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Curricular information is subject to change
Upon successful completion of the course, a student will have the ability to perform linear regression; to formally test statistical hypotheses and to evaluate empirical economic research. In addition, they will have an appreciation of the strength and weaknesses of econometrics and its use in the evaluation of competing economic theories and alternative policies.
Indicative Module Content:Core topics:
1) Statistics refresher
2) Linear regression with one regressor
3) Linear regression with multiple regressors
4) Non-linear models
Advanced topics (time permitting)
- Binary dependent variables
- Introduction to causal inference
- Introduction to predictions
Student Effort Type | Hours |
---|---|
Lectures | 22 |
Computer Aided Lab | 10 |
Autonomous Student Learning | 75 |
Total | 107 |
Students are required to have completed ECON 20040 Statistics for Economists, MIS 10010
Quantitative Analysis for Business, or an equivalent module on Basic Statistics and Probability.
It is recommended that students have an understanding of the basic Principles of Microeconomics and Principles of Macroeconomics such as ECON 10010 & ECON 10020
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Assignment: This assignment will require students to analyse particular datasets using R & answer a number of questions based on the results. Students may work in groups of up to three (3) people. | Week 7 | n/a | Graded | No | 30 |
Examination: Final exam | 2 hour End of Trimester Exam | No | Graded | No | 70 |
Remediation Type | Remediation Timing |
---|---|
Repeat | Within Two Trimesters |
• Group/class feedback, post-assessment
Advice will be provided to the class on what made for good and not-so-good projects/assignments with relevant examples.