Applied Regression Analysis, Linear Models, and Related Methods by Fox, John

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Item specifics

Condition
Like New: A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is ...
Binding
Hardcover
Product Group
Book
Book Title
Applied Regression Analysis, Linear Models, and Related Methods
Weight
2 lbs
IsTextBook
Yes
ISBN
9780803945401
Category

About this product

Product Identifiers

Publisher
SAGE Publications, Incorporated
ISBN-10
080394540X
ISBN-13
9780803945401
eBay Product ID (ePID)
20038699505

Product Key Features

Number of Pages
624 Pages
Language
English
Publication Name
Applied Regression Analysis, Linear Models, and Related Methods
Subject
Probability & Statistics / Regression Analysis, Research
Publication Year
1997
Type
Textbook
Author
John Fox
Subject Area
Mathematics, Social Science
Format
Hardcover

Dimensions

Item Weight
47.1 Oz
Item Length
10 in
Item Width
7 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
96-038084
Reviews
I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with-and he does not avoid the slippery ones-he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field., "I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with--and he does not avoid the slippery ones--he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field." , "I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with'”and he does not avoid the slippery ones'”he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field." , "I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with'e"and he does not avoid the slippery ones'e"he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field." , "I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with-and he does not avoid the slippery ones-he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field." , "I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals withe"and he does not avoid the slippery onese"he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field.", I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with--and he does not avoid the slippery ones--he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks that matches the works of the leading researchers within each field.
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
300/.01/519536
Table Of Content
PART ONE: PRELIMINARIESStatistics and Social ScienceWhat Is Regression Analysis?Examining DataTransforming DataPART TWO: LINEAR MODELS AND LEAST SQUARESLinear Least-Squares RegressionStatistical Inference for RegressionDummy-Variable RegressionAnalysis of VarianceStatistical Theory for Linear ModelsThe Vector Geometry of Linear ModelsPART THREE: LINEAR-MODEL DIAGNOSTICSUnusual and Influential DataDiagnosing Nonlinearity, Nonconstant Error Variance, and NonnormalityCollinearity and Its Purported RemediesPART FOUR: BEYOND LINEAR LEAST SQUARESExtending Linear Least Squares Time Series, Nonlinear, Robust, and Nonparametric RegressionLogit and Probit ModelsAssessing Sampling Variation Bootstrapping and Cross-Validation
Synopsis
An accessible, detailed, and up-to-date treatment of regression analysis, linear models, and closely related methods is provided in this book. Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear, An accessible, detailed and up-to-date treatment of regression analysis, linear models and closely related methods is provided in this book.Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation., An accessible, detailed and up-to-date treatment of regression analysis, linear models and closely related methods is provided in this book. Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation.
LC Classification Number
HA31.3.F69 1997

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