# 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 test1-sample t-test 1-sample Sign, 1-sample Wilcoxon Signed Rank test 2-sample t-test Mann-Whitney test One-Way ANOVA Kruskal-Wallis testMood’s median test Two-way ANOVA Friedman test #### Six Sigma Black Belt

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