學習多變量分析方法及其應用：
1.使學生了解多變量分析的方法與學理
2.能具備統計套裝軟體操作與分析技能
3.能體認多變量分析方法的嚴謹性及應用性
4.能利用多變量分析法於資料分析及論文寫作透過對研究生執行其論文研究極為重要的各項量化工具逐一介紹，包括：主成分分析、因素分析、區別分析、迴歸分析、典型相關分析、集群分析、多變量變異數分析、線性結構模式分析等...各種多變量的分析方法分別進行使用目的的說明及SPSS軟體的操作演練，藉以提昇碩士研究生對各種統計分析工具的應用能力。Learn multivariate analysis methods and their applications:
1. To enable students to understand the methods and theories of multivariate analysis
2. Be able to operate and analyze statistical package software
3. Be able to appreciate the rigor and applicability of multivariate analysis methods
4. Be able to use multivariate analysis methods in data analysis and thesis writing. Various quantitative tools that are extremely important for graduate students to perform their thesis research are introduced one by one, including: principal component analysis, factor analysis, difference analysis, regression analysis, canonical correlation analysis, Cluster analysis, multivariable variation analysis, linear structure pattern analysis, etc. Various multivariable analysis methods are explained separately for their purpose of use and the operation of SPSS software is practiced, so as to improve the application ability of various statistical analysis tools for master's students.
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.
1.吳萬益，2005，企業研究方法，華泰書局出版。
1. Wu Wanyi, 2005, Enterprise Research Methods, published by Huatai Book Company.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 課程參與課程參與 course participation |
30 | |
| 口頭及書面發表口頭及書面發表 Oral and written presentations |
40 | |
| 期刊閱讀心得分享期刊閱讀心得分享 Journal reading experience sharing |
30 |
