# Introducing Bayesian Analysis with $\text{m&m's}^\circledR$: an active-learning exercise for undergraduates

## TL;DR

This paper introduces an active-learning exercise for undergraduates that uses Bayesian analysis with M&M's to teach statistical concepts, including a graduate-level extension with hierarchical Bayesian methods.

## Contribution

It provides a practical, hands-on teaching activity using Bayesian analysis with M&M's, along with detailed lesson plans and open-source materials, and suggests an advanced extension for graduate students.

## Key findings

- Effective in teaching Bayesian concepts to undergraduates
- Utilizes real-world data from M&M's to illustrate Bayesian analysis
- Includes open-source materials and an extension for graduate-level learning

## Abstract

We present an active-learning strategy for undergraduates that applies Bayesian analysis to candy-covered chocolate $\text{m&m's}^\circledR$. The exercise is best suited for small class sizes and tutorial settings, after students have been introduced to the concepts of Bayesian statistics. The exercise takes advantage of the non-uniform distribution of $\text{m&m's}^\circledR~$ colours, and the difference in distributions made at two different factories. In this paper, we provide the intended learning outcomes, lesson plan and step-by-step guide for instruction, and open-source teaching materials. We also suggest an extension to the exercise for the graduate-level, which incorporates hierarchical Bayesian analysis.