User Guide

505
Nonparametric
Te s t s
Figure 34-21
Tests for Several Independent Samples dialog box
E Select o
ne or more numeric variables.
E Select a
grouping variable and click
Define Range to specify minimum and maximum
integer values for the grouping variable.
Tests fo
r Several Independent Samples Test Types
Three te
sts are available to determine if several independent samples come from the
same population.
The Kruskal-Wallis H test, the median test, and the Jonckheere-Terpstra test
all test
whether several independent samples are from the same population.
The Kruskal-Wallis H test, an extension of the Mann-Whitney U test, is the
nonparametric analog of one-way analysis of variance and detects differences in
distri
bution location. The median test, which is a more general test but not as
powerful, detects distributional differences in location and shape. The Kruskal-Wallis
H test and the median test assume there is no aprioriordering of the k populations
from w
hich the samples are drawn. When there is a natural aprioriordering
(ascending or descending) of the k populations, the Jonckheere-Terpstra test is more
powerful. For example, the k populations might represent k increasing temperatures.
The hy
pothesis that different temperatures produce the same response distribution
is tested against the alternative that as the temperature increases, the magnitude