4Modeling Formulation Data
“All models are wrong, but some are useful.”
George E. P. Box
Overview
Empirical modeling--fitting equations to data--is a process that can be studied and improved. It involves a lot of science, and a fair amount of art as well. When applied to formulation data, there are also some unique aspects that need to be kept in mind. In this chapter, we discuss the fundamentals of building good models, such as critical model evaluation. Also covered are the unique circumstances to consider when fitting formulation models. We focus on response surface models in this chapter and will address screening models in subsequent chapters.
CHAPTER CONTENTS
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