Postgraduate Course: Stochastic Modelling (MATH11029)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Not available to visiting students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Mathematics |
Other subject area | Operational Research |
| Course website |
http://student.maths.ed.ac.uk |
Taught in Gaelic? | No |
| Course description | Markov chains: discrete state, discrete time chains; classification of states; stationary and limit distributions; absorption problems; first passage and recurrence times; insurance, reservoir control, inventory, manpower planning problems; Markov processes in continuous time, viewed as a natural generalization of birth-death processes covered in the Simulation course.
Queueing systems; balance equations for M/M/1 systems and birth-death queues; Little's law; imbedded Markov chain analysis for M/G/1 systems; optimisation problems for single class queues; dynamic control of multi-class queueing systems. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Course Delivery Information
|
| Delivery period: 2014/15 Semester 2, Not available to visiting students (SS1)
|
Learn enabled: Yes |
Quota: None |
|
Web Timetable |
Web Timetable |
| Course Start Date |
12/01/2015 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 20,
Seminar/Tutorial Hours 10,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
66 )
|
| Additional Notes |
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
80 %,
Coursework
20 %,
Practical Exam
0 %
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | MSc Stochastic Modelling | 2:00 | |
Summary of Intended Learning Outcomes
| Knowledge of behaviour of discrete-state discrete and continuous time Markov Chains. Where appropriate, the ability to formulate real-life problems as a Markov Process. Understanding of elementary queueing theory. Awareness of modern developments in the control of queueing systems. |
Assessment Information
| See 'Breakdown of Assessment Methods' and 'Additional Notes' above. |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | SM_OR |
Contacts
| Course organiser | Dr Julian Hall
Tel: (0131 6)50 5075
Email: |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: |
|
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