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Probability Concepts Needed for Teaching a Repeated Sampling Approach to Inference

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Teaching and Learning Stochastics

Part of the book series: ICME-13 Monographs ((ICME13Mo))

Abstract

This paper uses theoretical and empirical perspectives to articulate what learners should understand about a repeated sampling approach to inference that emphasizes a process of randomizing data, repeating through simulation, and rejecting any model with observed data in the extreme of a distribution that does not fit the model. Key probability concepts, such as a probability model and data distributions, are identified and discussed as to why and how they can assist learners in developing richer understandings and capabilities to a repeated sampling approach to inference.

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Author information

Authors and Affiliations

  1. NC State University, 502C Poe Hall Campus, Box 7801, Raleigh, NC, 27695, USA

    Hollylynne S. Lee

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  1. Hollylynne S. Lee
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Correspondence to Hollylynne S. Lee .

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Editors and Affiliations

  1. Facultad de Ciencias de la Educación, University of Granada, Granada, Spain

    Carmen Batanero

  2. College of Education, University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Egan J Chernoff

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Lee, H.S. (2018). Probability Concepts Needed for Teaching a Repeated Sampling Approach to Inference. In: Batanero, C., Chernoff, E. (eds) Teaching and Learning Stochastics. ICME-13 Monographs. Springer, Cham. https://doi.org/10.1007/978-3-319-72871-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-72871-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72870-4

  • Online ISBN: 978-3-319-72871-1

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