What is the difference between parametric and non-parametric tests?

What is the difference between parametric and non-parametric tests?

Parametric tests are statistical tests that make assumptions about the population distribution, such as assuming that the data follows a normal distribution. These tests require the estimation of parameters, such as means or variances, and are more powerful when the assumptions are met. Non-parametric tests, on the other hand, do not make any assumptions about the population distribution. These tests are based on ranks or other non-numerical data and are used when the assumptions for parametric tests are not met or when dealing with categorical or ordinal data. Non-parametric tests are generally considered to be less powerful than parametric tests but are more robust to violations of assumptions.