Wendell F. Smith
ASA-SIAM Series on Statistics and Applied Probability 15
I have long awaited Dr. Smith's text and now that it is in print I am pleased to offer my heartiest congratulations on a job well done. I am very impressed by the amount of discussion in the text devoted to the topics of model building and model evaluation and I hope the software companies that support the fitting of mixture models will incorporate the topics discussed in the text in their software. -- John A. Cornell, Professor Emeritus of Statistics, University of Florida.
Many products, such as foods, personal-care products, beverages, and cleaning agents, are made by mixing ingredients together. This book describes a systematic methodology for formulating such products so that they perform according to one’s goals, providing scientists and engineers with a fast track to the implementation of the methodology. Experimental Design for Formulation contains examples from a wide variety of fields and includes a discussion of how to design experiments for a mixture setting and how to fit and interpret models in a mixture setting. It also introduces process variables, the combining of mixture and nonmixture variables in a designed experiment, and the concept of collinearity and the possible problems that can result from its presence.
Experimental Design for Formulation is a useful manual for the formulator and can also be used by a resident statistician to teach an in-house short course. Statistical proofs are largely absent, and the formulas that are presented are included to explain how the various software packages carry out the analysis. Many examples are given of output from statistical software packages, and the proper interpretation of computer output is emphasized. Other topics presented include a discussion of an effect in a mixture setting, the presentation of elementary optimization methods, and multiple-response optimization wherein one seeks to optimize more than one response.
This book is intended for formulators in industry as well as senior undergraduate and beginning graduate students in statistics. Although it evolved from material the author developed for an American Chemical Society short course for students from the industrial community, the book is suitable for a wider audience that includes students and researchers in the physical sciences, engineering disciplines, and statistics. It is assumed the reader is familiar with basic experimental designs and methods for modeling data and interpreting models in these settings.
List of Figures; List of Tables; Preface; Part I: Preliminaries. Chapter 1: Introduction; Chapter 2: Mixture Space; Chapter 3: Models for a Mixture Setting; Part II: Design. Chapter 4: Designs for Simplex-Shaped Regions; Chapter 5: Designs for Non-Simplex-Shaped Regions; Chapter 6: Design Evaluation; Chapter 7: Blocking Mixture Experiments; Appendix 7A: Mates for Latin Squares of Order 4 and 5; Part III: Analysis. Chapter 8: Building Models in a Mixture Setting; Chapter 9: Model Evaluation; Chapter 10: Model Revision; Chapter 11: Effects; Chapter 12: Optimization; Part IV: Special Topics. Chapter 13: Including Process Variables; Chapter 14: Collinearity; Bibliography; Index.
2005 / xx + 367 pages / Softcover / ISBN-13: 978-0-898715-80-4 / ISBN-10: 0-89871-580-6 /
List Price $113.50 / ASA/SIAM Member Price $79.45 / Order Code SA15