Teaching Bayesian Modeling to Beginners: A Case Study Using Educational Data

Ranadeep Daw, Subhash Bagui

Abstract: This study presents a case-based approach to teaching Bayesian statistical modeling to an undergraduate student with no prior exposure within a single semester. The project applied a Beta-binomial model to estimate population proportions using educational data related to student accommodation needs. A comparison between frequentist and Bayesian approaches demonstrated that Bayesian estimates produced narrower interval widths and incorporated prior information effectively. The instructional design combined guided theory with hands-on application, enabling the student to complete a full data analysis cycle, including modeling, interpretation, and presentation. The results suggest that project-based Bayesian instruction is feasible at the undergraduate level and can improve conceptual understanding of uncertainty and inference. This approach provides a practical framework for integrating Bayesian methods into statistics curricula.

Keywords: Bayesian inference, Beta-binomial model, statistics education, undergraduate pedagogy, proportion estimation, empirical Bayes, credible intervals

How to Cite?: Ranadeep Daw, Subhash Bagui, "Teaching Bayesian Modeling to Beginners: A Case Study Using Educational Data", Volume 15 Issue 5, May 2026, International Journal of Science and Research (IJSR), Pages: 193-198, https://www.ijsr.net/getabstract.php?paperid=SR26502014614, DOI: https://dx.doi.org/10.21275/SR26502014614

Download Citation: APA | MLA | BibTeX | EndNote | RefMan