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John Fox - Applied Regression Analysis and Generalized Linear Models - 9781452205663 - V9781452205663
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Applied Regression Analysis and Generalized Linear Models

€ 225.46
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Description for Applied Regression Analysis and Generalized Linear Models Hardback. .
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.

Product Details

Publisher
SAGE Publications Inc
Format
Hardback
Publication date
2015
Condition
New
Weight
1435g
Number of Pages
816
Place of Publication
Thousand Oaks, United States
ISBN
9781452205663
SKU
V9781452205663
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-2

About John Fox
John Fox received a BA from the City College of New York and a PhD from the University of Michigan, both in Sociology. He is Professor Emeritus of Sociology at McMaster University in Hamilton, Ontario, Canada, where he was previously the Senator William McMaster Professor of Social Statistics. Prior to coming to McMaster, he was Professor of Sociology, Professor of ... Read more

Reviews for Applied Regression Analysis and Generalized Linear Models
PRAISE FOR THE PREVIOUS EDITIONS [T]his wonderfully comprehensive book focuses on regression analysis and linear models... We enthusiastically recommend this book-having used it in class, we know that it is thorough and well-liked by students.
Chance (review of the first edition) PRAISE FOR THE PREVIOUS EDITIONS Even though the ... Read more

Goodreads reviews for Applied Regression Analysis and Generalized Linear Models


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