Pith. sign in

REVIEW

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1904.11006 v1 pith:WTGNLYYJ submitted 2019-04-16 stat.OT astro-ph.IMphysics.data-anstat.AP

classification stat.OTastro-ph.IMphysics.data-anstat.AP
keywords bayesianexerciseanalysiscircledrtextactive-learningundergraduatesadvantage
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
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.

Discussion (0). Sign in to comment.

Pith tools