โ Scribed by Douglas C. Montgomery
No coin nor oath required. For personal study only.
Learn How to Achieve Optimal Industrial Experimentation Through four editions, Douglas Montgomery has provided statisticians, engineers, scientists, and managers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. Now, in this fully revised and enhanced Fifth Edition, Montgomery has improved his best-selling text by focusing even more sharply on factorial and fractional factorial design and presenting new analysis techniques (including the generalized linear model). There is also expanded coverage of experiments with random factors, response surface methods, experiments with mixtures, and methods for process robustness studies. The book also illustrates two of today's most powerful software tools for experimental design: Design-Expert(r) and Minitab(r). Throughout the text, You'll find output from these two programs, along with detailed discussion on how computers are currently used in the analysis and design of experiments. You'll also learn how to use statistically designed experiments to: * Obtain information for characterization and optimization of systems * Improve manufacturing processes * Design and develop new processes and products * Evaluate material alternatives in product design * Improve the field performance, reliability, and manufacturing aspects of products * Learn how to conduct experiments effectively and efficiently Other important textbook features: * Student version of Design-Expert(r) software is available.
๐ SIMILAR VOLUMES
Readers will find this book an invaluable reference on the design of experiments. It contains hard-to-find information on topics such as change-over designs with residual effects and early treatment of analysis of covariance. Other topics include linear models and quadratic forms, experiments with o
The second volume of a revision of the 1952 work by Kempthorne (emeritus, statistics, Iowa State U.), now produced with collaboration by Hinkelmann (emeritus, statistics, Virginia Polytechnic U.), this advanced graduate level text provides mathematical coverage of generally applicable experimental d