t-Test
The example can teach you how to perform a t-Test in Excel. The t-Test is used to test the null hypothesis that the means of two populations are equal.
Below you can find the study hours of 6 female students and 5 male students.
H0: μ1 - μ2 = 0
H1: μ1 - μ2 ≠ 0
H1: μ1 - μ2 ≠ 0
![t-Test in Excel t-Test in Excel](https://www.excel-easy.com/examples/images/t-test/t-test-example.png)
To perform a t-Test, execute the following steps.
1. First, perform an F-Test to determine if the variances of the two populations are equal. This is not the case, because two populations are not equal here 😊.
2. On the Data tab, in the Analysis group, click Data Analysis.
![Click Data Analysis Click Data Analysis](https://www.excel-easy.com/examples/images/anova/click-data-analysis.png)
Note: can't find the Data Analysis button? Click here to load the Analysis ToolPak add-in.
3. Select t-Test: Two-Sample Assuming Unequal Variances and click OK.
![Select t-Test: Two-Sample Assuming Unequal Variances Select t-Test: Two-Sample Assuming Unequal Variances](https://www.excel-easy.com/examples/images/t-test/select-t-test-two-sample-assuming-unequal-variances.png)
4. Click in the Variable 1 Range box and select the range A2:A7.
5. Click in the Variable 2 Range box and select the range B2:B6.
6. Click in the Hypothesized Mean Difference box and type 0 (H0: μ1 - μ2 = 0).
7. Click in the Output Range box and select cell E1.
![t-Test Parameters t-Test Parameters](https://www.excel-easy.com/examples/images/t-test/t-test-parameters.png)
8. Click OK.
Result:
![t-Test Result in Excel t-Test Result in Excel](https://www.excel-easy.com/examples/images/t-test/t-test-result.png)
Conclusion: We do a two-tail test (inequality). lf t Stat < -t Critical two-tail or t Stat > t Critical two-tail, we reject the null hypothesis. This is not the case, -2.365 < 1.473 < 2.365. Therefore, we do not reject the null hypothesis. The observed difference between the sample means (33 - 24.8) is not convincing enough to say that the average number of study hours between female and male students differ significantly.
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