Experiments: Planning, Analysis, and Parameter Design Optimization

Praise for the First Edition:'If you... want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library.'—Journal of the American Statistical AssociationFully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments, Second Edition introduces some of the newest discoveries—and sheds further light on existing ones—on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences.The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including:Expected mean squares and sample size determinationOne-way and two-way ANOVA with random effectsSplit-plot designsANOVA treatment of factorial effectsResponse surface modeling for related factorsDrawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study.Experiments, Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians.C. F. Jeff Wu, PhD, is Coca-Cola Professor in Engineering Statistics at the Georgia Institute of Technology. Dr. Wu has published more than 130 papers and is the recipient of numerous accolades, including the National Academy of Engineering membership and the COPSS Presidents'Award.Michael S. Hamada, PhD, is Statistical Scientist at Los Alamos National Laboratory in New Mexico. Dr. Hamada is a Fellow of the American Statistical Association and the author of more than seventy published papers. Praise for the First Edition : "If you . . . want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library." Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments , Second Edition introduces some of the newest discoveriesand sheds further light on existing oneson the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences. The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including: Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study. Experiments , Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians. Title Page......Page 1 CONTENTS......Page 5 Preface to the Second Edition......Page 15 Preface to the First Edition......Page 17 Suggestions of Topics for Instructors......Page 21 1. Basic Concepts for Experimental Design and Introductory Regression Analysis......Page 29 2. Experiments with a Single Factor......Page 73 3. Experiments with More than One Factor......Page 115 4. Full Factorial Experiments at Two Levels......Page 183 5. Fractional Factorial Experiments at Two Levels......Page 239 6. Full Factorial and Fractional Factorial Experiments at Three Levels......Page 294 7. Other Design and Analysis Techniques for Experiments at More than Two Levels......Page 346 8. Nonregular Designs: Construction and Properties......Page 398 9. Experiments with Complex Aliasing......Page 448 10. Response Surface Methodology......Page 486 11. Introduction to Robust Parameter Design......Page 538 12. Robust Parameter Designfor Signal-Response Systems......Page 590 13. Experiments for Improving Reliability......Page 626 14. Analysis of Experiments with Nonnormal Data......Page 652 References......Page 688 App. A: Upper Tail Probabilities of the Standard Normal Distribution......Page 690 App. B: Upper Percentiles of the t Distribution......Page 692 App. C: Upper Percentiles of the X 2 Distribution......Page 694 App. D: Upper Percentiles of the F Distribution......Page 696 App. E: Upper Percentiles of the Studentized Range Distribution......Page 704 App. F: Upper Percentiles of the Studentized Maximum Modulus Distribution......Page 712 App. G: Coefficients of Orthogonal Contrast Vectors......Page 726 App. H: Critical Values for Lenth's Method......Page 728 Author Index......Page 732 SUBJECT INDEX......Page 736