Welcome to the fifth post in SPSS for Beginners from SPSS Mastering. Earlier, we learned how to compare means using SPSS in our Comprehensive Guide to Using SPSS for Data Analysis. Now, I’m going to show you how to test whether two means are different using a procedure called the one sample t-test. T-tests are easy to do in SPSS.

In the next three posts, we will learn about three kinds of T-tests. Each of them will use the data set that we created in the first post. I’m interested in the variable Height. Specifically, I want to know if my participants are taller or shorter than the national average.

Perhaps we sampled these people from a certain country and we want to know how they compare to the average American. Or perhaps they have a certain disorder and I want to know how they compare to the typical average healthy person. Or perhaps these are children who grew up eating a certain diet and I want to know if that diet affected their height compared to an average child.

So what I have is one group of people whom I have measured one time. I want SPSS to calculate the mean from my sample and then compare that sample mean to another known mean. And to do this, I’m going to use a one sample t-test.

Steps to Perform a One Sample T-Test in SPSS

1. Go to Analyze -> Compare Means -> One Sample T-Test.
2. A window pops up just like we have seen before. Move your variable Height into the Test Variables box. You can do that with the arrow or just by dragging it over.
3. Set your hypothesized population mean in the box labeled Test Value. Imagine that we read that other people, similar to this sample, have an average height of 65 inches tall.
4. Click OK. The output window will pop up and you will see two tables.

Interpreting the One-Sample T-Test Output

One-Sample Statistics

This table provides the following descriptive statistics for the variable height in inches:

• N: The sample size is 10.
• Mean: The mean height of the sample is 65.8000 inches.
• Standard Deviation: The standard deviation of the sample is 2.39444.
• Standard Error Mean: The standard error of the mean is 0.75719.

One-Sample Test

This table provides the inferential statistics used to determine whether the sample mean is significantly different from the test value (65 inches). Key results include:

• t: The t-score is 1.057.
• df: The degrees of freedom is 9 (which is N – 1).
• Sig. (2-tailed): The p-value is 0.318.
• Mean Difference: The mean difference between the sample mean and the test value is 0.80000 inches.
• 95% Confidence Interval of the Difference: The lower bound is -0.9129 and the upper bound is 2.5129.

Interpreting the Output

In this case, the test is not significant because p > 0.05. There is no significant difference between the average height of our sample and the known average height of 65 inches.

Conclusion

We have learned how to perform a one-sample t-test in SPSS and interpret the results. Remember, the one-sample t-test is useful for comparing a sample mean to a known value. This is just one of the many tools in SPSS that can help us analyze data effectively.