Tests for Several Independent Samples
The Tests for Several Independent Samples procedure compares two or more groups of cases on one variable.
Example. Do three brands of 100-watt lightbulbs differ in the average time that the bulbs will burn? From the Kruskal-Wallis one-way analysis of variance, you might learn that the three brands do differ in average lifetime.
Statistics. Mean, standard deviation, minimum, maximum, number of nonmissing cases, and quartiles. Tests: Kruskal-Wallis H, median.
Tests for Several Independent Samples Data Considerations
Data. Use numeric variables that can be ordered.
Assumptions. Use independent, random samples. The Kruskal-Wallis H test requires that the tested samples be similar in shape.
To Obtain Tests for Several Independent Samples
This feature requires the Statistics Base option.
- From the menus choose:
- Select one or more numeric variables.
- Select a grouping variable and click Define Range to specify minimum and maximum integer values for the grouping variable.
This procedure pastes NPAR TESTS command syntax.