When significant is not significant: Six clinical examples that disprove common wrong beliefs about statistical testing

Abstract

Since the original formulation by Sir Ronald Fisher in the early 1920s, the concept of statistical significance has been subject to serious misinterpretations. Despite more than 100 years having passed, these criticalities remain as vivid today as they were back then, if not more so. Given that the misuse of statistical testing in public health can lead to highly dangerous outcomes such as the approval of ineffective treatments or the rejection of effective ones, in this brief letter, we present a series of examples aimed at definitively dispelling some of the most common and erroneous beliefs about statistical significance.