Tools
ANOVA
Models
Regression by Backwards Elimination
Data Transforms
Transformations used in Regression
Lack of Fit, Sum of Squares -The difference between the total sum of squares of the residuals and the pure error sum of squares in a regression analysis. It is a measure of lack of fit between the Experimental and the Fitted response. An F-test is used to express the significance of the lack of fit, which is expected to be non-significant for a well-fitted model.
Learn more about the Regression tools in Six Sigma Demystified (2011, McGraw-Hill) by Paul Keller, in his online Regression short course (only $99), or his online Black Belt certification training course ($875).