Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Colin Lewis-Beck is a PhD candidate in Statistics at Iowa State University. He holds a BA from Middlebury College and a dual MPP/MA in Public Policy and Applied Statistics from the University of Michigan. While at Michigan, he received an Outstanding Teaching Award from the Department of Statistics. Also, he has worked as a Teaching Assistant and a Computer Consultant, during multiple summers at the Inter-University Consortium for Political and Social Research (ICPSR) Summer Program, University of Michigan. His research experiences in statistics are varied, and including serving as a Statistician in the Economic Analysis and Statistics Division of the OECD (Paris), and at STATinMED, a health outcomes research firm in Ann Arbor, MI. His interests are applied statistics related to social science research, causal inference, and spatial statistics. Mr. Lewis-Beck has co-authored papers on the quality of life and work productivity, modeling health care costs, and technology use in educational performance.
Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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