{"id":26638,"date":"2023-02-08T09:50:00","date_gmt":"2023-02-08T12:50:00","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/the-science-behind-falling-in-love-copy\/"},"modified":"2023-04-05T10:55:10","modified_gmt":"2023-04-05T13:55:10","slug":"statistics-parametric-tests","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/statistics-parametric-tests\/","title":{"rendered":"Kas ir statistikas parametriskie testi un kur tos piem\u0113rot?"},"content":{"rendered":"

Statistikas parametriskie testi ir statistisk\u0101s anal\u012bzes veids, ko izmanto, lai p\u0101rbaud\u012btu hipot\u0113zes par popul\u0101cijas vid\u0113jo v\u0113rt\u012bbu un dispersiju. \u0160o testu pamat\u0101 ir pie\u0146\u0113mums, ka pamat\u0101 eso\u0161ie dati atbilst norm\u0101lam sadal\u012bjumam, un tiem piem\u012bt vair\u0101kas galven\u0101s \u012bpa\u0161\u012bbas, tostarp notur\u012bba, ticam\u012bba un sp\u0113ja noteikt smalkas at\u0161\u0137ir\u012bbas datos.<\/p>\n\n\n\n

Parametriskos testus bie\u017ei izmanto da\u017e\u0101dos lietojumos, tostarp medic\u012bnas p\u0113t\u012bjumos, tirgus p\u0113t\u012bjumos un soci\u0101laj\u0101s zin\u0101tn\u0113s. \u0160aj\u0101s jom\u0101s p\u0113tnieki var izmantot parametriskos testus, lai noteiktu popul\u0101cijas vid\u0113jo v\u0113rt\u012bbu vai dispersiju izmai\u0146u noz\u012bm\u012bgumu vai lai noteiktu, vai konkr\u0113ta apstr\u0101de vai intervence ir b\u016btiski ietekm\u0113jusi datus.<\/p>\n\n\n\n

Visbie\u017e\u0101k sastopamie statistikas parametrisko testu veidi<\/h2>\n\n\n\n

T tests <\/h3>\n\n\n\n

Viens no visbie\u017e\u0101k izmantotajiem parametriskajiem testiem ir t-tests, ko izmanto, lai sal\u012bdzin\u0101tu divu popul\u0101ciju vid\u0113jos lielumus. . t-tests<\/a> pie\u0146em, ka pamat\u0101 eso\u0161ie dati ir norm\u0101li sadal\u012bti un ka abu popul\u0101ciju dispersijas ir vien\u0101das. Testa statistiku apr\u0113\u0137ina, izmantojot abu popul\u0101ciju vid\u0113jo v\u0113rt\u012bbu starp\u012bbu, kas dal\u012bta ar starp\u012bbas standartk\u013c\u016bdu.<\/p>\n\n\n\n

ANOVA tests<\/h3>\n\n\n\n

V\u0113l viens izplat\u012bts parametriskais tests ir dispersijas anal\u012bze (ANOVA), ko izmanto, lai sal\u012bdzin\u0101tu tr\u012bs vai vair\u0101ku popul\u0101ciju vid\u0113jos lielumus. . ANOVA tests<\/a> pie\u0146em, ka pamat\u0101 eso\u0161ie dati ir norm\u0101li sadal\u012bti un ka visu popul\u0101ciju dispersijas ir vien\u0101das. Testa statistiku apr\u0113\u0137ina, izmantojot dispersijas starp popul\u0101cij\u0101m attiec\u012bbu pret dispersiju popul\u0101cij\u0101s.<\/p>\n\n\n\n

Citi parametriskie testi<\/h3>\n\n\n\n

Papildus t-testam un ANOVA ir v\u0113l vair\u0101ki citi statistikas parametriskie testi, kurus izmanto da\u017e\u0101dos lietojumos, tostarp p\u0101ra t-tests, vienvirziena ANOVA, divvirzienu ANOVA, ANOVA ar atk\u0101rtotiem m\u0113r\u012bjumiem un jaukta dizaina ANOVA. Katram no \u0161iem testiem ir at\u0161\u0137ir\u012bgi pie\u0146\u0113mumi un testa statistika, un tos izmanto, lai risin\u0101tu da\u017e\u0101da veida p\u0113tniec\u012bbas jaut\u0101jumus.<\/p>\n\n\n\n

Viena no galvenaj\u0101m parametrisko testu priek\u0161roc\u012bb\u0101m ir to robustums, proti, tie nav jut\u012bgi pret pamat\u0101 eso\u0161o datu sadal\u012bjuma formu. Ja dati ir aptuveni norm\u0101li sadal\u012bti, parametriskie testi var sniegt prec\u012bzus rezult\u0101tus.<\/p>\n\n\n\n

Izveidojiet p\u0101rsteidzo\u0161u infografiku da\u017eu min\u016b\u0161u laik\u0101<\/h2>\n\n\n\n

Mind the Graph ir ide\u0101ls r\u012bks, lai apkopotu j\u016bsu datus un vizu\u0101li tos att\u0113lotu. Izmantojiet diagrammas, tabulas un zin\u0101tniskas ilustr\u0101cijas, lai padar\u012btu j\u016bsu darbu viegl\u0101k saprotamu.<\/p>\n\n\n\n

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Izveidot manu pirmo infografiku<\/a><\/div>\n<\/div>\n\n\n\n
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Statistikas parametrisko testu ticam\u012bba<\/h2>\n\n\n\n

V\u0113l viena parametrisko testu priek\u0161roc\u012bba ir to ticam\u012bba, jo tie balst\u0101s uz visp\u0101ratz\u012bt\u0101m statistikas metod\u0113m un pie\u0146\u0113mumiem. Parametrisko testu rezult\u0101ti ir \u013coti atk\u0101rtojami, un tos var izmantot, lai izdar\u012btu der\u012bgus secin\u0101jumus par pamatkopumu.<\/p>\n\n\n\n

Neraugoties uz to daudzaj\u0101m priek\u0161roc\u012bb\u0101m, parametriskie testi ne vienm\u0113r ir lab\u0101k\u0101 izv\u0113le katrai datu kopai. Da\u017eos gad\u012bjumos pamat\u0101 eso\u0161ie dati var neb\u016bt sadal\u012bti norm\u0101li vai popul\u0101ciju vari\u0101cijas var neb\u016bt vien\u0101das. \u0160\u0101dos gad\u012bjumos neparametriskie testi var b\u016bt piem\u0113rot\u0101ki.<\/p>\n\n\n\n

Parametriskie testi pret neparametriskajiem testiem<\/h2>\n\n\n\n

Neparametriskie testi ir statistisk\u0101s anal\u012bzes veids, kas neizvirza nek\u0101dus pie\u0146\u0113mumus par pamat\u0101 eso\u0161o datu sadal\u012bjumu. T\u0101 viet\u0101, lai noteiktu rezult\u0101tu noz\u012bm\u012bgumu, tie balst\u0101s uz datu rangu. Da\u017ei izplat\u012bt\u0101kie neparametriskie testi ir \u0161\u0101di. Vilkoksona rangu summas tests<\/a>, un Kruskala-Valisa tests<\/a>, un Manna-Vitnija tests<\/a>.<\/p>\n\n\n\n

Izv\u0113loties starp parametriskiem un neparametriskiem testiem, ir svar\u012bgi \u0146emt v\u0113r\u0101 datu raksturu un p\u0113t\u0101mo jaut\u0101jumu. Kopum\u0101 parametriskie testi ir piem\u0113roti datiem ar norm\u0101lu sadal\u012bjumu un vien\u0101d\u0101m vari\u0101cij\u0101m, bet neparametriskie testi ir piem\u0113roti datiem, kas neatbilst \u0161iem pie\u0146\u0113mumiem.<\/p>\n\n\n\n

Statistikas parametrisk\u0101 testa piem\u0113rs<\/h2>\n\n\n\n

Pie\u0146emsim, ka p\u0113tnieks ir ieinteres\u0113ts p\u0101rbaud\u012bt, vai past\u0101v at\u0161\u0137ir\u012bba starp divu b\u0113rnu grupu - A grupas un B grupas - vid\u0113jo augumu. Lai to izdar\u012btu, p\u0113tnieks nejau\u0161i izv\u0113las 20 b\u0113rnus no katras grupas un m\u0113ra vi\u0146u augumu.<\/p>\n\n\n\n

P\u0113tnieks v\u0113las noskaidrot, vai A grupas b\u0113rnu vid\u0113jais augums at\u0161\u0137iras no B grupas b\u0113rnu vid\u0113j\u0101 auguma. Lai p\u0101rbaud\u012btu \u0161o hipot\u0113zi, p\u0113tnieks var izmantot divu paraugu t-testu. T-tests pie\u0146em, ka pamat\u0101 eso\u0161ie dati ir norm\u0101li sadal\u012bti un ka abu grupu vari\u0101cijas ir vien\u0101das.<\/p>\n\n\n\n

P\u0113tnieks apr\u0113\u0137ina katras grupas vid\u0113jo augumu un konstat\u0113, ka A grupas vid\u0113jais augums ir 150 cm, bet B grupas vid\u0113jais augums ir 155 cm. P\u0113c tam p\u0113tnieks apr\u0113\u0137ina katras grupas standartnovirzi un konstat\u0113, ka A grupas standartnovirze ir 5 cm, bet B grupas standartnovirze ir 4 cm.<\/p>\n\n\n\n

P\u0113c tam p\u0113tnieks apr\u0113\u0137ina t-statistiku, izmantojot abu grupu vid\u0113jo v\u0113rt\u012bbu starp\u012bbu, kas dal\u012bta ar starp\u012bbas standartk\u013c\u016bdu. Ja t-statistika ir liel\u0101ka par kritisko v\u0113rt\u012bbu, ko nosaka p\u0113c noz\u012bm\u012bguma l\u012bme\u0146a un br\u012bv\u012bbas pak\u0101p\u0113m, p\u0113tnieks var secin\u0101t, ka past\u0101v noz\u012bm\u012bga at\u0161\u0137ir\u012bba A un B grupas b\u0113rnu vid\u0113j\u0101 augum\u0101.<\/p>\n\n\n\n

\u0160aj\u0101 piem\u0113r\u0101 ir par\u0101d\u012bts, k\u0101 ar divu paraugu t-testu var p\u0101rbaud\u012bt hipot\u0113zi par divu grupu vid\u0113jo v\u0113rt\u012bbu at\u0161\u0137ir\u012bbu. T-tests ir sp\u0113c\u012bgs un pla\u0161i izmantots parametriskais tests, kas nodro\u0161ina stabilu un uzticamu veidu, k\u0101 p\u0101rbaud\u012bt hipot\u0113zes par popul\u0101cijas vid\u0113jo v\u0113rt\u012bbu.<\/p>\n\n\n\n

Jaud\u012bgi r\u012bki datu anal\u012bzei<\/h2>\n\n\n\n

Nosl\u0113gum\u0101 var secin\u0101t, ka parametriskie testi ir sp\u0113c\u012bgs statistisk\u0101s anal\u012bzes r\u012bks, kas nodro\u0161ina stabilus un uzticamus rezult\u0101tus visda\u017e\u0101d\u0101kajiem lietojumiem. Tom\u0113r ir svar\u012bgi izv\u0113l\u0113ties piem\u0113rotu testu, pamatojoties uz datu raksturu un p\u0113t\u012bjuma jaut\u0101jumu. Neatkar\u012bgi no t\u0101, vai tiek izmantoti parametriskie vai neparametriskie testi, statistisk\u0101s anal\u012bzes m\u0113r\u0137is vienm\u0113r ir izdar\u012bt pamatotus secin\u0101jumus par pamat\u0101 eso\u0161o popul\u0101ciju un no datiem izdar\u012bt j\u0113gpilnus secin\u0101jumus.<\/p>\n\n\n\n

Nekas nevar p\u0101rsp\u0113t nevainojamu vizu\u0101lo darbu, kas sniedz sare\u017e\u0123\u012btu v\u0113st\u012bjumu.<\/h2>\n\n\n\n

Jums ir gr\u016bt\u012bbas pazi\u0146ot lielu inform\u0101cijas apjomu? Izmantojiet infografikas un ilustr\u0101cijas, lai padar\u012btu savu darbu saprotam\u0101ku un pieejam\u0101ku. Mind the Graph ir lielisks r\u012bks p\u0113tniekiem, kuri v\u0113las padar\u012bt savu darbu efekt\u012bv\u0101ku, izmantojot vizu\u0101li pievilc\u012bgas infografikas. <\/p>\n\n\n\n

<\/div>\n\n\n
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\"\"<\/figure><\/div>\n\n\n
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Palielini manu p\u0113t\u012bjumu ar ilustr\u0101cij\u0101m<\/a><\/div>\n<\/div>\n\n\n\n
<\/div>\n\n\n\n
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<\/p>","protected":false},"excerpt":{"rendered":"

\u0160is raksts pal\u012bdz\u0113s jums izprast statistikas parametriskos testus, to visbie\u017e\u0101k sastopamos veidus, k\u0101 ar\u012b to, kur un kad tos izmantot.<\/p>","protected":false},"author":4,"featured_media":26646,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[],"yoast_head":"\nWhat are statistics parametric tests and where to apply them?<\/title>\n<meta name=\"description\" content=\"This article will help you understand statistics parametric tests, their most common types, and also where and when to apply them.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mindthegraph.com\/blog\/lv\/statistics-parametric-tests\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What 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