SPSS makes t-test calculations straightforward. This guide covers one-sample, independent samples, and paired samples t-tests with step-by-step instructions and output interpretation.
| Group | N | Mean | SD | SE Mean |
|---|---|---|---|---|
| Online Teaching | 42 | 78.40 | 9.62 | 1.48 |
| In-Person Teaching | 42 | 71.95 | 10.84 | 1.67 |
| Levene's F | Sig. | t | df | p (2-tail) | Mean Diff |
|---|---|---|---|---|---|
| 2.34 | .130 | 2.93 | 82 | .004 | 6.45 |
Choose the correct t-test based on your research design and data structure
Compares the mean of a single sample against a known population mean or hypothesized value.
Compares means between two unrelated (independent) groups on a continuous outcome variable.
Compares means from the same participants measured at two different times or under two conditions.
Follow these instructions for each t-test type
Go to Analyze → Compare Means → One-Sample T Test.
Select the continuous variable you want to test and move it to the Test Variable(s) box.
Enter the population or hypothesized mean you are comparing against (e.g., 100 for IQ).
Review One-Sample Statistics (mean, SD) and One-Sample Test (t, df, p-value, mean difference).
Go to Analyze → Compare Means → Independent-Samples T Test.
Move your continuous outcome to Test Variable(s). Move your categorical grouping variable to Grouping Variable.
Click Define Groups and enter the numeric codes for your two groups (e.g., 1 and 2 for treatment/control).
Use Levene's test (Sig. column) to decide which t-value row to report. If Sig. > .05, use equal variances assumed row.
Go to Analyze → Compare Means → Paired-Samples T Test.
Select the pre-test variable, then hold Ctrl and click the post-test variable. Click the arrow to pair them.
Click OK. Examine Paired Samples Statistics (means), Paired Samples Correlations, and Paired Samples Test (t, df, p).
SPSS does not report effect size. Calculate manually: d = t / √n (paired) or using means/SD.