Last modified: 24 Jun 2020 14:31
The energy and the financial sector relies heavily on analysis based on quantitative and empirical methodologies. This course develops a mathematical and statistical ‘toolbox’ for the participant, essential for the in-depth understanding of economic analysis. This course surveys some of the basic methods used to understand the underlying theories and empirical examples and tests found in these fields.
The first part of the course covers basic mathematical models common across these fields. The second part of the course develops standard data analysis methods, including multivariate regression. Applications from various energy economic areas are used in order to illustrate the mathematical and statistical concepts.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Full Year | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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Participants will be introduced to basic mathematical concepts such as discounting, calculus, unconstrained and constrained optimisation, and matrix algebra focusing on straightforward examples of how these concepts are applied. The course will also review basic statistical concepts and extend them to hypothesis testing and least squares regression methodologies which form the backbone of empirical testing of theories. Examples and applications from various areas of energy economics and finance will be used in order to illustrate the methods. The course will also discuss some potential problems in these methodologies as well as offer ways to overcome these problems.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Students are given the option to choose between an essay and an exam, they will not do both. Individual feedback through online platform.
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Word Count | 3000 | |
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Students are given the option to choose between an essay and an exam, they will not do both. Generic feedback will be provided through the online platform. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Assessment Type | Formative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
informal feedback via model answers |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Conceptual | Analyse | By the end of the course, students should be able to demonstrate an understanding of probability and its applicability in modelling |
| Procedural | Evaluate | By the end of the course, students should be able to demonstrate an ability to formulate and evaluate testable statistical hypotheses using the linear regression model |
| Reflection | Evaluate | By the end of the course, students should be able to demonstrate an ability to carefully interpret regression results |
| Conceptual | Understand | By the end of the course students will acquire a knowledge and understanding of a variety of economic and financial data |
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