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 clearand 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)
Statistical design of experiments is useful in virtually every quantitative field. Two-level factorial designs, which are the focus of this book, provide the most efficient plans for exploring the effects of many factors at once. Engineers, physical scientists, and all who conduct experiments will find this book indispensible. The analysis of 50 published experiments from diverse fields gives the book broad appeal.
Robert Mee
Excel Variance analysis of variance chemistry design distribution experiment marketing modeling neural networks processing quality search engine marketing (SEM) statistics transport
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)