課程與核心能力關聯配比(%) |
課程目標之教學方法與評量方法 |
課程目標 |
核心能力 |
配比(%) |
教學方法 |
評量方法 |
This course aims to make students familiar with relevant concepts in fundamental Econometrics and data science and apply the methods in practice. |
1.獨立分析 |
2.專業知識 |
3.創意 |
4.科學方法運用 |
|
|
|
|
授課內容(單元名稱與內容、習作/每週授課、考試進度-共16週加自主學習) |
週次 |
授課內容 |
第1週 |
Course Introduction |
第2週 |
Holiday |
第3週 |
Introduction to Econometrics |
第4週 |
Review of Statistics |
第5週 |
Statistical Analysis and Statistical Software |
第6週 |
Simple Regression Analysis |
第7週 |
Multiple Regression Analysis |
第8週 |
Forecasting |
第9週 |
Midterm Exam |
第10週 |
Introduction of Time Series Analysis |
第11週 |
Stationary in Time Series data |
第12週 |
Midterm Case Presentation |
第13週 |
AR, MA, ARMA, and relevant data science models |
第14週 |
Other relevant topics |
第15週 |
Final Case Presentation |
第16週 |
Final Case Presentation
Self-directed learning in the course (Discussion for final report)
Self-directed learning in the course (Discussion for final report) |
自主學習 內容 |
|
|
學習評量方式 |
Participation: 15%
Homework: 20%
Case Presentation and Report: 40%
Midterm Exam: 25% |
教科書&參考書目(書名、作者、書局、代理商、說明) |
No textbook required.
Reference books:
1.Jeffrey M. Wooldridge (2013), Introductory Econometrics: A Modern Approach, 5th Edition, South-Western Cengage Learning.
2.Cowpertwait, P. S., & Metcalfe, A. V. (2009). Introductory time series with R. Springer Science & Business Media.
3.Shumway, R. H., Stoffer, D. S., & Stoffer, D. S. (2000). Time series analysis and its applications (Vol. 3). New York: springer. |
課程教材(教師個人網址請列在本校內之網址) |
Lecture notes from the books and the instructor. |
課程輔導時間 |
Tuesday (by appointment) |
聯合國全球永續發展目標(連結網址) |
|