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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2020/2021

Information in the Degree Programme Tables may still be subject to change in response to Covid-19

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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Economics and Business Analytics (CMSE11414)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits15 ECTS Credits7.5
SummaryThe objectives of the course are to give students both knowledge and understanding of selected key concepts in business economics and management science and the knowledge to understand when these concepts may be useful to make decisions. The basic skills to implement these techniques will also be developed. The first part of this course places special focus on the factors that influence the firms' economic environment, which, in turn, determines the level, growth and sustainability of profits. These include consumer demand, technology and costs, competition, entry, pricing strategies, and government regulations. The second part of this course focuses on the science behind decision-making, covering a wide range of quantitative methods typically employed to that end, such as forecasting and optimisation, and data visualization.
Course description The Economics part of the course comprises the following topics:

1) Quantitative Demand Analysis (drivers of demand and the econometric estimation of demand functions).

2) Productivity and Efficiency Analysis (Economies of Scale and Data Envelopment Analysis)

3) Market Structure, Conduct and Performance (The functioning of the market and the SCP Paradigm)

4) Pricing with Market Power (Price Discrimination and Versioning)

5) Network Economics



The Business Analytics part of the course comprises the following topics

6) Forecasting and Optimization (Time-series analysis and Linear Programming)

7) Decision Analysis (Single and multi-criteria methods, Location Analysis)

8) Data Visualization

9) Introduction to Data Mining (Clustering)



Student Learning Experience:

The weekly lectures will explore core concepts while the tutorials focus on the practical applications. Real-life examples will be discussed in class.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2020/21, Not available to visiting students (SS1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 117 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 100%

Two assignments (one on Economics and one on Business Analytics) each contributing 50%.

The assignment on Economics is related to Learning Outcome 1.

The assignment on Business Analytics is related to Learning Outcome 2.
Feedback All students will be given at least one formative feedback or feed forward event for every course they undertake, provided during the semester in which the course is taken and in time to be useful in the completion of summative work on the course. Such feedback may be at course or programme level, but must include input of relevance to each course in the latter case.

Feedback on formative assessed work will be provided within 15 working days of submission, or in time to be of use in subsequent assessments within the course, whichever is sooner. Summative marks will be returned on a published timetable, which has been made clear to students at the start of the academic year.

Students will gain feedback on their understanding of the material when they discuss their answers to the tutorial questions in the tutorials. Students may also ask questions in Lectures to assess their knowledge.

Week 1 - 11 Questions at lecturers

Week 2 - 11 Discussion in tutorials

Weeks 1-12 Ad hoc appointments that are made as required with the lecturers
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Apply economic concepts for the quantitative analysis of demand, pricing, productivity or efficiency as well as the qualitative understanding of market stucture and its implications on firm performance.
  2. Apply tools of business analytics (including data visualization) to the analysis of future demand, resource optimization, optimal business location or customer segmentation.
Reading List
Baye, M. Managerial Economics and Business Strategy. McGraw Hill. (7th ed)

Anderson, D.R. Sweeney, D.J., Williams, T.A. and Wisniewski, M. (2009). An Introduction to Management Science: Quantitative Approaches to Decision Making. South Western
Additional Information
Graduate Attributes and Skills After completing this course, students should be able to:

-use certain economic principles to recommend decisions to managers or evaluate certain decisions that managers make in the light of economic principles and models;

-analyse the demand, cost, and competitive conditions facing an organisation and their impacts on pricing, productivity and/or efficiency;

-identify situations in which model-building methods can be applied in the management decision process;

-build and solve certain types of model in Excel and interpret their solutions;

-use several analytics software packages;

-design effective data visualizations.
KeywordsNot entered
Contacts
Course organiserDr Augusto Voltes-Dorta
Tel: (0131 6)51 5546
Email: Augusto.Voltes-Dorta@ed.ac.uk
Course secretaryMiss Fionna Ogilvie
Tel: (0131 6)51 3028
Email: Fionna.Ogilvie@ed.ac.uk
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