Bayes factor hypothesis tests for ranks and researchers

This dissertation outlines general and specific tools for behavioral research. The first part of this dissertation provides guidelines and reflection on Bayesian inference in general, aimed at familiarizing researchers with the core concepts of the Bayesian framework. Additionally, this part explores the extent to which different researchers can approach a research question, both in simple and complex scenarios. The second part of this dissertation applies the Bayesian philosophy to rank-based tests, in order to combine the benefits of Bayesian inference with the benefits of rank-based tests. This part demonstrates the use of ranks in hypothesis testing, as well as the practical relevance of Kendall's τ in the modeling of psychological data.