Modern Regression Methods


Modern Regression Methods
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Modern Regression Methods


Modern Regression Methods
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Author : Thomas P. Ryan
language : en
Publisher: John Wiley & Sons
Release Date : 2008-11-10

Modern Regression Methods written by Thomas P. Ryan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-10 with Mathematics categories.


"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: A revised chapter on logistic regression, including improved methods of parameter estimation A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression A wealth of new and updated exercises with worked solutions An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures Updated references at the end of each chapter that direct the reader to the appropriate resources for further study 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.



Solutions Manual To Accompany Modern Regression Methods


Solutions Manual To Accompany Modern Regression Methods
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Author : Thomas P. Ryan
language : en
Publisher:
Release Date : 2009

Solutions Manual To Accompany Modern Regression Methods written by Thomas P. Ryan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Regression analysis categories.




Solutions Manual To Accompany Modern Regression Methods 2e


Solutions Manual To Accompany Modern Regression Methods 2e
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Author : Thomas P. Ryan
language : en
Publisher: Wiley
Release Date : 2009-03-09

Solutions Manual To Accompany Modern Regression Methods 2e written by Thomas P. Ryan and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-09 with Mathematics categories.


"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: A revised chapter on logistic regression, including improved methods of parameter estimation A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression A wealth of new and updated exercises with worked solutions An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures Updated references at the end of each chapter that direct the reader to the appropriate resources for further study 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 Set


Modern Regression Methods Set
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Author : Thomas P. Ryan
language : en
Publisher: Wiley
Release Date : 2009-05-18

Modern Regression Methods Set written by Thomas P. Ryan and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-18 with Mathematics categories.


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, 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: A revised chapter on logistic regression, including improved methods of parameter estimation A new chapter focusing on additional topics of study in regression, including quantile regression, semiparametric regression, and Poisson regression A wealth of new and updated exercises with worked solutions An extensive FTP site complete with Minitab macros, which allow the reader to compute analyses, and specialized procedures Updated references at the end of each chapter that direct the reader to the appropriate resources for further study 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 Techniques Using R


Modern Regression Techniques Using R
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Author : Daniel B Wright
language : en
Publisher: SAGE
Release Date : 2009-02-19

Modern Regression Techniques Using R written by Daniel B Wright and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-19 with Mathematics categories.


Statistics is the language of modern empirical social and behavioural science and the varieties of regression form the basis of this language. Statistical and computing advances have led to new and exciting regressions that have become the necessary tools for any researcher in these fields. In a way that is refreshingly engaging and readable, Wright and London describe the most useful of these techniques and provide step-by-step instructions, using the freeware R, to analyze datasets that can be located on the books′ webpage: www.sagepub.co.uk/wrightandlondon. Techniques covered in this book include multilevel modeling, ANOVA and ANCOVA, path analysis, mediation and moderation, logistic regression (generalized linear models), generalized additive models, and robust methods. These are all tested out using a range of real research examples conducted by the authors in every chapter. Given the wide coverage of techniques, this book will be essential reading for any advanced undergraduate and graduate student (particularly in psychology) and for more experienced researchers wanting to learn how to apply some of the more recent statistical techniques to their datasets. The Authors are donating all royalties from the book to the American Partnership for Eosinophilic Disorders.



A Modern Approach To Regression With R


A Modern Approach To Regression With R
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Author : Simon Sheather
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-02-27

A Modern Approach To Regression With R written by Simon Sheather and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-27 with Mathematics categories.


This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. Plots are shown to be an important tool for both building regression models and assessing their validity. We shall see that deciding what to plot and how each plot should be interpreted will be a major challenge. In order to overcome this challenge we shall need to understand the mathematical properties of the fitted regression models and associated diagnostic procedures. As such this will be an area of focus throughout the book. In particular, we shall carefully study the properties of resi- als in order to understand when patterns in residual plots provide direct information about model misspecification and when they do not. The regression output and plots that appear throughout the book have been gen- ated using R. The output from R that appears in this book has been edited in minor ways. On the book web site you will find the R code used in each example in the text.



Exploring Modern Regression Methods Using Sas


Exploring Modern Regression Methods Using Sas
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Author :
language : en
Publisher:
Release Date : 2019

Exploring Modern Regression Methods Using Sas written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Research categories.




Classical And Modern Regression With Applications


Classical And Modern Regression With Applications
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Author : Raymond H. Myers
language : en
Publisher: Arden Shakespeare
Release Date : 1986

Classical And Modern Regression With Applications written by Raymond H. Myers and has been published by Arden Shakespeare this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Mathematics categories.




Regression Linear Modeling


Regression Linear Modeling
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Author : Jason W. Osborne
language : en
Publisher: SAGE Publications
Release Date : 2016-03-24

Regression Linear Modeling written by Jason W. Osborne and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-24 with Psychology categories.


In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.



Modern Multivariate Statistical Techniques


Modern Multivariate Statistical Techniques
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Author : Alan J. Izenman
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-02

Modern Multivariate Statistical Techniques written by Alan J. Izenman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-02 with Mathematics categories.


This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.