Most neuroscientists would agree that for brain research to progress, we have to know which
experimental manipulations have no effect as much as we must identify those that do have …

Previous surveys of the literature have shown that reports of statistical analyses often lack
important information, causing lack of transparency and failure of reproducibility. Editors and …

Bayesian parameter estimation and Bayesian hypothesis testing present attractive
alternatives to classical inference using confidence intervals and p values. In part I of this …

Analysis of variance (ANOVA) is the standard procedure for statistical inference in factorial
designs. Typically, ANOVAs are executed using frequentist statistics, where p-values …

This article explains the foundational concepts of Bayesian data analysis using virtually no
mathematical notation. Bayesian ideas already match your intuitions from everyday …

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor
in reporting experimental results, particularly as a recommendation for articles in the Journal …

Bayesian inference has become a standard method of analysis in many fields of science.
Students and researchers in experimental psychology and cognitive science, however, have …

Statistical procedures such as Bayes factor model selection and Bayesian model averaging
require the computation of normalizing constants (eg, marginal likelihoods). These …

We illustrate the Bayesian approach to data analysis using the newly developed statistical
software program JASP. With JASP, researchers are able to take advantage of the benefits …

Bayes factors have been advocated as superior to p-values for assessing statistical
evidence in data. Despite the advantages of Bayes factors and the drawbacks of p-values …