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An Introduction to Regression Graphics (Wiley Series in Probability & Mathematical Statistics)

An Introduction to Regression Graphics (Wiley Series in Probability & Mathematical Statistics) Cover

 

Synopses & Reviews

Publisher Comments:

Understanding how a response variable depends on one or more predictor variables is a universal scientific problem. Regression analysis consists of ideas and methods for addressing this problem. Historically, regression methods have been largely numerical, with graphics playing an important but subsidiary role. By allowing informative and novel visualizations of regression data, modern computer hardware and software promise to reverse the historical roles of numerical and graphical regression methods. How shall this be done in practice? What can be learned from graphs and which graphs should be drawn? How can graphs be used to learn about fundamental features of regression problems? An Introduction to Regression Graphics answers these questions and more, providing the ideas, methodology, and software needed to use graphs in regression. From simple manipulations, such as changing the aspect ratio and marking points, to more sophisticated ideas like extracting smooths or looking at uncorrelated directions in 3D plots, R. Dennis Cook and Sanford Weisberg provide step-by-step software instructions and concise explanations of how graphs can be used in almost any regression problem. The accompanying disks?compatible with Macintosh, Windows, and UNIX workstations?contain an interactive regression program called R-code along with many sample data sets and demonstrations. The R-code is capable of performing all computations discussed in the book, and can be used with your own data. The book serves as a manual for the software. For data analysts, An Introduction to Regression Graphics provides new tools and insights for graphical analysis of regression data. For graduate and upper-level undergraduate students taking regression courses in the applied sciences, this book is a source for new methods and techniques that will continue to increase in importance for years to come.

Book News Annotation:

A book/disk set that provides access to a wide array of graphical tools and ideas for visualizing regression data and extracting meaningful summaries. Centering on two graphical activities--construction and interpretation--it shows users how to interact with the graphs they create to gain a greater understanding of the information they can convey. The two included disks contain R-code, a program for regression and graphics that permits the reproduction of every graph in the book and the performance of every procedure described. For advanced undergraduate and graduate students taking regression courses in the applied sciences.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

Synopsis:

Understanding how a response variable depends on one or more predictor variables is a universal scientific problem. Regression analysis consists of ideas and methods for addressing this problem. Historically, regression methods have been largely numerical, with graphics playing an important but subsidiary role. By allowing informative and novel visualizations of regression data, modern computer hardware and software promise to reverse the historical roles of numerical and graphical regression methods. How shall this be done in practice? What can be learned from graphs and which graphs should be drawn? How can graphs be used to learn about fundamental features of regression problems? An Introduction to Regression Graphics answers these questions and more, providing the ideas, methodology, and software needed to use graphs in regression. From simple manipulations, such as changing the aspect ratio and marking points, to more sophisticated ideas like extracting smooths or looking at uncorrelated directions in 3D plots, R. Dennis Cook and Sanford Weisberg provide step-by-step software instructions and concise explanations of how graphs can be used in almost any regression problem. The accompanying diskscompatible with Macintosh, Windows, and UNIX workstationscontain an interactive regression program called R-code along with many sample data sets and demonstrations. The R-code is capable of performing all computations discussed in the book, and can be used with your own data. The book serves as a manual for the software. For data analysts, An Introduction to Regression Graphics provides new tools and insights for graphical analysis of regression data. For graduate and upper-level undergraduate students taking regression courses in the applied sciences, this book is a source for new methods and techniques that will continue to increase in importance for years to come.

Synopsis:

Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

Description:

Includes bibliographical references (p. 241-244) and index.

About the Author

About the authors R. DENNIS COOK is Professor, Department of Applied Statistics, University of Minnesota. An active researcher in regression theory and methods, Dr. Cook is a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics, and is an elected member of the International Statistical Institute. Dr. Cook received his PhD degree in statistics from Kansas State University. SANFORD WEISBERG is Professor, Department of Applied Statistics, University of Minnesota. The author of Applied Linear Regression, Second Edition (Wiley), he is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute. Dr. Weisberg received his PhD degree in statistics from Harvard University. The authors have jointly published about twenty works, including Residuals and Influence in Regression and a 1989 paper on regression graphics that earned the Jack Youden prize.

Table of Contents

Getting Started.

Simple Regression Plots.

Two-Dimensional Plots.

Scatterplot Matrices.

Three-Dimensional Plots.

Visualizing Linear Regression with Two Predictors.

Visualizing Regression Without Linearity.

Finding Dimension.

Predictor Transformations.

Response Transformations.

Checking Models.

Assessing Predictors.

Influence and Outliers.

Confidence Regions.

Appendices.

References.

Index.

Product Details

ISBN:
9780471008392
With:
Weisberg, Sanford
Author:
Weisberg, Sanford
Author:
ook, R. Dennis
Author:
C
Author:
Cook, R. Dennis
Publisher:
Wiley-Interscience
Location:
New York :
Subject:
Statistics
Subject:
Graphic Methods
Subject:
Probability
Subject:
Regression analysis
Subject:
Regression analysis -- Graphic methods -- Data processing.
Subject:
Probability & Statistics - General
Subject:
Regression analysis -- Graphic methods.
Subject:
Computational & Graphical Statistics
Subject:
Mathematics | Probability and Statistics
Copyright:
Edition Description:
WOL online Book (not BRO)
Series:
Wiley Series in Probability and Statistics
Series Volume:
242
Publication Date:
July 1994
Binding:
Online electronic file accessible through online networks
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
Yes
Pages:
280
Dimensions:
25 cm. +

Related Subjects

History and Social Science » Economics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics

An Introduction to Regression Graphics (Wiley Series in Probability & Mathematical Statistics)
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$ In Stock
Product details 280 pages Wiley-Interscience - English 9780471008392 Reviews:
"Synopsis" by , An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.
"Synopsis" by , Understanding how a response variable depends on one or more predictor variables is a universal scientific problem. Regression analysis consists of ideas and methods for addressing this problem. Historically, regression methods have been largely numerical, with graphics playing an important but subsidiary role. By allowing informative and novel visualizations of regression data, modern computer hardware and software promise to reverse the historical roles of numerical and graphical regression methods. How shall this be done in practice? What can be learned from graphs and which graphs should be drawn? How can graphs be used to learn about fundamental features of regression problems? An Introduction to Regression Graphics answers these questions and more, providing the ideas, methodology, and software needed to use graphs in regression. From simple manipulations, such as changing the aspect ratio and marking points, to more sophisticated ideas like extracting smooths or looking at uncorrelated directions in 3D plots, R. Dennis Cook and Sanford Weisberg provide step-by-step software instructions and concise explanations of how graphs can be used in almost any regression problem. The accompanying diskscompatible with Macintosh, Windows, and UNIX workstationscontain an interactive regression program called R-code along with many sample data sets and demonstrations. The R-code is capable of performing all computations discussed in the book, and can be used with your own data. The book serves as a manual for the software. For data analysts, An Introduction to Regression Graphics provides new tools and insights for graphical analysis of regression data. For graduate and upper-level undergraduate students taking regression courses in the applied sciences, this book is a source for new methods and techniques that will continue to increase in importance for years to come.
"Synopsis" by , Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.

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