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DRPS : Course Catalogue : Business School : Business Studies

Undergraduate Course: Decision Analytics (BUST10133)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course provides students with an understanding of the techniques available for the analysis of management problems in which uncertainty plays a significant role.
Course description The techniques used for the analysis of management problems are illustrated using examples based on applications from the areas of capacity planning, quality control, consumer behaviour, inventory management, finance and purchasing.

Outline Content

The course is comprised of four modules which cover four modelling techniques:
1. Markov Chains
2. Markov Decision Processes
3. Decision Analysis
4. Sequential Sampling

Student Learning Experience

1. Lectures explain the concepts underpinning four modelling techniques for management problems involving uncertainty and present a series of illustrative examples. Lectures are supported by suggested readings from the recommended texts. Students are advised to attend all lectures.
2. Students gain further experience in the application of the techniques to management problems by working through the example questions uploaded in the 'Tutorials' folder on Learn at their own pace, with feedback via online solutions.
3. Optional example class tutorials summarise each topic covered by reviewing a past examination question.
4. Additional web-based material provides students with feedback as they tackle further past examination questions.
5. The coursework project requires students to build a model of a management case study, to analyse the model using techniques covered in the course and to present the findings in a written report. Students will develop skills in the use of Microsoft Excel to support their analysis of the model.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements Available to all students from the Business Schools as well students from other Schools (Mathematics, Economics, Informatics) who are on joint programmes with the Business School.
Information for Visiting Students
Pre-requisitesVisiting students must have at least 4 Business courses at grade B or above. This MUST INCLUDE at least one Finance course at intermediate level. We will only consider University/College level courses.
High Demand Course? Yes
Course Delivery Information
Academic year 2024/25, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 4, Supervised Practical/Workshop/Studio Hours 2, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 168 )
Assessment (Further Info) Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Additional Information (Assessment) 30% Coursework (Group) - includes 20% peer evaluation

70% Written Exam (Individual) - 3 hours
Feedback Formative: Feedback will be provided throughout the course.

Summative: Feedback will be provided on the assessments within agreed deadlines.
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. Discuss critically the practical use of the techniques covered.
  2. Apply the modelling techniques covered to structure management problems.
  3. Solve models built using the techniques covered.
  4. Make inferences about a management problem based on the solution of a model built using the techniques covered.
Reading List

Hillier, F. S & Lieberman, J.G. (2015). Introduction to Operations Research. NY: McGraw-Hill.

Further suggestions posted on Learn.
Additional Information
Graduate Attributes and Skills Communication, ICT, and Numeracy Skills

After completing this course, students should be able to:

Convey meaning and message through a wide range of communication tools, including digital technology and social media; to understand how to use these tools to communicate in ways that sustain positive and responsible relationships.

Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.

Knowledge and Understanding

After completing this course, students should be able to:

Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore
and solve them responsibly.
KeywordsDecision Analytics
Course organiserDr Maurizio Tomasella
Course secretaryMiss Tamara Turford
Tel: (0131 6)50 8074
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