A Statistical Inference Course Based on p-Values |
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Authors: | Ryan Martin |
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Institution: | 1. Department of Statistics, North Carolina State University, Raleigh, NC;2. Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL |
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Abstract: | Introductory statistical inference texts and courses treat the point estimation, hypothesis testing, and interval estimation problems separately, with primary emphasis on large-sample approximations. Here, I present an alternative approach to teaching this course, built around p-values, emphasizing provably valid inference for all sample sizes. Details about computation and marginalization are also provided, with several illustrative examples, along with a course outline. Supplementary materials for this article are available online. |
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Keywords: | Confidence interval Large-sample theory Monte Carlo Teaching statistics Valid inference |
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