|
Statistics for Experimenters: Design, Innovation, and Discovery , 2nd Edition | 
 enlarge | Authors: George E. P. Box, J. Stuart Hunter, William G. Hunter
Publisher: Wiley-Interscience
Category: Book
List Price: $121.95
Buy New: $89.98
You Save: $31.97 (26%)
New (25) Used (15) from $89.49
Rating:  7 reviews
Sales Rank: 70590
Media: Hardcover
Edition: 2
Pages: 664
Number Of Items: 1
Shipping Weight (lbs): 2.4
Dimensions (in): 9.3 x 6.3 x 1.4
ISBN: 0471718130
Dewey Decimal Number: 519.5
EAN: 9780471718130
Publication Date: June 14, 2005
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: Brand New, Perfect Condition, Please allow 4-14 business days for delivery. 100% Money Back Guarantee, Over 1,000,000 customers served.
| |
| Similar Items:
|
| Editorial Reviews:
Product Description
A Classic adapted to modern times Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the Second Edition provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from research data, illustrating how these tools may best be utilized during all stages of the investigative process. The authors’ practical approach starts with a problem that needs to be solved and then examines the appropriate statistical methods of design and analysis. Providing even greater accessibility for its users, the Second Edition is thoroughly revised and updated to reflect the changes in techniques and technologies since the publication of the classic First Edition. Among the new topics included are: - Graphical Analysis of Variance
- Computer Analysis of Complex Designs
- Simplification by transformation
- Hands-on experimentation using Response Service Methods
- Further development of robust product and process design using split plot arrangements and minimization of error transmission
- Introduction to Process Control, Forecasting and Time Series
- Illustrations demonstrating how multi-response problems can be solved using the concepts of active and inert factor spaces and canonical spaces
- Bayesian approaches to model selection and sequential experimentation
An appendix featuring Quaquaversal quotes from a variety of sources including noted statisticians and scientists to famous philosophers is provided to illustrate key concepts and enliven the learning process. All the computations in the Second Edition can be done utilizing the statistical language R. Functions for displaying ANOVA and lamba plots, Bayesian screening, and model building are all included and R packages are available online. All theses topics can also be applied utilizing easy-to-use commercial software packages. Complete with applications covering the physical, engineering, biological, and social sciences, Statistics for Experimenters is designed for individuals who must use statistical approaches to conduct an experiment, but do not necessarily have formal training in statistics. Experimenters need only a basic understanding of mathematics to master all the statistical methods presented. This text is an essential reference for all researchers and is a highly recommended course book for undergraduate and graduate students.
|
| Customer Reviews: Read 2 more reviews...
 Long-awaited update to a classic October 17, 2005
K. Fung (New York, USA)
20 out of 21 found this review helpful
This is the best applied book in any scientific or mathematical subject that I have ever read. The reviewers who are looking for equations and the typical assumptions-theory-proof presentation just picked up the wrong book.
If you're interested in applying experimental design to real-world problems, this book is indispensable. The authors help you get inside the math and really understand the important and often profound issues. It is easy to write a book that regurgitates equations and proofs; it is a major accomplishment to bring to bear decades of practical insights.
I still need to read the 2nd edition in detail and I plan to spend as much time as needed. Based on my brief reading of selected sections, the authors have retained the same style which has made their 1st edition a classic.
A Great Book Updated July 26, 2005
John Hunter (Arlington, VA United States)
21 out of 26 found this review helpful
A classic updated. The first edition, written in 1978, has 8 ratings of 5 stars and one of 4 stars ("due to it's age") on Amazon.
As Six Sigma grew in popularity many more organizations discovered the power of design of experiments, as developed by Sir Ronald Fisher. George Box, was his student. He built on the ideas of Fisher and together with the other authors created a book that had already become the classic reference for designed experiments and how to apply statistics to improve results before the term "Six Sigma" was coined. The new edition retains the clear and friendly writing style of the original and adds some new tools to the experimenters toolbox (as mentioned in the publishers text above).
I am biased as my father was one of the 3 authors of the original book and the second edition is dedicated to him. Luckily, you don't have to take my word for it, many others regard this book as the primary resource for design of experiments.
Statistics for Experimenters is a tool that is used frequently (not a book gathering dust on the shelf) by many experimenters, engineers, Six Sigma experts and others as they use experiments to learn, innovate and improve.
BHH, 2nd Edition January 7, 2008
George Samaras (Pueblo, CO USA)
3 out of 3 found this review helpful
Superb! If you are involved, in any way, with science or engineering, you need this book on your shelf (after you have carefully read it twice). My only complaint is that I found out about it circuitously reading Prof. Box's "Improving Almost Anything"; I was curious what the often cited BHH reference was. I think someone should have a word with the publisher's marketing department; if we don't know about it, how are we supposed to buy it?
classic revised February 22, 2008
Michael R. Chernick (Holland PA)
14 out of 14 found this review helpful
I am a mathematical statistician and I appreciate and understand modern books on experimental designs such as the book by Wu and Hamada. However the first edition of this book became an immediate classic because George Box is a genius and is a rare bread of statisticians who have strong theoretical and practical experience in statistical methods and in this case statistical design. Stu Hunter and Bill Hunter are two other statisticians with strong applied backgrounds in engineering and other applications of experimental design. Before you can appreciate the theory you need to understand the theory. The first edition of this book presented the concepts beautifully. This was a great help to me as I had learned the theory and the construction of factorial designs, fractional factorial designs and incomplete block designs but never had a clear understanding of when to use them until I read this book. Other important simple designs of great practical importance are also covered extremely well.
I wrote a review of the first edition of this text. John Hunter appreciated it so much that he wrote a very touching email to me on this and he was very kind to send me a complimentary copy of the second edition. John is the son of Bill Hunter. Unfortunately Bill past away before this second edition was conceived. I believe it was partly as a tribute to Bill that George Box and Stu Hunter put together this revised edition. The spirit and philosophy of the first edition has been maintained and since the first edition had appear way back in 1978 the production of an updated edition is welcome and way over due.
Please read the book review by John Hunter. He is very upfront about his bias for his father but what he writes is honest and comes from an interesting and unique persepctive.
 Not ideal for planning biomedical studies August 20, 2006
Brant Inman (Somewhere out there)
3 out of 8 found this review helpful
I have found it very difficult to identify a good book on study design for the biomedical industry as most are too focused on engineering/manufacturing applications. Though this book does discuss many different study designs and their theoretical underpinnings well, it does not do a very good job of explaining the issues of sample size and power. These issues are critical to designing studies in biologic settings.
If one is planning experiments on animals, it is mandatory to design studies that minimize the number of animals required to answer the scientific question at hand--given pre-specified levels of statistical power and effect size. Similarly, when experiments are conducted on humans (i.e. clinical trials) it is important to include enough patients so that adequate precision is obtained. I wish this book discussed better how to find the appropriate number of replications required to optimize experimental conclusions (like the interactions terms in a factorial experiment, for instance).
|
|
|
| |
