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＜E-Book＞
Statistical Analysis of Management Data / by Hubert Gatignon

Edition	3rd ed. 2014.
Publisher	(New York, NY : Springer US : Imprint: Springer)
Year	2014
Language	English
Size	XV, 563 p. 263 illus., 34 illus. in color : online resource
Authors	*Gatignon, Hubert author SpringerLink (Online service)
Subjects	LCSH:Statistics  LCSH:Marketing FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Marketing
Notes	1: Introduction -- 2: Multivariate Normal Distribution -- 3: Reliability Alpha, Principles Component Analysis and Exploratory Factor Analysis -- 4: Confirmatory Factor Analysis -- 5: Multiple Regression with a Single Dependent Variable -- 6: System of Equations -- 7: Canonical Correlation Analysis -- 8: Categorical Dependent Variables -- 9: Rank-Ordered Data -- 10: Error in Variables – Analysis of Covariance Structure – Structural Equation Models -- 11: Testing Mediation and Moderation Effects -- 12: Cluster Analysis -- 13: Analysis of Similarity and Preference Data -- Appendices: A: Rules in Matrix Algebra -- B: Statistical Tables -- C: Description of Data Sets 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 third 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, this edition includes: ·         A new chapter on the analysis of mediation and moderation effects ·         Examples using STATA for most of the statistical methods ·         Example of XLSTAT applications   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 particularly relevant and typically used in management research, and to learn how they can be applied using widely available statistical software.   HTTP:URL=https://doi.org/10.1007/978-1-4614-8594-0

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