An R and S-Plus Companion to Applied Regression

Fox, John

ISBN 10: 0761922806 / ISBN 13: 9780761922803

Editore: SAGE Publications, Inc, 2002

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Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Codice articolo M00761922806-G

Dati bibliografici

• Titolo: An R and S-Plus Companion to Applied Regression
• Editore: SAGE Publications, Inc
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 0761922806
• ISBN 13: 9780761922803
• Rilegatura: Brossura
• Condizione: good

Descrizione articolo

Riassunto

"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. "

—JEFF GILL, University of Florida, Gainesville 

Informazioni sull?autore

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 Mathematics and Statistics, and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics, including \emph{Applied Regression Analysis and Generalized Linear Models, Third Edition} (Sage, 2016). He is an elected member of the R Foundation, an associate editor of the Journal of Statistical Software, a prior editor of R News and its successor the R Journal, and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.