The volume deals with the exploration and optimization of response surfaces. Most common is the situation in which the underlying mechanism is not fully understood and the experimenter must approximate the unknown function with an appropriate empirical model. This empirical model is called a response surface model. The book assumes that readers have experience with statistical methods and matrix al-gebra. Formal coursework in basic principles of experimental design and regression analysis are also helpful, but not essential. This Second Edition of Response Surface Methodology is a major revision of the book. The authors have substantially re-written many sections to incorporate new material and ideas, new examples, and to more fully explain some topics that were only briefly mentioned in the first edition. They have also woven the computer more tightly into the presentation, relying on Design-Expert Version 6 for much of the computing, but also continuing to employ SAS and Minitab for some applications.

This book can be used as a text for a graduate course in experimental design, and is of use to applied statisticians, as well as engineers and chemical and physical sci-entists. It can also be used in industrial short courses and seminars for individuals with a wide variety of technical backgrounds.