## 基本素養 Basic Literacy

Ethical Reasoning
Graduate students should be able to identify ethical dilemmas and to determine necessary courses of action

Global Vision
Graduate students should possess a global statistical perspective and an awareness of the global business

## 核心能力 Competence

Speaking
Graduate students should be able to appreciate statistical research and to present research findings/ results effectively in speaking

Writing
Graduate students should be able to appreciate statistical research and to present research findings/ results effectively in writing

Interdiscip. Competence/ Prob. Solving
Graduate students should be able to integrate different functional areas in solving statistical problems

Critical Thinking/ Innovation
Graduate students should be able to analyze data effectively and to recommend effective statistical methods

Graduate students should be able to demonstrate leadership skills of a data analysis manager

Teamwork
Graduate students should be able to coordinate actions and solve problems jointly with other members of a professional team

## 課程概述 Course Description

1.多變量分析介紹。2.基本線性代數介紹。3.基本統計介紹。4.多變量常態分配。5.推論與比較。6.主成份分析。7.因子分析。8.判別與分類分析。9.群落分析。10.SAS與Statgraphics之介紹。
Topics on multivariate analysis basically can be divided into two parts: one is for mean vectors, the other one is for the analysis of covariance matrix (principal components analysis, factor analysis, discrimination and classification etc.). This course mainly focuses on the analysis of covariance structure, trying to explore the associations among a variety of variables. Emphasis will also be placed on cluster analysis, which deals with grouping subjects into several subpopulations. Inference on the mean vector(s) will be discussed if time is available.

## 課程學習目標 Course Objectives

• Understand the principles of each multivariate method.
• Select the appropriate methods in function to the research Problem.
• Apply those methods to real-world problems.
• Interpret and report the results from the analysis.
• ## 課程進度 Progress Description

進度說明 Progress Description
1Overview of multivariate analysis
2Short Review of Matrix Algebra
3Multivariate normal distribution
5Comparisons of several multivariate means
6Comparisons of several multivariate means
7Principal components
8Factor analysis
9Confirmatory factor analysis
10Structured equation models
11Canonical correlation
12Discriminate analysis
13Logistic regression
14Classification tree
15Cluster analysis
16Multidimensional scaling
17Corresponding analysis
18Final term (project presentation)
以上每週進度教師可依上課情況做適度調整。The schedule may be subject to change.

## 有關課程其他調查 Other Surveys of Courses

1.本課程是否規劃業界教師參與教學或演講? 否
Is there any industry specialist invited in this course? How many times? No
2.本課程是否規劃含校外實習(並非參訪)? 否
Are there any internships involved in the course? How many hours? No
3.本課程是否可歸認為學術倫理課程? 否
Is this course recognized as an academic ethics course? In the course how many hours are regarding academic ethics topics? No
4.本課程是否屬進入社區實踐課程? 否
Is this course recognized as a Community engagement and Service learning course? Which community will be engaged? No