Using JASP to perform a Bayesian paired-sample t-test for the Survey of Attitudes toward Statistics
In the realm of statistical analysis, Bayesian methods offer a powerful alternative to traditional frequentist approaches, providing researchers with robust tools for inference and hypothesis testing. This poster presents a practical application of Bayesian analysis using JASP (Jeffreys's Amazing Statistics Program), an open-source software package designed for intuitive Bayesian analysis. We use the Survey of Attitudes toward Statistics (SATS) data collected from students who enrolled in an Introduction to Statistics course at the University of Minnesota Rochester. Specifically, we focus on the Bayesian paired-sample t-test, a fundamental tool for comparing the means of paired observations. Through a step-by-step guide, we demonstrate how to conduct the Bayesian paired-sample t-test in JASP, including data preparation, specification of prior distributions, model estimation, and interpretation of results. By applying Bayesian principles, we showcase the advantages of incorporating prior knowledge, quantifying uncertainty, and making informed decisions in statistical analysis. This poster serves as a valuable resource for researchers and practitioners seeking to utilize JASP for Bayesian inference in the exploration of attitudes toward statistics and beyond, and aims to encourage researchers to explore and embrace Bayesian alternatives to traditional frequentist tests in their statistical analyses.