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Handbook of Regression Analysi
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Handbook of Regression Analysi Tapa dura - 2012 - 1st Edición

de Samprit Chatterjee; Jeffrey S. Simonoff


Información de la editorial

A Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis.

Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis. The focus is on the tools that both practitioners and researchers use in real life. It is intended to be a comprehensive collection of the theory, methods, and applications of regression methods, but it has been deliberately written at an accessible level.

The handbook provides a quick and convenient reference or "refresher" on ideas and methods that are useful for the effective analysis of data and its resulting interpretations. Students can use the book as an introduction to and/or summary of key concepts in regression and related course work (including linear, binary logistic, multinomial logistic, count, and nonlinear regression models). Theory underlying the methodology is presented when it advances conceptual understanding and is always supplemented by hands-on examples.

References are supplied for readers wanting more detailed material on the topics discussed in the book. R code and data for all of the analyses described in the book are available via an author-maintained website.

"I enjoyed the presentation of the Handbook, and I would be happy to recommend this nice handy book as a reference to my students. The clarity of the writing and proper choices of examples allows the presentations ofmany statisticalmethods shine. The quality of the examples at the end of each chapter is a strength. They entail explanations of the resulting R outputs and successfully guide readers to interpret them." American Statistician

Descripción de contraportada

A comprehensive account for data analysts of the methods and applications of regression analysis

Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis. The focus is on the tools that both practitioners and researchers use in real life. It is intended to be a comprehensive collection of the theory, methods, and applications of regression methods, but it has been deliberately written at an accessible level.

The handbook provides a quick and convenient reference or "refresher" on ideas and methods that are useful for the effective analysis of data and its resulting interpretations. Students can use the book as an introduction to and/or summary of key concepts in regression and related course work (including linear, binary logistic, multinomial logistic, count, and nonlinear regression models). Theory underlying the methodology is presented when it advances conceptual understanding and is always supplemented by hands-on examples.

References are supplied for readers wanting more detailed material on the topics discussed in the book. R code and data for all of the analyses described in the book are available via an author-maintained website.

Detalles

  • Título Handbook of Regression Analysi
  • Autor Samprit Chatterjee; Jeffrey S. Simonoff
  • Encuadernación Tapa dura
  • Número de edición 1st
  • Edición 1
  • Páginas 252
  • Volúmenes 1
  • Idioma ENG
  • Editorial Wiley
  • Fecha de publicación 2012-12-26
  • ISBN 9780470887165 / 0470887168
  • Peso 1.1 libras (0.50 kg)
  • Dimensiones 9.5 x 6.1 x 0.8 pulgadas (24.13 x 15.49 x 2.03 cm)
  • Library of Congress subjects Regression analysis, MATHEMATICS / Probability & Statistics /
  • Número de catálogo de la Librería del Congreso de EEUU 2012045175
  • Dewey Decimal Code 519.536

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Acerca del autor

SAMPRIT CHATTERJEE, PhD, is Professor Emeritus of Statistics at New York University. A Fellow of the American Statistical Association, Dr. Chatterjee has been a Fulbright scholar in both Kazakhstan and Mongolia. He is the coauthor of Regression Analysis by Example, Sensitivity Analysis in Linear Regression, and A Casebook for a First Course in Statistics and Data Analysis, all published by Wiley.

Jeffrey S. Simonoff, PhD, is Professor of Statistics at the Leonard N. Stern School of Business of New York University. He is a Fellow of the American Statistical Association, a Fellow of the Institute of Mathematical Statistics, and an Elected Member of the International Statistical Institute. He has authored or coauthored more than ninety articles and five books on the theory and applications of statistics.

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