Chapter 4
Dealing with Nonnormality via Response Transformations
No experiments are useless.
Thomas Edison
At the end of Chapter 3, we showed you how to check for normality—a fundamental assumption of the statistical analysis for design of experiments (DOE). In this chapter, we discuss how to deal with nonnormality (and nonconstant variance) via transformation of the response data. The most common transformation, the logarithm, is illustrated with a case study. This is the most complex DOE shown thus far: a two-level design on four factors, requiring 16 runs for all the combinations. After detailing this DOE, we will use fractional designs to squeeze more factors into the same number of runs.
Skating on Thin Ice
The data in this chapter comes ...
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