reading time: 5-10 min. Cohen’s d is a widely known and extensively used measure of effect size. That is, d is used to gauge how strong an effect is (given the fact that the effect exists). For example, one way to estimate d is as follows: data(tips, package = "reshape2") library(compute.es) t1 <- t.test(tip ~ sex, data = tips) t1$statistic ## t ## -1.489536 table(tips$sex) ## ## Female Male ## 87 157 tes(t1$statistic, 87, 157) ## Mean Differences ES: ## ## d [ 95 %CI] = …