Two-Sample T-Test in SPSS

I often use two-sample t-tests as an introduction to SPSS in my undergraduate statistics courses – and sometimes my graduate courses, too.  Because the students are still getting used to functions in SPSS, they tend to have many difficulties with this lesson.  For this reason, I created the page below to provide an easy-to-read guide on performing two-sample t-tests in SPSS.  As always, if you have any questions, please email me a MHoward@SouthAlabama.edu!


Before learning about two-sample t-tests in SPSS, we must first know what a two-sample t-test is used for.  The textbook definition says that a two-sample t-test is used to “determine whether two sets of data are significantly different from each other”; however, I am not a fan of this definition.  Instead, I prefer to say that a two-sample t-test is used to “test whether the means of a measured variable in two groups is significantly different.”  So, a two-sample t-test is used to answer questions that are similar to the following:

  • In our sample, do women have better test grades than men?
  • Are men taller than women?
  • Do people in a class taught by Dr. Howard perform better on a test than those in Dr. Smith’s class?
  • Do employees in Training Group A have better performance than Training Group B?

Now that we know what a two-sample t-test is used for, we can now calculate a two-sample t-test in Excel!  To begin, open your data in Excel.  If you don’t have a dataset, download the example dataset here. In the example dataset, we are comparing the test grades of two classes (Dr. Howard and Dr. Smith) to determine which class has higher grades on an exam.

The data should look something like this:

Two-Sample T-Test in SPSS 1

If it doesn’t, you may need to reformat your dataset.  It may be difficult to follow along if your dataset looks differently.

We first need to make a new grouping variable, because our current grouping variable in our dataset (Class) consists of fairly long text.  In SPSS, a two-sample t-test must be performed with a grouping variable that contains numerical values or very short text.  So, we need to create a new variable with 0s for everyone in Dr. Howard’s class and 1s for everyone in Dr. Smith’s class, which is called a dummy-coded variable.  Fortunately, creating a dummy variable is fairly easy.

To start this process, click on Transform and then Recode into Difference Variables.

Two-Sample T-Test in SPSS 2

You should then have a window that looks like the one below:

Two-Sample T-Test in SPSS 3

We are going to recode the Class variable.  Click on Class, then click on the highlighted arrow.

Two-Sample T-Test in SPSS 3b

This will place Class in the other window, as seen below:

Two-Sample T-Test in SPSS 4

We then want to give our new dummy-coded variable a name.  Let’s call it DumCode.  To do so, type DumCode into the Name and Label boxes.  Then click Change.

Two-Sample T-Test in SPSS 5

Afterwards, we want to assign the new values to our DumCode variable.  Click on Old and New Values.

Two-Sample T-Test in SPSS 6

The window seen below should pop up:

Two-Sample T-Test in SPSS 7

We want to recode our groups as 0 and 1.  To start, we’ll type Dr. Howard in the Old Value box, and we’ll type 0 in the New Value box.  Then, we’ll press add.

Two-Sample T-Test in SPSS 8

The result should look like the window below:

Two-Sample T-Test in SPSS 9

Now, we’ll type Dr. Smith in the Old Value box, and 1 in the New Value box.  Press Add again.

Two-Sample T-Test in SPSS 10

Press Continue.

Two-Sample T-Test in SPSS 11

And then OK.

Two-Sample T-Test in SPSS 12

Does your data now look like the image below?  If so, great!  If not, review the instructions above to see what happened.  You’ll need this dummy-coded variable to perform the actual two-sample t-test.

Two-Sample T-Test in SPSS 13

To conduct the actual two-sample t-test, we’ll want to click on Analyze, Compare Means, and then Independent-Samples T-Test.

Two-Sample T-Test in SPSS 14

The following window should pop up.

Two-Sample T-Test in SPSS 15

We’ll first want to put our outcome variable, Test Grades, into the test variable window.  To do so, click on Test Grades and then click on the arrow highlighted below.

Two-Sample T-Test in SPSS 15b

Next, we’ll want to identify our grouping variable.  Click on our dummy-coded variable, DumCode, and then click on the arrow highlighted below.

Two-Sample T-Test in SPSS 16

Once DumCode is in the Grouping Variable window, you’ll want to click on Define Groups.

Two-Sample T-Test in SPSS 17

The following window should pop up.

Two-Sample T-Test in SPSS 18

You’ll  want to enter the dummy-coded values, 0 and 1, into the Group 1 and Group 2 boxes, as seen below.  Then press continue.

Two-Sample T-Test in SPSS 19

Now press OK.

Two-Sample T-Test in SPSS 20

We should get results.  Yay!

Two-Sample T-Test in SPSS 21

We’ll first want to look at Levene’s Test for Equality of Variances.  If it is significant, we cannot assume equal variances.  If it is not significant, we can assume equal variances.  From looking below, the p-value for Levene’s Test of Equality of Variances is not significant (p > .05), so equal variances can be assumed.

Two-Sample T-Test in SPSS 21b

Looking at the equal variances assumed line, we can see that the results of the t-test are statistically significant (p < .05).  This indicates that a significant mean difference exists in the test scores of Dr. Howard’s class and Dr. Smith’s class; however, this result will not tell you which group scored higher.

Two-Sample T-Test in SPSS 21c

To determine the nature of this mean difference, we must look at the group means.  As we can see below, Group 0 had a much higher test average than Group 1.  If we remember our dummy-coded values, Dr. Howard was Group 0 and Dr. Smith was Group 1.  Thus, we can say that there is a significant difference in the mean test scores of Dr. Howard and Dr. Smith, with Dr. Howard’s class having higher grades than Dr. Smith.

Two-Sample T-Test in SPSS 21d

Together, we can identify that…

  • The test statistic is: 2.783
  • The p-value is .012 (< .05)
  • The mean of Dr. Howard’s class is 88.5
  • The mean of Dr. Smith’s class is 75.3
  • Dr. Howard’s class performed significantly better than Dr. Smith’s class.

We did it! We calculated everything that we needed to know about the two-sample t-test! Good work!

Do you still have any questions?  Or comments about this guide?  Feel free to email me at MHoward@SouthAlabama.edu.  I am always happy to chat!