What Nonparametric tests is
Nonparametric tests are a type of statistical test that do not assume the data is normally distributed and do not rely on the assumptions of the parametric tests. They are also known as distribution-free tests as they make no assumptions about the population distribution. Nonparametric tests are used in a variety of situations such as when the data is not normally distributed, when the sample size is small, or when the data is ordinal (i.e. ranks).
Steps for Nonparametric Tests:
- Define the research question and determine the type of nonparametric test to be used.
- Collect the data and organize it into a format that can be used for the nonparametric test.
- Determine the appropriate nonparametric test statistic.
- Calculate the nonparametric test statistic.
- Compare the calculated test statistic to a critical value and make a conclusion.
Examples
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A nonparametric test could be used to compare the average number of hours spent studying between two groups of students.
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A nonparametric test could be used to compare the success rates between two treatment groups in a medical study.
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A nonparametric test could be used to compare the levels of customer satisfaction between two businesses.
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A nonparametric test could be used to compare the average number of days absent from work between two groups of employees.
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A nonparametric test could be used to compare the level of job satisfaction between two different job roles.