Resampling techniques are a powerful tool in the hands of statisticians and data scientists. They provide a way to estimate the distribution of a statistic without making strong assumptions about the underlying data-generating process. This is particularly useful when the data is not normally distributed or when the sample size is small. Resampling techniques are widely used in a variety of applications, including hypothesis testing, confidence interval estimation, and model selection.

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