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Bootstrap sampling is being touted as a simple technique that any hacker can easily employ to quantify the uncertainty of statistical estimates. However, despite its apparent simplicity, there are many ways to misuse bootstrapping and thereby draw wrong conclusions about your data and the world. This talk gives a brief overview of bootstrap sampling and discusses ways to avoid common pitfalls when bootstrapping your data.
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