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Problem-Based Learning of Statistical Sampling Concepts Using Fantasy Sports Team Data

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Topics from Australian Conferences on Teaching Statistics

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 81))

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Abstract

This paper explores a case of using data from a fantasy sports competition (the AFL Dream Team competition) to teach the core concepts in statistical sampling and the central limit theorem as they apply to problems of inference regarding the population mean.

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Acknowledgment

The authors wish to thank Ian Weeding and the Australian Football League for the provision of the Dream Team data for use in the teaching program.

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Authors and Affiliations

  1. Department of Econometrics and Business Statistics, Faculty of Business and Economics, Monash University, 197, Caulfield East, VIC, 3145, Australia

    Robert Brooks

  2. Department of Economics, Monash University, Clayton, VIC, 3800, Australia

    Ross Booth

  3. Department of Econometrics and Business Statistics, Monash University, Berwick, 3806, Australia

    Jill Wright & Nishta Suntah

Authors
  1. Robert Brooks
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  2. Ross Booth
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  3. Jill Wright
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  4. Nishta Suntah
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Corresponding author

Correspondence to Robert Brooks .

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Editors and Affiliations

  1. Science and Engineering Faculty, Queensland University of Technology, Brisbane, Australia

    Helen MacGillivray

  2. Faculty of Life and Social Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia

    Brian Phillips

  3. Actuarial Studies and Applied Statistics, Australian National University, Research, Canberra, Aust Capital Terr, Australia

    Michael A. Martin

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Brooks, R., Booth, R., Wright, J., Suntah, N. (2014). Problem-Based Learning of Statistical Sampling Concepts Using Fantasy Sports Team Data. In: MacGillivray, H., Phillips, B., Martin, M. (eds) Topics from Australian Conferences on Teaching Statistics. Springer Proceedings in Mathematics & Statistics, vol 81. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0603-1_22

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