Multivariate Statistical Analysis and Applications

Author: Yu Jinhua Yang Weiquan
Publisher:
Publish Date: 2005-02-25
Features: "Multivariate Statistical Analysis" is a discipline that has rapidly developed in recent decades. With the widespread use of microcomputers and the popularization of statistical software, multivariate statistical methods have been widely applied in various disciplines of natural sciences and even in all fields of social sciences. This textbook aims to introduce the basic knowledge, fundamental theories, and applications of multivariate statistical analysis. The book is divided into two main parts: Part 1 includes the first four chapters, providing a concise introduction to the basic concepts and fundamental theories of multivariate statistical analysis, including multivariate normal distribution, multivariate parameter estimation, sampling distributions, and hypothesis testing, with the matrix knowledge involved supplemented by Appendix I. Part 2, from Chapter 5 to Chapter 13, sequentially introduces various effective multivariate statistical methods widely used in recent years and their application examples, including multiple regression analysis, analysis of variance, discriminant analysis, cluster analysis, principal component analysis, factor analysis, multidimensional scaling, correspondence analysis, and canonical correlation analysis. This book can serve as a textbook for statistical analysis courses offered in majors such as mathematics and applied mathematics, statistical science, and computational mathematics. It is also suitable for senior undergraduate or graduate students in engineering colleges, as well as in fields such as economics, management, psychology, and medical health statistics, as a textbook or reference book. Additionally, it provides a practical reference for practitioners in various fields, such as market research data analysis, for multidimensional data analysis."