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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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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