## 基本素養 Basic Literacy

With global vision and foreign language proficiency. PhD graduates are able to publish academic paper internationally.

With professional ethics and social responsibilities.

As citizen of the earth, respect multi-culture and enhance environment sustainability and generation justice.

With spirit of humanism and environmental aesthetics self-discipline.

## 核心能力 Competence

Ability to grasp the content of spatial planning and design theories and development issues.

Ability to grasp and flexibly implement the methodologies of spatial planning and design in research and development.

Ability to innovatively integrate theories and practical skills to achieve the best spatial planning and design practices.

Ability of independent study and academic publishing and communication.

Ability of accurate analysis and expound and effective communication.

PhD graduates are able to teach planning (/design) professional courses and supervise students.

Ability of teamwork and leadership.

Ability of integrating, implement, and developing inter-disciplinary knowledge from professional aspect.

## 課程概述 Course Description

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