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Categorical Data Analysis by Alan Agresti: Used
US $58.66
ApproximatelyRM 247.36
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A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages.
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eBay item number:364014769374
Item specifics
- Condition
- Book Title
- Categorical Data Analysis
- Publication Date
- 2012-12-03
- Edition Number
- 3
- Pages
- 752
- ISBN
- 9780470463635
About this product
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0470463635
ISBN-13
9780470463635
eBay Product ID (ePID)
2199709
Product Key Features
Number of Pages
752 Pages
Language
English
Publication Name
Categorical Data Analysis
Publication Year
2012
Subject
Probability & Statistics / Multivariate Analysis, Probability & Statistics / General, Databases / Data Mining
Type
Textbook
Subject Area
Mathematics, Computers
Series
Wiley Series in Probability and Statistics Ser.
Format
Hardcover
Dimensions
Item Height
1.9 in
Item Weight
49.5 Oz
Item Length
10.2 in
Item Width
7.3 in
Additional Product Features
Edition Number
3
Intended Audience
Scholarly & Professional
LCCN
2012-009792
Dewey Edition
23
Series Volume Number
792
Illustrated
Yes
Dewey Decimal
519.535
Synopsis
Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis." Statistics in Medicine "It is a total delight reading this book." Pharmaceutical Research "If you do any analysis of categorical data, this is an essential desktop reference." Technometrics The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial loglinear models for discrete data with normal regression for continuous data. This edition also features: An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis New sections introducing the Bayesian approach for methods in that chapter More than 100 analyses of data sets and over 600 exercises Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control., Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis." -- Statistics in Medicine "It is a total delight reading this book." -- Pharmaceutical Research "If you do any analysis of categorical data, this is an essential desktop reference." -- Technometrics The use of statistical methods for analyzing categorical data has increased dramatically, particularly in the biomedical, social sciences, and financial industries. Responding to new developments, this book offers a comprehensive treatment of the most important methods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial loglinear models for discrete data with normal regression for continuous data. This edition also features: An emphasis on logistic and probit regression methods for binary, ordinal, and nominal responses for independent observations and for clustered data with marginal models and random effects models Two new chapters on alternative methods for binary response data, including smoothing and regularization methods, classification methods such as linear discriminant analysis and classification trees, and cluster analysis New sections introducing the Bayesian approach for methods in that chapter More than 100 analyses of data sets and over 600 exercises Notes at the end of each chapter that provide references to recent research and topics not covered in the text, linked to a bibliography of more than 1,200 sources A supplementary website showing how to use R and SAS; for all examples in the text, with information also about SPSS and Stata and with exercise solutions Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and methodologists, such as biostatisticians and researchers in the social and behavioral sciences, medicine and public health, marketing, education, finance, biological and agricultural sciences, and industrial quality control., Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis. " Statistics in Medicine "It is a total delight reading this book., A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available.
LC Classification Number
QA278.A353 2012
Item description from the seller
Seller feedback (516,953)
- a***s (880)- Feedback left by buyer.Past monthVerified purchaseThe item was a book in great condition. It was a gift and I was happy to see it was of good quality. It will hold it's value and with care it's appearance will always be pleasing.
- y***w (2157)- Feedback left by buyer.Past monthVerified purchaseMemories of childhood!
- e***s (3517)- Feedback left by buyer.Past monthVerified purchaseBook in pristine condition. Fast shipping. A happy repeat buyer. Many thanks.
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Seller feedback (516,953)
- a***s (880)- Feedback left by buyer.Past monthVerified purchaseThe item was a book in great condition. It was a gift and I was happy to see it was of good quality. It will hold it's value and with care it's appearance will always be pleasing.
- y***w (2157)- Feedback left by buyer.Past monthVerified purchaseMemories of childhood!
- e***s (3517)- Feedback left by buyer.Past monthVerified purchaseBook in pristine condition. Fast shipping. A happy repeat buyer. Many thanks.