There are numerous instances of misunderstanding, misinterpreting, and misusing p-values, which have raised concerns about the reliability of statistical conclusions based on them. This paper provides a comprehensive reevaluation of the mathematical foundations of the p-value, discusses common misconceptions in its teaching and application, and explores alternatives such as confidence intervals, effect size, and Bayes’ factor. Additionally, it highlights scenarios where the p-value remains valuable beyond hypothesis testing. The goal is to emphasize the continued relevance of the p-value while acknowledging potential pitfalls in its misuse. Given that most of the discussion is rooted in applied statistics, this paper aims to offer clarity to researchers across various disciplines.
Avdovic et al. (Wed,) studied this question.