Nonparametric Tests
Before we talk about the Nonparametric Tests, let's understand what Parametric Tests are.
Parametric Tests:
These are hypothesis tests that assume that the data being analyzed follows a distribution (generally Normal Distribution).
Examples of Parametric Tests:
- One Sample z-Test
- Two Sample z-Test
- One Sample t-Test
- Two Sample t-Test
- Paired t-Test
- etc.
Nonparametric Tests:
A nonparametric test does not assume anything about the underlying distribution. That way, these tests can be used on any set of data without any condition.
But then why don't we always use Nonparametric Tests?
Since nonparametric tests do not assume any probability distribution, nonparametric tests' power is lower than the power of parametric tests.
Parametric vs Nonparametric Tests for Mean and Median
Parametric tests (for mean) | Nonparametric tests (for median) |
1-sample z test 1-sample t-test | 1-sample Sign, 1-sample Wilcoxon Signed Rank test |
2-sample t-test | Mann-Whitney test |
One-Way ANOVA | Kruskal-Wallis test Mood’s median test |
Two-way ANOVA | Friedman test |