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Rating: 
Summary: very useful
Review: A great book to understand the theory and the application of statistics. The examples used in each chapter are very useful in understanding the concept.
I suggest this book to every researcher and instructer to keep it on their desks. "This" is the reference.
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Summary: Get a more recent title for the important modern advances
Review: A solid excellent DOE book, however due to it's age, it obviously does not cover more recent topics, such as mixture experiments. I've run into a few chemical engineers that have read only this book and have no idea what mixture experiments are, and why they are important in their DOE work. Also, I do not remember seeing any material on split-plot designs, and this topic is very important in industrial experimentation since most experiments are split-plots whether you know it or not, and you cannot evaluate them as normal. This is no fault of the book due to its publish date, but a newer book, such as Montgomery's or Hamada & Wu should also be read through to learn about the more recent advancements in DOE.
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Summary: Applying Statistics to Industry has never been easier...
Review: Application of statistics in an industrial setting is often perceived as being difficult and time-consuming. This book clearly demonstrates that the use of experimental design not only enables a wider range of conclusions to be made, but the use of designs can minimizes the time, effort and cost required to obtain the results. George Box presents the theory clearly with many real-life industrial examples. It is the application of the theories to the examples which thoroughly convince the reader that the combination of a knowledge in ones area of expertise and the application of statistics can lead to extraordinarily promising results.
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Summary: Still the "Bible" of practical design of experiments.
Review: More than twenty years after its publication, this seminal work is still the undisputable "Bible" for users of statistical experimental design. The practical insights sprinkled throughout this book are invaluable especially to non-mathematical statisticians. This book will never be out-of-date!
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Summary: Excellent Book for the Statistically Challenged!!
Review: Not being a statistician but needing to understand Design of Experiments, I found this book to be extremely valuable. Box walks you thru the basic concepts through prediction and understanding of complex response surfaces. After taking it out of the library twice, I decided it was important to get my own copy. I now recommend it in every class I teach on optimization using finite element methods. DoE adds a whole new dimension to product performance simulation.
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Summary: classic but unconventional and practical book on design
Review: This book was published in 1978 but as other reviewers have noted its practical methods and advice are timeless. George Box and Stu Hunter are both very famous statisticians who are also great teachers and lecturers. Bill Hunter is now deceased. All three authors have made major contributions to the design of experiments. The book is written for practitioners and in the simplest language possible. Emphasis is placed on practical designs and not optimal designs because optimal designs are very sensitive to model specification.It does not include the robust designs of Taguchi which came later and could easily be included if the authors choose to revise it.
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Summary: Immediate usability in practice.
Review: This is an excellently written book with clear examples of how to apply statistics to everyday experimental settings. Box delves deep enough into the underlying theory to give an engineer such as myself an appreciation for the "reality" of the mathematics, but sticks to concrete examples and putting theory into practice. Each chapter follows the previous one, but each is also reasonably self-contained. Terminology is easily clarified with a quick use of the comprehensive index. Additionally, don't let the print date fool you... the book is timely.
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Summary: This text is the classic text referred to by other authors!
Review: This text has become a classic text on the subject of the statistical design of experiments. You will find this text footnoted, bibliographied, or listed as recommended reading in most of the books published on the subject today. The authors' approach to evaluating results by direct observation using graphs and plots of results helps the user to visualize the results of experiments. This is in contrast with others whose sole tool seems to be use of ANOVA methods alone. The authors also present helpful methods of data transformation and easy calculation of results. They also provide insight into correct design of an experimental model, and an easy method of sequential model building so that the user can build a larger model depending upon the results of his/her first effort. This book is an excellent value!
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