Statistical Analysis of Management Data

Statistical Analysis of Management Data

by Hubert Gatignon
Statistical Analysis of Management Data

Statistical Analysis of Management Data

by Hubert Gatignon

eBook2nd ed. 2010 (2nd ed. 2010)

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Overview

This book covers multivariate statistical analyses that are important for researchers in all fields of management. The book is especially designed to provide doctoral students with a theoretical knowledge of the basic concepts underlying the most important multivariate techniques and with an overview of applications in various fields. It addresses both underlying mathematics and problems of application. Students are assumed to be familiar with basic statistical techniques. Gatignon teaches business administration and marketing at INSEAD. Annotation ©2003 Book News, Inc., Portland, OR

Product Details

ISBN-13: 9781441912701
Publisher: Springer-Verlag New York, LLC
Publication date: 01/08/2010
Sold by: Barnes & Noble
Format: eBook
Pages: 388
File size: 7 MB

About the Author

Hubert Gatignon is the Claude Janssen Chaired Professor of Business Administration at INSEAD. He joined INSEAD in 1994 from the Wharton School of the University of Pennsylvania where he was Professor of Marketing. He holds a Ph.D. in Marketing from the University of California, Los Angeles, and the Habilitation à Diriger des Recherches from Université Paul Cézanne-Aix Marseille.

His research interests involve (1) the marketing of innovations (e.g., modeling the factors influencing the adoption and diffusion of innovations), (2) marketing strategy (e.g., explaining and econometrically measuring how the effects of marketing mix variables change over conditions and over time), and (3) statistical analysis of management data.

Dr. Gatignon's publications have appeared in Communications Research, International Journal of Research in Marketing, Journal of Business Research, Journal of Consumer Research, Journal of International Business Studies, Journal of Law, Economics and Organization, Journal of Marketing, Journal of Marketing Research, Journal of Retailing, Management Science, Marketing Letters, Marketing Science, Planning Review, and Strategic Management Journal. He has recently edited New Products and Services Development (4 volumes), and he is a co-author of MARKSTRAT3: The Strategic Marketing Simulation, ADSTRAT: An Advertising Decision Support System, and COMPTRACK: A Competitive Tracking Software. He co-edited The INSEAD-Wharton Alliance on Globalizing: Strategies for Building Successful Global Businesses.

Dr. Gatignon is an Associate Editor of the Journal of Marketing Research, and he serves on the editorial boards of International Journal of Research in Marketing (he was the Editor-in-Chief from 2000 through 2006), Journal of Business-to-Business Marketing, Journal of Marketing, Journal of the Academy of Marketing Science, Marketing Letters, Marketing Science, and Recherche et Applications en Marketing (he was theEditor-in-Chief from 1998 through 2000). He has also served on the editorial board of Journal of International Business Studies and Journal of International Marketing. Dr. Gatignon is on the advisory board of The Quantitative Marketing Network of the Social Sciences Research Network. He was an Academic Trustee of the Marketing Science Institute from 1998 through 2004 and is now an Academic Trustee at AiMark (Center for Advanced International Marketing Knowledge).

ISI Web of Knowledge identifies Hubert Gatignon as a Highly Cited Researcher in the Economics and Business category. He has been named a Fellow of the European Marketing Academy and is included in the 25th Anniversary Edition of Who’s Who in the World and in the Who’s Who in France.

Table of Contents

Multivariate Normal Distribution.- Reliability Alpha, Principle Component Analysis, and Exploratory Factor Analysis.- Confirmatory Factor Analysis.- Multiple Regression with a Single Dependent Variable.- System of Equations.- Canonical Correlation Analysis.- Categorical Dependent Variables.- Rank-Ordered Data.- Error in Variables – Analysis of Covariance Structure.- Cluster Analysis.- Analysis of Similarity and Preference Data.- Appendices.
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