If the test is statistically significant (e.g., p<0.05), then data do not follow a normal distribution, and a nonparametric test is warranted.
...
When to Use a Nonparametric Test
...
When to Use a Nonparametric Test
- when the outcome is an ordinal variable or a rank,
- when there are definite outliers or.
- when the outcome has clear limits of detection.
When should you use a non parametric test?
Non parametric tests are used when your data isn't normal. Therefore the key is to figure out if you have normally distributed data. For example, you could look at the distribution of your data. If your data is approximately normal, then you can use parametric statistical tests.
What are three reasons to use nonparametric tests?
The main reasons to apply the nonparametric test include the following:
- The underlying data do not meet the assumptions about the population sample. ...
- The population sample size is too small. ...
- The analyzed data is ordinal or nominal. ...
- Mann-Whitney U Test. ...
- Wilcoxon Signed Rank Test. ...
- The Kruskal-Wallis Test.
