Year: 2026
Type: preprint
Abstract: We present an interactive classroom activity designed to address a central challenge in teaching introductory Bayesian statistics: how to formalize subjective knowledge and available information into prior distributions and then update them with empirical data. Role-playing as data analysts for a racing team, students evaluate candidate tires by converting qualitative engineering reports into prior distributions, collecting primary data via a virtual racing game, and using a Beta-Binomial model to inform team strategy. This discovery-based exercise allows small groups to observe directly how different prior choices and sample data jointly shape posterior inference. Student feedback ($n=32$) highlights high enjoyment, engagement and improved conceptual clarity. Open-access materials to implement the activity are provided, alongside recommendations for adapting it to other teaching contexts.
Source: arXiv (Cornell University)
Authors: Ricci, Federica Zoe, Dogucu, Mine
Institutions: Swarthmore College, Harvard University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7213996098