This blogpost highlights a typical mistake when performing the bootstrap hypothesis test. Bootstrapping is a method of resampling data to estimate measures of variability, such as confidence intervals or variance. 

In the simplest form of the bootstrap, assume you have a set of values 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. You want to estimate the mean and variability of the mean using these data. The recipe is as follows: