| 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 |
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| 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 |
Introduction to Econometrics |
| 第3週 |
Statistics and Statistical Software |
| 第4週 |
Holiday |
| 第5週 |
Holiday |
| 第6週 |
Simple Regression Analysis |
| 第7週 |
Multiple Regression Analysis |
| 第8週 |
Forecasting |
| 第9週 |
Introduction to Time Series Analysis (I) |
| 第10週 |
Midterm Exam |
| 第11週 |
Introduction to Time Series Analysis (II) |
| 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
|
自主學習
內容 |
02.閱覽產業及學術相關多媒體資料
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| 學習評量方式 |
Participation: 15%
Homework: 15%
Case Presentation and Report: 40%
Midterm Exam: 30% |
| 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 |
| Monday (by appointment) |
| 聯合國全球永續發展目標(連結網址) |
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