Black Belts learning to apply the Six Sigma methodology to ordered category data should know that there are alternate methods for analyzing discrete ordered category data that are specifically useful when structuring voice of the client processes.
Learn two of the common mistakes made during measurement system analysis and how to avoid them.
Measurement is more important than ever. How measurement systems are evaluated is influenced by the types of data gathered. A gage R&R evaluates systems for continuous data, attribute data can be analyzed using MSA to deal with discrete data.
Sometimes Six Sigma practitioners find a Y that is discrete and Xs that are continuous. How then can a regression equation be developed? The correct technique is something called logistic regression, but this tool is often not well understood.
The distribution of data can be categorized in two ways: normal and non-normal. Non-normal data does not tend toward a central value. It can be skewed left or right, or follow no particular pattern.
When it comes to understanding discrete data, quadrant plots can provide visual clues for Six Sigma project team leaders as to where they should focus their efforts when measuring program performance.