Statistical interview question: What is the difference between a parametric and nonparametric test?

I have recently written a blog post about hypothesis tests, and that blog post can be read here:- https://medium.com/@tracyrenee61/use-python-in-excel-to-explore-20-popular-hypothesis-tests-f765962e320d

While I was writing that blog post, and others, one thing that crept up was that some of the hypothesis tests that I studied were of a nonparametric nature. If some tests are nonparametric the others will be parametric, so I thought this would be a good subject to write about. There is always the possibility that a related question can pop up in a data science interview, so it is important to know what they are and the differences between them.

Parametric hypothesis tests

Parametric hypothesis testing is a subtype of hypothesis testing in statistics. It is used to understand the characteristics of a population from a sample. Parametric tests are statistical measures used in the analysis phase of research to solve inferences and conclusions to solve a research problem. These tests usually have stricter requirements that nonparametric tests and are able to make stronger inferences from the data. The most common types of parametric tests include regression tests, comparison tests, and correlation tests.