Nonparametric test
Nonparametric Test
A nonparametric test is a type of statistical hypothesis testing that makes no assumptions about the probability distribution of the variables being assessed. The term nonparametric is not meant to imply that such tests have no parameters, but rather that the parameters are more flexible and less rigidly defined than in parametric statistics. Nonparametric tests are also known as distribution-free tests.
Overview[edit | edit source]
Nonparametric tests are widely used when the data is not normally distributed or when the sample size is small. They are less powerful than their parametric counterparts, but they are more robust and have fewer assumptions. Nonparametric tests are often used in social sciences, medicine, and business where data may not meet the assumptions of parametric tests.
Types of Nonparametric Tests[edit | edit source]
There are several types of nonparametric tests, including:
- Mann-Whitney U test: This test is used to compare two independent samples to determine if there is a significant difference between them.
- Wilcoxon signed-rank test: This test is used to compare two paired samples to determine if there is a significant difference between them.
- Kruskal-Wallis test: This test is used to compare more than two independent samples to determine if there is a significant difference between them.
- Friedman test: This test is used to compare more than two paired samples to determine if there is a significant difference between them.
Advantages and Disadvantages[edit | edit source]
Nonparametric tests have several advantages. They do not require the data to be normally distributed and can be used with ordinal, nominal, and interval data. They are also less sensitive to outliers and can be used with small sample sizes.
However, nonparametric tests also have some disadvantages. They are less powerful than parametric tests, meaning they are less likely to detect a significant effect if one exists. They also cannot provide as much information about the effect size or the relationship between variables.
See Also[edit | edit source]
- Parametric statistics
- Statistical hypothesis testing
- Mann-Whitney U test
- Wilcoxon signed-rank test
- Kruskal-Wallis test
- Friedman test
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