Provides a graphical and statistical (goodness-of-fit test) method for checking distribution assumptions when using various statistical tools. For example, many tools assume that the data are at least reasonably normal. A common way to check this assumption is to use 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 | Checks the assumption of reasonable normality for some of the statistics generated in a baseline capability analysis. |
Mid-project | Checks 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 | Checks the assumption of reasonable normality for some of the statistics generated in the improved process capability analysis. |
Continuous data.