16. Non-parametric Tests
The definition of what a non-parametric test is best understood by comparing parametric tests to non-parametric tests.
Parametric Tests | Non-parametric Tests |
Estimate a parameter like , , or (proportion) prior to hypothesis testing. | Hypothesis testing without parameter estimation. Involves counting or ranking. |
Generally require a population to be normally distributed. | “Distribution-free statistics”. |
Only works for quantitative data. | Works for both qualitative and quantitative data. |
More power. | Less power. |
Need more detailed data (more information). | Work with less detailed data (less information). |
Work with smaller sample sizes. | Need large sample sizes. |
If you have a choice, generally a parametric test is preferred to a non-parametric one because it has more power. On the other had, if you reject with a non-parametric test, you can be more confident in your decision.