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Teaching Statistics: A Bag of Tricks

Author

Listed:
  • Gelman, Andrew

    (Professor, Department of Statistics, Columbia University)

  • Nolan, Deborah

    (Professor, Department of Statistics, University of California)

Abstract

Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.

Suggested Citation

  • Gelman, Andrew & Nolan, Deborah, 2002. "Teaching Statistics: A Bag of Tricks," OUP Catalogue, Oxford University Press, number 9780198572244.
    • Handle: RePEc:oxp:obooks:9780198572244
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    Citations

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    Cited by:

    1. George W. Cobb, 2007. "One Possible Frame for Thinking about Experiential Learning," International Statistical Review, International Statistical Institute, vol. 75(3), pages 336-347, December.
    2. Roberto Behar & Pere Grima & Lluís Marco-Almagro, 2013. "Twenty-Five Analogies for Explaining Statistical Concepts," The American Statistician, Taylor & Francis Journals, vol. 67(1), pages 44-48, February.
    3. Miguel de Carvalho, 2016. "Mean, What do You Mean?," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 270-274, July.
    4. Antonoyiannakis, Manolis, 2018. "Impact Factors and the Central Limit Theorem: Why citation averages are scale dependent," Journal of Informetrics, Elsevier, vol. 12(4), pages 1072-1088.
    5. Andrew Gelman, 2003. "A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing," International Statistical Review, International Statistical Institute, vol. 71(2), pages 369-382, August.

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