- Provides a technical base for tackling most applications-oriented multivariate texts
- Presents a geometric perspective for aiding ones intuitive grasp of multivariate methods
- Emphasizes technical terms current in the social and behavioral sciences, statistics, and mathematics
- Can be used either as a stand-alone text or a supplement to a multivariate statistics textbook
- Employs many pictures and diagrams to convey an intuitive perception of matrix algebra concepts
- Toy problems provide a step-by-step approach to each model and matrix algebra concept
- Provides solutions for all exercises
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.
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.