Bayesian inference for psychology. Part II: Example applications with JASP

• DOI: 10.3758/s13423-017-1323-7
• Publication Date: 2017-07-06T18:32:57Z
• Authors: Eric-Jan Wagenmakers; Jonathon Love; Maarten Marsman; Tahira Jamil; Alexander Ly; Josine Verhagen; Ravi Selker; Quentin F. Gronau; Damian Dropmann; Bruno Boutin; Frans Meerhoff; Patrick Knight; Akash Raj; Erik-Jan van Kest...; Johnny van Doorn; Martin Šmíra; Sacha Epskamp; Alexander Etz; Dora Matzke; Tim de Jong; Don van den Bergh; Alexandra Sarafoglou; Helen Steingroever; Koen Derks; Jeffrey N. Rouder; Richard D. Morey
• Keywords: 03 medical and health sciences; 0302 clinical medicine; 330; Research Design; Brief Report; Humans; Psychology; Bayes Theorem; Software

Bayesian hypothesis testing presents an attractive alternative to p value testing. Part I of this series outlined several advantages testing, including the ability quantify evidence and monitor update as data come in, without need know intention with which were collected. Despite these other practical advantages, tests are still reported relatively rarely. An important impediment widespread adoption is arguably lack user-friendly software for run-of-the-mill statistical problems that confront psychologists analysis almost every experiment: t-test, ANOVA, correlation, regression, contingency tables. In II we introduce JASP ( http://www.jasp-stats.org ), open-source, cross-platform, graphical package allows users carry out standard problems. based in part on analyses implemented Morey Rouder's BayesFactor R. Armed JASP, only a mouse click away.