There are four tests for cases involving two independent samples. These tests are:
- The Mann-Whitney U test
- The Wald-Wolfowitz Runs test
- The Kolmogorov-Smirnov Z test
- The Moses Extreme Reactions test
The Mann-Whitney U test in the tests for two independent samples is an alternative form of the t-test. It is widely used to test whether or not the two independent samples are significantly different. In SPSS, the Mann-Whitney U test in the tests for two independent samples is done by selecting “analyze” from the menu, then clicking on “Nonparametric Tests.” After this, select “2 Independent Samples” and select the “Mann-Whitney U” option from the Test Type option.
The Wald-Wolfowitz Runs test in the tests for two independent samples is used for testing the significant difference between two independent samples of an ordinal variable. In SPSS, Wald-Wolfowitz Runs in the tests for two independent samples is done by selecting “Nonparametric Tests” from the analyze menu, and then selecting “2 Independent Samples from Nonparametric.” Finally, select the “Wald-Wolfowitz runs” option from the Test Type option.
The Kolmogorov-Smirnov Z test in the tests for two independent samples is used to test whether or not the maximum absolute difference in the overall distribution of the two groups is significant. In SPSS, Kolmogorov-Smirnov Z test in the tests for two independent samples is done by selecting “Nonparametric Tests” from the analyze menu, and then clicking on “2 Independent Samples from Nonparametric.” Finally, select the “Kolmogorov-Smirnov Z” option from the Test Type option.
The Moses Extreme Reactions test in the tests for two independent samples is used to test if the treatment variables will affect the subjects in a positive manner or in a negative manner. In SPSS, the Moses Extreme Reactions in the tests for two independent samples is done by selecting “Nonparametric Tests” from the analyze menu, and then clicking on “2 Independent Samples from Nonparametric.” Finally, choose the “Moses Extreme Reactions” option from the Test Type option.
Assumptions of tests for two independent samples:
In all the tests for two independent samples, sampling is done randomly. The four tests in the tests for two independent samples are non parametric tests that do not assume normal distribution. The four tests in the tests for two independent samples are based on ordinal data or higher.
