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I Hear, I Forget. I Do, I Understand: A Modified Moore-Method Mathematical Statistics Course

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  • Nicholas J. Horton

Abstract

Moore introduced a method for graduate mathematics instruction that consisted primarily of individual student work on challenging proofs. Cohen described an adaptation with less explicit competition suitable for undergraduate students at a liberal arts college. This article details an adaptation of this modified Moore method to teach mathematical statistics, and describes ways that such an approach helps engage students and foster the teaching of statistics. Groups of students worked a set of three difficult problems (some theoretical, some applied) every two weeks. Class time was devoted to coaching sessions with the instructor, group meeting time, and class presentations. R was used to estimate solutions empirically, where analytic results were intractable, as well as to provide an environment to undertake simulation studies with the aim of deepening understanding and complementing analytic solutions. Each group presented comprehensive solutions to complement oral presentations. Development of parallel techniques for empirical and analytic problem solving was an explicit goal of the course, which also attempted to communicate ways that statistics can be used to tackle interesting problems. The group problem-solving component and use of technology allowed students to attempt much more challenging questions than they could otherwise solve. Supplementary materials for this article are available online.

Suggested Citation

  • Nicholas J. Horton, 2013. "I Hear, I Forget. I Do, I Understand: A Modified Moore-Method Mathematical Statistics Course," The American Statistician, Taylor & Francis Journals, vol. 67(4), pages 219-228, November.
  • Handle: RePEc:taf:amstat:v:67:y:2013:i:4:p:219-228
    DOI: 10.1080/00031305.2013.849207
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    Cited by:

    1. Nicholas J. Horton, 2015. "Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward," The American Statistician, Taylor & Francis Journals, vol. 69(2), pages 138-145, May.

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