Undergraduate Course: Decision-Making under Uncertainty (BUST10013)

Course Outline
School	Business School	College	College of Humanities and Social Science
Course type	Standard	Availability	Available to all students
Credit level (Normal year taken)	SCQF Level 10 (Year 3 Undergraduate)	Credits	20
Home subject area	Business Studies	Other subject area	None
Course website	None	Taught in Gaelic?	No
Course description	Methods for decision making under uncertainty: topics from stochastic programming, probabilistic dynamic programming, Markov processes and decision theory, with applications.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites	Students MUST have passed:	Co-requisites
Prohibited Combinations		Other requirements	Pre-requisite: Business Studies Honours entry. Note: For Economics with Management Science, and Mathematics and Business Studies programmes EITHER Mathematical Programming (BUST10011) OR Decision Making Under Uncertainty is a mandatory course in Year 4.
Additional Costs	None

Information for Visiting Students
Pre-requisites	Visiting students should have at least 3 Business Studies courses at grade B or above (or be predicted to obtain this). We will only consider University/College level courses.
Displayed in Visiting Students Prospectus?	Yes

Course Delivery Information

Delivery period: 2014/15 Semester 1, Available to all students (SV1)			Learn enabled: Yes	Quota: None
Web Timetable	Web Timetable
Class Delivery Information	There will be 4 optional review tutorials. To accommodate students' schedules, students will sign up for either the Thursday or Friday series of DMU tutorials: Thursdays 15.10-16.00 on 17 October (Week 5), 7 November(Week 8), 14 November (Week 9), 28 November (Week 11) in Seminar Room 2.14, Appleton Tower. Fridays 12.10-13.00pm on 18 October (Week 5), 8 November (Week 8), 15 November (Week 9), 29 November (Week 11) in Seminar Room 1, Chrystal MacMillan Building.
Course Start Date	15/09/2014
Breakdown of Learning and Teaching activities (Further Info)	Total Hours: 200 ( Lecture Hours 20, Summative Assessment Hours 2, Revision Session Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 172 )
Additional Notes
Breakdown of Assessment Methods (Further Info)	Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Exam Information
Exam Diet	Paper Name	Hours & Minutes
Main Exam Diet S2 (April/May)		2:00

Delivery period: 2014/15 Semester 1, Part-year visiting students only (VV1)			Learn enabled: No	Quota: None
Web Timetable	Web Timetable
Class Delivery Information	There will be 4 optional review tutorials. To accommodate students' schedules, students will sign up for either the Thursday or Friday series of DMU tutorials: Thursdays 15.10-16.00 on 17 October (Week 5), 7 November(Week 8), 14 November (Week 9), 28 November (Week 11) in Seminar Room 2.14, Appleton Tower. Fridays 12.10-13.00pm on 18 October (Week 5), 8 November (Week 8), 15 November (Week 9), 29 November (Week 11) in Seminar Room 1, Chrystal MacMillan Building.
Course Start Date	15/09/2014
Breakdown of Learning and Teaching activities (Further Info)	Total Hours: 200 ( Lecture Hours 20, Revision Session Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Additional Notes
Breakdown of Assessment Methods (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
No Exam Information

Summary of Intended Learning Outcomes
Objectives/Learning Outcomes Knowledge & Understanding On completion of the course students should: a) be able to discuss critically the practical use of the techniques covered; b) be able to use the modelling techniques covered to structure management problems; c) be able to solve models built using the techniques covered; d) be able to make inferences about a management problem based on the solution of a model built using the techniques covered. Cognitive Skills On completion of the course students should: a) demonstrate that they can identify which of the techniques covered is most suitable for a management problem; b) demonstrate that they can discuss the results of their analysis of a management problem in written reports. Key Skills On completion of the course students should: a) demonstrate that they can build and analyse a model of a real world management problem involving uncertainty; b) demonstrate their ability to apply their computer skills to support the analysis of a management problem involving uncertainty; c) demonstrate that they can present the findings of a quantitative analysis in a concise written report. Subject Specific Skills On completion of the course students should: a) have developed their modelling skills.

Assessment Information
One project on Markov decision processes 30%; final degree exam 70% Visiting Student Variant Assessment One project on Markov decision processes 50% and one essay (min 3,000 words) 50%.

Special Arrangements
None

Additional Information
Academic description	Not entered
Syllabus	The course covers four modelling techniques: Markov Chains, Markov Decision Processes, Decision Analysis and Sequential Sampling.
Transferable skills	Not entered
Reading list	Recommended: 1. F S Hillier & G J Lieberman, Introduction to Operations Research (McGraw-Hill). 2. W L Winston, Operations Research: Applications and Algorithms (Duxbury).
Study Abroad	Not entered
Study Pattern	Not entered
Keywords	DMU