Statistical Analysis of Management Data [recurso electrónico] / by Hubert Gatignon.

Por: Gatignon, Hubert [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoDetalles de publicación: New York, NY : Springer New York, 2010Edición: 2Descripción: XVII, 388 p. online resourceISBN: 9781441912701Tema(s): Statistics | Mathematical statistics | Economics -- Statistics | Econometrics | Statistics | Statistics for Business/Economics/Mathematical Finance/Insurance | Statistical Theory and Methods | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | EconometricsClasificación LoC:QA276-280Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer eBooksResumen: 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 analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-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.
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Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA276 -280 (Browse shelf(Abre debajo)) 1 No para préstamo 371298-2001

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.

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 analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-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.

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