>[!abstract] >Statistical hypothesis testing is based on rejecting the null hypothesis when the likelihood of the observed data would be low if the null hypothesis were true. If multiple hypotheses are tested, the probability of observing a rare event increases, and therefore, the likelihood of incorrectly rejecting a null hypothesis (i.e., making a Type I error) increases. > >The Bonferroni correction compensates for that increase by testing each individual hypothesis at a significance level of $\alpha / m$, where $\alpha$ is the desired overall alpha level and $m$ is the number of hypotheses. For example, if a trial is testing $m = 20$ hypotheses with a desired overall $\alpha = 0.05$, then the Bonferroni correction would test each individual hypothesis at $\alpha = 0.05 / 20 = 0.0025$. (Wikipedia, 2025). >[!related] >- **North** (upstream): — >- **West** (similar): — >- **East** (different): [[Data dredging]] >- **South** (downstream): —