Combine Statistical Thinking With Open Scientific Practice: A Protocol of a Bayesian Research Project

TL;DR

This paper presents a holistic Bayesian research project designed to teach undergraduate psychology students about Bayesian inference, empirical data analysis, and open science practices through hands-on experience with real data.

Contribution

It introduces a structured protocol integrating statistical thinking, open scientific practice, and Bayesian methods in undergraduate education.

Findings

Students gained practical understanding of Bayesian inference.

Students experienced the full empirical cycle from data collection to interpretation.

The project demonstrated effective integration of open science practices.

Abstract

Current developments in the statistics community suggest that modern statistics education should be structured holistically, that is, by allowing students to work with real data and to answer concrete statistical questions, but also by educating them about alternative frameworks, such as Bayesian inference. In this article, we describe how we incorporated such a holistic structure in a Bayesian research project on ordered binomial probabilities. The project was conducted with a group of three undergraduate psychology students who had basic knowledge of Bayesian statistics and programming, but lacked formal mathematical training. The research project aimed to (1) convey the basic mathematical concepts of Bayesian inference; (2) have students experience the entire empirical cycle including collection, analysis, and interpretation of data and (3) teach students open science practices.