There is a lot of confusion about parametric vs. non-parametric statistics and tests. Some of the literature that explains the difference gets pretty technical. Here is a layman’s description that might not be 100% technically accurate but that will let you understand the difference.A parameter is a characteristic of a population. We often estimate parameters with statistics that come from samples. Some common parameters and statistics are the mean, the median, the standard deviation and so on.
Some tests use these parameters. For example, every variety of the t-test uses means and standard deviations. Therefore, the t-test is called a parametric test. On the other hand, some tests do not use these parameters. For example, the Mann Whitney U test uses no parameters. Therefore, it is called a non-parametric test.
If you want to tell if a test is parametric or not, look at the formulas used in calculating it. Do they contain parameters/statistics?