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.Topics covered include basic probability theory, introduction of random variables, basic statistical inference (estimation and testing hypothesis), principle component analysis, factor analysis, discriminant analysis, cluster analysis, and categorical data analysis.

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.Topics covered include basic probability theory, introduction of random variables, basic statistical inference (estimation and testing hypothesis), principle component analysis, factor analysis, discriminant analysis, cluster analysis, and category data analysis.

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