Run an independent, paired, or one-sample t-test. Paste your data to get t, degrees of freedom, the p-value, the means and standard deviations, a significance verdict, and a ready-to-paste APA sentence.
Separate values with commas, spaces, or new lines. A paired test needs the same number of values in both columns.
Pick the test that matches your design. An independent two-sample test compares two separate groups of different people or units, for example a treatment group and a control group. A paired test compares two measurements on the same people or units, for example a pre-test and a post-test, so each row is one matched pair. A one-sample test compares a single group against a known or hypothesized value, for example testing whether an average score differs from a passing mark of 100.
For the independent test you choose whether to assume the two groups share the same variance. The box is unchecked by default, which runs the Welch test. Welch does not assume equal spread and stays accurate when the groups differ in variance or in size, so it is the safer default. Tick the equal-variances box only when Levene's test is not significant and pooling is justified, which gives the classic Student pooled t-test with whole-number degrees of freedom.
This tool gives the correct numbers for the three common t-tests, but a graded assignment usually needs more: a Levene's test for equal variances, an effect size such as Cohen's d, a normality check, and the result written the way your course expects. Our t-test in SPSS guide walks through the full workflow, and a statistician can run and interpret your data end to end.
Send your data and a statistician runs the t-test, checks the assumptions, reports the effect size, and writes the results before your deadline.
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