Module Information
Course Delivery
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Group based coursework project (1,000 words per person). | 20% |
| Semester Assessment | 1 Hours Class based unseen test. | 10% |
| Semester Exam | 3 Hours | 70% |
| Supplementary Assessment | (Students must take elements of assessment equivalent to those that led to failure of the module.) | 30% |
| Supplementary Exam | 3 Hours (Students must take elements of assessment equivalent to those that led to failure of the module.) | 70% |
Learning Outcomes
On successful completion of this module students should be able to:
1. Demonstrate familiarity with and an appreciation of the need for statistical foundations behind regression analysis.
2. Estimate regression models using a statistical package, and interpret and critically evaluate the results of a regression analysis.
3. Apply and interpret key diagnostic tests.
4. Describe remedies for problems associated with the violation of assumptions underlying the linear regression model.
5. Critically assess the policy implications of econometric models in a range of contexts.
Brief description
This module introduces essential quantitative tools used in economic research to analyze economic data and model economic phenomena. The module presents a detailed and in-depth treatment of the method of ordinary least squares (OLS) used in estimating quantitative relationship between economic variables, the assumptions behind the appropriate use of OLS, the implications of the violation of such assumptions and the remedial measures.
Content
• Primer to regression analysis
• Ordinary Least Squares estimation
• Two-variable and multiple regression models
• Hypothesis testing
• Regression models using qualitative data
• Violation of the assumptions:
- Multicollinearity
- Heteroscedasticity
- Autocorrelation
- Non-Normality
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Development of quantitative (mathematical, statistical, econometric) skills. |
| Communication | Development of oral and written communication including data response. |
| Improving own Learning and Performance | Development of quantitative analytical skills instrumental for learning in other modules. |
| Information Technology | Use of statistical (computer) software for data and regression analysis. |
| Personal Development and Career planning | Development of quantitative analytical skills useful in a wide range of professions and in further study. |
| Problem solving | Identifying the problem to be solved Finding pertinent data in order to solve the problem. Application of appropriate methods and statistical tools for solving the problem Understanding and interpretation of results. |
| Research skills | Basic Research Skills pertaining to operationalization of economic theory into testable propositions. Testing these propositions using appropriate data and statistical techniques Analysis of economic data. |
| Subject Specific Skills | Use of statistical computer software to assess economic performance. Economic and policy analysis (in other subject areas of economics). |
| Team work | Team working skills through self-study working groups. |
Notes
This module is at CQFW Level 5