. Organisasi ieu nyiptakeun watang prototipe anyar taun 1889, ngajadikeun \'\'International Prototype Metre\'\' salaku jarak antara dua garis na watang baku campuran salapan puluh persén [[platinum]] jeung sapuluh persén [[iridium]].\n\nTaun [[1893]], méter baku munggaran diukur migunakeun [[interférométer]] ku [[Albert Abraham Michelson|Albert A. Michelson]], nu manggihan alat katut nu ngajengkeun digunakeunana [[panjang gelombang]] [[cahaya]] salaku baku jarak. Taun [[1925]], [[interférométri]] geus dipaké resmi di BIPM. Najan kitu, \'\'International Prototype Metre\'\' masih tetep dipaké nepi ka taun [[1960]], nalika Sawala Umum Timbangan jeung Ukuran ([[Conférence Générale des Poids et Mesures]], CGPM) ngawatesan méter dina sistim SI anyar nu sarua jeung 1.650.763,73 panjang gelombang [[garis émisi]] [[oranyeu]]-[[beureum]] dina [[spéktrum éléktromagnetik|spéktrum]] [[atom]] [[kripton]]-86 dina [[vakum]].\n\nPikeun ngurangan kateupastian, CGPM ka-17 taun [[1983]] ngaganti watesan méter ku watesan kiwari, ngaropéa panjang méter dina jihat [[waktu]] jeung [[laju cahaya]]:\n\n:\'\'Méter nyaéta panjang lintasan cahaya dina vakum dina selang waktu 1/299792458 detik.\'\'\n\nCatet yén watesan ieu kalawan tepat nangtukeun laju cahaya dina vakum 299.792.458 méter per detik. Watesan nu dumasar sipat fisik cahaya leuwih tepat jeung bisa diulang sabab sipat cahaya nu bisa dianggap konstan.\n\nPrototipe internasional méter asli disimpen kénéh di BIPM dina kaayaan nu dijéntrékeun taun [[1889]].\n\n==Tempo ogé==\n* [[1 E0 m]] pikeun perspéktif ngeunaan panjang saméter\n* [[Konversi unit]] pikeun babandingan jeung unit séjén\n* [[Émbohan SI]] pikeun émbohan nu nandakeun lilipetan atawa babagian ti méter, kayaning [[kilométer]] atawa [[séntiméter]]\n\n==Tumbu kaluar==\n* [http://physics.nist.gov/cuu/Units/meter.html History of the metre at the U.S. National Institute of Standards and Technology (NIST)]\n* [http://www.mel.nist.gov/div821/museum/timeline.htm Timeline of history of the metre at the NIST]\n* [http://www.sengpielaudio.com/ConvLeng.htm Distance unit conversions]\n* [http://www1.bipm.org/en/scientific/length/ Bureau International des Poids et Measures - Lengths]\n\n[[Category:Unit dasar SI]]\n[[Category:Unit panjang]]\n\n[[ast:Metru]]\n[[bg:Метър]]\n[[ca:Metre]]\n[[cs:Metr]]\n[[da:Meter]]\n[[de:Meter]]\n[[en:Metre]]\n[[et:Meeter]]\n[[es:Metro]]\n[[eo:Metro]]\n[[fr:Mètre]]\n[[gl:Metro]]\n[[hr:Metar]]\n[[id:Meter]]\n[[ia:Metro]]\n[[is:Metri]]\n[[it:Metro]]\n[[ko:미터]]\n[[la:Metrum]]\n[[hu:Méter]]\n[[ms:Meter]]\n[[nl:Meter]]\n[[ja:メートル]]\n[[no:Meter]]\n[[pl:Metr]]\n[[pt:Metro]]\n[[ro:Metru]]\n[[ru:Метр]]\n[[simple:Metre]]\n[[sl:Meter]]\n[[fi:Metri]]\n[[sv:Meter]]\n[[uk:Метр]]\n[[zh-cn:米 (计量单位)]]','/* Sajarah */',3,'Kandar','20050203020931','',0,0,1,0,0.05296196196,'20050211123919','79949796979068'); INSERT INTO cur VALUES (2078,0,'Kilogram','\'\'\'Kilogram\'\'\' (lambangna \'\'\'kg\'\'\') nyaéta [[unit dasar SI]] pikeun [[massa]]. Sa-[[gram]] diwatesan ku sapersaréwu kilogram. [[Konversi unit#Beurat|Konversi unit]] ngagambarkeun unit ékivalén massa dina sistim séjén.\n\n==Lilipetan==\n\n[[Émbohan SI]] dipaké pikeun méré ngaran lilipetan atawa babagian tina kilogram. Nu ilahar dipaké nyaéta,\n\n: [[ton]] = [[1 E3 kg|1 000 kg]] (kuduna mah disebutna \'\'mégagram\'\', ngan jarang pisan dipaké) (kadé pahili jeung \'\'US [[short ton]]\'\', 2000 pon atawa kira 907 kg)\n: [[gram]] = [[1 E-3 kg|1/1 000 kg]]\n: [[milligram]] = [[1 E-6 kg|sapersaréwu gram]] = [[1 E-6 kg|sapersayuta kilogram]]\n: [[mikrogram]] = [[1 E-9 kg|sapersayuta gram]] = [[1 E-9 kg|1/(10^9) kg]]\n\n==Watesan==\n\nKilogram mangrupakeun hiji-hijina unit SI nu masih kénéh watesanana dihubungkeun jeung artéfak batan sipat fisik.\n\nKilogram \'\'pituinna\'\' diwatesan salaku massa [[léter|saléter]] [[cai|cimurni]] dina [[temperatur]] 4 darajat [[Celsius]] jeung [[tekenan atmosfir baku]].\nWatesan ieu hésé pisan diwujudkeun sacara akurat, salasahijina sabab dénsitas cai gumantung kana tekenan, sedengkeun unit tekenan ngawengku massa salaku salasahiji faktorna, sahingga ngagasilkeun [[watesan sirkular|kagumantungan sirkular]] dina watesan kilogram. \n\nPikeun nyingkahan masalah ieu, watesan kilogram dibaru deui sacara \'\'tepat\'\' massa hiji [[baku]] husus nu dijieun sasarua-saruana jeung watesan asalna. Saprak [[1889]], sistim [[SI]] ngawatesan unit ieu sarua jeung massa \'\'\'prototipe kilogram internasional\'\'\', nu dijieun tina watang [[alloy]] [[platinum]] jeung [[Iridium (unsur)|iridium]] nu panjang jeung diaméterna [[1 E-2 m|39 mm]], sarta diteundeun di [[Bureau International des Poids et Mesures|Biro Internasional Timbangan jeung Ukuran]]. Salinan resmi prototipe kilogram dijieun pikeun prototipe nasional, nu dibandingkeun jeung prototipe Paris (\"\'\'Le Grand Kilo\'\'\"), kasarna unggal [[1 E8 d|10 taun]]. Prototipe kilogram internasional dijieun taun [[1880-an]]. \n\nDumasar watesan, kasalahan dina kabisaulangan watesan kiwari téh enol; ngan, dina harti ilahar kecapna, aya dina rentang 2 [[mikrogram]]. Ieu bisa kapanggih mun urang ngabandingkeun baku jeung salinan resmina, nu dijieun tina bahan sarta diteundeun dina kaayaan nu sarua. Teu aya nu bisa mastikeun mana nu leuwih stabil, naha nu asli aatawa nu salinanana. Ku kituna, prosedur ieu dipigawé unggal opat puluh taun.\n\nPrototipe internasional kilogram sigana ngahampangan kira 50 mikrogram salila saabad ieu, ku sabab nu tacan kanyahoan (dilaporkeun dina \'\'[[Der Spiegel]]\'\', 2003 #26). Bébédan nu kapanggih dina prototipena nyedek kana perluna néangan watesan anyar kilogram. Najan bener mun disebut yén sadaya objék di mayapada nambahan massana 50 mikrogram per kilogramna, sawangan ieu patojaiyah jeung ngéléhkeun tujuan unit baku massa.\n\n==Watesan ka hareup nu diajengkeun==\n\nAya sawatara usaha pikeun ngawanohkeun hiji watesan tina jalan fundaméntal atawa konstanta atomik:\n\n===Atom-counting approaches===\n* The [[Watt]] balance uses the [[current balance]] that formerly was used to define the [[ampere]] to relate the kilogram to a value for [[Planck\'s constant]], based on the definitions of the [[volt]] and the [[ohm]].\n* The [[Avogadro]] approach attempts at defining the kilogram by a fixed count of [[silicon]] atoms. As a practical realization, a [[sphere]] will be used where the size is measured by [[interferometry]].\n* The [[ion]] accumulation approach involves accumulation of [[gold]] atoms and measuring the electrical current required to neutralise them.\n\n===Fundamental-constant approaches===\n* The levitated [[superconductor]] approach relates the kilogram to electrical quantities by levitating a superconducting body in a magnetic field generated by a superconducting coil, and measuring the [[electrical current]] required in the coil.\n\n* Since the values of the [[Josephson constant|Josephson]] (CIPM (1988) Recommendation 1, PV 56; 19) and [[von Klitzing constant|von Klitzing]] (CIPM (1988), Recommendation 2, PV 56; 20) constants have been given conventional values, it is possible to combine these values (KJ ≡ 4.835 979×1014 Hz/V and RK ≡ 2.581 280 7×104 Ω) with the definition of the [[ampere]] to define the kilogram. As follows:\n\n:The kilogram is the mass which would be accelerated at precisely 2×10-7 m/s² if subjected to the per metre force between two straight parallel conductors of infinite length, of negligible circular cross section, placed 1 metre apart in vacuum, through which flow a constant current of exactly 6.241 509 629 152 65 × 1018 elementary charges per second.\n\n==Patalina jeung beurat==\nNalika sipat hiji barang disebutkeun dina kilogram, sipat ieu nujul ampir salawasna ka massa, padahal sipat dina pamakéan sapopoé mindengna disebut \"beurat\", a usage much deprecated by those communities (physicists and engineers) that prefer \'\'weight\'\' always to mean \"gravitational force\". Occasionally the gravitational force on an object is given in \"kilograms\", but the unit used is not a true kilogram: it is the deprecated kilogram-force (kgf), also known as the [[kilopond]] (kp). An object of mass 1 kg at the surface of the [[Earth]] will be subjected to a gravitational force (that is to say, it will have a weight) of approximately:\n\n:1 kgf = 1 kg × 9,806 65 m/s² = 9.806 65 [[newton|N]]\n\nnu mana N salaku [[Newton]], unit gaya SI. Catet yén faktor 9,806 65 ngan disatujuan salaku rataan (CGPM ka-3 (1901), CR 70), salaku niléy tepat \'\'g\'\', laju gravitasi lokal, béda-béda gumantung luhur-handap sarta tempatna di [[Marcapada|Bumi]]. (Tempo [[gee|graviti baku]]).\n\n==See also==\n* [[orders of magnitude (mass)]] for comparisons with other masses\n\n==Tumbu kaluar==\n\n*[http://www.npl.co.uk/mass/faqs/kilogram.html National Physical Laboratory FAQ on kilogram definition, the need for a new definition, and some alternatives]\n*[http://nvl.nist.gov/pub/nistpubs/jres/106/4/j64schw.pdf More on the NIST Watt Balance]\n*[http://www.npl.co.uk/mass/avogadro.html More on the Avogadro project]\n*[http://www.ex.ac.uk/trol/scol/ccmass.htm Conversion: Units of Weight]\n*[http://www.bipm.fr Le Bureau International des Poids et Mesures]\n\n[[Category:Unit dasar SI]]\n[[Category:Unit massa]]\n\n[[ca:Quilogram]]\n[[cs:Kilogram]]\n[[da:Kilogram]]\n[[de:Kilogramm]]\n[[en:Kilogram]]\n[[et:Kilogramm]]\n[[es:Kilogramo]]\n[[eo:Kilogramo]]\n[[fr:Kilogramme]]\n[[ia:Kilogramma]]\n[[it:Chilogrammo]]\n[[he:קילוגרם]]\n[[lv:Kilograms]]\n[[hu:Kilogramm]]\n[[minnan:Kong-kin]]\n[[nl:Kilogram]]\n[[ja:キログラム]]\n[[pl:Kilogram]]\n[[pt:Quilograma]]\n[[ru:Килограмм]]\n[[simple:Kilogram]]\n[[sl:Kilogram]]\n[[fi:Kilogramma]]\n[[sv:Kilogram]]\n[[th:กิโลกรัม]]\n[[zh:千克]]','/* Link with weight */',3,'Kandar','20050203072258','',0,0,0,0,0.188759767097,'20050203072258','79949796927741'); INSERT INTO cur VALUES (2079,0,'Litre','The \'\'\'litre\'\'\' (or \'\'\'liter\'\'\' in [[American English|US]]) is a metric unit of [[volume]]. The litre is not an [[SI]] unit, but (along with units such as hours and days) is listed as one of the \"units outside the SI that are accepted for use with the SI.\" ([http://physics.nist.gov/cuu/Units/outside.html NIST note])\nThe SI unit of volume is the [[cubic metre]] (m³). [http://physics.nist.gov/cuu/Units/units.html NIST note on SI units]\n\nThe symbol for the litre is the lowercase letter \'\'\'l\'\'\' or the uppercase letter \'\'\'L\'\'\'. A cursive or script small letter l (\'\'\'ℓ\'\'\') is also used, but is not accepted by the [[Bureau International des Poids et Mesures|BIPM]].\n\n== Definition ==\n\nA litre is equal to:\n* 0.001 [[cubic metre]]s,\n* 1 [[cubic decimetre]],\n* 1000 [[cubic centimetre]]s\n* the volume of a cube of side 10 [[centimetre]]s.\nThere are 1,000 litres in a [[cubic metre]] (m³). See [[1 E-3 m³]] for a comparison of volumes.\n\nThe litre is subdivided into smaller units by the application of [[SI prefix]]es, making 1 litre equivalent to:\n* 1,000 millilitres (ml) = 1,000 cubic centimetres (cm³),\n* 100 centilitres (cl),\n* 10 decilitres (dl),\n* 0.01 hectolitre (hl).\n\nLarger volumes can be measured using kilolitres (kl, 1,000 litres) or megalitres (Ml, 1,000,000 litres), but usually cubic metres (m³, 1,000 litres) are used instead. \n[[millilitre]] << [[centilitre]] << [[decilitre]] << \'\'\'litre\'\'\'\n\nThere is no international standard regarding when to use litres and when to use cubic metres. In practice, litres are most commonly used for items measured by the capacity or size of their container (such as liquids, berries), whereas cubic metres (and its derived units) are most commonly used for items measured either by their dimensions or their displacements. The litre is often also used in some calculated measurements, such as density (kg/L), allowing an easy comparison with the density of water. \n\n== Symbol ==\n\nThe symbol for the litre was originally \'\'\'l\'\'\' (lowercase letter l).\n\nIn order to reduce confusion with the number 1, \'\'\'L\'\'\' (uppercase letter L) was accepted as an alternative symbol in [[1979]]. The [[United States]] [[National Institute of Standards and Technology]] recommends the use of the uppercase letter L. Uppercase L is also preferred in Canada and in Australia. The symbols for the derived units (using uppercase L) are in the form of µL, mL, kL, ML, and so on.\n\nPrior to 1979, the symbol \'\'\'ℓ\'\'\' (script small l, U+2113), came into common use in some countries; for example, it was recommended by the [[South African Bureau of Standards]] publication M33 in the 1970s. This symbol remains in common use, but is still not officially recognised by the [[Bureau International des Poids et Mesures|BIPM]].\n\n== History ==\n\nIn [[1793]], the litre was introduced in [[France]] as one of the new \"Republican Measures\", and defined as one cubic decimetre. Its name derived from an older French unit, the \'\'litron\'\', whose name came from Greek via Latin.\n\nIn [[1879]], the [[Comité International des Poids et Mesures|CIPM]] adopted the definition of the litre, and the symbol \'\'\'l\'\'\' (lowercase letter l).\n\nIn [[1901]], at the 3rd [[Conférence Générale des Poids et Mesures|CGPM]] conference, the litre was redefined as the space occupied by 1 kg of pure [[water]] at the temperature of its maximum density (3.98 °C) under a pressure of 1 [[atmospheric pressure|atm]]. This made the litre equal to about 1.000 028 dm³ (earlier reference works usually put it at 1.000 027 dm³).\n\nIn [[1964]], at the 12th CGPM conference, the litre was once again defined in exact relation to the metre, as another name for the cubic decimetre, that is, exactly 1 dm³. [http://ts.nist.gov/ts/htdocs/230/235/appxc/appxc.htm#footnote1 NIST Reference]\n\nIn [[1979]], at the 16th CGPM conference, the alternative symbol \'\'\'L\'\'\' (uppercase letter L) was adopted.\n\n== See also ==\n\n*[[Claude Émile Jean-Baptiste Litre]]\n*[[Pint]]\n*[[Gallon]]\n\n== External Links ==\n\n*[http://www.sengpielaudio.com/ConvVolum.htm Conversions of English and American volume and capacity units to metric units] \n*[http://www.sengpielaudio.com/calculator-milliliter.htm Conversion: volume and liter, capacity measures, and weight of water - prefixes]\n*[http://www.npl.co.uk/npl/reference/international.html UK National physical laboratory\'s \"Internationally recognised non SI units\" page]\n*[http://physics.nist.gov/cuu/Units/outside.html NIST recommends uppercase letter L]\n*[http://www.bipm.org/utils/en/pdf/si-brochure.pdf BIPM\'s \"SI Brochure\"]\n\n[[ca:Litre]]\n[[cs:Litr]]\n[[de:Liter]]\n[[el:Λίτρο]]\n[[es:Litro]]\n[[eo:Litro]]\n[[fr:Litre]]\n[[is:Lítri]]\n[[it:Litro]]\n[[nl:Liter]]\n[[ja:リットル]]\n[[no:Liter]]\n[[pl:Litr]]\n[[pt:Litro]]\n[[ru:Литр]]\n[[simple:Litre]]\n[[sl:Liter]]\n[[fi:Litra]]\n[[sv:Liter]]\n[[zh:升]]\n\n[[Category:Units of volume]]','',0,'84.191.105.127','20050306093628','',0,0,0,0,0.019610319527,'20050306093628','79949693906371'); INSERT INTO cur VALUES (2080,0,'Traceability','\'\'\'Traceability\'\'\' refers to an unbroken chain of measurements relating an instrument\'s [[measurement]]s to a known standard. Traceability can be used to certify an [[instrument]]\'s [[accuracy]] relative to a known standard.\n\nIn the USA, national standards for weights and measures are maintained by the [[National Institute of Standards and Technology]]. As defined by NIST, \"Traceability requires the establishment of an unbroken chain of comparisons to stated references.\"\n\n==See also==\n*[[Trade war over genetically modified food]]\n\n==External links==\n*[http://www.nist.gov National Institute of Standards and Technology]\n*[http://www.nist.gov/traceability/nist%20traceability%20policy-external.htm NIST Policy on Traceability]\n\n[[de:Rückverfolgbarkeit]]','',13,'Budhi','20041229225606','',0,0,0,1,0.017205619246,'20050303214455','79958770774393'); INSERT INTO cur VALUES (2081,0,'Calibration','#REDIRECT [[Kalibrasi]]\n','Calibration dipindahkeun ka Kalibrasi',13,'Budhi','20041229225734','',0,1,0,1,0.088558849183,'20041229225734','79958770774265'); INSERT INTO cur VALUES (2082,0,'Scientific_fraud','#redirect [[Scientific misconduct]]','',13,'Budhi','20041229234932','',0,1,0,1,0.260196202579,'20050303214455','79958770765067'); INSERT INTO cur VALUES (2083,0,'Ethics','\'\'\'Ethics\'\'\' is a general term for what is often described as the \"[[science]] of [[morality]]\". In [[philosophy]], ethical [[behavior]] is that which is \"[[Goodness and value theory|good]]\". The Western tradition of ethics is sometimes called \'\'\'moral philosophy\'\'\'. This is one of the three major branches of philosophy, alongside [[metaphysics]] and [[epistemology]]. \n\n==The history of ethics==\n\nThe formal study of ethics in a serious and analytical sense began with the early Greeks, and later Romans. Important Greek ethicists include the [[Sophists]] and [[Socrates]], [[Plato]] and [[Aristotle]], who developed [[ethical naturalism]]. The study of ethics was developed further by [[Epicurus]] and the [[Epicureanism|epicurean]] movement, and by [[Zeno of Citium|Zeno]] and the [[stoicism|stoics]].\n\nAlthough not developed in a formal and analytical sense, the subject of ethics was of great concern to the Hindu people in Ancient India. For the first time in world history, they described the highest ethical standards called \"absolute ethics\" by [[Albert Schweitzer]]. Millennia later, the [[Society of Friends]] or the Quakers reached as high as the [[Tirthankar|Jinas]]. \nSee also [[Ethics in religion]] \n\nIn Europe, the formal study of philosophy stagnated until the era of [[Maimonides]], [[Thomas Aquinas]] and others. It was in those days that the debate between ethics based on natural law and \"divine law\" gained a new importance.\n\nModern Western philosophy began with the work of greats such as [[Thomas Hobbes]], [[David Hume]] and [[Immanuel Kant]]. Their work was followed up by the utilitarians, [[Jeremy Bentham]] and [[John Stuart Mill]]. [[Arthur Schopenhauer]] must be mentioned here because of his [[Preisschrift über die Grundlage der Moral]]. He was the first European philosopher to start out from the ethical achievements of Ancient India. The study of analytic ethics went on with [[G. E. Moore]] and [[W. D. Ross]], followed by the emotivists, [[C. L. Stevenson]] and [[A. J. Ayer]]. [[Existentialism]] was developed by writers such as Jean Paul Sartre. Some modern philosophers who have done serious philosophical writing on ethics include [[John Rawls]], [[Elliot N. Dorff]], [[Jürgen Habermas]], [[Christine Korsgaard]] and [[Charles Hartshorne]].\n\n== Disputes of definition ==\n\nThere are at least five well-recognized ways to approach this subject: \n\n*Philosophers sometimes call it the \"[[science]] of [[morality]]\" , but generally emphasize its non-empirical character. \n*Theologians consider ethics a branch of [[theology]], especially in [[Judaism]], [[Buddhism]], [[Islam]], [[Roman Catholicism]] and some [[Christian_fundamentalism|Fundamentalist Protestant]] sects. \n*Ethics is inseparable from [[economics]] in some theories, notably [[Marxism]] and [[social ecology]], from [[feminism]], and from [[gender]] in [[Queer studies]]. These views are said to represent workers, women, and sexual outcasts who have historically been degraded by traditional ethics.\n*Professionals usually use or interpret \"ethics\" to refer to elements of professional practice that are part of [[dispute resolution]] or which have some great potential for: [[bodily harm]], [[urban planning]], [[medicine]], [[law]], [[politics]] and theories of [[civics]]. \n*A fifth way derives from theories of [[nonviolence]], [[pacifism]], [[anarchism]] ,and [[secession]] as a route to [[peace]].\n*Sometimes, ethics is simply regarded as the [[de-escalation]] and mediation of conflicts. \n\n=== The first social science === \n\nAssumptions about ethical underpinnings of human behaviour are reflected in every [[social science]], including: [[economics]] because of its role in the distribution of scarce resources, in [[political science]] because of its role in allocating [[power]], in [[sociology]] because of its roots in the dynamics of groups, in [[law]] because of its role in codifying ethical constructs like [[mercy]] and [[punishment]], in [[criminology]] because of its role in rewarding ethical behaviour and discouraging unethical behaviour, in [[psychology]] because of its role in defining, understanding, and treating unethical behaviour. \n\nHowever, hard science needs ethics too. It is also important in [[biology]] (as [[bioethics]]) and [[ecology]] (as [[environmental ethics]]). \n\nAs these fields become more complex, and deal with more situations, ethics, too, tends to become complex.\nBut Schopenhauer stated that the first ethical principle was extremely simple and convincing: \"Neminem laede; imo omnes, quantum potes, juva.\" (Do no harm to anyone, but give a helping hand to as many people as you can.)\n\n=== Ethics vs. politics vs. religion vs. practice ===\n\nMany questions in ethics are deeply concerned with the claiming of [[rights]], especially when [[authority]] is present. The potential to invoke authority and force of arms lies heavy over all ethical decisions in all but an [[anarchy]]: \n\nWhen balances between rights are considered, especially in public policy, ethics becomes [[politics]]. When religious concepts are considered to dominate over human conceptions of right and wrong, ethics are often presumed to derive from a [[moral code]] - usually divinely inspired or revealed. See Ethics in religion below. \n\nNon-philosophers may wish to review the article \'\'[[simple view of ethics and morals]]\'\', which deals with ethics in much simpler language. That article focuses on how people who \'\'make\'\' decisions see things, while this one focuses on how people who \'\'study\'\' decisions see things. The two are typically not the same, as much more [[doubt]] and deliberation is involved in coming to agreement about principles that are to apply for a long time, for a whole [[society]] or for mankind, and those who make decisions see things more simply.\n\n==Divisions of ethics==\n\nIn [[analytic philosophy]], ethics is traditionally divided into three fields: [[Metaethics]], [[Normative ethics]] (including [[value theory]] and the [[theory of conduct]]) and [[applied ethics]] - which is seen to be derived, top-down, from normative and thus meta-ethics.\n\n===Metaethics===\n\n[[Metaethics]] is the investigation of the nature of ethical statements. It involves such questions as: Are ethical claims truth-apt, i.e., capable of being true or false, or are they, for example, expressions of emotion? If they are truth-apt, are they ever true? If they are ever true, what is the nature of the facts that they express? And are they ever true absolutely, or always only relative to some individual, society, or culture? (See [[moral relativism]], [[cultural relativism]].) Metaethics is one of the most important fields in [[philosophy]].\n\nMetaethics studies the nature of ethical sentences and attitudes. This includes such questions as what \"good\" and \"right\" \'\'mean\'\', whether and how we \'\'know\'\' what is right and good, whether moral values are objective, and how ethical attitudes motivate us. Often this is derived from some list of moral absolutes, e.g. a religious [[moral code]], whether explicit or not. Some would view [[aesthetics]] as itself a form of meta-ethics.\n\nMetaethics also investigates where our ethical principles come from, and what they mean. Are they merely social inventions? Do they involve more than expressions of our individual emotions? Metaethical answers to these questions focus on the issues of universal truths, the will of God, the role of reason in ethical judgments, and the meaning of ethical terms themselves.\n\n===Normative ethics===\n\n[[Normative ethics]] bridges the gap between metaethics and applied ethics. It is the attempt to arrive at practical moral standards that tell us right from wrong, and how to live moral lives. This may involve articulating the good habits that we should acquire, the duties that we should follow, or the consequences of our behavior on others. \n\n*One branch of normative ethics is [[theory of conduct]]; this is the study of right and wrong, of obligation and permissions, of duty, of what is above and beyond the call of duty, and of what is so wrong as to be evil. Theories of conduct propose standards of [[morality]], or [[moral code]]s or rules. For example, the following would be the sort of rules that a theory of conduct would discuss (though different theories will differ on the merit of each of these particular rules): \"Do unto others as you would have them do unto you\"; \"The right action is the action that produces the greatest happiness for the greatest number\"; \"Stealing is wrong\". Theories of moral conduct can be distinguished from [[etiquette]] by their concern with finding guidelines for action that are not dependent entirely on social convention. For example, it may not be a breach of etiquette to fail to give money to help those in poverty, but it could still be a failure to act morally.\n\n*Another branch of normative ethics is [[theory of value]]; this looks at what things are deemed to be valuable. Suppose we have decided that certain things are intrinsically good, or are more valuable than other things that are also intrinsically good. Given this, the next big question is what would this imply about how we should live our lives? The theory of value also asks: What sorts of things are good? What sorts of situations are good? Is pleasure always good? Is it good for people to be equally well-off? Is it intrinsically good for beautiful objects to exist? Or: What does \"good\" mean? It may literally define \"good\" and \"bad\" for a community or society.\n\n===Applied ethics===\n\n[[Applied ethics]] applies normative ethics to specific controversial issues. Many of these ethical problems bear directly on public policy. For example, the following would be questions of applied ethics: \"Is getting an abortion ever moral?\"; \"Is euthanasia ever moral?\"; \"What are the ethical underpinnings of [[affirmative action]] policies?\"; \"Do animals have rights?\" \n\nWithout these questions there is no clear fulcrum on which to balance [[law]], [[politics]], and practice of [[arbitration]] - in fact no common assumptions of all participants - so the ability to formulate the questions are prior to rights balancing.\n\nBut not all questions studied in applied ethics concern public policy. For example: Is [[lying]] always wrong? If not, when is it permissible? The ability to make these ethical judgements is prior to any etiquette.\n\nThere are several sub-branches of applied ethics examining the ethical problems of different professions, such as business ethics, medical ethics, engineering ethics and legal ethics, while technology assessment and environmental assessment study the effects and implications of new technologies or projects on nature and society. \n\nEach branch to characterize common issues and problems that arise in the [[ethical code]]s of the professions, and define their common responsibility to the public, e.g. to preserve its natural capital, or to obey some social expectations of honest dealings and disclosure. \n\n*[[Abortion, legal and moral issues]]\n*[[Animal rights]]\n*[[Bioethics]]\n*[[Business ethics]]\n*[[Criminal justice]]\n*[[Environmental ethics]]\n*[[Feminism]]\n*[[Gay rights]]\n*[[Just war theory]] \n*[[Medical ethics]]\n*[[Utilitarian ethics]]\n*[[Utilitarian Bioethics]]\n\nEthics has been applied to [[economics]], [[politics]] and [[political science]], leading to several distinct and unrelated fields of applied ethics, including [[Business ethics]] and [[Marxism]].\n\nEthics has been applied to family structure, sexuality, and how society views the roles of individuals; leading to several distinct and unrelated fields of applied ethics, including [[feminism]].\n\nEthics has been applied to war, leading to the fields of [[pacifism]] and [[nonviolence]].\n\nEthics has been applied to analyze human use of Earth\'s limited resources. This has led to the study of [[environmental ethics]] and [[social ecology]]. A growing trend has been to combine the study of both ecology and economics to help provide a basis for sustainable decisions on environmental use. This has led to the theories of [[ecological footprint]] and [[bioregional autonomy]]. Political and social movements based on such ideas include [[eco-feminism]], [[eco-anarchism]], [[deep ecology]], the [[green movement]], and ideas about their possible integration into [[Gaia philosophy]].\n\nEthics has been applied to [[criminology]] leading to the field of [[criminal justice]].\n\nThere are several sub-branches of applied ethics examining the ethical problems of different professions, such as [[business ethics]], [[medical ethics]], [[engineering ethics]] and [[legal ethics]], while [[technology assessment]] and [[environmental assessment]] study the effects and implications of new technologies or projects on nature and society. \nEach branch characterizes common issues and problems that may arise, and define their common responsibility to the public, e.g. to preserve its natural capital, or to obey some social expectations of honest dealings and disclosure.\n\n===Ethics by cases===\n\nBy far the most common way to approach applied ethics is by resolving individual cases. This is, not coincidentally, also the way [[business]] and [[law]] tend to be taught. \'\'[[Casuistry]]\'\' is one such application of [[case-based reasoning]] to applied ethics. Almost all American states have tried to discourage dishonest practices by their public employees and elected officials by establishing an Ethics Commission for their state.\n\n\n[[Bernard Crick]] in [[1982]] offered a more socially-centered view, that [[politics]] was the only applied ethics, that it was how cases were really resolved, and that \"[[political virtues]]\" were in fact necessary in all matters where human morality and interests were destined to clash. This and other views of modern universals is dealt with below under \'\'Global Ethics\'\'.\n\nThe lines of distinction between metaethics, normative ethics, and applied ethics are often blurry. For example, the issue of [[abortion]] is an applied ethical topic since it involves a specific type of controversial behavior. But it also depends on more general normative principles, such as the right of self-rule and the right to life, which are litmus tests for determining the morality of that procedure. The issue also rests on metaethical issues such as, \"where do rights come from?\" and \"what kind of beings have rights?\"\n\n==Descriptive ethics==\n\nSome philosophers rely on [[descriptive ethics]] and choices made and unchallenged by a [[society]] or [[culture]] to derive categories, which typically vary by context. This leads to [[situational ethics]] and [[situated ethics]]. These philosophers often view [[aesthetics]] and [[etiquette]] and [[arbitration]] as more fundamental, percolating \'bottom up\' to imply, rather than explicitly state, theories of value or of conduct. In these views ethics is not derived from a top-down a priori \"philosophy\" (many would reject that word) but rather is strictly derived from observations of actual choices made in practice:\n\n* [[Ethical code]]s applied by various groups. Some consider aesthetics itself the basis of ethics - and a personal [[moral core]] developed through art and storytelling as very influential in one\'s later ethical choices.\n\n* Informal theories of [[etiquette]] which tend to be less rigorous and more situational. Some consider etiquette a simple negative ethics, i.e. where can one evade an uncomfortable truth without doing wrong? One notable advocate of this view is [[Judith Martin]] (\"Miss Manners\"). In this view, ethics is more a summary of common sense social decisions.\n\n* Practices in [[arbitration]] and [[law]], e.g. the claim by [[Rushworth Kidder]] that ethics itself is a matter of balancing \"right versus right\", i.e. putting priorities on two things that are both right, but which must be traded off carefully in each situation. This view many consider to have potential to reform ethics as a practice, but it is not as widely held as the \'aesthetic\' or \'common sense\' views listed above.\n\n* Observed choices made by ordinary people, without expert aid or advice, who [[vote]], [[buy]] and decide what is worth fighting about. This is a major concern of [[sociology]], [[political science]] and [[economics]].\n\nThose who embrace such descriptive approaches tend to reject overtly normative ones. There are exceptions, such as the movement to more [[moral purchasing]]. \n\n==The analytic view==\n\nThe descriptive view of ethics is modern and in many ways more empirical. But because the above are dealt with more deeply in their own articles, the rest of this article will focus on the formal academic categories, which are derived from classical [[Greek philosophy]], especially [[Aristotle]].\n\nFirst, we need to define an \'\'ethical sentence\'\', also called a \'\'normative statement\'\'. An ethical sentence is one that is used to make either a positive or a negative (moral) evaluation of something. Ethical sentences use words such as \"good,\" \"bad,\" \"right,\" \"wrong,\" \"moral,\" \"immoral,\" and so on. Here are some examples:\n\n* \"Sally is a good person.\" \n* \"People should not steal.\"\n* \"The [[O. J. Simpson|Simpson]] verdict was unjust.\"\n* \"Honesty is a virtue.\"\n* \"One ought not to break the law.\"\n\nIn contrast, a \'\'non\'\'-ethical sentence would be a sentence that does \'\'not\'\' serve to (morally) evaluate something. Examples would include:\n\n* \"Sally is a tall person.\"\n* \"Someone took the stereo out of my car.\"\n* \"Simpson was acquitted at his trial.\"\n* \"Many people are dishonest.\"\n* \"I dislike it when people break the law.\"\n\n==Is ethics futile?==\n\nThe whole assumption of the field of ethics is that consistent description, consistent deliberation, and consistent and [[fairness|fair]] application of authority is possible. However, the more case-based views seem to suggest that a great deal of judgement is required, and that for instance one could never train a [[robot]] to do ethics, as it requires [[empathy]] and [[wisdom]]. However, one might be able to teach an [[artificial intelligence]] with empathy and wisdom to do ethics.\n\nIs each case unique? Possibly. The view that ethics is innate and tied to a personal [[moral core]] or [[aesthetic]] is harder to relate to the formal categories above other than as a meta-ethics in itself. \n\nIt is considered by some ethicists to be just a variant of [[mysticism]] or [[narcissism]], permitting those who avow aesthetic choices as being \'above ethics\' to justify anything.\n\nHowever, the term \'\'ethics\'\' is actually derived from the ancient Greek \'\'ethos\'\', meaning \'\'[[moral character]]\'\'. \'\'Mores\'\', from which \'\'morality\'\' is derived, meant social rules or etiquette or inhibitions from the society. In modern times, these meanings are often somewhat reversed, with ethics being the external \"science\" and morals referring to one\'s inmost character or choices. But it is significant that the origins of the words reflect the tension between an inner-driven and an outer-driven view of what makes moral choices consistent.\n\n==Ethics in religion==\n\n\'\'See [[Ethics in religion]] and [[Ethics in the Bible]].\'\'\n\n==Ethics in medicine==\n\nOne of the major areas where ethics and ethicists practice is in the field of medicine. Example issues are [[euthanasia]], medical experiments, [[genetic]] modification of organisms and humans, [[vaccine trials]], [[triage]] and others.\n\n==Ethics in psychology==\n\nBy the [[1960s]] there was increased interest in [[moral reasoning]]. [[Psychology|Psychologists]] such as [[Lawrence Kohlberg]] and [[Carol Gilligan]] developed theories which are based on the idea that moral behaviour is made possible by moral reasoning. Their theories subdivided moral reasoning into so-called stages, which refer to the set of principles or methods that a person uses for ethical judgement. The first and most famous theory of this type was [[Kohlberg\'s stages of moral development|Kohlberg\'s theory of moral development.]]. \n\nAnother group of influential psychological theories with ethical implications is the [[humanistic psychology]] movement. One of the most famous humanistic theories is [[Abraham Maslow|Abraham Maslow\'s]] [[Maslow\'s hierarchy of needs|hierarchy of needs]]. Maslow argued that the highest human need is [[self-actualization]], which can be described as fulfilling one\'s potential, and trying to fix what is wrong in the world. [[Carl Rogers|Carl Rogers\'s]] work was based on similar assumptions. He thought that in order to be a \'fully functioning person\', one has to be creative and accept one\'s own feelings and needs. He also emphasized the value of self-actualization. A similar theory was proposed by [[Fritz Perls]], who assumed that taking responsibility of one\'s own life is an important value. \n\nA third group of psychological theories that have implications for the nature of ethics are based on [[evolutionary psychology]]. These theories are based on the assumption that the behaviour that ethics prescribe can sometimes be seen as an evolutionary adaptation. For instance, altruism towards members of one\'s own family promotes one\'s [[inclusive fitness]].\n\n==Ethics in politics==\n\nOften, such efforts take legal or political form before they are understood as works of [[normative ethics]]. The [[UN Declaration of Universal Human Rights]] of [[1948]] and the [[Global Green Charter]] of [[2001]] are two such examples. However, as [[war]] and the development of [[weapon technology]] continues, it seems clear that no non-violent means of dispute resolution is accepted by all.\n\nThe need to redefine and align politics away from ideology and towards dispute resolution was a motive for [[Bernard Crick]]\'s list of [[political virtues]].\n\n==Major doctrines of ethics==\n\nPhilosophers have developed a number of competing systems to explain how to choose what is best for both the individual and for society. No one system has gained universal assent. The major philosophical doctrines of ethics include:\n\n*[[Altruism]]\n*[[Divine command theory|Divine command ethics]]\n*[[Consequentialism]]\n*[[Virtue ethics]]\n*[[Social contract]] theory\n*[[Ethical fitnessism]]\n*[[Ethical skepticism]]\n*[[Ethical relativism]]\n*[[Ethical subjectivism]]\n*[[nihilism | Ethical nihilism]]\n*[[Ethical egoism]]\n*[[hedonism | Ethical hedonism]]\n*Non-hedonistic [[ethical egoism]]\n*[[Utilitarianism]]\n*[[Immanuel Kant]]\'s [[Deontology|Deontological ethics]]\n*[[Ayn Rand]]\'s [[Objectivist philosophy|Rational Self-Interest Ethics]]\n*The Utilitarian Kantian Principle (Cornman, Lehrer)\n*[[Universal prescriptivism]]\n\n==Related topics in philosophy==\n\n*[[Deontology]]\n*[[Meta-ethics]]\n*[[Morality]]\n*[[Goodness and value theory]]\n*[[Virtue ethics]]\n\n==References ==\n\n*Singer, P., Ed. (2001). A Companion To Ethics. Blackwell Companions to Philosophy. Malden, Massachusetts, Blackwell Publishers.\n\n\n\n\nSee the [[list of ethics topics]] for more specialized and applied topics.\n\nSee the [[list of ethicists]] for theorists who have contributed to the above.\n\n==External Links==\n\n* [http://www.galilean-library.org/int11.html An Introduction to Ethics] by Paul Newall, aimed at beginners.\n\n\n\n[[da:Etik]]\n[[de:Ethik]]\n[[es:Ética]]\n[[et:Eetika]]\n[[fr:Éthique]]\n[[fi:Etiikka]]\n[[he:פילוסופיה של המוסר]]\n[[ja:倫理]]\n[[nl:Ethiek]]\n[[pl:Etyka]]\n[[ru:Этика]]\n[[simple:Ethics]]\n[[sv:Etik]]\n[[tl:Etika]]\n[[zh:伦理学]]\n[[Category:Ethics]]\n[[Category:Social philosophy]]','',13,'Budhi','20041229235109','',0,0,0,1,0.292264414905,'20041229235109','79958770764890'); INSERT INTO cur VALUES (2084,0,'Bias_publikasi','\'\'\'Bias publikasi\'\'\', ogé disebut [[bias hasil positif]] (Ing. \'\'positive outcome bias\'\'), nyaéta kacondongan panalungtik pikeun mublikasikeun percobaan nu mibanda hasil positif (manggihan lumangsungna hiji hal), sarta dina sisi séjén teu mublikasikeun percobaan nu hasilna négatif (manggihan teu lumangsungna hiji hal). As such, this may distort [[meta-analysis]] of large numbers of studies. The problem is particularly significant when the research is sponsored by entities that may have a financial interest in achieving favourable results.\n\n[[Séptémber]] [[2004]], éditor sababaraha jurnal poko widang médis (kaasup [[New England Journal of Medicine]], [[The Lancet]], [[Annals of Internal Medicine]], jeung [[JAMA]]) ngabéwarakeun yén maranéhna moal deui mublikasikeun hasil panalungtikan nu dibobotohan ku maskapé farmasi iwal mun panalungtikanana geus didaptarkeun na basis data umum ti anggalna kénéh [http://www.smh.com.au/articles/2004/09/09/1094530773888.html]. Ku cara kieu, hasil négatif moal leungit kitu baé.\n\n==Tempo ogé== \n*[[selection bias|bias pamilihan]]\n*[[confirmation bias|bias konfirmasi]]\n*[[daptar bias kognitif]]\n\n==Tumbu kaluar==\n* \'\'[http://skepdic.com/posoutbias.html Skeptic\'s Dictionary: positive outcome bias]\'\'.\n\n[[Category:Bias kognitif]]','',3,'Kandar','20050215062350','',0,0,0,0,0.031178799086,'20050215062350','79949784937649'); INSERT INTO cur VALUES (2085,0,'Confirmation_bias','In [[statistical inference]], \'\'\'confirmation bias\'\'\' is a type of [[cognitive bias]] towards confirmation of the hypothesis under study. See also [[bias (statistics)]]. To compensate for this observed human tendency, the [[scientific method]] is constructed so that we must try to \'\'disprove\'\' our hypotheses. See [[falsifiability]].\n\nIn [[psychology]], confirmation bias is a phenomenon whereby, in a variety of settings, decision makers have been shown to notice more, assign more weight to, and actively seek out evidence that confirms their claims, and tend to ignore and not seek out evidence which might discount their claims. As such, it can be thought of as a form of [[selection bias]] in collecting evidence.\n\nIn one classic experiment, subjects were shown the [[hypothesis]] that \"If a card has a vowel on one side, it must have an even number on the other side\" and four large cards, that looked something like:\n\n{| border=2 cellpadding=6 cellspacing=6\n| E\n| 4\n|-\n| 7\n| K\n|}\n\nSubjects were then asked which two cards they would turn over to test the rule.\n\nAlmost all experimental subjects did not choose the correct two cards, which would be E (via [[modus ponens]]) and 7 (via [[modus tollens]]). Most chose E and 4, committing the [[logical fallacy]] of [[affirming the consequent]], and choosing a test that might confirm but which could never falsify the hypothesis.\n\nIt should be noted, however, that studies that used more concrete concepts showed very different results. In one study, students had no trouble with a version of the cards experiment in choosing \"Beer\" and \"16\" testing the hypothesis that \"People who drink beer must be at least 21 years old.\"\n\nSome have argued that confirmation bias may be the cause of self-perpetuating and [[self-fulfilling prophecy|self-fulfilling]] social beliefs.\n\nIn addition, many legal and political systems depend on adversarial relations in order to achieve just decisions despite the biases of the parties. In these systems it is assumed that it is beyond the ability of a single human being to avoid confirmation bias, and hence the systems are in place so that different biases work against each other.\n\n[[Decision making|Decision makers]] should consider opposing views and try to think about why they might be wrong in order to reduce [[overconfidence effect]]s.\n\nThis bias may occur at least partially because negatives are inherently more difficult to process mentally than positives.\n\nMore recent studies, however, have shown that while confirmation bias tends to be present as an initial condition, the repeated presentation of disconfirmatory data induces changes in theoretical thinking. In other words, the initial disconfirmatory data is regarded as the result of error, or some other externally attributed factor; it is only after similar results or data are repeatedly obtained that a change in causal reasoning strategies occurs. \n\n\'\'See also:\'\' [[disconfirmation bias]], [[expectancy effect]], [[list of cognitive biases]].\n\n==References==\n\n* Wason, P. C. (1966). Reasoning. In B. M. Foss (Ed.), \'\'New horizons in psychology I\'\', 135-151. Harmondsworth, UK: Penguin.\n* Wason, P. C. (1968). Reasoning about a rule. \'\'Quarterly Journal of Experimental Psychology\'\', 20, 273-281.\n* Mynatt, C. R., Doherty, M. E., & Tweney, R. D. (1977). Confirmation bias in a simulated research environment: an experimental study of scientific inference. \'\'Quarterly Journal of Experimental Psychology\'\', 29, 85-95.\n* Griggs, R. A. & Cox, J. R. (1982). The elusive thematic materials effect in the Wason selection task. \'\'British Journal of Psychology\'\', 73, 407-420.\n* Fugelsang, J., Stein, C., Green, A., & Dunbar, K. (2004). Theory and data interactions of the scientific mind: Evidence from the molecular and the cognitive laboratory. \'\'Canadian Journal of Experimental Psychology\'\', 58, 132-141.\n\n==External links==\n\n*[http://skepdic.com/confirmbias.html Skeptic\'s Dictionary: confirmation bias]\n*[http://www.devpsy.org/teaching/method/confirmation_bias.html Teaching about confirmation bias]\n\n[[Category:cognitive biases]]','',13,'Budhi','20041229235346','',0,0,0,1,0.00920264463,'20050303214455','79958770764653'); INSERT INTO cur VALUES (2086,0,'Computational_physics','\'\'\'Computational physics\'\'\' is the study and implementation of numerical [[algorithm]]s in order to solve problems in [[physics]] for which a quantitative theory already exists.\n\nPhysicists often have a very precise mathematical theory describing how a system will behave. Unfortunately, it is often the case that solving the theory\'s equations in order to produce a useful prediction is a computationally difficult problem. This is especially true with [[quantum mechanics]], where only a handful of simple models can be solved exactly. Even apparently simple problems, such as calculating the [[wavefunction]] of an electron orbiting an atom in a strong [[electric field]], may require great effort to formulate a practical algorithm.\n\nIn addition, the computational cost of solving quantum mechanical problems is generally [[exponential function|exponential]] in the size of the system (see [[computational complexity theory]]). \n\nMany other more general numerical problems fall loosely under the domain of computational physics, although they could easily be considered pure [[mathematics]] or part of any number of applied areas. For example:\n\n* Solving [[differential equation]]s\n* Evaluating [[integral]]s\n* Stochastic methods, specifically the [[Monte Carlo Method]]\n* Specialised [[partial differential equation]] methods, for example the [[finite difference]] method and the [[finite element method]]\n* The [[matrix eigenvalue problem]] – i.e. the problem of finding [[eigenvalue]]s of very large matrices.\n* The [[pseudo-spectral method]]\n\nSee also [[list of publications in physics#Computational physics|important publications in computational physics]]\n\n[[Category:Computational physics|*]]\n\n[[de:Computational physics]]\n[[ja:計算物理学]]','',13,'Budhi','20041230005609','',0,0,0,1,0.170160979184,'20050303214455','79958769994390'); INSERT INTO cur VALUES (2087,0,'Quantum_chromodynamics','\'\'\'Quantum chromodynamics\'\'\' (QCD) is the [[physics|physical]] theory describing one of the [[fundamental force]]s, the [[strong interaction]]. Because of its special property called [[asymptotic freedom]]. It was first proposed in the early [[1970s]] by [[David Politzer]] and by [[Frank Wilczek]] and [[David Gross]] as a theory to understand the structure of [[proton]]s, [[neutron]]s, and similar particles. It uses [[quantum field theory]] to describe the interaction of [[quark]]s and [[gluon]]s. For their work in quantum chromodynamics, Gross, Wilczek, and Politzer were awarded the 2004 Nobel Prize in Physics.\n\nAccording to this theory, the character of the strong interaction is determined by a special symmetry between the [[color charge]]s of the [[quark]]s. This symmetry is known as the [[Special unitary group|SU(3)]] [[Gauge theory|gauge group]] and the [[quark]]s transform under this group as [[Special unitary group|SU(3)]] [[Representations of Lie groups/algebras|triplet]] [[Dirac spinor|Dirac]] [[fermion]]ic [[Field (physics)|field]]s. Although the [[perturbative expansion]]s were important for development of QCD, QCD also predicts many [[perturbation theory (quantum mechanics)|non-perturbative]] effects such as [[confinement]], [[fermion condensate]]s and [[instanton]]s.\n\nQuantum chromodynamics is an important part of the [[Standard Model]] of [[particle physics]]. The name \"chromodynamics\" comes from the Greek word \"chromos\" (color). This name is relevant because the charge of the quarks is usually referred to as \"[[color charge|color]]\" although it is unrelated to the visual perception of color.\n\nA particular approach to QCD, namely the [[QCD lattice model|lattice models]], has enabled the researchers to obtain some theoretical results and quantities that were previously uncalculable.\n\nQCD has a [[confining phase]] and a [[deconfining phase]].\n\n==See also==\n*[[Gauge theory]]\n*[[Strong interaction]]\n*[[QCD lattice model]]\n*[[Fermion condensate]]\n*[[Quantum field theory]]\n\n[[de:Quantenchromodynamik]]\n[[es:Cromodinámica cuántica]]\n[[it:Cromodinamica quantistica]]\n[[ja:量子色力学]]\n[[pl:Chromodynamika kwantowa]]\n[[ru:Квантовая хромодинамика]]\n\n[[Category:Quantum field theory]]','',13,'Budhi','20041230005716','',0,0,0,1,0.090621785345,'20050303214455','79958769994283'); INSERT INTO cur VALUES (2088,0,'Heat_shield','In [[aeronautics]], a \'\'\'heat shield\'\'\' is a protective layer on a [[spacecraft]] or [[ballistic missile]] that is designed to protect it from high temperatures, usually those that result from [[aerobraking]] during entry into a [[planet]]\'s [[celestial body atmosphere|atmosphere]]. It is also a design consideration for high-velocity [[aircraft]].\n\n==Shape==\n[[H. Julian Allen]] of the [[National Advisory Committee for Aeronautics]] discovered in [[1952]] that a blunt \"dish shape\" makes the most effective heat shield. The shape increases [[drag (physics)|drag]] and creates a [[shock wave]] ahead of the spacecraft that causes [[shock heating]] of the atmosphere, but deflects the heat away from the spacecraft. However the atmosphere between the heat shield and the shock wave is under very high [[pressure]] turning it from a [[gas]] to a very hot [[plasma]]. The heat from the plasma must be dissipated by the material of the heat shield.\n\n==Ablative Heat Shields==\nThe simplest and cheapest type of heat shield is the ablative heat shield, which dissipates heat from the plasma by allowing its outer layers to vaporize.\n\nAll of the early spacecraft with the exception of the early [[Mercury program|Mercury capsules]] used ablative technologies to assist with the transition from high orbital speeds down to aerodynamic regimes where a spacecraft can be flown or [[parachute]]d to safety.\n\nSuch heat shields are used on virtually all expendable spacecraft and on many ballistic missiles, since it doesn\'t matter whether they can withstand a second reentry.\n\n[[Image:Shuttle_heat_shield.jpg|thumb|200px|Astronaut Andrew S. W. Thomas takes a close look at the heat shield underneath the Space Shuttle Atlantis in the Orbiter Processing Facility at Kennedy Space Center (KSC).]]\n==Reusable Heat Shields==\nWhen the reusable [[Space Shuttle]] system was designed, it was decided that a non-reusable heat shield would not be an efficient approach. Instead the Space Shuttle\'s underside was coated with thousands of [[ceramic]] ([[HRSI]]-based) tiles that were intended to be able to survive multiple reentries with only minor repairs between missions. However, the original design proved to be somewhat less robust than intended; the Shuttle suffered from frequent lost and damaged tiles, and ultimately the [[Space Shuttle Columbia]] was [[Space Shuttle Columbia disaster|destroyed]] with all hands when a piece of insulating [[foam]] from its external fuel tank fell off and damaged the heat shield on its left wing.\n\n==Passive Cooling==\nIn some ballistic missiles and the [[orbit|sub-orbital]] [[Mercury program|Mercury spacecraft]], [[heat sink]]s were used to dissipate the plasma heat. However the technique required a considerable quantity of metal material, adding greatly to the [[mass]]. Consequently ablative or reusable shields are now far more common.\n\nSome high-velocity [[aircraft]], such as the [[SR-71 Blackbird]] and [[Concorde]], have to deal with heating similar to that suffered by spacecraft but with lower intensity. [[Shockwave]]s can attach to the pointed nose and heat the aircraft through [[wave drag]]. Generally heat is conducted through the [[aluminium]] or [[titanium]] [[alloy]], or occasionally [[stainless steel]] skins. In the case of Concorde the nose is permitted to reach a maximum operating [[temperature]] of 127 degrees [[Celsius|C]], typically 180 degrees warmer than the external air.\n\n==Active Cooling==\nVarious advanced reusable spacecraft and [[hypersonic]] aircraft designs have been proposed recently that employ heat shields made from temperature-resistant [[metal]] [[alloy]]s, some of them including active cooling systems in which water or cryogenic fuel is circulated over or through them.\n\n==Temperatures==\nThe most violent reentry temperatures (14,000 degrees [[Celsius|C]]) successfully survived by a spacecraft were those endured by the [[Jupiter (planet)|Jupiter]] atmospheric probe carried by the [[Galileo spacecraft]], which entered the giant planet\'s atmosphere at 106,000 miles per hour (170,700 km per hour). The heat shield, made from carbon-phenolic, made up around 50% of the probe\'s [[mass]] prior to entry.\n\n==See Also==\n* [[Conservation of energy]] for details of the conversion of [[kinetic energy]] into [[heat|heat energy]].\n\n[[Category:Spacecraft components]]\n\n[[de:Hitzeschild]]\n[[eo:Termika ŝildo]]\n[[nl:Hitteschild]]','',13,'Budhi','20041230005803','',0,0,0,1,0.285531653242,'20050303214455','79958769994196'); INSERT INTO cur VALUES (2089,0,'Simulation','\'\'\'Simulasi\'\'\' nyaeta tironan tina sababaraha alat atawa tina kaayaan nu sabenerna. Percobaan simulasi dipake keur ngagambarkeun kaayaan nu penting tina paripolah [[system]] sacara fisik atawa abstrak ku paripolah sistem sejenna.\n\nSimulasi dipake dina sababaraha hal, kaasup [[model (abstract)|pa-model-an]] sistim alami, sarta sistim manusa keur mikanyaho leuwih teleb kana sistim operasina; sarta simulasi dina [[technology|teknologi]] sarta [[safety engineering|rekayasa kaamanan]] numana hasilna bakal dipake keur nguji hal-hal nu pakait dina kaayaan nu sabenerna. Simulasi, make hiji \'\'simulator\'\' atawa percobaan sejenna nu dijieun dina kaayaan fiktif ahirna bisa nembongkeun efek nu sabenerna tina sababaraha kaayaan nu mungkin.\n\n==Physical and interactive simulation ==\n\n\'\'Physical simulation\'\' refers to simulation in which physical objects are substituted for the real thing, these physical objects are often chosen because they are smaller or cheaper, than the actual object or system.\n\n\'\'Interactive simulation\'\', which is a special kind of physical simulation, and often referred to as \'\'human in the loop\'\' simulations, are physical simulations that include humans, such as the model used in a flight simulator.\n\n===Simulation in training===\n\nSimulation is often used in the [[training]] of civilian and military personnel. This usually occurs when it is prohibitively expensive or simply too dangerous to allow trainees to use the real equipment in the real world. In such situations they will spend time learning valuable lessons in a \"safe\" virtual environment. Often the convenience is to permit mistakes during training for a safety-critical system.\n\nTraining simulations typically come in one of three categories:\n\n* \"live\" simulation (where real people use simulated (or \"dummy\") equipment in the real world);\n* \"virtual\" simulation (where real people use simulated equipment in a simulated world (or \"virtual environment\")), or\n* \"constructive\" simulation (where simulated people use simulated equipment in a simulated environment). Constructive simulation is often referred to as \"wargaming\" since it bears some resemblance to table-top war games in which players command armies of soldiers and equipment which move around a board.\n\n===Flight simulators===\n\n\'\'Main article:\'\' [[Flight simulator]]\n\nA flight simulator is used to train pilots on the ground. It permits a pilot to crash his simulated \"aircraft\" without being hurt. Flight simulators are often used to train pilots to operate aircraft in extremely hazardous situations, such as landings with no engines, or complete electrical or hydraulic failures. The simulator is normally cheaper to operate than a real [[trainer]] aircraft.\n\n===Engineering simulation===\n\nSimulation is an important feature when engineering systems. For example in [[electrical engineering]], [[delay]] lines may be used to simulate [[propagation]] delay and [[phase shift]] caused by an actual [[transmission line]]. Similarly, [[dummy load]]s may be used to simulate [[impedance]] without simulating propagation, and is used in situations where propagation is unwanted. A simulator may imitate only a few of the operations and functions of the unit it simulates. \'\'Contrast with\'\': [[emulator|emulate]].\n\n\'\'Source:\'\' [[Federal Standard 1037C]]\n\n==Computer simulation==\n\n\'\'Main article:\'\' [[Computer simulation]]
    \n\'\'Related article:\'\' [[Model (abstract)|Model]]\n\nComputer simulation, has become a useful part of [[model]]ing many natural systems in [[physics]], [[chemistry]] and [[biology]], and human systems in [[economics]] and [[social science]] (the [[computational sociology]]) as well as in [[engineering]] to gain insight into the operation of those systems. In such simulations the [[model]] behaviour will change according to a set of initial parameters such as a meteorological model.\nComputer simulations are often considered \'\'human out of the loop\'\' simulations.\n\nTraditionally, the formal modeling of systems has been via a [[mathematical model]], which attempts to find [[analytical solution]]s to problems which enables the prediction of the behaviour of the system from a set of parameters and initial conditions. Computer simulation is often used an adjunct to, or substitution for, modeling systems for which simple [[closed-form solution|closed form analytic solutions]] are not possible. There are many different types of computer simulation, the common feature they all share is the attempt to generate a sample of representative scenarios for a model in which a complete enumeration of all possible states of the model would be prohibitive or impossible.\n\nIt is increasingly common to hear simulations of many kinds referred to as \"synthetic environments\". This label has been adopted to broaden the definition of \"simulation\" to encompass virtually any computer-based representation.\n\n==Simulation in computer science==\n\nIn [[computer science]], simulation has an even more a specialized meaning: [[Alan Turing]] uses the term \"simulation\" to refer to what happens when a digital computer runs a state transition table (runs a program) that describes the state transitions, inputs and outputs of a subject discrete-state machine. The computer simulates the subject machine.\n\nIn [[computer programming]], a simulator is often used to execute a program that has to run on some inconvenient type of computer. For example, simulators are usually used to debug a [[microprogram]]. Since the operation of the computer is simulated, all of the information about the computer\'s operation is directly available to the programmer, and the speed and execution of the simulation can be varied at will.\n\nSimulators may also be used to interpret [[fault tree]]s, or test [[VLSI]] logic designs before they are constructed. Many video games are also simulators, implemented inexpensively. These are sometimes called \"[[sim game]]s\".\n\nIn [[theoretical computer science]] the term \'\'[[simulation preorder|simulation]]\'\' represents a relation between [[state transition system]]s. This is useful in the study of [[operational semantics]].\n\n==References==\n* [[Roger D. Smith]]: [http://www.modelbenders.com/encyclopedia/encyclopedia.html Simulation Article], Encyclopedia of Computer Science, Nature Publishing Group, ISBN 0-333-77879-0.\n* [[Roger D. Smith]]: [http://www.modelbenders.com/Bookshop/techpapers.html \"Simulation: The Engine Behind the Virtual World\"], eMatter, December, 1999.\n\n== See also ==\n*[[emulator]]\n*[[modeling]]\n*[[simulated reality]]\n* [http://www.modelbenders.com/mastersim.html Mastering Simulation: Online Course]\n* [http://www.sisostds.org/ Simulation Interoperability Standards Organization]\n* [https://www.dmso.mil/ United States Defense Modeling and Simulation Office]\n\n[[da:Simulere]]\n[[de:Simulation]]\n[[es:Simulación]]\n[[fr:Simulation]]\n[[it:Simulazione]]\n[[nl:Simulatie]]\n[[ja:シミュレーション]]\n[[fi:Simulointi]]\n\n[[Category:Operations research]]','',13,'Budhi','20050218012042','',0,0,0,0,0.148701807962,'20050218012042','79949781987957'); INSERT INTO cur VALUES (2090,0,'Cox\'s_theorem','\'\'\'Teorema Cox\'\'\', ngaran teorema nu dipake keur ngahargaan ka ahli fisika [[Richard Threlkeld Cox]], nyaeta turunan hukum teori [[kamungkinan|probabiliti]] tina sababaraha susunan postulat penting. Turunan ieu mere alesan ku sabab kitu disebut intepretasi probabiliti \"logika\". Salaku hukum probabiliti teorema Cox bisa dipake keur sababaraha dalil, probabiliti logika ngarupakeun salah sahiji tina [[Bayesian probability]]. Bentuk sejen Bayesianism, saperti [[subjective probability|interpretasi subjektif]], dijelaskeun dina kaca sejen.\n\n==Cox\'s assumptions==\n\nCox wanted his system to satisfy the following desiderata\n\n#Divisibility and comparability - The plausibility of a statement is a real number and is dependent on information we have related to the statement.\n#Common sense - Plausibilities should vary sensibly with the assessment of plausibilities in the model.\n#Consistency - If the plausibility of a statement can be derived in two ways, the two results must be equal.\n\nThe postulates as stated here are taken from Arnborg and Sjödin (1999).\n\"Common sense\" includes consistency with Aristotelian [[logic]] when\nstatements are completely plausible or implausible.\n\nThe postulates as originally stated by Cox were not mathematically\nrigorous (although better than the informal description above), e.g.,\nas noted by Halpern (1999a, 1999b). However it appears to be possible\nto augment them with various mathematical assumptions made either\nimplicitly or explicitly by Cox to produce a valid proof.\n\nCox\'s axioms and functional equations are:\n\n*The plausibility of a proposition determines the plausibility of the proposition\'s negation; either decreases as the other increases. Because \"a double negative is an affirmative\", this becomes a functional equation\n\n::f(f(x))=x,\n\n:saying that the function \'\'f\'\' that maps the probability of a proposition to the probability of the proposition\'s negation is an involution, i.e., it is its own inverse.\n\n*The plausibility of the conjunction [\'\'A\'\' & \'\'B\'\'] of two propositions \'\'A\'\', \'\'B\'\', depends only on the plausibility of \'\'B\'\' and that of \'\'A\'\' \'\'\'\'\'given\'\'\'\'\' that \'\'B\'\' is true. (From this Cox eventually infers that multiplication of probabilities is associative, and then that it may as well be ordinary multiplication of real numbers.) Because of the associative nature of the \"and\" operation in propositional logic, this becomes a functional equation saying that the function \'\'g\'\' such that\n\n::P(A\\ \\mbox{and}\\ B)=g(P(A),P(B|A))\n\n:is an [[associativity|associative]] binary operation. All strictly increasing associative binary operations on the real numbers are isomorphic to multiplication of numbers in the interval [0, 1]. This function therefore may be taken to be multiplication.\n\n*Suppose [\'\'A\'\' & \'\'B\'\'] is equivalent to [\'\'C\'\' & \'\'D\'\']. If we take acquire new information \'\'A\'\' and then acquire further new information \'\'B\'\', and update all probabilities each time, the updated probabilities will be the same as if we had first acquired new information \'\'C\'\' and then acquired further new information \'\'D\'\'. In view of the fact that multiplication of probabilities can be taken to be ordinary multiplication of real numbers, this becomes a [[functional equation]]\n\n::y\\,f\\left({f(z) \\over y}\\right)=z\\,f\\left({f(y) \\over z}\\right)\n\n:where \'\'f\'\' is as above.\n\nCox\'s theorem implies that any plausibility model that meets the\npostulates is equivalent to the subjective probability model, i.e.,\ncan be converted to the probability model by rescaling.\n\n==Implications of Cox\'s postulates==\n\nThe laws of probability derivable from these postulates are the following (Jaynes, 2003). Here \'\'w\'\'(\'\'A\'\'|\'\'B\'\') is the \"plausibility\" of the proposition \'\'A\'\' given \'\'B\'\', and \'\'m\'\' is some positive number.\n\n# Certainty is represented by \'\'w\'\'(\'\'A\'\'|\'\'B\'\') = 1.\n# \'\'w\'\'\'\'m\'\'(\'\'A\'\'|\'\'B\'\') + \'\'w\'\'\'\'m\'\'(\'\'A\'\'\'\'C\'\'|\'\'B\'\') = 1\n# \'\'w\'\'(\'\'A\'\', \'\'B\'\'|\'\'C\'\') = \'\'w\'\'(\'\'A\'\'|\'\'C\'\') \'\'w\'\'(\'\'B\'\'|\'\'A\'\', \'\'C\'\') = \'\'w\'\'(\'\'B\'\'|\'\'C\'\') \'\'w\'\'(\'\'A\'\'|\'\'B\'\', \'\'C\'\')\n\nIt is important to note that the postulates imply only these general properties. These are equivalent to the usual laws of probability assuming some conventions, namely that the scale of measurement is from zero to one, and the plausibility function, conventionally denoted \'\'P\'\' or Pr, is equal to \'\'w\'\'\'\'m\'\'. (We could have equivalently chosen to measure probabilities from one to infinity, with infinity representing certain falsehood.) With these conventions, we obtain the laws of probability in a more familiar form:\n\n# Certain truth is represented by Pr(\'\'A\'\'|\'\'B\'\') = 1, and certain falsehood by Pr(\'\'A\'\'|\'\'B\'\') = 0.\n# Pr(\'\'A\'\'|\'\'B\'\') + Pr(\'\'A\'\'\'\'C\'\'|\'\'B\'\') = 1\n# Pr(\'\'A\'\', \'\'B\'\'|\'\'C\'\') = Pr(\'\'A\'\'|\'\'C\'\') Pr(\'\'B\'\'|\'\'A\'\', \'\'C\'\') = Pr(\'\'B\'\'|\'\'C\'\') Pr(\'\'A\'\'|\'\'B\'\', \'\'C\'\')\n\nRule 2 is a rule for negation, and rule 3 is a rule for conjunction. Given that any proposition containing conjunction, disjunction, and negation can be equivalently rephrased using conjunction and negation alone (the [[conjunctive normal form]]), we can now handle any compound proposition.\n\nThe laws thus derived yield [[measure|finite additivity]] of probability, but not [[measure|countable additivity]]. The [[Probability theory|measure-theoretic formulation]] of Kolmogorov assumes that a probability measure is countably additive. This slightly stronger condition is necessary for the proof of certain theorems, however, it is not clear what difference countable additivity makes in practice.\n\n\n==Interpretation and further discussion==\n\nCox\'s theorem has come to be used as one of the justifications for the\nuse of Bayesian probability theory. For example, in Jaynes (2003) it is\ndiscussed in detail in chapters 1 and 2 and is a cornerstone for the\nrest of the book. Probability is interpreted as a formal system of\n[[logic]], the natural extension of Aristotelian logic (in which every\nstatement is either true or false) into the realm of reasoning in the\npresence of uncertainty.\n\nIt has been debated to what degree the theorem excludes alternative\nmodels for reasoning about uncertainty. For example, if certain\n\"unintuitive\" mathematical assumptions were dropped then alternatives\ncould be devised, e.g., an example provided by Halpern (1999a).\nHowever Arnborg and Sjödin (1999, 2000a, 2000b) suggest additional\n\"common sense\" postulates, which would allow the assumptions to be\nrelaxed in some cases while still ruling out the Halpern example.\n\nThe original formulation of Cox\'s theorem is in Cox (1946), which is extended with additional results and more discussion in Cox (1961). [[Edwin Jaynes|Jaynes]] (2003) cites Abel (1826) as first known instance of the associativity functional equation which is used in the proof of the theorem. Aczél (1966) refers to the \"associativity equation\" and lists 98 references to works that discuss it or use it, and gives a proof that doesn\'t require differentiability (pages 256-267).\n\n\n==References and external links==\n\n# [[Niels Henrik Abel]] \"Untersuchung der Functionen zweier unabhängig veränderlichen Gröszen x und y, wie f(x, y), welche die Eigenschaft haben, dasz f[z, f(x,y)] eine symmetrische Function von z, x und y ist.\", \'\'Jour. Reine u. angew. Math.\'\' (Crelle\'s Jour.), 1, 11-15, (1826). \n# [[R. T. Cox]], \"Probability, Frequency, and Reasonable Expectation,\" \'\'Am. Jour. Phys.,\'\' 14, 1-13, (1946).\n# [[R. T. Cox]], \'\'The Algebra of Probable Inference,\'\' Johns Hopkins University Press, Baltimore, MD, (1961).\n# [[Janos Aczél]], \'\'Lectures on Functional Equations and their Applications,\'\' Academic Press, New York, (1966).\n# [[Terrence L. Fine]], \'\'Theories of Probability; An examination of foundations,\'\' Academic Press, New York, (1973).\n# [[Edwin Thompson Jaynes]], \'\'Probability Theory: The Logic of Science,\'\' Cambridge University Press (2003). -- preprint version (1996) at http://omega.albany.edu:8008/JaynesBook.html; Chapters 1 to 3 of published version at http://bayes.wustl.edu/etj/prob/book.pdf\n# Joseph Y. Halpern, \"A counterexample to theorems of Cox and Fine,\" \'\'Journal of AI research,\'\' 10, 67-85 (1999) -- http://www.cs.washington.edu/research/jair/abstracts/halpern99a.html\n# Joseph Y. Halpern, \"Technical Addendum, Cox\'s theorem Revisited,\" \'\'Journal of AI research,\'\' 11, 429-435 (1999) -- http://www.cs.washington.edu/research/jair/abstracts/halpern99b.html\n# Stefan Arnborg and Gunnar Sjödin, \'\'On the foundations of Bayesianism,\'\' Preprint: Nada, KTH (1999) -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/06arnborg.ps -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/06arnborg.pdf\n# Stefan Arnborg and Gunnar Sjödin, \'\'A note on the foundations of Bayesianism,\'\' Preprint: Nada, KTH (2000a) -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/fobshle.ps -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/fobshle.pdf\n# Stefan Arnborg and Gunnar Sjödin, \"Bayes rules in finite models,\" in \'\'European Conference on Artificial Intelligence,\'\' Berlin, (2000b) -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/fobc1.ps -- ftp://ftp.nada.kth.se/pub/documents/Theory/Stefan-Arnborg/fobc1.pdf\n# Michael Hardy, in \'\'[http://www.sciencedirect.com/science/journal/01968858 Advances in Applied Mathematics]\'\' August 2002, pages 243-292 (or [http://arxiv.org/abs/math.PR/0203249 preprint]) \"I assert there that I think Cox\'s assumptions are too strong, although I don\'t really say why. I do say what I would replace them with.\" (The quote is from a Wikipedia discussion page, not from the article.)','',13,'Budhi','20050101215835','',0,0,1,0,0.097395460824,'20050101215835','79949898784164'); INSERT INTO cur VALUES (2091,0,'Ayatrohaédi','\'\'\'Ayatrohaédi\'\'\' dibabarkeun di [[Jatiwangi]], [[Majalengka]], [[5 Désémber]] [[1939]], jadi mahasiswa Fakultas Sastra taun [[1959]] Jurusan Ilmu Purbakala jeung Sejarah Kuna Indonesia (ayeuna [[Arkéologi]]). Sanggeus lulus taun [[1964]], Ayatrohaédi damel di [[Lembaga Purbakala dan Peninggalan Nasional]] di [[Mojokerto]]. Kungsi ngajar di Fakultas Sastra [[Universitas Pajajaran]] [[Bandung]] salila lima taun, salajengna taun [[1972]] balik deui ka Fakultas Sastra [[Universitas Indonesia|UI]]. Taun [[1978]] dileler gelar doktor ti UI kalawan disertasi nu judulna \'\'Bahasa Sunda di Daerah Cirebon: Sebuah Kajian Lokabasa\'\'. Numutkeun promotorna, Prof. Dr. [[Amran Halim]], disertasi ieu ngarupakeun disertasi munggaran ngeunaan dialéktologi di [[Asia Tenggara]].\n\nAyatrohaédi pernah ngajabat salaku Ketua Jurusan Arkéologi ([[1983]]-[[1987]]), Pembantu Dékan Bidang Akademik ([[1999]]-[[2000]]), Pembantu Réktor [[Institut Kesenian Jakarta]] (IKJ) salila lima tahun ([[1989]]-[[1994]]). Ayatrohaédi ogé loba aub dina kagiatan widang kabasaan, kasusastran, kasajarahan, kabudayaan, jeung kapurbakalaan.\n\nAyatrohaédi mimiti nulis karya sastra ([[sajak]], [[prosa]]) dina [[basa Sunda]] taun [[1955]] sarta [[basa Indonésia]] taun [[1956]]. Nepi ka ayeuna karyana nu geus medal di antarana \'\'Hujan Munggaran\'\' ([[1960]]), \'\'Kabogoh Téré\'\' ([[1967]]), jeung \'\'Pamapag\'\' ([[1972]]). Karyana dina basa Indonesia di antarana \'\'Panji Segala Raja\'\' ([[1974]]), \'\'Pabila dan di mana\'\' ([[1976]]), \'\'Senandung Ombak\'\' (tarjamahan, [[1976]]), \'\'Kacamata Sang Singa\'\' (tarjamahan, [[1977]]). Karya non-fiksina kayaning \'\'Bahasa Sunda di Daerah Cirebon: Sebuah Kajian Lokabasa\'\' (disertasi 1978, medal taun [[1985]]), \'\'Dialektologi: Sebuah Pengantar\'\' ([[1979]], [[1981]]), \'\'Tatabahasa Sunda\'\' (tarjamah karya [[Daéng Kanduruan Ardiwinata|D. K. Ardiwinata]], [[1985]]), \'\'Tatabahasa dan Ungkapan Bahasa Sunda\'\' (tarjamah karya J. Kats jeung R. Suriadiraja, [[1986]]).\n\n\n{{pondok}}\n\n[[id:Ayatrohaedi]]','',3,'Kandar','20041230035553','',0,0,0,1,0.622005226168,'20050303214455','79958769964446'); INSERT INTO cur VALUES (2092,2,'Hégésippe_Cormier/monobook.css','@import url(http://fr.wikipedia.org/w/index.php?title=Utilisateur:H%C3%A9g%C3%A9sippe_Cormier/monobook.css&action=raw&ctype=text/css);','',31,'Hégésippe Cormier','20041230234751','',0,0,1,1,0.048847985204,'20050303214455','79958769765248'); INSERT INTO cur VALUES (2093,2,'Hégésippe_Cormier','[[fr:Utilisateur:Hégésippe Cormier]]','fr:',31,'Hégésippe Cormier','20041230235008','',0,0,1,1,0.380126929732,'20050303214455','79958769764991'); INSERT INTO cur VALUES (2094,3,'Hégésippe_Cormier','[[fr:Discussion Utilisateur:Hégésippe Cormier]] (also English spoken)','fr:',31,'Hégésippe Cormier','20041230235122','',0,0,1,1,0.461971157014,'20050112020603','79958769764877'); INSERT INTO cur VALUES (2096,0,'26_Désémber','==Kajadian==\n*2004: [[Lini]] [[lini téktonik|téktonik]] 9.0 skala [[Richter]] di kuloneun [[Sumatra]] ngakibatkeun [[gelombang tsunami]] nu nyaahan wewengkon (utamana basisir) [[Acéh]] jeung [[Sumatra Kalér]], [[Muangtai]], [[Malaysia]], [[Srilangka]], [[India]], sarta basisir wétan [[Afrika]]. Data samentara nunjukkeun yén korban nu perlaya alatan kajadian ieu nepi ka leuwih ti 150 réwu urang nu lolobana, 80-an réwu, ti wewengkon Acéh).\n\n[[id:26 Desember]]','',3,'Kandar','20050103034437','',0,0,0,0,0.150426112729,'20050103034437','79949896965562'); INSERT INTO cur VALUES (2097,0,'Komputer','[[image:computer.tower.750pix.jpg|thumb|right|200px|Sarupaning [[Bungkus komputer|munara]] [[komputer pribadi]].]]\n\n\'\'\'Komputer\'\'\' nyaeta hiji [[wiktionary:device|alat]] atawa [[wiktionary:machine|mesin]] keur nyieun [[wiktionary:calculation|itungan]] atawa kontrol operasi nu bisa ditembongkeun dina watesan [[wiktionary:numerical|numeris]] atawa [[wiktionary:logical|logis]]. Komputers dumasar kana sipat fisikna sarta nu pakait nembongkeun sababaraha hal atawa hal tina masalah dina hiji bagian, maka pakait mekanik bakal sacara otomatis ngahasilkeun \"penyelesaian\" tina masalah. Dasar teori keur itungan make komputer disebut \'\'\'[[élmu komputer]].\'\'\'\n\n==Prinsip umum==\n\nKomputer bisa meta ku ayana ketak bagian mékanis, [[éléktron]], [[foton]], [[partikel kuantum]], atawa fénoména fisik séjén nu bisa dijéntrékeun.\n\nComputers may \'\'directly\'\' model the problem being solved, in the sense that the problem being solved is mapped as closely as possible onto the physical phenomena being exploited. For example, electron flows might be used to model the flow of water in a dam. Such \'\'analog\'\' computers were once common in the 1960s but are now rare. In most computers today, the problem is translated into mathematical terms, then reduced to simple [[Boolean algebra]]. Electronic circuits are then used to represent Boolean operations. Since almost all of mathematics can be reduced to Boolean operations, a sufficiently fast electronic computer is capable of attacking the majority of mathematical problems, and much, much more. This basic idea, which made modern \'\'digital\'\' computers possible, was formally identified and explored by [[Claude E. Shannon]]. \n\nComputers \'\'cannot\'\' solve all mathematical problems. [[Alan Turing]] identified which problems could and could not be solved by computers, and in doing so founded [[theoretical computer science]].\n\n==Étimologi==\n\nHarti kecap komputer geus robah tapi tetep ngait kana kamampuhan mesin nu dipaké dina mangsana. Kecap ieu asalna dipaké pikeun ngadadarkeun jalma nu migawé itungan aritmétik and this usage is still valid (although it is becoming quite rare in the [[United States]]). The [[Oxford English Dictionary|OED2]] lists the year [[1897]] as the first year the word was used to refer to a [[mechanical calculating device]]. By [[1946]] several qualifiers were introduced by the OED2 to differentiate between the different types of machine. These qualifiers included [[analogue]], [[digital]] and [[electronic]]. However, from the context of the citation, it is obvious these terms were in use prior to 1946. \n\n(tempo éntri Wiktionary pikeun kecap [[wiktionary:computer|computer]] pikeun definisi, tarjamah, jeung rincian [[wiktionary:etymology|étimologina]])\n\n==The exponential progress of computer development== \nThe complexities involved in classifying the various types of computer are compounded by the [[exponential growth]] in computing capacity. Roughly speaking computing devices have doubled in capacity (instructions processed per second per $1000) every 18 to 24 months since [[1900]]. [[Gordon E. Moore|Gordon E. Moore]], co-founder of [[Intel]], first described this property of computer development in [[1965]] (see [[Moore\'s Law]]). The exponential growth in capacity has been sustained by the rapid evolution of engineering techniques used to build computers. Hand-in-hand with this increase in capacity per unit cost has been an equally dramatic process of [[wiktionary:miniaturization|miniaturization]]. The first electronic computers, such as the [[ENIAC]] (announced in [[1946]]), were huge devices that weighed tons, occupied entire rooms, and required many operators to function successfully. They were so expensive that only governments and large research organizations could afford them and were considered so exotic that only a handful would ever be required to satisfy global demand. By contrast modern computers are orders of magnitude; more powerful, less expensive, smaller and have become [[wiktionary:ubiquitous|ubiquitous]].\n\n==Classification of computers==\n\nTo define what a computer is it is necessary to develop a classification of computing devices. The following sections describe several different approaches to classifying computers. These classification approaches must be used in combination to unambiguously describe a given machine.\n\n===Classification by intended use=== \nThe most obvious way to classify computing machines is by their usage. This approach is commonly employed by manufacturers of computers to describe their products and users of computers to describe the machines they interact with. For example:\n\n*[[Supercomputer]]\n*[[Minisupercomputer]]\n*[[Mainframe|Mainframe computer]]\n*[[Enterprise server]]\n*[[Minicomputer]]\n*[[Workstation]]\n*[[Personal computer|Personal computer]] (PC or desktop computer)\n*[[Laptop|Laptop computer]]\n*[[Personal Digital Assistant]] (PDA)\n*[[Wearable computer]]\n\nThe [[wiktionary:colloquial|colloquial]] nature of this classification approach means it is [[wiktionary:ambiguous|ambiguous]]. It is usual for only current, commonly available devices to be included. The rapid nature of computer development means new uses for computers are frequently found and current definitions quickly become outdated. Many classes of computer that are no longer used, such as [[differential analyzer]]s, are not commonly included in such lists. Other classification schemes are required to unambiguously define the term computer.\n\n===Classification by implementation technology=== \nA less ambiguous approach for classifying computing machines is by their implementation technology. The earliest computers were purely mechanical. In the [[1930s]] electro-mechanical components ([[relay]]s) were introduced from the [[telecommunication|telecommunications industry]], and in the [[1940s]] the first purely [[electronic]] computers were constructed from [[thermionic valve]]s (tubes). In the [[1950s]] and [[1960s]] valves were gradually replaced with [[transistor]]s and in the late [[1960s]] and early [[1970s]] [[microprocessor|semiconductor integrated circuits]] (silicon chips) were adopted and have been the mainstay of computing technology ever since.\n\nThis description of implementation technologies is not exhaustive; it only covers the mainstream of development. Historically many exotic technologies have been explored and abandoned. For example, [[model (economics)|economic models]] have been constructed using water flowing through multiple-constricted channels, and between [[1903]] and [[1909]] [[Percy E. Ludgate]] developed a design for a programmable analytical machine based [[weaving]] technologies in which variables were carried in [[shuttle]]s. \n\nEfforts are currently underway to develop [[optical computer]]s that use light rather than electricity and the possibility that [[DNA computing|DNA]] can be used for computing is being explored. One radical new area of research that could lead to computers with dramatic new capabilities is the field of [[quantum]] computing but this is presently in its early experimental stages. With the exception of [[quantum computer]]s the implementation technology of a computer is not as important for classification purposes as the features that the machine implements.\n\n===Classification by design features===\nModern computers combine many fundamental design features that have been developed by various contributors over many years. These features are often independent of implementation technology. Modern computers derive their overall capabilities from the way these features interact. Some of the most important design features are listed below.\n\n====Digital versus analog====\nA fundamental decision in designing a computer is whether it should be [[digital]] or [[analog]]. Digital computers process discrete numeric or symbolic values, while [[analog computer]]s process continuous data signals. Since the [[1940s]] digital computers have become by far the most common, although analog computers are still used for some specialized purposes such as [[robotics]] and [[cyclotron]] control. Other approaches, such as [[pulse computer|pulse computing]] and [[quantum computer|quantum computing]] are possible but are either used for special purposes or are still experimental.\n\n====Binary versus decimal====\nA significant design development in digital computing was the introduction of [[Binary numeral system|binary]] as the internal [[numeral system]]. This removed the need for complex carry mechanisms required for computers based on other numeral systems, such as the [[decimal|decimal system]]. The adoption of binary resulted in simplified designs for implementing arithmetic functions and [[Boolean algebra|logic operation]]s.\n\n====Programmability====\nThe ability to [[Computer program|program]] a computer - provide it with a set of instructions for execution- without physically reconfiguring the machine is a fundamental design feature of most computers. This feature was significantly extended when machines were developed that could [[wiktionary:dynamically|dynamically]] control the flow of execution of the program. This allowed computers to control the order in which the program of instructions was executed based on data calculated by the program as it executed. This major design advance was dramatically simplified by the introduction of binary arithmetic which can be used to represent various [[Boolean algebra|logic operation]]s.\n\n====Storage==== \nDuring the course of a calculation it is often necessary to store intermediate values for use in later calculations. The performance of many computers is largely dictated by; the speed with which they can read and write values to and from this [[computer storage|memory]], and the overall capacity of the memory. Originally [[computer storage|memory]] was used only for intermediate values but in the [[1940s]] it was suggested that the program itself could be stored in this way. This advance led to the development of the first stored-program computers of the type used today.\n\n===Classification by capability===\nPerhaps the best way to classify the various types of computing device is by their intrinsic capabilities rather than their usage, implementation technology or design features. Computers can be subdivided into three main types based on capability: Single-Purpose devices that can compute only one function (e.g. [[Antikythera mechanism|The Antikythera Mechanism]] [[87 BC]], and [[Lord Kelvin]]\'s Tide predictor [[1876]]), Special-Purpose devices that can compute a limited range of functions (e.g. [[Charles Babbage]]\'s [[Difference Engine No 1]]. [[1832]] and [[Vannevar Bush]]\'s [[Differential analyser]] [[1932]]), and General-Purpose devices of the type used today. Historically the word computer has been used to describe all these types of machine but modern colloquial usage usually restricts the term to general-purpose machines.\n\n====General-purpose computers==== \nBy definition a general-purpose computer can solve any problem that can be expressed as a [[Computer program|program]] and executed within the practical limits set by: the [[computer storage|storage]] capacity of the computer, the size of program, the speed of program execution, and the reliability of the machine. In [[1934]] [[Alan Turing]] proved that, given the right program, any general-purpose computer could emulate the behavior of any other computer. This [[mathematical proof]] was purely [[wiktionary:theoretical|theoretical]] as no general-purpose computers existed at the time. The implications of this proof are profound, for example, any existing general-purpose computer is theoretically able to emulate, albeit slowly, any general-purpose computer that may be built in the future. \n\nComputers with general-purpose capabilities are called [[Turing completeness|Turing-complete]] and this status is often used as the [[wiktionary:threshold|threshold]] capability that defines modern computers, however, this definition is [[wiktionary:problematic|problematic]]. Several computing devices with simplistic designs have been shown to be Turing-complete. The [[Z3]], developed by [[Konrad Zuse]] in [[1941]] is the earliest working computer that has been shown to be Turing-complete, so far (the proof was developed in [[1998]]). While the [[Z3]] and possibly other early devices may be theoretically Turing-complete they are impractical as general-purpose computers. They lie in what is humorously known as the [http://catb.org/~esr/jargon/html/T/Turing-tar-pit.html Turing Tar-Pit] - \"a place where anything is possible but nothing of interest is practical\" (See [http://catb.org/~esr/jargon/ The Jargon File]). Modern computers are more than theoretically general-purpose; they are also \'\'practical\'\' general-purpose tools. The modern, digital, electronic, general-purpose computer was developed, by many contributors, over an extended period from the mid [[1930s]] to the late [[1940s]], during this period many experimental machines were built that were possibly Turing-complete ([[Atanasoff Berry Computer|ABC]], [[ENIAC]], [[Harvard Mark I|Harvard Mk I]], [[Colossus]] etc see the [[History of computing hardware]]). All these machines have been claimed, at one time or another, as the first computer, but they all had limited utility as general-purpose problem-solving devices and their designs have been discarded. \n\n=====Stored-program computers===== \nDuring the late [[1940s]] the first design for a Stored-Program Computer was developed and documented (see [[The first draft]]) at the [[Moore School of Electrical Engineering]] at The [[University of Pennsylvania]]. The approach described by this document has become known as the [[Von Neumann architecture]], after it\'s only named author [[Jon von Neumann]] although others at the Moore School essentially invented the design. The [[Von Neumann architecture]] solved problems inherent in the design of the [[ENIAC]], which was then under construction, by storing the machines program in it\'s own memory. Von Neumann made the design available to other researchers shortly after the ENIAC was annouced in 1946. Plans were developed to implemented the design at the Moore School in a machine called the [[EDVAC]]. The [[EDVAC]] was not operational until [[1953]] due to technical difficulties in implementing a reliable memory. Other research institutes, who had obtained copies of the design, solved the considerable technical problems of implimenting a working memory before the Moore School team and implemented their own stored-program computers. In order of first successful operation the first 5 stored-program computers, that implemented the main features of the von Neumann Architecture were: \n\n*[[Small-Scale Experimental Machine|Manchester Mk I Prototype (Baby)]] [[Manchester University]] [[Britain]]. [[June 21]], [[1948]], \n*[[EDSAC]]. [[University of Cambridge|Cambridge University]]. [[Britain]]. [[May 6]], [[1949]]\n*[[BINAC]] [[United States]] ,[[April]] [[1949]] or [[August]], [[1949]]. \n*[[CSIRAC|CSIR Mk 1]] [[Australia]] [[November]], [[1949]]\n*[http://museum.nist.gov/panels/seac/INTROD~1.HTM SEAC] [[US]] [[May 9]], [[1950]]\n\nThe Stored Program design defined by the von-Neumann Architecture finally allowed computers to readily exploit their general-purpose potential. By storing the computer\'s program in its own memory it became possible to rapidly \"jump\" from one instruction to another based on the result of evaluating a condition defined within the program. This condition usually evaluated data values calculated by the program and allowed programs to become highly dynamic. The design also supported the ability to automatically re-write the program as it executed - a powerful feature that must be used carefully. These features are fundamental to the way modern computers work. \n\nTo be precise, most modern computers are binary, electronic, stored-program, general-purpose, computing devices.\n\n====Special-purpose computers==== \nThe special-purpose computers that were popular in the [[1930s]] and early [[1940s]] have not been completely replaced by General-Purpose computers. As the cost and size of computers has fallen and their capabilities have increased it has become cost effective to use them for special-purpose applications. Many [[domestic]] and [[Industry|industrial]] devices including; [[mobile telephone]]s, [[video recorder]]s, automotive [[ignition system]]s, etc now contain special-purpose computers. In some cases these computers are [[Turing-complete]] ([[Video Game]]s, [[Personal Digital Assistant|PDA]]s) but many are programmed once in the factory and only seldom, if ever, reprogrammed. The program that these devices execute is often contained in a [[Read Only Memory]] (ROM chip) which would need to be replaced to change the operation of the machine. Computers embedded inside other devices are commonly referred to as [[microcontrollers]] or [[embedded computers]].\n\n====Single-purpose computers====\nSingle-purpose computers were the earliest form of computing device. Given some inputs they could calculate the result of the single [[function (programming)|function]] that was implemented by their mechanism. General-Purpose computers have almost completely replaced single-purpose computers and in doing so have created a completely new field of human endeavor - [[Software engineering|Software Development]]. General-purpose computers must be programmed with a set of instructions specific to the task they are required to perform and these instructions are collectively know as [[computer software]]. The design of single-purpose computing devices and many special-purpose computing devices is now a conceptual exercise that consists solely of designing software.\n\n===Classification by type of operation===\nComputers may be classified according to the way they are operated by the users. Two main types exist: [[batch processing]] and [[interactive processing]].\n\n==Computer applications==\n\nThe first electronic digital computers, with their large size and cost, mainly performed scientific calculations, often to support military objectives. The [[ENIAC]] was originally designed to calculate ballistics firing tables for [[artillery]], but it was also used to calculate neutron cross-sectional densities to see if the [[hydrogen bomb]] would work properly. This calculation, performed in [[December]], [[1945]] through [[January]], [[1946]] and involving over a million [[punch card]]s of [[data]], showed the design then under consideration would fail. (Interestingly, many of the most powerful [[supercomputer]]s available today are also used for [[nuclear weapon]]s [[simulation]]s.) The [[CSIRAC|CSIR Mk I]], the first [[Australia]]n stored-program computer, evaluated rainfall patterns for the [[catchment area]] of the [[Snowy Mountains]] Scheme, a large [[hydroelectric]] generation project. Others were used in [[cryptanalysis]], for example the world\'s first programmable (though not general-purpose) digital electronic computer, [[Colossus]], built during [[World War II]]. Despite this early focus of scientific applications, computers were quickly used in other areas. \n\nFrom the beginning, stored program computers were applied to business problems. The [[LEO computer|LEO]], a stored program-computer built by [[J. Lyons and Co.]] in [[Britain]], was operational and being used for inventory management and other purposes 3 years before [[IBM]] built their first commercial stored-program computer.\nContinual reductions in the cost and size of computers saw them adopted by ever-smaller organizations. And with the invention of the [[microprocessor]] in the [[1970s]], it became possible to produce inexpensive computers. In the [[1980s]], [[personal computers]] became popular for many tasks, including [[book-keeping]], writing and printing documents, calculating forecasts and other repetitive mathematical tasks involving [[spreadsheet]]s.\n\n===The Internet=== \nIn the 1970s, computer engineers at various research institutions throughout the US began to link their computers together using telecommunications technology. This effort was funded by [[Advanced Research Projects Agency|ARPA]], and the [[computer network]] that it produced was called the [[ARPANET]]. The technologies that made the Arpanet possible rapidly spread and evolved. In time, the network spread beyond academic institutions and became known as the [[Internet]]. In the [[1990s]], the development of [[World Wide Web]] technologies enabled ordinary, non-technical people to use the internet, and it grew rapidly to become a [[wiktionary:global|global]] communications medium.\n\n==How computers work==\nWhile the technologies used in computers have changed dramatically since the first electronic, general-purpose, computers of the [[1940s]] (see [[History of computing hardware]] for more details), most still use the [[von Neumann architecture]]. \n\nThe von Neumann [[von Neumann architecture|architecture]] describes a computer with four main sections: the [[ALU|Arithmetic and Logic Unit]] (ALU), the [[control unit|control circuitry]], the [[computer storage|memory]], and the input and output devices (collectively termed I/O). These parts are interconnected by a bundle of wires (a \"[[computer bus|bus]]\") and are usually driven by a timer or [[clock]] (although other [[event]]s could drive the control circuitry).\n\n===Memory===\nIn this system, \'\'\'[[computer storage|memory]]\'\'\' is a sequence of numbered cells, each containing a small piece of information. The information may be an [[instruction]] to tell the computer what to do. The cell may contain [[data]] that the computer needs to perform the instruction. Any cell may contain either, and indeed what is at one time data might be instructions later. \n\nIn general, the contents of a memory cell can be changed at any time - it is a scratchpad rather than a stone tablet. \n\nThe size of each cell, and the number of cells, varies greatly from computer to computer, and the technologies used to implement memory have varied greatly - from electromechanical [[relays]], to mercury-filled tubes (and later springs) in which acoustic pulses were formed, to matrices of permanent magnets, to individual [[transistors]], to [[integrated circuits]] with millions of [[capacitor]]s on a single [[chip]].\n\n===Processing ([[Processor]])===\n[[Image:CPU with pins.jpg|thumb|right|A [[central processing unit|CPU]]]]\nThe \'\'\'arithmetic and logical unit\'\'\', or [[arithmetic and logical unit|ALU]], is the device that performs elementary [[operation]]s such as arithmetic operations (addition, subtraction, and so on), [[logic]]al operations ([[logic gate|AND, OR, NOT]]), and comparison operations (for example, comparing the contents of two [[byte]]s for equality). This unit is where the \"real work\" is done.\n\nThe \'\'\'[[control unit]]\'\'\' keeps track of which bytes in memory contain the current instruction that the computer is performing, telling the ALU what operation to perform and retrieving the information (from memory) that it needs to perform it, and transfers the result back to the appropriate memory location. Once that occurs, the control unit goes to the next instruction (typically located in the next slot ([[memory address]]), unless the instruction is a [[jump instruction]] informing the computer that the next instruction is located in another location).\nWhen referrring to memory, the current instruction may use\nvarious [[addressing mode]]s to determine the relevant address in memory.\n\nToday there are mainly two kinds of CPU\'s available for home use. The first is made by [http://www.intel.com Intel] (the CPU giant) and the other is made by [http://www.amd.com AMD](their main competition). In the past [http://www.motorolla.com Motorolla]and Cyrix have also manufactured CPU\'s for desktop use, but Intel (Pentium & Celeron) and AMD (Athlon, Opteron, 64) have proven themselves.\n\n===Input and output===\nThe \'\'\'[[Input/output|I/O]]\'\'\' allows the computer to obtain information from the outside world, and send the results of its work back there. There is an incredibly broad range of I/O devices, from the familiar [[Alphanumeric keyboard|keyboard]]s, [[Computer display|monitors]] and [[floppy disk]] drives, to the more unusual such as [[webcam]]s.\n\nWhat all input devices have in common is that they [[encode]] (convert) information of some type into [[data]] which can further be processed by the digital computer system. Output devices on the other hand, [[decode]] the data into information which can be understood by the computer user. In this sense, a digital computer system is an example of a [[data processing system]].\n\n===Instructions===\nThe machine set of instructions are not the rich instructions of a human language. A computer only has a limited number of well-defined, simple instructions. Computers can perform two tasks. They can count and they can compare. Typical sorts of instructions supported by most computers are \"copy the contents of cell 123, and place the copy in cell 456\", \"add the contents of cell 666 to cell 042, and place the result in cell 013\", \"if the contents of cell 999 are 0, your next instruction is at cell 345\".\n\nInstructions are represented within the computer as [[binary]] code - a base two system of counting. The code for \"copy\" might be 001, for example. The particular instruction set that a specific computer supports is known as that computer\'s [[machine language]]. In practice, people do not normally write the instructions for computers directly in machine language but rather use a \"high level\" [[programming language]] which is then translated into the machine language automatically by special computer programs ([[Interpreter (computing)|interpreter]]s and [[compiler]]s). Some programming languages map very closely to the machine language, such as [[assembler]] (low level languages); at the other end, languages like [[Prolog]] are based on abstract principles far removed from the details of the machine\'s actual operation (high level languages).\n\n===Architecture===\nContemporary computers put the [[ALU]] and [[control unit]] into a single [[integrated circuit]] known as the [[Central processing unit|Central Processing Unit]] or CPU. Typically, the computer\'s memory is located on a few small integrated circuits near the CPU. The overwhelming majority of the computer\'s mass is either ancillary systems (for instance, to supply electrical power) or I/O devices.\n\nSome larger computers differ from the above model in one major respect - they have multiple CPUs and control units working simultaneously. Additionally, a few computers, used mainly for research purposes and scientific computing, have differed significantly from the above model, but they have found little commercial application, because their programming model has not yet standardized.\n\nThe functioning of a computer is therefore in principle quite straightforward. Typically, on each clock cycle, the computer fetches instructions and data from its memory. The instructions are executed, the results are stored, and the next instruction is fetched. This procedure repeats until a \'\'halt\'\' instruction is encountered.\n\n===Programs===\n[[Computer program]]s are simply large lists of instructions for the computer to execute, perhaps with tables of data. Many computer programs contain millions of instructions, and many of those instructions are executed repeatedly. A typical modern [[personal computer|PC]] (in the year [[2003]]) can execute around 2-3 billion instructions per second. Computers do not gain their extraordinary capabilities through the ability to execute complex instructions. Rather, they do millions of simple instructions arranged by clever people, \"[[programmer]]s.\" Good programmers develop sets of instructions to do common tasks (for instance, draw a dot on screen) and then make those sets of instructions available to other programmers.\n\nNowadays, most computers appear to execute several programs at the same time. This is usually referred to as [[multitasking]]. In reality, the CPU executes instructions from one program, then after a short period of time, it switches to a second program and executes some of its instructions. This small interval of time is often referred to as a time slice. This creates the illusion of multiple programs being executed simultaneously by sharing the CPU\'s time between the programs. This is similar to how a movie is simply a rapid succession of still frames. The [[operating system]] is the program that usually controls this time sharing.\n\n====Sistim operasi====\n\nKomputer salawasna butuh sahanteuna hiji program nu salawasna jalan sangkang operasina jalan. Dina operasi normal program ieu katelah [[sistim operasi]] (Ing. \'\'operating system\'\', OS). Sistim operasi nangtukeun program mana nu jalan, iraha, jeung sumberdaya naon (kayaning mémori atawa I/O) nu kudu dipaké. The operating system also provides a layer of abstraction over the hardware, and gives access by providing services to other programs, such as code (\"drivers\") which allow programmers to write programs for a machine without needing to know the intimate details of all attached electronic devices.\n\n==Tempo ogé==\n* \'\'[[computability theory]]\'\'\n* [[lambardata komputer]] (Ing. \'\'computer datasheet\'\')\n* [[paméran komputer]]\n* [[élmu komputer]]\n* tipe komputer: \'\'[[desktop]]\'\', \'\'[[notebook]]\'\', \'\'[[desknote]]\'\', \'\'[[Roll-away]]\'\' \n* [[digital]]\n\n==Tumbu kaluar==\n* [http://s8.invisionfree.com/ComputerGeek/index.php ComputerGeek forums] Computer programming discussion forum\n* [http://www.xtremecomputing.co.uk Xtreme Computing] Computing reviews, articles and forum\n* [http://www.computerhistory.org Computer History Museum]\n* [http://www.obsoletecomputermuseum.org Pictures and information on old computers]\n* [http://www.webopedia.com/TERM/C/computer.html Definition of Computer @ Webopedia]\n* [http://www.navito.co.uk/computers.asp Guide to buying a new computer]\n* [http://open-site.org/Computers/ Open Site Project - Computers Section]\n* [http://www.ittips.com/ Computer Help]\n* [http://www.elook.org/computing/ eLook Computing Reference - computer terms and definitions]\n* http://dmoz.org/Computers/\n* [http://www.simplecomputeranswers.com/ Volunteer-Answered Free Computer Help]\n\n[[Category:Ngitung]]\n[[Category:Alat Matematik]]\n[[Category:Téhnologi informasi]]\n\n\n[[af:Rekenaar]]\n[[ar:حاسوب]]\n[[ast:Computadora]]\n[[bg:Компютър]]\n[[ca:Ordinador]]\n[[cs:Počítač]]\n[[cy:Cyfrifiadur]]\n[[da:Computer]]\n[[de:Computer]]\n[[nv:Béésh bee ak\'e\'elchíhí t\'áá bí nitsékeesígíí]]\n[[en:Computer]]\n[[et:Arvuti]]\n[[es:Computadora]]\n[[eo:Komputilo]]\n[[fa:رایانه]]\n[[fo:Telda]]\n[[fr:Ordinateur]]\n[[fy:Kompjûter]]\n[[gd:Coimpiutaireachd]]\n[[ko:컴퓨터]]\n[[hi:संगणक]]\n[[id:Komputer]]\n[[ia:Computator]]\n[[is:Tölva]]\n[[it:Computer]]\n[[he:מחשב]]\n[[ku:Kompûter]]\n[[la:Computator]]\n[[lv:Datori]]\n[[lt:Kompiuteris]]\n[[hu:Számítógép]]\n[[mg:Mpikajy]]\n[[ml:കംപ്യുട്ടര്‍]]\n[[ms:Komputer]]\n[[nds:Reekner]]\n[[nl:Computer]]\n[[ja:コンピュータ]]\n[[no:Datamaskin]]\n[[nds:Computer]]\n[[pl:Komputer]]\n[[pt:Computador]]\n[[ro:Computer]]\n[[ru:Компьютер]]\n[[simple:Computer]]\n[[sr:Рачунар]]\n[[fi:Tietokone]]\n[[sv:Dator]]\n[[vi:Máy tính]]\n[[tr:Bilgisayar]]\n[[uk:Комп\'ютер]]\n[[zh:计算机]]','/* Etymology */',3,'Kandar','20050128080300','',0,0,0,0,0.491041408239,'20050208191941','79949871919699'); INSERT INTO cur VALUES (2098,0,'Bayes\'_Theorem','#REDIRECT [[Bayes\' theorem]]','',13,'Budhi','20041231122452','',0,1,0,1,0.239689558007,'20041231122452','79958768877547'); INSERT INTO cur VALUES (2099,0,'Classification','\'\'\'\'\'Classification\'\'\'\'\' may refer to:\n* \'\'\'Taxonomic classification\'\'\', the act of placing an object or concept into a set of categories (such as a [[taxonomy]] or a [[subject index]]), based on the properties of the object or concept. A person may classify the object or concept according to an [[ontology]]. Confusingly, such a classification may be referred to as \"statistical\" (see below), if its purpose is to compute statistics over objects or concepts. Examples of taxonomic classification include:\n** [[Library classification]]\n** [[Scientific classification]]\n** [[Biological classification]]\n** [[Classification of finite simple groups]]\n** [[Medical classification]] like [[International Statistical Classification of Diseases and Related Health Problems|ICD]]\n\n* \'\'\'Statistical classification\'\'\', a type of [[statistics|statistical]] [[algorithm]] which takes a feature representation of an object or concept and maps it to a classification label. A classification algorithm is designed to learn (to approximate the behavior of) a function which maps a vector of features [X1,X2,...XN] into one of several classes by looking at several input-output examples of the function. See also [[machine learning]], [[supervised learning]]. Examples of these algorithms include:\n** [[Boosting]]\n** [[Decision trees]]\n** [[Logistic regression]]\n** [[Naive Bayes classifier]]\n** [[Neural networks]]\n** [[Support vector machines]]\n\n[[Category:Knowledge representation]]\n[[de:Klassifikation]]\n[[fr:classification]]\n[[ja:分類]]\n[[nl:Classificatie]]\n[[uk:Класифікація]]','',13,'Budhi','20041231122708','',0,0,0,1,0.078169296002,'20050303214455','79958768877291'); INSERT INTO cur VALUES (2100,0,'Supervised_learning','\'\'\'Supervised learning\'\'\' is a [[machine learning]] technique for creating a function from training data. The training data consists of pairs of input objects (typically vectors), and desired outputs. The output of the function\ncan be a continuous value (called [[regression]]), or can predict a class label of the input object (called [[classification]]). The task of the supervised learner is to predict the value of the function for any valid input object after having seen only a small number of training examples (i.e. pairs of input and target output). To achieve this, the learner has to generalize from the presented data to unseen situations in a \"reasonable\" way (see [[inductive bias]]).\n(Compare with [[unsupervised learning]].)\n\nIn order to solve a given problem of supervised learning (e.g. learning to [[handwriting recognition|recognize handwriting]]) one has to consider various steps:\n# Determine the type of training examples. Before doing anything else, the engineer should decide what kind of data is to be used as an example. For instance, this might be a single handwritten character, an entire handwritten word, or an entire line of handwriting.\n# Gathering a training set. The training set needs to be characteristic of the real-world use of the function. Thus, a set of input objects is gathered and corresponding outputs are also gathered, either from human experts or from measurements. \n# Determine the input feature representation of the learned function. The accuracy of the learned function depends strongly on how the input object is represented. Typically, the input object is transformed into a feature vector, which contains a number of features that are descriptive of the object. The number of features should not be too large, because of the [[curse of dimensionality]]; but should be large enough to accurately predict the output.\n# Determine the structure of the learned function and corresponding learning algorithm. For example, the engineer may choose to use [[neural networks]] or [[decision tree]]s.\n# Complete the design. The engineer then runs the learning algorithm on the gathered training set. Parameters of the learning algorithm may be adjusted by optimizing performance on a subset (called a validation set) of the training set, or via [[cross-validation]]. After parameter adjustment and learning, the performance of the algorithm may be measured on a test set that is separate from the training set.\n\n== Approaches and algorithms ==\n\n* [[analytical learning]]\n* artificial [[neural network]]s\n** [[Instantaneously trained neural networks]]\n* [[backpropagation]]\n* [[boosting]]\n* [[Bayesian statistics]]\n* [[case-based reasoning]]\n* [[decision tree]] learning\n* [[inductive logic programming]]\n* [[Gaussian process regression]]\n* [[learning automata theory]]\n* [[naive Bayes classifier]]\n* [[probably approximately correct learning]] (PAC) learning\n* [[symbolic machine learning]] algorithms\n* [[subsymbolic machine learning]] algorithms\n* [[support vector machine]]s\n\n== Applications ==\n* [[bioinformatics]]\n* [[handwriting recognition]]\n* [[information retrieval]]\n* object recognition in [[computer vision]]\n* [[optical character recognition]]\n* [[spamming|spam detection]]\n* [[pattern recognition]]\n* [[speech recognition]]\n\n\n== General issues ==\n\n* [[computational learning theory]]\n* [[inductive bias]]\n* [[overfitting]]\n* [[version space]]s\n\n[[Category:Machine learning]]\n[[de:Überwachtes Lernen]]\n[[it:Apprendimento supervisionato]]\n[[th:การเรียนรู้แบบมีผู้สอน]]','',13,'Budhi','20041231122801','',0,0,0,1,0.022287223027,'20041231124514','79958768877198'); INSERT INTO cur VALUES (2101,0,'Joint_probability','#REDIRECT[[conditional probability]]','',13,'Budhi','20041231123438','',0,1,0,1,0.304707394401,'20050303214455','79958768876561'); INSERT INTO cur VALUES (2102,0,'Conditional_probability','This article defines some terms which characterize [[probability distribution]]s of two or more variables.\n\n\'\'\'Conditional probability\'\'\' is the [[probability]] of some [[Probability/Event|event]] \'\'A\'\', assuming event \'\'B\'\'.\nConditional probability is written \'\'P\'\'(\'\'A\'\'|\'\'B\'\'), and is read \"the probability of \'\'A\'\', given \'\'B\'\'\".\n\n\'\'\'Joint probability\'\'\' is the probability of two events in conjunction. That is, it is the probability of both events together.\nThe joint probability of \'\'A\'\' and \'\'B\'\' is written \'\'P\'\'(\'\'A\'\', \'\'B\'\').\n\n\'\'\'Marginal probability\'\'\' is the probability of one event, \nignoring any information about the other event.\nMarginal probability is obtained by summing (or integrating, more generally) the joint probability over the ignored event.\nThe marginal probability of \'\'A\'\' is written \'\'P\'\'(\'\'A\'\'), \nand the marginal probability of \'\'B\'\' is written \'\'P\'\'(\'\'B\'\').\n\nIn these definitions,\nnote that there need not be a causal or temporal relation between \'\'A\'\' and \'\'B\'\'.\n\'\'A\'\' may precede \'\'B\'\', or vice versa, or they may happen at the same time.\n\'\'A\'\' may [[cause]] \'\'B\'\', or vice versa, or they may have no causal relation at all.\n\n==Relations==\n\nIf \'\'A\'\' and \'\'B\'\' are events, and \'\'P\'\'(\'\'B\'\') > 0, then\n\n:P(A\\mid B)=\\frac{P(A, B)}{P(B)}\n\nEquivalently, we have\n\n:P(A,B)=P(A\\mid B)\\cdot P(B)\n\nIf P(A, B) = P(A)P(B)\n(equivalently, P(A|B) = P(A)), \nthen we say that A and B are [[statistical independence|independent]].\n\nIf B is an event and P(B) > 0, then the function Q defined by Q(A) = P(A|B) for all events A is a [[probability measure]].\n\nIf P(B)=0, P(A|B) is left [[undefined]].\n\nConditional probability is more easily calculated with a [[decision tree]].\n\n==See also==\n*[[Probability theory]] \n*[[Bayes\' theorem]] \n*[[Likelihood]]\n*[[Posterior probability]]\n\n[[Category:Probability theory]]\n\n[[de:Bedingte Wahrscheinlichkeit]]\n[[fr:Probabilité conditionnelle]]\n[[it:Probabilità condizionata]]\n[[nl:Voorwaardelijke kans]]\n[[pl:Prawdopodobieństwo warunkowe]]','',13,'Budhi','20041231123513','',0,0,0,1,0.171928248196,'20041231123513','79958768876486'); INSERT INTO cur VALUES (2103,0,'Document_classification','\'\'\'Document classification\'\'\' is a problem in [[information science]]. The task is to assign a document to one or more categories, based on its contents. Document classification tasks can be divided into two sorts: \'\'\'supervised document classification\'\'\' where some external mechanism (such as human feedback) provides information on the correct classification for documents, and \'\'\'unsupervised document classification\'\'\', where the classification must be done entirely without reference to external information.\n\nDocument classification techniques include:\n* [[naive Bayes classifier]]\n* [[latent semantic indexing]]\n* [[support vector machine]]s\nand approaches based on [[natural language processing]].\n\nA recent notable use of document classification techniques has been [[spam filter]]ing which tries to discern [[E-mail spam]] messages from legitimate emails.\n\n== See also ==\n* [[Classification]]\n* [[Document retrieval]]\n* [[Information retrieval]]\n\n== External links ==\n* Rafael A. Calvo, Jae-Moon Lee and Xiaobo Li. [http://jodi.ecs.soton.ac.uk/Articles/v05/i02/Calvo/ Managing Content with Automatic Document Classification]. \'\'Journal of Digital Information\'\', Volume 5 Issue 2, Article No. 282, 2004-06-08\n* [http://isp.imm.dtu.dk/thor/projects/multimedia/textmining/node11.html Introduction to document classification]\n\n{{stub}}\n\n[[Category:information science]]\n[[Category:natural language processing]]\n[[Category:knowledge representation]]\n[[Category:data mining]]','',13,'Budhi','20041231124303','',0,0,0,1,0.000553566529,'20041231124303','79958768875696'); INSERT INTO cur VALUES (2104,0,'Probability_axiom','#REDIRECT [[Probability_axioms]]','',13,'Budhi','20041231124408','',0,1,0,1,0.004054966403,'20050303214455','79958768875591'); INSERT INTO cur VALUES (2105,0,'Spamming','#REDIRECT [[Spam (electronic)]]','',13,'Budhi','20041231124514','',0,1,0,1,0.03649810479,'20041231124600','79958768875485'); INSERT INTO cur VALUES (2106,0,'Spam_(electronic)','\'\'\'Spamming\'\'\' nyaeta kalakuan ngirimkeun surelek [[electronics|electronik]] nu teu dipiharep. Hiji kaca [http://www.personal.psu.edu/mjs501/SPAM.pdf article] ngarupakeun masalah spam dina [[1998]] dumasar kana salaku pesen \'\'\"[[text]] taya harti nu ngalir taya eureunna.\"\'\'\n\nTina panempo nu populer, spam ilaharnad dikirim ngaliwatan [[e-mail|surelek]] saperti dina bentuk [[advertising|iklan]]. However, over the short history of electronic media, people have done things comparable to spamming for many purposes other than the commercial, and in many media other than e-mail. In this article and those related, the term \'\'spamming\'\' is used broadly to refer to all of these behaviors, regardless of medium and commercial intent.\n\nThis article provides a general overview of the spamming phenomenon. Separate articles discuss the techniques of spammers on particular media: [[E-mail spam|Internet e-mail]], [[Messaging spam|instant messaging]], [[Newsgroup spam|Usenet newsgroups]], [[spamdexing|Web search engines]], [[blog spam|weblogs]], and [[mobile phone spam|mobile phone messaging]]. Another article describes ways of [[stopping e-mail abuse]].\n\n==Overview==\n\nOne of the strengths of electronic communications media is that it costs virtually nothing to send a message. These media are not free of charge: setting up a [[cellular telephone]] network or an [[Internet]] [[e-mail]] service has substantial overhead costs in equipment and connectivity. However, once these costs are paid for, the cost to transmit a message to a single recipient is minuscule when compared with older media such as [[mail|postal mail]]. Electronic messaging is cheap and fast. It is also easy to automate: computer programs can send out millions of messages via e-mail, instant message (IM), or Usenet netnews in minutes or hours at nearly no labor cost.\n\nFrom these economic realities, a sort of [[tragedy of the commons]] emerges. Any communications mechanism which is cheap and easy to automate is easy to flood with bulk messages. To send instant messages to millions of users on most IM services, all one needs is a piece of scriptable software and those users\' IM usernames. The ability to send e-mail from a computer program is built in to popular operating systems such as [[Microsoft Windows]] and [[Unix]] — the only added ingredient needed is the list of addresses to target.\n\nSending bulk messages in this fashion, to recipients who have not solicited them, has come to be known as \'\'\'spamming\'\'\', and the messages themselves as \'\'\'spam\'\'\'. The [[etymology]] of the term is discussed [[spamming#Etymology|below]]. Traditional advertising methods, such as billboards, TV or newspaper ads are similar to spam in that they are usually unsolicited and sent in bulk. Pollution of public space by advertising is also quite similar to the problem of spam. However, traditional \"legitimate\" advertising is usually spared the \"spam\" label on the grounds that distribution costs are borne by the advertiser.\n\nSpamming has been considered by various commercial, government, and independent entities to be one of the foremost social problems facing electronic media today. All manner of attempts have been made to curb this problem: technical measures such as e-mail filtering and the automated cancellation of [[netnews]] spam; contractual measures such as [[Internet Service Provider]]s\' [[acceptable use policy|acceptable-use policies]]; laws such as the [[Can Spam Act of 2003]]; and market pressures such as boycotts of those who use or support spam.\n\nThe growing importance of [[Search Engine]]s has led to a new form of spam, [[Spamdexing]], which aims at boosting a commercial site\'s [[Pagerank]].\n\n==Spamming in different media==\n\n===E-mail spam===\n\n[[E-mail spam]] is by far the most common form of spamming on the internet. It involves sending identical or nearly identical messages to a large number of recipients. Unlike legitimate commercial e-mail, spam is generally sent without the explicit permission of the recipients, and frequently contains various tricks to bypass e-mail filters.\n\nSpammers obtain e-mail addresses by a number of means: \'\'harvesting\'\' addresses from [[Usenet]] postings, [[DNS]] listings, or Web pages; guessing common names at known domains (known as a \'\'dictionary attack\'\'); and \'\'\"e-pending\"\'\' or searching for e-mail addresses corresponding to specific persons, such as residents in an area.\n\nMany e-mail spammers go to great lengths to conceal the origin of their messages. They might do this by [[spoof]]ing e-mail addresses (similar to [[Internet protocol spoofing]]). In this technique, the spammer modifies the e-mail message so it looks like it is coming from another e-mail address. However, many spammers also make it easy for recipients to identify their messages as spam by placing an ad phrase in the FROM field (i.e. chances are, very few people you know have names like \"GetMyCigs\" or \"Giving away playstation2s\").\n\nAmong the tricks used by spammers to try to circumvent the filters is to intentionally misspell common spam filter trigger words, ie. \"viagra\" might become \"vaigra\", or by inserting other symbols within the word, i.e. \"v/i/a/g./r/a\". Sometimes this intentional corruption backfires and leads to the advertiser\'s message becoming so obfuscated that it is illegible.\n\nThe weird thing is that the human mind can handle the misspellings (see [http://loopbiz.com/business.small/mind-gaps.html Wrod Illusinos]) and while one would think the misspellings make it harder for email [[ISP]]s to trap the spam, it actually makes it easier for them to recognize and stop the spam.\n\nThe most dedicated spammers are often one step ahead of the ISPs. The dedicated ones are those making a lot of money or engaged in illegal activities, such as the porn industry, casinos and [[Nigerian scam]]mers. Report them early and often.\n\nSpambots are a big problem now. The worst spammers have created various [[computer virus|email viruses]] that will turn your PC into a [[zombie computer]] with a spambot; the zombie will inform a master spammer of its existence, and, and the spammer will command it to send a low volume of spam. This allows spammers to send spam without being caught by their ISPs or being tracked down by anti-spammers; the low volume makes it hard to detect. Dialup and DSL ISPs could stop spambots by blocking the [[SMTP]] [[port (computing)|port]] (port 25) - link Earthlink does.\n\n===Messaging spam===\n\n[[Messaging spam]], sometimes termed \'\'spim\'\', is a type of spamming where the target of the spamming is [[instant messaging]] (IM). Many IM systems offer a directory of users, including demographic information such as age and sex. Advertisers can gather this information, sign on to the system, and send unsolicited messages.\n\nA similar sort of spam can be sent with the [[Windows Messenger Service]] in [[Microsoft Windows]]. The Messenger Service is an [[server message block|SMB]] facility intended to allow servers to send pop-up alerts to a Windows workstation. When Windows systems are connected to the Internet with this service running and without an adequate firewall, it can be used to send spam. The Messenger Service can, however, be easily disabled. [http://www.itc.virginia.edu/desktop/docs/messagepopup/]\n\n===Newsgroup spam===\n\n[[Newsgroup spam]] is a type of spamming where the target of the spamming are [[Usenet]] [[newsgroup]]s. Spamming of Usenet newsgroups actually pre-dates e-mail spam. Old Usenet convention defines spamming as \'\'excessive multiple posting,\'\' that is, the repeated posting of a message (or substantially similar messages). Since posting to newsgroups is nearly as easy as sending e-mails, newsgroups are a popular target of spammers. The [[Breidbart Index]] was developed to provide an objective measure of the \"spamminess\" of a multi-posted or cross-posted message on Usenet.\n\n===Mobile phone spam===\n\n[[Mobile phone spam]] is a form of spamming directed at the [[text messaging]] service of a [[mobile phone]]. This can be especially irritating to consumers not only for the inconvenience but also because they sometimes have to pay to receive the text message.\n\n===Internet telephony spam===\n\nIt has been predicted that [[voice over IP]] (VoIP) communications will be vulnerable to being spammed by pre-recorded messages. Although there have been few reported incidents, some companies have already tried to sell defenses against it. [http://www.internetnews.com/security/article.php/3398331]\n\n==Spam targeting search engines==\n\n===Spamdexing===\n\n[[Spamdexing]] (a combination of \'\'spamming\'\' and \'\'indexing\'\') refers to the practice on the [[World Wide Web]] of deliberately modifying [[HTML]] pages to increase the chance of them being placed high on [[search engine]] relevancy lists. People who do this are called [[search engine spammer]]s.\n\n===Blog spam===\n\nIn [[blog spam]] the targets are [[weblog]]s. In 2003, this type of spam took advantage of the open nature of comments in the blogging software [[Movable Type]] by repeatedly placing comments to various blog posts that provided nothing more than a link to the spammer\'s commercial web site. These link would in theory enhance the ranking of the target page in search engine indexes. [http://www.wired.com/wired/archive/12.03/google.html?pg=7]\n\n===Wiki spam===\n\n[[Wiki]]s are also a target of search engine spam, quite similar to [[blog spam]].\n\n===Guestbook spam===\n\nThough more \"old-school\" than blogs or wikis, [[guestbook]]s are still present on some sites, and are subject to the same sorts of spam.\n\n== Commercial uses ==\n\nThe most common purpose for spamming is [[advertising]]. Goods commonly advertised in spam include [[pornography]], [[computer software]], medical products such as [[Viagra]], [[credit card]] accounts, and fad products. In part because of the bad reputation (and dubious legal status) which spamming carries, it is chiefly used to carry offers of an ill-reputed or questionably legal nature. Many of the products advertised in spam are fraudulent in nature, such as [[quackery|quack medications]] and [[Make money fast|get-rich-quick scheme]]s. Spam is frequently used to advertise scams, such as [[diploma mill]]s, [[advance fee fraud]], [[pyramid scheme]]s, stock [[pump and dump|pump-and-dump]] schemes and [[password phishing]]. It is also often used to advertise [[pornography]] indiscriminately, even in jurisdictions where it is illegal to transmit pornographic solicitations to minor children, or even for anyone to view it at all.\n\nThe use of spamming in other countries is often different. For example, in [[Russia]] spamming is commonly used by many mainstream legitimate businesses, such as travel agencies, printing shops, training centres, real estate agencies, seminar and conference organisers and even self-employed electricians and garbage collection companies. In fact, the most prominent Russian spammer was [[American English Center]], a language school in Moscow. That spamming sparked a powerful anti-spam movement, including enraging the deputy minister of communications [[Andrey Korotkov]] and provoked a wave of counter attacks on the spammer through non-internet channels, including a massive telephone [[DDOS]] attack.\n\n=== Comparison to postal \"junk\" mail ===\n\nThere are a number of differences between spam and junk mail:\n\n*Unlike junk [[postal mail]], the costs of spam paid for by the recipient\'s mail site commonly approach or even exceed those of the sender, in terms of bandwidth, CPU processing time, and storage space. Spammers frequently use free dial-up accounts, so their costs may be quite minimal indeed. Because of this offloading of costs onto the recipient, many consider spamming to be [[theft]] or criminal conversion.\n*Junk mail can be said to subsidize the delivery of mail customers want to receive. For example, the [[United States Postal Service]] allows [[bulk mail]] senders to pay a lower rate than for first-class mail, because they are required to sort their mailings and apply [[bar code]]s, which makes their mail much cheaper to process. While some ISPs receive large fees from spammers, most do not — and most pay the costs of carrying or filtering unwanted spam.\n*Another distinction is that the costs of sending junk mail provide incentives to be somewhat selective about recipients, whereas the spammer has much lower costs, and therefore much less incentive.\n*Finally, bulk mail is by and large used by businesses who are traceable and can be held responsible for what they send. Spammers frequently operate on a fly-by-night basis, using the so-called \"anarchy\" of the Internet as a cover.\n\n== Non-commercial spam ==\n\nE-mail and other forms of spamming have been used for purposes other than advertisements. Many early Usenet spams were religious or political in nature. [[Serdar Argic]], for instance, spammed Usenet with historical revisionist screeds. A number of [[evangelism|evangelists]] have spammed Usenet and e-mail media with preaching messages.\n\nSpamming has also been used as a [[denial of service]] tactic, particularly on Usenet. By overwhelming the readers of a newsgroup with an inordinate number of nonsense messages, legitimate messages can be lost and computing resources are consumed. Since these messages are usually forged (that is, sent falsely under regular posters\' names) this tactic has come to be known as [[sporgery]] (from \'\'spam\'\' + \'\'forgery\'\'). This tactic has for instance been used by partisans of the [[Church of Scientology]] against the [[alt.religion.scientology]] newsgroup (see [[Scientology vs. the Internet]]) and by spammers against [[news.admin.net-abuse.e-mail]], a forum for mail administrators to discuss spam problems. Applied to e-mail, this is termed [[mailbomb]]ing.\n\nIn a handful of cases, forged e-mail spam has been used as a tool of [[harassment]]. The spammer collects a list of addresses as usual, then sends a spam to them signed with the name of the person he wishes to harass. Some recipients, angry that they received spam and seeing an obvious \"source\", will respond angrily or pursue various sorts of revenge against the apparent spammer, the forgery victim. A widely known victim of this sort of harassment was [http://joes.com/ Joe\'s CyberPost], which has lent its name to the offense: it is known as a \'\'[[joe job]]\'\'. Such [[joe jobs]] have been most often used against anti-spammers: in more recent examples, [[Steve Linford]] of [[Spamhaus Project]] and [[Timothy Walton]], a California attorney, have been targeted.\n\nSpammers have also abused resources set up for purposes of anonymous speech online, such as [[anonymous remailer]]s. As a result, many of these resources have been shut down, denying their utility to legitimate users.\n\nE-mail [[computer virus|worms or viruses]] may be spammed to set up an initial pool of infected machines, which then re-send the virus to other machines in a spam-like manner. The infected machines can often be used as remote-controlled [[zombie computers]], for more conventional spamming or [[DDoS]] attacks. Sometimes [[Trojan horse (computing)|trojan]]s are spammed to [[phishing|phish]] for bank account details, or to set up a pool of zombies without using a virus.\n\n== Etymology ==\n\nThe term \'\'spam\'\' is derived from the [[Monty Python]] [[Spam (Monty Python)|SPAM sketch]], set in a cafe where everything on the menu includes [[SPAM]] luncheon meat. While a customer plaintively asks for some kind of food without SPAM in it, the server reiterates the SPAM-filled menu. Soon, a chorus of [[Viking]]s join in with a song, repeating \"SPAM, SPAM, SPAM, SPAM\" and singing \"lovely SPAM, wonderful SPAM\" over and over again, drowning out all conversation.\n\nAlthough the [http://www.templetons.com/brad/spamreact.html first known instance of unsolicited commercial e-mail] occurred in [[1978]] (unsolicited electronic messaging had already taken place over other media, with the first recorded instance being on September 13th 1904 via telegram), the term \"spam\" for this practice had not yet been applied. In the [[1980s]] the term was adopted to describe certain abusive users who frequented [[Bulletin Board System|BBS]]s and [[MUD]]s, who would repeat \"SPAM\" a huge number of times to scroll other users\' text off the screen. This act, previously termed \'\'flooding\'\' or \'\'trashing\'\', came to be called \'\'spamming\'\' as well. [http://groups.google.com/groups?threadm=MAT.90Sep25210959%40zeus.organpipe.cs.arizona.edu] By analogy, the term was soon applied to any large amount of text broadcast by one user, or sometimes by many users.\n\nIt later came to be used on [[Usenet]] to mean \'\'excessive multiple posting\'\' — the repeated posting of the same message. The first evident usage of this sense was by [[Joel Furr]] in the aftermath of the [[ARMM (Usenet)|ARMM]] incident of [[March 31]] [[1993]], in which a piece of experimental software released dozens of recursive messages onto the \'\'news.admin.policy\'\' newsgroup. Soon, this use had also become established — to spam Usenet was to flood newsgroups with junk messages.\n\nCommercial spamming started in force on [[March 5]], [[1994]] when a pair of lawyers, [[Canter & Siegel|Laurence Canter and Martha Siegel]], began using bulk [[Usenet]] posting to advertise [[immigration]] law services. The incident was commonly termed the \"Green Card spam\", after the subject line of the postings. The two went on to widely promote spamming of both Usenet and e-mail as a new means of advertisement — over the objections of Internet users they labeled \"anti-commerce radicals.\" Within a few years, the focus of spamming (and anti-spam efforts) moved chiefly to e-mail, where it remains today. [http://www.templetons.com/brad/spamterm.html]\n\nThere are two popular [[fake etymology|fake etymologies]] of the word \"spam\". The first, promulgated by Canter & Siegel themselves, is that \"spamming\" is what happens when one dumps a can of [[SPAM]] luncheon meat into a fan blade. The second is the [[backronym]] \"[[shit|\'\'\'s\'\'\'hit]] \'\'\'p\'\'\'osing \'\'\'a\'\'\'s \'\'\'m\'\'\'ail.\"\n\n[[Hormel Foods Corporation]], the makers of SPAM® luncheon meat, do not object to the Internet use of the term \"spamming.\" However, they do ask that the capitalized word \"SPAM\" be reserved to refer to their product and trademark. [http://www.spam.com/ci/ci_in.htm] By and large, this request is obeyed in forums which discuss spam -- to the extent that to write \"SPAM\" for \"spam\" brands the writer as a [[newbie]]. Hormel has, to date, pressed the trademark issue only once -- when a firm registered the trademark \"SpamArrest\" in 2003, Hormel sued to invalidate the mark. [http://www.siliconvalley.com/mld/siliconvalley/6419416.htm]\n\n:See also: [[History of spamming]]\n\n=== Alternate meanings ===\n\nThe term \"spamming\" is also used in the older sense of something repetitious and disruptive by players of [[first-person shooter]] computer games. In this sense it refers to \"area denial\" tactics—repeatedly firing rockets or other explosive shells into an area. Or to any tactic whereby a large volume of ammunition is expended in the hope of scoring a single hit.\n\n[[MUD]], [[MUSH]], and [[MUCK]] players happily continue using the word in its original sense. When a player returns to the terminal after a brief break to find her screen filled with pages of random chat, that\'s still called \"spam\". [http://www.graphxpress.com/cgi-bin/wcotp.cgi?date=19980407]\n\nNeither of these senses of the word imply that the \"spamming\" is abusive.\n\n== Costs of spam ==\n\nSpam\'s direct effects include the consumption of computer and network resources, and the cost in human time and attention of dismissing unwanted messages. In addition, spam has costs stemming from the \'\'kinds\'\' of spam messages sent, from the \'\'ways\'\' spammers send them, and from the \'\'[[arms race]]\'\' between spammers and those who try to stop or control spam.\n\nThe methods of spammers are likewise costly. Because spamming contravenes the vast majority of ISPs\' acceptable-use policies, most spammers have for many years gone to some trouble to conceal the origins of their spam. E-mail, Usenet, and instant-message spam are often sent through insecure [[proxy server]]s belonging to unwilling third parties. Spammers frequently use false names, addresses, phone numbers, and other contact information to set up \"disposable\" accounts at various Internet service providers. In some cases, they have used falsified or stolen [[credit card]] numbers to pay for these accounts. This allows them to quickly move from one account to the next as each one is discovered and shut down by the host ISPs.\n\nThe costs of spam also can be taken to include the collateral costs of the struggle between spammers and the administrators and users of the media threatened by spamming. [http://linxnet.com/misc/spam/thank_spammers.html]\n\nMany users are bothered by spam because it impinges upon the amount of time they spend reading their e-mail. Many also find the content of spam frequently offensive, in that [[pornography]] is one of the most frequently advertised products. Spammers send their spam largely indiscriminately, so pornographic ads may show up in a work place e-mail inbox — or a child\'s, the latter of which is illegal in many jurisdictions.\n\nSome spammers argue that most of these costs could potentially be alleviated by having spammers reimburse ISPs and individuals for their material. There are two problems with this logic: first, the rate of reimbursement they could credibly budget is unlikely to be nearly high enough to pay the cost; and second, the human cost (lost mail, lost time, and lost opportunities) is basically unrecoverable.\n\nE-mail spam exemplifies a [[tragedy of the commons]]: spammers use resources (both physical and human), without bearing the entire cost of those resources. In fact, spammers commonly do not bear the cost at all. This raises the costs for everyone. In some ways spam is even a potential threat to the entire email system, as operated in the past.\n\nSince E-mail is so cheap to send, a tiny number of spammers can saturate the Internet with junk mail. Although only a tiny percentage of their targets are motivated to purchase their products (or fall victim to their scams), the low cost sometimes provides a sufficient conversion rate to keep spamming alive. Furthermore, even though spam appears not to be economically viable as a way for a reputable company to do business, it suffices for professional spammers to convince a tiny proportion of gullible advertisers that it is viable for those spammers to stay in business. Finally, new spammers go into business every day, and the low costs allow a single spammer to do a lot of harm before finally realizing that the business is not profitable.\n\n\n\n== Political issues ==\n\nSpamming remains a hot discussion topic. In fact, many online users have even suggested (presumably jokingly) that cruel forms of [[capital punishment]] would be appropriate for spammers. In 2004, the seized Porsche of an indicted spammer was advertised on the internet, which revealed the extent of the financial rewards available to those who are willing to waste everybody\'s time and was a popular item because the car had been confiscated, which was seen as tough justice, but also sweet vengeance. However, some of the possible ways to stop spamming may lead to other side effects, such as increased government control over the Net, loss of privacy, barriers to free expression or commercialisation of e-mail.\n\nOne of the chief values favored by many long-time Internet users and experts, as well as by many members of the public, is the free exchange of ideas. Many have valued the relative [[anarchy]] of the Internet, and bridle at the idea of restrictions placed upon it. A common refrain from spam-fighters is that spamming itself abridges the historical freedom of the Internet, by attempting to force users to carry the \'\'costs\'\' of material which they would not choose. \n\nAn ongoing concern expressed by parties such as the [[Electronic Frontier Foundation]] and the [[ACLU]] has to do with so-called \"stealth blocking\", a term for ISPs employing aggressive spam blocking without their users\' knowledge. These groups\' concern is that ISPs or technicians seeking to reduce spam-related costs may select tools which (either through error or design) also block non-spam e-mail from sites seen as \"spam-friendly\". [[SPEWS]] is a common target of these criticisms. Few object to the existence of these tools; it is their use in filtering the mail of users who are not informed of their use which draws fire.\n\nSome see spam-blocking tools as a threat to free expression — and laws against spamming as an untoward precedent for regulation or taxation of e-mail and the Internet at large. Even though it is to possible in some jurisdictions to treat some spam as unlawful merely by applying existing laws against [[trespass]] and [[conversion]], some laws specifically targeting spam have been proposed. In [[2004]] United States passed the [[Can Spam Act of 2003]] which provided ISPs and users with tools to combat spam. This act allowed [[Yahoo!]] to successfully sue [[Eric Head]], reportedly one of the biggest spammers in the world, who settled the lawsuit for several thousand US dollars in June 2004. But the law is criticised by many for not being effective enough, and was even supported by some spammers and organizations which support spamming.\n\n==See also==\n\n===Types of spam===\n* [[Email spam]]\n* [[Messaging spam]]\n* [[Newsgroup spam]]\n* [[Spamdexing]]\n* [[Blog spam]]\n* [[Mobile phone spam]]\n\n===Related topics===\n* [[List of e-mail spammers]]\n* [[Email fraud]]\n* [[Make money fast]]\n* [[Advance fee fraud|Nigerian spam]]\n* [[Spam wars]]\n* [[Phishing]]\n* [[Joe job]]\n* [[Hashcash]]\n* [[MAAWG|Messaging Anti-Abuse Working Group]]\n\n===Background===\n* [[Electronic mailing list]]\n* [[Netiquette]]\n* [[Advertising]]\n* [[E-marketing]]\n\n== Newsgroups ==\n\n* \'\'[[news.admin.net-abuse.email]]\'\'\n* \'\'[[news.admin.net-abuse.usenet]]\'\'\n* others in \'\'news.admin.net-abuse.*\'\' hierarchy\n* \'\'alt.spam\'\'\n\n== External links ==\n\n* [[IETF]] views on spamming can be found in [http://www.faqs.org/rfcs/rfc2635.html RFC 2635].\n* [http://www.myTrashmail.com Fake Email Address]. Prevent spamming with a fake email address from myTrashMail\n\n=== Anti-spam organizations ===\n\n* [http://asrg.sp.am/ Anti Spam Research Group]\n* [http://www.cauce.org CAUCE]\n* [http://www.spamhaus.org/ The Spamhaus Project]\n* [http://spam.abuse.net/ spam.abuse.net]\n\n=== More writing on the subject ===\n\n* [http://www.spamfo.co.uk/ Spamfo.co.uk] Latest news on junk email, scams, fraud, legal aspects and reviews of software and services]\n* [http://www.webcogs.com/spam_protection.aspx Spam Protection]\n* [http://www.spamprimer.com/ Getting Rid of Spam]\n* [http://www.spamfaq.net Spam FAQs]\n* [http://www.millersmiles.co.uk Email Scam Reports]\n* [http://bruce.pennypacker.org/spamrules.html The rules of spam, according to net.admin.net-abuse.email]\n* [http://www.spamnews.co.uk/ SpamNews.co.uk Delivering your daily slice of fresh Spam. All the spam news, all the time]\n* [http://alistapart.com/articles/spam/ A List Apart: Win The Spam Arms Race]\n* [http://www.timothywalton.com California lawyer who sues spammers]\n* [http://members.aol.com/emailfaq/mungfaq.html Address Munging FAQ: Spam-Blocking Your E-mail Address]\n* [http://www.millersmiles.co.uk Library of Email Spam Reports and Articles]\n* [http://www.cdt.org/speech/spam/030319spamreport.shtml \'\'Unsolicited Commercial E-mail Research Six Month Report\'\'] by the Center for Democracy & Technology\n* [http://www.ftc.gov/bcp/conline/pubs/alerts/spamalrt.htm \'\'E-mail Address Harvesting: How Spammers Reap What You Sow\'\'] by the Federal Trade Commission\n* [http://www.out-law.com/php/page.php?page_id=pressrele3360&area=about \'\'The spammers are watching you\'\'] by Masons, a London-based international law firm\n* [http://www.internetnews.com/index.php/4491 \'\'The War Against Spam\'\'] — a collection of reading material on the subject\n* [http://shumans.com/archives/000036.php \'\'Yahoo Domain Keys: Another Ineffective Spam Solution\'\'] — shumans.com article, Dec 6, 2003\n* [http://www.pmail.com/spamwp.htm White paper from e-mail client developers]\n* [http://www.antiphishing.org.uk/ Antiphishing Crusade]Daily News of phishing spam collected from around the net.\n* [http://www.scmagazine.com/features/index.cfm?fuseaction=FeatureDetails&newsUID=7e360307-9bb0-485a-ac9a-f938895d83dc&newsType=Features Article by Andy Coote in SC Magazine June 2004]\n* [http://polispam.blogspot.com Political Spam]\n\n=== Popular Anti-Spam Services ===\n*http://www.mailwasher.net\n*http://www.clearswift.com\n*http://www.cloudmark.com\n*http://www.postini.com\n*http://www.proofpoint.com\n*http://www.surfcontrol.com\n*http://www.swirbo.com\n*http://www.tumbleweed.com\n*http://www.lafraia.com.br/spambr/\n\n=== Humor ===\n* [http://spamusement.com/ Spamusement] A collection of humorously drawn cartoons inspired by actual spam subject lines.\n\n\n{{Spamming}}\n\n[[Category:Spamming]][[category:Electronic commerce]][[category:Marketing]][[category:Information technology management]][[category:Business]]\n\n[[ca:Correu brossa]]\n[[cs:Spam]]\n[[da:Spammail]] \n[[de:Spam]] \n[[es:espamaje]] \n[[pt:Spam]]\n[[fr:Spam]] \n[[it:Spamming]] \n[[ja:スパム (メール)]] \n[[nl:Spam]] \n[[pl:Spam]]\n[[ro:Spam]]\n[[ru:Спам]]\n[[simple:Spamming]] \n[[sv:spam]] \n[[zh:垃圾邮件]]\n[[he:דואר_זבל]]','',13,'Budhi','20050218014135','',0,0,0,0,0.184521649873,'20050218014135','79949781985864'); INSERT INTO cur VALUES (2107,0,'E-mail','#redirect [[Electronic mail]]','',13,'Budhi','20041231124655','',0,1,0,1,0.383160617784,'20050315050619','79958768875344'); INSERT INTO cur VALUES (2109,0,'Subjective_probability','#REDIRECT [[Bayesian probability]]','',13,'Budhi','20050101215557','',0,1,0,1,0.296903913414,'20050101215557','79949898784442'); INSERT INTO cur VALUES (2110,0,'Richard_Threlkeld_Cox','\'\'\'Richard Threlkeld Cox\'\'\' ([[1898]] - [[May 2]], [[1991]]) was a professor of [[physics]] at [[Johns Hopkins University]], known for [[Cox\'s theorem]] relating to the foundations of [[probability]]. \n\nHe was born in [[Portland, Oregon]] the son of attorney Lewis Cox and Elinor Junkin Cox. After Lewis Cox died, Elinor Cox married John Latane, who became a professor at Johns Hopkins University in 1913. In 1915 Richard enrolled at JHU to study physics, but his studies were cut short when he was drafted for [[WW I]]. He stayed in the US after being drafted and returned to JHU after the war, completing his BA in 1920. He earned his PhD in 1924; his thesis was \"A Study of Pfund\'s Pressure Gauge\".\n\nHe taught at [[New York University]] (NYU) from 1924 to 1943, before returning to JHU to teach. He studied probability theory, the scattering of electrons, and the discharges of [[electric eel]]s. Richard Cox\'s most important work was Cox\'s Theorem.\n\nHis wife [[Shelby Shackleford]] (1899 [[Halifax, Virginia]] - 1987), who he married in 1926, was an accomplished artist and illustrated Richard\'s books on electric eels.\n\nHis publications included:\n\n* R. T. Cox, \"Probability, Frequency, and Reasonable Expectation,\" \'\'Am. Jour. Phys.,\'\' 14, 1-13, (1946).\n* R. T. Cox, \'\'The Algebra of Probable Inference,\'\' Johns Hopkins University Press, Baltimore, MD, (1961).\n* \'\'Electric Eel Calling\'\' (1941)\n\n== External links ==\n* http://www.jhuapl.edu/maxent2001/001Tribus.doc (MS Word)\n* http://www.jhuapl.edu/maxent2001/richardcox.ppt (MS Power Point presentation)\n\n[[Category:1898 births|Cox, Richard Threlkeld]]\n[[Category:1991 deaths|Cox, Richard Threlkeld]]\n[[Category:Statisticians|Cox, Richard Threlkeld]]\n[[it:Richard Threlkeld Cox]]','',13,'Budhi','20050101215717','',0,0,0,1,0.408330209488,'20050101215717','79949898784282'); INSERT INTO cur VALUES (2111,0,'Demographics','#REDIRECT [[Demografi]]\n','Demographics dipindahkeun ka Demografi',3,'Kandar','20050103070335','',0,1,0,1,0.138178414737,'20050103070335','79949896929664'); INSERT INTO cur VALUES (2112,0,'Demografi','#REDIRECT [[Demografik]]\n','Demografi dipindahkeun ka Demografik',3,'Kandar','20050103081603','',0,1,0,1,0.568855529558,'20050103081603','79949896918396'); INSERT INTO cur VALUES (2113,0,'Statistical_hypothesis_testing','#REDIRECT [[Tes hipotesa statistik]]\n','Statistical hypothesis testing dipindahkeun ka Tes hipotesa statistik',13,'Budhi','20050104012539','',0,1,0,1,0.121013088709,'20050104012539','79949895987460'); INSERT INTO cur VALUES (2114,0,'Tatasurya','Asep Sunandar','',0,'202.51.232.228','20050104210506','',0,0,0,1,0.529195424304,'20050303214455','79949895789493'); INSERT INTO cur VALUES (2115,0,'Measures_of_central_tendency','#REDIRECT [[Central_tendency]]','',13,'Budhi','20050104234039','',0,1,0,1,0.285820492225,'20050303214455','79949895765960'); INSERT INTO cur VALUES (2116,0,'Frequency_distribution','#REDIRECT [[Sebaran frekuensi]]\n','Frequency distribution dipindahkeun ka Sebaran frekuensi',13,'Budhi','20050104234548','',0,1,0,1,0.316783679851,'20050104234548','79949895765451'); INSERT INTO cur VALUES (2117,0,'Standardized_test','Originally a \'\'\'standardized test\'\'\' was simply a standard [[test]] – of academic achievement or of knowledge in a specific academic or vocational domain. It has since acquired the meaning of a written test whose scores are interpreted by reference to the scores of a [[Norm|norm group]] which has taken the test and which is usually considered to be representative of the population which takes the test. For example, standardized tests of academic achievement provide conversion tables showing the [[percentile rank]]s in the norm group of all possible [[raw score]]s. Some standardized tests are now analyzed with [[item response theory]].\n\n==Criticisms of standardized tests==\nStandardized tests are widely used in education, placement, and certification. Their [[Validity (psychometric)|validity]] has been criticized on several grounds.\n\nSome of the criticisms are standard [[Psychometrics|psychometric]] ones. For example, scores on tests of achievement in mathematics problem-solving are often correlated with scores on tests of language ability; this suggests that the mathematics test is actually measuring the linguistic ability required to understand the presentation of the problems rather than the mathematical ability required to solve them. Educational tests also tend to become outdated as curriculum changes.\n\nStandardized tests are also widely criticized as culturally inappropriate for many groups, both in content and in process. It is argued, for example, that in some cultures parents routinely reward children for answering unsolicited questions about the world, and that these children therefore have an advantage on tests of academic achievement. Criticism of content usually centers on the differing relevance of the content to people from different cultures – for example, newly arrived immigrants can be expected to have greater difficulty with an intelligence test which asks them to name past leaders of the country to which they have recently immigrated.\n\nAttempts have been made to develop culture-free and culture-fair (culture-neutral) tests of intelligence, but on the whole these attempts have not been successful. Conceptions of intelligence vary widely from culture to culture, and abstracting the few common elements, or what appear to be the few common elements, cannot be depended on to produce a reliable guide to intelligence. \n\nA common criticism of standardized testing programs in schools is that they encourage teachers to \"teach to the test.\" That is, teachers concentrate on the parts of the curriculum they know will be covered on the test and neglect those that will not. This criticism is certainly worth considering if teachers have foreknowledge of the test and the test is not comprehensive. However, if enough alternative forms of the test are provided, if teachers do not know which form will be used, and if the forms provide a comprehensive sampling of the curriculum, this danger would probably be avoided. Despite the obvious danger of teaching to the test in certain circumstances, though, little research has investigated the prevalence of the phenomenon, or its effects. Furthermore, any form of testing will promote teaching to the test if the consequences of testing are serious.\n\nA related criticism is that students whose teachers train them in test-taking skills unrelated to content will perform better than equally accomplished students whose teachers do not. Some simple test-taking skills can improve scores on multiple-choice standardized tests, so this criticism points to a real danger, especially if standardized tests are used (incorrectly) as the sole measures of achievement or skill. However, little research has investigated the prevalence or effects of this training.\n\nStandardized tests are also criticized for emphasizing recall and recognition rather than higher-order cognitive skills. However, this criticism is not generally valid. While many standardized tests do emphasize recall and recognition, many others assess analytical skills.\n\nAnother criticism is that standardized tests assess inadequate samples of skills. Again, however, this criticism cannot validly be made of all standardized tests, although it can be made about the majority of tests of any type.\n\nLarge-scale attempts have been made to substitute [[Performance assessment (academic)|performance assessment]] or \"authentic\" testing for standardized academic testing. Performance tests require actual performance of a skill; for example, instead of answering questions about a science experiment a student would be required to perform it. However, performance tests have poor [[Reliability (psychometric)|reliability]] simply because they accumulate so little data. Standardized tests have been found to predict scores on performance tests better than other performance tests do.\n\nMuch of the opposition to standardized tests has centred on the incorrect use of these tests. In particular, the use of standardized tests of academic achievement to assess individual students is questionable, given the tests\' reliability – they are simply not accurate enough to provide adequate assessments of individual students by themselves. \n\nPerhaps the most important criticism of standardized testing is that many standardized tests fail to meet the standards of their own field. For example, tests of adult [[literacy]] are widely used although there is little evidence that they assess literacy accurately.\n\n==Advantages of standardized tests==\nPerhaps the simplest advantage of standardized tests is that they are standardized. While some people may systematically score lower on certain tests, these differences will be systematic. On the opposite end of the spectrum, scores on subjective tests change significantly according to whoever is grading them. In the case of college admissions, for example, interviews with prospective students has been repeatedly shown to predict later college performance no better than chance, while statistical measures such as prior [[GPA]] are much more accurate.\n\nOne of the main advantages of standardized testing is that it is able to provide assessments that are psychometrically [[Validity (psychometric)|valid]] and [[Reliability (psychometric)|reliable]], and well as results which are generalizable and replicable.\n\nAnother advantage is aggregation. A well designed standardized test provides an assessment of an individual\'s mastery of a domain of knowledge or skill which at some level of aggregation will provide useful information. That is, while individual assessments may not be accurate enough for practical purposes, the mean scores of classes, schools, branches of a company, or other groups may well provide useful information because of the reduction of error accomplished by increasing the sample size.\n\nWhile standardized tests are often criticized as unfair, the psychometric standards applied in the development of standardized tests would produce fairer testing if applied in other types of testing. In particular, the effectiveness of each test item in accomplishing the goal of the test would have to be demonstrated.\n[[Category:Standardized tests| ]]\n\n[[Category:Education]]','',13,'Budhi','20050104235932','',0,0,0,1,0.044790391705,'20050104235932','79949895764067'); INSERT INTO cur VALUES (2119,0,'Normal-inverse_Wishart_distribution','\'\'\'Téks kandel\'\'\'\'\'Tulisan déngdék\'\'[[Judul tumbu]]\n== Headline text ==\n[[Media:Example.mp3]]Insert non-formatted text here--[[User:128.174.64.41|128.174.64.41]] 20:29, 13 Jan 2005 (UTC)','',0,'128.174.64.41','20050113202958','',0,0,0,1,0.088664131931,'20050303214455','79949886797041'); INSERT INTO cur VALUES (2120,0,'Latin','#REDIRECT [[Basa Latin]]\n','Latin dipindahkeun ka Basa Latin',3,'Kandar','20050114074215','',0,1,0,1,0.012703419151,'20050114074215','79949885925784'); INSERT INTO cur VALUES (2121,0,'Monéra','protozoa\n\n\n{{pondok}}','',0,'202.155.37.50','20050118013920','',0,0,0,0,0.341958640966,'20050303211247','79949881986079'); INSERT INTO cur VALUES (2122,0,'Déwi_Sartika','\'\'\'Déwi Sartika\'\'\' dilahirkeun di Cinéam, Tasikmalaya, [[4 Désémber]] [[1884]], pupus di Tasikmalaya [[11 Séptémber]] [[1947]]. Dileler salaku [[Pahlawan Nasional]] taun [[1966]]. Anjeuna nu munggaran ngadegkeun sakola kanggo kaum wanita di [[Indonesia]]. Ngawitan muka sakola, dina ping [[16 Januari]] [[1904]], anu terasna éta sakola téh dinamian [[Sakola Kautamaan Istri]], atanapi sok seueur ogé nu nyebat sakola Rd. Déwi. Ramana, Patih Bandung, R. A. Somanagara. Nuju anomna Dewi Sartika lebet ka sakola anu murid-muridna téh seuseueurna pameget. Ahirna ku pamaréntah jajahan [[Walanda]], Déwi Sartika dihargaan, salaku wanita Sunda anu gedé kahayangna kanggo ngangkat darajat wanita. Dibanding sareng [[Kartini|R. A. Kartini]], Déwi Sartika mah langkung natrat léngkahna, margi anjeunna mah dina ngaréalisasikeun cita-citana, ngadegkeun atikan formal keur kaum wanita , henteu ngan ukur kahayang atanapi seseratan wungkul. Sigana geus waktuna urang Sunda, utamana kaum wanita Sunda (malah Indonesia), sadar yén kapahlawanan Déwi Sartika téh, perlu dipiéling, digedurkeun jeung diteruskeun deui. Anjeunna anu parantos naratas jeung narétés gawé nyata, tinggal urang misadaran kana jasana.\n\n[[Category:Pahlawan Nasional]]\n{{pondok}}','',3,'Kandar','20050118020010','',0,0,0,1,0.248941292788,'20050303214455','79949881979989'); INSERT INTO cur VALUES (2123,0,'4_Désémber','==Kalahiran==\n[[1884]]\n* [[Déwi Sartika]] babar.\n\n\n{{pondok}}','',3,'Kandar','20050119101628','',0,0,0,1,0.437738625968,'20050303211247','79949880898371'); INSERT INTO cur VALUES (2124,0,'PPM_compression_algorithm','This is a test of the emergency broadcast system','',0,'24.211.162.162','20050120003732','',0,0,0,1,0.046115612455,'20050120003732','79949879996267'); INSERT INTO cur VALUES (2125,1,'Wikipédia:Pitulung','naon atuh ari sunda teh, abdi hoyong terang sareng neuleuman.','',0,'203.77.222.35','20050121152855','',0,0,0,1,0.046694819253,'20050303214455','79949878847144'); INSERT INTO cur VALUES (2128,0,'6_Maret','==Kajadian==\n\n==Kalahiran inohong==\n*[[1911]]: [[Achdiat Karta Mihardja]];\n\n\n{{pondok}}','',3,'Kandar','20050125055134','',0,0,0,1,0.023111433422,'20050303214455','79949874944865'); INSERT INTO cur VALUES (2129,0,'Rumus_prediksi_Spearman-Brown','#REDIRECT [[Rumus prédiksi Spearman-Brown]]\n','Rumus prediksi Spearman-Brown dipindahkeun ka Rumus prédiksi Spearman-Brown',3,'Kandar','20050125103616','',0,1,0,1,0.100082749198,'20050125103616','79949874896383'); INSERT INTO cur VALUES (2130,8,'Speciallogtitlelabel','Judul:','',3,'Kandar','20050126053304','',0,0,0,1,0.186045679053,'20050303214455','79949873946695'); INSERT INTO cur VALUES (2131,8,'Specialloguserlabel','Pamaké:','',3,'Kandar','20050126053319','',0,0,0,1,0.029682124889,'20050303214455','79949873946680'); INSERT INTO cur VALUES (2132,0,'Proton','{| border=\"1\" cellspacing=\"0\" align=\"right\" cellpadding=\"2\" style=\"margin-left:1em\"\n|-\n! align=\"center\" bgcolor=gray | [[Proton]]\n|-\n! align=\"center\" bgcolor=gray | Klasifikasi\n|-\n|\n{| align=\"center\"\n|-\n|[[Partikel subatomik]]\n|-\n|[[Fermion]]\n|-\n|[[Hadron]]\n|-\n|[[Baryon]]\n|-\n|[[Nukléon]]\n|-\n|\'\'Proton\'\'\n|}\n|-\n|\n|-\n! align=\"center\" bgcolor=gray | Sipat\n|-\n|\n|-\n|\n{| align=\"center\"\n|-\n|Massa: \n|938 [[MeV]]/[[Laju cahaya|c]]2\n|-\n|Muatan listrik: \n| 1.6 × 10−19 [[Coulomb|C]]\n|-\n|Spin: \n|1/2\n|-\n|Komposisi [[Quark]]: \n|1 Turun, 2 Naék\n|}\n|}\n\nDina [[fisika]], \'\'\'proton\'\'\' ([[basa Yunani]] \'\'proton\'\' = munggaran) nyaéta [[partikel subatomik]] nu mibanda hiji [[muatan listrik]] fundaméntal positif 1.6 × 10−19 [[coulomb]] sarta massa 938 [[MeV]]/[[laju cahaya|c]]2 ([[1 E-27 kg|1.6726231 × 10−27 kg]], atawa kira 1800 kali massa [[éléktron]]). Proton watekna stabil, nu wates handap [[waktu paruh]]na kira 1035 taun, najan sababaraha téori ngaduga yén [[proton decay|proton bisa luruh]].\n\n[[Inti atom|Inti]] [[isotop]] [[atom]] [[hidrogén]] pangilaharna nyaéta proton tunggal. Inti atom séjén diwangun ku proton jeung [[neutron]] nu kabeungkeut ku [[gaya inti kuat]]. Jumlah proton na inti nangtukeun sipat kimia atom katut kaasup [[unsur kimia]] nu mana.\n\nProton digolongkeun kana [[baryon]] nu diwangun ku dua [[quark]] Naék jeung hiji quark Turun, nu ogé kabeungkeut ku gaya inti nu kuat, nu dimédiasi ku [[gluon]]. Ékivalén [[antizat]] proton nyaéta [[antiproton]], nu mibanda tingkat muatan nu sarua tapi tanda nu sabalikna.\n\nBecause the [[electromagnetic force]] is many [[order of magnitude|orders of magnitude]] stronger than the [[gravitational force]], we see that the charge on the proton must be equal to the charge on the [[electron]], otherwise the net repulsion of having an excess of positive or negative charge (depending on which charge was numerically greater - atoms would not be electrically neutral) would cause a noticeable expansion effect on the universe, and indeed any gravitationally aggregated matter (planets, stars, etc.).\n\nDina [[kimia]] jeung [[biokimia]], istilah \'\'\'proton\'\'\' bisa nujul ka [[ion]] [[hidrogén]]. DIna kontéks ieu, donor proton nyaéta [[asam]], sedengkeun akséptor proton salaku [[basa (kimia)|basa]] (tempo [[téori réaksi asam-basa]]).\n\n==Sajarah==\nProton kapanggih taun [[1918]] ku [[Ernest Rutherford]]. He noticed that when alpha particles were shot into [[nitrogén]] gas, his [[scintillation (physics)|scintillation]] detectors showed the signatures of hydrogen nuclei. Rutherford determined that the only place this hydrogen could have come from was the nitrogen, and therefore nitrogen must contain hydrogen nuclei. He thus suggested that the hydrogen nucleus, which was known to have an atomic number of 1, was an elementary particle. This he named proton, from \'\'protos\'\', the Greek for \"first\".\n\n==Larapan Téhnologis==\nProtons can exist in spin states. This property is exploited by [[nuclear magnetic resonance]] [[spectroscopy]]. In NMR spectroscopy, a magnetic field is applied to a substance in order to detect the shielding around the protons in the nuclei of that substance, which is provided by the surrounding electron clouds. Scientists can use this information to then construct the molecular structure of the molecule under study.\n\n==Tempo ogé==\n*[[fisika partikel]]\n*[[neutron]]\n*[[ranté proton-proton]]\n*[[inhibitor kompa proton]]\n*[[terapi proton]]\n*[[daptar partikel]]\n\n==Tumbu kaluar==\n* [http://pdg.lbl.gov/ Particle Data Group]\n\n[[bg:Протон]]\n[[bs:Proton]]\n[[ca:Protó]]\n[[da:Proton]]\n[[de:Proton]]\n[[en:Proton]]\n[[es:Protón]]\n[[eo:Protono]]\n[[fr:Proton]]\n[[hr:Proton]]\n[[id:Proton]]\n[[ia:Proton]]\n[[it:Protone]]\n[[he:פרוטון]]\n[[la:Proton]]\n[[hu:Proton]]\n[[nl:Proton]]\n[[ja:陽子]]\n[[no:Proton]]\n[[nds:Proton]]\n[[pl:Proton]]\n[[pt:Próton]]\n[[ro:Proton]]\n[[ru:Протон]]\n[[sl:Proton]]\n[[sr:Протон]]\n[[fi:Protoni]]\n[[sv:Proton]]\n[[zh:質子]]\n\n[[Category:Nukléon]]','',3,'Kandar','20050127030545','',0,0,0,0,0.207691433101,'20050127030545','79949872969454'); INSERT INTO cur VALUES (2133,0,'Curug','\'\'\'Curug\'\'\' ilaharna mangrupa bentukan géologis nu dihasilkeun ku cai, biasana dina bentuk [[aliran]], ngamalir dina bentukan batu tahan-[[érosi]] nu pegat \'\'élevasi\'\'na ku ayana [[jurang]]. Curug bisa ogé hasil jijieunan, misalna di [[taman]] jeung ornamén \'\'[[landscape]]\'\'. \n\nCurug nu aya di wewengkon [[pagunungan]] nu érosina cepet bisa ogé mangrupa hasil kajadian alami nu ngadadak. Curug nu kieu bisa jadi lain hasil tina bentukan alam mangtaun-taun, tapi mangrupa hasil prosés géologis nu ngadadak kayaning géséhna kulit Bumi atawa [[gunung api|kajadian vulkanik]].\n[[image:Base of Tower Fall with rainbow-750px.JPG|thumb|right|[[Tower Fall]] in [[Yellowstone National Park]]]]\n\n==Bentukan==\n[[Image:Waterfall_formation.png|frame|none|Waterfall formation]]\nCurug lolobana mangrupa hasil aliran cai nu mangtaun-taun na beungeut lemah. Typically, a stream will flow across an area of formations, and more resistant rock strata will form shelves across the streamway, elevated above the further stream bed when the less erosion-resistant rock around it disappears. Over a period of years, the edges of this shelf will gradually break away and the waterfall will steadily move upstream. Often, the rock strata just below the more resistant shelf will be of a softer type, and will erode out to form a shallow cave-like formation known as a [[rock shelter]] (also known as a rock house) under and behind the waterfall.\n\nStreams often become wider and more shallow just above waterfalls due to flowing over the rock shelf, and there is usually a deep pool just below the waterfall due to the [[kinetic energy]] of the water hitting the bottom.\n\nWaterfalls are a hindrance to river transportation, and so the [[Welland Canal]] was built in [[1829]] to allow ships to pass [[Niagara Falls]] in the [[Great Lakes (North America)|Great Lakes]].\n\n==Tipe curug==\n[[image:waterfall_oregon.jpg|thumb|150px|Cascade-style waterfall in Oregon, United States.]]\nAya istilah-istilah nu dicirikeun pikeun rupa-rupa curug:\n*Blok, nu caina ragrag tina aliran [[walungan]] nu kawilang lega;\n*[[Undak]] (Ing. \'\'cascade\'\'), nu caina ragrag ngaliwatan runtuyan batu undak-undakan;\n*Fan, where the water spreads horizontally as it descends while remaining in contact with [[bedrock]];\n*Horsetail, where descending water maintains some contact with bedrock;\n*Plunge, where the water descends vertically, losing contact with the bedrock surface;\n*Punchbowl, where the water descends in a constricted form, then spreads out in a wider pool;\n*Segmented, where distinctly separate flows of water form as it descends; and\n*Tiered, where water drops in a series of distinct steps or falls.\n
    \n\n==Conto curug-curug baradag==\nCurug pangbadagna di antarana,\n* [[Curug Angel|Curug \'\'Angel\'\']] Amérika Kidul, pangluhurna sadunya (979 m), di [[Vénézuéla]];\n* [[Curug Victoria]] Afrika, pangbadagna sadunya, di [[walungan Zambezi]];\n* [[Curug Boyoma]] Afrika, nu volumena pangbadagna sadunya (17,000 m³/s), di [[walungan Kongo]];\n* [[Curug Yosemite]], pangjangkungna di Amérika Kalér, di [[Taman Nasional Yosemite]];\n* [[Curug Niagara]], pang-\'\'voluminous\'\'-na di Amérika Kalér, di wates antara AS jeung Kanada;\n* [[Curug Rhine]], pangbadagna sa-[[Éropa]], di [[Swis]].\n\n==Tumbu kaluar==\n{{Wiktionary}}\n*[http://www.world-waterfalls.com/ World Waterfall Database]\n*[http://www.panoramas.dk/fullscreen3/f44_niagara.html Niagara Falls - Fullscreen QTVR Panorama]\n\n[[de:Wasserfall]]\n[[en:Waterfall]]\n[[eo:Akvofalo]]\n[[es:Cataratas]]\n[[et:Juga]]\n[[he:מפל מים]]\n[[it:Cascata]]\n[[ja:滝]]\n[[nl:Waterval]]\n[[pl:Wodospad]]\n[[sl:Slap]]\n[[sv:vattenfall]]','',3,'Kandar','20050128070600','',0,0,0,0,0.020239870197,'20050225084322','79949871929399'); INSERT INTO cur VALUES (2134,0,'Evidence','#REDIRECT [[Bukti]]\n','Evidence dipindahkeun ka Bukti',3,'Kandar','20050128043155','',0,1,0,1,0.184969583577,'20050128043155','79949871956844'); INSERT INTO cur VALUES (2135,0,'Computer','#REDIRECT [[Komputer]]\n','Computer dipindahkeun ka Komputer',3,'Kandar','20050128065809','',0,1,0,1,0.004805636586,'20050128065809','79949871934190'); INSERT INTO cur VALUES (2136,0,'Selat_Sunda','\'\'\'Selat Sunda\'\'\' nyaéta [[selat]] antara [[pulo Jawa]] jeung [[pulo Sumatra|Sumatra]] di [[Indonésia]]. Selat ieu ngahubungkeun [[Laut Jawa]] jeung [[Samudra Indonésia]].\n\nLébar dina titik nu pangheureutna--nu aya lebah tungtung kalér sapanjang kira 30 km--kurang-leuwih 30 km. Sedengkeun titik panglébarna, kurang-leuwih sapanjang 100 km, ogé boga jarak 100-an km. Aya sababaraha pulo leutik na selat ieu; gunung [[Anak Krakatau]] aya di salasahijina.\n\nSalaku salasahiji jalur peupeuntasan utama ti [[Laut Cina Kidul]] ka Samudra Indonésia (nu hiji deui nyaéta [[Selat Malaka]]), Selat Sunda geus lila dianggap penting pikeun navigasi. Najan mibanda kalemahan sabab déét jeung loba batuna, tapi nguntungkeun sabab leuwih pondok batan Selat Malaka, sahingga ancaman [[bajak laut]] leuwih leutik.\n\nAwal taun [[1942]] lumangsung [[perang Selat Sunda]], armada [[Jepang]] nu dipingpin ku Laksamana [[Kenzaburo Hara]] ngancurkeun armada Sekutu [[USS Houston (CA-30)|USS \'\'Houston\'\']] jeung [[HMAS Perth (1934)|HMAS \'\'Perth\'\']] nalika nyegat sangkan teu balabuh di Jawa.\n\n[[Category:Selat]]\n[[en:Sunda Strait]]\n[[es:Estrecho de Sunda]]\n[[et:Sunda väin]]\n[[nl:Straat Soenda]]\n[[pl:Cieśnina Sundajska]]','',3,'Kandar','20050129093749','',0,0,1,0,0.011119709847,'20050129093749','79949870906250'); INSERT INTO cur VALUES (2137,0,'Kapuloan_Sunda_Leutik','[[Image:Sunda_Leutik.png|thumb|300px|right|Atlas Kapuloan Sunda Leutik]]\n\n\'\'\'Nusa Tenggara\'\'\', atawa \'\'\'Kapuloan Sunda Leutik\'\'\' nyaéta sakumpulan [[pulo]] di [[Indonésia Wétan]]. Jeung [[Kapuloan Sunda Gedé]] di béh kulon, kapuloan ieu ngabentuk [[Kapuloan Sunda]].\n\n==Pamaréntahan==\n\nKapuloan Sunda Leutik kabagi kana propinsi-propinsi [[Indonésia]] ([[Bali]], [[Nusa Tenggara Kulon]], jeung [[Nusa Tenggara Wétan]]) jeung nagara merdika [[Timor Wétan]].\n\n==Daptar parsial==\n* [[Adonara]]\n* [[Alor]]\n* [[Bali]]\n* [[Flores]]\n* [[Komodo]]\n* [[Lombok]]\n* [[Palu\'e]]\n* [[Rote]]\n* [[Solor]]\n* [[Sumba]]\n* [[Sumbawa]]\n* [[Timor]]\n\n==Tempo ogé==\n* [[Nusantara]]\n\n[[Category:Nusantara]]\n{{pondok}}\n\n[[de:Kleine Sunda-Inseln]]\n[[en:Lesser Sunda Islands]]\n[[et:Väikesed Sunda saared]]\n[[id:Kepulauan Sunda Kecil]]\n[[pl:Małe Wyspy Sundajskie]]','',3,'Kandar','20050315043906','',0,0,1,0,0.002459397626,'20050315043906','79949684956093'); INSERT INTO cur VALUES (2138,0,'Kapuloan_Sunda_Gedé','\'\'\'Kapuloan Sunda Gedé\'\'\' nyaéta sakumpulan [[pulo]] di [[Indonésia]] Kulon nu ngawengku,\n\n*[[Kalimantan]] atawa Bornéo\n*[[Jawa (pulo)|Jawa]]\n*[[Sulawesi]]\n*[[Sumatra]]\n\nKumpulan ieu sacara politis kabagi ku utamana Indonésia, [[Brunéi]], jeung [[Malaysia]].\n\nMun digabungkeun jeung [[Kapuloan Sunda Leutik]] di béh wétan, mangka kapuloan ieu jadi wangunan [[Kapuloan Sunda]].\n\n==Tempo ogé==\n* [[Nusantara]]\n\n\n{{pondok}}\n[[de:Große Sunda-Inseln]]\n[[en:Greater Sunda Islands]]\n[[id:Kepulauan Sunda Besar]]\n[[ja:大スンダ列島]]','',3,'Kandar','20050315043301','',0,0,1,0,0.157972109207,'20050315043301','79949684956698'); INSERT INTO cur VALUES (2139,0,'Kapuloan_Sunda','\'\'\'Kapuloan Sunda\'\'\' nyaéta sakumpulan gugusan [[pulo]] di wewengkon kulon [[Nusantara]], nu kabagi kana dua kumpulan:\n\n*[[Kapuloan Sunda Gedé]]\n**[[Kalimantan]]\n**[[Jawa (pulo)|Jawa]]\n**[[Sumatra]]\n*[[Kapuloan Sunda Leutik]], ti kulon ka wétan\n**[[Bali]]\n**[[Lombok]]\n**[[Sumbawa]]\n**[[Florés]]\n**[[Sumba]]\n**[[Timor]]\n**[[Kapuloan Barat Daya]]\n**[[kapulona Tanimbar]]\n\nGugusan ieu sacara pulitik kabagi ku [[Indonésia]] (utama), [[Brunei]], [[Timor Wétan]], jeung [[Malaysia]].\n\n==Tempo ogé==\n* [[Nusantara]]\n\n[[de:Sunda-Inseln]]\n[[en:Sunda Islands]]\n[[no:Sundaøyene]]\n\n[[Category:Kapuloan]]\n{{pondok}}','',3,'Kandar','20050129101159','',0,0,0,0,0.593993214438,'20050303211247','79949870898840'); INSERT INTO cur VALUES (2140,10,'NCBI-scienceprimer','\'\'Artikel ieu ngandung bahan-bahan ti [http://www.ncbi.nlm.nih.gov/About/Primer Science Primer] nu medal ti NCBI, nu, salaku publikasi pamaréntah AS, aya dina [[domain publik]] [http://www.ncbi.nlm.nih.gov/About/disclaimer.html (1)].','',3,'Kandar','20050201034245','',0,0,0,1,0.498939654187,'20050303214455','79949798965754'); INSERT INTO cur VALUES (2141,0,'Metre','#REDIRECT [[Méter]]\n','Metre dipindahkeun ka Méter',3,'Kandar','20050201050325','',0,1,0,1,0.08091748781,'20050201050325','79949798949674'); INSERT INTO cur VALUES (2142,6,'Sél_biologis.png','Ti Wikipédia Inggris','Ti Wikipédia Inggris',3,'Kandar','20050201062108','',0,0,0,1,0,'20050201062108','79949798937891'); INSERT INTO cur VALUES (2144,0,'Econometrics','#REDIRECT [[Ékonométri]]\n','Econometrics dipindahkeun ka Ékonométri',3,'Kandar','20050202082526','',0,1,0,1,0.230938203778,'20050202082526','79949797917473'); INSERT INTO cur VALUES (2145,0,'Bledug_Kuwu','[[Image:Bledug_Kuwu.jpg|thumb|200px|right|Bledug Kuwu]]\n\'\'\'Bledug kuwu\'\'\' nyaéta hiji fénoména gunung api leutak (\'\'mud volcanoes\'\') nu aya di Désa Kuwu, Kacamatan Kradenan, Kabupatén [[Purwodadi]], [[Propinsi Jawa Tengah]]. Bituna ieu leutak ngandung uyah sarta ;umangsung ampir terus-terusan.\n\n==Legenda==\nNurutkeun carita, Bledug Kuwu téh liangna nyambung nepi ka Laut Kidul. Liang ieu mangrupa torowongan urut jalan balik Jaka Linglung ti Laut Kidul ka Karajaan Medang Kamulan satutasna manéhna ngéléhkeun Prabu Déwata Cengkar nu geus robah jadi buhaya bodas di Laut Kidul. Jaka Linglung bisa nyieun liang sarupa kitu sabab manéhna bisa ngarupakeun oray naga salaku sarat sangkan diaku salaku anak [[Aji Saka]].\n\n==Géologi==\n[[Image:gunung_api_leutak.jpg|thumb|200px|right|Skéma fénoména gunung api leutak]]\nSacara [[géologi|géologis]], fénoména gunung api leutak ieu teu anéh. Di tempat séjén loba kajadian nu sarupa kieu, di antarana di [[Palo Seco]], [[Républik Trinidad & Tobago]], [[Afrika]].\n\n==Kandungan uyah==\nAyana Bledug Kuwu ieu, nu caina ngandung uyah, ku masarakat sabudeureunana dimangpaatkeun pikeun bahan nyieun uyah sacara tradisional. Carana ku nampung cai tina Bledug Kuwu kana \'\'glagah\'\' ([[awi]] nu dibeulah dua), lajeng digaringkeun.\n\n\n[[id:Bledug Kuwu]]','',3,'Kandar','20050202100805','',0,0,0,0,0.021557989891,'20050202100805','79949797899194'); INSERT INTO cur VALUES (2146,2,'Shikai_shaw','\'\'\'Shikai_shaw\'\'\' ([[w:ja:利用者:Shikai shaw|shikai shaw]]) is a Japanese Wikipedian.\n\n== Other Wikimedia Project ==\n* [[m:User:Shikai shaw|Meta-Wiki]] \n* [[commons:User:Shikai shaw|Wikimedia Commons]] \n* [[wikt:en:User:Shikai shaw|Wiktionary (English)]] \n** [[wikt:ja:利用者:Shikai shaw|Wiktionary (Japanese)]] \n* [[b:en:User:Shikai shaw|Wikibooks (English)]] \n** [[b:ja:利用者:Shikai shaw|Wikibooks (Japanese)]] \n* [[q:en:User:Shikai shaw|Wikiquote (English)]] \n** [[q:ja:利用者:Shikai shaw|Wikiquote (Japanese)]] \n* [[wikisource:User:Shikai shaw|Wikisource]] \n* [[wikispecies:User:Shikai shaw|Wikispecies]] \n\n[[af:Gebruiker:Shikai shaw]] \n[[als:Benutzer:Shikai shaw]] \n[[ang:User:Shikai shaw]] \n[[ar:مستخدم:Shikai shaw]] \n[[ast:User:Shikai shaw]] \n[[be:User:Shikai shaw]] \n[[bg:Потребител:Shikai shaw]] \n[[bs:User:Shikai shaw]] \n[[ca:Usuari:Shikai shaw]] \n[[cs:Wikipedista:Shikai shaw]] \n[[csb:User:Shikai shaw]] \n[[cy:Defnyddiwr:Shikai shaw]] \n[[da:Bruger:Shikai shaw]] \n[[de:Benutzer:Shikai shaw]] \n[[el:User:Shikai shaw]] \n[[en:User:Shikai shaw]] \n[[eo:Vikipediisto:Shikai shaw]] \n[[es:Usuario:Shikai shaw]] \n[[et:Kasutaja:Shikai shaw]] \n[[eu:User:Shikai shaw]] \n[[fa:کاربر:Shikai shaw]] \n[[fi:Käyttäjä:Shikai shaw]] \n[[fo:Brúkari:Shikai shaw]] \n[[fr:Utilisateur:Shikai shaw]] \n[[fy:Brûker:Shikai shaw]] \n[[ga:Úsáideoir:Shikai shaw]] \n[[gd:User:Shikai shaw]] \n[[gl:User:Shikai shaw]] \n[[he:משתמש:Shikai shaw]] \n[[hi:सदस्य:Shikai shaw]] \n[[hr:User:Shikai shaw]] \n[[hu:User:Shikai shaw]] \n[[ia:Usator:Shikai shaw]] \n[[id:Pengguna:Shikai shaw]] \n[[ie:User:Shikai shaw]] \n[[is:Notandi:Shikai shaw]] \n[[it:Utente:Shikai shaw]] \n[[ja:利用者:Shikai shaw]] \n[[jv:User:Shikai shaw]] \n[[kn:User:Shikai shaw]] \n[[ko:사용자:Shikai shaw]] \n[[ks:User:Shikai shaw]] \n[[ku:User:Shikai shaw]] \n[[kw:User:Shikai shaw]] \n[[la:Usor:Shikai shaw]] \n[[lb:User:Shikai shaw]] \n[[lt:User:Shikai shaw]] \n[[lv:User:Shikai shaw]] \n[[mi:User:Shikai shaw]] \n[[ml:User:Shikai shaw]] \n[[ms:Pengguna:Shikai shaw]] \n[[nds:User:Shikai shaw]] \n[[nl:Gebruiker:Shikai shaw]] \n[[nn:Brukar:Shikai shaw]] \n[[no:Bruker:Shikai shaw]] \n[[oc:Utilisator:Shikai shaw]] \n[[pl:Wikipedysta:Shikai shaw]] \n[[pt:Usuário:Shikai shaw]] \n[[ro:Utilizator:Shikai shaw]] \n[[ru:Участник:Shikai shaw]] \n[[sa:User:Shikai shaw]] \n[[scn:User:Shikai shaw]] \n[[simple:User:Shikai shaw]] \n[[sk:Redaktor:Shikai shaw]] \n[[sl:Uporabnik:Shikai shaw]] \n[[sr:Корисник:Shikai shaw]] \n[[sv:Användare:Shikai shaw]] \n[[ta:பயனர்:Shikai shaw]] \n[[th:ผู้ใช้:Shikai shaw]] \n[[tl:User:Shikai shaw]] \n[[tokipona:User:Shikai shaw]] \n[[tr:User:Shikai shaw]] \n[[tt:Äğzä:Shikai shaw]] \n[[uk:Користувач:Shikai shaw]] \n[[ur:User:Shikai shaw]] \n[[vi:User:Shikai shaw]] \n[[wa:Uzeu:Shikai shaw]] \n[[zh:User:Shikai shaw]] \n[[zh-cn:User:Shikai shaw]] \n[[zh-min-nan:User:Shikai shaw]] \n[[zh-tw:User:Shikai shaw]] ','interwiki',37,'Shikai shaw','20050203012329','',0,0,1,1,0.256632297582,'20050303214455','79949796987670'); INSERT INTO cur VALUES (2147,0,'Kastroli','\'\'\'Kastroli\'\'\' atawa \'\'\'minyak kastroli\'\'\' nyaéta [[minyak sayur]] nu dihasilkeun tina [[castor bean]] (atawa \'\'castor seed\'\', sabab tangkal \'\'castor\'\' (\'\'Ricinus communis\'\' L.) teu kaasup kulawarga [[kacang]]).\n\nMinyak kastroli versatil pisan sarta ahéng komposisina, sabab ngandung 90% asam lemak risinoléat C:18 [[lemak teu jenuh|teu jenuh]]. It is a major source of [[sebacic acid]].\n\nCastor oil and its derivatives have major applications in the manufacturing of [[soap]]s, [[lubricant]]s, hydraulic and [[brake fluid]]s, [[paint]]s, [[dye]]s, [[coating]]s, [[ink]]s, cold resistant [[plastics]], [[wax]]es and polishes, [[nylon]], [[pharmaceuticals]] and [[perfume]]s.\n\nThe [[poison]] [[ricin]] is made from the byproducts in the manufacture of castor oil.\n\nAbout 1% of the global castor oil production goes into medical or health store products. It is used to ease [[constipation]] and as an [[emetic]] to induce [[vomit]]ing. Consumption of large amounts of castor oil (below lethal doses, such as one bottle) can induce [[Childbirth|labor]] in near-term [[pregnancy|pregnant]] women. It is notorious for its strong taste, which was for many years a standard gag in [[comic strip]]s and \'\'[[Our Gang]]\'\' [[film shorts]].\n\n== Castor oil as a tool of political terror ==\n{{Wiktionary}}\nIn [[Fascism|Fascist]] [[Italy]] under the regime of [[Benito Mussolini]], castor oil was one of the tools of the [[blackshirts]]. Political dissidents would be force-fed large dosages of castor oil by Fascist thugs. This technique was said to have been originated by [[Gabriele D\'Annunzio]]. Victims of this treatment would experience severe [[diarrhea]] and [[dehydration]], often resulting in death. \n\nSometimes when the blackshirts wished to make sure that the victim would die rather than simply be badly disabled, they would mix [[gasoline]] with the castor oil.\n\nIt came to be said that Mussolini\'s power was backed by \"the [[bludgeon]] and castor oil\".\n\n[[en:Castor oil]]','',3,'Kandar','20050203050836','',0,0,0,1,0.060470395143,'20050225084322','79949796949163'); INSERT INTO cur VALUES (2148,0,'Optimization_(mathematics)','#REDIRECT [[Optimisasi (matematik)]]\n','Optimization (mathematics) dipindahkeun ka Optimisasi (matematik)',3,'Kandar','20050203084259','',0,1,0,1,0.011612283342,'20050203084259','79949796915740'); INSERT INTO cur VALUES (2149,14,'Matematik','\'\'\'Matematik\'\'\' sacara umum dihartikeun salaku ulikan [[pola]] struktur, [[parobahan]], jeung [[ruang]]; jéntréna, urang bisa nyebut ulikan ngeunaan \'gambar jeung angka\'.\n\nDi handap ieu mangrupa daptar jejer dina widang matematik:','',3,'Kandar','20050203102033','',0,0,0,1,0.210720960653,'20050316082300','79949796897966'); INSERT INTO cur VALUES (2151,0,'Hujan','[[Image:22 Regen ubt.jpeg|thumb|250px|right|Rain falling]]\n[[Image:Umbrella with raindrops.jpg|thumb|250px|right|Rain on an umbrella]]\n\n\'\'\'Hujan\'\'\' nyaéta hiji bentuk [[Présipitasi (météorologi)|présipitasi]], kawas [[salju]]. Hujan lumangsung nalika [[cai]] ngareclak ragrag kana beungeut [[Marcapada|Bumi]] tina [[awan]]. Teu sadaya hujan nepi kana lemah, sawaréhna nguap nalika ragrag ngaliwatan hawa garing, hiji tipe présipitasi nu disebut [[virga]].\n\nHujan maénkeun peran utama dina [[daur hidrologis]] in which [http://wiktionary.org/wiki/moisture moisture] from the [[ocean]]s evaporates, condenses into clouds, precipitates back to earth, and eventually returns to the ocean via streams and [[river]]s to repeat the cycle again.\n\nThe amount of rainfall is measured using a [[rain gauge]]. It is expressed as the depth of water that collects on a flat surface, and can be measured to the nearest 0.25 mm or 0.01 in. It is sometimes expressed in litres per square metre (1 L/m² = 1 mm).\n\nFalling raindrops are often described as \"tear-shaped\", round at the bottom and narrowing towards the top, but this is incorrect (only drops of water dripping from some sources are tear-shaped at the moment of formation). Small raindrops are nearly [[sphere|spherical]]. Larger ones become increasingly flattened, like [[hamburger]] buns; very large ones are shaped like [[parachute]]s. On average, raindrops are 1 to 2 mm in diameter. The biggest raindrops on Earth were recorded over [[Brazil]] and the [[Marshall Islands]] in [[2004]] - some of them were as large as 10 mm. The large size is explained by condensation on large [[smoke]] particles or by collisions between drops in small regions with particularly high content of liquid water.\n\nSeveral cultures have developed means of dealing with rain and have developed numerous protection devices such as [[umbrella]]s and [[raincoat]]s. Many people also prefer to stay inside on rainy days, especially in tropical climates where rain is usually accompanied by [[thunderstorm]]s.\n\nGenerally, rain has a [[pH|\'\'p\'\'H]] slightly under 6, simply from absorption of atmospheric [[carbon dioxide]], which dissociates in the droplet to form minute quantities of [[carbonic acid]]. In some desert areas, airborne dust contains enough [[calcium carbonate]] to counter the natural acidity of precipitation, and rainfall can be neutral or even [[alkaline]]. Rain below \'\'p\'\'H 5.6 is considered [[acid rain]].\n\n==Budaya==\nCultural attitudes towards rain differ across the world. In the [[Western world]], rain traditionally has a sad and negative connotation, in contrast to the bright and happy [[sun]]. In other places such as [[India]], the rain is greeted with [[euphoria]].\n\n==Tempo ogé==\n*[[Daur cai]]\n*[[Sumberdaya cai]]\n*[[Cuaca]]\n*[[Iklim]]\n\n[[Category:Cuaca]]\n\n[[ca:Pluja]]\n[[da:Regn]]\n[[de:Regen]]\n[[en:rain]]\n[[eo:Pluvo]]\n[[es:Lluvia]]\n[[fi:sade]]\n[[fr:Pluie]]\n[[he:גשם]]\n[[it:Pioggia]]\n[[nl:Regen]]\n[[id:hujan]]\n[[ja:雨]]\n[[ms:hujan]]\n[[pl:Deszcz]]\n[[sr:Киша]]\n[[simple:Rain]]\n[[sv:Regn]]\n[[zh:雨]]\n[[Category:Forms of water]]','',3,'Kandar','20050203164811','',0,0,0,1,0.120265258714,'20050303214455','79949796835188'); INSERT INTO cur VALUES (2152,0,'Wikipédia:Kuncén','\'\'\'Kuncén\'\'\' (pituinna mah \'\'\'administratur\'\'\') disebut ogé \'\'sysop\'\'. Anjeun bisa ngajukeun pamundut na kaca ieu pikeun hal-hal nu ngan bisa dipigawé ku kuncén.\n\nMun anjeun hayang ngahapus hiji kaca, béjakeun na kaca [[Wikipédia:Proposal ngahapus]].\n\nKuncén wenang migawé sababaraha hal nu teu bisa dipigawé ku pamaké séjén. Hal ieu ditujukeun pikeun alesan kinerja (mun kabéh pamaké bisa, jalaloka ieu bakal laun pisan jalanna). Ogé pikeun alesan kaamanan (hartina kuncén mah geus kapercaya). Mun anjeun hayang jadi kuncén, tepikeun baé di dieu.\n\nSing saha baé nu geus ngeusian jalaloka ieu diwenangkeun jadi kuncén, teu aya masalah.\n\nKuncén teu mibanda kawenangan husus, sarua baé jeung nu séjén.\n\nNu bisa dipigawé ku kuncén, nyaéta,\n*ngahapus kaca\n*ngonci eusi kaca\n*muka konci eusi kaca\n*ngédit kaca nu dikonci\n*meungpeuk pamaké nu ngaruksak loka.\n\n\n==Kaca-kaca penting pikeun kuncén==\n*[[Wikipédia:Kawijakan]]\n*[[Wikipédia:Vandalisme nu keur lumangsung]]\n*[[Wikipédia:Peungpeuk]]\n*[[Wikipedia:Proposal ngahapus]]\n*[[Wikipédia:Kawijakan ngahapus]]\n*[[Wikipédia:Kawijakan ngajaga]]\n\n==Daptar kuncén==\nMangga langsung buka kaca \'\'\'[[Special:Listadmins|Daptar kuncén]]\'\'\'.\n\n==Isu jeung pamundut kiwari==\n\nPamaké bisa ménta ka kuncén di dieu pikeun ngajaga kaca. Pamundut pikeun ngahapus kaca mangga tulis di [[Wikipédia:Proposal ngahapus]], sedengkeun pikeun meungpeuk na kaca [[Wikipédia:Vandalisme nu keur lumangsung]].\n\nSadaya kuncén kudu ngawaskeun bagian ieu pikeun isu-isu nu mémang sakuduna kuncén awas, sarta pikeun wawar ngeunaan parobahan kawijakan nu mangaruhan kuncén.\n\n==Tempo ogé==\n*[[meta:Administrators of various Wikipedias|Kuncén lintas Wikipédia]]\n\n[[Category:Wikipédia]]\n\n[[bg:Уикипедия:Администратори]]\n[[ca:Viquipèdia:Administradors]]\n[[cs:Wikipedie:Správci]]\n[[da:Wikipedia:Administratorer]]\n[[de:Wikipedia:Administratoren]]\n[[el:Wikipedia:Διαχειριστές]]\n[[en:Wikipedia:Administrators]]\n[[eo:Vikipedio:Administrantoj]]\n[[es:Wikipedia:Administradores]]\n[[eu:Wikipedia:Administratzaileak]]\n[[fi:Wikipedia:Ylläpitäjät]]\n[[fo:Wikipedia:Umboðsstjóri]]\n[[fr:Wikipédia:Administrateurs]]\n[[ga:Vicipéid:Riarthóirí]]\n[[he:ויקיפדיה:מפעיל מערכת]]\n[[id:Wikipedia:Pengurus]]\n[[is:Wikipedia:Stjórnendur]]\n[[it:Wikipedia:Amministratori]]\n[[ja:Wikipedia:管理者]]\n[[ko:위키백과:관리자]]\n[[lb:Wikipedia:Administrators]]\n[[na:Wikipedia:Administrators]]\n[[nl:wikipedia:systeembeheerders]]\n[[no:Wikipedia:Administratorer]]\n[[pl:Wikipedia:Administratorzy]]\n[[pt:Wikipedia:Administradores]]\n[[ru:Википедия:Administrators]]\n[[simple:Wikipedia:Administrators]]\n[[sl:Wikipedija:Administratorji]]\n[[sr:%D0%92%D0%B8%D0%BA%D0%B8%D0%BF%D0%B5%D0%B4%D0%B8%D1%98%D0%B0:%D0%90%D0%B4%D0%BC%D0%B8%D0%BD%D0%B8%D1%81%D1%82%D1%80%D0%B0%D1%82%D0%BE%D1%80%D0%B8]]\n[[sv:Wikipedia:Administrat%F6rer]]\n[[vi:Wikipedia:Người quản lý]]\n[[zh:Wikipedia:管理员]]','/* Tempo ogé */',3,'Kandar','20050308091842','move=:edit=',0,0,1,0,0.347715117503,'20050308091842','79949691908157'); INSERT INTO cur VALUES (2154,0,'Wikipédia:_Kaca_nu_dijaga','[[Wikipédia:Kuncén|Kuncén]] wenang \"ngajaga\" kaca atawa gambar sahingga teu bisa dirobah iwal ku sasama kuncén. Kawenangan ieu ngan dipaké dina kaayaan husus.\n\n==Kawijakan==\n#Ulah ngédit kaca nu samentara dijaga.\n#Ulah ngajaga kaca nu nu anjeun pribadi kalibet dina éditan nu mibanda masalah.\n\nTempo [[Wikipédia: Kawijakang ngajaga]] pikeun saran nu leuwih rinci sarta tujuan kaca nu dijaga.\n\n==Prosedur==\n#Jaga kacana, béré alesan.\n#Tambahkeun {{protected}} (atawa {{vprotected}} pikeun vandalisme) lebah luhur kaca nu samentara dijaga sarta dadarkeun naon masalahna dina ringkesan ngédit.\n#Daptarkeun kaca nu dijaga éta kana \'\'Wikipédia: Kaca nu dijaga\'\'; mun ngajaga ieu alatan konflik, anjeun bisa ogé ngadaptarkeun \'\'sadaya\'\' pamaké/IP nu kalibet konflik.\n#Téang kasapukan di antara nu konflik.\n#Piceun pangjaga (béré alesan) mun konflikna geus réngsé.\n#Leungitkeun {{protected}} tina punclut kaca nu teu dijaga sarta écéskeun kateranganana dina ringkesan ngédit.\n\n==Tempo ogé==\n* [[Wikipedia:Requests for page protection|Requests for page protection]] - place to request protection; use when your involvement in editing a page precludes protecting it yourself. Also used by non-administrators who wish for a page to be protected.\n* [[Special:Log/protect|Protection log]] - automated log of protections and unprotections\n* [[Wikipedia:This page is protected|This page is protected]]\n* [[Wikipedia:Wikipedia_maintenance#Protected_pages|Wikipedia maintenance section on maintaining this page]]\n* [[Wikipedia:Most vandalized pages]] - please add pages subjected to repeated vandalism to this list\n* [[m:Protected pages considered harmful]] - essay\n* [[m:The Wrong Version]] - semi-humorous essay about revert warriors\' perception of page protection\n\n== Rationale ==\nSee [[meta:Protected pages considered harmful]], [[meta:edit wars]]\n\n==Némbongkeun sumber kaca nu dijaga==\nPikeun némbongkeun sumber, misalna [[Tepas]], paké salasahiji cara d handap:\n\n*{{SERVER}}{{localurl:Tepas|action=edit}}\n*[[Special:Export/Tepas]]\n\nNu kadua mah sakaligus méré [[metadata]] (tempo [[m:page metadata]]) ngeunaan éditan panungtungan. Hasilna mangrupa koropak [[XML]]; tags are coded in its source, and plainly shown when rendered by the browser. However, blank lines in the wikisource are shown in the xml-source, but not in the rendering.\n\n== List of protected pages ==\nIf you protect a page, or find a protected page not listed here, please add it to this list. Please also add a \'\'\'short\'\'\' description of ten words or less indicating why you protected it. If you need to say more, discuss on the talk page of the page you protected. Also see the [[Special:Log/protect|protection log]] for recent unprotections, which replaces the manual list of recently unprotected pages. The {{protected}} header automatically adds [[:Category:Protected]] to the page, adding it to the Category\'s listing.\n\n===Pages protected due to edit wars or vandalism===\n\n===Images protected while on the [[Main Page]]===\nImages on the main page often become the target of vandalism, particularly being overwritten with [[shock site]] images, which harms the credibility of the project due to that page\'s extreme visibility. Also, it takes some time for sysops to determine what caused a main page change. As such, images have begun to be protected during their time there, and this has become a [[de facto]] policy since the second or third week of November 2004. \n\nIn order to keep track of these images, please add {{[[template:mpimgprotected|mpimgprotected]]}} to them. This will add the image to [[:Category:Protected main page images]]. There are typically 4 to 5 images on the main page, although some of them may be from the [[m:Wikicommons|Wikicommons]].\n\n===Permanently/semi-permanently protected pages and images===\n====Alesan \'\'visibility\'\'====\n*[[Tepas]] (dijaga tina vandalisme). Sawalakeun sagala parobahan Tepas dina [[Talk:Tepas|kaca sawalana]]\n*[[:Image:Wiki.png]] jeung [[:Image:Wiki.PNG]] (lambang Wikipedia)\n*[[MediaWiki:Sitenotice]]\n*Citakan pikeun artikel fitur kiwari - [[Wikipédia: Artikel fitur poé ieu/{{CURRENTDAY}} {{CURRENTMONTHNAME}} {{CURRENTYEAR}}]]\n*[[Template:Wikipedialang]]\n*[[Template:Wikipediasister]]\n*[[Template:Donate]]\n*[[Template:Newpagelinksmain]]\n*[[Template:TFAfooter]]\n\n====Legal reasons====\n*[[Wikipedia:Copyrights]], [[Wikipedia:Text of the GNU Free Documentation License]] (copyright and license pages)\n*[[Text of the GNU Free Documentation License]] (redirect to the above)\n*Press releases: [[Wikipedia:Press releases/January 2002|January 2002]], [[Wikipedia:Press releases/January 2003|January 2003]], [[Wikipedia:Press releases/February 2004|February 2004]] (should remain static indefinitely)\n** [[Wikipedia:Press releases/February 2004/Text-Only]]\n*[[Wikipedia:designated agent]] (see [[meta:designated agent]])\n*[[Wikipedia:Foldoc license]]\n*[[Wikipedia:Donation addresses]] (It should not be possible to falsify donation addresses.)\n*[[Wikipedia:Site support]]: Should be a link to the Foundation site, should not be changed, should not be possible to have donations going elsewhere. (This was linked from the sidebar and might still be in some skins.)\n*[[Wikipedia:General disclaimer]] (linked from every article. It also needs to keep its precise wording in order to protect us and warn our readers.)\n**[[Wikipedia:Risk disclaimer]] - (linked to from the General disclaimer)\n**[[Wikipedia:Legal disclaimer]] (same)\n**[[Wikipedia:Medical disclaimer]] (same)\n**[[Wikipedia:Content disclaimer]] (same)\n\n====Alesan administrasi sistim====\n*[[Wikipedia:Block log/Archive1]]\n*[[Wikipedia:Blocked IPs]]\n*[[Wikipedia:Popular articles]]\n*[[Wikipedia:Village pump archive 2004-09-26|Village pump archive 2004-09-26]] (to prevent page move vandalism of large history)\n\nKaca-kaca di handap ieu dijieun otomatis sarta biasana dijaga pikeun alesan administrasi sistim:\n*Log otomatis: [[Wikipedia:Deletion log|Log hapusan]], [[Wikipedia:Upload log|Long ngamuat]], [[Wikipedia:Protection log|Log pangjaga]], [[Wikipedia:Block log|Log peungpeuk]], [[Wikipedia:Bureaucrat log|Log birokrat]], katut arsipna\n*[[Wikipedia:All pages by title]] (for [[Special:Allpages]])\n*[[Wikipedia:!Long articles]] (for [[Special:Longpages]])\n*[[Wikipedia:!Most wanted articles]] (for [[Special:Wantedpages]])\n*[[Wikipedia:!Orphaned articles]] (for [[Special:Lonelypages]])\n*[[Wikipedia:!Dead-end pages]] (for [[Special:Deadendpages]])\n*[[Wikipedia:!Short articles]] (for [[Special:Shortpages]])\n*Sadaya kaca na [[Wikipedia:MediaWiki namespace|spasingaran MédiaWiki]] iwal [[Wikipedia:Unprotected MediaWiki messages|nu teu dijaga]].\n\n====Various template pages====\n*[[Template:Cc-by]]\n*[[Template:Cc-by-nc]]\n*[[Template:Cc-by-nc-sa]]\n*[[Template:Cc-by-nd]]\n*[[Template:Cc-by-nd-nc]]\n*[[Template:Cc-by-sa]]\n*[[Template:Cc-nc]]\n*[[Template:Cc-nc-sa]]\n*[[Template:Cc-nd]]\n*[[Template:Cc-sa]]\n*[[Template:Controversial]]\n*[[Template:Copyrighted]]\n*[[Template:CopyrightedFreeUse]]\n*[[Template:CopyrightedFreeUseProvided]]\n*[[Template:CrownCopyright]]\n*[[Template:Disambig]]\n*[[Template:Disputed]]\n*[[Template:Fairuse]]\n*[[Template:GFDL]]\n*[[Template:GPL]]\n*[[Template:Ifd]]\n*[[Template:LGPL]]\n*[[Template:LandRegistryCopyright]]\n*[[Template:LearningandSkillsCouncilCopyright]]\n*[[Template:NHSCopyright]]\n*[[Template:NPOV]]\n*[[Template:NationalAuditOfficeCopyright]]\n*[[Template:Noncommercial]]\n*[[Template:PAphoto]]\n*[[Template:PD]]\n*[[Template:PD-US]]\n*[[Template:PD-USGov]]\n*[[Template:PermissionAndFairUse]]\n*[[Template:QualificationsandCurriculumAuthorityCopyright]]\n*[[Template:Sandbox]]\n*[[Template:Sitesupportpage]]\n*[[Template:TeacherTrainingAuthorityCopyright]]\n*[[Template:Unverified]]\n*[[Template:Verifieduse]]\n*[[Template:Vandal]]\n*[[Template:Vprotected]]\n\n===Kaca pamaké===\nKaca pamaké kadang jadi sasaran [[Wikipédia: Vandalisme|vandalisme]], sahingga bisa waé dijaga dumasar pamundut pamakéna.\n\n====Kaca omongan pamaké====\nSakumaha nu tumiba ka kaca pamaké, ngan pangjaga dina kaca omongan sipatna kudu samentara.\n\n[[de:Wikipedia:Geschützte Seiten]]\n[[en:Wikipedia:Protected page]]\n[[eo:Vikipedio:Sxlositaj pagxoj]]\n[[fr:Wikipédia:page protégée]]\n[[id:Halaman yang dilindungi]]\n[[it:Wikipedia:Pagina protetta]]\n[[pt:Wikipedia:Protected page]]\n[[simple:Wikipedia:Protected page]]\n[[sv:Wikipedia:Skyddade sidor]]\n[[zh:Wikipedia:保护页面]]','/* Viewing the source of a protected page */',3,'Kandar','20050203210718','',0,0,0,0,0.138309567781,'20050215053251','79949796789281'); INSERT INTO cur VALUES (2156,0,'Wikipédia:_Padungdengan','[[ar:Wikipedia:واحة جالية]] [[ca:Discussió:Portada]] [[cs:Wikipedie:Pod lípou]] [[cy:Wicipedia:Y Caffi]] [[da:Wikipedia:Landsbybrønden]] [[de:Wikipedia:Ich brauche Hilfe]] [[en:Wikipedia:Village pump]] [[es:Wikipedia:Café]] [[eo:Vikipedio:Babilejo]] [[et:Vikipeedia:Üldine arutelu]] [[eu:Wikipedia:Txoko]] [[fi:Wikipedia:Kahvihuone]] [[fr:Wikipédia:Le Bistro]] [[hi:विकिपीडिया:गाँव_का_पम्प]] [[hr:Wikipedia:Kafić]] [[id:Wikipedia:Warung Kopi]] [[it:Wikipedia:Bar]] [[la:Wikipedia:Taberna]] [[ms:Wikipedia:Kedai Kopi]] [[nl:Wikipedia:De kroeg]] [[ja:Wikipedia:井戸端]] [[nah:Wikipedia:Tlatlahtoaloyan]] [[no:Wikipedia:Vannposten]] [[oc:Oiquipedià:La tavèrna]] [[ro:Wikipedia:Cafenea]] [[simple:Wikipedia:Simple talk]] [[sk:Wikipédia:Krčma]] [[sl:Wikipedija:Pod lipo]] [[sq:Wikipedia:Kuvendi]] [[sr:Википедија:Пијаца]] [[sv:Wikipedia:Bybrunnen]] [[zh:Wikipedia:互助客栈]]\n\nWilujeng sumping! Kaca ieu mangrupa tempat pikeun ngajukeun patarosan-patarosan sadérék ngeunaan Wikipédia Sunda. Anjeun bisa males/ngajawab kana bagian-bagian mana baé di handap ku jalan nga-klik tumbu \"édit\", atawa \'\'\'[http://su.wikipedia.org/w/wiki.phtml?title=Wikipédia:_Padungdengan&action=edit§ion=new nambahan sawala anyar]\'\'\' na kaca ieu.\n\nAnjeun ogé bisa manggihan jawaban di [[Wikipédia: mangpaat]], [[Wikipédia:NLD]], atawa [[Pitulung: Eusi]].\n\nMun Wikipédia teu jalan atawa jalanna lambat pisan, coba téang jawabanana di [http://openfacts.berlios.de/index-en.phtml?title=Wikipedia_Status FaktaNembrak] \n----','',3,'Kandar','20050217083323','',0,0,0,0,0.200712843166,'20050217083323','79949782916676'); INSERT INTO cur VALUES (2157,0,'Lumangsung_kiwari','Teu acan kagarap, dihaturan sindang ka [http://en.wikipedia.org/wiki/Current_events loka utama basa Inggris].\n\n\n{{pondok}}','',3,'Kandar','20050204091134','',0,0,0,1,0.184322087573,'20050303214455','79949795908865'); INSERT INTO cur VALUES (2158,0,'Current_events','#REDIRECT [[Lumangsung kiwari]]\n','Current events dipindahkeun ka Lumangsung kiwari',3,'Kandar','20050204091556','',0,1,0,1,0.237433799084,'20050204091556','79949795908443'); INSERT INTO cur VALUES (2159,0,'TTA',':\'\'TTA may also refer to the [[Triangle Transit Authority]], a regional transit service in [[North Carolina]].\'\'\n\n\'\'\'True Audio\'\'\' (abbreviated \'\'\'TTA\'\'\') is a [[free]], simple real-time [[lossless]] [[audio]] [[Codec|encoder/decoder]], based on adaptive prognostic filters which has shown the same or the better results comparing to majority of modern analogs.\n\n==TTA Compressor==\n* Down to 30% [[lossless]] [[audio]] [[data]] [[compression]]\n* Real-time encoding/decoding [[algorithm]]\n* [[Fast]] operation speed and minimal system requirements\n* Can be compiled and executed on several different platforms\n* [[Free]] and [[open]] [[source]] [[code]] and documentation\n* [[Hardware]] support\n\nTTA performs [[lossless]] compression on multichannel 8, 16 and 24 [[bit]] data of the [[Wav]] [[audio]] files. Being \"[[lossless]]\" means that no data/quality is lost in the [[compression]] - when uncompressed, the data will be identical to the original. The [[compression]] ratios of TTA depend on the type of music file being compressed, but the compression size will generally range between 30% - 70% of the original. TTA format supports both of [[ID3]]v1 and [[ID3]]v2 information tags.\n\nUsing True Audio codec, you can store up to 20 [[audio]] [[CD]] from your music collection on one single DVD-R for playback, while keeping all of [[CD]] information in a popular [[ID3]] information tags.\n\n==The Project==\n\nThe TTA project provides:\n\n* [[Free]] and simple [[data]] [[format]]\n* [[Plugins]] for the most popular media players\n* TTA [[DirectShow]] filters\n* Tau Producer - GUI based compressor for [[Microsoft Windows|Windows]]\n* Set of the C/C++ TTA development libraries\n\n==See also==\n\n* [[Lossless data compression]]\n* [[Lossy data compression]]\n* [[Audio data compression]]\n\n== External links ==\n\n* [http://www.true-audio.com True Audio Software Project]\n* [http://www.true-audio.com/codec.theory Compression theory]\n* [http://www.true-audio.com/codec.format TTA format description]\n* [http://www.true-audio.com/codec.comparison True Audio codec comparison]\n* [http://www.true-audio.com/codec.hardware Hardware Support]\n* [http://www.true-audio.com/ftp/WinTTA-setup.exe Tau Producer (GUI-based TTA compressor for Windows)]\n* [http://www.true-audio.com/codec.images Tau Producer Screen Shoots]\n* [http://tta.corecodec.org/ Project @ Corecodec.Org]\n* [http://tta.sourceforge.net/ Project @ Sourceforge.Net]\n\n[[Category:Audio codecs]]\n\n[[de:True Audio Codec]]','',0,'195.161.236.130','20050206113115','',0,0,0,1,0.208973414081,'20050206113115','79949793886884'); INSERT INTO cur VALUES (2162,1,'Bodor','\'\'\'Kabayan Jeung Motor Mitoha ..\'\'\'\n\nSikabayan jeung siiteung jalan-jalan di kampungna tiap pasosore, make motorna bapakna si iteung .. hisi mangsa kapeutingan .. dijalan aya barudak baragajul kekebutan .. babarengan di tengah jalan .. ari si kabayan jelemana usil pisan .. tetep embung ngelehan kalahkah ngahajakeun malahan kalahkan ngomong \"Teung .. (Ka Si Iteung) Ku Akan urang beset tengahna, (katingalina itu lampu aya 2 rerempetan), puguh we barudak teh nyararisi ... Hiji mangsa si kabayan ka kota .. di titah mitohana meuli pupuk .. pas balikna kapeutingan ... pan di jalan gedebojong katingali aya lampu dua rerempetan .. ari sikabayan mikirna arek usil deui .. ngabeset tengahna .. jiga kajadian nu jeung Si Iteung ... bari gugurutu .. \"Ku Aing arek di beset deui siah ... ngarah nyararisi\" ... teras si kabayan ngebut ... saking kebutna nancep gas ari pas geus aya 100 m si horeng teh lain lain barudak keur kekebutan ... tapi Toronton ... Ari sikabayan teh bingung ... arek ngerem hese arek balik deui hese .. akhirna .. sikabayan teh baseuh .. da di hudangkeun ku mitohana .. lantaran munding mitohana kabur .. dasar sikabayar kalahkan sare wae ...\n\nDedenthea2003@yahoo.com','',0,'203.130.226.94','20050207074124','',0,0,0,1,0.319051230318,'20050303214455','79949792925875'); INSERT INTO cur VALUES (2164,0,'Pulau_Jawa','#REDIRECT [[Jawa (pulo)]]\n','Pulau Jawa dipindahkeun ka Jawa (pulo)',3,'Kandar','20050208040526','',0,1,0,1,0.226519558723,'20050208040526','79949791959473'); INSERT INTO cur VALUES (2165,0,'Jawa_Barat','#REDIRECT [[Jawa Kulon]]\n','Jawa Barat dipindahkeun ka Jawa Kulon',3,'Kandar','20050208043349','',0,1,0,1,0.399122459795,'20050208043349','79949791956650'); INSERT INTO cur VALUES (2166,0,'Zipf-Mandelbrot_law','#REDIRECT [[Hukum Zipf-Mandelbrot]]\n','Zipf-Mandelbrot law dipindahkeun ka Hukum Zipf-Mandelbrot',3,'Kandar','20050208061849','',0,1,0,1,0.141616678145,'20050208061849','79949791938150'); INSERT INTO cur VALUES (2167,0,'Wikipédia:_Wikipédiawan','\'\'\'Wikipédiawan\'\'\' nyaéta jalma nu nulis jeung ngédit artikel keur [[Wikipédia]]. Pikeun sawala tambahan ngeunaan masarakat Wikipédia, tempo [[m:Main Page|Loka Méta]] [http://meta.wikimedia.org/wiki/Wikipedians] jeung [http://en.wikipedia.org/wiki/Wikipedia:Who%2C_Why%3F Wikipédia: Saha, naha?].\n\nWikipédiawan di Wikipédia vérsi Inggris jumlahna geus leuwih ti 180,000 rekening pamaké, can kaasup kontributor nu teu daptar, sedengkeun Wikipédiawan Sunda nu kadaptar aya 37 rekening. Wawar statistis nu leuwih mérélé bisa ditempo di [[Wikipédia: statistik]].\n\n==Daptar alfabét==\n*[[Special:Listusers|Daptar pamaké]] nu mangrupa daptar otomatis; tapi, kusabab hal téhnis, teu sadaya pamaké kadaptar.\n*Mangga daptarkeun nami anjeun di handap, katut widang garapanana.\n\n==Tempo ogé==\n* [[Meta:Wikipedian]]\n* [http://en.wikipedia.org/wiki/Wikipedia:Facebook Wikipedia:Facebook], pikeun gambar-gambar Wikipédiawan\n* [http://en.wikipedia.org/wiki/Wikipedia:Wikipediholic Wikipedia:Wikipediholic]\n* [[M:Wikipedians who blog]]\n\n[[ca:Viquipèdia:Viquipedistes]]\n[[cs:Wikipediiste]]\n[[da:Wikipedia:Wikipedianere]]\n[[de:Wikipedia:Die Wikipedianer]]\n[[el:Βικιπαίδεια:Βικιπαιδιστές]]\n[[en:Wikipedia:Wikipedians]]\n[[eo:Vikipedio:Vikipediistoj]]\n[[es:Wikipedia:Wikipedistas]]\n[[fr:Wikipédia:Wikipédiens]]\n[[fy:Wikipedy:Wikipedianen]] \n[[ga:Vicipéid:Vicipéideoirí]]\n[[hr:Wikipedia:Wikipedianci]]\n[[hu:Wikipédia:Wikipédisták]]\n[[ja:Wikipedia:ウィキペディアン]]\n[[ko:위키백과:위키백과사전가]]\n[[nl:Wikipedia:Wikipedianen]]\n[[pl:Wikipedia:Twórcy Polskiej Wikipedii]]\n[[pt:Wikipedia:Wikipedistas]] \n[[ro:Wikipedia:Wikipedist]]\n[[ru:Википедия:Участники]]\n[[simple:Wikipedia:Wikipedians]]\n[[sl:Wikipedija:Wikipedisti]]\n[[sv:Wikipedia:Wikipedianer]]\n[[zh:Wikipedia:Wikipedia人]]\n\n[[Category:Wikipédiawan]]','',3,'Kandar','20050208081335','',0,0,0,0,0.112669484522,'20050208083141','79949791918664'); INSERT INTO cur VALUES (2168,0,'Wikipédia:_statistik','Pikeun statistik na Wikipédia katut kumaha tumuwuhna, tempo\n\n==Nu mindeng diropéa==\n===Ukuran Wikipédia===\n\n*[http://su.wikipedia.org/wikistats/EN/Sitemap.htm Kaca statistik Wikipédia] - rupa-rupa statistik sadaya vérsi basa Wikipédia.\n*[[Special:Statistics]] - Statistik dasar mutahir Wikipédia basa Sunda.\n*[http://en.wikipedia.org/wiki/Wikipedia:Size_comparisons Babandingan ukuran] (jeung énsiklopédi katut kumpulan informasi)\n*[http://en.wikipedia.org/wiki/Wikipedia:Multilingual_statistics Statistik multibasa]\n\n===Lalu lintas===\n*[http://wikimedia.org/stats/live/ Grafik langsung] lalu lintas Wikipédia\n*\'\'[http://en.wikipedia.org/wiki/Wikipedia:Awareness_statistics Awareness statistics]\'\' (ngalacak tumuwuhna kasadaran umum)\n*[[meta:Wikipedia.org_is_more_popular_than...|Leuwih populér batan...]] (daptar babandingan lalu lintas Alexa)\n\n===Status sistim===\n*\'\'[http://download.wikimedia.org/ganglia/ Ganglia toolkit monitoring system]\'\'\n\n==Tempo ogé==\n* [[m:Statistics]]\n* \'\'[http://kohl.wikimedia.org/kates-tools/index.action Kate\'s Tools]\'\'\n\n[[Category:Statistik Wikipédia|Statistik]]\n\n[[ca:Viquipèdia:Estadístiques]]\n[[cs:Wikipedie:Statistika]]\n[[de:Wikipedia:Statistik]]\n[[el:Βικιπαίδεια:Στατιστικά]]\n[[en:Wikipedia:Statistics]]\n[[es:Wikipedia:Estadísticas]]\n[[fr:Wikipédia:Statistiques]]\n[[ku:Wikipedia:Statîstîk]]\n[[nl:Wikipedia:Bezoekersaantallen van Wikipedia NL]]\n[[fi:Wikipedia:Tilastoja]]\n[[pl:Specjalna:Statistics]]\n[[pt:Wikipedia:Estatísticas]]\n[[sl:Wikipedija:Statistika]]\n[[tr:Wikipedia:İstatistikler]]\n[[zh:Wikipedia:统计]]','/* Ukuran Wikipédia */',3,'Kandar','20050208083249','',0,0,0,0,0.068988027489,'20050208083249','79949791916750'); INSERT INTO cur VALUES (2169,2,'Robin_Patterson','http://mi.wikipedia.org/wiki/User:Robin_Patterson\n\n[[Selandia Baru]]\n\n[[2004]]\n\n[[Januari]]\n[[Pébruari]]\n[[Maret]]\n\n[[Juli]]\n[[Agustus]]\n\n\n[[Désémber]]\n\n[[Special:Shortpages]] - {{pondok...\n\n== Tumbu kaluar ==\n*[','more months?',38,'Robin Patterson','20050209002924','',0,0,1,0,0.026973138194,'20050215003557','79949790997075'); INSERT INTO cur VALUES (2170,0,'2003','\n[[Januari]] - 28 [[Propinsi di Indonesia]]\n\n[[Donald Knuth]] elected as a Fellow of the Royal Society.\n\n==Hadiah Nobel==\n\'\'\'[[Hadiah Nobel widang kimia]]:\'\'\'\n[[Peter Agre]], [[Roderick MacKinnon]], for discoveries concerning channels in cell membranes \n\n\'\'\'Economic sciences:\'\'\'\n[[Robert Engle]] and [[Clive Granger]], for work on analysing economic time series. - [[Statistik ékonomi]]\n\n*[[Abad ka-20]] [[Abad ka-21]]\n*[[1998]] [[1999]] [[2000]] [[2001]] [[2002]] \'\'\'2003 (MMIII)\'\'\' [[2004]] [[2005]] [[2006]] [[2007]] [[2008]]\n\n\n{{pondok}}\n\n[[en:2003]]\n[[id:2003]]\n[[mi:2003]]','These year pages are useful for links \"to and from\"',38,'Robin Patterson','20050208111609','',0,0,0,1,0.265716906959,'20050303214455','79949791888390'); INSERT INTO cur VALUES (2171,0,'1945','*[[15 Agustus]] - [[Jepang]] unconditional surrender to the United States\n*[[17 Agustus]] - [[Indonésia]] independence, flying [[Bandéra Indonésia]]; [[Sukarno]] [[Presiden]]\n\n\'\'\'[[Hadiah Nobel widang kimia]]:\'\'\'\n[[Artturi Ilmari Virtanen]] for his research in agricultural and nutrition [[kimia]]\n \n----\n*[[Abad ka-19]] [[Abad ka-20]] [[Abad ka-21]]\n*[[1942]] [[1943]] [[1944]] \'\'\'1945 (MCMLXIV)\'\'\' [[1946]] [[1947]] [[1948]]\n----\n{{pondok}}\n\n[[en:1945]]','Hadiah Nobel widang kimia',38,'Robin Patterson','20050208220217','',0,0,0,0,0.015533712822,'20050303211247','79949791779782'); INSERT INTO cur VALUES (2172,0,'New_Zealand','#REDIRECT [[Selandia Baru]]','redirect - to the right name, I presume!',38,'Robin Patterson','20050209000829','',0,1,0,1,0.073750745454,'20050303214455','79949790999170'); INSERT INTO cur VALUES (2173,0,'Selandia_Baru','\'\'\'Selandia Baru\'\'\' (\'\'New Zealand; Aotearoa\'\') ngarupakeun salah sahiji nagara di [[Samudera Pacific]].\n\n==Tumbu kaluar==\n*[http://zeal.com/category/preview.jhtml?cid=560009 \"Zeal\" - Aotearoa]\n\n{{pondok}}\n\n[[mi:Aotearoa]]','',38,'Robin Patterson','20050209002459','',0,0,1,0,0.141027134637,'20050303211247','79949790997540'); INSERT INTO cur VALUES (2174,0,'Agustus','{{KalénderAgustus{{CURRENTYEAR}}}}\n\'\'\'Agustus\'\'\' nyaéta bulan ka-8 [[kalénder]] Maséhi, satutasna [[Juli]] sarta saméméh [[Séptémber]]. \n\n==Bulan ieu na sajarah==\n===Kajadian===\n===Lahir===\n[[4 Agustus]] [[1940]] - [[Abdurrahman Wahid]] \n\n===Pupus===\n\n\n{{BulanMaséhi}}\n\n{{pondok}}\n\n[[en:August]]\n[[id:Agustus]]','',3,'Kandar','20050211090853','',0,0,0,0,0.327432611102,'20050303211247','79949788909146'); INSERT INTO cur VALUES (2175,3,'Gangleri','__TOC__','',39,'Gangleri','20050209145525','',0,0,0,1,0.02262402644,'20050303214455','79949790854474'); INSERT INTO cur VALUES (2176,2,'Gangleri','*[[:de:Benutzer:Gangleri]]\n*[[:en:User:Gangleri]]\n*[[:eo:Vikipediisto:Gangleri]]\n*[[:is:Notandi:Gangleri]]\n*[[:ro:Utilizator:Gangleri]]\n*\'\'\'[[meta:User:Gangleri]]\'\'\'\n\n[[de:Benutzer:Gangleri]] [[en:User:Gangleri]] [[eo:Vikipediisto:Gangleri]] [[is:Notandi:Gangleri]] [[ro:Utilizator:Gangleri]]','',39,'Gangleri','20050209145542','',0,0,0,1,0.006940584238,'20050303214455','79949790854457'); INSERT INTO cur VALUES (2177,0,'Presiden_Indonesia','#REDIRECT [[Présidén Indonésia]]\n','Presiden Indonesia dipindahkeun ka Présidén Indonésia',3,'Kandar','20050210184507','',0,1,0,1,0.027020708351,'20050210184507','79949789815492'); INSERT INTO cur VALUES (2178,3,'Robin_Patterson','==Thanks==\nHi, there...\n\nWell, I really need some fresh air here... :) Working with this huge project by four or six hands is a big thing. I\'m still promoting this site to colleages & network. The bad thing is that our rate of interaction with Internet is still low.\n\nO.K., thank you for joining \'\'\'Wikipédia basa Sunda\'\'\'. [[User:Kandar|kandar]] 19:06, 10 Péb 2005 (UTC)','Thanks...',3,'Kandar','20050210190643','',0,0,0,1,0.023954097094,'20050303214455','79949789809356'); INSERT INTO cur VALUES (2179,10,'BulanMaséhi','{| border=\"0\" class=\"toccolours\" style=\"margin: 0 auto\" align=center\n|align=center| [[Januari]] | [[Pébruari]] | [[Maret]] | [[April]] | [[Méi]] | [[Juni]] | [[Juli]] | [[Agustus]] | [[Séptémber]] | [[Oktober]] | [[Nopémber]] | [[Désémber]]\n|}\n[[Category:Days]] ','',3,'Kandar','20050211090703','',0,0,0,1,0.052941397624,'20050303214455','79949788909296'); INSERT INTO cur VALUES (2180,0,'Beureum','\'\'\'Beureum\'\'\' nyaéta [[warna]] dina frékuénsi [[cahya]] panghandapna nu bisa kénéh katangkep ku [[panon]] manusa. Cahya beureum mibanda panjang gelombang kira 700 [[Nanométer|nm]]. [[Getih]] kaoxigénan warnana beureum alatan ayana [[hémoglobin]]. Cahya beureum mangrupakeun nu munggaran kaserep ku cilaut, sahingga loba lauk jeung invertebrata laut katémbongna beureum caang nu tadina [[hideung]] di habitat aslina.\n\n==Tempo ogé==\n{{Wiktionary}}\n*[[Daptar warna]]\n\n\n{{pondok}}\n[[ca:Roig]]\n[[cs:Červená]]\n[[da:Rød]]\n[[de:Rot]]\n[[el:Κόκκινο]]\n[[en:Red_(color)]]\n[[es:Rojo]]\n[[eo:Ruĝa]]\n[[fr:Rouge]]\n[[he:אדום (צבע)]]\n[[nl:Rood]]\n[[no:Rød]]\n[[ja:赤]]\n[[lt:Raudona]]\n[[pt:Vermelho]]\n[[simple:Red]]\n[[fi:Punainen]]\n[[sv:Röd]]\n[[zh-cn:红色]]\n\n[[Category:Warna]]\n[[Category:Spéktrum optik]]','',3,'Kandar','20050211123912','',0,0,0,1,0.495984051455,'20050303214455','79949788876087'); INSERT INTO cur VALUES (2181,0,'Januari','\'\'\'Januari\'\'\' nyaéta bulan ka-1 [[kalénder]] Maséhi, satutasna [[Désémber]] sarta saméméh [[Pébruari]]. \n\n==Bulan ieu na sajarah==\n===Kajadian===\n*[[Wikipédia]] dikawitan ti [[15 Januari]] [[2001]] ku [[Jimmy Wales]], [[Larry Sanger]], sarta sababaraha urang kolaborator basa Inggris nu parinuh ku sumanget. \n\n===Lahir===\n*[[31 Januari]] [[1938]] - [[Ayip Rosidi]] lahir di [[Jatiwangi]], [[Majaléngka]].\n\n===Pupus===\n\n\n{{BulanMaséhi}}\n\n{{pondok}}\n\n[[en:January]]\n[[id:Januari]]','/* Lahir */',3,'Kandar','20050215055232','',0,0,1,0,0.146301341431,'20050303211247','79949784944767'); INSERT INTO cur VALUES (2182,0,'Pébruari','\'\'\'Pébruari\'\'\' nyaéta bulan ka-2 [[kalénder]] Maséhi, satutasna [[Januari]] sarta saméméh [[Maret]]. \n\n\n==Bulan ieu na sajarah==\n===Kajadian===\n* [[27 Pébruari]] [[1940]] - [[Carbon-14]], the radioactive isotope of carbon, discovered by [[Martin Kamen]] and [[Sam Ruben]].\n\n===Lahir===\n\n===Pupus===\n* [[3 Pébruari]] [[1929]] - [[A. K. Erlang]] ([[1 Januari]] [[1878]] lahir), Danish mathematician, statistician, and engineer\n* [[15 Pébruari]] [[1849]] - [[Pierre François Verhulst]] ([[28 Oktober]] [[1804]] lahir) \"[[Dinamika populasi]])\"\n\n\n{{BulanMaséhi}}\n\n{{pondok}}\n\n[[en:February]]\n[[id:Februari]]','éditan minor?',38,'Robin Patterson','20050215003553','',0,0,1,1,0.120436397441,'20050303214455','79949784996446'); INSERT INTO cur VALUES (2183,0,'Publication_bias','#REDIRECT [[Bias publikasi]]\n','Publication bias dipindahkeun ka Bias publikasi',3,'Kandar','20050215060740','',0,1,0,1,0.83280005708,'20050215060740','79949784939259'); INSERT INTO cur VALUES (2184,0,'Bias_(statistics)','#REDIRECT [[Bias (statistik)]]\n','Bias (statistics) dipindahkeun ka Bias (statistik)',3,'Kandar','20050215060959','',0,1,0,1,0.01020091302,'20050215060959','79949784939040'); INSERT INTO cur VALUES (2185,0,'Hydrology','#REDIRECT [[Hidrologi]]\n','Hydrology dipindahkeun ka Hidrologi',3,'Kandar','20050216033917','',0,1,0,1,0.547984387464,'20050216033917','79949783966082'); INSERT INTO cur VALUES (2187,10,'ASEAN','
    \n{| align=\"center\" class=\"toccolours\" cellspacing=\"0\"\n|- bgcolor=\"#ccccff\"\n! align=\"center\" | [[Nagara-nagara di dunya|Nagara]] di [[Asia Tenggara]]\n|-\n| align=\"center\" style=\"font-size: 90%;\" | \n[[Brunéi]] | [[Kamboja]] | [[Timor Wétan]] | [[Indonésia]] | [[Laos]] | [[Malaysia]] | [[Myanmar]] | [[Filipina]] | [[Singapura]] | [[Muangthai]] | [[Viétnam]]\n|}','',3,'Kandar','20050221102257','',0,0,1,0,0.013367005168,'20050221102257','79949778897742'); INSERT INTO cur VALUES (2188,10,'OKI','
    \n{| id=\"toc\" align=\"center\" style=\"margin: 0 2em 0 2em; text-align:center\"\n|-\n! style=\"background:#ccccff;\" | [[Organisasi Konferénsi Islam]]\n| [[Image:Bandéra_OKI.gif|55px|Bandéra OKI]]\n|-\n| style=\"font-size: 90%;\" | [[Afghanistan]] | [[Albania]] | [[Aljazair]] | [[Azérbaijan]] | [[Bahrain]] | [[Bangladés]] | [[Benin]] | [[Burkina Faso]] | [[Brunéi]] | [[Kamérun]] | [[Chad]] | [[Komoro]] | [[Basisir Gading]] | [[Jibouti]] | [[Mesir]] | [[Gabon]] | [[Gambia]] | [[Guinea]] | [[Guinea-Bissau]] | [[Guyana]] | [[Indonésia]] | [[Iran]] | [[Iraq]] | [[Yordania]] | [[Kuwait]] | [[Kazakhstan]] | [[Kyrgyzstan]] | [[Libanon]] | [[Libya]] | [[Maldiva]] | [[Malaysia]] | [[Mali]] | [[Mauritania]] | [[Maroko]] | [[Mozambik]] | [[Nigeria]] | [[Nigeria]] | [[Oman]] | [[Pakistan]] | [[Paléstina]] | [[Qatar]] | [[Saudi Arabia]] | [[Senegal]] | [[Sierra Leone]] | [[Somalia]] | [[Sudan]] | [[Suriname]] | [[Syria]] | [[Tajikistan]] | [[Turkey]] | [[Tunisia]] | [[Togo]] | [[Turkmenistan]] | [[Uganda]] | [[Uzbekistan]] | [[Uni Émirat Arab]] | [[Yaman]]\n|-\n|align=\"center\" style=\"font-size: 90%;\" colspan=\"2\"|\n\'\'\'Nagara peninjau:\'\'\' [[Bosnia Herzegovina]] | [[Républik Afrika Tengah]] | [[Muangthai]]\n|-\n|align=\"center\" style=\"font-size: 90%;\" colspan=\"2\"|\n\'\'\'Organisasi jeung masarakat peninjau Muslim:\'\'\' [[Front Pangbébas Nasional Moro]] | [[Wilayah Siprus Turki]]\n|-\n|align=\"center\" style=\"font-size: 90%;\" colspan=\"2\"|\n\'\'\'Organisasi peninjau internasional:\'\'\' [[Organisasi Koperasi Ékonomi]] | [[Organisasi Uni Afrika]] | [[Liga Nagara-nagara Arab]] | [[Gerakan Non-Blok]] | [[United Nations]]\n|}','',3,'Kandar','20050221102245','',0,0,0,1,0.078294760988,'20050303214455','79949778897754'); INSERT INTO cur VALUES (2189,14,'Quran','sayah teh sabenerna mah teu ngahaja oge muka ieu situs teh ngan minangka urang islam mak enyak teu gaduh perhatian posan kana kitab sucinya teh nyaak kukituna ieu aya sakedik pamadeg atanapi naon baelah namina etama teu penting3 teuing pan ? \nkieu kumaha lamun terjemah basa sundana teh nu sunda ayeuna entonk sunda pihun kitu da abdi mah tie wetan soalna rada buyeteg oge ngaleunyeupanana aden \nabdi nuhun pisan upami tiyasa katampi janten keluarga besar panganggo quran ngalangkungan basa sunda kumaha nyak carana supados diwartosan abdi mah di pravtoviq@yahoo.com \ninsya Allah iraha2 abdi bade ngiringan ngeusian ieu kenging pan ? nuhun punten \nwassalaam','atoh pisan ku ayana tarjamah quran ku basa sunda ieu teh',0,'210.23.64.250','20050223040910','',0,0,0,1,0.250169009518,'20050303214455','79949776959089'); INSERT INTO cur VALUES (2190,15,'Quran','abdi leres2 bingah luar biasana ningal di internet aya basa sunda mun orang kulon nu nuju studi basa sunda di chicago di mana deuih maca ieu tulisan nyak mudah-mudahan kenging hidayah ti gusti nu maha suci aamiin','',0,'210.23.64.250','20050223041752','',0,0,0,1,0.473116927221,'20050303214455','79949776958247'); INSERT INTO cur VALUES (2191,0,'Hiburan','ieu mah ngabandingkeun antawis jalmi anu percanten kana ayana nu gaib sareng anu heunteu ku kodok sareng lauk ari kodk mah tiyasa di lebet cai tiyasa di luhur cai (kaluar tina cai) sedengkeun lauk mah ngan di jero cai wungkul \nHiji waktos kodok teh nuju nongkrong di sisi balong ningal aya anu siga benang nyelup ka cai balong ujug-ujug aya lauk nu kaluar ti cai teras we di tewak ku jelema anu nyepeng gagang senar eta kodok panasaran manehna ngajleng blus ka balong di jero cai manehna ningal aya cacing anu ngarengkol di cai ujug-ujug aya lauk nu nyaplok eta cacing teras lauk teh ka luhur teras lengit teu katempo deuih ku kodok teh kodok panasaran deuih manehna kaluar tina cai ka sisi balong deuih katingal ku manehna lauk nu ngadahar lauk bingkeung tadi tos di cepeng ku jelma nu gaduh benang senar wah wah wah cilaka ieu ceuk kodok teh bisa beak lamun kitu carana mah lauk teh \nGancang carios kodok ngajleng asup ka cai balong deuih teras manehna gegeroan siga kodok gelo kieu he para lauk anu hayang salamet kadek aranjeun ka cacing bingkeung ulah didahar nyak cilaka aranjeun lamun maksa ngadahar cacing ngarengkol nyak dasar lauk aya keneh weh nu percanten ka kodok ayak keneh wee nu masih wantun ngadahar eta cacing bingkeung\ntah ieu para wargi sadayana, kodok mah minangkana para nabi para utusan anu tos terang pisan kana alam kubur alam luhur alam anu bade sumping tos wawartos kayaan alam engke teh kumaha \n(bersambung nyak kabujeng duhur)','kodok ibarat nabi lauk urang-urang',0,'210.23.64.250','20050223044954','',0,0,0,1,0.179223068031,'20050303214455','79949776955045'); INSERT INTO cur VALUES (2192,4,'Ngarojong_loka','Pikeun iber nu leuwih écés, mangga lebet ka [http://wikimediafoundation.org/wiki/Home loka Yayasan Wikimédia].','',3,'Kandar','20050223073723','',0,0,0,1,0.141678090394,'20050303214455','79949776926276'); INSERT INTO cur VALUES (2193,0,'Wikipédia:artikel_pamundut','\'\'\'Kaca ieu ditujukeun pikeun ngadaptarkeun artikel-artikel nu sakirana dipikabutuh ku para pamaké Wikipédia, mangga serat di handap.\'\'\'\n\n:Artikel-artikel nu dipikabutuh tiasa ditempo [[Special:Wantedpages|di dieu]].\n----','',3,'Kandar','20050228060138','',0,0,1,0,0.09245969423,'20050228060138','79949771939861'); INSERT INTO cur VALUES (2194,8,'Rightslogtext','Ieu mangrupa log parobahan hak-hak pamaké.','',3,'Kandar','20050224111051','',0,0,1,1,0.667234519083,'20050303214455','79949775888948'); INSERT INTO cur VALUES (2195,6,'Ceuli.jpg','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050227074816','',0,0,0,1,0,'20050228064811','79949772925183'); INSERT INTO cur VALUES (2196,6,'Anatomi_ceuli_manusa.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050227075553','',0,0,0,1,0,'20050228064811','79949772924446'); INSERT INTO cur VALUES (2197,0,'Mamalia','\'\'\'Mamalia\'\'\' nyaéta [[kelas (biologi)|kelas]] [[sato]] [[vertebrata]] nu utamana dicirikeun ku ayana [[kalenjar susu]], nu na [[bikang]] ngahasilkeun susu pikeun asupan orokna; ayana [[bulu]]; sarta mibanda awak éndotérmis atawa \"[[getih haneut]]\". Uteuk ngatur sistim sirkulasi jeung éndotérm, kaasup [[jantung]] nu boga opat kamar. Mamalia ngawengku leuwih ti 5,000 [[génus]], nu nyebar di 425 [[kulawarga (biologi)|kulawarga]] jeung 46 [[Ordo]], najan hal ieu gumantung kana [[klasifikasi ilmiah]] nu dipaké.\n\nSacara [[filogenetik]], \'\'\'mamalia\'\'\' diwatesan salaku sakabéh turunan karuhun umum (Ing. \'\'common ancestor\'\') [[monotréma]] (nyaéta mamalia \'\'[[echidna]]\'\') jeung \'\'[[therian]]\'\' mammals (\'\'[[placental]]\'\' jeung \'\'[[marsupial]]\'\').\n\n==Rujukan==\n\n*McKenna, Malcolm C., and Bell, Susan K. 1997. \'\'Classification of Mammals Above the Species Level.\'\' Columbia University Press, New York, 631 pp. ISBN 0-231-11013-8\n\n*Nowak, Ronald M. 1999. \'\'Walker\'s Mammals of the World\'\', 6th edition. Johns Hopkins University Press, 1936 pp. ISBN 0-801-85789-9\n\n*Simpson, George Gaylord. 1945. \"The principles of classification and a classification of mammals\". \'\'Bulletin of the American Museum of Natural History\'\', \'\'\'85\'\'\':1–350.\n\n*Springer, Mark S., Michael J. Stanhope, Ole Madsen, and Wilfried W. de Jong. 2004. \"Molecules consolidate the placental mammal tree\". Trends in Ecology and Evolution, \'\'\'19\'\'\':430–438. ([http://www.zi.ku.dk/evolbiology/courses/ME04/7_9/springer200-phyl.pdf pdf version])\n\n*Vaughan, Terry A., James M. Ryan, and Nicholas J. Capzaplewski. 2000. \'\'Mammalogy: Fourth Edition\'\'. Saunders College Publishing, 565 pp. ISBN 0-030-25034-X (Brooks Cole, 1999)\n\n*Wilson, Don E., and Deeann M. Reeder (eds). 1993. \'\'Mammal Species of the World\'\'. Smithsonian Institution Press, 1206 pp. ISBN 1-560-98217-9\n\n==Tempo ogé==\n\n*[[Daptar mamalia]]\n*[[Klasifikasi mamalia]]\n\n==Tumbu kaluar==\n\n*[http://www.nceas.ucsb.edu/~alroy/nafmsd.html North American Fossil Mammal Systematics Database.]\n*[http://paleocene-mammals.de/ Paleocene Mammals], an excellent site covering the rise of the mammals\n*[http://www.enchantedlearning.com/subjects/mammals/Evolution.shtml Evolution of Mammals], a brief intro to early mammals\n*[http://home.arcor.de/ktdykes/mesomamm.htm The Evolution of Mesozoic Mammals, a Rough Sketch], a nice informal introduction \n*[http://www.carnegiemnh.org/research/news.html Carnegie Museum of Natural History], some leading discoveries of early mammal fossils \n\n{{pondok}}\n\n{{Mamalia}}\n[[Category:Chordata]]\n[[he:יונקים]]\n[[ast:Mamíferu]]\n[[bg:Бозайник]]\n[[ca:Mamífer]]\n[[cs:Savci]]\n[[cy:Mamal]]\n[[da:Pattedyr]]\n[[de:Säugetiere]]\n[[et:Imetajad]]\n[[es:Mamífero]]\n[[eo:Mamulo]]\n[[fr:Mammifère]]\n[[fy:Sûchdier]]\n[[ko:포유류]]\n[[id:Mamalia]]\n[[it:Mammiferi]]\n[[la:Mammalia]]\n[[lb:Mamendéieren]]\n[[li:Zoegdiere]]\n[[lt:Žinduolis]]\n[[jbo:mabru]]\n[[ms:Mamalia]]\n[[nl:Mammalia]]\n[[ja:哺乳類]]\n[[no:Pattedyr]]\n[[nn:Pattedyr]]\n[[oc:Mammifèr]]\n[[nds:Söögdeer]]\n[[pl:Ssaki]]\n[[pt:Mammalia]]\n[[ru:Млекопитающие]]\n[[simple:Mammal]]\n[[fi:Nisäkkäät]]\n[[sv:Däggdjur]]\n[[uk:Ссавці]]\n[[zh:哺乳动物]]','/* Tumbu kaluar */',3,'Kandar','20050228110849','',0,0,1,0,0.008897336402,'20050303211247','79949771889150'); INSERT INTO cur VALUES (2198,10,'Mamalia','{| style=\"margin:0 auto\" align=center class=\"toccolours\"\n!align=center style=\"background:#ccccff;\"| [[Mamalia]]\n|-\n|align=center style=\"font-size:85%;\"|\'\'\'[[Monotreme|Monotremata]]\'\'\'\n|-\n|align=center style=\"font-size:85%;\"| \n\'\'\'[[Placentalia]]\'\'\':\n[[Xenarthra]] | \n[[Colugo|Dermoptera]] | \n[[Desmostylia]] | \n[[Tree shrew|Scandentia]] | \n[[Primate|Primates]] | \n[[Rodent|Rodentia]] | \n[[Lagomorpha]] | \n[[Insectivora]] | \n[[Bat|Chiroptera]] | \n[[Pangolin|Pholidota]] | \n[[Carnivora]] | \n[[Odd-toed ungulate|Perissodactyla]] | \n[[Even-toed ungulate|Artiodactyla]] | \n[[Cetacea]] | \n[[Afrosoricida]] | \n[[Elephant shrew|Macroscelidea]] | \n[[Aardvark|Tubulidentata]] | \n[[Hyrax|Hyracoidea]] | \n[[Proboscidea]] | \n[[Sirenia]]\n|-\n|align=center style=\"font-size:85%;\"|\n\'\'\'[[Marsupialia]]\'\'\': [[Didelphimorphia]] | \n[[Shrew Opossum|Paucituberculata]] | \n[[Monito del Monte|Microbiotheria]] | \n[[Dasyuromorphia]] | \n[[Peramelemorphia]] | \n[[Marsupial mole|Notoryctemorphia]] | \n[[Diprotodontia]]\n|}\n\n[[Category:Mamalia]]','',3,'Kandar','20050228103334','',0,0,0,1,0.112040432325,'20050303214455','79949771896665'); INSERT INTO cur VALUES (2199,0,'Allah','\'\'\'Téks kandel\'\'\'','',0,'24.188.22.247','20050301011517','',0,0,0,1,0.397039039031,'20050303214455','79949698988482'); INSERT INTO cur VALUES (2200,0,'Spérma','[[Image:Sperma.jpg|right|frame|Diagram skématik sél spérma, nunjukkeun (1) [[akrosom]], (2) [[mémbran sél]], (3) [[inti sél|inti]], (4) [[mitokondria]], jeung (5) [[flagélum]] (buntut)]]\n\n\'\'\'Sél spérma\'\'\', atawa \'\'\'spermatozoon\'\'\'/\'\'\'spermatozoa\'\'\' ([[Basa Latin]]: \'\'sperm\'\' = mani, jeung \'\'zoon\'\' = hirup), nyaéta [[sél (biologi)|sél]] [[haploid]] [[gamét]] jalu/lalaki. Spérma dibawa na cairan nu disebut [[mani]] (Ing. \'\'semen\'\'), nu bisa [[fértilisasi|ngabuahan]] [[ovum|sél endog]] pikeun jadi [[zigot]]. Zigot bisa tumuwuh jadi organisme anyar, kaasup [[manusa]].\n \nSél spérma ngandung satengah [[gén|iber genetik]] nu dipikabutuh pikeun \"nyiptakeun\" mahluk hirup. Sacara umum, [[kelamin]] turunan ditangtukeun ku spvrma, ku ayana papasangan [[kromosom]] \"XX\" (pikeun [[bikang]]) atawa \"XY\" (pikeun [[jalu]]). Sél spérma munggaran katalungtik ku [[Anton van Leeuwenhoek]] taun [[1679]].\n\n==Struktur jeung ukuran spérma==\n\nSpérmatozoa mangrupa sél nu geus didiferensiasikeun, normalna diwangun ku hulu, awak, jeung [[flagelum|buntut]]. Huluna ngandung [[sitoplasma]] jeung bahan [[inti sél|inti]] pikeun [[fértilisasi]]. Awakna ngandung loba pisan [[mitokondria]] nu nyadiakeun tanaga pikeun hojahna spérma ku ngahasilkeun [[adénosin trifosfat|ATP]]. Buntut spérmatozoa dipaké pikeun ngawelah.\n\nDi manusa, sél spérma ngawengku hulu 5 [[mikrométer|µm]], awak 3 µm, jeung buntut nu panjangna 50 µm. Sél ieu dicirikeun ku saeutikna sitoplasma.\n\n==Produksi spérma==\n\'\'Artikel utama:\'\' [[Spérmatogenesis]]\n\nSpérma dihasilkeun dina [[solobong mani]] na [[siki kanjut|téstés]] dina prosés nu disebut spérmatogenesis. Sél buleud nu disebut [[spérmatogonia]] beulah sarta didiferensiasi sahingga jadi spérma. Nalika [[sapatemon|rarasmi]], spérma asup kana [[heunceut]] - nu salajengna asup ka rahim.\n\n== Tumbu kaluar ==\n* [http://www.andrologysociety.com/resources/handbook.asp The Handbook of Andrology]\n\n[[Category:Sistim baranahan]]\n[[Category:Sél bibit]]\n[[Category:Andrologi]]\n\n[[de:Spermium]]\n[[en:Sperm]]\n[[es:Espermatozoide]]\n[[fr:Spermatozoïde]]\n[[it:Spermatozoo]]\n[[nl:Sperma]] \n[[ja:精子]]\n[[lt:Spermatozoidas]]\n[[pl:Plemnik]]\n[[ru:Сперматозоид]]','',3,'Kandar','20050301070102','',0,0,1,0,0.046495237776,'20050316113156','79949698929897'); INSERT INTO cur VALUES (2202,0,'Mani','\'\'\'Mani\'\'\' nyaéta [[cairan]] nu dikaluarkeun tina [[sirit]] nalika [[bucat|éjakulasi]], biasana dina waktu [[orgasme]]. Kawas [[getih]], mani ngandung dua bagian: bagian [[sél (biologi)|sélular]] ([[spérmatozoa]]) jeung bagian nonsélular (\'\'plasma mani\'\'). Mani ngandung [[spérma]], nu kadang ngakibatkeun [[reuneuh|kakandungan]] satutasna [[sapatemon|rarasmi]]. Mani mangrupa cairan semu [[bodas]], kawas [[susu]], rada [[viskositas|kentel]], ngandung [[cai]] jeung saeutik [[uyah]], [[protéin]], jeung [[fruktosa]].\n\n==Komposisi==\nKira-kira 200 nepi ka 500 yuta [[spérmatozoa]] (atawa pondokna \'spérma\') nu dihasilkeun dina [[siki kanjut|téstés]] dileupaskeun nalika éjakulasi. Ngan, sakitu loba téh ukur 2–5% tina volume mani. Plasma mani nu loba, bagian cairan dina mani, dihasilkeun ku \'\'[[male accessory organs of reproduction]]\'\'. Kira-kira 60% mani dihasilkeun ku [[seminal vesicle|seminal vesicles]], sedengkeun sésana lolobana dihasilkeun ku [[prostat]]. Sékrési prostatik [[manusa]] ngandung [[asam sitrat]], [[asam fosfatase]], jeung [[séng]] dina kadar nu loba. A small amount of viscous [[mucus]] comes from the [[bulbourethral gland|bulbourethral glands]]. Gemblengna, plasma mani ngandung rupa-rupa bahan [[organik]] jeung [[anorganik]]: [[ion]] [[logam]], [[gula]], [[lipid]], [[hormon]] [[stériod]], [[prostaglandin]], [[asam amino]], jeung [[pasangan basa|basa]] nu ngandung [[nitrogén]]. Sababaraha amina basa kuat (kationik atawa boga muatan positif) kayaning \'\'putrésin\'\', \'\'spérmin\'\', \'\'spérmidin\'\', jeung \'\'kadaverin\'\' nyababkeun bauna mani. However, an offensive and putrid smell indicates a urinary tract or other urogenital infection. Basa kationik penting pikeun ngalawan watek asam sékrési heunceut, ogé nyangga DNA dina spérma. \n\nFruktosa mangrupakeun sumber tanaga utama pikeun sél spérma. Sababaraha komponén séjén disadiakeun pikeun ngaronjatkeun mobilitas sél spérma. Spérma dina kaayaan paling hadé mun aya dina lingkungan [[basa]], sedengkeun [[heunceut]] biasana rada [[asam|haseum]]. Cairan nu dikaluarkeun ku \'\'seminal vesicles\'\' sipatna basa. Prostaglandin nyaéta asam lemak nu dipaké pikeun peta hormonal. \n\nSakali éjakulasi umumna ngandung nepi ka 5 [[mili|m]][[gram|g]] [[séng]]. Lalaki nu mindeng éjakulasi bisa kakurangan séng, mangkaning kakurangan séng bisa ngabalukarkeun masalah réproduktif jeung masalah dina [[spérmatogenesis]].\n\n==Mani jeung népana panyakit==\nMani sacara mandiri teu bahya pikeun [[kulit]], ngan, mani bisa jati tutunggangan pikeun [[kasakit nu ditépakeun sacara séksual]], kayaning [[HIV]], virus nu nyababkeun [[AIDS]]. Ogé aya hipotésis yén kandungan mani, kayaning spérmatozoa ogé plasma mani, bisa ngabalukarkeun [[imunosupresi]] na awak mun asup ka [[aliran getih]] atawa [[limfa]]. Bukti ngeunaan hal ieu balik deui ka taun [[1898]], nalika Elie Metchnikoff nu nyuntik \'\'[[guinea pig]]\'\' ku spérma guinea pig séjénna, manggihan kabentukna [[antibodi]]; tapi antibodi éta teu aktif, nu nunjukkeun ayana suprési ku [[sistim imun]]na. Panalungtikan salajengna, kayaning nu dipidamel ku S. Mathur jeung J.M. Goust, nunjukkeun dihasilkeunana antibodi nu saméméhna teu aya ngaréspon asupna spérma. Antibodi ieu sacara salah mikawanoh [[limfosit T]] asli salaku [[antigén]] \'\'deungeun\'\', sahingga limfosit T diserang ku [[limfosit B]].\n\nKandungan mani séjénna nu nunjukkeun pangaruh imunosuprésif nyaéta plasma jeung limfosit mani. Catet yén tepungna kulit jeung mani ti nu kainféksi HIV kudu dicegah, kaasup ku jalma nu geus kainféksi ku virusna, sabab bisa ngabalukarkeun réinféksi nu pibahyaeun.\n\n==Tempo ogé==\n* [[spérma]]\n* [[spérmatogenesis]]\n* [[kapasitasi]]\n\n==Rujukan==\n*Mann T, Lutwak-Mann C. [[1981]]. \'\'[[Male Reproductive Function and Semen]]\'\'. [[Berlin, Germany|Berlin]]: [[Springer-Verlag]]. [[ISBN]] 3-540-10383, 0-387-10383.\n*Shivaji S, Scheit K-H, Bhargava PM. [[1990]]. \'\'Proteins of seminal plasma\'\'. [[New York]]: [[John Wiley & Sons]]. [[ISBN]] 0-471-84685-6.\n\n==Tumbu kaluar==\n*[http://www.jackinworld.com/library/science/semcomp.html \"What is semen made of?\" by Fred Guerra at JackinWorld.com]\n*[http://www.jackinworld.com/library/science/semprod.html \"Semen Production and ejaculation\" by M.J. Ecker at JackinWorld.com]\n*[http://www.tiscali.co.uk/lifestyle/healthfitness/menshealth/part1_4-2.html \"factors that affect spermatogenesis\"]\n*[http://www.salon.com/sex/feature/2002/06/19/semen/ Can semen cure the blues?]\n*[http://www.skfriends.com/hormones-semen.htm Hormones in semen may help to ease female depression]\n\n[[Category:Andrologi]]\n[[Category:Sistim baranahan]]\n\n[[de:Sperma]]\n[[en:Semen]]\n[[es:Semen]]\n[[fr:Sperme]]\n[[ja:精液]]\n[[pl:Sperma]]','',3,'Kandar','20050301102016','',0,0,0,0,0.358018721131,'20050302051215','79949698897983'); INSERT INTO cur VALUES (2203,0,'Spérmatogenesis','\'\'\'Spérmatogenesis\'\'\' nujul ka nyipta (Ing. \'\'genesis\'\') [[sél (biologi)|sél]] [[spérma]], nu lumangsung dina [[kanjut]] atawa [[siki kanjut|téstés]] [[jalu]]. Sél spérma tumuwuh tina [[sél stém]] bibit nu katelah [[spérmatogonia]]. Spérmatogonia didiferensiasi jadi [[spérmatosit]], [[spérmatid]] (satutasna [[miosis]]) nu ahirna jadi spérmatozoa nu \"asak\". Layanna spérmatogenesis pikeun [[bikang]] nyaéta [[oogenesis]].\n\nProsés spérmatogenesis diatur ku iber-iber [[hormon]]al sarta komunikasi sél-sél antara sél bibit nu keur tumuwuh (sél spérma) jeung [[sél Sertoli]]. \n\nSél Sertoli penting pikeun spérmatogenesis sabab nyadiakeun pangrojong pikeun sél nu keur tumuwuh - mindahkeun ka lumen \'\'[[semiferous tubule]]\'\' nepi ka asakna nalika dileupaskeun. Sél Sertoli ogé ngurangan motilitas jeung kapasitasi sél spérma sahingga hirupna bisa kajaga.\n\nSpérmatozoa dihasilkeun dina \'\'seminiferous tubule\'\' dina téstés. Mimitina [[spérmatogonia]], ngalaman [[mitosis]] jadi spérmatogonium tipe A atawa tipe B. Spérmatogonia tipe B jadi \'\'spérmatosit primér\'\', lajeng ngalaman beulah miosis sahingga jadi \'\'spérmatosit sekundér\'\', nu ngalaman beulah miotik séjénna sahingga jadi [[spérmatid]]. Spérmatogonia tipe A tetep salaku spérmatogonia, teu robah, nu pungsina jadi sél stém nu bakal beulah deui ngahasilkeun sél tipe A jeung B nu leuwih loba.\n\nSpérmatosit primér ngandung dua kali lipet [[DNA]] dibanding sél awak normal (2 × 2N). Unggal spérmatosit primér beulah jadi dua spérmatosit sekundér nu ngandung dua sét [[kromosom]] (2 × 1N).\nSpérmatosit sekundér beulah jadi dua spérmatid nu masing-masing ngandung sasét kromosom (1N), satengah tina DNA nu dipikabutuh pikeun nyiptakeun manusa (satengahna deui ti [[ovum]] nalika fértilisasi).\n\nSpérmatid masih mangrupa sél buleud. Nalika prosés nu disebut spérmiogenesis, sélna ngaluarkeun buntut, mungkus DNA na huluna, nutupan huluna ku [[akrosom]] nu kawas lisosom, sarta ngawangun wewengkon beuheung nu ngahasilkeun tanaga/[[énergi]] nu padet ku [[mitokondria]] sahingga jadi spérmatozoa asak. Salajengna spérmatozoa dileupaskeun ka lumén \'\'seminiferous tubule\'\' sarta pindah dina cairan téstis ka [[épididimis]] pikeun ngasakkeun sangkan bisa ngojay jeung ngabuahan ovum.\n\n[[Category:Sistim baranahan]]\n[[Category:Biologi tumuwuh]]\n[[Category:Sél bibit]]\n[[Category:Andrologi]]\n[[en:Spermatogenesis]]','',3,'Kandar','20050301112649','',0,0,0,1,0.126656661873,'20050315112136','79949698887350'); INSERT INTO cur VALUES (2204,0,'Kangaranan_Urang_Sunda','Loba pisan ngaran anu geus ilahar dipake ku urang [[Sunda]]. Diantarana aya dina catetan ieu.\n==Anu ilahar dipaké boh ku lalaki, boh ku awéwé==\n;A: [[Ade]] \n;D: [[Dian]]\n;I: [[Ira]]\n\n==Anu ilahar dipake ku Lalaki wungkul==\n;A: [[Aa]], [[Aang]], [[Aceng]], [[Agus]], [[Ahmad]], [[Ajat]], [[Amat]], [[Andung]], [[Ara]], [[Asep]], [[Adun]]\n;C: [[Cahya]], [[Cecep]], [[Cece]]\n;D: [[Dana]], [[Dani]], [[Dayat]], [[Dedi]], [[Deni]], [[Dodo]], [[Dudi]], [[Duduh]], [[Dudung]], [[Durahman]], [[Dadan]]\n;E: [[Edi]], [[Encep]], [[Engkus]], [[Endang]], [[Elan]], [[Enjang]]\n;G: [[Ganjar]], [[Gigin]],[[Ginanjar]], [[Gugum]], [[Gugun]], [[Gunawan]]\n;H: [[Hamdani]], [[Heri]], [[Hidayat]]\n;I: [[Ihin]], [[Indra]]\n;J: [[Jajang]]\n;K: [[Kurniawan]], [[Kuswara]]\n;L: [[Lili]]\n;M: [[Maman]], [[Mamat]], [[Memed]], [[Momoh]], [[Momon]], [[Mulyana]]\n;N: [[Nanang]], [[Nandar]], [[Nugraha]]\n;O: [[Oman]], [[Omo]], [[Ono]]\n;P: [[Pupun]], [[Purnama]]\n;R: [[Raditya]], [[Rahmat]]\n;S: [[Sadeli]], [[Sasmita]], [[Sobana]], [[Sobarna]], [[Solihin]], [[Soma]], [[Sudirja]], [[Sudrajat]], [[Sukarya]], [[Sutarja]], [[Sutarya]], [[Sutisna]]\n;T: [[Tata]], [[Teteng]], [[Tirta]], [[Tutun]]\n;Y: [[Yaya]], [[Yoyo]], [[Yayat]]\n;U: [[Udung]], [[Ujang]], [[Uu]]\n;W: [[Waluya]], [[Wahyu]], [[Wijaya]], [[Wawan]]\n \n[[Category:Sunda]]\n\n==Anu ilahar dipake ku Awewe wungkul==\n;A: [[Aam]]\n;D: [[Dadah]], [[Dedah]]\n;E: [[Ecin]], [[Ela]], [[Enok]], [[Entin]], [[Eros]], [[Esih]], [[Euis]], [[Éndah]]\n;É: [[Endang|Éndang]], [[Eem]], [[Enah]]\n;I: [[Iceu]], [[Icih]], [[Ikoh]], [[Ira]], [[Ita]], [[Irma]], [[Iyah]], [[Ijah]]\n;K: [[Kokom]]\n;L: [[Lilis]]\n;M: [[Mamah]], [[Mariah]], [[Mariam]]\n;N: [[Neneng]], [[Nenden]], [[Neni]], [[Nia]], [[Nining]], [[Nunung]]\n;O: [[Omah]], [[Omoh]], [[Odah]], [[Ocoh]]\n;P: [[Pupung]], [[Puspita]]\n;R: [[Ratna]], [[Ratih]], [[Ratnasih]], [[Rela]], [[Rusita]], [[Rusti]]\n;S: [[Sari]], [[Sekar]]\n;T: [[Tia]], [[Tita]], [[Titin]], [[Tiktik]]\n\n(Aya nu sanes? Mangga dicutat di dieu ngagunakeun tumbu \'édit\' di luhur.)','',3,'Kandar','20050307104856','',0,0,1,0,0.23543878979,'20050307104856','79949692895143'); INSERT INTO cur VALUES (2205,0,'Asep','*Ngaran \'Asep\' (dibaca asép), minangka ngalandikeun budak anu kasep.\n
    \n
    \n
    \n
    \n----\nBalik deui ka [[Kangaranan_Urang_Sunda]]','hapus \"(ceuk kolotna)\"',0,'83.129.218.95','20050303014806','',0,0,0,0,0.015404946841,'20050303014900','79949696985193'); INSERT INTO cur VALUES (2206,0,'Lipid','[[Image:Struktur_dasar_lipid.png|frame|Gambar 1: Struktur lipid. Loba lipid nu diwangun ku gugus hulu polar (P) jeung buntut nonpolar (U pikeun nonpolar). Lipid nu ditunjukkeun mangrupa fosfolipid (dua buntut). Gambar nu beulah kénca mangrupa vérsi nu dibadagkeun pikeun gambar nu beulah katuhu, nu bakal dipaké di handap pikeun ngawakilan lipid nu mibanda ranté hiji, dua, atawa tilu.]]\nIstilah lipid ngawengku rupa-rupa [[molekul]], malah kaasup sanyawaan nu rélatif teu leyur na cai atawa [[nonpolar]] nu asalna tina mahluk hirup, kayaning [[malam]], [[asam lemak]], fosfolipid, sfingolipid, jeung glikolipid turunan asam lemak sarta terpenoid kayaning rétinoid jeung [[stéroid]]. Sababaraha lipid mangrupa molekul liniér [[alifatik]], sedengkeun nu séjénna mibanda struktur cingcin. Sababaraha di antarana [[aromatik]], sedengkeun nu séjénna henteu. Sababaraha di antarana fléksibel, sedengkeun nu séjénna kaku.\n\nLipid loba mibanda ciri [[molekul polar|polar]] ti antara kalolobaan ciri nonpolarna. Umumna, guruntulan strukturna mah nonpolar atawa [[hidrofobik]] (\"sieun cai\"), nu hartina teu ngahiji jeung pangleyur polar kawas cai. Bagian séjén tina strukturna mibanda ciri polar atawa [[hidrofilik]] (\"resep cai\") sarta condong ngahiji jeung pangleyur polar kawas cai. Sipat ieu ngajadikeun lipid kaasup molekul amfifilik (mibanda boh bagian hidrofilik jeung hidrofobik). Dina kasus [[koléstérol]], gugus polarna mangrupa -OH ([[hidroxil]] atawa alkohol). Dina kasus fosfolipid, gugus polarna leuwih badag jeung leuwih polar, sakumaha didadarkeun di handap ieu.\n\nFosfolipid, atawa, leuwih benerna, gliserofosfolipid, diwangun dina pancuh gliserol nu numbukeun dua \"buntut\" turunan asam lemak ku beungkeut [[éster]] sarta hiji gugus \"hulu\" ku beungkeut éster [[fosfat]]. Asam lemak mangrupakeun ranté hidrokarbon nu teu cabangan, nu disambungkeun ku beungkeut tunggal (asam lemak \'\'\'[[lemak jenuh|jenuh]]\'\'\') atawa ku buh beungkeut tunggal jeung [[beungkeut ganda]] (asam lemak \'\'\'[[lemak teu jenuh|teu jenuh]]\'\'\'). Ranténa biasana mangrupa 14-24 gugus karbon. Gugus huluna fosfolipid nu kapanggih dina [[mémbran biologis]] nyaéta fosfatidil kolin ([[lésitin]]), fosfatidil étanol amin, fosfatidil serin, jeung fosfatidil inositol, nu gugus huluna bisa dirobah ku nambahkeun 1-3 gugus fosfat. Najan fosfolipid mangrupa komponén utama mémbran biologis, nu séjén kayaning sfingolipid jeung stérol (misalna koléstérol na mémbran sél sato) ogé aya.\n\nDina cai, hulu lipid nyanghareup ka lingkungan cai nu polar, sedengkeun buntut hidrofobikna ngajauhan cai. Buntut nonpolar lipid (U) ngagunduk jadi [[lipid lapis ganda]] (1) atawa [[misél]] (2). Hulu polarna (P) nyanghareup ka lingkungan caina. Dina lingkungan cairan polar, mun lipidna amfifilik buntut tunggal, mangka bakal kabentuk misél, sedengkeun lipid lapis ganda kabentuk mun lipidna fosfolipid nu buntutna dua (Fig. 2). Misél mangrupakeun lapisan \"lapis tunggal\" (\'\'monolayer\'\') sarta ngan bisa nepi ka ukuran nu tangtu, sedengkeun lapis ganda (\'\'bilayer\'\') bisa leuwih badag.\n\nMisél jeung lapis ganda misah ti lingkungan polar ku prosés nu disebut \"pangaruh hidrofobik\" (Ing. \'\'hydrophobic effect\'\'). When dissolving a nonpolar substance in a polar environment, the polar molecules (i.e. water in an aqueous solution) become more ordered around the dissolved nonpolar substance, since the polar molecules cannot form [[hydrogen bond]]s to the nonpolar molecule. Therefore, in an aqueous environment, the polar water molecules form an ordered \"clathrate\" cage around the dissolved nonpolar molecule. However, when the nonpolar molecules separate out from the polar liquid, the [[entropy]] (state of disorder) of the polar molecules in the liquid increases. This is essentially a form of phase separation, similar to the spontaneous separation of oil and water into two separate phases when one puts them together.\n\n[[Image:Lipid_bilapis_jeung_misel.png|thumb|250px|Gambar 2: Pangaturan mandiri lipid.]] \n\nThe self-organisation depends on the concentration of the lipid present in solution. Below the critical micelle concentration the lipids form a single layer on the liquid surface and are dispersed in solution. At the first critical micelle concentration (CMC-I), the lipids organise in spherical micelles, at the second critical micelle concentration (CMC-II) into elongated pipes, and at the lamellar point (LM or CMC-III) into stacked lamellae of pipes. The CMC depends on the chemical composition, mainly on the ratio of the head area and the tail length.\n\nLipid lapis ganda mangrupakeun pondasi pikeun sadaya mémbran biologis.\n\n==Tempo ogé==\n*[[Biokimia]]\n*[[Gajih]]\n\n==Tumbu kaluar==\n*[http://www.biochemweb.org/lipids_membranes.shtml Lipids, Membranes and Vesicle Trafficking - The Virtual Library of Biochemistry and Cell Biology]\n\n[[Category:Lipid]]\n\n[[ca:Lípid]]\n[[da:Lipid]]\n[[de:Lipide]]\n[[en:Lipid]]\n[[es:Lípido]]\n[[eo:Lipido]]\n[[lv:Lipīdi]]\n[[nl:Lipide]]\n[[ja:脂質]]\n[[pl:Lipid]]\n[[sv:Lipid]]\n[[is:Lípíð]]','',3,'Kandar','20050302085225','',0,0,0,0,0.061011134747,'20050302085225','79949697914774'); INSERT INTO cur VALUES (2207,6,'Struktur_dasar_lipid.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050302063344','',0,0,0,1,0,'20050302085244','79949697936655'); INSERT INTO cur VALUES (2208,1,'Wikipédia:_Panglawungan','','',3,'Kandar','20050302110430','',0,0,0,0,0.272024735599,'20050302110430','79949697889569'); INSERT INTO cur VALUES (2209,1,'Unsur_kimia','Di handap ieu citakan pikeun eusi kaca [[unsur kimia|unsur-unsur kimia]].\n----\n\n\n__ nyaéta [[unsur kimia]] na [[tabel periodik]] nu lambangna __ jeung [[nomer atom]] __. \n\n\n\n\n \n\n\n\n \n\n\n\n\n\n\n\n \n \n \n\n \n\n \n\n \n\n \n\n\n\n \n\n \n\n \n \n\n \n\n \n\n\n\n \n\n \n\n\n\n\n\n \n\n\n\n\n\n \n\n \n\n \n\n\n\n \n\n\n\n\n\n\n\n
    \'\'\'Sipat-sipat\'\'\'
    \'\'\'Umum\'\'\'
    [[Daptar unsur dumasar ngaran|Ngaran]], [[Daptar unsur dumasar lambang|Lambang]], [[Daptar unsur dumasar wilangan|Wilangan]]__, __, __
    [[dérét tabel periodik|Dérét]] ____________
    [[golongan tabel periodik|Golongan]], [[periode tabel periodik|Periode]], [[blok tabel periodik|Blok]][[unsur golongan _|_(_)]], [[unsur periode _|_]] , [[Orbital atom|_]]
    [[Dénsitas]], [[skala teuas Mohs|Kateuasan]] __ [[kilogram per méter kubik|kg/m3]], __
    [[warna|katémbong]] __
    \'\'\'Atomik\'\'\'
    [[beurat atom]] __ [[unit massa atom|amu]]
    [[radius atom]] __ [[pikométer|pm]]
    [[radius kovalén]] (kira) __ (_) pm
    [[radius van der Waals]] __ pm
    [[konfigurasi éléktron]] [[[__|_]]]___
    [[éléktron|e-]] per [[tingkat énergi]]_, _
    [[Wujud oksidasi]] ([[Oxida]]) _ (__)
    [[Struktur kristal]] __
    \'\'\'Fisik\'\'\'
    [[Wujud zat]] __ ([[magnetisme|__]])
    [[Titik lééh]] __ [[Kélvin|K]] (__ °[[Fahrenheit|F]])
    [[Titik golak]] __ K (__ °F)
    [[Eusi molar]] __ [[angka ilmiah|×]]10-3 [[méter kubik per mol|m3/mol]]
    [[Panas nguap]] __ [[kilojoule per mol|kJ/mol]]
    [[Panas fusi]] __ kJ/mol
    [[Tekenan uap]] __ [[Pascal (unit)|Pa]] at __ K
    [[Cepet sora]] __ [[méter per detik|m/s]] at __ K
    \'\'\'Rupa-rupa\'\'\'
    [[Éléktronégativitas]] __ ([[skala Pauling]])
    [[Kapasitas panas spésifik]] __ [[joule per kilogram-kélvin|J/(kg*K)]]
    [[Konduktivitas listrik]] __ 106/m [[ohm]]
    [[Konduktivitas panas]] __ [[watt per méter-kélvin|W/(m*K)]]
    1st [[poténsial ionisasi]] __ kJ/mol
    2nd poténsial ionisasi __ kJ/mol
    3rd poténsial ionisasi __ kJ/mol
    \'\'\'Isotop Pangstabilna\'\'\'
    \n\n\n\n\n\n\n\n\n\n\n
    [[Isotop|iso]][[kalimpahan alami|KA]][[waktu paruh]] [[mode uray|MU]][[énergi urai|ÉU]] [[méga|M]][[éléktron volt|eV]][[hasil uray|HU]]
    ___[[radioisotop sintétik|{sin.}]]______[[__|___]]
    _____%__ [[isotop stabil|stabil]] mibanda __ [[neutron]]
    _____%__ stabil mibanda __ neutron
    ___[[radioisotop renik|renik]]______[[__|___]]\n
    \n
    Unit [[SI]] & [[Suhu jeung tekenan baku|STP]] dipaké iwal mun disebutkeun béda.
    \n===Ciri penting=== \n\n===Mangpaat===\n*\n\n===Sajarah===\n\n===Sumber===\n
    \'\'Isolasi\'\' (* nuturkeun):
    \n\n===Sanyawaan===\n\n===Isotop===\n\n===Bahya===\n__\n\n\n\'\'\'Sumber iber jeung tumbu kaluar\'\'\'
    \n[http://periodic.lanl.gov/elements/_.html Los Alamos National Laboratory - _]
    \n[http://www.webelements.com/webelements/elements/text/_/index.html WebElements.com - _]
    \n[http://environmentalchemistry.com/yogi/periodic/_.html EnvironmentalChemistry.com - _]
    ','',3,'Kandar','20050302110213','',0,0,0,1,0.077671342071,'20050303214455','79949697889786'); INSERT INTO cur VALUES (2211,1,'Asep','asep juarna to urangsunda\n\nAsa ku teungteuingeun eta nu ngasupan wikipedia teh.\nEta we palebah ngaran \"Asep\" kateranganana teh\n\"Ngaran \'Asep\' (dibaca asép), minangka ngalandikeun\nbudak anu (ceuk kolotna) kasep.\" Padahal mah ulah make\n\"(ceuk kolotna)\", da geus puguh kuring teh kasep ceuk\nsarerea oge...\n\nAJ','hapus \"(ceuk kolotna)\"',0,'83.129.218.95','20050303014900','',0,0,0,1,0.68556335675,'20050303214455','79949696985099'); INSERT INTO cur VALUES (2212,1,'Kangaranan_Urang_Sunda','== Awewe atawa Lalaki? ==\n\n\nkela kela kela... abdi ngabuka eta web wikipeda teh naha dinu judul nami lalaki tina nami nu di awalan huruf n bet aya nami \" Neneng, neni, nia, nugrah\" tah palebah nami nugraha namah leres tapi eta teh nami kangge pameget atanapi lalaki.. tapi naha ari nami neneng, neni, nia sakaterang abdimah eta teh nami istri .\nAbdi terang teh pedah we nami abdi neni, da ku raraosan mah abdi teh kalebet istri saur sasaha ge teu acan aya nu nyebat abdi pameget sanaos ngarumaoskeun abdi kirang feminim \nmangga kanu ngadamel eta web mugi di lereskeun atuh !!\n\nbaktos\n\nNeni Kalong Van Batam Pos','',0,'83.129.218.95','20050303015455','',0,0,0,1,0.401737745386,'20050303214455','79949696984544'); INSERT INTO cur VALUES (2213,0,'Muhamad_Musa','\'\'\'Muhamad Musa\'\'\', atawa, mun lengkep jeung gelarna, \'\'\'Radén Haji Muhamad Musa\'\'\' ([[1822]] - [[10 Agustus]] [[1886]]), [[pangarang Sunda|pangarang]] nu ngaluluguan kasusastran citak Sunda, ulama, sarta inohong [[Sunda]] [[abad ka-19]].\n\n==Babad Salira==\nMuhamad Musa dibabarkeun di [[Garut]] salaku turunan ménak, anak Radén Rangga Suryadikusumah, Patih Kabupatén [[Limbangan]]. Munggaran meunang atikan formal ti [[pasantrén]] di [[Purwakarta]]. Geus kungsi munggah [[haji]] ka Mekah nalika ngora, diajak ku bapana. Kungsi nolak tawaran Pamaréntah [[Hindia Walanda]] sangkan jadi kapala gudang, anjeunna milih widang kaagamaan. Sanggeus jadi [[panghulu]], taun [[1864]] anjeunna diangkat jadi panghulu besar (Wal. \'\'Hoofdpanghoeloe\'\') Kabupatén Limbangan nepi ka maotna.\n\nMuhamad Musa sosobatan dalit pisan jeung [[Karel Frederik Holle|K. F. Holle]], pangusaha perkebunan entéh bangsa Walanda di Cikajang, nu naséhat-naséhatna ngeunaan bangsa pribumi (utamana [[Parahiangan]]) ka Pamaréntah Hindia Walanda diaku/dipercaya pisan.\n\nDalitna Musa jeung Holle nguntungkeun Musa, utamana tina campur gaulna jeung bangsa Walanda. Musa ku Pamaréntah Hindia Walanda dipercaya pisan, nepi ka ku jasana ka pamaréntah, kungsi dijangjian kalungguhan pikeun kulawargana nepi ka tujuh turunan. Tina dalitna jeung Holle ogé Musa bisa ngembangkeun bakat nulis/ngarangna sahingga karya-karyana (boh pituin atawa saduran/tarjamah) bisa dicitak nepi ka rébuan éksemplar di Jakarta.\n\nTi antara para putrana, nu kawarisan bakat/karesep nyerat nyaéta [[Lasminingrat]] jeung Kartawinata.\n\n==Karya-karyana==\nKarya Muhamad Musa pangmashurna nyaéta [[Wawacan Panji Wulung]] nu munggaran dicitak taun [[1871]]. Karya-karya séjénna nu dicitak di antarana,\n*[[1862]]: Wawacan Raja Sudibya, Wawacan Wulang Krama, Wawacan Dongéng-dongéng, Wawacan Wulang Tani;\n*[[1863]]: Carita Abdurahman jeung Abdurahim, Wawacan Seca Nala;\n*[[1864]]: Ali Muhtar, Élmu Nyawah;\n*[[1865]]: Wawacan Wulang Murid, Wawacan Wulang Guru;\n*[[1866]]: Dongéng-dongéng nu Aranéh;\n*[[1867]]: Dongéng-dongéng Pieunteungeun;\n*[[1872]]: Wawacan Lampah Sekar;\n*[[1881]]: Santri Gagal, Hibat.\n\n==Rujukan==\n*\'\'\'Mikihiro Moriyama\'\'\'. 2005. \'\'Semangat Baru: Kolonialisme, Budaya Cetak, dan Kesastraan Sunda Abad ke-19\'\'. Jakarta: Kepustakaan Populer Gramedia. ISBN 979-91-0023-2.\n\n[[Category:Inohong Sunda]]','/* Babad Salira */',3,'Kandar','20050309023445','',0,0,0,0,0.142083956463,'20050315084342','79949690976554'); INSERT INTO cur VALUES (2214,0,'Lasminingrat','\'\'\'Lasminingrat\'\'\' atanapi \'\'\'Radén Ayu Lasminingrat\'\'\', salasaurang lulugu kamajuan kaom istri Sunda, ku jalan ngadegkeun [[Sakola Kautamaan Istri]].\n\n{{pondok}}\n[[Category:Inohong Sunda]]','kategori',20,'DiN','20050303211127','',0,0,1,0,0.208318833362,'20050303211247','79949696788872'); INSERT INTO cur VALUES (2215,2,'DiN','\'\'\'DiN\'\'\', pondok tina Dian Tresna Nugraha.\nLangkung lengkep tiasa ditingali di http://diantn.free.fr, oge di http://en.wikipedia.org/wiki/User:DiN\n\n=== Proyek Kuring dina Wikipédia ===\n*[http://su.wikipedia.org/w/index.php?title=Special:Categories&limit=500&offset=0 Sistem kategori]\n{{browsergarapeun}}\n{{browserstandar}}\n
    \n{{browserkumplit}}
    \n=== Tumbu ===\n*[http://su.wikipedia.org/wiki/Wikipédia:Kuncén Rohangan kuncén]\n*[http://su.wikipedia.org/wiki/Special:Listadmins Daptar kuncén]','',20,'DiN','20050304081241','',0,0,1,0,0.185892708792,'20050304081241','79949695918758'); INSERT INTO cur VALUES (2216,0,'Wikipédia:Kategori','\'\'\'Bukaan\'\'\' [[Wikipédia]] dumasar kana [[Wikipédia:Kategori|kategori]], sumber-sumber referensi, artikel pinilih, [[Wikipédia:Indeks|urutan abjad]] atawa [[Wikipédia:Panéangan|paneangan]].\n\n{| \n|width=70% id=toc|\n

    \'\'\'[[:Category:Budaya|Budaya]]\'\'\'

    \n
    \n[[:Category:Ageman|Ageman]] – \n[[:Category:Basa|Basa]] –\n[[:Category:Budaya dumasar wewengkon|Dumasar wewengkon]] –\n[[:Category:Budaya Pop|Budaya Pop]] –\n[[:Category:Cultural movements|Movements]] –\n[[:Category:Féstival|Féstival]] –\n[[:Category:Filosofi|Filosofi]] –\n[[:Category:Hiburan|Hiburan]] –\n[[:Category:Hobi|Hobi]] –\n[[:Category:Humor|Humor]] –\n[[:Category:Ibing|Ibing]] –\n[[:Category:Kaulinan|Kaulinan]] –\n[[:Category:Literatur|Literatur]] –\n[[:Category:Média masa|Média masa]] –\n[[:Category:Mitos|Mitos]] –\n[[:Category:Musik|Musik]] –\n[[:Category:Musium|Musium]] –\n[[:Category:Olahraga|Olahraga]] –\n[[:Category:Pangibur|Pangibur]] –\n[[:Category:Partéy|Partéy]] –\n[[:Category:Radio|Radio]] –\n[[:Category:Sélébritis|Sélébritis]] –\n[[:Category:Seni|Seni]] –\n[[:Category:Sinéma|Sinéma]] –\n[[:Category:Télévisi|Télévisi]] –\n[[:Category:Tradisi|Tradisi]] –\n[[:Category:Wisata|Wisata]] –\n
    \n|\n|rowspan=8 valign=top id=toc|\n

    [[Wikipédia:Indeks|Indeks Abjad]]

    \n
    \n[[Special:Allpages/A|A]]\n[[Special:Allpages/B|B]]\n[[Special:Allpages/C|C]]\n[[Special:Allpages/D|D]]\n[[Special:Allpages/E|E]]\n[[Special:Allpages/F|F]]\n[[Special:Allpages/G|G]]\n[[Special:Allpages/H|H]]\n[[Special:Allpages/I|I]]\n[[Special:Allpages/J|J]]\n[[Special:Allpages/K|K]]\n[[Special:Allpages/L|L]]\n[[Special:Allpages/M|M]]\n[[Special:Allpages/N|N]]\n[[Special:Allpages/O|O]]\n[[Special:Allpages/P|P]]\n[[Special:Allpages/Q|Q]]\n[[Special:Allpages/R|R]]\n[[Special:Allpages/S|S]]\n[[Special:Allpages/T|T]]\n[[Special:Allpages/U|U]]\n[[Special:Allpages/V|V]]\n[[Special:Allpages/W|W]]\n[[Special:Allpages/X|X]]\n[[Special:Allpages/Y|Y]]\n[[Special:Allpages/Z|Z]]\n
    \n\n

    Référénsi

    \n*[[:Category:Akademik|Akademik]]\n*[[Wikipedia:Browse by overview|Article overviews]]\n*[[Daptar inohong|Biografi]]\n*[[Daftar diagram waktu|Diagram Waktu]]\n*[[:Category:Dokumen|Dokumen]] \n*[[Kumaha carana]]\n*[[:Category:Référénsi|Référénsi]]\n*[[:Category:Daftar|Rupa-rupa daptar]]\n*[[Daptar siklus|Siklus]]\n*[[Daptar tabel referensi|Tabel Referensi]]\n*[[:Category:Taun|Taun]]\n\n

    Artikel Pinilih

    \n*[[Lumangsung kiwari]]\n*[[Olahraga kiwari]]\n*[[Wikipedia:Artikel pinilih|Artikel Pinilih]]\n*[[Wikipedia:Gambar pinilih|Gambar Pinilih]]\n*[[Daptar poé géde|Poé gédé]]\n*[[Special:NewPages|Kaca Anyar]]\n*[[Wikipédia:Artikel ahéng|Artikel ahéng]]\n*[[:Category:Artikel pondok|Artikel pondok]]\n\n

    Sumber séjén

    \n*[[wiktionary:|Kamus]]\n*Images and media: [[:Category:Wikipedia images by topic|Wikipedia]], [[Commons:]]\n*[[wikinews:News|Warta]]\n*[[q:|Kutipan]]\n*[[wikisource:Main Page:English|Teks sumber]]\n*[[wikispecies:|Direktori spesies]]\n*[[wikibooks:|Buku teks]]\n|-\n|width=70% id=toc|\n\n

    \'\'\'[[:Category:Geografi|Geografi]]\'\'\'

    \n\n
    \n[[:Category:Afrika|Afrika]] –\n[[:Category:Amerika Kalér|Amerika Kalér]] –\n[[:Category:Amerika Kidul|Amerika Kidul]]\n[[:Category:Antartika|Antartika]] –\n[[:Category:Asia|Asia]] –\n[[:Category:Australia|Australia]] –\n[[:Category:Eropa|Eropa]] –\n[[:Category:Oseania|Oseania]] –\n
    \n \n[[:Category:Dayeuh|Dayeuh]] –\n[[:Category:Bumi|Bumi]] –\n[[:Category:Iklim|Iklim]] –\n[[:Category:Kampung|Kampung]]\n[[:Category:Kota|Kota]] –\n[[:Category:Nagara|Nagara]] –\n[[:Category:Peta|Peta]] –\n[[:Category:Subterranea|Subterranea]] –\n[[:Category:Taman nasional|Taman nasional]] –\n\n
    \n|-\n|width=70% id=toc|\n

    \'\'\'[[:Category:Sajarah|Sajarah]]\'\'\'

    \n
    \n[[:Category:Sajarah dumasar nagara|By Nagara]] –\n[[:Category:Sajarah dumasar waktu|By Waktu]] –\n[[:Category:Sajarah dumasar wewengkon|By Wewengkon]] –\n[[:Category:Sajarah dumasar topik|By Topik]] –\n[[:Category:Sajarawan|Sajarawan]] –\n[[:Category:Diagram waktu|Diagram waktu]]\n
    \n|\n|-\n|width=70% id=toc|\n

    \'\'\'[[:Category:Matematika|Matematika]]\'\'\'

    \n
    \n[[:Category:Aljabar|Algebra]] –\n[[:Category:Analisis matematik|Analisis]] –\n[[:Category:Angka|Angka]] –\n[[:Category:Aritmetika|Arithmetic]] –\n[[:Category:Bukti|Bukti]] –\n[[:Category:Ekonomi|Ekonomi]] –\n[[:Category:Èlmu komputer|Èlmu komputer]] –\n[[:Category:Geometri|Geometri]] –\n[[:Category:Kamungkinan jeung statistik|Statistik]] –\n[[:Category:Kasaruaan|Kasaruaan]] –\n[[:Category:Logika|Logika]] –\n[[:Category:Pangukuran|Pangukuran]] –\n[[:Category:Teorema|Teorema]] –\n[[:Category:Trigonometri|Trigonometri]]\n
    \n|-\n|id=toc|\n

    \'\'\'[[:Category:Kahirupan pribadi|Kahirupan pribadi]]\'\'\'

    \n
    \n[[:Category:Hiburan|Hiburan]] –\n[[:Category:Imah|Imah]] – \n[[:Category:Jalma|Jalma-jalma]] –\n[[:Category:Kadaharan|Kadaharan]] –\n[[:Category:Kaséhatan|Kaséhatan]] – \n[[:Category:Kulawarga|Kulawarga]] – \n[[:Category:Pangajaran|Pangajaran]] – \n[[:Category:Piaraan|Piaraan]] –\n[[:Category:Pikiran|Pikiran]]\n
    \n|-\n|id=toc|\n

    \'\'\'[[:Category:Sains|Sains]] and [[:Category:Alam|Alam]]\'\'\'

    \n
    \n[[:Category:Alam|Alam]] –\n[[:Category:Antropologi|Antropologi]] – \n[[:Category:Arkeologi|Arkeologi]] – \n[[:Category:Astronomi|Astronomi]] – \n[[:Category:Biologi|Biologi]] – \n[[:Category:Ekologi|Ekologi]] – \n[[:Category:Èlmu bumi|Èlmu bumi]] – \n[[:Category:Èlmu politik|Politik]] – \n[[:Category:Èlmu sosial|Èlmu sosial]] –\n[[:Category:Èlmuwan|Èlmuwan]] –\n[[:Category:Fisika|Fisika]] –\n[[:Category:Heuristik|Heuristik]] –\n[[:Category:Informatik|Informatik]] –\n[[:Category:Kimia|Kimia]] – \n[[:Category:Luar bumi|Luar bumi]] –\n[[:Category:Metode sains|Metode sains]] –\n[[:Category:Protosains|Protosains]] –\n[[:Category:Psikologi|Psikologi]] – \n[[:Category:Sains terapan|Sains terapan]] –\n[[:Category:Sajarah sains|Sajarah sains]]\n
    \n|-\n|id=toc|\n\n

    \'\'\'[[:Category:Kamasarakatan|Kamasarakatan]]\'\'\'

    \n
    \n[[:Category:Antropologi|Antropologi]] – \n[[:Category:Arkeologi|Arkeologi]] – \n[[:Category:Bahasa|Bahasa]] – \n[[:Category:Bisnis|Bisnis]] – \n[[:Category:Demografi|Demografi]] –\n[[:Category:Ekonomi|Ekonomi]] –\n[[:Category:Èlmu politik|Èlmu politik]] – \n[[:Category:Èlmu sosial|Èlmu sosial]] –\n[[:Category:Filosofi|Filosofi]] –\n[[:Category:Finance|Finance]] –\n[[:Category:Gender|Gender]] –\n[[:Category:Grup etnis|Grup etnis]] –\n[[:Category:Hukum|Hukum]] – \n[[:Category:Industri|Industri]] –\n[[:Category:Komunikasi|Komunikasi]] –\n[[:Category:Média|Média]] –\n[[:Category:Organisasi|Organisasi]] –\n[[:Category:Otomasi|Otomasi]] –\n[[:Category:Pamaréntahan|Pamaréntahan]] – \n[[:Category:Perang|Perang]] –\n[[:Category:Psikologi|Psikologi]] – \n[[:Category:Sajarah|Sajarah]] – \n[[:Category:Seksologi|Seksologi]] –\n[[:Category:Sosiologi|Sosiologi]]\n
    \n|-\n|id=toc|\n\n

    \'\'\'[[:Category:Téknologi|Téknologi]]\'\'\'

    \n
    \n[[:Category:Agrikultur|Agrikultur]] – \n[[:Category:Arsitektur|Arsitektur]] –\n[[:Category:Big Science|Big Science]] –\n[[:Category:Bioteknologi|Bioteknologi]] –\n[[:Category:Èléktronik|Èléktronik]] –\n[[:Category:Farmasi|Farmasi]] –\n[[:Category:Internét|Internét]] –\n[[:Category:Komputasi|Komputasi]] – \n[[:Category:Manufaktur|Manufaktur]] –\n[[:Category:Nanoteknologi|Nanoteknologi]] –\n[[:Category:Nuklir|Nuklir]] –\n[[:Category:Pakakas|Pakakas]] –\n[[:Category:Proses kimia|Proses kimia]] –\n[[:Category:Rékayasa|Rékayasa]] – \n[[:Category:Sora|Sora]] –\n[[:Category:Telekomunikasi|Telekomunikasi]] –\n[[:Category:Transportasi|Transportasi]] – \n[[:Category:Tutumpakan|Tutumpakan]]\n
    \n|}\n\n
    \n
    \n

    [[Wikipedia:Wikiportal|Wikiportals]]

    \n
    {{Wikiportals}}
    \n
    \n
    \n\n__NOTOC__ __NOEDITSECTION__ \n\n[[da:Kategorier]]\n[[de:Wikipedia nach Themen]]\n\n[[es:Wikipedia:Cómo explorar Wikipedia]]\n[[fr:Wikip%C3%A9dia:Cat%C3%A9gories]]\n[[ro:Wikipedia:Răsfoire]]\n[[ru:Википедия:Обзор]]\n[[fi:Wikipedia:Selaa luokittain]]','anyar',20,'DiN','20050303163418','',0,0,0,1,0.009195526939,'20050303214455','79949696836581'); INSERT INTO cur VALUES (2217,0,'Wikipédia:Indeks','Ieu tumbu pikeun artikel anu dimimitian ku abjad kasebut.\n\n\n{| class=\"plainlinks\" style=\"width: 80%; font-family:monospace; padding: 3px; background: #f7f8ff; border: 1px solid gray; margin: 0 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    \'\'\'[[:Category:Budaya|Budaya]]\'\'\'

    \n
    \n[[:Category:Ageman|Ageman]] – \n[[:Category:Arsitéktur|Arsitéktur]] –\n[[:Category:Bodor|Bodor]] –\n[[:Category:Budaya dumasar wewengkon|Dumasar wewengkon]] –\n[[:Category:Budaya pop|Pop]] –\n[[:Category:Cultural movements|Movements]] –\n[[:Category:Filosofi|Filosofi]] –\n[[:Category:Hiburan|Hiburan]] –\n[[:Category:Hobi|Hobi]] –\n[[:Category:Kaulinan|Kaulinan]] –\n[[:Category:Literatur|Literatur]] –\n[[:Category:Média|Média]] –\n[[:Category:Musik|Musik]] –\n[[:Category:Olahraga|Olahraga]] –\n[[:Category:Seni|Seni]] –\n[[:Category:Télévisi|Télévisi]] –\n[[:Category:Tradisi|Tradisi]] –\n[[:Category:Wisata|Wisata]] –\n
    \n|-\n|id=toc|\n\n

    \'\'\'Umum\'\'\'

    \n\n
    \n[[:Category:Filosofi|Filosofi]] –\n[[:Category:Geografi|Geografi]] –\n[[:Category:Matematika|Matematika]] –\n[[:Category:Sains|Sains]] –\n[[:Category:Sajarah|Sajarah]] –\n
    \n|\n|-\n|id=toc|\n

    \'\'\'[[:Category:Kahirupan pribadi|Kahirupan pribadi]]\'\'\'

    \n
    \n[[:Category:Atikan|Atikan]] – \n[[:Category:Gender|Gender]] –\n[[:Category:Hiburan|Hiburan]] –\n[[:Category:Imah|Imah]] – \n[[:Category:Jalma|Jalma]] –\n[[:Category:Kadaharan|Kadaharan]] –\n[[:Category:Kaséhatan|Kaséhatan]] – \n[[:Category:Kulawarga|Kulawarga]] – \n[[:Category:Piaraan|Piaraan]] –\n[[:Category:Pikiran|Pikiran]] –\n[[:Category:Psikologi|Psikologi]] – \n[[:Category:Séksologi|Séksologi]] –\n
    \n|-\n|id=toc|\n

    \'\'\'[[:Category:Alam|Alam]]\'\'\'

    \n
    \n[[:Category:Astronomi|Astronomi]] – \n[[:Category:Biologi|Biologi]] – \n[[:Category:Kimia|Kimia]] – \n[[:Category:Élmu bumi|Élmu bumi]] – \n[[:Category:Ekologi|Ekologi]] – \n[[:Category:Natural hazards|Natural hazards]] –\n[[:Category:Fisika|Fisika]] –\n[[:Category:Luar angkasa|Luar angkasa]]\n\n
    \n|-\n|id=toc|\n\n

    \'\'\'[[:Category:Kamasarakatan|Kamasarakatan]]\'\'\'

    \n
    \n[[:Category:Antropologi|Antropologi]] – \n[[:Category:Arkéologi|Arkéologi]] – \n[[:Category:Bisnis|Bisnis]] – \n[[:Category:Démografi|Démografi]] –\n[[:Category:Ekonomi|Ekonomi]] –\n[[:Category:Élmu bahasa|Élmu bahasa]] – \n[[:Category:Élmu pulitik|Pulitik]] – \n[[:Category:Élmu sosial|Élmu sosial]] –\n[[:Category:Finance|Finance]] –\n[[:Category:Grup étnis|Grup étnis]] –\n[[:Category:Hukum|Hukum]] – \n[[:Category:Komunikasi|Komunikasi]] –\n[[:Category:Média|Média]] –\n[[:Category:Organisasi|Organisasi]] –\n[[:Category:Pamaréntahan|Pamaréntahan]] – \n[[:Category:Perang|Perang]]\n[[:Category:Sajarah|Sajarah]] – \n[[:Category:Sosiologi|Sosiologi]] –\n
    \n|-\n|id=toc|\n\n

    \'\'\'[[:Category:Téknologi|Téknologi]]\'\'\'

    \n
    \n[[:Category:Biotéknologi|Biotéknologi]] –\n[[:Category:Éléktronik|Éléktronik]] –\n[[:Category:Industri|Industri]] –\n[[:Category:Internét|Internét]] –\n[[:Category:Komputasi|Komputasi]] – \n[[:Category:Manufaktur|Manufaktur]] –\n[[:Category:Prosés kimia|Prosés kimia]] –\n[[:Category:Rékayasa|Rékayasa]] – \n[[:Category:Télékomunikasi|Télékomunikasi]] –\n[[:Category:Transportasi|Transportasi]] – \n
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INSERT INTO cur VALUES (2260,14,'Téhnologi','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Budaya]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303195850','',0,0,0,1,0.239016135788,'20050316082300','79949696804149'); INSERT INTO cur VALUES (2261,14,'Atikan','{{artikelutama}}\n[[Category:Manusa]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201535','',0,0,0,0,0.118433521547,'20050303201535','79949696798464'); INSERT INTO cur VALUES (2262,14,'Biografi','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201234','',0,0,0,1,0.559157831997,'20050303214455','79949696798765'); INSERT INTO cur VALUES (2263,14,'Hirup-hurip','{{artikelutama}}\n[[Category:Budaya]]','',20,'DiN','20050303201303','',0,0,0,1,0.215531668236,'20050303214455','79949696798696'); INSERT INTO cur VALUES (2264,14,'Imah','{{artikelutama}}\n[[Category:Budaya]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201313','',0,0,0,1,0.024987692235,'20050303214455','79949696798686'); INSERT INTO cur VALUES (2265,14,'Kadaharan','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201326','',0,0,0,1,0.384771426979,'20050303214455','79949696798673'); INSERT INTO cur VALUES (2266,14,'Kaséhatan','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201345','',0,0,0,1,0.056258339682,'20050303214455','79949696798654'); INSERT INTO cur VALUES (2267,14,'Kulawarga','{{artikelutama}}\n[[Category:Budaya]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201400','',0,0,0,1,0.837928604916,'20050303214455','79949696798599'); INSERT INTO cur VALUES (2268,14,'Linguistik','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Budaya]]','',20,'DiN','20050303201413','',0,0,0,1,0.263390750605,'20050309114449','79949696798586'); INSERT INTO cur VALUES (2269,14,'Manusa','{{artikelutama}}\n[[Category:Alam]]','',20,'DiN','20050303201423','',0,0,0,1,0.390190525082,'20050303214455','79949696798576'); INSERT INTO cur VALUES (2270,14,'Psikologi','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Manusa]]','',20,'DiN','20050303201445','',0,0,0,1,0.437962499839,'20050303214455','79949696798554'); INSERT INTO cur VALUES (2271,14,'Tatamba','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303201500','',0,0,0,1,0.216713295799,'20050303214455','79949696798499'); INSERT INTO cur VALUES (2272,14,'Budaya','{{artikelutama}}','',20,'DiN','20050303201734','',0,0,0,1,0.130569421976,'20050303214455','79949696798265'); INSERT INTO cur VALUES (2273,14,'Bisnis','{{artikelutama}}\n[[Category:Masarakat]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202138','',0,0,0,1,0.160444001821,'20050303214455','79949696797861'); INSERT INTO cur VALUES (2274,14,'Ekonomi','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202155','',0,0,0,1,0.253237780496,'20050303214455','79949696797844'); INSERT INTO cur VALUES (2275,14,'Élmu_sosial','{{artikelutama}}\n[[Category:Sains]]','',20,'DiN','20050303202215','',0,0,0,1,0.442154560278,'20050303214455','79949696797784'); INSERT INTO cur VALUES (2276,14,'Hukum','{{artikelutama}}\n[[Category:Hirup-hurip]]\n[[Category:Budaya]]','',20,'DiN','20050303202245','',0,0,0,1,0.431187836213,'20050303214455','79949696797754'); INSERT INTO cur VALUES (2277,14,'Komunikasi','{{artikelutama}}\n[[Category:Hirup-hurip]]\n[[Category:Budaya]]','',20,'DiN','20050303202311','',0,0,0,1,0.109808548644,'20050303214455','79949696797688'); INSERT INTO cur VALUES (2278,14,'Masarakat','{{artikelutama}}\n[[Category:Budaya]]\n[[Category:Manusa]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202909','',0,0,0,0,0.047534288071,'20050316083953','79949696797090'); INSERT INTO cur VALUES (2279,14,'Pulitik','{{artikelutama}}\n[[Category:Hirup-hurip]]\n[[Category:Masarakat]]','',20,'DiN','20050303202400','',0,0,0,1,0.118269126157,'20050303214455','79949696797599'); INSERT INTO cur VALUES (2280,14,'Pamaréntah','{{artikelutama}}\n[[Category:Budaya]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202404','',0,0,0,1,0.374984531994,'20050303214455','79949696797595'); INSERT INTO cur VALUES (2281,14,'Sajarah','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Manusa]]','',20,'DiN','20050303202431','',0,0,0,1,0.438256686145,'20050304133905','79949696797568'); INSERT INTO cur VALUES (2282,14,'Sosiologi','{{artikelutama}}\n[[Category:Sains]]\n[[Category:Élmu sosial]]\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202506','',0,0,0,1,0.419334744676,'20050303214455','79949696797493'); INSERT INTO cur VALUES (2283,14,'Tata_nagara','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303202523','',0,0,0,1,0.154768253587,'20050303214455','79949696797476'); INSERT INTO cur VALUES (2284,14,'Karesep','{{artikelutama}}\n[[Category:Hirup-hurip]]\n[[Category:Manusa]]','',20,'DiN','20050303202553','',0,0,0,1,0.652331288646,'20050303214455','79949696797446'); INSERT INTO cur VALUES (2285,14,'Pelesir','{{artikelutama}}\n[[Category:Hiburan]]','',20,'DiN','20050303202603','',0,0,0,1,0.299431427884,'20050303214455','79949696797396'); INSERT INTO cur VALUES (2286,14,'Sajak','{{artikelutama}}\n[[Category:Seni]]\n[[Category:Budaya]]\n[[Category:Linguistik]]','',20,'DiN','20050303202629','',0,0,0,1,0.019216513762,'20050303214455','79949696797370'); INSERT INTO cur VALUES (2287,14,'Seni_visual_lan_desain','{{artikelutama}}\n[[Category:Seni]]','',20,'DiN','20050303202639','',0,0,0,1,0.686147600988,'20050303214455','79949696797360'); INSERT INTO cur VALUES (2288,14,'Televisi','{{artikelutama}}\n[[Category:Komunikasi]]\n[[Category:Téhnologi]]\n[[Category:Média]]','',20,'DiN','20050303202721','',0,0,0,1,0.209193811993,'20050303214455','79949696797278'); INSERT INTO cur VALUES (2289,14,'Matematika','{{artikelutama}}','',20,'DiN','20050303203422','',0,0,0,1,0.089778240962,'20050303214455','79949696796577'); INSERT INTO cur VALUES (2290,14,'Anatomi','{{artikelutama}}\n[[Category:Biologi]]\n[[Category:Manusa]]','',20,'DiN','20050303204724','',0,0,1,0,0.282590470486,'20050303205905','79949696795275'); INSERT INTO cur VALUES (2291,14,'Alat_Matematik','{{artikelutama}}\n[[Category:Matematik]]','',20,'DiN','20050303204705','',0,0,0,1,0.03348296597,'20050303214455','79949696795294'); INSERT INTO cur VALUES (2292,14,'Andrologi','{{artikelutama}}\n[[Category:Biologi]]','',20,'DiN','20050303204850','',0,0,0,1,0.10803636894,'20050303214455','79949696795149'); INSERT INTO cur VALUES (2293,14,'Asam','{{artikelutama}}\n[[Category:Kimia]]','',20,'DiN','20050303204920','',0,0,0,1,0.192017438163,'20050303210525','79949696795079'); INSERT INTO cur VALUES (2294,14,'Asam_amino','{{artikelutama}}\n[[Category:Protéin]]\n[[Category:Kimia]]','',20,'DiN','20050303205033','',0,0,0,1,0.006830930329,'20050307092343','79949696794966'); INSERT INTO cur VALUES (2295,14,'Analisis_matematik','{{artikelutama}}\n[[Category:Matematik]]','',20,'DiN','20050303205150','',0,0,0,1,0.01414828146,'20050303214455','79949696794849'); INSERT INTO cur VALUES (2296,14,'Asia','{{artikelutama}}\n[[Category:Bumi]]\n[[Category:Élmu bumi]]\n[[Category:Géografi]]','',20,'DiN','20050303205625','',0,0,1,0,0.207221617165,'20050303205625','79949696794374'); INSERT INTO cur VALUES (2297,14,'Aljabar','{{artikelutama}}\n[[Category:Matematik]]','',20,'DiN','20050303210119','',0,0,1,0,0.011200214319,'20050303210119','79949696789880'); INSERT INTO cur VALUES (2298,14,'Aljabar_abstrak','{{artikelutama}}\n[[Category:Aljabar]]','',20,'DiN','20050303205948','',0,0,1,1,0.009400165743,'20050303214455','79949696794051'); INSERT INTO cur VALUES (2299,14,'Aljabar_linear','{{artikelutama}}\n[[Category:Aljabar]]','',20,'DiN','20050303210001','',0,0,1,1,0.030903083596,'20050303214455','79949696789998'); INSERT INTO cur VALUES (2300,0,'Asam_karboxilat','#REDIRECT [[Asam karboksilat]]\n','Asam karboxilat dipindahkeun ka Asam karboksilat',20,'DiN','20050303210134','',0,1,0,1,0.498452981116,'20050303210134','79949696789865'); INSERT INTO cur VALUES (2301,14,'Algoritma','{{artikelutama}}\n[[Category:Élmu komputer]]\n[[Category:Matematik]]','',20,'DiN','20050303210221','',0,0,0,1,0.820494932778,'20050303214455','79949696789778'); INSERT INTO cur VALUES (2302,14,'Inohong_Sunda','{{artikelutama}}\n[[Category:Sunda]]','',20,'DiN','20050304133622','',0,0,1,0,0.022092248145,'20050309023445','79949695866377'); INSERT INTO cur VALUES (2304,14,'Dahareun_jeung_inuman','{{artikelutama}}\n[[Category:Hirup-hurip]]','',20,'DiN','20050303211548','',0,0,1,1,0.434905398241,'20050303211548','79949696788451'); INSERT INTO cur VALUES (2305,14,'Sanyawa_anorganik','{{artikelutama}}\n[[Category:Sanyawa kimia]]\n[[Category:Kimia]]','',20,'DiN','20050303211723','',0,0,1,1,0.289873794627,'20050303214455','79949696788276'); INSERT INTO cur VALUES (2306,14,'Sanyawa_kimia','{{artikelutama}}\n[[Category:Kimia]]','',20,'DiN','20050303211807','',0,0,1,1,0.320245302126,'20050303214455','79949696788192'); INSERT INTO cur VALUES (2309,0,'Wikipédia:Pitulung','\'\'Salengkepna tiasa ditingali dina [[Pitulung:_Eusi|daptar eusi pitulung]]\'\'','',20,'DiN','20050303214442','',0,0,1,1,0.101274950627,'20050303214442','79949696785557'); INSERT INTO cur VALUES (2310,10,'Browsergarapeun','
    \n\'\'\'[[Special:Lonelypages|Kaca nunggelis]] - [[Special:Uncategorizedpages|Kaca nu can dikategorisasi]] - [[Special:Wantedpages|Kaca nu dipikabutuh]] - [[Special:Shortpages|Kaca pondok]] - [[Special:Deadendpages|Kaca buntu]]\'\'\'\n
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    \'\'\'Topik nu aya patula-patalina jeung [[runtah]]:\'\'\'
    \n[[Kompos]] - \n[[Polusi]] - \n[[Treuk runtah]] - \n[[Wadah runtah]] - \n[[Ngokolakeun runtah]] - \n[[Ngamangpaatkeun runtah]]\n
    ','',20,'DiN','20050304203155','',0,0,0,1,0.05722790082,'20050304203155','79949695796844'); INSERT INTO cur VALUES (2314,0,'Wikipédia:Kasalahan_umum','Wikipédia mangrupa proyek balaréa pikeun ngawujudkeun [[ensiklopédi]] nu pangmunelna dina sakabéh basa di dunia, kaasup [[Basa Sunda]]. Kukituna, hayu babarengan jeung nurut kana sababaraha aturan ngeunaan Wikipédia di handap ieu.\n\nWikipédia téh lain:\n* \'\'\'Kamus\'\'\'. Cikan tuliskeun artikel anu rada munel. Kamus ayana di proyek [[Wiktionary]].\n* \'\'\'\'\'Bulletin board\'\'\'\'\' atawa tempat neundeun pesen. Cikan tulis artikel anu boga harti, ulah nulis pesen-pesen nu \'\'ngawur\'\'. Pikeun coba-coba, gunakeun tempat [[Wikipédia:Kotrétan| ngotrét]].\n* \'\'\'Rohangan \'\'chat\'\'\'\'\'. Wikipédia lain tempat pikeun ngobrol, kaca sawala lain jang maksud éta.\n* \'\'\'Tempat nyimpen data\'\'\'. Pakakas Wikipedia aya watesna, kukituna kudu dijaga munel jeung \'\'éfisien\'\'.\n* \'\'\'Portal warta\'\'\'. Wikipédia utamana mangrupa ensiklopédi, jadi cutatkeun warta aktual saperluna, teu kudu loba teuing, cukup nu ngawakilan. Pikeun warta, sabenerna aya [[Wikinews]].\n* \'\'\'Porum pulitik\'\'\'. Kami di Wikipédia ngajungjung hak kabébasan ngungkapkeun pamadegan, namung ensiklopédi kudu nétral jeung inpormatip, lain persuasip.\n* \'\'\'Tempat dakwah\'\'\'. Kami di Wikipédia ngajungjung hak kabébasan ngagem ageman jeung ngalakukeun ibadah. Kukituna, urang silih ngahormat kabébasan batur. Saupama aya artikel patali jeung ageman, coba ngagunakeun [[Wikipédia:NPOP|sikep nu netral]].\n* \'\'\'Tempat iklan\'\'\'. Ulah ngiklankeun hiji produk di Wikipédia. Pamaké bisa nyutatkeun tumbu (link) dina halaman ngeunaan hiji produk, namung teu kudu kaleuleuwihan tur tetep nétral.\n\nPanutup, Wikipédia Basa Sunda diayakeun pikeun lain jang [[urang Sunda]] wungkul, namung pikeun saha waé nu ngagunakeun Basa Sunda. Hatur nuhun..\n\n==Tingali ogé==\n*[[Wikipédia:Pituduh éjaan]]\n*[[Wikipédia:Pituduh ngagunakeun kekecapan]]\n\n[[Category:Wikipédia|Kasalahan umum]]\n\n[[ca:Viquipèdia:Errors freqüents]]\n[[da:Wikipedia:Mest almindelige begynderfejl på Wikipedia]]\n[[de:Wikipedia:Die häufigsten Wikipedia faux pas]]\n[[en:Wikipedia:Avoiding common mistakes]]\n[[fr:Wikipédia:Les faux-pas les plus courants]]\n[[ia:Wikipedia:Errores commun a evitar]]\n[[ja:Wikipedia:ウィキペディアで起こしがちな間違い]]\n[[ms:Wikipedia:Kesalahan_biasa_Wikipedia]]\n[[pl:Wikipedia:Najczęstsze nieporozumienia]] \n[[pt:Wikipedia:Erros freqüentes]]\n[[sl:Wikipedija:Najpogostejše stranpoti Wikipedije]]\n[[zh:Wikipedia:最常见失礼行为]]','',20,'DiN','20050305092944','',0,0,0,1,0.618704759951,'20050305092944','79949694907055'); INSERT INTO cur VALUES (2315,10,'KolomWikipédia','==== Alam jeung Élmu Alam ====\n[[:Category:Alam|Alam]] - \n[[:Category:Astronomi|Astronomi]] - \n[[:Category:Biologi|Biologi]] - \n[[:Category:Ékologi|Ékologi]] - \n[[:Category:Élmu alam|Élmu alam]] - \n[[:Category:Élmu bumi|Élmu bumi]] - \n[[:Category:Fisika|Fisika]] -\n[[:Category:Géografi|Géografi]] - \n[[:Category:Kimia|Kimia]] - \n\n==== Téhnologi, Rékayasa, \'\'Software\'\', jeung Matematik ====\n[[:Category:Agrikultur|Agrikultur]] - \n[[:Category:Angkutan|Angkutan]] - \n[[:Category:Arsitéktur|Arsitéktur]] - \n[[:Category:Élmu komputer|Élmu komputer]] - \n[[:Category:Internét|Internét]] - \n[[:Category:Logika|Logika]] - \n[[:Category:Matematik|Matematik]] - \n[[:Category:Otomotif|Otomotif]] - \n[[:Category:Rékayasa software|Rékayasa software]] - \n[[:Category:Rékayasa|Rékayasa]] - \n[[:Category:Statistik|Statistik]] -\n[[:Category:Téhnologi|Téhnologi]] - \n\n==== Manusa, Kaséhatan, jeung Hirup-hurip ====\n[[:Category:Antropologi|Antropologi]] - \n[[:Category:Arkéologi|Arkéologi]] - \n[[:Category:Atikan|Atikan]] - \n[[:Category:Biografi|Biografi]] - \n[[:Category:Dahareun jeung inuman|Dahareun jeung inuman]] - \n[[:Category:Hirup-hurip|Hirup-hurip]] - \n[[:Category:Imah|Imah]] - \n[[:Category:Kaséhatan|Kaséhatan]] - \n[[:Category:Kulawarga|Kulawarga]] - \n[[:Category:Linguistik|Linguistik]] - \n[[:Category:Manusa|Manusa]] - \n[[:Category:Psikologi|Psikologi]] - \n[[:Category:Tatamba|Tatamba]] - \n[[:Category:sejenna|séjénna]]\n\n==== Masarakat, Élmu sosial, jeung Nagara ====\n[[:Category:Bisnis|Bisnis]] - \n[[:Category:Ekonomi|Ékonomi]] - \n[[:Category:Élmu sosial|Élmu sosial]] -\n[[:Category:Hukum|Hukum]] - \n[[:Category:Komunikasi|Komunikasi]] - \n[[:Category:Masarakat|Masarakat]] - \n[[:Category:Média|Média]] - \n[[:Category:Pamaréntah|Pamaréntah]] - \n[[:Category:Pulitik|Pulitik]] - \n[[:Category:Sajarah|Sajarah]] - \n[[:Category:Sosiologi|Sosiologi]] - \n[[:Category:Tata nagara|Tata nagara]] - \n[[:Category:Urusan umum|Urusan umum]] - \n[[Daptar nagara|Nagara]]\n\n==== Budaya, Ageman, Filosofi, Hiburan ====\n[[:Category:Ageman|Ageman]] - \n[[:Category:Bodor|Bodor]] - \n[[:Category:Budaya|Budaya]] - \n[[:Category:Filosofi|Filosofi]] - \n[[:Category:Hiburan|Hiburan]] - \n[[:Category:Karesep|Karesep]] - \n[[:Category:Kaulinan|Kaulinan]] - \n[[:Category:Musik|Musik]] - \n[[:Category:Olahraga|Olahraga]] - \n[[:Category:Pelesir|Pelesir]] - \n[[:Category:Sajak|Sajak]] - \n[[:Category:Seni visual lan desain|Seni visual lan desain]] - \n[[:Category:Seni|Seni]] - \n[[:Category:Televisi|Televisi]]\n\n[[http://su.wikipedia.org/w/index.php?title=Template:KolomWikipédia&action=edit édit]]\n__NOTOC__ __NOEDITSECTION__','',20,'DiN','20050305094447','',0,0,0,1,0.742847204612,'20050305094447','79949694905552'); INSERT INTO cur VALUES (2316,2,'Jae_hungkul','bismillaahirrahmaanirrohiim......
    \naduh..! kela.. urang mapatkeun ajian heula, babacaan heula howtona
    \nrada puyeng oge gitu loooooohh..!','',43,'Jae hungkul','20050308063053','',0,0,0,0,0.071181331843,'20050308063053','79949691936946'); INSERT INTO cur VALUES (2317,3,'Jae_hungkul','Wilujeng sumping, Kang Jae!\n\nNepangkeun, kuring kapapancénan jadi kuncén di ieu jalaloka. Mangga diantos sumbangsihna di Wikipédia Basa Sunda. [[User:Kandar|kandar]] 10:41, 7 Mar 2005 (UTC)','',3,'Kandar','20050307104124','',0,0,1,1,0.060618142335,'20050307104124','79949692895875'); INSERT INTO cur VALUES (2320,0,'Priangan','#REDIRECT [[Parahyangan]]\n','Priangan dipindahkeun ka Parahyangan',3,'Kandar','20050315075432','',0,1,0,1,0.75290252606,'20050315075432','79949684924567'); INSERT INTO cur VALUES (2321,0,'Garut','\'\'\'Garut\'\'\' mangrupakeun salasahiji [[kabupatén]] di propinsi [[Jawa Kulon]], [[Indonésia]]. Legana 3065.19 km² (1183.48 mi²), nu sacara [[géografi]]s, aya di antara 6°57′34″ – 7°44′57″ Lintang Kidul jeung 107°24′34″ – 108°7′34″ Bujur Wétan. Wawatesanana,\n\n* beulah wétan: kabupatén [[Tasikmalaya]]\n* beulah kulon: kabupatén [[Cianjur]] jeung [[Bandung]]\n* beulah kalér: kabupatén [[Sumedang]]\n* beulah kidul: [[samodra Indonésia]]\n\n===Kaayaan umum===\nSacara umum, Garut mibanda [[iklim]] [[tropis]] tapi tiis, suhu hawa rata-ratana 24 °C (76 °F). Curah hujan taunan rata-rata 2,590 mm (102 inci). Wilayah ieu ngawengku wewengkon [[lembah]] nu dikuriling ku [[gunung api]] (Gunung Karacak 1838 m, Cikuray 2821 m, [[Gunung Guntur|Guntur]] 2249 m, Papandayan 2622 m) di béh kalér, nu luhurna rata-rata 700–750 m luhureun beungeut laut.\n\n===Sajarah===\nDina [[2 Maret]] [[1811]], Kabupatén Balubur Limbangan direbut ku Gubernur Jéndral Herman W. Daendels (tentara kolonial Walanda) sahingga bupatina, Tumenggung Wangsakusumah II, turun. Kabupatén Balubur Limbangan ngawengku 6 subdistrik: Balubur, Malangbong, Wanaraja, Wanakerta, Cibeureum, jeung Papandak.\n\n[[16 Pébruari]] [[1813]], Kabupatén Limbangan anyar diadegkeun ku Thomas S. Raffles nu salajengna robah jadi Kabupatén Garut. RAA. Adiwijaya jadi Bupati munggaran Kabupatén Garut. Bupati nu katelah Dalem Cipeujeuh ieu jeneng bupati ti taun 1813 nepi ka [[1821]].\n\n===Pamaréntahan===\nSacara administratif, Garut kabagi jadi 42 [[kacamatan]] jeung 419 désa, nu pangeusina 2,173,623 jiwa (51% lalaki, 49% istri).\n\n===Topologi===\nDumasar [[topologi]]na, Garut dibagi jadi dua wilayah: \n* \'\'Garut Kalér\'\' nu ngawengku tatar luhur/pagunungan salaku pamasok poko [[béas]] di Garut\n* \'\'Garut Kidul\'\' nu lolobana mangrupa tataran nu teu rata, aya salosin walungan nu ngalir ka kidul, ngamuara di laut kidul.\n\n===Wisata===\nAya loba tempat wisata di Garut, ti mimiti wisata basisir di kidul nepi ka panorama pagunungan, kawah, situ, jeung curug. Malah geus ti jaman kolonial Walanda kénéh Garut kawentar salaku salasahiji tujuan wisata, boh keur wisatawan lokal atawa luar, nepi ka katelah salaku \"Swiss Van Java\".\n\n===Hasil bumi & industri===\nKasuburan taneuh teu rata kapangaruhan ku pagunungan, walungan, jeung tatar handap basisir, sahingga usaha [[tatanén]] nu loyog nyaéta perkebunan kawas entéh, ogé tani (sawah & huma), sayur, peternakan, sarta ngokolakeun leuweung.\n\nSababaraha hasil bumi Garut nu has di antarana,\n* [[jeruk Garut]]\n* [[domba Garut]]\n* [[dodol Garut]] \n* minyak akar wangi (Vetiver, \'\'Andropogon zizanioides\'\')\n* [[batik]] tulis Garutan\n* kaén [[sutra]] \n* batu akik\n* karajinan kulit\n* karajinan awi\n\n[[en:Garut]]','',3,'Kandar','20050315085532','',0,0,0,0,0.453138061484,'20050315085532','79949684914467'); INSERT INTO cur VALUES (2323,6,'Sperma.jpg','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050315110736','',0,0,0,1,0,'20050315110736','79949684889263'); INSERT INTO cur VALUES (2324,0,'Ovum','[[Image:Ovum.png|right|thumb|Ovum manusa]]\n\'\'\'Ovum\'\'\' (atawa sacara bébas, \'\'\'endog\'\'\' atawa \'\'\'sél endog\'\'\') nyaéta [[sél]] kelamin/séks [[bikang]]/wanoja atanapi [[gamét]]. Boh [[sato]] atawa [[siki]] tatangkalan mibanda endog. Istilah \'\'\'ovule\'\'\' dipaké pikeun endog siki tutuwuhan sarta pikeun endog ngora sato. Kecap ieu diturunkeun tina kecap [[basa Latin|Latin]] \'\'ovum\'\' (loba \'\'ova\'\') pikeun [[endog]].\n\nDina sato nu leuwih luhur, endog dihasilkeun ku [[organ (anatomi)|organ]] nu disebut [[ovarium]]. Dina sato [[ovipar]] (sadaya [[manuk]], kalolobaan [[lauk]], [[amfibi]], jeung [[réptil]]) endogna tumuwuhkeun lapisan panyalindungan nu dibawa ngaliwatan [[oviduk]] ka luar awak. Endog ieu [[fértilisasi|dibuahan]] ku [[spérma]] jalu boh di jero (kawas manuk) atawa saluareun awak bikangna (kawas lauk). Satutasna dibuahan, lajeng tumuwuh [[émbrio]], nu kaparaban ku gizi nu dikandung ku endog. It then hatches from the egg, outside the mother\'s body. See [[egg (biology)]] for a discussion of eggs of oviparous animals.\n\nIn the [[viviparous]] animals (which include [[human]]s and all other placental [[mammal]]s), the ovum is fertilized inside the female body, and the embryo then develops inside the [[uterus]] until it is born. It receives nutrition directly from the mother.\nThe ovum is the largest [[biological cell|cell]] in the human body, typically visible to the naked eye without the aid of a [[microscope]] or other magnification device.\n\nThere is an intermediate form, the [[ovoviviparous]] animals: the embryo develops within and is nourished by an egg as in the oviparous case, but then it hatches inside the mother\'s body shortly before birth, or just after the egg leaves the mother\'s body. Some fish, reptiles and many [[invertebrate]]s use this technique.\n\n==Tempo ogé==\n* [[endog (biologi)]]\n* [[fértilisasi]]\n* [[inseminasi]]\n* [[ovulasi]] \n* [[polinasi]]\n* [[reuneuh]]\n* [[spérma]]\n\n[[de:Eizelle]]\n[[en:Ovum]]\n[[es:Óvulo]]\n[[fr:Ovule]]\n[[lt:Kiaušialąstė]]\n[[nl:Eicel]]\n[[ja:卵子]]\n\n[[Category:Sistim baranahan]]\n[[Category:Sél bibit]]\n[[Category:Ginekologi]]\n[[Category:Cloning]]','',3,'Kandar','20050316110120','',0,0,1,0,0.639476669707,'20050316113156','79949683889879'); INSERT INTO cur VALUES (2325,14,'Unsur_kimia','[[Category:Kimia]]\n[[af:Category:Chemiese elemente]]\n[[ar:تصنيف:عناصر كيميائية]]\n[[bg:Категория:Химични елементи]]\n[[ca:Categoria:Elements químics]]\n[[cs:Kategorie:Chemické prvky]]\n[[da:Kategori:Grundstoffer]]\n[[de:Kategorie:Chemisches Element]]\n[[en:Category:Chemical elements]]\n[[eo:Kategorio:Kemiaj elementoj]]\n[[es:Categoría:Elementos químicos]]\n[[et:Kategooria:Keemilised elemendid]]\n[[eu:Category:Elementu kimikoak]]\n[[fi:Luokka:Alkuaineet]]\n[[fr:Catégorie:Élément chimique]]\n[[ga:Rang:Eolaíocht]]\n[[he:קטגוריה:יסודות כימיים]]\n[[hr:Category:Kemijski element]]\n[[hu:Kategória:Kémiai elemek]]\n[[id:Kategori:Unsur kimia]]\n[[is:Flokkur:Frumefni]]\n[[it:Categoria:Elementi chimici]]\n[[ja:Category:元素]]\n[[ko:Category:화학 원소]]\n[[ku:Kategorî:Element]]\n[[lt:Category:Cheminiai elementai]]\n[[lv:Category:Ķīmiskie elementi]]\n[[mk:Category:Хемиски елементи]]\n[[ms:Category:Химические элементы]]\n[[nds:Category:Chemisch Element]]\n[[nl:Categorie:Scheikundig element]]\n[[nn:Kategori:Grunnstoff]]\n[[no:Kategori:Grunnstoffer]]\n[[pl:Kategoria:Pierwiastki chemiczne]]\n[[pt:Categoria:Elementos químicos]]\n[[ru:Category:Химические элементы]]\n[[simple:Category:Chemical elements]]\n[[sk:Category:Chemické prvky]]\n[[sl:Category:Kemijski elementi]]\n[[sr:Category:Хемијски елемент]]\n[[sv:Kategori:Grundämnen]]\n[[th:Category:ธาตุเคมี]]\n[[vi:Category:Nguyên tố hóa học]]\n[[uk:Category:Хімічний елемент]]\n[[zh:Category:化学元素]]','interwiki',0,'61.10.7.26','20050315142330','',0,0,0,1,0.395275931213,'20050315142330','79949684857669'); INSERT INTO cur VALUES (2326,10,'Bandéranasional','{| cellpadding=\"1\" style=\"border: 1px solid #8888aa; background: #f7f8ff; padding: 5px; font-size: 95%; margin: 0 auto; text-align: center;\" align=\"center\"\n| style=\"background: #ccf;\" | \'\'\'[[Bandéra nasional]]\'\'\'\n|-\n| | [[Daptar bandéra nasional]] | [[Galeri bandéra nasional]]\n|-\n| | [[Daptar lambang nagara]]\n|}','',3,'Kandar','20050316085551','',0,0,0,1,0.581320591137,'20050316085551','79949683914448'); INSERT INTO cur VALUES (2327,6,'Ovum.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050316105929','',0,0,0,1,0,'20050316110122','79949683894070'); INSERT INTO cur VALUES (2328,6,'Fértilisasi.jpg','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050316112931','',0,0,0,1,0,'20050316113624','79949683887068'); INSERT INTO cur VALUES (2329,0,'Fértilisasi','[[Image:Fértilisasi.jpg|right|300px|thumb|Sél spérma keur nyoba ngabuahan sél endog]]\n\n\'\'\'Fértilisasi\'\'\' nyaéta prosés ngahijina [[spérma]] jeung [[ovum]], nu ngahasilkeun tumuwuhna [[émbrio]].\n\nSakabéh prosés tumuwuhna individu anyar disebut [[prokréasi]].\n\n==Fértilisasi mamalia==\n\nPikeun nganteurkeun spérma ka bikangna, si jalu ngasupkeun [[organ kelamin]]na, [[sirit]], kana [[heunceut]], palawangan kana organ kelamin bikang séjénna (prosés ieu mangrupa bagian tina [[sapatemon|kopulasi]]). Nalika si jalu [[éjakulasi|bucat]], sél-sél spérma nu dipancerkeun nuju ka ovum. \n\nThe [[capacitation|capacitated]] spermatozoon and the oocyte meet and interact in the \'\'ampulla\'\' of the [[fallopian tube]]. In mammals, binding of the spermatozoon to the [[zona pellucida]], an extracellular layer surrounding the [[oocyte]], initiates the [[acrosome reaction]]. This process releases the [[enzyme]] [[hyaluronidase]], which digests the matrix of [[hyaluronic acid]] in the vestments surrounding the oocyte. Fusion between the sperm and oocyte [[plasma membrane]]s follows, allowing the entry of the sperm [[nucleus]], [[mitochondrion|mitochondria]], [[centriole]] and [[flagellum]] into the oocyte. \n\nThis process ultimately leads to the formation of a [[diploid]] cell called a [[zygote]]. Once this happens, the female is said to be [[pregnant]].\n\n== Fértilisasi tatangkalan ==\n\nSanggeus na [[kembang]] lumangsung [[penyerbukan]], pollen grains attempt to travel into the ovary by creating a path called \"[[pollen tube]].\" The pollen tube does not directly reach the ovary in a straight line. It travels near the skin of the [[style]] and curls to the bottom of the ovary, then near the [[receptacle]], it breaks through the [[ovule]] and reaches the ovum to fertilize it. After being fertilized, the ovary starts to swell and becomes a [[fruit]]. \n\nWith multi-seeded fruits, multiple grains of pollen are necessary for syngamy with each ovule. \nThe process is easy to visualize if one looks at [[corn]] silk, which is the female flower of corn. Pollen from the [[tassel]] (the male flower) falls on the sticky external portion of the silk, then pollen tubes grow down the silk to the attached ovule. The dried silk remains inside the husk of the ear as the seeds mature, so one can carefully remove the husk to show the floral structures. The development of the flesh of the fruit is proportional to the percentage of fertilized ovules. For example, with [[watermelon]], about a thousand grains of pollen must be delivered and spread evenly on the three lobes of the stigma to make a normal sized and shaped fruit.\n\n==Tempo ogé==\n* [[fértilisasi in vitro]]\n* [[reuneuh]]\n* [[pollination]]\n\n==Rujukan==\n* \'\'\'Evans, JP & HM Florman\'\'\'. 2002. The state of the union: the cell biology of fertilization. \'\'Nature Medicine\'\'. 8 Suppl S57-63. \n\n[[Category:Réproduksi biologis]]\n[[en:Fertilisation]]\n[[es:Fecundación]]\n[[it:Fecondazione]]\n[[nl:Bevruchting]]\n[[pl:Zapłodnienie]]\n[[fr:Fécondation]]','/* Rujukan */',3,'Kandar','20050316113624','',0,0,1,0,0.250628984882,'20050316113624','79949683886375'); INSERT INTO cur VALUES (2330,6,'Organ_kelamin_wanoja.png','ti Wikipédia Inggris','ti Wikipédia Inggris',3,'Kandar','20050316115237','',0,0,0,1,0,'20050316115816','79949683884762'); INSERT INTO cur VALUES (2331,10,'SistimBaranahan','
    \n{| style=\"margin:0 auto;\" align=center width=\"75%\" class=\"toccolours\"\n|align=center style=\"background:#ccccff\"| \'\'\'[[Sistim baranahan]]\'\'\'\n|-\n|align=center| Wanoja: [[Cervix]] - [[Clitoris]] - [[Fallopian tube]]s - [[kalenjar Bartholin]] - [[Hymen]] - [[Kalenjar susu]]s - [[Ovary|Ovaries]] - [[Kalenjar Skene]] - [[Urethra]] - [[Uterus]] - [[Heunceut]]\n|-\n|align=center| Lalaki: [[Kalenjar Bulbourethral]] - [[Kalenjar Cowper]] - [[Ejaculatory duct]] - [[Epididymis]] - [[Sirit]] - [[Prostat]] - [[Kanjut]] - [[Seminal vesicle]]s - [[Spermatic cord]] - [[Testicle|Testes]] - [[Urethra]] - [[Vas deferens]]\n|}','',3,'Kandar','20050316120503','',0,0,0,1,0.048831116844,'20050316120503','79949683879496');