We therefore require an alternative approach while conducting multiple tests that will account for an increased probability of discovering a significant effect through repeated trials. The Bonferroni correction is a very simple adjustment that ensures we are unlikely to make Type I errors. It does this by adjusting the alpha for our tests.
The adjustment is a simple one—the Bonferroni correction simply divides our desired alpha by the number of tests we are performing. For example, if we had k site designs to test and an experimental alpha of 0.05, the Bonferroni correction is expressed as:
This is a safe way to mitigate the increased probability of making a Type I error in multiple testing. The following example is identical to ex-2-22, except the alpha value has been divided by the number of groups:
(defn ex-2-23 []
(let [data (->> (load-data "multiple-sites.tsv")
(:rows)
(group-by :site)
(map-vals (partial...
