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Pretest/Posttest. Data is collected from a sample before some type of treatment and then data is
collected again from that same sample after the treatment. We then work with the mean
difference between the pre and posttest scores. The null hypothesis is that the average difference
is zero. By working with the differences between the variables, we can perform a one-sample T-
Test.
Example: Blood Pressure
A researcher wanted to find the effects of a special diet on systolic blood pressure. She selected
a sample of seven adults and put them on a dietary plan for three months. The following table
gives the systolic blood pressures of the seven adults before and after the completion of the plan.
Before 210 180 195 220 231 199 224
After 193 186 186 223 220 183 233
Let µ
d
be the mean reduction in the systolic blood pressures due to this special dietary plan for
the population of all adults. Test to see if there was a significant reduction in systolic blood
pressure at a .05 significance level. Assume that the population of paired differences is
(approximately) normally distributed.
Enter the Before scores into the list labeled L1.
Enter the After scores into the list labeled L2.
Move the cursor to highlight L3 and type in L1-L2.
Press the ENTER key.
That will subtract the values in L2 from the values
in L1 and store the differences in L3.
Press the STAT key.
Press the ► key twice to highlight TESTS.
Press the number 2 key to select T-Test.
Highlight Data and press the ENTER key.
Type in 0 for µ
0
.
Type in L3 for List since the differences are stored there.
Leave Freq at 1.
Highlight >µ
0
and press the ENTER key.
Highlight Calculate and press the ENTER key.
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