Undergraduate Course: Decision-Making under Uncertainty (BUST10013)

Course Outline
School	Business School	College	College of Humanities and Social Science
Credit level (Normal year taken)	SCQF Level 10 (Year 3 Undergraduate)	Availability	Available to all students
SCQF Credits	20	ECTS Credits	10
Summary	This 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. Syllabus 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 in the course booklet at their own pace, supported by the web-based materials provided. 3. Optional example class tutorials summarise each topic covered by reviewing a past examination question. 4. Additional web-based material provides support for students 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 use their knowledge of the Microsoft Excel package to support their analysis of the model.

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.

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.
High Demand Course?	Yes

Course Delivery Information

Academic year 2015/16, 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, Summative Assessment Hours 2, Revision Session Hours 2, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 172 )
Assessment (Further Info)	Written Exam 70 %, Coursework 30 %, Practical Exam 0 %
Additional Information (Assessment)	One 1000-word project report 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%.
Feedback	1. Generic feedback on your COURSEWORK, together with individual marks, will be posted on Learn within 15 working days from the submission deadline; also the individual feedback for your coursework will be available to collect from the Business School UG Office (Room 1.11, Business School, 29 Buccleuch Place), but you will not be able to take away the original piece of coursework, as it may be required by the Board of Examiners. 2. The optional EXAMPLE CLASS TUTORIALS at the end of each module provide the opportunity to do further exercises and ask questions. 3. Your EXAMINATION marks will be posted on Learn (together with generic feedback and examination statistics) as soon as possible after the April/May Diet Board of Examiners' meeting (normally early-mid JUNE). During the summer months (i.e. mid/end June - end August), you may come into the Business School UG Office (Room 1.11, Business School, 29 Buccleuch Place) to look at your examination scripts. Note that you will not be able to remove any examination scripts from the UG Office as they may be required by the Board of Examiners. Continuing students will also be given the opportunity to review their examination scripts early in the new academic year in Semester 1 (i.e. in October).
Exam Information
Exam Diet	Paper Name		Hours & Minutes
Main Exam Diet S2 (April/May)			2:00

Academic year 2015/16, Part-year visiting students only (VV1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
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 )
Assessment (Further Info)	Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment)	One 1000-word project report 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%.
Feedback	1. Generic feedback on your COURSEWORK, together with individual marks, will be posted on Learn within 15 working days from the submission deadline; also the individual feedback for your coursework will be available to collect from the Business School UG Office (Room 1.11, Business School, 29 Buccleuch Place), but you will not be able to take away the original piece of coursework, as it may be required by the Board of Examiners. 2. The optional EXAMPLE CLASS TUTORIALS at the end of each module provide the opportunity to do further exercises and ask questions. 3. Your EXAMINATION marks will be posted on Learn (together with generic feedback and examination statistics) as soon as possible after the April/May Diet Board of Examiners' meeting (normally early-mid JUNE). During the summer months (i.e. mid/end June - end August), you may come into the Business School UG Office (Room 1.11, Business School, 29 Buccleuch Place) to look at your examination scripts. Note that you will not be able to remove any examination scripts from the UG Office as they may be required by the Board of Examiners. Continuing students will also be given the opportunity to review their examination scripts early in the new academic year in Semester 1 (i.e. in October).
No Exam Information

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
Recommended: 1. F S Hillier & G J Lieberman, Introduction to Operations Research (McGraw-Hill). 2. W L Winston, Operations Research: Applications and Algorithms (Duxbury).

Additional Information
Graduate Attributes and Skills	Cognitive Skills On completion of the course students will: 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 will: 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 will have developed their modelling skills.
Additional Class Delivery Information	There will be 4 optional example class 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 6 November(Week 8), 13 November(Week 9), 20 November (Week 10), 27 November (Week 11) venue tba. Fridays 12.10-13.00pm on 7 November(Week 8), 14 November (Week 9), 21 November (Week 10), 28 November (Week 11) venue tba.
Keywords	DMU