A tutorial on conducting and interpreting a Bayesian ANOVA in JASP
Number of pages
Sourcel'Année Psychologique, 120, 1, (2020), pp. 73-96
Article / Letter to editor
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SW OZ DCC AI
SubjectCognitive artificial intelligence
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.
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