Introduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for ``statistical thinking'' by using examples drawn from actual case studies.
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Book Description
Editorial Reviews
Review
"In fact, [Statistics for Experimenters] might be [one of ] the most readable...books on statistical methods...would be a wonderful background for someone who wants to move into quality control. For such practical purposes, it exceeds any five books on mathematical statistics. The first three chapters are a superb introduction to statistical thinking, something that does not occur anywhere in most texts." -- The UMAP Journal
"It is hoped...that experimenters in all fields will be encouraged to read this text. " -- Biometrics
"The authors are to be congratulated for having written an excellent book. Students fortunate enough to have this as a text will have the opportunity to learn much, and not the least from the review questions and numerous well-contracted problems. Engineers wishing to advance their elementary understanding of statistical design and analysis will be delighted with this work. The writing is literate, and the technical aspects impeccable." -- Journal of Quality Technology
"It is hoped...that experimenters in all fields will be encouraged to read this text. " -- Biometrics
"The authors are to be congratulated for having written an excellent book. Students fortunate enough to have this as a text will have the opportunity to learn much, and not the least from the review questions and numerous well-contracted problems. Engineers wishing to advance their elementary understanding of statistical design and analysis will be delighted with this work. The writing is literate, and the technical aspects impeccable." -- Journal of Quality Technology
From the Publisher
Introduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for ``statistical thinking'' by using examples drawn from actual case studies.
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Most Helpful Customer Reviews
26 of 27 people found the following review helpful:
5.0 out of 5 stars
Outstanding book, but you should buy the newer edition, not this version,
This review is from: Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building (Hardcover)
All of the reviews on this book are generally consistent in their praise for the book and the authors. I do not have any points to add to the discussion other than this:It is a credit to this version of Statistics for Experimenters that it has remained relevant throughout the years as a classic introductory text that has kept selling consistently since it was released in the 1970's. Nevertheless, unless you have a particular reason for purchasing this version, you should purchase the updated version(also available through Amazon). The full title of the newer edition is: Statistics for Experimenters: Design, Innovation, and Discovery, 2nd Edition The 2nd edition, written in the same engaging and readable style as the 1st, contains virtually all of the content of the 1st edition plus advances in design of experiments that have happened since the 1st edition was published.
21 of 21 people found the following review helpful:
5.0 out of 5 stars
Immediate usability in practice.,
By Kenneth R Litko (Indiana) - See all my reviews
This review is from: Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building (Hardcover)
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.
28 of 30 people found the following review helpful:
5.0 out of 5 stars
classic text on design, well presented,
By
This review is from: Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building (Hardcover)
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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Inside This Book
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First Sentence:
Scientific research is a process of guided learning. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
external reference distribution, biased pennies, industrial experiment example, randomized paired comparison design, chain length regulator, appropriate reference distribution, random sampling hypothesis, tth treatment, collar screen, square replicated, combinatoric design, relevant reference set, lottery drum, block deviations, random sampling model, confounding pattern, central limit effect, confound main effects, randomization distribution, equiangular line, injection molding example, treatment deviations, experimental error variance, conceptual population, random sampling assumption Key Phrases - Capitalized Phrases (CAPs): (learn more)
Repeat Exercise, Industrial Experimentation, Applications of Statistics, Cambridge University Press, Peter Minerex New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Scientific research is a process of guided learning. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
external reference distribution, biased pennies, industrial experiment example, randomized paired comparison design, chain length regulator, appropriate reference distribution, random sampling hypothesis, tth treatment, collar screen, square replicated, combinatoric design, relevant reference set, lottery drum, block deviations, random sampling model, confounding pattern, central limit effect, confound main effects, randomization distribution, equiangular line, injection molding example, treatment deviations, experimental error variance, conceptual population, random sampling assumption Key Phrases - Capitalized Phrases (CAPs): (learn more)
Repeat Exercise, Industrial Experimentation, Applications of Statistics, Cambridge University Press, Peter Minerex New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 22
books:
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100
books
cite this book:
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- Time Series Analysis: Forecasting & Control (3rd Edition) by George Box on page 508, page 553, and page 605
- Experimental Designs by William Gemmel Cochran in Front Matter, page 279, and page 345
- Applied Regression Analysis (Wiley Series in Probability and Statistics) by Norman R. Draper on page 508, and page 553
- Applications of Statistics to Industrial Experimentation (Wiley Series in Probability and Statistics) by Cuthbert Daniel on page 345, and page 373
- Juran's Quality Control Handbook by J.M. Juran on page 583
See all 22 books this book cites
- Fundamental Concepts in the Design of Experiments by Charles R. Hicks on 6 pages
- Response Surfaces (Statistics: A Series of Textbooks and Monographs) by Andre I. Khuri on 5 pages
- Experimental Design in Biotechnology (Statistics: A Series of Textbooks and Monographs) by Perry D. Haaland on 5 pages
- Case Studies in Biometry by Nicholas Lange in Back Matter (1), and Back Matter (2)
- Evaluating E-Learning (The Astd E-Learning Series) by William Horton on page 39, and Back Matter
See all 100 books citing this book
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