Introducing Bayesian Analysis with m&m's^: an active-learning exercise for undergraduates

by   Gwendolyn Eadie, et al.
University of Washington

We present an active-learning strategy for undergraduates that applies Bayesian analysis to candy-covered chocolate m&m's^. 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 m&m's^ 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.


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