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 theories and practical applications of multi-variable statistical analysis.
Chapter 2- Matrix Algebra / Matrix Generations
Chapter 4- Multivariate Normal Distribution / Multivariate Normal Distribution
Chapter 6- Comparisons of Several Multivariate Means/Comparisons of Multivariate Means
Chapter 7- Multivariate Linear Regression Models/Multivariate Linear Regression Models
Chapter 8- Principal Components / Principal Components
Chapter 9- Factor Analysis / Factor Analysis
Chapter 10- Canonical Correlation Analysis / Typical Related Analysis
Chapter 11- Discriminant and Classification /Discriminant and Classification
Chapter 12- Clustering /Clustering
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. w i car let you.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時考平時考 Regular exam |
35 | 包括平時考(30%)、上機考(5%) |
| 期中考期中考 Midterm exam |
30 | |
| 期末考期末考 Final exam |
35 |
