Last modified: 23 Jul 2024 10:43
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 | First Term | 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 | 75 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
One exam style open book assessment consisting of up to five compulsory questions with a maximum of 3000 words for the entire assessment. There is a one-week window to complete the examination. Feedback is given on the examination. |
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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 |
| Conceptual | Understand | By the end of the course students will acquire a knowledge and understanding of a variety of economic and financial data |
| 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 |
| Assessment Type | Summative | Weighting | 5 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
For participation in online discussion and community. Expectations set that students will contribute by posting at least once per week to online discussion forums either by posing a question or by responding and interacting with fellow students. Count of contributions across semester be tallied to allocate mark. Token submissions will not be counted. (A definition of a token submission will be provided to students e.g. student posing a random question not connected to the learning materials. A C6 will be given to the student if at the end of the module a student has failed to make any submissions to the online discussion forums across the semester.) |
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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 |
| Conceptual | Understand | By the end of the course students will acquire a knowledge and understanding of a variety of economic and financial data |
| 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 |
| Assessment Type | Summative | Weighting | 20 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Distinct from those used for formative assessment, up to two online quizzes during the semester restricted to a single attempt and with time limit. Feedback given with correct answers after marking. (Note: The technical content of courses means the learning outcomes are able to be effectively tested via this route). |
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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 |
| Conceptual | Understand | By the end of the course students will acquire a knowledge and understanding of a variety of economic and financial data |
| 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 |
| Assessment Type | Formative | Weighting | 0 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
Up to 5 progression tests consisting of up to ten questions each where detailed feedback is given for correct and incorrect answers. A progression test must be successfully completed before moving on to the next section. Up to 10 self-assessments ranging between 3 and 10 questions each, depending upon the content within the relevant topic. Detailed feedback is given for correct and incorrect answers. For information – the feedback on the formative assessment is automated part the Moodle platform developed by CAPDM |
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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 |
| Conceptual | Understand | By the end of the course students will acquire a knowledge and understanding of a variety of economic and financial data |
| 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 |
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
One exam style open book assessment consisting of up to five compulsory questions with a maximum of 3000 words for the entire assessment. There is a one-week window to complete the examination. Feedback is given on the examination. |
|||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
|
|
||
| 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 |
| 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 |
| 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 |
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