Meaningful results for meaningful hypotheses: A tutorial on hypothesis testing with Bayes factors using ROPEs

Recent times have seen an increase of interest in Bayesian inference across the behavioral sciences. However, the process of testing hypotheses is often conceptually challenging or computationally costly. This tutorial provides an accessible, non-technical introduction to a technique that is both conceptually easy to understand and computationally cheap, and that also covers many common scenarios in the experimental sciences: Quantifying the relative evidence for a pair of interval-based hypotheses using Bayes factors through the Savage Dickey approximation.