What are non-parametric tests in statistics?
An example of an AI chatbot conversation about non-parametric tests in statistics.
What are non-parametric tests in statistics?
Non-parametric tests are statistical methods that do not assume a specific distribution for the data. They are useful when data doesn't meet the assumptions of parametric tests.
Can you give me some examples of non-parametric tests?
Sure! Common examples include the Mann-Whitney U test, Kruskal-Wallis test, and Wilcoxon signed-rank test.
When should I use non-parametric tests instead of parametric tests?
You should use non-parametric tests when your data is ordinal, not normally distributed, or when you have small sample sizes.
Are non-parametric tests less powerful than parametric tests?
Generally, yes. Non-parametric tests can be less powerful than parametric tests when the assumptions of the latter are met.
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