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Independent Samples T-test

Independent Samples T-test

The independent samples t-test is used to compare two sample means from unrelated groups. This means that there are different people providing scores for each group. The purpose of this test is to determine if the samples are different from each other.

Basic Hypotheses

Null: The sample mean from Group 1 is not different from the sample mean from Group 2.
Alternative: The sample mean from Group 1 is significantly different from the sample mean from Group 2.

Real-World Examples
  • Finding differences between two groups.
    • Is Lowfya more effective at reducing depression symptoms than DepLo?
    • Do students that take the SAT Prep course score higher on the SAT than those that don't?
    • Is there a difference in income based on gender?

Reporting Results in APA Style

When reporting the results of the independent-samples t-test, APA Style has very specific requirements on what information should be included. Below is the key information required for reporting the results of the. You want to replace the red text with the appropriate values from your output.

t(degrees of freedom) = the t statistic, p = p value.

Example:
An independent-samples t-test was run to determine if the Mind Over Matter coping strategy was more effective at reducing anxiety than deep breathing exercises. The results showed that the participants using the Mind Over Matter strategy (M = 21, SD = 2.2) reported lower levels of anxiety than participants using deep breathing exercises (M = 28, SD = 2.7). This difference was significant (t(19) = 4.37, p < .01).
 

Notes:
  • When reporting the p-value, there are two ways to approach it. One is when the results are not significant. In that case, you want to report the p-value exactly: p = .24. The other is when the results are significant. In this case, you can report the p-value as being less than the level of significance: p < .05.
  • The t statistic should be reported to two decimal places without a 0 before the decimal point: .36
  • Degrees of freedom for this test are (n1 - 1) + (n2 - 1) or (n1 + n2) - 2, where "n1" represents the number of people in one group and "n2" represents the number of people in the other group. The n for each group can be found in the SPSS output.
     
Additional Resources

Laerd Statistics - Independent t-test guide
Khan Academy - Testing the difference between two means

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