# What is the difference between bootstrap hypothesis testing/permutation test and traditional hypothesis testing?

I recently learned about doing hypothesis tests by bootstrapping and permutation. I'm trying to relate it to other traditional hypothesis testing such as t-test or chi-square test. Are they in the same category? Can I think of bootstrap hypothesis testing as a non-parametric approach?

• Can you provide a citation or example? Bootstrapping is generally a method for obtaining confidence intervals and, to my knowledge, is not a specific formulation or approach to hypothesis testing. Commented Jul 21, 2018 at 2:22
• Similar interesting Q&A, and last comment: stats.stackexchange.com/questions/41683/…
– Rob
Commented Jul 21, 2018 at 3:22
• @Todd You're correct. But we can also use it to test a hypothesis. For example, we have a dataset of height measurements for kids and adults. We compute the mean of the data and then split the dataset into kids' heights and adults' heights. Calculate the means of each split and the their difference. Then shift the means of both splits to the mean of the original dataset. Perform bootstrapping to construct the confidence interval of mean difference. Then check the probability of the mean difference of the two splits from CI. Commented Jul 21, 2018 at 4:41