Probability and Statistics for Engineers and Scientists, 2nd Edition, by Ronald E. Walpole and Raymond H. Myers, Hardback

Probability and Statistics for Engineers and Scientists

Science & Math

Ronald E. Walpole

Raymond H. Myers

Mathematics

Macmillan Pubishing Company

Probability And Statistics For Engineers And Scientists

Sharon L. Myers

Probability & Statistics for Engineers & Scientists

Keying E. Ye

Pearson Education US

Probability & Statistics for Engineers & Scientists, MyLab Statistics Update

Raymond H Meyers

Keying Ye

Pearson Education Limited

Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." --Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences. This new edition maintains its accessible approach to the topic by reviewing the various types of problems that support the use of GLMs and providing an overview of the basic, related concepts such as multiple linear regression, nonlinear regression, least squares, and the maximum likelihood estimation procedure. Incorporating the latest developments, new features of this Second Edition include: <ul> <li> A new chapter on random effects and designs for GLMs </li> <li> A thoroughly revised chapter on logistic and Poisson regression, now with additional results on goodness of fit testing, nominal and ordinal responses, and overdispersion </li> <li> A new emphasis on GLM design, with added sections on designs for regression models and optimal designs for nonlinear regression models </li> <li> Expanded discussion of weighted least squares, including examples that illustrate how to estimate the weights </li> <li> Illustrations of R code to perform GLM analysis </li> </ul> The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology and biopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS®, Minitab®, JMP®, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets. Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also serves as a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work.

Generalized Linear Models: With Applications in Engineering and the Sciences

DOUGLAS C. MONTGOMERY

Timothy J Robinson

wiley

For seniors or graduate students with backgrounds in calculus and linear algebra; concepts are emphasized by using a blend of real data sets and mathematical development.

Classical and Modern Regression with Applications

International Thomson Publishing

Regression analysis is a vitally important statistical tool, with major advancements made by both practical data analysts and statistical theorists. In CLASSICAL AND MODERN REGRESSION WITH APPLICATIONS, Second Edition, Raymond H. Myers provides a solid foundation in classical regression, while introducing modern techniques. Throughout the text, a broad spectrum of applications are included from the physical sciences, engineering, biology, management, and economics.

Classical and Modern Regression With Applications

Duxbury Press

Response Surface Methodology: Process and Product Optimization Using Designed Experiments

Christine M. Anderson-Cook

Probability And Statistics For Engineers And Scientists, Updated 9th Edition

Pearson.India

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Books by Raymond H. Myers