{"id":1921,"date":"2019-03-25T06:30:54","date_gmt":"2019-03-25T06:30:54","guid":{"rendered":"https:\/\/www.aiproblog.com\/index.php\/2019\/03\/25\/determining-sample-size-in-one-picture\/"},"modified":"2019-03-25T06:30:54","modified_gmt":"2019-03-25T06:30:54","slug":"determining-sample-size-in-one-picture","status":"publish","type":"post","link":"https:\/\/www.aiproblog.com\/index.php\/2019\/03\/25\/determining-sample-size-in-one-picture\/","title":{"rendered":"Determining Sample Size in One Picture"},"content":{"rendered":"

Author: Stephanie Glen<\/p>\n

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Determining sample sizes is a challenging undertaking. For simplicity, I’ve limited this picture to the one of the most common testing situation: testing for differences in means<\/a><\/strong>. Some assumptions have been made (for example, normality<\/a>\u00a0and equal sample sizes). Additionally, the formulas shown are for one-tailed tests<\/a>. Usually, a small tweak (e.g. replacing Z\u03b1<\/sub> by Z\u03b1<\/sub>\/2) is all that’s required for two-tailed tests.<\/p>\n

<\/a><\/p>\n

Click on the picture to zoom in<\/em><\/p>\n

The picture shows the traditional (frequentist) route for determining sample size. Another possible route is to use Bayesian methods. Although becoming more popular, none of the major software programs include those methods and–unlike the frequentist<\/a>\u00a0route\u2014no standard Bayesian methods exist for determining sample size. If you’re interested in Bayesian<\/a>\u00a0methods, refer to Chapter 13 in Chow, et al, 2008.<\/p>\n

Further Information:<\/h2>\n