{"id":4739,"date":"2014-08-22T16:07:08","date_gmt":"2014-08-22T20:07:08","guid":{"rendered":"http:\/\/www.decisionsciencenews.com\/?p=4739"},"modified":"2014-08-23T13:11:51","modified_gmt":"2014-08-23T17:11:51","slug":"effect-size-s","status":"publish","type":"post","link":"https:\/\/www.decisionsciencenews.com\/?p=4739","title":{"rendered":"It’s the effect size"},"content":{"rendered":"

HOT COHEN’S D EFFECT SIZE VISUALIZER<\/p>\n

\"coh\"<\/a>
\nVisualization by Kristoffer Magnusson<\/a> (@RPsychologist)<\/p>\n

Social science research puts the p-value on a pedestal. The p value, or probability of the data given the null hypothesis is true, is seen as the gateway to publication, giving authors an incentive to “p hack<\/a>“, or use various tricks <\/a>to get p-values down below .05. And they do this despite the lord loving the .06 as much as the .05<\/a>. We have written<\/a> on this before:<\/p>\n

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Cartoon by Decision Science News<\/p>\n

One gripe with the p-value is that statistical significance is cheap. Most plausible hypotheses become statistically significant when the sample size is large enough. Among other things, statistical significance is a function of sample size. In the age of mTurk-scale <\/a>data, attaining statistical significance is easier than ever. We have heard it said that that if you draw a line anywhere through the belly of the United States, you’ll find a significant different in height on opposite sides of the line because of the massive sample size. But it may be a puny difference.<\/p>\n

Enter the concept of effect size. Effect size gives one a way to think about the magnitude of effects, not just the probability of the data given the null hypothesis (aka, the p-value). One popular measure of effect size, Cohen’s D, is discussed along with in the beautiful visualization pictured above<\/a>. Learn more from the article It’s The Effect Size, Stupid<\/a>, from which this post gets its name. And learn why you need lots of data to estimate effect sizes<\/a> from our friends at Data Colada.<\/p>\n","protected":false},"excerpt":{"rendered":"

Enter the concept of effect size. Effect size gives one a way to think about how large an effect (e.g. a height difference) is, not just the probability of the data given the null hypothesis.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[4,16],"tags":[919,922,920,361,52,386,222,208,60,917,36,59,916,70,918,921],"class_list":["post-4739","post","type-post","status-publish","format-standard","hentry","category-encyclopedia","category-ideas","tag-cohens","tag-colada","tag-d","tag-data","tag-decision","tag-effect","tag-gelman","tag-goldstein","tag-news","tag-p","tag-psychology","tag-science","tag-size","tag-statistics","tag-value","tag-visualizer"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4LKj-1er","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4739","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4739"}],"version-history":[{"count":7,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4739\/revisions"}],"predecessor-version":[{"id":4747,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=\/wp\/v2\/posts\/4739\/revisions\/4747"}],"wp:attachment":[{"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4739"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4739"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.decisionsciencenews.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4739"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}