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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Stochastic Modelling (MATH11029)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaMathematics Other subject areaOperational Research
Course website http://student.maths.ed.ac.uk Taught in Gaelic?No
Course descriptionMarkov 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: 2013/14 Semester 2, Not available to visiting students (SS1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 13/01/2014
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 Modelling2:00
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
KeywordsSM_OR
Contacts
Course organiserDr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk
Course secretaryMrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk
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