{"id":29176,"date":"2023-08-28T08:29:01","date_gmt":"2023-08-28T11:29:01","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/hypothesis-testing-copy\/"},"modified":"2024-12-05T15:51:53","modified_gmt":"2024-12-05T18:51:53","slug":"one-way-anova","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/vienvirziena-anova\/","title":{"rendered":"Vienvirziena ANOVA: izpratne, vad\u012b\u0161ana un prezent\u0113\u0161ana"},"content":{"rendered":"<p>Varian\u010du anal\u012bze (ANOVA) ir statistikas metode, ko izmanto, lai sal\u012bdzin\u0101tu vid\u0113jos lielumus starp div\u0101m vai vair\u0101k\u0101m grup\u0101m. Jo \u012bpa\u0161i vienvirziena ANOVA ir pla\u0161i izmantota metode, lai analiz\u0113tu viena nep\u0101rtraukt\u0101 main\u012bg\u0101 vari\u0101ciju div\u0101s vai vair\u0101k\u0101s kategorisk\u0101s grup\u0101s. \u0160o metodi pla\u0161i izmanto da\u017e\u0101d\u0101s jom\u0101s, tostarp uz\u0146\u0113m\u0113jdarb\u012bb\u0101, soci\u0101laj\u0101s un dabas zin\u0101tn\u0113s, lai p\u0101rbaud\u012btu hipot\u0113zes un izdar\u012btu secin\u0101jumus par at\u0161\u0137ir\u012bb\u0101m starp grup\u0101m. Izpratne par vienvirziena ANOVA pamatiem var pal\u012bdz\u0113t p\u0113tniekiem un datu anal\u012bti\u0137iem pie\u0146emt pamatotus l\u0113mumus, pamatojoties uz statistikas pier\u0101d\u012bjumiem. \u0160aj\u0101 rakst\u0101 m\u0113s detaliz\u0113ti izskaidrosim vienvirziena ANOVA metodi un apspried\u012bsim t\u0101s pielietojumu, pie\u0146\u0113mumus un citus aspektus.<\/p>\n\n\n\n<h2 id=\"h-what-is-one-way-anova\"><strong>Kas ir vienvirziena ANOVA?<\/strong><\/h2>\n\n\n\n<p>Vienvirziena ANOVA (vari\u0101ciju anal\u012bze) ir statistikas metode, ko izmanto, lai p\u0101rbaud\u012btu b\u016btiskas at\u0161\u0137ir\u012bbas starp datu grupu vid\u0113jiem r\u0101d\u012bt\u0101jiem. To parasti izmanto eksperiment\u0101los p\u0113t\u012bjumos, lai sal\u012bdzin\u0101tu da\u017e\u0101du apstr\u0101des vai intervences pas\u0101kumu ietekmi uz konkr\u0113tu rezult\u0101tu.<\/p>\n\n\n\n<p>ANOVA pamatideja ir sadal\u012bt datu kop\u0113jo main\u012bgumu div\u0101s sast\u0101vda\u013c\u0101s: main\u012bgums starp grup\u0101m (apstr\u0101des d\u0113\u013c) un main\u012bgums katras grupas iek\u0161ien\u0113 (nejau\u0161\u0101s main\u012bguma un individu\u0101lo at\u0161\u0137ir\u012bbu d\u0113\u013c). ANOVA tests apr\u0113\u0137ina F-statistiku, kas ir starpgrupu vari\u0101ciju attiec\u012bba pret grupas iek\u0161\u0113j\u0101m vari\u0101cij\u0101m.<\/p>\n\n\n\n<p>Ja F-statistika ir pietiekami liela un ar to saist\u012bt\u0101 p-v\u0113rt\u012bba ir zem\u0101ka par iepriek\u0161 noteiktu noz\u012bm\u012bguma l\u012bmeni (piem\u0113ram, 0,05), tas nor\u0101da, ka ir p\u0101rliecino\u0161i pier\u0101d\u012bjumi, kas liecina, ka vismaz viens no grupas vid\u0113jiem lielumiem b\u016btiski at\u0161\u0137iras no citiem. \u0160\u0101d\u0101 gad\u012bjum\u0101 var izmantot turpm\u0101kus post hoc testus, lai noteiktu, kuras konkr\u0113tas grupas at\u0161\u0137iras viena no otras. Vair\u0101k par post hoc testiem varat izlas\u012bt m\u016bsu materi\u0101l\u0101 \"<a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\" target=\"_blank\" rel=\"noreferrer noopener\">Post Hoc anal\u012bze: Process un testu veidi<\/a>&#8220;.<\/p>\n\n\n\n<p>Vienvirziena ANOVA pie\u0146em, ka dati ir sadal\u012bti norm\u0101li un ka grupu dispersijas ir vien\u0101das. Ja \u0161ie pie\u0146\u0113mumi nav izpild\u012bti, to viet\u0101 var izmantot alternat\u012bvus neparametriskus testus.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/researcher.life\/all-access-pricing?utm_source=mtg&amp;utm_campaign=all-access-promotion&amp;utm_medium=blog\"><img decoding=\"async\" loading=\"lazy\" width=\"1024\" height=\"410\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-1024x410.png\" alt=\"\" class=\"wp-image-55425\" srcset=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-1024x410.png 1024w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-300x120.png 300w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-768x307.png 768w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-1536x615.png 1536w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-2048x820.png 2048w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-18x7.png 18w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/08\/Banner3-100x40.png 100w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<h2 id=\"h-how-is-one-way-anova-used\"><strong>K\u0101 izmanto vienvirziena ANOVA?<\/strong><\/h2>\n\n\n\n<p>Vienvirziena ANOVA ir statistiskais tests, ko izmanto, lai noteiktu, vai past\u0101v b\u016btiskas at\u0161\u0137ir\u012bbas starp divu vai vair\u0101ku neatkar\u012bgu grupu vid\u0113jiem lielumiem. To izmanto, lai p\u0101rbaud\u012btu nulles hipot\u0113zi, ka visu grupu vid\u0113jie lielumi ir vien\u0101di, pret alternat\u012bvo hipot\u0113zi, ka vismaz viens vid\u0113jais lielums at\u0161\u0137iras no p\u0101r\u0113jiem.<\/p>\n\n\n\n<h2 id=\"h-assumptions-of-anova\"><strong>ANOVA pie\u0146\u0113mumi<\/strong><\/h2>\n\n\n\n<p>ANOVA ir vair\u0101ki pie\u0146\u0113mumi, kas j\u0101iev\u0113ro, lai rezult\u0101ti b\u016btu der\u012bgi un ticami. \u0160ie pie\u0146\u0113mumi ir \u0161\u0101di:<\/p>\n\n\n\n<ul>\n<li><strong>Normalit\u0101te:<\/strong> Atkar\u012bgajam main\u012bgajam katr\u0101 grup\u0101 j\u0101b\u016bt norm\u0101li sadal\u012btam. To var p\u0101rbaud\u012bt, izmantojot histogrammas, norm\u0101l\u0101s varb\u016bt\u012bbas diagrammas vai statistikas testus, piem\u0113ram, \u0160apiro-Vilka testu.<\/li>\n\n\n\n<li><strong>Dispersijas viendab\u012bgums: <\/strong>Atkar\u012bg\u0101 main\u012bg\u0101 lieluma dispersijai vis\u0101s grup\u0101s j\u0101b\u016bt aptuveni vien\u0101dai. To var p\u0101rbaud\u012bt, izmantojot statistiskos testus, piem\u0113ram, Levena testu vai Bartleta testu.<\/li>\n\n\n\n<li><strong>Neatkar\u012bba: <\/strong>Nov\u0113rojumiem katr\u0101 grup\u0101 j\u0101b\u016bt savstarp\u0113ji neatkar\u012bgiem. Tas noz\u012bm\u0113, ka vienas grupas v\u0113rt\u012bbas nedr\u012bkst b\u016bt saist\u012btas vai atkar\u012bgas no k\u0101das citas grupas v\u0113rt\u012bb\u0101m.<\/li>\n\n\n\n<li><strong>Nejau\u0161\u012bbas izlases metode:<\/strong> Grupas j\u0101veido, izmantojot nejau\u0161as izlases metodi. Tas nodro\u0161ina, ka rezult\u0101tus var attiecin\u0101t uz liel\u0101ku popul\u0101ciju.<\/li>\n<\/ul>\n\n\n\n<p>Pirms ANOVA veik\u0161anas ir svar\u012bgi p\u0101rbaud\u012bt \u0161os pie\u0146\u0113mumus, jo to p\u0101rk\u0101p\u0161ana var novest pie neprec\u012bziem rezult\u0101tiem un nepareiziem secin\u0101jumiem. Ja viens vai vair\u0101ki pie\u0146\u0113mumi ir p\u0101rk\u0101pti, to viet\u0101 var izmantot alternat\u012bvus testus, piem\u0113ram, neparametriskus testus.<\/p>\n\n\n\n<h2 id=\"h-performing-a-one-way-anova\"><strong>Vienvirziena ANOVA veik\u0161ana<\/strong><\/h2>\n\n\n\n<p>Lai veiktu vienvirziena ANOVA, varat veikt \u0161\u0101das darb\u012bbas:<\/p>\n\n\n\n<p><strong>1. solis:<\/strong> Nosauciet hipot\u0113zes<\/p>\n\n\n\n<p>Defin\u0113jiet nulles hipot\u0113zi un alternat\u012bvo hipot\u0113zi. Nulles hipot\u0113ze ir, ka starp grupu vid\u0113jiem lielumiem nav b\u016btisku at\u0161\u0137ir\u012bbu. Alternat\u012bv\u0101 hipot\u0113ze ir, ka vismaz vienas grupas vid\u0113jais lielums b\u016btiski at\u0161\u0137iras no p\u0101r\u0113jo grupu vid\u0113jiem lielumiem.<\/p>\n\n\n\n<p><strong>2. solis:<\/strong> Apkopot datus<\/p>\n\n\n\n<p>Apkopojiet datus no katras grupas, ko v\u0113laties sal\u012bdzin\u0101t. Katrai grupai j\u0101b\u016bt neatkar\u012bgai un ar l\u012bdz\u012bgu izlases lielumu.<\/p>\n\n\n\n<p><strong>3. solis:<\/strong> Apr\u0113\u0137iniet katras grupas vid\u0113jo v\u0113rt\u012bbu un dispersiju.<\/p>\n\n\n\n<p>Apr\u0113\u0137iniet katras grupas vid\u0113jo v\u0113rt\u012bbu un dispersiju, izmantojot sav\u0101ktos datus.<\/p>\n\n\n\n<p><strong>4. solis:<\/strong> Apr\u0113\u0137in\u0101t kop\u0113jo vid\u0113jo v\u0113rt\u012bbu un dispersiju<\/p>\n\n\n\n<p>Apr\u0113\u0137iniet kop\u0113jo vid\u0113jo v\u0113rt\u012bbu un dispersiju, \u0146emot vid\u0113jo v\u0113rt\u012bbu un dispersiju katrai grupai.<\/p>\n\n\n\n<p><strong>5:<\/strong> Apr\u0113\u0137in\u0101t kvadr\u0101tu summu starp grup\u0101m (SSB)<\/p>\n\n\n\n<p>Apr\u0113\u0137iniet kvadr\u0101tu summu starp grup\u0101m (SSB), izmantojot formulu:<\/p>\n\n\n\n<p>SSB = \u03a3ni (x\u0304i - x\u0304i)^2<\/p>\n\n\n\n<p>kur ni ir i-t\u0101s grupas izlases lielums, x\u0304i ir i-t\u0101s grupas vid\u0113jais lielums un x\u0304 ir kop\u0113jais vid\u0113jais lielums.<\/p>\n\n\n\n<p><strong>6. solis:<\/strong> Apr\u0113\u0137in\u0101t kvadr\u0101tu summu grup\u0101s (SSW)<\/p>\n\n\n\n<p>Apr\u0113\u0137iniet kvadr\u0101tu summu grup\u0101s (SSW), izmantojot formulu:<\/p>\n\n\n\n<p>SSW = \u03a3\u03a3(xi - x\u0304i)^2<\/p>\n\n\n\n<p>kur xi ir i-tais nov\u0113rojums j-taj\u0101 grup\u0101, x\u0304i ir j-t\u0101s grupas vid\u0113jais lielums, un j ir no 1 l\u012bdz k grup\u0101m.<\/p>\n\n\n\n<p><strong>7. solis: <\/strong>Apr\u0113\u0137in\u0101t F-statistiku<\/p>\n\n\n\n<p>Apr\u0113\u0137iniet F-statistiku, dalot dispersiju starp grup\u0101m (SSB) ar dispersiju grupas iek\u0161ien\u0113 (SSW):<\/p>\n\n\n\n<p>F = (SSB \/ (k - 1)) \/ (SSW \/ (n - k))<\/p>\n\n\n\n<p>kur k ir grupu skaits un n ir kop\u0113jais izlases lielums.<\/p>\n\n\n\n<p><strong>8. solis:<\/strong> Noteikt F kritisko v\u0113rt\u012bbu un p-v\u0113rt\u012bbu<\/p>\n\n\n\n<p>Nosakiet F kritisko v\u0113rt\u012bbu un atbilsto\u0161o p-v\u0113rt\u012bbu, pamatojoties uz v\u0113lamo noz\u012bm\u012bguma l\u012bmeni un br\u012bv\u012bbas pak\u0101p\u0113m.<\/p>\n\n\n\n<p><strong>9. solis:<\/strong> Sal\u012bdziniet apr\u0113\u0137in\u0101to F-statistiku ar kritisko v\u0113rt\u012bbu F<\/p>\n\n\n\n<p>Ja apr\u0113\u0137in\u0101t\u0101 F-statistika ir liel\u0101ka par F kritisko v\u0113rt\u012bbu, noraidiet nulles hipot\u0113zi un seciniet, ka starp vismaz divu grupu vid\u0113jiem lielumiem ir b\u016btiska at\u0161\u0137ir\u012bba. Ja apr\u0113\u0137in\u0101t\u0101 F-statistika ir maz\u0101ka vai vien\u0101da ar F kritisko v\u0113rt\u012bbu, nenoraidiet nulles hipot\u0113zi un seciniet, ka starp grupu vid\u0113jiem r\u0101d\u012bt\u0101jiem nav b\u016btiskas at\u0161\u0137ir\u012bbas.<\/p>\n\n\n\n<p><strong>10. solis:<\/strong> post hoc anal\u012bze (ja nepiecie\u0161ams).<\/p>\n\n\n\n<p>Ja nulles hipot\u0113ze tiek noraid\u012bta, veiciet post hoc anal\u012bzi, lai noteiktu, kuras grupas b\u016btiski at\u0161\u0137iras viena no otras. Bie\u017e\u0101k izmantotie post hoc testi ietver Tukija HSD testu, Bonferoni korekciju un \u0160ef\u012b testu.<\/p>\n\n\n\n<h2 id=\"h-interpreting-the-results\"><strong>Rezult\u0101tu interpret\u0101cija<\/strong><\/h2>\n\n\n\n<p>Veicot vienvirziena ANOVA, rezult\u0101tus var interpret\u0113t \u0161\u0101di:<\/p>\n\n\n\n<p><strong>F-statistika un p-v\u0113rt\u012bba: <\/strong>F-statistika m\u0113ra starpgrupu dispersijas attiec\u012bbu pret dispersiju grupas iek\u0161ien\u0113. P v\u0113rt\u012bba nor\u0101da varb\u016bt\u012bbu, ka tiks ieg\u016bta tikpat liela F-statistika k\u0101 nov\u0113rot\u0101, ja nulles hipot\u0113ze ir patiesa. Neliela p v\u0113rt\u012bba (maz\u0101ka par izv\u0113l\u0113to noz\u012bm\u012bguma l\u012bmeni, parasti 0,05) liecina par sp\u0113c\u012bgu pier\u0101d\u012bjumu pret nulles hipot\u0113zi, nor\u0101dot, ka starp vismaz divu grupu vid\u0113jiem lielumiem ir b\u016btiska at\u0161\u0137ir\u012bba.<\/p>\n\n\n\n<p><strong>Br\u012bv\u012bbas pak\u0101pes: <\/strong>Br\u012bv\u012bbas pak\u0101pes starpgrupu un iek\u0161grupu faktoriem ir attiec\u012bgi k-1 un N-k, kur k ir grupu skaits un N ir kop\u0113jais izlases lielums.<\/p>\n\n\n\n<p><strong>Vid\u0113j\u0101 kvadr\u0101tisk\u0101 k\u013c\u016bda:<\/strong><em> <\/em>Vid\u0113j\u0101 kvadr\u0101tisk\u0101 k\u013c\u016bda (MSE) ir grupas iek\u0161\u0113j\u0101s kvadr\u0101tu summas attiec\u012bba pret grupas iek\u0161\u0113j\u0101m br\u012bv\u012bbas pak\u0101p\u0113m. Tas atspogu\u013co apl\u0113sto dispersiju katr\u0101 grup\u0101 p\u0113c at\u0161\u0137ir\u012bbu \u0146em\u0161anas v\u0113r\u0101 starp grup\u0101m.<\/p>\n\n\n\n<p><strong>Efekta lielums:<\/strong> Ietekmes lielumu var izm\u0113r\u012bt, izmantojot eta kvadr\u0101tu (\u03b7\u00b2), kas par\u0101da atkar\u012bg\u0101 main\u012bg\u0101 lieluma kop\u0113j\u0101s vari\u0101cijas da\u013cu, ko nosaka grupu at\u0161\u0137ir\u012bbas. Bie\u017e\u0101k lietot\u0101s eta kvadr\u0101ta v\u0113rt\u012bbu interpret\u0101cijas ir \u0161\u0101das:<\/p>\n\n\n\n<p>Neliela ietekme: \u03b7\u00b2 &lt; 0,01<\/p>\n\n\n\n<p>Vid\u0113ja ietekme: 0,01 \u2264 \u03b7 \u03b7\u00b2 &lt; 0,06<\/p>\n\n\n\n<p>Liela ietekme: \u03b7\u00b2 \u2265 0,06<\/p>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\"><strong>Post hoc anal\u012bze:<\/strong><\/a> Ja nulles hipot\u0113ze tiek noraid\u012bta, var veikt post hoc anal\u012bzi, lai noteiktu, kuras grupas b\u016btiski at\u0161\u0137iras viena no otras. To var izdar\u012bt, izmantojot da\u017e\u0101dus testus, piem\u0113ram, Tukija HSD testu, Bonferroni korekciju vai \u0160ef\u012b testu.<\/p>\n\n\n\n<p>Rezult\u0101ti j\u0101interpret\u0113 p\u0113t\u012bjuma jaut\u0101juma un anal\u012bzes pie\u0146\u0113mumu kontekst\u0101. Ja pie\u0146\u0113mumi nav izpild\u012bti vai rezult\u0101ti nav interpret\u0113jami, var b\u016bt nepiecie\u0161ami alternat\u012bvi testi vai anal\u012bzes modifik\u0101cijas.<\/p>\n\n\n\n<h2 id=\"h-post-hoc-testing\"><strong>Post hoc test\u0113\u0161ana<\/strong><\/h2>\n\n\n\n<p>Statistik\u0101 vienvirziena ANOVA ir metode, ko izmanto, lai sal\u012bdzin\u0101tu tr\u012bs vai vair\u0101ku grupu vid\u0113jos lielumus. Kad ANOVA tests ir veikts un ja nulles hipot\u0113ze ir noraid\u012bta, kas noz\u012bm\u0113, ka ir b\u016btiski pier\u0101d\u012bjumi, kas liecina, ka vismaz vienas grupas vid\u0113jais r\u0101d\u012bt\u0101js at\u0161\u0137iras no p\u0101r\u0113jo grupu vid\u0113jiem r\u0101d\u012bt\u0101jiem, var veikt post hoc test\u0113\u0161anu, lai noteiktu, kuras grupas b\u016btiski at\u0161\u0137iras viena no otras.<\/p>\n\n\n\n<p>Lai noteiktu konkr\u0113tas at\u0161\u0137ir\u012bbas starp grupu vid\u0113jiem r\u0101d\u012bt\u0101jiem, tiek izmantoti post hoc testi. Da\u017ei izplat\u012bt\u0101kie post hoc testi ir Tuk\u012b (Tukey) god\u012bgi noz\u012bm\u012bgas at\u0161\u0137ir\u012bbas (HSD), Bonferoni korekcija, \u0160eifes (Scheffe) metode un Duneta (Dunnett) tests. Katram no \u0161iem testiem ir savi pie\u0146\u0113mumi, priek\u0161roc\u012bbas un ierobe\u017eojumi, un izv\u0113le, kuru testu izmantot, ir atkar\u012bga no konkr\u0113t\u0101 p\u0113t\u012bjuma jaut\u0101juma un datu \u012bpa\u0161\u012bb\u0101m.<\/p>\n\n\n\n<p>Kopum\u0101 post hoc testi ir noder\u012bgi, lai sniegtu detaliz\u0113t\u0101ku inform\u0101ciju par konkr\u0113t\u0101m grupu at\u0161\u0137ir\u012bb\u0101m vienvirziena ANOVA anal\u012bz\u0113. Tom\u0113r ir svar\u012bgi \u0161os testus izmantot piesardz\u012bgi un interpret\u0113t rezult\u0101tus p\u0113t\u012bjuma jaut\u0101juma un datu specifisko \u012bpa\u0161\u012bbu kontekst\u0101.<\/p>\n\n\n\n<p>Uzziniet vair\u0101k par Post Hoc anal\u012bzi m\u016bsu satur\u0101 \"<a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\">Post Hoc anal\u012bze: Process un testu veidi<\/a>&#8220;.<\/p>\n\n\n\n<h2 id=\"h-reporting-the-results-of-anova\"><strong>ANOVA rezult\u0101tu pazi\u0146o\u0161ana<\/strong><\/h2>\n\n\n\n<p>Zi\u0146ojot par ANOVA anal\u012bzes rezult\u0101tiem, j\u0101iek\u013cauj vair\u0101kas inform\u0101cijas da\u013cas:<\/p>\n\n\n\n<p><strong>F statistika: <\/strong>\u0160\u012b ir ANOVA testa statistika, un t\u0101 ir starpgrupu dispersijas attiec\u012bba pret grupas iek\u0161\u0113jo dispersiju.<\/p>\n\n\n\n<p><strong>F statistikas br\u012bv\u012bbas pak\u0101pes:<\/strong> Tas ietver br\u012bv\u012bbas pak\u0101pes skait\u012bt\u0101jam (starpgrupu vari\u0101cijas) un sauc\u0113jam (grupas iek\u0161\u0113j\u0101s vari\u0101cijas).<\/p>\n\n\n\n<p><strong>P v\u0113rt\u012bba: <\/strong>T\u0101 ir varb\u016bt\u012bba, ka nov\u0113roto F statistiku (vai ekstr\u0113m\u0101ku v\u0113rt\u012bbu) var ieg\u016bt tikai nejau\u0161\u012bbas d\u0113\u013c, pie\u0146emot, ka nulles hipot\u0113ze ir patiesa.<\/p>\n\n\n\n<p><strong>Pazi\u0146ojums par to, vai nulles hipot\u0113ze ir vai nav noraid\u012bta:<\/strong> Tam j\u0101balst\u0101s uz p-v\u0113rt\u012bbu un izv\u0113l\u0113to noz\u012bm\u012bguma l\u012bmeni (piem\u0113ram, alfa = 0,05).<\/p>\n\n\n\n<p><strong>Post hoc test\u0113\u0161ana:<\/strong> Ja nulles hipot\u0113ze tiek noraid\u012bta, tad j\u0101pazi\u0146o post hoc test\u0113\u0161anas rezult\u0101ti, lai noteiktu, kuras grupas b\u016btiski at\u0161\u0137iras viena no otras.<\/p>\n\n\n\n<p>Piem\u0113ram, zi\u0146ojuma paraugs var\u0113tu b\u016bt \u0161\u0101ds:<\/p>\n\n\n\n<p>Tika veikta vienvirziena ANOVA, lai sal\u012bdzin\u0101tu tr\u012bs grupu (A grupa, B grupa un C grupa) vid\u0113jos rezult\u0101tus atmi\u0146as saglab\u0101\u0161anas test\u0101. F statistika bija 4,58 ar br\u012bv\u012bbas pak\u0101p\u0113m 2, 87 un p-v\u0113rt\u012bbu 0,01. Nulles hipot\u0113ze tika noraid\u012bta, nor\u0101dot, ka vismaz vien\u0101 no grup\u0101m ir b\u016btiska at\u0161\u0137ir\u012bba atmi\u0146as saglab\u0101\u0161anas rezult\u0101tos. post hoc test\u0113\u0161ana, izmantojot Tukey's HSD, par\u0101d\u012bja, ka A grupas vid\u0113jais rezult\u0101ts (M = 83,4, SD = 4,2) bija iev\u0113rojami augst\u0101ks nek\u0101 B grupas (M = 76,9, SD = 5,5) un C grupas (M = 77,6, SD = 5,3), kas b\u016btiski neat\u0161\u0137\u012br\u0101s viena no otras.<\/p>\n\n\n\n<h2 id=\"h-find-the-perfect-infographic-template-for-you\"><strong>Atrodiet sev piem\u0113rotu infografikas veidni<\/strong><\/h2>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Mind the Graph<\/a> ir platforma, kas pied\u0101v\u0101 pla\u0161u iepriek\u0161 izstr\u0101d\u0101tu infografikas veid\u0146u kolekciju, lai pal\u012bdz\u0113tu zin\u0101tniekiem un p\u0113tniekiem izveidot vizu\u0101lus pal\u012bgl\u012bdzek\u013cus, kas efekt\u012bvi inform\u0113 par zin\u0101tniskiem j\u0113dzieniem. Platforma pied\u0101v\u0101 piek\u013cuvi pla\u0161ai zin\u0101tnisko ilustr\u0101ciju bibliot\u0113kai, nodro\u0161inot, ka zin\u0101tnieki un p\u0113tnieki var viegli atrast ide\u0101lu infografikas veidni, lai vizu\u0101li pazi\u0146otu savus p\u0113t\u012bjumu rezult\u0101tus.<\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/mindthegraph.com\/offer-trial\"><img decoding=\"async\" loading=\"lazy\" width=\"651\" height=\"174\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/02\/banner-blog-trial-04.jpg\" alt=\"\" class=\"wp-image-26792\" srcset=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/02\/banner-blog-trial-04.jpg 651w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/02\/banner-blog-trial-04-300x80.jpg 300w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/02\/banner-blog-trial-04-18x5.jpg 18w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/02\/banner-blog-trial-04-100x27.jpg 100w\" sizes=\"(max-width: 651px) 100vw, 651px\" \/><\/a><\/figure><\/div>\n\n\n<div style=\"height:44px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>","protected":false},"excerpt":{"rendered":"<p>Uzziniet vair\u0101k par vienvirziena ANOVA - statistikas metodi, ko izmanto, lai datu anal\u012bz\u0113 sal\u012bdzin\u0101tu vid\u0113jos lielumus starp vair\u0101k\u0101m grup\u0101m, un uzziniet, k\u0101 to piem\u0113rot.<\/p>","protected":false},"author":35,"featured_media":29180,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>One-Way ANOVA: Understanding, Conducting, and Presenting - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Learn about the one-way ANOVA, a statistical method used to compare means among multiple groups in data analysis, and how to apply it.\" \/>\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\/vienvirziena-anova\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"One-Way ANOVA: Understanding, Conducting, and Presenting\" \/>\n<meta property=\"og:description\" content=\"Learn about the one-way ANOVA, a statistical method used to compare means among multiple groups in data analysis, and how to apply it.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mindthegraph.com\/blog\/lv\/vienvirziena-anova\/\" \/>\n<meta property=\"og:site_name\" content=\"Mind the Graph Blog\" \/>\n<meta property=\"article:published_time\" content=\"2023-08-28T11:29:01+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-12-05T18:51:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/08\/one-way-anova-blog.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1123\" \/>\n\t<meta property=\"og:image:height\" content=\"612\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Ang\u00e9lica Salom\u00e3o\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"One-Way ANOVA: Understanding, Conducting, and Presenting\" \/>\n<meta name=\"twitter:description\" content=\"Learn about the one-way ANOVA, a statistical method used to compare means among multiple groups in data analysis, and how to apply it.\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/08\/one-way-anova-blog.jpg\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ang\u00e9lica Salom\u00e3o\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"9 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"One-Way ANOVA: Understanding, Conducting, and Presenting - 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