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Bayes and MCMC for Undergraduates

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  • Jeff Witmer

Abstract

Students of statistics should be taught the ideas and methods that are widely used in practice and that will help them understand the world of statistics. Today, this means teaching them about Bayesian methods. In this article, I present ideas on teaching an undergraduate Bayesian course that uses Markov chain Monte Carlo and that can be a second course or, for strong students, a first course in statistics.

Suggested Citation

  • Jeff Witmer, 2017. "Bayes and MCMC for Undergraduates," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 259-264, July.
    • Handle: RePEc:taf:amstat:v:71:y:2017:i:3:p:259-264
    DOI: 10.1080/00031305.2017.1305289
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    References listed on IDEAS

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    1. George Cobb, 2015. "Mere Renovation is Too Little Too Late: We Need to Rethink our Undergraduate Curriculum from the Ground Up," The American Statistician, Taylor & Francis Journals, vol. 69(4), pages 266-282, November.
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