{"id":55853,"date":"2025-01-09T12:04:31","date_gmt":"2025-01-09T15:04:31","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=55853"},"modified":"2025-01-23T12:12:27","modified_gmt":"2025-01-23T15:12:27","slug":"null-hypothesis-significance","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/cs\/null-hypothesis-significance\/","title":{"rendered":"Porozum\u011bn\u00ed v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy ve statistick\u00e9m testov\u00e1n\u00ed"},"content":{"rendered":"

V\u00fdznamnost nulov\u00e9 hypot\u00e9zy je z\u00e1kladn\u00edm pojmem statistick\u00e9ho testov\u00e1n\u00ed, kter\u00fd pom\u00e1h\u00e1 v\u00fdzkumn\u00edk\u016fm ur\u010dit, zda jejich data potvrzuj\u00ed ur\u010dit\u00e9 tvrzen\u00ed nebo pozorov\u00e1n\u00ed. Tento \u010dl\u00e1nek se zab\u00fdv\u00e1 konceptem v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy, jeho aplikacemi ve v\u00fdzkumu a jeho v\u00fdznamem p\u0159i rozhodov\u00e1n\u00ed na z\u00e1klad\u011b dat.<\/p>\n\n\n\n

Ve sv\u00e9 nejjednodu\u0161\u0161\u00ed podob\u011b nulov\u00e1 hypot\u00e9za p\u0159edpokl\u00e1d\u00e1, \u017ee mezi testovan\u00fdmi prom\u011bnn\u00fdmi neexistuje \u017e\u00e1dn\u00fd v\u00fdznamn\u00fd vliv nebo vztah. Jin\u00fdmi slovy p\u0159edpokl\u00e1d\u00e1, \u017ee ve\u0161ker\u00e9 rozd\u00edly, kter\u00e9 v datech pozorujete, jsou zp\u016fsobeny n\u00e1hodou, nikoliv skute\u010dn\u00fdm efektem.<\/p>\n\n\n\n

V\u00fdznam nulov\u00e9 hypot\u00e9zy spo\u010d\u00edv\u00e1 v jej\u00ed objektivit\u011b. Ale u toho se zastavme, proto\u017ee p\u0159\u00edli\u0161n\u00e9 krmen\u00ed na za\u010d\u00e1tku by v\u00e1s zm\u00e1tlo. Poj\u010fme se sezn\u00e1mit s v\u00fdznamnost nulov\u00e9 hypot\u00e9zy<\/strong>  od nuly!<\/p>\n\n\n\n

Porozum\u011bn\u00ed v\u00fdznamu nulov\u00e9 hypot\u00e9zy ve v\u00fdzkumu<\/h2>\n\n\n\n

Nulov\u00e1 hypot\u00e9za je kl\u00ed\u010dov\u00e1 pro pochopen\u00ed v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy, proto\u017ee p\u0159edstavuje p\u0159edpoklad neexistence \u00fa\u010dinku nebo vztahu mezi prom\u011bnn\u00fdmi p\u0159i statistick\u00e9m testov\u00e1n\u00ed. Jin\u00fdmi slovy p\u0159edpokl\u00e1d\u00e1, \u017ee cokoli testujete - a\u0165 u\u017e jde o nov\u00fd l\u00e9k, v\u00fdukovou metodu nebo jak\u00fdkoli jin\u00fd z\u00e1sah - nem\u00e1 \u017e\u00e1dn\u00fd dopad ve srovn\u00e1n\u00ed se standardn\u00edm nebo v\u00fdchoz\u00edm sc\u00e9n\u00e1\u0159em. <\/p>\n\n\n\n

\u00da\u010delem nulov\u00e9 hypot\u00e9zy je poskytnout v\u00fdchoz\u00ed bod pro anal\u00fdzu, kdy p\u0159edpokl\u00e1d\u00e1te, \u017ee nedo\u0161lo k \u017e\u00e1dn\u00e9 zm\u011bn\u011b nebo rozd\u00edlu.<\/p>\n\n\n\n

Nulovou hypot\u00e9zu si m\u016f\u017eete p\u0159edstavit jako v\u00fdchoz\u00ed stanovisko, kter\u00e9 se sna\u017e\u00edte vyvr\u00e1tit nebo zam\u00edtnout. Nam\u00edsto p\u0159\u00edm\u00e9ho p\u0159edpokladu, \u017ee v\u00e1\u0161 experiment bude m\u00edt n\u011bjak\u00fd efekt, nejprve uva\u017eujete, \u017ee se nic nezm\u011bnilo.\u00a0<\/p>\n\n\n\n

\""Propaga\u010dn\u00ed<\/a>
Vytv\u00e1\u0159ejte v\u011bdeck\u00e9 ilustrace bez n\u00e1mahy pomoc\u00ed Mind the Graph<\/a>.<\/figcaption><\/figure>\n\n\n\n

To v\u00e1m pom\u016f\u017ee p\u0159istupovat k situaci objektivn\u011b a zabr\u00e1n\u00ed v\u00e1m to d\u011blat un\u00e1hlen\u00e9 z\u00e1v\u011bry bez d\u016fkaz\u016f. Kdy\u017e za\u010dnete s p\u0159edpokladem \"\u017e\u00e1dn\u00fd \u00fa\u010dinek\", m\u016f\u017eete svou my\u0161lenku d\u016fsledn\u011b otestovat pomoc\u00ed dat, a teprve pokud jsou d\u016fkazy dostate\u010dn\u011b siln\u00e9, m\u016f\u017eete nulovou hypot\u00e9zu zam\u00edtnout a tvrdit, \u017ee k n\u011b\u010demu v\u00fdznamn\u00e9mu do\u0161lo.<\/p>\n\n\n\n

\u00daloha ve v\u011bdeck\u00fdch experimentech<\/h3>\n\n\n\n

Nulov\u00e1 hypot\u00e9za hraje v procesu v\u011bdeck\u00e9ho zkoum\u00e1n\u00ed z\u00e1sadn\u00ed roli. Vytv\u00e1\u0159\u00ed jasn\u00fd r\u00e1mec pro experimentov\u00e1n\u00ed a anal\u00fdzu dat. P\u0159i prov\u00e1d\u011bn\u00ed experimentu je obvykle va\u0161\u00edm c\u00edlem zjistit, zda ur\u010dit\u00e1 prom\u011bnn\u00e1 ovliv\u0148uje jinou prom\u011bnnou. <\/p>\n\n\n\n

M\u016f\u017eete nap\u0159\u00edklad cht\u00edt v\u011bd\u011bt, zda nov\u00fd l\u00e9k sni\u017euje p\u0159\u00edznaky \u00fa\u010dinn\u011bji ne\u017e placebo. Nulov\u00e1 hypot\u00e9za by v tomto p\u0159\u00edpad\u011b tvrdila, \u017ee l\u00e9k nem\u00e1 lep\u0161\u00ed \u00fa\u010dinek ne\u017e placebo, a va\u0161\u00edm \u00fakolem je shrom\u00e1\u017edit \u00fadaje, kter\u00e9 tuto my\u0161lenku bu\u010f podpo\u0159\u00ed, nebo vyvr\u00e1t\u00ed.<\/p>\n\n\n\n

Stanoven\u00edm nulov\u00e9 hypot\u00e9zy zav\u00e1d\u00edte do sv\u00e9ho experimentu tak\u00e9 pojem \"falzifikovatelnost\". Falzifikovatelnost znamen\u00e1, \u017ee va\u0161i hypot\u00e9zu lze testovat a p\u0159\u00edpadn\u011b prok\u00e1zat jej\u00ed nespr\u00e1vnost. To je d\u016fle\u017eit\u00e9, proto\u017ee to zaji\u0161\u0165uje, \u017ee va\u0161e v\u011bdeck\u00e1 tvrzen\u00ed jsou zalo\u017eena na m\u011b\u0159iteln\u00fdch \u00fadaj\u00edch, nikoli na p\u0159edpokladech nebo odhadech.<\/p>\n\n\n\n

P\u0159\u00edklady nulov\u00e9 hypot\u00e9zy<\/h3>\n\n\n\n

P\u0159\u00edklad 1: Testov\u00e1n\u00ed nov\u00e9ho dietn\u00edho pl\u00e1nu<\/strong><\/p>\n\n\n\n

P\u0159edstavte si, \u017ee testujete nov\u00fd dietn\u00ed pl\u00e1n, abyste zjistili, zda pom\u00e1h\u00e1 lidem zhubnout ve srovn\u00e1n\u00ed s b\u011b\u017enou dietou. Va\u0161e nulov\u00e1 hypot\u00e9za by zn\u011bla: \"Nov\u00fd j\u00eddeln\u00ed\u010dek nem\u00e1 \u017e\u00e1dn\u00fd vliv na hubnut\u00ed ve srovn\u00e1n\u00ed s b\u011b\u017en\u00fdm j\u00eddeln\u00ed\u010dkem\". To znamen\u00e1, \u017ee vych\u00e1z\u00edte z p\u0159edpokladu, \u017ee nov\u00e1 dieta nefunguje l\u00e9pe ne\u017e to, co lid\u00e9 ji\u017e jed\u00ed.<\/p>\n\n\n\n

Jakmile budete m\u00edt tuto nulovou hypot\u00e9zu, m\u016f\u017eete shrom\u00e1\u017edit \u00fadaje tak, \u017ee budete m\u00edt dv\u011b skupiny lid\u00ed - jednu, kter\u00e1 bude dodr\u017eovat novou dietu, a druhou, kter\u00e1 bude dodr\u017eovat svou b\u011b\u017enou dietu. Pokud po anal\u00fdze dat zjist\u00edte, \u017ee skupina dr\u017e\u00edc\u00ed novou dietu zhubla v\u00fdrazn\u011b v\u00edce ne\u017e kontroln\u00ed skupina, m\u016f\u017eete nulovou hypot\u00e9zu zam\u00edtnout. To by nazna\u010dovalo, \u017ee nov\u00fd dietn\u00ed pl\u00e1n m\u00e1 skute\u010dn\u011b pozitivn\u00ed \u00fa\u010dinek.<\/p>\n\n\n\n

P\u0159\u00edklad 2: Studium vlivu sp\u00e1nku na v\u00fdsledky test\u016f<\/strong><\/p>\n\n\n\n

V jin\u00e9m p\u0159\u00edpad\u011b byste mohli cht\u00edt zjistit, zda v\u00edce sp\u00e1nku zlep\u0161uje v\u00fdsledky \u017e\u00e1k\u016f v testech. Va\u0161e nulov\u00e1 hypot\u00e9za by zn\u011bla: \"Neexistuje \u017e\u00e1dn\u00fd vztah mezi mno\u017estv\u00edm sp\u00e1nku a v\u00fdsledky student\u016f v testech.\" Jin\u00fdmi slovy, p\u0159edpokl\u00e1d\u00e1te, \u017ee mno\u017estv\u00ed sp\u00e1nku student\u016f nem\u00e1 vliv na jejich v\u00fdkony v testech.<\/p>\n\n\n\n

Pot\u00e9 byste shroma\u017e\u010fovali \u00fadaje o sp\u00e1nkov\u00fdch n\u00e1vyc\u00edch student\u016f a jejich v\u00fdsledc\u00edch v testech. Pokud zjist\u00edte, \u017ee studenti, kte\u0159\u00ed v\u00edce sp\u00ed, dosahuj\u00ed trvale lep\u0161\u00edch v\u00fdsledk\u016f, m\u016f\u017eete zam\u00edtnout nulovou hypot\u00e9zu a doj\u00edt k z\u00e1v\u011bru, \u017ee v\u00edce sp\u00e1nku skute\u010dn\u011b zlep\u0161uje studijn\u00ed v\u00fdsledky. <\/p>\n\n\n\n

Pokud v\u0161ak va\u0161e data neprok\u00e1\u017e\u00ed \u017e\u00e1dn\u00fd v\u00fdznamn\u00fd rozd\u00edl mezi dob\u0159e odpo\u010dinut\u00fdmi studenty a t\u011bmi, kte\u0159\u00ed sp\u00ed m\u00e9n\u011b, nulovou hypot\u00e9zu nezam\u00edtnete, co\u017e znamen\u00e1, \u017ee neexistuje \u017e\u00e1dn\u00fd d\u016fkaz, kter\u00fd by nazna\u010doval, \u017ee sp\u00e1nek m\u00e1 v\u00fdznamn\u00fd vliv na v\u00fdsledky test\u016f.<\/p>\n\n\n\n

V obou p\u0159\u00edkladech slou\u017e\u00ed nulov\u00e1 hypot\u00e9za jako z\u00e1klad pro testov\u00e1n\u00ed a pom\u00e1h\u00e1 v\u00e1m posoudit, zda shrom\u00e1\u017ed\u011bn\u00e1 data poskytuj\u00ed dostatek d\u016fkaz\u016f pro vyvozen\u00ed smyslupln\u00fdch z\u00e1v\u011br\u016f.<\/p>\n\n\n\n

Souvisej\u00edc\u00ed \u010dl\u00e1nek: <\/strong>Definujte hypot\u00e9zu: Odhalen\u00ed prvn\u00edho kroku v\u011bdeck\u00e9ho zkoum\u00e1n\u00ed<\/strong><\/a><\/p>\n\n\n\n

D\u016fle\u017eitost v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy p\u0159i testov\u00e1n\u00ed<\/h2>\n\n\n\n

\u00da\u010del nulov\u00e9 hypot\u00e9zy<\/h3>\n\n\n\n

Koncept v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy je z\u00e1kladem v\u00fdzkumu, proto\u017ee poskytuje neutr\u00e1ln\u00ed v\u00fdchoz\u00ed bod pro objektivn\u00ed hodnocen\u00ed v\u011bdeck\u00fdch tvrzen\u00ed. Jeho \u00fa\u010delem je poskytnout neutr\u00e1ln\u00ed v\u00fdchoz\u00ed bod, kter\u00fd v\u00e1m pom\u016f\u017ee otestovat, zda jsou v\u00fdsledky va\u0161eho experimentu zp\u016fsobeny n\u00e1hodou, nebo skute\u010dn\u00fdm \u00fa\u010dinkem. <\/p>\n\n\n\n

Kdy\u017e prov\u00e1d\u00edte v\u00fdzkum, \u010dasto m\u00e1te na mysli n\u011bjakou teorii nebo p\u0159edpov\u011b\u010f - n\u011bco, co chcete dok\u00e1zat. Nulov\u00e1 hypot\u00e9za v\u0161ak p\u0159edpokl\u00e1d\u00e1, \u017ee neexistuje \u017e\u00e1dn\u00fd \u00fa\u010dinek nebo vztah. Pokud nap\u0159\u00edklad testujete, zda nov\u00fd l\u00e9k zlep\u0161uje zotaven\u00ed pacienta, nulov\u00e1 hypot\u00e9za bude tvrdit, \u017ee l\u00e9k nem\u00e1 \u017e\u00e1dn\u00fd \u00fa\u010dinek ve srovn\u00e1n\u00ed s placebem.<\/p>\n\n\n\n

Tento p\u0159edpoklad je velmi d\u016fle\u017eit\u00fd, proto\u017ee udr\u017euje va\u0161i anal\u00fdzu objektivn\u00ed. Pokud vych\u00e1z\u00edte z p\u0159edpokladu, \u017ee se nic nezm\u011bnilo ani nezlep\u0161ilo, m\u00e1te jistotu, \u017ee ve\u0161ker\u00e9 z\u00e1v\u011bry, kter\u00e9 vyvod\u00edte, jsou zalo\u017eeny na spolehliv\u00fdch d\u016fkazech, a nikoli na osobn\u00edch p\u0159esv\u011bd\u010den\u00edch nebo o\u010dek\u00e1v\u00e1n\u00edch. <\/p>\n\n\n\n

Pom\u00e1h\u00e1 v\u00e1m to zachovat si nezaujat\u00fd p\u0159\u00edstup a zabr\u00e1nit un\u00e1hlen\u00fdm z\u00e1v\u011br\u016fm jen proto, \u017ee chcete, aby va\u0161e hypot\u00e9za byla pravdiv\u00e1.<\/p>\n\n\n\n

Nulov\u00e1 hypot\u00e9za nav\u00edc poskytuje standard, s n\u00edm\u017e m\u016f\u017eete pom\u011b\u0159ovat sv\u00e1 zji\u0161t\u011bn\u00ed. Bez n\u00ed byste nem\u011bli jasn\u00fd z\u00e1klad pro porovn\u00e1n\u00ed v\u00fdsledk\u016f, tak\u017ee by bylo obt\u00ed\u017en\u00e9 zjistit, zda data skute\u010dn\u011b potvrzuj\u00ed va\u0161i teorii. <\/p>\n\n\n\n

Nulov\u00e1 hypot\u00e9za je tedy v ka\u017ed\u00e9m experimentu pojistkou, kter\u00e1 zaji\u0161\u0165uje, \u017ee va\u0161e z\u00e1v\u011bry jsou podlo\u017eeny daty, nikoli p\u0159edpoklady.<\/p>\n\n\n\n

\u00daloha p\u0159i testov\u00e1n\u00ed hypot\u00e9z<\/h3>\n\n\n\n

Testov\u00e1n\u00ed hypot\u00e9z se to\u010d\u00ed kolem v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy, kdy se posuzuje, zda jsou pozorovan\u00e9 v\u00fdsledky v\u00fdznamn\u00e9, nebo zda jsou zp\u016fsobeny pouze n\u00e1hodnou variac\u00ed. Zde se nulov\u00e1 hypot\u00e9za st\u00e1v\u00e1 kl\u00ed\u010dovou. Za\u010d\u00edn\u00e1te stanoven\u00edm dvou hypot\u00e9z: nulov\u00e9 hypot\u00e9zy (kter\u00e1 p\u0159edpokl\u00e1d\u00e1, \u017ee neexistuje \u017e\u00e1dn\u00fd \u00fa\u010dinek) a alternativn\u00ed hypot\u00e9zy (kter\u00e1 p\u0159edpokl\u00e1d\u00e1, \u017ee \u00fa\u010dinek nebo vztah existuje).<\/p>\n\n\n\n

Proces testov\u00e1n\u00ed hypot\u00e9z obvykle zahrnuje sb\u011br dat a jejich anal\u00fdzu, aby se zjistilo, kterou hypot\u00e9zu data potvrzuj\u00ed. Nejprve se p\u0159edpokl\u00e1d\u00e1, \u017ee nulov\u00e1 hypot\u00e9za je pravdiv\u00e1. Pot\u00e9 provedete experiment a shrom\u00e1\u017ed\u00edte data, abyste tento p\u0159edpoklad ov\u011b\u0159ili. <\/p>\n\n\n\n

Pot\u00e9 pou\u017eijete statistick\u00e9 metody k anal\u00fdze dat, nap\u0159\u00edklad v\u00fdpo\u010det p-hodnot nebo interval\u016f spolehlivosti. Tyto metody v\u00e1m pomohou posoudit pravd\u011bpodobnost, \u017ee pozorovan\u00e9 v\u00fdsledky vznikly n\u00e1hodou.<\/p>\n\n\n\n

Pokud data ukazuj\u00ed, \u017ee pozorovan\u00e9 v\u00fdsledky jsou velmi nepravd\u011bpodobn\u00e9 p\u0159i nulov\u00e9 hypot\u00e9ze (obvykle se ur\u010duje p-hodnotou ni\u017e\u0161\u00ed ne\u017e ur\u010dit\u00e1 hranice, nap\u0159. 0,05), nulovou hypot\u00e9zu zam\u00edtnete. <\/p>\n\n\n\n

To nutn\u011b neznamen\u00e1, \u017ee alternativn\u00ed hypot\u00e9za je absolutn\u011b pravdiv\u00e1, ale nazna\u010duje to, \u017ee existuje dostatek d\u016fkaz\u016f, kter\u00e9 ji podporuj\u00ed oproti nulov\u00e9 hypot\u00e9ze.<\/p>\n\n\n\n

Na druhou stranu, pokud data neposkytuj\u00ed dostate\u010dn\u011b siln\u00fd d\u016fkaz pro zam\u00edtnut\u00ed nulov\u00e9 hypot\u00e9zy, \"nezam\u00edtnete\" ji. To znamen\u00e1, \u017ee nem\u00e1te dostatek d\u016fkaz\u016f pro tvrzen\u00ed o v\u00fdznamn\u00e9m \u00fa\u010dinku nebo vztahu, tak\u017ee nulov\u00e1 hypot\u00e9za z\u016fst\u00e1v\u00e1 v platnosti.<\/p>\n\n\n\n

Testov\u00e1n\u00ed nulov\u00e9 hypot\u00e9zy je z\u00e1sadn\u00ed, proto\u017ee v\u00e1m umo\u017e\u0148uje \u010dinit informovan\u00e1 rozhodnut\u00ed o v\u00fdznamnosti va\u0161ich v\u00fdsledk\u016f. Pom\u00e1h\u00e1 v\u00e1m vyhnout se fale\u0161n\u011b pozitivn\u00edm v\u00fdsledk\u016fm, kdy m\u016f\u017eete nespr\u00e1vn\u011b doj\u00edt k z\u00e1v\u011bru, \u017ee vztah existuje, i kdy\u017e tomu tak nen\u00ed. <\/p>\n\n\n\n

Faktory ovliv\u0148uj\u00edc\u00ed testov\u00e1n\u00ed nulov\u00e9 hypot\u00e9zy<\/h2>\n\n\n\n

Hladina v\u00fdznamnosti, \u010dasto ozna\u010dovan\u00e1 symbolem \u03b1 (alfa), je kl\u00ed\u010dov\u00fdm faktorem p\u0159i testov\u00e1n\u00ed hypot\u00e9z. Jedn\u00e1 se o hranici, kterou stanov\u00edte, abyste ur\u010dili, zda jsou v\u00fdsledky va\u0161eho experimentu statisticky v\u00fdznamn\u00e9, tedy zda je pozorovan\u00fd \u00fa\u010dinek pravd\u011bpodobn\u011b skute\u010dn\u00fd, nebo zda je zp\u016fsoben pouhou n\u00e1hodou. <\/p>\n\n\n\n

Hladina v\u00fdznamnosti se obvykle vol\u00ed 0,05 (nebo 5%). To znamen\u00e1, \u017ee jste ochotni p\u0159ipustit 5% \u0161anci, \u017ee v\u00fdsledky jsou zp\u016fsobeny sp\u00ed\u0161e n\u00e1hodnou variac\u00ed ne\u017e skute\u010dn\u00fdm \u00fa\u010dinkem.<\/p>\n\n\n\n

Hladinu v\u00fdznamnosti pova\u017eujte za mezn\u00ed bod. Pokud je p-hodnota, kter\u00e1 m\u011b\u0159\u00ed pravd\u011bpodobnost pozorov\u00e1n\u00ed \u00fa\u010dinku, pokud je nulov\u00e1 hypot\u00e9za pravdiv\u00e1, men\u0161\u00ed ne\u017e hladina v\u00fdznamnosti, nulovou hypot\u00e9zu zam\u00edtnete. To nazna\u010duje, \u017ee existuje dostatek d\u016fkaz\u016f pro z\u00e1v\u011br, \u017ee skute\u010dn\u00fd \u00fa\u010dinek nebo vztah existuje. Na druhou stranu, pokud je p-hodnota v\u011bt\u0161\u00ed ne\u017e hladina v\u00fdznamnosti, nulovou hypot\u00e9zu nezam\u00edtnete, co\u017e nazna\u010duje, \u017ee data neposkytuj\u00ed dostate\u010dn\u011b siln\u00e9 d\u016fkazy pro podporu v\u00fdznamn\u00e9ho zji\u0161t\u011bn\u00ed.<\/p>\n\n\n\n

Zvolen\u00e1 hladina v\u00fdznamnosti ovliv\u0148uje p\u0159\u00edsnost testov\u00e1n\u00ed. Ni\u017e\u0161\u00ed hladina v\u00fdznamnosti (nap\u0159. 0,01 nebo 1%) znamen\u00e1, \u017ee jste opatrn\u011bj\u0161\u00ed p\u0159i zam\u00edt\u00e1n\u00ed nulov\u00e9 hypot\u00e9zy, ale tak\u00e9 sni\u017euje pravd\u011bpodobnost nalezen\u00ed v\u00fdznamn\u00fdch v\u00fdsledk\u016f. <\/p>\n\n\n\n

Vy\u0161\u0161\u00ed hladina v\u00fdznamnosti (nap\u0159. 0,10 nebo 10%) zvy\u0161uje \u0161anci na nalezen\u00ed v\u00fdznamn\u00fdch v\u00fdsledk\u016f, ale zvy\u0161uje pravd\u011bpodobnost, \u017ee byste mohli nepravdiv\u011b zam\u00edtnout nulovou hypot\u00e9zu. Proto je volba hladiny v\u00fdznamnosti d\u016fle\u017eit\u00e1 a m\u011bla by odr\u00e1\u017eet kontext va\u0161\u00ed studie.<\/p>\n\n\n\n

Chyby typu I a typu II<\/h3>\n\n\n\n

P\u0159i testov\u00e1n\u00ed hypot\u00e9z se mohou vyskytnout dva typy chyb: Chyby typu I a chyby typu II. Tyto chyby p\u0159\u00edmo souvisej\u00ed s v\u00fdsledkem testu a volbou hladiny v\u00fdznamnosti.<\/p>\n\n\n\n

Chyba typu I<\/h4>\n\n\n\n

K chyb\u011b typu I doch\u00e1z\u00ed, kdy\u017e zam\u00edtnete nulovou hypot\u00e9zu, p\u0159esto\u017ee je ve skute\u010dnosti pravdiv\u00e1. Jin\u00fdmi slovy, dojdete k z\u00e1v\u011bru, \u017ee existuje \u00fa\u010dinek nebo vztah, i kdy\u017e ve skute\u010dnosti neexistuje. <\/p>\n\n\n\n

Tomuto jevu se tak\u00e9 \u0159\u00edk\u00e1 \"fale\u0161n\u00e1 pozitivita\", proto\u017ee detekujete n\u011bco, co tam ve skute\u010dnosti nen\u00ed.<\/p>\n\n\n\n

Nastaven\u00e1 hladina v\u00fdznamnosti (\u03b1) p\u0159edstavuje pravd\u011bpodobnost chyby typu I. Nap\u0159\u00edklad pokud je va\u0161e hladina v\u00fdznamnosti 0,05, existuje 5% pravd\u011bpodobnost, \u017ee nespr\u00e1vn\u011b zam\u00edtnete nulovou hypot\u00e9zu, i kdy\u017e je pravdiv\u00e1. <\/p>\n\n\n\n

D\u016fsledky chyby typu I mohou b\u00fdt z\u00e1va\u017en\u00e9, zejm\u00e9na v oborech, jako je medic\u00edna nebo farmacie. Pokud je testov\u00e1n nov\u00fd l\u00e9k a dojde k chyb\u011b typu I, mohou se v\u011bdci domn\u00edvat, \u017ee l\u00e9k je \u00fa\u010dinn\u00fd, i kdy\u017e nen\u00ed, co\u017e m\u016f\u017ee v\u00e9st ke \u0161kodliv\u00fdm n\u00e1sledk\u016fm.<\/p>\n\n\n\n

Chcete-li sn\u00ed\u017eit riziko chyby typu I, m\u016f\u017eete zvolit ni\u017e\u0161\u00ed hladinu v\u00fdznamnosti. P\u0159\u00edli\u0161n\u00e1 opatrnost a p\u0159\u00edli\u0161n\u00e9 sn\u00ed\u017een\u00ed hladiny v\u00fdznamnosti v\u0161ak m\u016f\u017ee m\u00edt i sv\u00e9 nev\u00fdhody, proto\u017ee m\u016f\u017ee zt\u00ed\u017eit odhalen\u00ed skute\u010dn\u00fdch \u00fa\u010dink\u016f (co\u017e vede k dal\u0161\u00edmu typu chyby - chyb\u011b typu II).<\/p>\n\n\n\n

Chyba typu II<\/h4>\n\n\n\n

Chyba typu II nastane, kdy\u017e se nepoda\u0159\u00ed zam\u00edtnout nulovou hypot\u00e9zu, i kdy\u017e je ve skute\u010dnosti nepravdiv\u00e1. Zjednodu\u0161en\u011b \u0159e\u010deno to znamen\u00e1, \u017ee v\u00e1m unik\u00e1 skute\u010dn\u00fd \u00fa\u010dinek nebo vztah, kter\u00fd skute\u010dn\u011b existuje. Tato chyba se naz\u00fdv\u00e1 \"fale\u0161n\u011b negativn\u00ed\", proto\u017ee se v\u00e1m nepoda\u0159\u00ed odhalit n\u011bco, co ve skute\u010dnosti existuje.<\/p>\n\n\n\n

Pravd\u011bpodobnost chyby II. typu je vyj\u00e1d\u0159ena symbolem \u03b2 (beta). Na rozd\u00edl od hladiny v\u00fdznamnosti, kterou nastav\u00edte p\u0159ed testov\u00e1n\u00edm, je \u03b2 ovlivn\u011bna faktory, jako je velikost vzorku, velikost \u00fa\u010dinku a hladina v\u00fdznamnosti. <\/p>\n\n\n\n

V\u011bt\u0161\u00ed velikost vzorku sni\u017euje pravd\u011bpodobnost chyby typu II, proto\u017ee poskytuje v\u00edce \u00fadaj\u016f, co\u017e usnad\u0148uje odhalen\u00ed skute\u010dn\u00fdch \u00fa\u010dink\u016f. Stejn\u011b tak v\u011bt\u0161\u00ed velikosti efekt\u016f (siln\u011bj\u0161\u00ed vztahy) jsou snadn\u011bji zjistiteln\u00e9 a sni\u017euj\u00ed pravd\u011bpodobnost chyby typu II.<\/p>\n\n\n\n

Chyby II. typu mohou b\u00fdt stejn\u011b problematick\u00e9 jako chyby I. typu, zvl\u00e1\u0161t\u011b kdy\u017e jde o hodn\u011b. <\/p>\n\n\n\n

Pokud nap\u0159\u00edklad testujete, zda nov\u00e1 l\u00e9\u010dba funguje, a dopust\u00edte se chyby II. typu, m\u016f\u017eete doj\u00edt k z\u00e1v\u011bru, \u017ee l\u00e9\u010dba nem\u00e1 \u017e\u00e1dn\u00fd \u00fa\u010dinek, i kdy\u017e ve skute\u010dnosti \u00fa\u010dinek m\u00e1, a zabr\u00e1nit tak pacient\u016fm, aby dost\u00e1vali potenci\u00e1ln\u011b prosp\u011b\u0161nou l\u00e9\u010dbu.<\/p>\n\n\n\n

D\u016fle\u017eit\u00e9 je vyv\u00e1\u017eit riziko obou typ\u016f chyb. Pokud se p\u0159\u00edli\u0161 soust\u0159ed\u00edte na to, abyste se vyhnuli chyb\u00e1m typu I t\u00edm, \u017ee nastav\u00edte velmi n\u00edzkou hladinu v\u00fdznamnosti, zv\u00fd\u0161\u00edte riziko chyb typu II, tedy p\u0159ehl\u00e9dnut\u00ed skute\u010dn\u00fdch zji\u0161t\u011bn\u00ed. Na druhou stranu, pokud se sna\u017e\u00edte vyhnout chyb\u00e1m typu II nastaven\u00edm vy\u0161\u0161\u00ed hladiny v\u00fdznamnosti, zvy\u0161ujete t\u00edm pravd\u011bpodobnost chyby typu I. Proto je kl\u00ed\u010dov\u00e9 pe\u010dliv\u00e9 pl\u00e1nov\u00e1n\u00ed a zohledn\u011bn\u00ed kontextu va\u0161\u00ed studie.<\/p>\n\n\n\n

P\u0159e\u010dt\u011bte si tak\u00e9: <\/strong>Testov\u00e1n\u00ed hypot\u00e9z: Principy a metody<\/strong><\/a><\/p>\n\n\n\n

Aplikace v\u00fdznamu nulov\u00e9 hypot\u00e9zy v re\u00e1ln\u00e9m sv\u011bt\u011b<\/h2>\n\n\n\n

Ka\u017edodenn\u00ed p\u0159\u00edklady<\/h3>\n\n\n\n

Koncept nulov\u00e9 hypot\u00e9zy se neomezuje pouze na slo\u017eit\u00e9 v\u011bdeck\u00e9 studie - ve skute\u010dnosti se vztahuje na mnoho sc\u00e9n\u00e1\u0159\u016f v ka\u017edodenn\u00edm \u017eivot\u011b. Abyste jej l\u00e9pe pochopili, pod\u00edvejme se na dva jednoduch\u00e9 a snadno pochopiteln\u00e9 p\u0159\u00edklady, kde se nulov\u00e1 hypot\u00e9za pou\u017e\u00edv\u00e1.<\/p>\n\n\n\n

P\u0159\u00edklad 1: Testov\u00e1n\u00ed nov\u00e9ho tr\u00e9ninkov\u00e9ho pl\u00e1nu<\/strong><\/p>\n\n\n\n

P\u0159edstavte si, \u017ee jste narazili na nov\u00fd cvi\u010debn\u00ed pl\u00e1n, kter\u00fd tvrd\u00ed, \u017ee v\u00e1m pom\u016f\u017ee zhubnout v\u00edce ne\u017e va\u0161e sou\u010dasn\u00e1 rutina. Nulovou hypot\u00e9zou by zde bylo, \u017ee nov\u00fd cvi\u010debn\u00ed pl\u00e1n nep\u0159in\u00e1\u0161\u00ed v\u00fdznamn\u00fd rozd\u00edl v \u00fabytku hmotnosti ve srovn\u00e1n\u00ed s va\u0161\u00ed st\u00e1vaj\u00edc\u00ed rutinou. Jin\u00fdmi slovy, vych\u00e1z\u00edte z p\u0159edpokladu, \u017ee nov\u00fd pl\u00e1n v\u00e1m nepom\u016f\u017ee zhubnout v\u00edce.<\/p>\n\n\n\n

Pak byste to mohli vyzkou\u0161et tak, \u017ee budete po ur\u010ditou dobu dodr\u017eovat oba tr\u00e9ninkov\u00e9 pl\u00e1ny a sledovat, jak s ka\u017ed\u00fdm z nich hubnete. Pokud po shrom\u00e1\u017ed\u011bn\u00ed dostate\u010dn\u00e9ho mno\u017estv\u00ed \u00fadaj\u016f zjist\u00edte, \u017ee s nov\u00fdm pl\u00e1nem hubnete v\u00fdrazn\u011b v\u00edce, m\u016f\u017eete nulovou hypot\u00e9zu zam\u00edtnout a doj\u00edt k z\u00e1v\u011bru, \u017ee nov\u00fd pl\u00e1n je \u00fa\u010dinn\u00fd. <\/p>\n\n\n\n

Na druhou stranu, pokud jsou v\u00fdsledky hubnut\u00ed podobn\u00e9, nulovou hypot\u00e9zu se nepoda\u0159\u00ed zam\u00edtnout, co\u017e znamen\u00e1, \u017ee nov\u00fd pl\u00e1n nep\u0159inesl \u017e\u00e1dn\u00fd dal\u0161\u00ed p\u0159\u00ednos.<\/p>\n\n\n\n

P\u0159\u00edklad 2: Hodnocen\u00ed \u00fa\u010dinnosti aplikace pro sp\u00e1nek<\/strong><\/p>\n\n\n\n

\u0158ekn\u011bme, \u017ee si st\u00e1hnete aplikaci pro sp\u00e1nek, kter\u00e1 tvrd\u00ed, \u017ee v\u00e1m pom\u016f\u017ee zlep\u0161it kvalitu sp\u00e1nku. Chcete vyzkou\u0161et, zda pou\u017e\u00edv\u00e1n\u00ed t\u00e9to aplikace skute\u010dn\u011b vede ke zlep\u0161en\u00ed sp\u00e1nku. Va\u0161e nulov\u00e1 hypot\u00e9za by byla, \u017ee aplikace nem\u00e1 \u017e\u00e1dn\u00fd vliv na kvalitu va\u0161eho sp\u00e1nku.<\/p>\n\n\n\n

Chcete-li to vyzkou\u0161et, m\u016f\u017eete sledovat sv\u016fj sp\u00e1nkov\u00fd re\u017eim po dobu jednoho t\u00fddne bez pou\u017e\u00edv\u00e1n\u00ed aplikace a pot\u00e9 po dobu dal\u0161\u00edho t\u00fddne s jej\u00edm pou\u017e\u00edv\u00e1n\u00edm. Pokud zjist\u00edte, \u017ee se v\u00e1\u0161 sp\u00e1nek po pou\u017e\u00edv\u00e1n\u00ed aplikace v\u00fdrazn\u011b zlep\u0161il - nap\u0159\u00edklad us\u00edn\u00e1te rychleji nebo se bud\u00edte m\u00e9n\u011b \u010dasto - m\u016f\u017eete nulovou hypot\u00e9zu zam\u00edtnout. To by nazna\u010dovalo, \u017ee aplikace skute\u010dn\u011b zlep\u0161ila v\u00e1\u0161 sp\u00e1nek. Pokud by v\u0161ak \u00fadaje nevykazovaly \u017e\u00e1dn\u00fd znateln\u00fd rozd\u00edl, nulovou hypot\u00e9zu byste nezam\u00edtli, co\u017e by znamenalo, \u017ee aplikace pravd\u011bpodobn\u011b nem\u00e1 \u017e\u00e1dn\u00fd m\u011b\u0159iteln\u00fd \u00fa\u010dinek.<\/p>\n\n\n\n

Obvykl\u00e9 myln\u00e9 p\u0159edstavy o v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy<\/h3>\n\n\n\n

Interpretace v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy m\u016f\u017ee b\u00fdt n\u00e1ro\u010dn\u00e1 kv\u016fli b\u011b\u017en\u00fdm myln\u00fdm p\u0159edstav\u00e1m, jako je ztoto\u017en\u011bn\u00ed statistick\u00e9 v\u00fdznamnosti s praktick\u00fdm v\u00fdznamem.<\/p>\n\n\n\n

Nej\u010dast\u011bj\u0161\u00ed myln\u00e9 p\u0159edstavy<\/h4>\n\n\n\n

Jedn\u00edm z \u010dast\u00fdch omyl\u016f je, \u017ee pokud se nepoda\u0159\u00ed zam\u00edtnout nulovou hypot\u00e9zu, znamen\u00e1 to, \u017ee nulov\u00e1 hypot\u00e9za je ur\u010dit\u011b pravdiv\u00e1. Nen\u00ed tomu tak. Ne\u00fasp\u011bch p\u0159i zam\u00edtnut\u00ed nulov\u00e9 hypot\u00e9zy jednodu\u0161e znamen\u00e1, \u017ee nem\u00e1te dostatek d\u016fkaz\u016f pro podporu alternativn\u00ed hypot\u00e9zy. <\/p>\n\n\n\n

Nedokazuje, \u017ee nulov\u00e1 hypot\u00e9za je spr\u00e1vn\u00e1, ale sp\u00ed\u0161e to, \u017ee data, kter\u00e1 jste shrom\u00e1\u017edili, neposkytuj\u00ed dostate\u010dnou podporu pro jin\u00fd z\u00e1v\u011br.<\/p>\n\n\n\n

Dal\u0161\u00edm nedorozum\u011bn\u00edm je p\u0159esv\u011bd\u010den\u00ed, \u017ee zam\u00edtnut\u00ed nulov\u00e9 hypot\u00e9zy znamen\u00e1, \u017ee va\u0161e zji\u0161t\u011bn\u00ed jsou automaticky d\u016fle\u017eit\u00e1 nebo cenn\u00e1. Statistick\u00e1 v\u00fdznamnost znamen\u00e1 pouze to, \u017ee pozorovan\u00fd \u00fa\u010dinek pravd\u011bpodobn\u011b nevznikl n\u00e1hodn\u011b na z\u00e1klad\u011b \u00fadaj\u016f, kter\u00e9 jste shrom\u00e1\u017edili. Nemus\u00ed nutn\u011b znamenat, \u017ee \u00fa\u010dinek je velk\u00fd nebo prakticky v\u00fdznamn\u00fd. <\/p>\n\n\n\n

M\u016f\u017eete nap\u0159\u00edklad zjistit statisticky v\u00fdznamn\u00fd v\u00fdsledek, kter\u00fd vykazuje nepatrn\u00fd \u00fa\u010dinek, kter\u00fd m\u00e1 v re\u00e1ln\u00e9m sv\u011bt\u011b jen mal\u00fd dopad.<\/p>\n\n\n\n

Vyhnut\u00ed se n\u00e1strah\u00e1m<\/h4>\n\n\n\n

Abyste se vyhnuli t\u011bmto n\u00e1strah\u00e1m, je nutn\u00e9 si uv\u011bdomit, \u017ee statistick\u00e1 v\u00fdznamnost je pouze jedn\u00edm z d\u00edlk\u016f skl\u00e1da\u010dky. M\u011bli byste tak\u00e9 zv\u00e1\u017eit praktickou v\u00fdznamnost, kter\u00e1 se pt\u00e1, zda je pozorovan\u00fd \u00fa\u010dinek dostate\u010dn\u011b velk\u00fd, aby m\u011bl v\u00fdznam v re\u00e1ln\u00e9m sv\u011bt\u011b. <\/p>\n\n\n\n

I kdy\u017e nap\u0159\u00edklad nov\u00e1 vyu\u010dovac\u00ed metoda vede k mal\u00e9mu zlep\u0161en\u00ed v\u00fdsledk\u016f v testech, nemus\u00ed to b\u00fdt dostate\u010dn\u011b v\u00fdznamn\u00e9 na to, aby bylo nutn\u00e9 m\u011bnit cel\u00e9 u\u010debn\u00ed osnovy.<\/p>\n\n\n\n

Dal\u0161\u00ed d\u016fle\u017eitou radou je ujistit se, \u017ee se nespol\u00e9h\u00e1te pouze na p-hodnoty. P-hodnoty v\u00e1m mohou pomoci rozhodnout, zda nulovou hypot\u00e9zu zam\u00edtnout, nebo nezam\u00edtnout, ale ne\u0159eknou v\u00e1m cel\u00fd p\u0159\u00edb\u011bh. <\/p>\n\n\n\n

Z\u00e1sadn\u00ed je tak\u00e9 sledovat velikost efektu a intervaly spolehlivosti kolem v\u00fdsledk\u016f. Ty v\u00e1m poskytnou jasn\u011bj\u0161\u00ed p\u0159edstavu o tom, jak spolehliv\u00e1 jsou va\u0161e zji\u0161t\u011bn\u00ed.<\/p>\n\n\n\n

Nakonec se vyhn\u011bte poku\u0161en\u00ed manipulovat s daty nebo testovat tak dlouho, dokud nezjist\u00edte v\u00fdznamn\u00fd v\u00fdsledek. Tento postup, zn\u00e1m\u00fd jako \"p-hacking\", m\u016f\u017ee v\u00e9st k fale\u0161n\u00fdm z\u00e1v\u011br\u016fm. M\u00edsto toho si studii pe\u010dliv\u011b napl\u00e1nujte, shrom\u00e1\u017ed\u011bte dostatek dat a prove\u010fte \u0159\u00e1dnou anal\u00fdzu, abyste se ujistili, \u017ee va\u0161e z\u00e1v\u011bry jsou zalo\u017eeny na spolehliv\u00fdch d\u016fkazech.<\/p>\n\n\n\n

Z\u00e1v\u011brem lze \u0159\u00edci, \u017ee testov\u00e1n\u00ed nulov\u00fdch hypot\u00e9z m\u016f\u017ee b\u00fdt \u00fa\u010dinn\u00fdm n\u00e1strojem, je v\u0161ak d\u016fle\u017eit\u00e9 interpretovat v\u00fdsledky opatrn\u011b a vyvarovat se b\u011b\u017en\u00fdch myln\u00fdch p\u0159edstav. Zam\u011b\u0159\u00edte-li se nejen na statistickou v\u00fdznamnost, ale tak\u00e9 na re\u00e1ln\u00fd v\u00fdznam sv\u00fdch zji\u0161t\u011bn\u00ed, budete na z\u00e1klad\u011b sv\u00fdch dat \u010dinit informovan\u011bj\u0161\u00ed a smyslupln\u011bj\u0161\u00ed rozhodnut\u00ed.<\/p>\n\n\n\n

Z\u00e1v\u011brem lze \u0159\u00edci, \u017ee nulov\u00e1 hypot\u00e9za slou\u017e\u00ed jako z\u00e1kladn\u00ed prvek statistick\u00e9ho testov\u00e1n\u00ed a poskytuje objektivn\u00ed v\u00fdchoz\u00ed bod pro anal\u00fdzu, zda jsou pozorovan\u00e9 \u00fa\u010dinky skute\u010dn\u00e9, nebo zda jsou zp\u016fsobeny n\u00e1hodou. Pe\u010dliv\u00fdm stanoven\u00edm hladiny v\u00fdznamnosti lze vyv\u00e1\u017eit riziko chyb typu I a typu II, co\u017e zajist\u00ed spolehliv\u011bj\u0161\u00ed v\u00fdsledky. <\/p>\n\n\n\n

Aplikace nulov\u00e9 hypot\u00e9zy na ka\u017edodenn\u00ed sc\u00e9n\u00e1\u0159e v\u00e1m pom\u016f\u017ee pochopit jej\u00ed praktickou hodnotu, p\u0159i\u010dem\u017e se vyhnete b\u011b\u017en\u00fdm chybn\u00fdm p\u0159edstav\u00e1m a zam\u011b\u0159\u00edte se na statistickou i praktickou v\u00fdznamnost, aby va\u0161e z\u00e1v\u011bry byly smyslupln\u00e9. <\/p>\n\n\n\n

Pochopen\u00ed t\u011bchto koncept\u016f v\u00e1m umo\u017en\u00ed p\u0159ij\u00edmat rozhodnut\u00ed zalo\u017een\u00e1 na datech s v\u011bt\u0161\u00ed jistotou.<\/p>\n\n\n\n

P\u0159e\u010dt\u011bte si tak\u00e9: <\/strong>Jak napsat hypot\u00e9zu<\/strong><\/a><\/p>\n\n\n\n

Velk\u00fd dopad a v\u011bt\u0161\u00ed viditelnost va\u0161\u00ed pr\u00e1ce<\/h2>\n\n\n\n

Pochopen\u00ed v\u00fdznamnosti nulov\u00e9 hypot\u00e9zy je z\u00e1sadn\u00ed, ale efektivn\u00ed sd\u011blen\u00ed va\u0161ich zji\u0161t\u011bn\u00ed m\u016f\u017ee m\u00edt z\u00e1sadn\u00ed v\u00fdznam. Mind the Graph<\/a> poskytuje v\u00fdzkumn\u00fdm pracovn\u00edk\u016fm n\u00e1stroje pro vytv\u00e1\u0159en\u00ed vizu\u00e1ln\u011b poutav\u00fdch infografik a diagram\u016f, kter\u00e9 usnad\u0148uj\u00ed pochopen\u00ed slo\u017eit\u00fdch statistick\u00fdch koncept\u016f. A\u0165 u\u017e jde o akademick\u00e9 prezentace, v\u00fdzkumn\u00e9 pr\u00e1ce nebo pr\u00e1ci s ve\u0159ejnost\u00ed, na\u0161e platforma v\u00e1m pom\u016f\u017ee sd\u00edlet va\u0161e poznatky srozumiteln\u011b a p\u016fsobiv\u011b. Za\u010dn\u011bte p\u0159ev\u00e1d\u011bt sv\u00e1 data do vizu\u00e1ln\u00ed podoby je\u0161t\u011b dnes.<\/p>\n\n\n\n

\""Animovan\u00fd<\/a>
Animovan\u00fd GIF p\u0159edstavuj\u00edc\u00ed \u0161irokou \u0161k\u00e1lu v\u011bdeck\u00fdch obor\u016f, kter\u00e9 pokr\u00fdv\u00e1 Mind the Graph<\/a>.<\/figcaption><\/figure>\n\n\n\n
\n
Zviditeln\u011bte svou pr\u00e1ci<\/strong><\/a><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

Seznamte se s v\u00fdznamnost\u00ed nulov\u00e9 hypot\u00e9zy, jej\u00ed \u00falohou ve v\u00fdzkumu a jej\u00edm vlivem na statistick\u00e1 zji\u0161t\u011bn\u00ed.<\/p>","protected":false},"author":33,"featured_media":55854,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[961,982],"tags":[],"yoast_head":"\nUnderstanding Null Hypothesis Significance in Statistical Testing - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Learn about null hypothesis significance, its role in research, and how it impacts statistical findings.\" \/>\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\/cs\/null-hypothesis-significance\/\" \/>\n<meta property=\"og:locale\" content=\"cs_CZ\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Understanding Null Hypothesis Significance in Statistical Testing - 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