Statistics for Experimenters: Design, Innovation, and Discovery: 559 (Wiley Series in Probability and Statistics) - Tapa dura

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GEORGE E. P. BOX, PhD, DSc, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin–Madison. He is a Fellow of the Royal Society, an Honorary Fellow and Shewhart and Deming Medalist of the American Society for Quality and was awarded the Guy Medal in Gold of the Royal Statistical Society. He is also the recipient of the Samuel S. Wilks Memorial Medal of the American Statistical Association.

J. STUART HUNTER, PhD, DSc, is Professor Emeritus of Civil Engineering at Princeton University. Dr. Hunter is a member of the National Academy of Engineering and has served as consultant to many industries and government agencies. He has been a staff member of the National Academy of Sciences, Committee on National Statistics; statistician in residence at the University of Wisconsin; and is the founding editor of Technometrics.

The late WILLIAM G. HUNTER, PhD, was Professor of Statistics and Engineering at the University of Wisconsin–Madison.

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<b>The new classic</b> <p>For many years, the <i>First Edition</i> of <i>Statistics for Experimenters</i> has been a premier guide and reference for the application of statistical methods, especially as applied to experimental design. Rewritten and updated, this new edition of <i>Statistics for Experimenters</i> adopts the same approach as the landmark <i>First Edition</i> by demonstrating through worked examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the <i>Second Edition</i> provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from investigation and research. The authors' practical approach starts with a problem that needs to be solved and then illustrates the statistical methods best utilized in all stages of design and analysis.</p> <p>Providing even greater accessibility for its users, the <i>Second Edition</i> reflects new techniques and technologies developed since the publication of the classic First Edition.</p> <p><b>Among the new topics included are:</b></p> <ul> <li>Graphical analysis of variance</li> <li>Computer analysis to determine best follow-up runs</li> <li>Simplification by transformation</li> <li>Hands-on experimentation using response surface methods</li> <li>Further development of robust product and process design using split-plot arrangements and minimization of error transmission</li> <li>Introduction to process control, forecasting, and time series</li> <li>Illustrations demonstrating how multiresponse problems can be solved using the concepts of active and inert factor spaces and canonical spaces</li> <li>Bayesian approaches to model selection and sequential experimentation</li> <li>Applications for Six Sigma initiatives in a variety of disciplines</li> <li>Aappendix featuring Quaquaversal quotes from noted statisticians, scientists, and philosophers that embellish key concepts and enliven the learning process</li> </ul> <p>Computations in the <i>Second Edition</i> can be done utilizing the statistical language R. Functions for displaying ANOVA and lambda plots, Bayesian screening, and model building are all included, and R packages are available on a related FTP site. These topics can also be applied utilizing easy-to-use commercial software packages.</p> <p>Complete with applications covering the physical, engineering, biological, and social sciences, <i>Statistics for Experimenters</i> is designed for all individuals who must use statistical approaches to conduct an experiment. 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 an invaluable course book for undergraduate and graduate students.</p>