User Guide

358
Chapter 20
Example. Patients with high blood pressure are randomly assigned to a placebo group
and a treatment group. The placebo subjects receive an inactive pill and the treatment
subjects re
ceive a new drug that is expected to lower blood pressure. After treating the
subjects for two months, the two-sample t test is used to compare the average blood
pressures for the placebo group and the treatment group. Each patient is measured
once and be
longs to one group.
Statistics. For each variable: sample size, mean, standard deviation, and standard
error of the mean. For the difference in means: mean, standard error, and confidence
interval (
you can specify the confidence level). Tests: Levene’s test for equality of
variances, and both pooled- and separate-variances t tests for equality of means.
Data. The values of the quantitative variable of interest are in a single column in the
data file
. The procedure uses a grouping variable with two values to separate the cases
into two groups. The grouping variable can be numeric (values such as 1 and 2, or
6.25 and 12.5) or short string (such as yes and no). As an alternative, you can use a
quantita
tive variable, such as age, to split the cases into two groups by specifying a
cut point (cut point 21 splits age into an under-21 group and a 21-and-over group).
Assumptions. For the equal-variance t test, the observations should be independent,
random s
amples from normal distributions with the same population variance. For
the unequal-variance t test, the observations should be independent, random samples
from normal distributions. The two-sample t test is fairly robust to departures
from no
rmality. When checking distributions graphically, look to see that they are
symmetric and have no outliers.
Figure
20-1
Indepe
ndent-Samples T Test output
10 142.50 17.04 5.39
10 116.40 13.62 4.31
placebo
new_drug
TreatmentBlood
pressure
N Mean
Std.
Deviation
Std. Error
Mean
Group Statistics