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

Area of Science:

• Psychology
• Statistics
• Computational Statistics

Background:

• Traditional p-value hypothesis testing is widely used but has limitations.
• Bayesian hypothesis testing offers advantages like quantifying evidence and updating it with new data.
• Widespread adoption of Bayesian methods is hindered by a lack of accessible software for common statistical analyses.

Purpose of the Study:

• Introduce JASP, a user-friendly graphical software package for Bayesian hypothesis testing.
• Provide psychologists with an accessible tool for common statistical problems like t-tests, ANOVA, correlation, regression, and contingency tables.
• Facilitate the practical application of Bayesian hypothesis testing in psychological research.

Main Methods:

• Introduction of JASP, an open-source, cross-platform graphical software.
• JASP implements Bayesian analyses based on Morey and Rouder's BayesFactor package for R.
• The software allows users to perform Bayesian hypothesis tests with a simple graphical interface.

Main Results:

• JASP provides a user-friendly interface for conducting Bayesian hypothesis tests.
• The software supports standard statistical analyses frequently used in psychology.
• Bayesian hypothesis testing is made easily accessible through JASP's point-and-click functionality.

Conclusions:

• JASP significantly lowers the barrier to entry for Bayesian hypothesis testing in psychology.
• The software empowers researchers to leverage the benefits of Bayesian methods for their experiments.
• JASP makes the practical advantages of Bayesian hypothesis testing readily available to a wider audience.