This volume on the design of experiments covers two-level factorial and fractional factorial designs, and some aspects of empirical modelling with regression techniques. It also concentrates on response surface methodology, mixture experiments, and robust design methodology. The text includes many examples of the applications of this methodology and illustrates how the computer can be a useful aid in problem-solving.
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Gets you quickly up and running with the full range of powerful statistical experimental design, modeling, and optimization techniques
Coauthored by widely recognized experts in the fields of quality control and the design of experiments, this book is a practical guide to Response Surface Methodology (RSM) the process of identifying and fitting an appropriate response surface model from experimental data. While in the opening chapters the authors lay down the basic conceptual groundwork preliminary to a working understanding of the methods described, the bulk of the book is devoted to providing students and professionals with clear, step–by–step guidance on the use of powerful statistical and empirical modeling techniques that have proven their efficacy in industry. Throughout, numerous real–world examples help illuminate critical points covered, and chapter–end problems help you to gauge your command of the concepts and procedures described. Important topics covered include:
Providing clear, hands–on guidance to the application of some of today′s most useful techniques, Response Surface Methodology is an essential working resource for process development and quality engineering professionals, engineering designers, product formulators, engineers, chemists, and all those whose professional activities involve the design of experiments.
Raymond H. Myers, PhD, is Professor Emeritus in the Department of Statistics at Virginia Polytechnic Institute and State University. He has over forty years of academic experience in the areas of experimental design and analysis, response surface analysis, and designs for nonlinear models. A Fellow of the American Statistical Society, Dr. Myers has authored or coauthored numerous journal articles and books, including Generalized Linear Models: With Applications in Engineering and the Sciences, also published by Wiley.
Douglas C. Montgomery, PhD, is Regents′ Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery has over thirty years of academic and consulting experience and has devoted his research to engineering statistics, specifically the design and analysis of experiments. He has authored or coauthored numerous journal articles and twelve books, including Generalized Linear Models: With Applications in Engineering and the Sciences; Introduction to Linear Regression Analysis, Fourth Edition; and Introduction to Time Series Analysis and Forecasting, all published by Wiley.
Christine M. Anderson–Cook, PhD, is Project Leader a t the Los Alamos National Laboratory, New Mexico. Dr. Anderson–Cook has over ten years of academic and consulting experience and has written numerous journal articles on the topics of design of experiments and response surface methodology.
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