The need for Bayesian hypothesis testing in psychological science

This chapter explains why the logic behind p‐value significance tests is faulty, leading researchers to mistakenly believe that their results are diagnostic when they are not. It outlines a Bayesian alternative that overcomes the flaws of the p‐value procedure, and provides researchers with an honest assessment of the evidence against or in favor of the null hypothesis. The p‐value is the probability of encountering the value of a test statistic at least as extreme as the one that was observed, given that the null hypothesis is true. The logic that underlies the p‐value as a measure of evidence is based on what is known as Fisher's disjunction. The chapter focuses on an inherent weakness of p‐value: the fact that they depend only on what is expected under the null hypothesis H ₀, what is expected under an alternative hypothesis H ₁ is simply not taken into consideration.