When to p and when not to p

Abstract

AbstractThe p‐value was proposed in the early 20th century as a potentially useful metric for statistical inference and was defined as “the probability of the observed result, plus more extreme results, if the null hypothesis were true,” in the context of a formal statistical testing process. A century later, the scientific community uses it extensively, mostly inappropriately, and often interprets it incorrectly. This editorial briefly reviews the history of the p‐value, provides how to properly interpret it, and recommends when to use it and when not to use it.