*Using
the Paired Samples T-Test Function *

The paired
samples t-test in EZAnalyze allows you to determine the statistical significance
of a difference between two paired means. This test is the most appropriate
when you have a *repeated measures* design where the data are
from a single group of cases exposed to two measures over time, as in
a pretest-posttest design. Since this is an Advanced feature of EZAnalyze,
it will not be discussed at length here. Feel free to consult a statistics
textbook or the Internet for information on what a paired t-test is and
how it works. If you are already familiar with paired samples t-tests
and want EZAnalyze to crunch the numbers for you, read on!

To conduct this analysis, your data will need to have at least two "paired" variables - each variable should have similar data. Think of each of these as a dependent variable. What this test does is tell you if the mean of the first variable is significantly different from mean of the second variable.

To conduct an independent samples t-test, select "Advanced" from the EZAnalyze menu in Excel, then choose "T-Tests" and "Paired Samples".

In the "Paired Samples T-Test" dialog box, select your paired variables - one variable under "Variable 1" and another under "Variable 2" and click OK. If you are running this test on a pre-post test experimental design, you will want to use Variable 1 for your pretest variable, and Variable 2 for your posttest variable.

*A
note about your variables. *These variables should be on the same
metric - for example, GPA for social studies and science, or the mean
scores of a variable coded from 1-5. This procedure will not be accurate
if your variables are not on the same metric - for example, comparing
GPA and SAT scores is not appropriate in a paired samples t-test.

When
you click OK, a results report will
be printed on a separate sheet for your review. *(click on "results
report" for information on how to interpret this analysis)*