Neural networks are worth surveying as part of the extended data mining and modeling toolkit. Of particular interest is the comparison of more traditional tools like regression analysis to neural networks as applied to empirical model-building.
A quick and easy-to-remember way for Lean Six Sigma practitioners to get the most benefit from simple linear regression analysis is with a simple check-up method. The method borrows and adapts the familiar concept found in the 5S tool.
Details of the use of linear regression are often considered difficult or confusing by those practitioners just beginning to delve into the Six Sigma toolkit. Making sense of the process starts at a basic level.
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.
