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. Enable students to understand the methods and science of multivariate analysis
2. Be able to have the operation and analysis skills of the stereoscopic software
3. Ability to recognize the seriousness and application of multivariate analysis methods
4. The multi-variable analysis method can be used to introduce various important quantification tools for graduate students through the implementation of their literary research, including: principal component analysis, factor analysis, regional analysis, replication analysis, typical related analysis, cluster analysis, multi-variable variation analysis, linear structure pattern analysis, etc.... Various multi-variable analysis methods can explain the purpose of use and the operation performance of SPSS software, so as to improve the application ability of master graduate students to various statistical analysis tools.

Fields in the biological, physical and social sciences frequently collect observations involved several variables. Data analysis on such cases becomes truly fascinating and challenging. Modern computer packages readily provide the techniques for complex statistical data analysis. Therefore, we integrate several aspects of computer usage into the course for illustration. This course contains an understanding of the basic knowledge and well-developed statistical theories necessary for selecting appropriate techniques in a wide variety of application environments. Some topics including principal analysis, factor analysis, canonical correlation analysis, discriminant analysis, clustering and classification analysis etc. are contained in the course.

Fields in the biological, physical and social sciences frequently collect observations involved several variables. Data analysis on such cases becomes truly fascinating and challenging. Modern computer packages readily provide the techniques for complex statistical data analysis. Therefore, we integrate several aspects of computer usage into the course for illustration. This course contains an understanding of the basic knowledge and well-developed statistical theories necessary for selecting appropriate techniques in a wide variety of application environments. Some topics including principal analysis, factor analysis, canonical correlation analysis, discriminant analysis, clustering and classification analysis etc. are contained in the course.

1.吳萬益，2005，企業研究方法，華泰書局出版。

1. Wu Wanyi, 2005, Corporate Research Methods, published by Huatai Books Bureau.