The objective of this course is to equip students with the fundamental concepts of multivariate analysis and coding skill, which is helpful in their research.the objective of this course is to equip students with the fundamental concepts of multivariate analysis and co-curricular skills, which is helpful in black research.
The topics of this course include (1) Basic concepts of modeling, estimation and testing (2) Factor analysis;
(3) Discrimination analysis; (4) Cluster analysis; (5) MANOVA ;(6) Corresponding analysis; (7) SAS coding.
Midterm:40%; Final:40%; HW:20%
Text: (1) Applied multivariate statistical analysis by R. A. Johnson
(2) Applied multivariate techniques by Subhash Sharma
(3) SAS coding and data analysis by Pao-sheng Shen
The topics of this course include (1) Basic concepts of modeling, estimation and testing (2) Factor analysis;
(3) Discrimination analysis; (4) Cluster analysis; (5) MANOVA; (6) Corresponding analysis; (7) SAS coding.
Midterm:40%; Final:40%; HW:20%
Text: (1) Applied multivariate statistical analysis by R. A. Johnson
(2) Applied multivariate techniques by Subhash Sharma
(3) SAS coding and data analysis by Pao-sheng Shen
1. SAS 統計軟體與資料分析
2. Applied Multivariate Statistical Analysis (sixth edition),
Richard A. Johnson and Dean W. Wichern
1. SAS statistical software and data analysis
2. Applied Multivariate Statistical Analysis (sixth edition),
Richard A. Johnson and Dean W. Wichern
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| midtermmidterm midterm |
50 | |
| finalfinal final |
50 |
