Applied regression analysis and generalized linear models / John Fox

Fox, John:

ISBN 10: 0761930426 / ISBN 13: 9780761930426

Editore: Los Angeles : Sage,, 2008

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xxi, 665 pp., figs. In English language. Illustrated hardbound (no dustjacket as issued). Former library copy without external labelings in very good condition. Signature stamps on fl. endpaper and imprint. + + + Illustrierter Originalpappeinband (kein Schutzumschlag). Ordentlich ausgesondertes Biblioteksexemplar ohne äußerliche Kennzeichungen in sehr guter Erhaltung. Signatur- / Entwidmungsstempel a. Vorsatz und Druckvermerk. 0761930426 Werktäglicher Versand. Jede Lieferung m. ordentl. Rechnung und ausgew. MwSt. Der Versand erfolgt als Büchersendung / Einschreiben mit der Deutschen Post bzw. als Päckchen / Paket mit DHL. Die Lieferzeit ist abhängig von der Versandart und beträgt innerhalb Deutschlands 3-5 Tage, in der EU 5 - 12 Tage. KEIN Versand an Packstationen. Körperschaften und juristische Personen werden auf Wunsch per offener Rechnung beliefert. Sprache: Englisch Gewicht in Gramm: 1200.

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Dati bibliografici

• Titolo: Applied regression analysis and generalized linear models / John Fox
• Editore: Los Angeles : Sage,
• Data di pubblicazione: 2008
• Lingua: Inglese
• ISBN 10: 0761930426
• ISBN 13: 9780761930426
• Rilegatura: Gebundene Ausgabe
• Edizione: 2nd. ed.
• Condizione: Sehr gut
• Peso: 1200 grammi
• Cataloghi dei venditori:
  • Naturwissenschaften: Mathematik: Wirtschaftsmat...

Descrizione articolo

Riassunto

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Second Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material throughout the book.

Key Updates to the Second Edition:

• Provides greatly enhanced coverage of generalized linear models, with an emphasis on models for categorical and count data
• Offers new chapters on missing data in regression models and on methods of model selection
• Includes expanded treatment of robust regression, time-series regression, nonlinear regression, and nonparametric regression
• Incorporates new examples using larger data sets
• Includes an extensive Web site at http://www.sagepub.com/fox that presents appendixes, data sets used in the book and for data-analytic exercises, and the data-analytic exercises themselves

Intended Audience:
This core text will be a valuable resource for graduate students and researchers in the social sciences (particularly sociology, political science, and psychology) and other disciplines that employ linear and related models for data analysis.

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.