Seminar 20th April 2015 10 a.m. Building 2, Room 1083, Highfield Campus, University of Southampton
Bayesian Analyses with JASP: A Fresh Way to do Statistics
Prof Eric-Jan Wagenmakers
University of Amsterdam
- Web page
- http://www.ejwagenmakers.com/
- Submitter
- Luke Goater
The Schools of Psychology, Economics, and Mathematical Sciences, and the Southampton Statistical Sciences Research Institute are proud to present the second lecture of the “Modeling Our World” speaker series. These talks are specifically intended to foster interest and collaboration among the different disciplines, and all are invited to attend. As indicated below, this particular talk, which will be given by Prof. Eric-Jan Wagenmakers, should be of interest to anyone interested in behavioral research, statistics, and Bayesian methods.
Bayesian hypothesis testing presents an attractive alternative to p-value hypothesis testing. The most prominent advantages of Bayesian hypothesis testing include (1) ability to quantify evidence in favor of the null hypothesis; (2) ability to quantify evidence in favor of the alternative hypothesis; and (3) ability to monitor and update evidence as the data come in. Despite these practical advantages, Bayesian hypothesis testing is still relatively rare. An important impediment to the widespread use of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. Here we introduce JASP http://jasp-stats.org, an open-source, cross platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in large part on the Bayesian analyses implemented in Morey and Rouder's powerful BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian inference are only a mouse click away.