文章基本信息

标题：Introducing Bayesian Analysis With m&m's®: An Active-Learning Exercise for Undergraduates
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作者：Gwendolyn Eadie ; Daniela Huppenkothen ; Aaron Springford 等
期刊名称：Journal of Statistics Education
电子版ISSN：1069-1898
出版年度：2019
卷号：27
期号：2
页码：60-67
DOI：10.1080/10691898.2019.1604106
出版社：American Statistical Association
摘要：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 nonuniform distribution of m&m’s® colors, 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.
关键词：Active-learning ; Bayesian methods ; Education ; Eliciting priors ; Inference