TOKT1127 — ECONOMETRICS 1
Mô tả học phần
Econometrics is the application of statistical techniques to economic models in an effort to achieve numerical results and to verify economic theorems. The purpose of this course is to introduce students to the theory and application of econometric methods. It covers the basic tools of estimation and inference in the context of the single-equation linear regression model, deals primarily with least squares methods of estimation. The course emphasizes the intuitive understanding and practical application of these basic tools of regression analysis, as distinct from their formal theoretical development. Course material is presented predominantly in scalar terms. The practical part introduces the R language as the main tool.
Yêu cầu của học phần
Requirements for Final Examination
Attendance score must be at least 5 (according to University regulations).
See Appendix 2, Rubric 1 for attendance evaluation.
Requirements for Class Attendance
Participate at least 80% of total class
In cases of absence due to force majeure, students are expected to actively acquire the required knowledge through materials provided by the instructor and other assigned readings.
Requirements for In-class Behaviour
Respect between students and instructors.
Contribute to lesson, take notes and answer questions
Read assigned materials in advance, do Homework
Do not disturb the others in class
Do not eat, use cell phone in class
Laptop, ipad are allowed if needed in practicing, calculating only.
Kế hoạch giảng dạy
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Học liệu
- 1. Course Books (bắt buộc có ít nhất 01 giáo trình được Đại học phê duyệt, không quá 02 giáo trình, ưu tiên xuất bản trong vòng 5 năm gần nhất), đánh số để kết nối với Bảng 4
- Regression Modeling with Actuarial and Financial Applications — Edward W. Frees, Cambridge, 2010
- 2. References
- Introductory Econometrics - A Modern Approach — Jeffrey M. Wooldridge, 6th Edition, 2016
- Introduction to Linear Regression Analysis — Douglas C. Montgomery, 5th Edition, 2012
- Applied Econometrics with R — Christian Kleiber, Springer, 2008
- SOA Exam SRM Study Manual — Runhuan Feng et al, ACTEX Learning, 2018
- Standard lecture notes/slides …
- 3. Other resources available at the University Library