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A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and... more...

A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software... more...

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,... more...

Statistical science as organized in formal academic departments is relatively new.  With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years.  This book consists of a set of memoirs, one for each department in the U.S. created by the mid-1960s. The memoirs describe key aspects of the department’s history -- its founding, its growth, key people in its development, success... more...

Praise for the First Edition "This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended." —Short Book Reviews "Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few." —Journal of Quality Technology "Alan Agresti has... more...


Statistical science’s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data, Second Edition provides an introduction to basic descriptive and inferential methods for categorical data, giving thorough coverage of new developments... more...

Assuming no prior knowledge of statistics, these authors combine their varied backgrounds—one a statistician, the other a social scientist—to introduce statistical methods with a high degree of statistical accuracy and a wealth of examples that are interesting and relevant to social scientists. The Third Edition has been both updated and improved to integrate real-world data into examples and exercises, and make coverage more... more...

Alan Agresti and Chris Franklin have merged their research and classroom experience to develop this successful introductory statistics text. Statistics: The Art and Science of Learning from Data, Third Edition, helps students become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible... more...

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Categorical Data Analysis was among those chosen.A valuable new edition of a standard reference"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."–Statistics in Medicine on Categorical Data Analysis, First EditionThe use of statistical methods for categorical data has increased dramatically,... more...

The book presents an introduction to statistical methods for students majoring in social science disciplines.  No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra).  The book contains sufficient material for a two-semester sequence of courses.  Such sequences are commonly required of social science graduate students in sociology, political science, and psychology.... more...