Paired Samples T-Test Assignment Help — Pre/Post Comparisons in SPSS

What Is the Paired Samples T-Test and When Do You Use It?

The paired samples t-test compares two related measurements from the same subjects: a pre-test and post-test score, or two matched-pair observations. Use it when the same people (or matched pairs) are measured twice on a continuous variable, and you want to know whether the average difference between the two measurements is statistically significant.

If you’re comparing two different groups of people instead of the same people twice, you need the independent samples t-test instead.

Assumptions You Must Check Before Running It in SPSS

• Normality of the difference scores, not the raw scores. Compute the difference between each pair (Transform > Compute Variable), then run a Shapiro-Wilk test on that difference variable. This is the detail students most often miss: the assumption applies to the differences, not to each measurement separately.
• The pairs must be genuinely related: the same subject or a deliberately matched pair measured under two conditions, not two independent samples.

How to Run It in SPSS (Step by Step)

1. Go to Analyze > Compare Means > Paired-Samples T Test.
2. Select your two related variables and move them into Paired Variables as Variable 1 and Variable 2.
3. Click OK.

SPSS produces three tables: Paired Samples Statistics, Paired Samples Correlations, and Paired Samples Test (the t-test itself).

How to Interpret the Output

1. In the Paired Samples Test table, read the t-value, degrees of freedom (df = number of pairs − 1), and Sig. (2-tailed).
2. Check the Mean column under “Paired Differences” for the direction and size of the average change.
3. Calculate effect size as Cohen’s d for paired data: mean difference ÷ standard deviation of the differences (0.2 small, 0.5 medium, 0.8 large).

How to Report the Results in APA Format

A paired samples t-test showed that post-intervention scores (M = 82.1, SD = 5.4) were significantly higher than pre-intervention scores (M = 75.6, SD = 6.9), t(29) = 4.18, p < .001, d = 0.76.

Paired Samples T-Test vs Independent Samples T-Test: Understanding the Difference

The paired test compares the same subjects measured twice: pre/post designs, matched pairs. The independent samples test compares two different groups. Running the independent version on paired data ignores the correlation between the two measurements and typically understates the true effect, while running the paired version on independent groups is simply invalid: the “pairing” isn’t real.

Not sure which one your design needs? See the full SPSS statistical test guide, or get help with this specific assignment.