Response Surface Methodology

Part of the Springer Texts in Statistics book series (STS)


Experiments for fitting a predictive model involving several continuous variables are known as response surface experiments. The objectives of response surface methodology include the determination of variable settings for which the mean response is optimized and the estimation of the response surface in the vicinity of this good location. The first part this chapter discusses first-order designs and first-order models, including lack of fit and the path of steepest ascent to locate the optimum. The second part of the chapter introduces second-order designs and models for exploring the vicinity of the optimum location. The application of response surface methodology is demonstrated through a real experiment. The concepts introduced in this chapter are illustrated through the use of SAS and R software.


Response surface Steepest ascent First-order design Second-order design Polynomial regression Center points Central composite designs Canonical analysis 

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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.The Ohio State UniversityColumbusUSA
  2. 2.Wright State UniversityDaytonUSA
  3. 3.Franklin & Marshall CollegeLancasterUSA

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