Use a normality test to provide a graphical and statistical (goodness-of-fit test) method to determine if the normal distribution fits your data. A common way to check normality is to use what is called the "fat pencil" test. The basis of this test is that if you laid a fat pencil over the plot, most of the plot points would be covered. If that is true, the distribution provides a reasonable fit for the data, which is usually all that is required.
When to Use | Purpose |
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Start of project | Check the assumption of reasonable normality for some of the statistics generated in a baseline capability analysis. |
Mid-project | Check the assumption of reasonable normality for many of the statistical tools used to determine whether an input has a significant effect on the output. |
End of project | Check the assumption of reasonable normality for some of the statistics generated in the improved process capability analysis. |
Your data must be continuous values.
If you have discrete numeric data from which you can obtain every equally spaced value and you have measured at least 10 possible values, you can evaluate these data as if they are continuous.
For more information, go to Insert an analysis capture tool.