Two-Independent-Samples Tests

The Two-Independent-Samples Tests procedure compares two groups of cases on one variable.

Example. New dental braces have been developed that are intended to be more comfortable, to look better, and to provide more rapid progress in realigning teeth. To find out whether the new braces have to be worn as long as the old braces, 10 children are randomly chosen to wear the old braces, and another 10 children are chosen to wear the new braces. From the Mann-Whitney U test, you might find that, on average, children with the new braces did not have to wear the braces as long as children with the old braces.

Statistics. Mean, standard deviation, minimum, maximum, number of nonmissing cases, and quartiles. Tests: Mann-Whitney U, Moses extreme reactions, Kolmogorov-Smirnov Z, Wald-Wolfowitz runs.

Two-Independent-Samples Tests Data Considerations

Data. Use numeric variables that can be ordered.

Assumptions. Use independent, random samples. The Mann-Whitney U test tests equality of two distributions. In order to use it to test for differences in location between two distributions, one must assume that the distributions have the same shape.

To Obtain Two-Independent-Samples Tests

This feature requires the Statistics Base option.

1. From the menus choose:

Analyze > Nonparametric Tests > Legacy Dialogs > 2 Independent Samples...

2. Select one or more numeric variables.
3. Select a grouping variable and click Define Groups to split the file into two groups or samples.

This procedure pastes NPAR TESTS command syntax.