基本素養 Basic Literacy

具國際觀與流利的外語溝通能力,博士班畢業生並具專業外語撰寫及發表學術論文的能力
With global vision and foreign language proficiency. PhD graduates are able to publish academic paper internationally.
具備專業倫理與社會責任感
With professional ethics and social responsibilities.
具備地球公民觀,尊重多元文化、環境永續與世代正義
As citizen of the earth, respect multi-culture and enhance environment sustainability and generation justice.
具備人文關懷與環境美學素養
With spirit of humanism and environmental aesthetics self-discipline.

核心能力 Competence

能掌握空間規劃設計專業理論內涵與發展議題
Ability to grasp the content of spatial planning and design theories and development issues.
能掌握並靈活運用空間規劃設計方法學於研究發展
Ability to grasp and flexibly implement the methodologies of spatial planning and design in research and development.
能發揮創意整合學理與操作技能,達成最佳之空間規劃設計實務工作。
Ability to innovatively integrate theories and practical skills to achieve the best spatial planning and design practices.
具獨立研究與學術發表交流能力
Ability of independent study and academic publishing and communication.
具備分析論述與有效表達溝通能力
Ability of accurate analysis and expound and effective communication.
具備規劃(或設計)與教授專業課程、指導學生的能力
博士班畢業生從事教學工作應具備之核心能力。
PhD graduates are able to teach planning (/design) professional courses and supervise students.
具備團隊合作與領導管理能力
Ability of teamwork and leadership.
具備跨領域知識整合應用與研發能力
Ability of integrating, implement, and developing inter-disciplinary knowledge from professional aspect.

課程概述 Course Description

透過理論與實例,介紹多變量分析之應用。內容包括線性代數簡介、機率分佈函數、MLE、OLS、GLS、LISREL、Discrete Choice、主成分與因子分析、判別分析、群落分析等模式之理論與應用。
Introduce the application of multivariate analysis with the theory and examples. The content includes the theory and application of models of linear algebra, probability distribution functions, MLE, OLS, GLS, LISREL, Discrete Choice, principal component and factor analysis, discriminant analysis, and community analysis.

課程學習目標 Course Objectives

  • 1. Fundamental concepts of linear algebra and econometric analysis;
  • 2. Operational capability of statistical software;
  • 3. Applications of multivariate analysis techniques.
  • 課程進度 Progress Description

    進度說明 Progress Description
    1Introduction to Matrix Algebra and Simple Linear Regression
    2Ordinary Least Squares: Basic Formula
    3Ordinary Least Squares: Inference and Model Structure
    4Restricted Regression and Hypothesis Testing
    5Data Problems: Multi-Collinearity and Missing Data
    6Data Problems: Measurement Error & Instrumental Variables
    7Generalized Least Squares: Heteroscedasticity & Time Series
    8Progress Report (1) & Review
    9Midterm
    10Non-linear Regression: Geographically Weighted Regression
    11Applications of Matrix Algebra: Eigenvectors and Eigenvalues
    12Principal Components & Factor Analysis
    13Discriminant and Classification Analysis
    14Cluster Analysis
    15Progress Report (2) and LISREL
    16Discrete Choice Model and Nested Logit
    17Logistic Regression & Fuzzy Logic
    18Final Exam
     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.

    課程是否與永續發展目標相關調查
    Survey of the conntent relevant to SDGs

    本課程與SDGs相關項目如下:
    This course is relevant to these items of SDGs as following:
    • 消除貧窮 (No poverty)
    • 健康與福祉 (Good health and Well Being)
    • 可負擔能源 (Affordable and clean energy)
    • 就業與經濟成長 (Decent work and Economic growth)
    • 永續城市與社區 (Sustainable cities and communities)
    • 氣候行動 (Climate action)

    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