# 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.

- From the menus choose:
- Select one or more numeric variables.
- Select a grouping variable and click Define Groups to split the file into two groups or samples.

This procedure pastes NPAR TESTS command syntax.