基本素養 Basic Literacy

倫理推論
統計專業者主要從事蒐集資料和資料分析的工作,對資料的使用與保密,須遵循個資法的規範
Ethical Reasoning
Graduate students should be able to identify ethical dilemmas and to determine necessary courses of action
全球化思維
學生需具自我學習的能力,適時的掌握現在國際間統計分析方法的更替,及全球商務變化地趨勢
Global Vision
Graduate students should possess a global statistical perspective and an awareness of the global business

核心能力 Competence

口頭表達能力
學生應具備口頭表達及描述能力,能將統計方法做適當描述、及與人溝通統計想法、概念、使用方式
Speaking
Graduate students should be able to appreciate statistical research and to present research findings/ results effectively in speaking
寫作能力
學生能具備良好寫作能力,能將統計方法做適當描述、及與人溝通統計想法、概念、使用方式
Writing
Graduate students should be able to appreciate statistical research and to present research findings/ results effectively in writing
跨領域性之融合與解題
學生不僅需瞭解統計方法的來龍去脈,還需瞭解問題的本質,才能提出適合的統計方法解決問題
Interdiscip. Competence/ Prob. Solving
Graduate students should be able to integrate different functional areas in solving statistical problems
批判思考及創新力
學生要能就所面對的資料及時提供出可行的統計分析策略及迅速完成相關資料分析
Critical Thinking/ Innovation
Graduate students should be able to analyze data effectively and to recommend effective statistical methods
領導能力
同學需具備領導其他專長同仁解讀數據的才能
Leadership
Graduate students should be able to demonstrate leadership skills of a data analysis manager
團隊合作
學生應具有與其他背景專長者,一同解決職場上問題的能力
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
    4Inferences about a mean vector
    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