{"id":180238,"date":"2022-11-08T16:24:41","date_gmt":"2022-11-08T16:24:41","guid":{"rendered":"https:\/\/datascientest.com\/?p=180238"},"modified":"2023-11-09T13:56:01","modified_gmt":"2023-11-09T13:56:01","slug":"4-types-de-biais-statistique-a-eviter-dans-vos-analyses","status":"publish","type":"post","link":"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses","title":{"rendered":"4 types de biais statistique \u00e0 \u00e9viter dans vos analyses"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"180238\" class=\"elementor elementor-180238\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dbc5d45 e-flex e-con-boxed e-con\" data-id=\"dbc5d45\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9b814e5 elementor-widget elementor-widget-heading\" data-id=\"9b814e5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Le biais statistique peut \u00eatre d\u00e9fini comme tout ce qui conduit \u00e0 une diff\u00e9rence syst\u00e9matique entre les vrais param\u00e8tres d'une population et les statistiques utilis\u00e9es pour estimer ces param\u00e8tres. Il existe une longue liste de types de biais de statistique.<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4fdc0a0 elementor-widget elementor-widget-text-editor\" data-id=\"4fdc0a0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>Nous avons d\u00e9cid\u00e9 de vous pr\u00e9senter ces quatre types, car ce sont ceux que nous voyons le plus affecter le quotidien des <a href=\"https:\/\/datascientest.com\/metier-data-scientist\">Data Scientists<\/a> et <a href=\"https:\/\/datascientest.com\/metier-data-analyst\">Analystes<\/a>.<\/p><p>Nous allons vous les d\u00e9crire et vous en donner un exemple concret.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-cf52cc6 e-flex e-con-boxed e-con\" data-id=\"cf52cc6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-11727bf elementor-widget elementor-widget-heading\" data-id=\"11727bf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">1) Biais de s\u00e9lection<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4dbc65b elementor-widget elementor-widget-text-editor\" data-id=\"4dbc65b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Le biais de s\u00e9lection a lieu lorsque, comme son nom l&rsquo;indique, la s\u00e9lection de donn\u00e9es est fausse. <strong>Cela signifie en g\u00e9n\u00e9ral, que vous travaillez avec un sous-ensemble sp\u00e9cifique de votre groupe et non un sous-ensemble al\u00e9atoire<\/strong>.<\/p><p>Si vous souhaitez par exemple d\u00e9ployer un nouveau produit, avant de d\u00e9penser du temps et de l\u2019argent, il vous faut savoir si votre audience est int\u00e9ress\u00e9e par celui-ci. Vous r\u00e9alisez donc une enqu\u00eate que vous envoyez \u00e0 vos clients existants. C\u2019est bien s\u00fbr une part importante de votre audience, mais elle ne repr\u00e9sente absolument pas l\u2019enti\u00e8ret\u00e9 de votre audience. Vous venez de r\u00e9aliser un biais de s\u00e9lection qui peut vous co\u00fbter tr\u00e8s cher !<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c034d0 elementor-widget elementor-widget-image\" data-id=\"3c034d0\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"425\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-statistique.png\" class=\"attachment-full size-full wp-image-180239\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-statistique.png 800w, https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-statistique-300x159.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-statistique-768x408.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-37f8904 e-flex e-con-boxed e-con\" data-id=\"37f8904\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-750b26f elementor-widget elementor-widget-heading\" data-id=\"750b26f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">2) Biais de rappel\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b9cd93b elementor-widget elementor-widget-text-editor\" data-id=\"b9cd93b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Le biais de rappel est une autre erreur courante dans des situations d\u2019enqu\u00eate, et notamment de feedback. <strong>Il appara\u00eet lorsque les participants ne se souviennent pas d\u2019\u00e9v\u00e8nements, de souvenirs ou de d\u00e9tails ant\u00e9rieurs.<\/strong> La m\u00e9moire humaine \u00e9tant s\u00e9lective par d\u00e9faut, c\u2019est un ph\u00e9nom\u00e8ne normal mais qui rend plus difficile la recherche.<\/p><p>Le cerveau humain a tendance \u00e0 se rappeler davantage des bons souvenirs plut\u00f4t que des mauvais. Si vous r\u00e9alisez une enqu\u00eate \u00e0 la suite d\u2019une conf\u00e9rence par exemple, il est pr\u00e9f\u00e9rable d\u2019envoyer le formulaire rapidement, si vous voulez qu\u2019il soit plus exact.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-558c99a e-flex e-con-boxed e-con\" data-id=\"558c99a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-05b6d7c elementor-widget elementor-widget-heading\" data-id=\"05b6d7c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">3) Biais des survivants<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0e237a1 elementor-widget elementor-widget-text-editor\" data-id=\"0e237a1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Le biais des survivants est une autre forme de biais de s\u00e9lections ou le chercheur se concentre uniquement sur le sous-ensemble du groupe ayant d\u00e9j\u00e0 \u00e9t\u00e9 soumis \u00e0 un processus de pr\u00e9s\u00e9lection.<\/strong><\/p><p>On retrouve de nombreux cas de biais des survivants dans le secteur militaire. On peut citer par exemple le statisticien Abraham Wald qui a \u00e9t\u00e9 consult\u00e9 au cours de la Seconde Guerre mondiale et qui a propos\u00e9 une id\u00e9e allant \u00e0 contre-courant. Il recommande de renforcer les avions revenus de leur missions aux endroits montrant le moins de dommages. En effet, seuls les avions revenus de leur mission ont \u00e9t\u00e9 \u00e9tudi\u00e9.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0860230 elementor-widget elementor-widget-image\" data-id=\"0860230\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"585\" height=\"433\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-des-survivants.png\" class=\"attachment-full size-full wp-image-180248\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-des-survivants.png 585w, https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/biais-des-survivants-300x222.png 300w\" sizes=\"(max-width: 585px) 100vw, 585px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e2e3315 e-flex e-con-boxed e-con\" data-id=\"e2e3315\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-275ab1a elementor-widget elementor-widget-heading\" data-id=\"275ab1a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">4) Biais de variable omise<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b342c13 elementor-widget elementor-widget-text-editor\" data-id=\"b342c13\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Il s\u2019agit d\u2019un biais qui d\u00e9coule de l\u2019absence de variables pertinentes dans un mod\u00e8le. <strong>En <\/strong><a href=\"https:\/\/datascientest.com\/machine-learning-et-voyage\">Machine Learning<\/a><strong>, la suppression de variables pertinentes et\/ou d\u2019un trop grand nombre de variables peut rendre ce mod\u00e8le inutilisable.<\/strong><\/p><p>Un exemple plus concret serait l\u2019achat d\u2019une voiture en fonction de certains crit\u00e8res mais pas d\u2019autres. Par exemple, imaginez une Bentley Continental 2021 \u00e0 20 000 euros, cela semble \u00eatre une affaire en or, jusqu\u2019\u00e0 ce que vous d\u00e9couvriez qu\u2019elle a 600 000 km au compteur.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4c8a113 e-flex e-con-boxed e-con\" data-id=\"4c8a113\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4854888 elementor-widget elementor-widget-text-editor\" data-id=\"4854888\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Nous vous avons dress\u00e9 une liste non exhaustive des principaux biais statistiques que l\u2019on retrouve le plus souvent en <a href=\"https:\/\/datascientest.com\/data-science-prediction-des-prix-de-vente-dans-le-monde-des-montres-de-luxe\">Data Science<\/a> mais aussi dans notre quotidien.<\/p><p>Il nous semble important de conclure sur le fait que <strong>les statistiques biais\u00e9es sont de mauvaises statistiques<\/strong>. Il faut toujours chercher \u00e0 minimiser au maximum les biais. Une technique tr\u00e8s efficace pour \u00e9viter les biais est la randomisation par exemple. Faire en sorte que l\u2019\u00e9chantillon de l\u2019\u00e9tude soit tir\u00e9 au hasard.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-12da8c2 e-flex e-con-boxed e-con\" data-id=\"12da8c2\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e018444 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"e018444\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir nos formations en Data Science<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Le biais statistique peut \u00eatre d\u00e9fini comme tout ce qui conduit \u00e0 une diff\u00e9rence syst\u00e9matique entre les vrais param\u00e8tres d&rsquo;une population et les statistiques utilis\u00e9es pour estimer ces param\u00e8tres. Il existe une longue liste de types de biais de statistique. Nous avons d\u00e9cid\u00e9 de vous pr\u00e9senter ces quatre types, car ce sont ceux que nous [&hellip;]<\/p>\n","protected":false},"author":77,"featured_media":182737,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>4 types de biais statistique \u00e0 \u00e9viter dans vos analyses<\/title>\n<meta name=\"description\" content=\"D\u00e9couvrez dans cet article quatre types de biais statistiques qui peuvent affecter le quotidien des data scientists et analysts.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"4 types de biais statistique \u00e0 \u00e9viter dans vos analyses\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2022-11-08T16:24:41+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-09T13:56:01+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2022\/11\/Illu_BLOG_4_biais-1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"562\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Raphael Kassel\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Raphael Kassel\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses\",\"url\":\"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses\",\"name\":\"4 types de biais statistique \u00e0 \u00e9viter dans vos analyses\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2022-11-08T16:24:41+00:00\",\"dateModified\":\"2023-11-09T13:56:01+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/6eca16f63daaafcbc96e15549b9d4ee1\"},\"description\":\"D\u00e9couvrez dans cet article quatre types de biais statistiques qui peuvent affecter le quotidien des data scientists et analysts.\",\"inLanguage\":\"fr-FR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/datascientest.com\/4-types-de-biais-statistique-a-eviter-dans-vos-analyses\"]}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/datascientest.com\/#website\",\"url\":\"https:\/\/datascientest.com\/\",\"name\":\"Formation Data Science | DataScientest.com\",\"description\":\"Leader de la formation en Data Science\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/datascientest.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"fr-FR\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/6eca16f63daaafcbc96e15549b9d4ee1\",\"name\":\"Raphael Kassel\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"fr-FR\",\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/raph.jpeg\",\"contentUrl\":\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/11\/raph.jpeg\",\"caption\":\"Raphael Kassel\"},\"description\":\"Raphael Kassel est le Head of Data Programs chez DataScientest. 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