"Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one." ―The American Statistician "The book is well written and has many exercises. It can serve as a very good textbook for scientists and engineers, with only basic statistics as a prerequisite. I also highly recommend it to practitioners who want to solve real-life prediction problems." (Computing Reviews) Modern Regression Methods, Second Edition maintains the accessible organization, breadth of coverage, and cutting-edge appeal that earned its predecessor the title of being one of the top five books for statisticians by an Amstat News book editor in 2003. This new edition has been updated and enhanced to include all-new information on the latest advances and research in the evolving field of regression analysis. The book provides a unique treatment of fundamental regression methods, such as diagnostics, transformations, robust regression, and ridge regression. Unifying key concepts and procedures, this new edition emphasizes applications to provide a more hands-on and comprehensive understanding of regression diagnostics. New features of the Second Edition include: <ul>
<li>A revised chapter on logistic regression, including improved methods of parameter estimation</li> <li>A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression</li> <li>A wealth of new and updated exercises with worked solutions</li> <li>An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures</li> <li>Updated references at the end of each chapter that direct the reader to the appropriate resources for further study</li> </ul>
An accessible guide to state-of-the-art regression techniques, Modern Regression Methods, Second Edition is an excellent book for courses in regression analysis at the upper-undergraduate and graduate levels. It is also a valuable reference for practicing statisticians, engineers, and physical scientists.

Modern Regression Methods

Science & Math

Ryan, Thomas P.

Mathematics

Wiley-Interscience

An introductory perspective on statistical applications in the field of engineering Modern Engineering Statistics presents state-of-the-art statistical methodology germane to engineering applications. With a nice blend of methodology and applications, this book provides and carefully explains the concepts necessary for students to fully grasp and appreciate contemporary statistical techniques in the context of engineering. With almost thirty years of teaching experience, many of which were spent teaching engineering statistics courses, the author has successfully developed a book that displays modern statistical techniques and provides effective tools for student use. This book features: <ul>
<li> Examples demonstrating the use of statistical thinking and methodology for practicing engineers </li> <li> A large number of chapter exercises that provide the opportunity for readers to solve engineering-related problems, often using real data sets </li> <li> Clear illustrations of the relationship between hypothesis tests and confidence intervals </li> <li> Extensive use of Minitab and JMP to illustrate statistical analyses </li> </ul>
The book is written in an engaging style that interconnects and builds on discussions, examples, and methods as readers progress from chapter to chapter. The assumptions on which the methodology is based are stated and tested in applications. Each chapter concludes with a summary highlighting the key points that are needed in order to advance in the text, as well as a list of references for further reading. Certain chapters that contain more than a few methods also provide end-of-chapter guidelines on the proper selection and use of those methods. Bridging the gap between statistics education and real-world applications, Modern Engineering Statistics is ideal for either a one- or two-semester course in engineering statistics.

Modern Engineering Statistics

Solutions Manual to accompany Modern Regression Methods, 2e (Wiley Series in Probability and Statistics)

wiley

Solutions Manual to accompany Modern Engineering Statistics

This set contains: 9780471483076 SAS Regression Using JMP(r) by Rudolf Freund, Ramon Littell, Lee Creighton and 9780471210771 Experimental Design by Thomas P. Ryan.

SAS Regression Using JMP Set + Modern Experimental Design Set

Freund, Rudolf

Littell, Ramon

Creighton, Lee

This set contains ISBN 978-0-470-08186-0 Modern Regression Methods, 2nd Edition and the Solutions Manual 978-0-470-09606-2.

Modern Regression Methods, Set (Wiley Series in Probability and Statistics)

Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." ―Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: <ul>
<li>Updated coverage of control charts, with newly added tools</li> <li>The latest research on the monitoring of linear profiles and other types of profiles</li> <li>Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures</li> <li>New discussions on design of experiments that include conditional effects and fraction of design space plots</li> <li>New material on Lean Six Sigma and Six Sigma programs and training</li> </ul>
Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.

Statistical Methods for Quality Improvement

Business & Money

Management & Leadership

A comprehensive, up-to-date survey of statistical methods for quality improvement Statistical methods for quality improvement offer numerous benefits for industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. In the Second Edition of his successful book that is still unrivaled in content, Tom Ryan continues to offer clear, thorough coverage of all available techniques-from basic control charts to regression and design of experiments, and the combined use of these tools. This edition is fully expanded and revised, bringing readers up to date with very recent research and providing a solid foundation from which to explore the statistical literature. Dr. Ryan tackles complicated topics in a logical, engaging, easy-to-understand style, downplaying mathematical formulas and making the material accessible to industrial engineers and applied statisticians alike. Special features of Statistical Methods for Quality Improvement, Second Edition include: Greatly expanded chapters on process capability indices and multivariate control chart methods Improved attributes control charts based on the author's research A detailed presentation of Six Sigma programs A new, separate chapter on CUSUM and EWMA procedures New material on robust design and Taguchi-type procedures Chapter appendices for more in-depth coverage of selected topics Very extensive and up-to-date references in each chapter, in addition to a bibliography of papers on a variety of control chart applications

Statistical Methods for Quality Improvement (Wiley Series in Probability and Statistics)

A complete and well-balanced introduction to modern experimental design Using current research and discussion of the topic along with clear applications, Modern Experimental Design highlights the guiding role of statistical principles in experimental design construction. This text can serve as both an applied introduction as well as a concise review of the essential types of experimental designs and their applications. Topical coverage includes designs containing one or multiple factors, designs with at least one blocking factor, split-unit designs and their variations as well as supersaturated and Plackett-Burman designs. In addition, the text contains extensive treatment of: <ul>
<li>Conditional effects analysis as a proposed general method of analysis</li> <li>Multiresponse optimization</li> <li>Space-filling designs, including Latin hypercube and uniform designs</li> <li>Restricted regions of operability and debarred observations</li> <li>Analysis of Means (ANOM) used to analyze data from various types of designs</li> <li>The application of available software, including Design-Expert, JMP, and MINITAB</li> </ul>
This text provides thorough coverage of the topic while also introducing the reader to new approaches. Using a large number of references with detailed analyses of datasets, Modern Experimental Design works as a well-rounded learning tool for beginners as well as a valuable resource for practitioners.

Modern Experimental Design

The most comprehensive book available on state-of-the-art regression methodology, complete with exercises and solutions This combination book and disk set presents the full range of regression techniques available today to practitioners, researchers, and students of this popular and ever-changing field. Featuring a strong data analysis orientation and a more comprehensive treatment of regression diagnostics than is found in other texts, Modern Regression Methods contains a wealth of material assembled here for the first time, including recently developed techniques and some new methods introduced by the author, as well as fresh approaches to standard concepts. With thorough analyses of real-world data sets and many exercises with worked solutions, this unique resource reinforces learning while providing you with crucial hands-on experience in the practical application of skills. The book offers: * In-depth treatment of standard regression methods, including diagnostics, transformations, ridge regression, and variable selection techniques * A detailed examination of nonlinear regression, robust regression, and logistic regression, including both exact and maximum likelihood approaches for logistic regression * New graphical techniques and transformation strategies for multiple regression and a survey of nonparametric regression * Experimental designs for regression * Minitab macros to facilitate understanding and use of many of the new methods that are presented Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Modern Regression Methods was among those chosen.

Modern Regression Methods (Wiley Series in Probability and Statistics)

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