{"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\/cs\/jednosmerna-anova\/","title":{"rendered":"Jednosm\u011brn\u00e1 ANOVA: porozum\u011bn\u00ed, proveden\u00ed a prezentace"},"content":{"rendered":"<p>Anal\u00fdza rozptylu (ANOVA) je statistick\u00e1 metoda pou\u017e\u00edvan\u00e1 k porovn\u00e1n\u00ed pr\u016fm\u011br\u016f mezi dv\u011bma nebo v\u00edce skupinami. Zejm\u00e9na jednosm\u011brn\u00e1 ANOVA je b\u011b\u017en\u011b pou\u017e\u00edvanou technikou pro anal\u00fdzu rozptylu jedn\u00e9 spojit\u00e9 prom\u011bnn\u00e9 ve dvou nebo v\u00edce kategori\u00e1ln\u00edch skupin\u00e1ch. Tato technika se \u0161iroce pou\u017e\u00edv\u00e1 v r\u016fzn\u00fdch oblastech, v\u010detn\u011b obchodu, spole\u010densk\u00fdch a p\u0159\u00edrodn\u00edch v\u011bd, k testov\u00e1n\u00ed hypot\u00e9z a vyvozov\u00e1n\u00ed z\u00e1v\u011br\u016f o rozd\u00edlech mezi skupinami. Pochopen\u00ed z\u00e1klad\u016f jednosm\u011brn\u00e9 anal\u00fdzy ANOVA m\u016f\u017ee v\u00fdzkumn\u00fdm pracovn\u00edk\u016fm a analytik\u016fm dat pomoci \u010dinit informovan\u00e1 rozhodnut\u00ed zalo\u017een\u00e1 na statistick\u00fdch d\u016fkazech. V tomto \u010dl\u00e1nku podrobn\u011b vysv\u011btl\u00edme techniku jednocestn\u00e9 ANOVA a probereme jej\u00ed pou\u017eit\u00ed, p\u0159edpoklady a dal\u0161\u00ed informace.<\/p>\n\n\n\n<h2 id=\"h-what-is-one-way-anova\"><strong>Co je to jednosm\u011brn\u00e1 ANOVA?<\/strong><\/h2>\n\n\n\n<p>Jednosm\u011brn\u00e1 ANOVA (anal\u00fdza rozptylu) je statistick\u00e1 metoda pou\u017e\u00edvan\u00e1 k testov\u00e1n\u00ed v\u00fdznamn\u00fdch rozd\u00edl\u016f mezi pr\u016fm\u011bry skupin dat. B\u011b\u017en\u011b se pou\u017e\u00edv\u00e1 v experiment\u00e1ln\u00edm v\u00fdzkumu k porovn\u00e1n\u00ed \u00fa\u010dink\u016f r\u016fzn\u00fdch l\u00e9\u010debn\u00fdch postup\u016f nebo intervenc\u00ed na ur\u010dit\u00fd v\u00fdsledek.<\/p>\n\n\n\n<p>Z\u00e1kladn\u00ed my\u0161lenkou ANOVA je rozd\u011blit celkovou variabilitu dat na dv\u011b slo\u017eky: variabilitu mezi skupinami (zp\u016fsobenou l\u00e9\u010dbou) a variabilitu uvnit\u0159 ka\u017ed\u00e9 skupiny (zp\u016fsobenou n\u00e1hodnou variabilitou a individu\u00e1ln\u00edmi rozd\u00edly). Test ANOVA vypo\u010d\u00edt\u00e1 F-statistiku, co\u017e je pom\u011br variability mezi skupinami a variability uvnit\u0159 skupin.<\/p>\n\n\n\n<p>Pokud je F-statistika dostate\u010dn\u011b velk\u00e1 a souvisej\u00edc\u00ed p-hodnota je ni\u017e\u0161\u00ed ne\u017e p\u0159edem stanoven\u00e1 hladina v\u00fdznamnosti (nap\u0159. 0,05), znamen\u00e1 to, \u017ee existuje siln\u00fd d\u016fkaz, \u017ee alespo\u0148 jeden ze skupinov\u00fdch pr\u016fm\u011br\u016f se v\u00fdznamn\u011b li\u0161\u00ed od ostatn\u00edch. V takov\u00e9m p\u0159\u00edpad\u011b lze pou\u017e\u00edt dal\u0161\u00ed post hoc testy k ur\u010den\u00ed, kter\u00e9 konkr\u00e9tn\u00ed skupiny se od sebe li\u0161\u00ed. V\u00edce informac\u00ed o post hoc si m\u016f\u017eete p\u0159e\u010d\u00edst v na\u0161em obsahu \"<a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\" target=\"_blank\" rel=\"noreferrer noopener\">Post Hoc anal\u00fdza: Postup a typy test\u016f<\/a>&#8220;.<\/p>\n\n\n\n<p>Jednosm\u011brn\u00e1 ANOVA p\u0159edpokl\u00e1d\u00e1, \u017ee data jsou norm\u00e1ln\u011b rozd\u011blena a \u017ee rozptyly skupin jsou stejn\u00e9. Pokud tyto p\u0159edpoklady nejsou spln\u011bny, lze m\u00edsto nich pou\u017e\u00edt alternativn\u00ed neparametrick\u00e9 testy.<\/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>Jak se pou\u017e\u00edv\u00e1 jednocestn\u00e1 ANOVA?<\/strong><\/h2>\n\n\n\n<p>Jednosm\u011brn\u00e1 ANOVA je statistick\u00fd test pou\u017e\u00edvan\u00fd ke zji\u0161t\u011bn\u00ed, zda existuj\u00ed v\u00fdznamn\u00e9 rozd\u00edly mezi pr\u016fm\u011bry dvou nebo v\u00edce nez\u00e1visl\u00fdch skupin. Pou\u017e\u00edv\u00e1 se k testov\u00e1n\u00ed nulov\u00e9 hypot\u00e9zy, \u017ee pr\u016fm\u011bry v\u0161ech skupin jsou stejn\u00e9, proti alternativn\u00ed hypot\u00e9ze, \u017ee alespo\u0148 jeden pr\u016fm\u011br se od ostatn\u00edch li\u0161\u00ed.<\/p>\n\n\n\n<h2 id=\"h-assumptions-of-anova\"><strong>P\u0159edpoklady ANOVA<\/strong><\/h2>\n\n\n\n<p>ANOVA m\u00e1 n\u011bkolik p\u0159edpoklad\u016f, kter\u00e9 mus\u00ed b\u00fdt spln\u011bny, aby v\u00fdsledky byly platn\u00e9 a spolehliv\u00e9. Tyto p\u0159edpoklady jsou n\u00e1sleduj\u00edc\u00ed:<\/p>\n\n\n\n<ul>\n<li><strong>Norm\u00e1lnost:<\/strong> Z\u00e1visl\u00e1 prom\u011bnn\u00e1 by m\u011bla b\u00fdt v ka\u017ed\u00e9 skupin\u011b norm\u00e1ln\u011b rozd\u011blena. To lze ov\u011b\u0159it pomoc\u00ed histogram\u016f, norm\u00e1ln\u00edch pravd\u011bpodobnostn\u00edch graf\u016f nebo statistick\u00fdch test\u016f, jako je Shapir\u016fv-Wilk\u016fv test.<\/li>\n\n\n\n<li><strong>Homogenita rozptylu: <\/strong>Rozptyl z\u00e1visl\u00e9 prom\u011bnn\u00e9 by m\u011bl b\u00fdt ve v\u0161ech skupin\u00e1ch p\u0159ibli\u017en\u011b stejn\u00fd. To lze ov\u011b\u0159it pomoc\u00ed statistick\u00fdch test\u016f, jako je Levene\u016fv test nebo Bartlett\u016fv test.<\/li>\n\n\n\n<li><strong>Nez\u00e1vislost: <\/strong>Pozorov\u00e1n\u00ed v ka\u017ed\u00e9 skupin\u011b by m\u011bla b\u00fdt na sob\u011b nez\u00e1visl\u00e1. To znamen\u00e1, \u017ee hodnoty v jedn\u00e9 skupin\u011b by nem\u011bly souviset s hodnotami v jin\u00e9 skupin\u011b ani na nich z\u00e1viset.<\/li>\n\n\n\n<li><strong>N\u00e1hodn\u00fd v\u00fdb\u011br vzork\u016f:<\/strong> Skupiny by m\u011bly b\u00fdt vytvo\u0159eny na z\u00e1klad\u011b n\u00e1hodn\u00e9ho v\u00fdb\u011bru. T\u00edm je zaji\u0161t\u011bno, \u017ee v\u00fdsledky lze zobecnit na v\u011bt\u0161\u00ed populaci.<\/li>\n<\/ul>\n\n\n\n<p>P\u0159ed proveden\u00edm ANOVA je d\u016fle\u017eit\u00e9 tyto p\u0159edpoklady zkontrolovat, proto\u017ee jejich poru\u0161en\u00ed m\u016f\u017ee v\u00e9st k nep\u0159esn\u00fdm v\u00fdsledk\u016fm a nespr\u00e1vn\u00fdm z\u00e1v\u011br\u016fm. Pokud je jeden nebo v\u00edce p\u0159edpoklad\u016f poru\u0161eno, existuj\u00ed alternativn\u00ed testy, nap\u0159\u00edklad neparametrick\u00e9 testy, kter\u00e9 lze pou\u017e\u00edt m\u00edsto nich.<\/p>\n\n\n\n<h2 id=\"h-performing-a-one-way-anova\"><strong>Proveden\u00ed jednosm\u011brn\u00e9 ANOVA<\/strong><\/h2>\n\n\n\n<p>Chcete-li prov\u00e9st jednosm\u011brnou anal\u00fdzu ANOVA, m\u016f\u017eete postupovat podle n\u00e1sleduj\u00edc\u00edch krok\u016f:<\/p>\n\n\n\n<p><strong>Krok 1:<\/strong> Uve\u010fte hypot\u00e9zy<\/p>\n\n\n\n<p>Definujte nulovou a alternativn\u00ed hypot\u00e9zu. Nulov\u00e1 hypot\u00e9za zn\u00ed, \u017ee mezi pr\u016fm\u011bry skupin nejsou v\u00fdznamn\u00e9 rozd\u00edly. Alternativn\u00ed hypot\u00e9za zn\u00ed, \u017ee alespo\u0148 jeden pr\u016fm\u011br skupiny se v\u00fdznamn\u011b li\u0161\u00ed od ostatn\u00edch.<\/p>\n\n\n\n<p><strong>Krok 2:<\/strong> Shroma\u017e\u010fov\u00e1n\u00ed dat<\/p>\n\n\n\n<p>Shrom\u00e1\u017ed\u011bte \u00fadaje z ka\u017ed\u00e9 skupiny, kter\u00e9 chcete porovnat. Ka\u017ed\u00e1 skupina by m\u011bla b\u00fdt nez\u00e1visl\u00e1 a m\u00edt podobnou velikost vzorku.<\/p>\n\n\n\n<p><strong>Krok 3:<\/strong> Vypo\u010d\u00edtejte pr\u016fm\u011br a rozptyl ka\u017ed\u00e9 skupiny.<\/p>\n\n\n\n<p>Vypo\u010d\u00edtejte pr\u016fm\u011br a rozptyl ka\u017ed\u00e9 skupiny na z\u00e1klad\u011b shrom\u00e1\u017ed\u011bn\u00fdch \u00fadaj\u016f.<\/p>\n\n\n\n<p><strong>Krok 4:<\/strong> Vypo\u010d\u00edtejte celkov\u00fd pr\u016fm\u011br a rozptyl<\/p>\n\n\n\n<p>Vypo\u010d\u00edtejte celkov\u00fd pr\u016fm\u011br a rozptyl zpr\u016fm\u011brov\u00e1n\u00edm pr\u016fm\u011br\u016f a rozptyl\u016f jednotliv\u00fdch skupin.<\/p>\n\n\n\n<p><strong>Krok 5:<\/strong> V\u00fdpo\u010det sou\u010dtu \u010dtverc\u016f mezi skupinami (SSB)<\/p>\n\n\n\n<p>Vypo\u010d\u00edtejte sou\u010det \u010dtverc\u016f mezi skupinami (SSB) podle vzorce:<\/p>\n\n\n\n<p>SSB = \u03a3ni (x\u0304i - x\u0304)^2<\/p>\n\n\n\n<p>kde ni je velikost vzorku i-t\u00e9 skupiny, x\u0304i je pr\u016fm\u011br i-t\u00e9 skupiny a x\u0304 je celkov\u00fd pr\u016fm\u011br.<\/p>\n\n\n\n<p><strong>Krok 6:<\/strong> V\u00fdpo\u010det sou\u010dtu \u010dtverc\u016f v r\u00e1mci skupin (SSW)<\/p>\n\n\n\n<p>Vypo\u010d\u00edtejte sou\u010det \u010dtverc\u016f v r\u00e1mci skupin (SSW) podle vzorce:<\/p>\n\n\n\n<p>SSW = \u03a3\u03a3(xi - x\u0304i)^2<\/p>\n\n\n\n<p>kde xi je i-t\u00e9 pozorov\u00e1n\u00ed v j-t\u00e9 skupin\u011b, x\u0304i je pr\u016fm\u011br j-t\u00e9 skupiny a j je od 1 do k skupin.<\/p>\n\n\n\n<p><strong>Krok 7: <\/strong>V\u00fdpo\u010det F-statistiky<\/p>\n\n\n\n<p>Vypo\u010d\u00edtejte F-statistiku vyd\u011blen\u00edm rozptylu mezi skupinami (SSB) rozptylem uvnit\u0159 skupiny (SSW):<\/p>\n\n\n\n<p>F = (SSB \/ (k - 1)) \/ (SSW \/ (n - k))<\/p>\n\n\n\n<p>kde k je po\u010det skupin a n je celkov\u00e1 velikost vzorku.<\/p>\n\n\n\n<p><strong>Krok 8:<\/strong> Ur\u010dete kritickou hodnotu F a p-hodnotu<\/p>\n\n\n\n<p>Ur\u010dete kritickou hodnotu F a odpov\u00eddaj\u00edc\u00ed p-hodnotu na z\u00e1klad\u011b po\u017eadovan\u00e9 hladiny v\u00fdznamnosti a stup\u0148\u016f volnosti.<\/p>\n\n\n\n<p><strong>Krok 9:<\/strong> Porovnejte vypo\u010dtenou F-statistiku s kritickou hodnotou F<\/p>\n\n\n\n<p>Pokud je vypo\u010dten\u00e1 F-statistika v\u011bt\u0161\u00ed ne\u017e kritick\u00e1 hodnota F, zam\u00edtn\u011bte nulovou hypot\u00e9zu a dojd\u011bte k z\u00e1v\u011bru, \u017ee existuje v\u00fdznamn\u00fd rozd\u00edl mezi pr\u016fm\u011bry alespo\u0148 dvou skupin. Pokud je vypo\u010dten\u00e1 F-statistika men\u0161\u00ed nebo rovna kritick\u00e9 hodnot\u011b F, nezam\u00edtn\u011bte nulovou hypot\u00e9zu a dojd\u011bte k z\u00e1v\u011bru, \u017ee mezi pr\u016fm\u011bry skupin nen\u00ed v\u00fdznamn\u00fd rozd\u00edl.<\/p>\n\n\n\n<p><strong>Krok 10:<\/strong> post hoc anal\u00fdza (v p\u0159\u00edpad\u011b pot\u0159eby)<\/p>\n\n\n\n<p>Pokud je nulov\u00e1 hypot\u00e9za zam\u00edtnuta, prove\u010fte post hoc anal\u00fdzu, abyste zjistili, kter\u00e9 skupiny se od sebe v\u00fdznamn\u011b li\u0161\u00ed. Mezi b\u011b\u017en\u00e9 post hoc testy pat\u0159\u00ed Tukeyho HSD test, Bonferroniho korekce a Scheffeho test.<\/p>\n\n\n\n<h2 id=\"h-interpreting-the-results\"><strong>Interpretace v\u00fdsledk\u016f<\/strong><\/h2>\n\n\n\n<p>Po proveden\u00ed jednocestn\u00e9 anal\u00fdzy ANOVA lze v\u00fdsledky interpretovat n\u00e1sledovn\u011b:<\/p>\n\n\n\n<p><strong>F-statistika a p-hodnota: <\/strong>Statistika F m\u011b\u0159\u00ed pom\u011br rozptylu mezi skupinami a rozptylu uvnit\u0159 skupiny. Hodnota p ud\u00e1v\u00e1 pravd\u011bpodobnost, \u017ee v p\u0159\u00edpad\u011b pravdivosti nulov\u00e9 hypot\u00e9zy bude F-statistika stejn\u011b extr\u00e9mn\u00ed jako ta, kter\u00e1 byla zji\u0161t\u011bna. Mal\u00e1 p-hodnota (men\u0161\u00ed ne\u017e zvolen\u00e1 hladina v\u00fdznamnosti, obvykle 0,05) nazna\u010duje siln\u00fd d\u016fkaz proti nulov\u00e9 hypot\u00e9ze, co\u017e znamen\u00e1, \u017ee existuje v\u00fdznamn\u00fd rozd\u00edl mezi pr\u016fm\u011bry alespo\u0148 dvou skupin.<\/p>\n\n\n\n<p><strong>Stupn\u011b volnosti: <\/strong>Stupn\u011b volnosti pro faktory mezi skupinami a uvnit\u0159 skupin jsou k-1 a N-k, kde k je po\u010det skupin a N je celkov\u00e1 velikost vzorku.<\/p>\n\n\n\n<p><strong>St\u0159edn\u00ed kvadratick\u00e1 chyba:<\/strong><em> <\/em>St\u0159edn\u00ed kvadratick\u00e1 chyba (MSE) je pom\u011br sou\u010dtu \u010dtverc\u016f uvnit\u0159 skupiny a stup\u0148\u016f volnosti uvnit\u0159 skupiny. P\u0159edstavuje odhadovan\u00fd rozptyl v r\u00e1mci ka\u017ed\u00e9 skupiny po zohledn\u011bn\u00ed rozd\u00edl\u016f mezi skupinami.<\/p>\n\n\n\n<p><strong>Velikost \u00fa\u010dinku:<\/strong> Velikost \u00fa\u010dinku lze m\u011b\u0159it pomoc\u00ed eta-kvadr\u00e1tu (\u03b7\u00b2), kter\u00fd p\u0159edstavuje pod\u00edl celkov\u00e9 variability z\u00e1visl\u00e9 prom\u011bnn\u00e9, kter\u00e1 je vysv\u011btlena skupinov\u00fdmi rozd\u00edly. Obvykl\u00e9 interpretace hodnot eta-squared jsou n\u00e1sleduj\u00edc\u00ed:<\/p>\n\n\n\n<p>Mal\u00fd \u00fa\u010dinek: \u03b7\u00b2 &lt; 0,01<\/p>\n\n\n\n<p>St\u0159edn\u00ed \u00fa\u010dinek: 0,01 \u2264 \u03b7\u00b2 &lt; 0,06<\/p>\n\n\n\n<p>Velk\u00fd \u00fa\u010dinek: \u03b7\u00b2 \u2265 0,06<\/p>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\"><strong>Post hoc anal\u00fdza:<\/strong><\/a> Pokud je nulov\u00e1 hypot\u00e9za zam\u00edtnuta, lze prov\u00e9st post hoc anal\u00fdzu, kter\u00e1 ur\u010d\u00ed, kter\u00e9 skupiny se od sebe v\u00fdznamn\u011b li\u0161\u00ed. To lze prov\u00e9st pomoc\u00ed r\u016fzn\u00fdch test\u016f, nap\u0159\u00edklad Tukeyho HSD testu, Bonferroniho korekce nebo Scheffeho testu.<\/p>\n\n\n\n<p>V\u00fdsledky je t\u0159eba interpretovat v kontextu v\u00fdzkumn\u00e9 ot\u00e1zky a p\u0159edpoklad\u016f anal\u00fdzy. Pokud p\u0159edpoklady nejsou spln\u011bny nebo v\u00fdsledky nelze interpretovat, m\u016f\u017ee b\u00fdt nutn\u00e9 prov\u00e9st alternativn\u00ed testy nebo upravit anal\u00fdzu.<\/p>\n\n\n\n<h2 id=\"h-post-hoc-testing\"><strong>Post hoc testov\u00e1n\u00ed<\/strong><\/h2>\n\n\n\n<p>Jednocestn\u00e1 ANOVA je ve statistice technika pou\u017e\u00edvan\u00e1 k porovn\u00e1v\u00e1n\u00ed pr\u016fm\u011br\u016f t\u0159\u00ed nebo v\u00edce skupin. Jakmile je proveden test ANOVA a je-li zam\u00edtnuta nulov\u00e1 hypot\u00e9za, co\u017e znamen\u00e1, \u017ee existuje v\u00fdznamn\u00fd d\u016fkaz, kter\u00fd nazna\u010duje, \u017ee alespo\u0148 jeden pr\u016fm\u011br skupiny se li\u0161\u00ed od ostatn\u00edch, lze prov\u00e9st post hoc testov\u00e1n\u00ed, aby se zjistilo, kter\u00e9 skupiny se od sebe v\u00fdznamn\u011b li\u0161\u00ed.<\/p>\n\n\n\n<p>Post hoc testy se pou\u017e\u00edvaj\u00ed k ur\u010den\u00ed konkr\u00e9tn\u00edch rozd\u00edl\u016f mezi pr\u016fm\u011bry skupin. Mezi b\u011b\u017en\u00e9 post hoc testy pat\u0159\u00ed Tukeyho poctiv\u011b v\u00fdznamn\u00fd rozd\u00edl (HSD), Bonferroniho korekce, Scheffeho metoda a Dunnett\u016fv test. Ka\u017ed\u00fd z t\u011bchto test\u016f m\u00e1 sv\u00e9 vlastn\u00ed p\u0159edpoklady, v\u00fdhody a omezen\u00ed a volba, kter\u00fd test pou\u017e\u00edt, z\u00e1vis\u00ed na konkr\u00e9tn\u00ed v\u00fdzkumn\u00e9 ot\u00e1zce a vlastnostech dat.<\/p>\n\n\n\n<p>Celkov\u011b jsou post hoc testy u\u017eite\u010dn\u00e9, proto\u017ee poskytuj\u00ed podrobn\u011bj\u0161\u00ed informace o specifick\u00fdch rozd\u00edlech mezi skupinami v jednocestn\u00e9 anal\u00fdze ANOVA. Je v\u0161ak d\u016fle\u017eit\u00e9 pou\u017e\u00edvat tyto testy s opatrnost\u00ed a interpretovat v\u00fdsledky v kontextu v\u00fdzkumn\u00e9 ot\u00e1zky a specifick\u00fdch charakteristik dat.<\/p>\n\n\n\n<p>Dal\u0161\u00ed informace o anal\u00fdze Post Hoc naleznete v na\u0161em obsahu \"<a href=\"https:\/\/mindthegraph.com\/blog\/post-hoc-analysis\/\">Post Hoc anal\u00fdza: Postup a typy test\u016f<\/a>&#8220;.<\/p>\n\n\n\n<h2 id=\"h-reporting-the-results-of-anova\"><strong>Vykazov\u00e1n\u00ed v\u00fdsledk\u016f ANOVA<\/strong><\/h2>\n\n\n\n<p>P\u0159i vykazov\u00e1n\u00ed v\u00fdsledk\u016f anal\u00fdzy ANOVA je t\u0159eba uv\u00e9st n\u011bkolik informac\u00ed:<\/p>\n\n\n\n<p><strong>Statistika F: <\/strong>Jedn\u00e1 se o testovac\u00ed statistiku pro ANOVA, kter\u00e1 p\u0159edstavuje pom\u011br rozptylu mezi skupinami a rozptylu uvnit\u0159 skupiny.<\/p>\n\n\n\n<p><strong>Stupn\u011b volnosti pro statistiku F:<\/strong> To zahrnuje stupn\u011b volnosti pro \u010ditatele (variaci mezi skupinami) a jmenovatele (variaci uvnit\u0159 skupiny).<\/p>\n\n\n\n<p><strong>Hodnota p: <\/strong>P\u0159edstavuje pravd\u011bpodobnost z\u00edsk\u00e1n\u00ed pozorovan\u00e9 statistiky F (nebo extr\u00e9mn\u011bj\u0161\u00ed hodnoty) pouhou n\u00e1hodou za p\u0159edpokladu, \u017ee nulov\u00e1 hypot\u00e9za je pravdiv\u00e1.<\/p>\n\n\n\n<p><strong>Prohl\u00e1\u0161en\u00ed o tom, zda nulov\u00e1 hypot\u00e9za byla zam\u00edtnuta, nebo ne:<\/strong> Ta by m\u011bla vych\u00e1zet z p-hodnoty a zvolen\u00e9 hladiny v\u00fdznamnosti (nap\u0159. alfa = 0,05).<\/p>\n\n\n\n<p><strong>Post hoc testov\u00e1n\u00ed:<\/strong> Pokud je nulov\u00e1 hypot\u00e9za zam\u00edtnuta, je t\u0159eba uv\u00e9st v\u00fdsledky post hoc testov\u00e1n\u00ed, aby bylo mo\u017en\u00e9 ur\u010dit, kter\u00e9 skupiny se od sebe v\u00fdznamn\u011b li\u0161\u00ed.<\/p>\n\n\n\n<p>P\u0159\u00edkladem m\u016f\u017ee b\u00fdt nap\u0159\u00edklad tato zpr\u00e1va:<\/p>\n\n\n\n<p>Pro porovn\u00e1n\u00ed pr\u016fm\u011brn\u00fdch v\u00fdsledk\u016f t\u0159\u00ed skupin (skupina A, skupina B a skupina C) v testu udr\u017een\u00ed pam\u011bti byla provedena jednocestn\u00e1 ANOVA. Statistick\u00e1 hodnota F byla 4,58 se stupni volnosti 2, 87 a p-hodnotou 0,01. Nulov\u00e1 hypot\u00e9za byla zam\u00edtnuta, co\u017e znamen\u00e1, \u017ee existuje v\u00fdznamn\u00fd rozd\u00edl ve sk\u00f3re v testu udr\u017een\u00ed pam\u011bti alespo\u0148 v jedn\u00e9 ze skupin. post hoc testov\u00e1n\u00ed pomoc\u00ed Tukeyho HSD uk\u00e1zalo, \u017ee pr\u016fm\u011brn\u00e9 sk\u00f3re skupiny A (M = 83,4, SD = 4,2) bylo v\u00fdznamn\u011b vy\u0161\u0161\u00ed ne\u017e u skupiny B (M = 76,9, SD = 5,5) i skupiny C (M = 77,6, SD = 5,3), kter\u00e9 se od sebe v\u00fdznamn\u011b neli\u0161ily.<\/p>\n\n\n\n<h2 id=\"h-find-the-perfect-infographic-template-for-you\"><strong>Najd\u011bte si ide\u00e1ln\u00ed \u0161ablonu infografiky<\/strong><\/h2>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\/\" target=\"_blank\" rel=\"noreferrer noopener\">Mind the Graph<\/a> je platforma, kter\u00e1 poskytuje rozs\u00e1hlou sb\u00edrku p\u0159edp\u0159ipraven\u00fdch infografick\u00fdch \u0161ablon, je\u017e v\u011bdc\u016fm a v\u00fdzkumn\u00edk\u016fm pom\u00e1haj\u00ed vytv\u00e1\u0159et vizu\u00e1ln\u00ed pom\u016fcky, kter\u00e9 \u00fa\u010dinn\u011b sd\u011bluj\u00ed v\u011bdeck\u00e9 koncepty. Platforma nab\u00edz\u00ed p\u0159\u00edstup k rozs\u00e1hl\u00e9 knihovn\u011b v\u011bdeck\u00fdch ilustrac\u00ed, d\u00edky \u010demu\u017e mohou v\u011bdci a v\u00fdzkumn\u00edci snadno naj\u00edt dokonalou infografickou \u0161ablonu pro vizu\u00e1ln\u00ed sd\u011blen\u00ed v\u00fdsledk\u016f sv\u00e9ho v\u00fdzkumu.<\/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>Seznamte se s jednocestnou ANOVA, statistickou metodou pou\u017e\u00edvanou k porovn\u00e1v\u00e1n\u00ed pr\u016fm\u011br\u016f mezi v\u00edce skupinami p\u0159i anal\u00fdze dat, a nau\u010dte se ji pou\u017e\u00edvat.<\/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 - 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