Tests for Several Related Samples
The Tests for Several Related Samples procedure compares the distributions of two or more variables.
Example. Does the public associate different amounts of prestige with a doctor, a lawyer, a police officer, and a teacher? Ten people are asked to rank these four occupations in order of prestige. Friedman's test indicates that the public does associate different amounts of prestige with these four professions.
Statistics. Mean, standard deviation, minimum, maximum, number of nonmissing cases, and quartiles. Tests: Friedman, Kendall's W, and Cochran's Q.
Tests for Several Related Samples Data Considerations
Data. Use numeric variables that can be ordered.
Assumptions. Nonparametric tests do not require assumptions about the shape of the underlying distribution. Use dependent, random samples.
To Obtain Tests for Several Related Samples
This feature requires the Statistics Base option.
- From the menus choose:
- Select two or more numeric test variables.
This procedure pastes NPAR TESTS command syntax.