{"id":11043,"date":"2019-12-07T23:44:44","date_gmt":"2019-12-07T21:44:44","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?post_type=dt_courses&#038;p=11043"},"modified":"2019-12-07T23:44:44","modified_gmt":"2019-12-07T21:44:44","slug":"tests-statistiques-et-hypotheses","status":"publish","type":"dt_courses","link":"https:\/\/www.datanovia.com\/en\/fr\/courses\/tests-statistiques-et-hypotheses\/","title":{"rendered":"Tests Statistiques et Hypoth\u00e8ses"},"content":{"rendered":"<div id=\"rdoc\">\n<h2>Description du cours<\/h2>\n<p>Dans ce chapitre, nous pr\u00e9senterons quelques questions de recherche et les <strong>tests statistiques<\/strong> correspondants, ainsi que les <strong>hypoth\u00e8ses<\/strong> des tests.<\/p>\n<p>Sommaire:<\/p>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div class='dt-sc-ico-content type1'><div class='custom-icon' ><a href='https:\/\/www.datanovia.com\/en\/fr\/produit\/pratiques-des-statistiques-dans-r-pour-comparaison-de-groupes-variables-numeriques\/' target='_blank'><span class='fa fa-book'><\/span><\/a><\/div><h4><a href='https:\/\/www.datanovia.com\/en\/fr\/produit\/pratiques-des-statistiques-dans-r-pour-comparaison-de-groupes-variables-numeriques\/' target='_blank'> Livre Apparent\u00e9 <\/a><\/h4>Pratique des Statistiques dans R II - Comparaison de Groupes: Variables Num\u00e9riques<\/div>\n<div class='dt-sc-hr-invisible-medium  '><\/div>\n<div id=\"questions-de-recherche-et-statistiques\" class=\"section level2\">\n<h2>Questions de recherche et statistiques<\/h2>\n<p>Les questions de recherche les plus populaires sont les suivantes:<\/p>\n<ol style=\"list-style-type: decimal;\">\n<li>est-ce que <strong>deux variables<\/strong> (n = 2) sont <strong>corr\u00e9l\u00e9es<\/strong> (c.-\u00e0-d. associ\u00e9es)?<\/li>\n<li>est-ce que <strong>plusieurs variables<\/strong> (n &gt; 2) sont <strong>corr\u00e9l\u00e9es<\/strong>?<\/li>\n<li>est-ce que <strong>deux groupes<\/strong> (n = 2) d\u2019\u00e9chantillons <strong>diff\u00e9rent<\/strong> les uns des autres?<\/li>\n<li>est-ce que <strong>plusieurs groupes<\/strong> (n &gt;= 2) d\u2019\u00e9chantillons <strong>diff\u00e9renci\u00e9s<\/strong> les uns des autres?<\/li>\n<li>est-ce que la <strong>variabilit\u00e9<\/strong> de deux \u00e9chantillons ou plus diff\u00e8re?<\/li>\n<\/ol>\n<p>On peut r\u00e9pondre \u00e0 chacune de ces questions \u00e0 l\u2019aide des tests statistiques suivants:<\/p>\n<ol style=\"list-style-type: decimal;\">\n<li><strong>Test de corr\u00e9lation<\/strong> entre deux variables<\/li>\n<li><strong>Matrice de corr\u00e9lation<\/strong> entre plusieurs variables<\/li>\n<li><strong>Comparaison des moyennes de deux groupes<\/strong>:\n<ul>\n<li><strong>Test t de Student<\/strong> (param\u00e9trique)<\/li>\n<li><strong>Test de Wilcoxon<\/strong> (non param\u00e9trique)<\/li>\n<\/ul>\n<\/li>\n<li><strong>Comparaison des moyennes de plus de deux groupes<\/strong>\n<ul>\n<li><strong>Test ANOVA<\/strong> (analyse de variance, param\u00e9trique) : extension du test t pour comparer plus de deux groupes.<\/li>\n<li><strong>Test de Kruskal-Wallis<\/strong> (non param\u00e9trique) : extension du test de Wilcoxon pour comparer plus de deux groupes<\/li>\n<\/ul>\n<\/li>\n<li><strong>Comparaison des variances<\/strong>:\n<ul>\n<li>Comparaison des variances de deux groupes : <strong>Test F<\/strong> (param\u00e9trique)<\/li>\n<li>Comparaison des variances de plus de deux groupes : <strong>Test de Bartlett<\/strong> (param\u00e9trique), <strong>Test de Levene<\/strong> (param\u00e9trique) et <strong>Test de Fligner-Killeen<\/strong> (non-param\u00e9trique)<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<\/div>\n<div id=\"hypotheses-des-tests-statistiques\" class=\"section level2\">\n<h2>Hypoth\u00e8ses des tests statistiques<\/h2>\n<p>Bon nombre des m\u00e9thodes statistiques, notamment la corr\u00e9lation, la r\u00e9gression, le test t et l\u2019analyse de la variance, supposent certaines caract\u00e9ristiques des donn\u00e9es. En g\u00e9n\u00e9ral, ils supposent que:<\/p>\n<ul>\n<li>les donn\u00e9es suivent une <strong>distribution normale<\/strong><\/li>\n<li>et les <strong>variances<\/strong> des groupes \u00e0 comparer sont <strong>homog\u00e8nes<\/strong> (\u00e9gales).<\/li>\n<\/ul>\n<p>Ces hypoth\u00e8ses doivent \u00eatre prises au s\u00e9rieux pour tirer une interpr\u00e9tation et des conclusions fiables de la recherche.<\/p>\n<p>Ces tests - corr\u00e9lation, t-test et ANOVA - sont appel\u00e9s <strong>tests param\u00e9triques<\/strong>, car leur validit\u00e9 d\u00e9pend de la distribution des donn\u00e9es.<\/p>\n<p>Avant d\u2019utiliser les tests param\u00e9triques, certains tests pr\u00e9liminaires doivent \u00eatre effectu\u00e9s pour s\u2019assurer que les hypoth\u00e8ses de test sont respect\u00e9es. Dans les cas o\u00f9 les hypoth\u00e8ses ne sont pas respect\u00e9es, il est recommand\u00e9 d\u2019utiliser des tests <strong>non param\u00e9triques<\/strong>.<\/p>\n<\/div>\n<div id=\"evaluer-la-normalite\" class=\"section level2\">\n<h2>\u00c9valuer la normalit\u00e9<\/h2>\n<ol style=\"list-style-type: decimal;\">\n<li>Avec <strong>des \u00e9chantillons suffisamment grands<\/strong> (n &gt; 30), la violation de l\u2019hypoth\u00e8se de normalit\u00e9 ne devrait pas poser de probl\u00e8mes majeurs (th\u00e9or\u00e8me central limite). Cela implique que nous pouvons ignorer la distribution des donn\u00e9es et utiliser des tests param\u00e9triques.<\/li>\n<li>Cependant, par souci de logique, nous pouvons utiliser le <strong>test statistique de Shapiro-Wilk<\/strong> comparant la distribution de l\u2019\u00e9chantillon \u00e0 une distribution normale afin de d\u00e9terminer si les donn\u00e9es montrent ou non un \u00e9cart important par rapport \u00e0 la disribution normale <span class=\"citation\">(Ghasemi and Zahediasl 2012)<\/span>.<\/li>\n<\/ol>\n<\/div>\n<div id=\"evaluer-legalite-des-variances\" class=\"section level2\">\n<h2>\u00c9valuer l\u2019\u00e9galit\u00e9 des variances<\/h2>\n<p>Le <strong>test t standard de Student<\/strong> (comparaison de deux \u00e9chantillons ind\u00e9pendants) et le test ANOVA (comparaison de plusieurs \u00e9chantillons) supposent \u00e9galement que les \u00e9chantillons \u00e0 comparer ont des variances \u00e9gales.<\/p>\n<p>Si les \u00e9chantillons, \u00e0 comparer, suivent une distribution normale, alors il est possible d\u2019utiliser:<\/p>\n<ul>\n<li><strong>Test F<\/strong> pour comparer les variances de deux \u00e9chantillons<\/li>\n<li><strong>Test de Bartlett<\/strong> ou <strong>Test de Levene<\/strong> pour comparer les variances de plusieurs \u00e9chantillons.<\/li>\n<\/ul>\n<\/div>\n<div id=\"resume\" class=\"section level2\">\n<h2>R\u00e9sum\u00e9<\/h2>\n<p>Ce chapitre pr\u00e9sente les tests statistiques les plus couramment utilis\u00e9s et leurs hypoth\u00e8ses.<\/p>\n<\/div>\n<div id=\"references\" class=\"section level2 unnumbered\">\n<h2>References<\/h2>\n<div id=\"refs\" class=\"references\">\n<div id=\"ref-ghasemi2012\">\n<p>Ghasemi, Asghar, and Saleh Zahediasl. 2012. \u201cNormality Tests for Statistical Analysis: A Guide for Non-Statisticians.\u201d <em>Int J Endocrinol Metab<\/em> 10 (2): 486\u201389. doi:<a href=\"https:\/\/doi.org\/10.5812\/ijem.3505\">10.5812\/ijem.3505<\/a>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><!--end rdoc--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dans ce cours, nous pr\u00e9senterons quelques questions de recherche et les tests statistiques correspondants, ainsi que les hypoth\u00e8ses des tests.<\/p>\n","protected":false},"author":1,"featured_media":10348,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","class_list":["post-11043","dt_courses","type-dt_courses","status-publish","has-post-thumbnail","hentry","course_category-biostatistique","course_category-comparaison-de-moyennes","course_category-statistiques-de-base"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - 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