A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP

By D. van den Bergh, J. V. van Doorn, Maarten Marsman, Tim Draws, Erik-Jan van Kesteren, Koen Derks, F. Dablander, Quentin F. Gronau, Š. Kucharský, Akash Raj and 7 more. L’Année psychologique, 2019

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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. Herewe 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 twoempirical examples.

Subfields: Management Science and Operations Research, Statistics and Probability

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