Springer A Comprehensive Guide to Factorial Two-Level Experimentation

With applications in virtually every quantitative field, the statistical design of experiments is a useful skill. Practitioners wanting to expand their repertoire will find this book a helpful guide, while examples from many fields give the book broad appeal. Review From the reviews: “Robert Mee’s new work on two-level factorial designs is an unusually good statistics book, which should be bought and read by anyone with even a passing interest in the subject. This book covers almost everything users of two-level factorial designs need to know. Experimenters, statistical consultants, and researchers will all learn a lot and find plenty of new ideas to think about. …Careful thought has been given to how to describe every single topic. The result is a book that deserves to become a classic.” (Biometrics) “Mee’s new book is … a comprehensive guide to factorial two-level experimentation. … I believe this book will help nonstatisticians and statisticians … plan and analyze factorial experiments correctly. The breadth, depth, and clarity of this book make it a valuable asset for anyone using two-level of factorial designs. The large number of examples … adds much to the book’s utility. … Overall, this is an excellent reference book … . it should be in the library of anyone who uses two-level factorial designs.” (Lewis VanBrackle, Technometrics, Vol. 52 (4), November, 2010) From the Back Cover Factorial designs enable researchers to experiment with many factors. The 50 published examples re-analyzed in this guide attest to the prolific use of two-level factorial designs. As a testimony to this universal applicability, the examples come from diverse fields: Analytical Chemistry Animal Science Automotive Manufacturing Ceramics and Coatings Chromatography Electroplating Food Technology Injection Molding Marketing Microarray Processing Modeling and Neural Networks Organic Chemistry Product Testing Quality Improvement Semiconductor Manufacturing Transportation Focusing on factorial experimentation with two-level factors makes this book unique, allowing the only comprehensive coverage of two-level design construction and analysis. Furthermore, since two-level factorial experiments are easily analyzed using multiple regression models, this focus on two-level designs makes the material understandable to a wide audience. This book is accessible to non-statisticians having a grasp of least squares estimation for multiple regression and exposure to analysis of variance. Robert W. Mee is Professor of Statistics at the University of Tennessee. Dr. Mee is a Fellow of the American Statistical Association. He has served on the Journal of Quality Technology (JQT) Editorial Review Board and as Associate Editor for Technometrics. He received the 2004 Lloyd Nelson award, which recognizes the year’s best article for practitioners in JQT. "This book contains a wealth of information, including recent results on the design of two-level factorials and various aspects of analysis… The examples are particularly clear and insightful." (William Notz, Ohio State University "One of the strongest points of this book for an audience of practitioners is the excellent collection of published experiments, some of which didn’t ‘come out’ as expected… A statistically literate non-statistician who deals with experimental design will have plenty of motivation to read this book, and the payback for the effort will be substantial." (Max Morris, Iowa State University)