User Guide

364
Chapter 20
Confidence Interval. By default, a 95%-confidence interval for the difference in means
is displayed. Enter a value between 1 and 99 to request a different confidence level.
Missing Val
ues.
When you test several variables and data are missing for one or more
variables, you can tell the procedure which cases to include (or exclude):
 Exclude cases an alysis by analysis. Each t test uses all cases that have valid data
for the pair
of variables tested. Sample sizes may vary from test to test.
 Exclude ca
ses listwise.
Each t test uses only cases that have valid data for all pairs
of variables tested. The sample size is constant across tests.
One-Sample T Test
The One-Sample T Test procedure tests whether the mean of a single variable differs
from a specified constant.
Examples.
A researcher might want to test whether the average IQ score for a group of
students differs from 100. Or, a cereal manufacturer can take a sample of boxes from
the production line and check whether the mean weight of the samples differs from
1.3 pounds
at the 95%-confidence level.
Statistics. For each test variable: mean, standard deviation, and standard error of the
mean. The average difference between each data value and the hypothesized test
value, a t
test that tests that this difference is 0, and a confidence interval for this
difference (you can specify the confidence level).
Data. To test the values of a quantitative variable against a hypothesized test value,
choose a
quantitative variable and enter a hypothesized test value.
Assumptions. This test assumes that the data are normally distributed; however, this
test is fairly robust to departures from normality.