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An independent-samples t-test compares the means between two unrelated groups, such as comparing the difference between class 1 and class 2, another very common example would be used to compare a binary gender difference.

If you have more than three groups consider using a **One-Way Between-Subjects ANOVA**

It is considered a parametric test and is only suitable for parametric data. To check if your data is parametric, please read our dedicated guide: **Parametric or Not Guide (PDF)**

If your data is non-parametric you should consider using a **Mann-Whitney U-Test**.

- Click Analyze > Compare Means > Independent-Samples T Test
- In the "Independent-Samples T Test" box, select the test variable (dependent variable) you are analysing and move it to the "Test Variable(s)" box. Then move your grouping variable (independent variable) into the “Grouping Variable” box.
- Click "Define Groups..." and specify the groups you are going to test. In this example I am testing Class 1 against Class 2 therefore my groups are numbered 1 and 2.
- Click "Continue" and then "OK".

SPSS will generate three tables, for this test we need to read from: "Group Statistics" and "Independent Samples Test".

This table shows a selection of descriptive statistics: the sample size of each group (N), the mean of each group (Mean), and the standard deviation of each group (Std. Deviation), these are typically all reported.

This table shows the specific test results including the t-statistic (t), the degrees of freedom (df) the two-tailed significance or p-value (Two-Sided p), and the 95% Confidence Interval (95% Confidence Interval of the Difference).

*M *= 6.00, *SD* = 1.77) scored higher than class 2 students (*M* = 5.00, *SD *= 2.62). An independent-samples t-test indicated this difference, 1.00, 95%*CI* [-1.40, 3.40], was not statistically significant, *t *(19) = 0.89, *p *=.386

- Last Updated: May 23, 2023 4:04 PM
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