One-Sample T-Test Assignment Help — Running and Interpreting It in SPSS

What Is the One-Sample T-Test and When Do You Use It?

The one-sample t-test compares the mean of a single continuous variable against a known or hypothesised value: for example, testing whether a class’s average exam score differs from the national average of 70, or whether a sample’s mean satisfaction rating differs from the scale’s neutral midpoint. Use it when you have one continuous dependent variable and a single, specific comparison value that doesn’t come from your data.

If you’re comparing two groups from your own data instead of a fixed external value, you need the independent or paired samples t-test instead.

Assumptions You Must Check Before Running It in SPSS

• Normality. The dependent variable should be approximately normally distributed. Check with a Shapiro-Wilk test (Analyze > Descriptive Statistics > Explore, Normality plots requested); p > .05 suggests the assumption holds. With larger samples (roughly n > 30), the t-test is fairly robust to mild violations.
• Independence of observations. Each case must be a separate, unrelated observation, not repeated measurements from the same subject.
• No pre-set variance assumption to check: unlike the independent samples t-test, there’s only one group, so there’s no Levene’s test involved.

How to Run It in SPSS (Step by Step)

1. Go to Analyze > Compare Means > One-Sample T Test.
2. Move your continuous variable into the Test Variable(s) box.
3. Enter your comparison value in the Test Value box. This is the fixed number you’re comparing your sample mean against.
4. Click OK.

SPSS produces two tables: One-Sample Statistics (mean, SD, and n) and One-Sample Test (the t-test itself, including the mean difference and confidence interval).

How to Interpret the Output

1. In the One-Sample Test table, read the t-value, degrees of freedom (df = n − 1), and Sig. (2-tailed), your p-value.
2. Check the Mean Difference column to see the direction and size of the gap between your sample mean and the test value.
3. Calculate Cohen’s d (mean difference ÷ sample standard deviation) for effect size: 0.2 small, 0.5 medium, 0.8 large.

How to Report the Results in APA Format

A one-sample t-test showed that the sample’s mean score (M = 74.3, SD = 8.1) was significantly higher than the test value of 70, t(49) = 3.75, p < .001, d = 0.53.

One-Sample T-Test vs Independent Samples T-Test: Understanding the Difference

The one-sample t-test compares your sample against a fixed, external number, not against another group in your dataset. The independent samples t-test compares two different groups of people. Using a one-sample test when you actually have two groups to compare (or vice versa) produces a technically valid-looking result that answers the wrong question.

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