Last modified: 31 Jul 2023 11:19
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 indepth 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 

Session  First Sub Session  Credit Points  15 credits (7.5 ECTS credits) 
Campus  Aberdeen  Sustained Study  No 
Coordinators 

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 oneweek window to complete the examination. Feedback is given on the examination. 
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). 
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.) 
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 selfassessments 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 
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 oneweek 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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