學習多變量統計分析之基礎理論與實務應用.
Chapter 2- Matrix Algebra /矩陣代數
Chapter 4- Multivariate Normal Distribution /多變量常態分配
Chapter 6- Comparisons of Several Multivariate Means /多變量平均數比較
Chapter 7- Multivariate Linear Regression Models /多變量線性迴歸模型
Chapter 8- Principal Components /主成份
Chapter 9- Factor Analysis /因子分析
Chapter 10- Canonical Correlation Analysis /典型相關分析
Chapter 11- Discriminant and Classification /區別與分類
Chapter 12- Clustering /群集

Learn the basic theory and practical application of multivariate statistical analysis.
Chapter 2- Matrix Algebra/Matrix Algebra
Chapter 4- Multivariate Normal Distribution/Multivariate Normal Distribution
Chapter 6- Comparisons of Several Multivariate Means/Comparison of multivariate means
Chapter 7- Multivariate Linear Regression Models/Multivariate Linear Regression Models
Chapter 8- Principal Components/main components
Chapter 9- Factor Analysis/Factor Analysis
Chapter 10- Canonical Correlation Analysis/Canonical Correlation Analysis
Chapter 11- Discriminant and Classification /Difference and Classification
Chapter 12- Clustering/Cluster

Giving the overview of Multivariate Data Analysis and insights into Multivariate Data Analysis components. Main topics include:
1.Basic Statistics.
2.Dependence Method.
3.InterDependence Methods.
4.Structural Model.
5.Case Exercise.

Giving the overview of Multivariate Data Analysis and insights into Multivariate Data Analysis components. Main topics include:
1.Basic Statistics.
2.Dependence Method.
3.InterDependence Methods.
4.Structural Model.
5.Case Exercise.

Textbook: Applied Multivariate Statistical Analysis by Richard A. Johnson and Dean W. Wichern.

Textbook: Applied Multivariate Statistical Analysis by Richard A. Johnson and Dean W. Wichern.