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MASH : Maths and Stats Help

Independent Samples t-Test

Introduction

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 three or more 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.

 

Test Procedure

  1. Click Analyze > Compare Means > Independent-Samples T Test

    Step 1: Click Analyze > Compare Means > Independent-Samples T Test

  2. 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.

    Step 2: Within the Independent-Samples T Test box, select the test variable or dependent variable you are analysing and move it to the test variable box. Then move your independent/grouping variable into the “Grouping Variable” box.

  3. 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.

    Step 3: Select Define Groups and specify the groups you are going test. In this example I am testing Class 1 against Class 2 therefore my groups are numbered 1 and 2.

  4. Click "Continue" and then "OK".

 

Results

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

Group Statistics

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.

Independent Samples Test

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), the mean difference between the groups (which we report below using d̄), and the 95% Confidence Interval (95% Confidence Interval of the Difference).

 

Reporting the Results in APA Formatting

English scores of class 1 and class 2 students were compared. On average, class 1 students (M = 6.31, SD = 1.71) scored higher than class 2 students (M = 4.63, SD = 2.16). An independent-samples t-test indicated this difference, d̄ = 1.69, 95%CI [0.28, 3.09], was statistically significant, t (30) = 2.45, p =.020.