A common statistical test involves hypotheses about means.
The TTEST
command is used to find out whether or not two separate
subsets have the same mean.
A researcher suspected that the heights and core body temperature of persons might be different depending upon their sex. To investigate this, he posed two null hypotheses based on the data from physiology.sav previously encountered:
For the purposes of the investigation the researcher decided to use a pvalue of 0.05.
In addition to the Ttest, the TTEST
command also performs the
Levene test for equal variances.
If the variances are equal, then a more powerful form of the Ttest can be used.
However if it is unsafe to assume equal variances,
then an alternative calculation is necessary.
PSPP performs both calculations.
For the height variable, the output shows the significance of the Levene test to be 0.33 which means there is a 33% probability that the Levene test produces this outcome when the variances are equal. Had the significance been less than 0.05, then it would have been unsafe to assume that the variances were equal. However, because the value is higher than 0.05 the homogeneity of variances assumption is safe and the “Equal Variances” row (the more powerful test) can be used. Examining this row, the two tailed significance for the height ttest is less than 0.05, so it is safe to reject the null hypothesis and conclude that the mean heights of males and females are unequal.
For the temperature variable, the significance of the Levene test is 0.58 so again, it is safe to use the row for equal variances. The equal variances row indicates that the two tailed significance for temperature is 0.20. Since this is greater than 0.05 we must reject the null hypothesis and conclude that there is insufficient evidence to suggest that the body temperature of male and female persons are different.
The syntax for this analysis is:
PSPP> get file='//share/pspp/examples/physiology.sav'. PSPP> recode height (179 = SYSMIS). PSPP> ttest group=sex(0,1) /variables = height temperature.
PSPP produces the following output for this syntax:

The TTEST
command tests for differences of means.
Here, the height variable’s two tailed significance is less than
0.05, so the null hypothesis can be rejected.
Thus, the evidence suggests there is a difference between the heights of
male and female persons.
However the significance of the test for the temperature
variable is greater than 0.05 so the null hypothesis cannot be
rejected, and there is insufficient evidence to suggest a difference
in body temperature.