# How to Perform a Normality Test on Minitab

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Before beginning to perform any statistical analysis of the given data, it is important to determine whether the data follows a normal distribution. If the data provided follows a normal distribution, you can use parametric tests (test of means) for additional levels of statistical analysis. If the data provided does not follow a normal distribution, you should use nonparametric tests (median test). As we all know, parametric tests are more powerful than non-parametric tests. Therefore, verifying the normality of the data provided becomes even more important.

1. Write a hypothesis. A good way to perform any statistical analysis is to start by writing a hypothesis. For a normality test, the null hypothesis is “The data follows a normal distribution” and the alternative hypothesis is “The data does not follow a normal distribution.”

2. Select data. Select and copy the data from the spreadsheet on which you want to test for normality.

3. Paste the data into a Minitab worksheet. Open Minitab and paste the data into the Minitab worksheet.

4. Press “Statistics”. On the Minitab menu bar, click Statistics.

5. Click on “Basic Statistics”.

6. Click on “Test for normality”

7. Select data. A small window called “Normal Test” will appear on the screen. Click on an available option within the white box, then click “Select.”

• Note that “VariableThe ” tab will have the name of the selected data.

• Also note that “Anderson-Darling” is already selected under “Tests for Normality”. Anderson-Darling is the most widely used normality test. Therefore, the default test selection for normality in Minitab is “Anderson-Darling”.

8. Press OK.”

9. Understand the p-value shown on the normal probability plot. A normal probability plot will appear on the screen.

• Note whether the p-value shown on the normal probability plot is greater than 0.05 or less than 0.05.

10. Conclude the results. As described in the hypothesis writing step, if we do not reject the null hypothesis, the conclusion will be “The data follow a normal distribution.” If we reject the null hypothesis, the conclusion will be “The data do not follow a normal distribution.” Let’s relate the p-value to the written hypothesis.

11. Do not reject the null hypothesis if the p-value is greater than 0.05. If the observed p-value on the normal probability plot is greater than 0.05, we cannot reject the null hypothesis. Therefore, the conclusion is “The data follow a normal distribution.”

12. Reject the null hypothesis if the p value is less than 0.05. If the observed p-value on the normal probability plot is less than 0.05, we reject the null hypothesis. Therefore, the conclusion is “The data do not follow a normal distribution.”