國立中山大學 111學年度第2學期 課程教學大綱

National Sun Yat-sen University 111Academic year Course syllabus

Course name(Chinese)


Course Code


Course name(English)


Type of the course











         同步遠距【透過網路直播技術,同時進行線上教學,得採Microsoft Teams、Adobe connect等軟體進行】
同步遠距含錄影【透過網路直播技術,同時進行線上教學並同時錄影,課程內容可擇日再重播,得採Microsoft Teams、Adobe connect等軟體進行】



1.Group project35%
3.Final exam40%

課程大綱 Course syllabus

         本課程教學大綱已提供完整英文資訊(本選項僅供統計使用,未提供完整英文資訊者,得免勾記)【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】

This course will teach you quantitative research methods when you conduct an industrial analysis. I will also take several types of industrial datasets as examples to discuss how to apply these quantitative methods. Because our discussion in this course is based on the concepts in economics and statistics, I strongly suggest you have a good understanding in economics (microeconomics or managerial economics) and statistics before you take this course.
This course has two parts: basic analysis tool/quantitative method, and different types of datasets you will possibly face and advanced quantitative method to deal with these data. In the basic part, I will focus on regression analysis. We will discuss how to use this method, and how to properly interpret the regression result; I will then introduce topics regarding endogeneity, nonlinear regression, and interaction terms.
In the data part, I will introduce several types of datasets, including time-series cross-sectional data, housing or artwork transaction data, market equilibrium data, and business registration data. While introducing these datasets, we will discuss the proper way to observe/interpret these data, and advanced methods to deal with these data. These methods some of which can help you to do a proper casual inference include difference-in-differences estimation (DID), propensity score matching (PSM), instrumental variable regression, quantile regression, and survival analysis.
Moreover, to let you have an opportunity to apply these quantitative methods to practice, you need to complete a group project. In this project, you have to pick an industry first. Then, you have to collect data, and try to find the demand or supply curve, or try to answer relevant questions in that industry via data. You can learn how to make decisions based on evidence; understand the idea of evidence-based management.

課程目標 Objectives

         1. Understand the quantitative methods in industrial analysis.
2. Know how to use market or industrial data to get market or industrial insights.
3. Know how to answer managerial questions via data.

授課方式 Teaching methods

         Lectures and Data Science Project

評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference

2.Group project30%
4.Final exam35%

參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use

         1. Required reading
1A. James H. Stock and Mark W. Watson (2010) 胥愛琦與呂瓊瑜譯。計量經濟學。台北:台灣培生教育 (ISBN: 978-986-280-021-8)。
1B. Related papers or industry analysis reports, which will be regularly posted on the National Sun Yat-sen Cyber University
2. Reference
2A. 陳正倉、林惠玲、陳忠榮與莊春發 (2014)。產業經濟學。台北:雙葉書廊 (ISBN: 978-986-7433-80-0)。

每週課程內容及預計進度 Weekly scheduled progress

WeekDateContent and topic
12023/02/12~2023/02/18Course Introduction
22023/02/19~2023/02/25Basic Tool: Regression Analysis
32023/02/26~2023/03/04Basic Tool: Regression Analysis
42023/03/05~2023/03/11Basic Tool: Regression Analysis and Causal Inference
52023/03/12~2023/03/18Basic Tool: Regression Analysis and Causal Inference
62023/03/19~2023/03/25Basic Tool: Regression Analysis and Nonlinear Models
82023/04/02~2023/04/08Time-series Cross-sectional Data: Fixed Effects Model, DID Estimator, and PSM
92023/04/09~2023/04/15Housing or Artwork Transaction Data: Hedonic Pricing Method
102023/04/16~2023/04/22Market Equilibrium Data: Instrumental Variable Regression
112023/04/23~2023/04/29Market Equilibrium Data: Instrumental Variable Regression
122023/04/30~2023/05/06Business Registration Data: Survival Analysis
132023/05/07~2023/05/13Business Registration Data: Survival Analysis
142023/05/14~2023/05/20Final Exam
152023/05/21~2023/05/27Group Presentation and Discussion
162023/05/28~2023/06/03Group Presentation and Discussion

課業討論時間 Office hours

         時段1 Time period 1:
時間 Time:星期三1000-1200
地點 Office/Laboratory:CM4067
時段2 Time period 2:
時間 Time:星期四1400-1600
地點 Office/Laboratory:CM4067

系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university

basic disciplines and core capabilities of the department and the university
Class activities and evaluation
本課程欲培養之能力與素養 This course enables students to achieve.紙筆考試或測驗 Test.課堂討論︵含個案討論︶ Group discussion (case analysis).個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment.群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment.個人口頭報告 Indivisual oral presentation.群組口頭報告 Group oral presentation.課程規劃之校外參訪及實習 Off-campus visit and intership.證照/檢定 License.
參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.課外閱讀 Outside reading.
※系所學生專業能力 Basic disciplines and core capabilities of the department
1.溝通能力與團隊合作(Communication ability and team cooperation) 1. Communication ability and team cooperation.V V V V    
2.進階管理知識(Advanced knowledge of management) 2. Advanced knowledge of management.VVV V V   V
3.倫理觀與社會責任實踐(Ethics and social responsibilities) 3. Ethics and social responsibilities.           
4.問題分析與解決能力(Ability of problem analysis and solution) 4. Ability of problem analysis and solution.VVV V V   V
5.國際觀與外語能力(Global perspective and foreign language ability) 5. Global perspective and foreign language ability.           
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skillsV V V V    
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilitiesVVV V V   V
3.終身學習能力。 3. Lifelong learningV V V V   V
4.倫理與社會責任。 4. Ethnics and social responsibility           
5.美感品味。 5. Aesthetic appreciation           
6.創造力。 6. Creativity           
7.全球視野。 7. Global perspective           
8.合作與領導能力。 8. Team work and leadership           
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature            

本課程與SDGs相關項目:The course relates to SDGs items:

SDG1-消除貧窮(No Poverty)
SDG2-消除飢餓 (Zero Hunger)
SDG3-良好健康與福祉(Good Health and Well-being)
SDG4-教育品質(Quality Education)
SDG5-性別平等(Gender Equality)
SDG6-乾淨水源與公共衛生(Clean Water and Sanitation)
SDG7-可負擔乾淨能源(Affordable and Clean Energy)
SDG8-優質工作與經濟成長(Decent Work and Economic Growth)
SDG9-工業、創新和基礎建設(Industry,Innovation and Infrastructure)
SDG10-減少不平等(Reduced Inequalities)
SDG11-永續城市(Sustainable Cities and Communities)
SDG12-責任消費與生產(Responsible Consumption and Production)
SDG13-氣候行動(Climate Action)
SDG14-海洋生態(Life Below Water)
SDG15-陸域生態(Life on Land)
SDG16-和平、正義和穩健的制度(Peace,Justice And Strong Institutions)
SDG17-促進目標實現的全球夥伴關係(Partnership for the Goals)

本課程校外實習資訊: This course is relevant to internship:

The course includes internship.(For statistical use only. If the course without internship, please ignore this item.)


Internship: The required or elective courses should include credits and learning hours. Students should participate in the corporative company or institution to practice and learn the real skills. An internship certification must be handed in at the end of internship to get the credits or to fulfil the graduation requirements.