預計講授內容大致包括以下數項：
(1). 多變量資料介紹與矩陣運算之複習。
(2). 多變量常態分配。
(3). 多變量變異數分析，profile analysis。
(4). Principal Component Analysis。
(5). Factor Analysis。
(6). Discriminant Analysis。
(7). Clustering。
(8). Multidimensional Scaling (MDS) 。
(9). LISREL 方法。The intended teaching content roughly includes the following:
(1). Copy between multi-variable data introduction and matrix operation.
(2). Multivariate constant allocation.
(3). Multivariate variation analysis, profile analysis.
(4). Principal Component Analysis.
(5). Factor Analysis.
(6). Discriminant Analysis.
(7). Clustering.
(8). Multidimensional Scaling (MDS).
(9). LISREL method.
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.
Johnson and Wichern, 2007, Applied Multivariate Statistical Analysis, 6th. ed., 雙葉。
Johnson and Wichern, 2007, Applied Multivariate Statistical Analysis, 6th. ed., Double Leaf.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 作業作業 Action |
15 | |
| 小考1小考1 Small Test 1 |
20 | |
| 小考2小考2 Tips 2 |
20 | |
| 期中考期中考 Midterm exam |
20 | |
| 期末考期末考 Final exam |
25 |
