Six Sigma projects often deal with experiments whose outcomes are ordered categorical data, rather than continuous. It is important to know the right analysis methods for these cases, such as Jeng and Guos weighted probability-scoring scheme (WPSS).
Learn two of the common mistakes made during measurement system analysis and how to avoid them.
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.