Most empirical research continues to be reported in terms of classical test statistics such as t or F, and their associated p-values. The evidentiary content of p-values (small values of p are supposed to be decisive for rejecting a null hypothesis) has been severely questioned by Bayesian theorists, and for good reason. It turns out however that an examination of the distribution of p-values under typical alternate hypotheses links p-values to Bayes factors. A typical ANOVA can thus be reported in terms of F values together with associated Bayes factors. Until our empirical colleagues commit to a fully Bayesian analysis of their data, they can in the interim quickly learn to compute Bayes factors to assist in the analysis and interpretation of their data. |