{"id":15301,"date":"2020-03-15T16:19:25","date_gmt":"2020-03-15T15:19:25","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?post_type=dt_lessons&#038;p=15301"},"modified":"2020-03-15T16:19:25","modified_gmt":"2020-03-15T15:19:25","slug":"formule-du-test-t-pour-echantillon-unique","status":"publish","type":"dt_lessons","link":"https:\/\/www.datanovia.com\/en\/fr\/lessons\/formule-du-test-t\/formule-du-test-t-pour-echantillon-unique\/","title":{"rendered":"Formule du Test-T pour Echantillon Unique"},"content":{"rendered":"<div id=\"rdoc\">\n<p>Le pr\u00e9sent article d\u00e9crit la <strong>formule du test t pour \u00e9chantillon unique<\/strong>, qui est utilis\u00e9e pour comparer la moyenne d\u2019un \u00e9chantillon \u00e0 une moyenne standard connue. C\u2019est ce qu\u2019on appelle aussi:<\/p>\n<ul>\n<li><em>formule du test t pour \u00e9chantillon unique<\/em> et<\/li>\n<li><em>\u00e9quation du test t pour \u00e9chantillon unique<\/em><\/li>\n<\/ul>\n<p>Sommaire:<\/p>\n<div id=\"TOC\">\n<ul>\n<li><a href=\"#formule\">Formule<\/a><\/li>\n<li><a href=\"#article-apparent\u00e9\">Article apparent\u00e9<\/a><\/li>\n<\/ul>\n<\/div>\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=\"formule\" class=\"section level2\">\n<h2>Formule<\/h2>\n<p>La formule du test t \u00e0 \u00e9chantillon unique peut s\u2019\u00e9crire comme suit:<\/p>\n<p><span class=\"math display\">\\[<br \/>\nt = \\frac{m-\\mu}{s\/\\sqrt{n}}<br \/>\n\\]<\/span><\/p>\n<p>o\u00f9,<\/p>\n<ul>\n<li><span class=\"math inline\">\\(m\\)<\/span> est la moyenne de l\u2019\u00e9chantillon<\/li>\n<li><span class=\"math inline\">\\(n\\)<\/span> est la taille de l\u2019\u00e9chantillon<\/li>\n<li><span class=\"math inline\">\\(s\\)<\/span> est l\u2019\u00e9cart-type de l\u2019\u00e9chantillon avec les degr\u00e9s de libert\u00e9 <span class=\"math inline\">\\(n-1\\)<\/span><\/li>\n<li><span class=\"math inline\">\\(\\mu\\)<\/span> est la moyenne th\u00e9orique<\/li>\n<\/ul>\n<p>La p-value, correspondant \u00e0 la valeur absolue des statistiques du test t (|t|), est calcul\u00e9e pour les degr\u00e9s de libert\u00e9 (df): <code>df = n - 1<\/code>.<\/p>\n<p><strong>Comment interpr\u00e9ter les r\u00e9sultats du test t \u00e0 \u00e9chantillon unique ?<\/strong><\/p>\n<div class=\"success\">\n<p>Si la p-value est inf\u00e9rieure ou \u00e9gale au seuil de significativit\u00e9 0,05, nous pouvons rejeter l\u2019hypoth\u00e8se nulle et accepter l\u2019hypoth\u00e8se alternative. En d\u2019autres termes, nous concluons que la moyenne de l\u2019\u00e9chantillon est significativement diff\u00e9rente de la moyenne th\u00e9orique.<\/p>\n<\/div>\n<\/div>\n<div id=\"article-apparent\u00e9\" class=\"section level2\">\n<h2>Article apparent\u00e9<\/h2>\n<p><a href=\"https:\/\/www.datanovia.com\/en\/fr\/lessons\/test-t-dans-r\/\">Test t dans R<\/a><\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>D\u00e9crit la formule du test t pour \u00e9chantillon unique, qui est utilis\u00e9e pour comparer la moyenne d&rsquo;un \u00e9chantillon \u00e0 une moyenne standard connue. <\/p>\n","protected":false},"author":1,"featured_media":15302,"parent":15299,"menu_order":75,"comment_status":"open","ping_status":"closed","template":"","class_list":["post-15301","dt_lessons","type-dt_lessons","status-publish","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Formule du Test-T pour Echantillon Unique: Excellente R\u00e9f\u00e9rence \u00e0 Lire - 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