Journal of Data Science

Abstract: Frequentist Null Hypothesis Significance Testing (NHST) is so an integral part of scientists’ behavior that its uses cannot be discontinued by flinging it out of the window. Faced with this situation, the suggested strategy for training students and researchers in statistical inference methods for experimental data analysis involves a smooth transition towards the Bayesian paradigm. Its general outlines are as follows. (1) To present natural Bayesian interpretations of NHST outcomes to draw attention to their shortcomings. (2) To create as a result of this the need for a change of emphasis in the presentation and interpretation of results. (3) Finally to equip users with a real possibility of thinking sensibly about statistical inference problems and behaving in a more reasonable manner. The conclusion is that teaching the Bayesian approach in the context of experimental data analysis appears both desirable and feasible. This feasibility is illustrated for analysis of variance methods.