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What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum

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Bootstrapping has enormous potential in statistics education and practice, but there are subtle issues and ways to go wrong.

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For example, the common combination of nonparametric bootstrapping and bootstrap percentile confidence intervals is less accurate than using t -intervals for small samples, though more accurate for larger samples. My goals in this article are to provide a deeper understanding of bootstrap methods—how they work, when they work or not, and which methods work better—and to highlight pedagogical issues.

Supplementary materials for this article are available online. [Received December 2014. Revised August 2015]

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