production
Skip to Content

Log In

  1. University Home
  2. Catalogue of Courses
  3. Online
  4. 2024-2025
  5. Economics
  6. EC55D3: Data Analysis for Energy

EC55D3: DATA ANALYSIS FOR ENERGY (2024-2025)

Last modified: 23 Jul 2024 11:07


Course Overview

The main aim of the course is to equip students with good analytical skills in order to understand the role of data within the energy sector, in particular in the context of decision making under uncertainty and to apply time series econometric tools 

After completing the course students should acquire not only a sound knowledge about underlying statistical concepts, but also practical skills of using that knowledge for solving practical problems within the energy sector.

Special attention in this course is given to the Oil&Gas sector and the discussed topics are referred to the examples from this sector.

Course Details

Study Type Postgraduate Level 5
Term Second Term Credit Points 15 credits (7.5 ECTS credits)
Campus Aberdeen Sustained Study No
Co-ordinators
  • Dr Marc Gronwald

What courses & programmes must have been taken before this course?

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

This course introduces students to essential concepts of statistics such as statistical distributions, random number generation, Monte Carlo Simulation, statistical tests, time series data, time series models like ARMA,

Studying this course, students obtain a broad theoretical and practical knowledge of these topics as well as the understanding for and how to apply these concepts in the context of the energy industry.

The main course objectives are:

  • To develop knowledge and understanding of essential statistical concepts such as probabilities, random variables, and distributions.
  • To develop the practical skills that equip students with the ability to apply Monte Carlo Simulations in the context of decision making under uncertainty.
  • To develop intellectual skills by understanding time series data, and the reduced form time series models like ARMA.
  • To develop the practical skills to apply time series models.

The specific topics covered in this course include:

  • The concept of random variables and their distributions. This topic gives the students sound theoretical underpinnings for the application of Monte Carlo Simulation in the context of the energy industry.
  • The concept of parameter estimation. This topic provides the students with knowledge of how to use existing data in decision analysis under uncertainty.
  • The discussion of the role of uncertainty in economic decision making. This topic is relevant for many within the Oil&Gas Industry.
  • The concept of time series data and time series modelling.

Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

Take Home Exam

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback

3000 words. The submitted coursework will be commented.
Learning Outcomes
Knowledge LevelThinking SkillOutcome
ConceptualAnalyseTo develop knowledge and understanding of essential statistical concepts such as probabilities, random variables and distributions.
ConceptualEvaluateTo develop intellectual skills by understanding time series data and the reduced form time series models like ARMA.
ProceduralEvaluateTo develop the practical skills to apply time series models.
ReflectionEvaluateTo develop the practical skills that equip students with the ability to apply Monte Carlo Simulations in the context of decision making under uncertainty.

Formative Assessment

There are no assessments for this course.

Resit Assessments

Essay

Assessment Type Summative Weighting 100
Assessment Weeks Feedback Weeks

Look up Week Numbers

Feedback Word Count
Learning Outcomes
Knowledge LevelThinking SkillOutcome
Sorry, we don't have this information available just now. Please check the course guide on MyAberdeen or with the Course Coordinator

Course Learning Outcomes

Knowledge LevelThinking SkillOutcome
ConceptualAnalyseTo develop knowledge and understanding of essential statistical concepts such as probabilities, random variables and distributions.
ReflectionEvaluateTo develop the practical skills that equip students with the ability to apply Monte Carlo Simulations in the context of decision making under uncertainty.
ConceptualEvaluateTo develop intellectual skills by understanding time series data and the reduced form time series models like ARMA.
ProceduralEvaluateTo develop the practical skills to apply time series models.
 

Compatibility Mode

We have detected that you are have compatibility mode enabled or are using an old version of Internet Explorer. You either need to switch off compatibility mode for this site or upgrade your browser.