Use the normal probability plots to assess the requirement that your data follow a normal distribution.
If the normal distribution is a good fit for the data, the points form an approximately straight line and fall along the fitted line that is located between the confidence bounds. Departures from this straight line indicate departures from normality. If the p-value is greater than 0.05, you can assume that the data follow the normal distribution. You can evaluate the capability of your process using a normal distribution.
If the distributions differ for multiple variables, you should perform a separate capability analysis for each variable.
The capability histogram shows the distribution of your sample data for each variable. Each bar on the histogram represents the frequency of data within an interval.
Use the capability histogram to view your sample data in relation to the distribution fit and the specification limits.
For each variable, compare the solid overall curve to the bars of the histogram to assess whether your data are approximately normal. If the bars vary greatly from the curve, your data may not be normal and the capability analysis results might be inaccurate. If your data appear to be nonnormal, use Individual Distribution Identification to determine whether you should transform the data or fit a nonnormal distribution to perform the capability analysis.
If the distributions differ for multiple variables, you should perform a separate capability analysis for each variable.
For each variable, compare the solid overall curve and the dashed within curve in the histogram to see how closely the curves are aligned. A substantial difference between the curves may indicate that the process is not stable or that there is a significant amount of variation between subgroups for that variable. Use a control chart to assess whether your process is stable for the variable before you perform a capability analysis.
To determine the actual number of nonconforming items in your process, use the results for PPM < LSL, PPM > USL, and PPM Total. For more information, go to All statistics and graphs.
For a more thorough analysis of the assumptions for normal capability analysis, use Normal Capability Sixpack.