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Hardcover Design and Analysis of Experiments Book

ISBN: 047148735X

ISBN13: 9780471487357

Design and Analysis of Experiments

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Book Overview

Now in its 6th edition, this bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. Douglas Montgomery arms readers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. He shows how to use statistically designed experiments to obtain information for characterization and optimization of systems, improve manufacturing processes, and design and develop new processes and products. You will also learn how to evaluate material alternatives in product design, improve the field performance, reliability, and manufacturing aspects of products, and conduct experiments effectively and efficiently. Discover how to improve the quality and efficiency of working systems with this highly-acclaimed book. This 6th Edition: Places a strong focus on the use of the computer, providing output from two software products: Minitab and DesignExpert. Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects. Includes detailed discussions on how computers are currently used in the analysis and design of experiments. Offers new material on a number of important topics, including follow-up experimentation and split-plot design. Focuses even more sharply on factorial and fractional factorial design.

Customer Reviews

5 ratings

Pretty Good Experimental Design Textbook

I really liked reading and learning about Experimental Analysis and Design from this book. I think it is pretty well paced, and quite well illustrated with many examples. I addition, the author also provides an online space with further expansion to the ideas presented in the book, as well as digital resources to all the data used in solved examples, as well as question problems. I strongly recommend this book for anyone with moderate statistical backgrouns, wishing to learn about experimental design and analysis.

EXCELLENT BOOK

This is the best book for beginners to DOE, students and for future reference. Chapters 12 and 13 are useful for people interested on Gauge R & R studies (variance components models) and for those that have to understand and apply ISO/IEC 5725 standards at the laboratory. A lot of references are listed at the end of the book.

Great DOE book

Having taken two experimental design classes with Dr. Montgomery himself, hands down this book is excellent, as is the author himself. A lot of the material that we used in our advanced level experimental design class comes from the extra material that is available for free of off the books supplemental website, and there is a great wealth of more advanced material in there that is worth printing off, and there is a lot of supplemental material. So if you feel solid on what is in the textbook, tackle the supplemental material to further delve into DOE topics. The book uses numerous examples using SAS, Minitab and Design-Expert and lots of enjoyable practice problems, so following along using any of the packages is pretty easy.

great DOE book for engineers

Doug Montgomery is an engineer with great statistical training. This enabled him to be a great teacher for statistical practitioners and an author of several excellent applied books in the design and analysis of experimental data and statistical process control. This book is one of the best sources for Design of Experiments for engineers, currently a very important topic in industry. He provides a wealth of information on classical designs and the analysis of variance models. In addition he provides a balanced perspective on the value of Taguchi designs. Other topics covered include response surface methods, evolutionary operation and mixture experiments.

A good blend of theory and practical examples.

This book, along with the Box, Hunter, and Hunter book (also available by Wiley) are good references for the experimenter.
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