Many analyses in psychological research involve testing hypotheses about means or mean differences. Below we describe the SPSS procedures that allow you to determine if a given mean is equal to either a fixed value or some other mean.
One-sample t-test
You perform a one-sample t-test when you want to determine if the mean value of a target variable is different from a hypothesized value.
To perform a one-sample t-test in SPSS
• Choose Analyze then goto Compare Means then goto One-sample t-test.
• Move the variable of interest to the Test variable(s) box.
• Change the test value to the hypothesized value.
• Click the OK button.
The output from this analysis will contain the following sections.
• One-Sample Statistics. Provides the sample size, mean, standard deviation, and standard error of the mean for the target variable.
• One-Sample Test. Provides the results of a t-test comparing the mean of the target variable to the hypothesized value. A significant test statistic indicates that the sample mean differs from the hypothesized value. This section also contains the upper and lower bounds for a 95% confidence interval around the sample mean.
Independent-samples t-test
You perform an independent-samples t-test (also called a between-subjects t-test) when you want to determine if the mean value on a given target variable for one group differs from the mean value on the target variable for a different group. This test is only valid if the two groups have entirely different members. To perform this test in SPSS you must have a variable representing group membership, such that different values on the group variable correspond to different groups.
To perform an independent-samples t-test in SPSS
• Choose Analyze then goto Compare Means then goto Independent-sample t-test.
• Move the target variable to the Test variable(s) box.
• Move the group variable to the Grouping variable box.
• Click the Define groups button.
• Enter the values corresponding to your two groups you want to compare in the boxes labeled group 1 and group 2.
• Click the Continue button.
• Click the OK button.
The output from this analysis will contain the following sections.
• Group Statistics. Provides descriptive information about your two groups, including the sample size, mean, standard deviation, and the standard error of the mean.
• Independent Samples Test. Provides the results of two t-tests comparing the means of your two groups. The first row reports the results of a test assuming that the two variances are equal, while the second row reports the results of a test that does not assume the two variances are equal. The columns labeled Levene’s Test for Equality of Variances report an F test comparing the variances of your two groups. If the F test is significant then you should use the test in the second row. If it is not significant then you should use the test in the first row. A significant t-test indicates that the two groups have different means. The last two columns provide the upper and lower bounds for a 95% confidence interval around the difference between your two groups.
Paired-samples t-test
You perform a paired samples t-test (also called a within-subjects t-test) when you want to determine whether a single group of participants differs on two measured variables. Probably the most common use of this test would be to compare participants. response on a measure before a manipulation to their response after a manipulation. This test works by first computing a difference score for each participant between the within-subject conditions (e.g. post-test-pretest). The mean of these difference scores is then compared to zero. This is the same thing as determining whether there is a significant difference between the means of the two variables.
To perform a paired-samples t-test in SPSS
• Choose Analyze then goto Compare Means then goto Paired-samples t-test.
• Click the two variables you want to compare in the box on the left-hand side.
• Click the arrow button.
• Click the OK button.
The output from this analysis will contain the following sections.
• Paired Samples Statistics. Provides descriptive information about the two variables, including the sample size, mean, standard deviation, and the standard error of the mean.
• Paired Samples Correlations. Provides the correlation between the two variables.
• Paired Samples Test. Provides the results of a t-test comparing the means of the two variables. A significant t-test indicates that there is a difference between the two variables. It also contains the upper and lower bounds of a 95% confidence interval around the difference between the two means.