Statistical Analysis of Management Data (Hardback)Hubert Gatignon (author)
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Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on:confirmatory factor analysiscanonical correlation analysiscluster analysisanalysis of covariance structuremulti-group confirmatory factor analysis and analysis of covariance structures.
Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software.
Publisher: Springer-Verlag New York Inc.
Number of pages: 388
Weight: 1650 g
Dimensions: 235 x 155 x 23 mm
Edition: 2nd ed. 2010
From the reviews of the second edition:"This edition deals with statistical topics useful to researchers and graduate students in many fields of management ... . updated and expanded according to current needs and demands of the field. ... I really enjoyed reading this book. ... In summary, it is a nicely packaged book for the intended audience and I have no hesitation to recommend it as a textbook for a graduate course in management sciences and related areas. ... used as an excellent reference book for researchers in these areas." (Technometrics, Vol. 52 (3), August, 2010)
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