Mathematical Tools for Applied Multivariate Analysis

Edited by Anil Chaturvedi
Erscheinungsjahr 1997
ISBN: 978-0-12-160955-9
Verlag: William Andrew Publishing

Buch, Englisch, 376 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 490 g

This revised edition presents the relevant aspects of transformational geometry, matrix algebra, and calculus to those who may be lacking the necessary mathematical foundations of applied multivariate analysis. It brings up-to-date many definitions of mathematical concepts and their operations. It also clearly defines the relevance of the exercises to concerns within the business community and the social and behavioral sciences. Readers gain a technical background for tackling applications-oriented multivariate texts and receive a geometric perspective for understanding multivariate methods."Mathematical Tools for Applied Multivariate Analysis, Revised Edition illustrates major concepts in matrix algebra, linear structures, and eigenstructures geometrically, numerically, and algebraically. The authors emphasize the applications of these techniques by discussing potential solutions to problems outlined early in the book. They also present small numerical examples of the various concepts.

Zielgruppe

Undergraduate and graduate-level courses in quantitative methods and applied multivariate analysis. These courses include: applied multivariate analysis in statistics departments, introductory applied statistics and statisticaltechniques in psychology departments, sociological research in sociology departments, social statistics and marketing information in marketing departments, and mathematics for economists in economics departments.

Autoren/Hrsg.

Carroll, J. Douglas

Green, Paul

Chaturvedi, Anil

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Mathematische Analysis Moderne Anwendungen der Analysis
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Algebra Homologische Algebra

Inhaltsverzeichnis

The Nature of Multivariate Data Analysis.
Vector and Matrix Operations for Multivariate Analysis.
Vector and Matrix Concepts from a Geometric Viewpoint.
Linear Transformations from a Geometric Viewpoint.
Decomposition of Matrix Transformations: Eigenstructures and Quadratic Forms.
Applying the Tools to Multivariate Data.
Appendix A: Symbolic Differentiation and Optimization of Multivariable Functions.

Appendix B: Linear Equations and Generalized Inverses.
Answers to Numerical Problems.
References.
Index.

Über Autor(innen)

Carroll, J. Douglas
J. Douglas Carroll is the Board of Governor's Professor of Marketing and Psychology in the Graduate School of Management at Rutgers, the State University of New Jersey. He holds a Ph.D. in mathematics from Princeton University. Dr. Carroll has published widely on multidimensional scaling and related techniques of data analysis. He is a member of several professional organizations.