Analysis of variance (ANOVA) is the standard procedure for statistical inference in factorial designs. Typically, ANOVAs are executed using frequentist statistics, where p-values determine statistical significance in an all-or-none fashion. In recent years, the Bayesian approach to statistics is increasingly viewed as a legitimate alternative to the p-value. However, the broad adoption of Bayesian statistics-and Bayesian ANOVA in particular-is frustrated by the fact that Bayesian concepts are rarely taught in applied statistics courses. Consequently, practitioners may be unsure how to conduct a Bayesian ANOVA and interpret the results. Here we provide a guide for executing and interpreting a Bayesian ANOVA with JASP, an open-source statistical software program with a graphical user interface. We explain the key concepts of the Bayesian ANOVA using two empirical examples.

Analysis of Variance, Bayes Factor, Hypothesis Test, JASP, Posterior distribution, Tutorial
Annee Psychologique
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands

van den Bergh, D, van Doorn, J, Marsman, M, Draws, T, Kesteren, E.-J, Derks, K, … Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a bayesian ANOVA in JASP Tutoriel pour réaliser et interpréter une analyse de variance bayésienne dans JASP. Annee Psychologique, 120(1), 73–96. doi:10.3917/anpsy1.201.0073