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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2010/2011
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Stochastic Modelling (Ord) (MATH09018)

Course Outline
School School of Mathematics College College of Science and Engineering
Course type Standard Availability Available to all students
Credit level (Normal year taken) SCQF Level 9 (Year 3 Undergraduate) Credits 10
Home subject area Mathematics Other subject area Specialist Mathematics & Statistics (Ordinary)
Course website http://student.maths.ed.ac.uk Taught in Gaelic? No
Course description Syllabus summary: Markov Chains in discrete time: classification of states, first passage and recurrence times, absorption problems, stationary and limiting distributions. Markov Processes in continuous time: Poisson processes, birth-death processes. The Q matrix, forward and backward differential equations, imbedded Markov Chain, stationary distribution.
Entry Requirements
Pre-requisites Students MUST have passed: Foundations of Calculus (MATH08005) AND Several Variable Calculus (MATH08006) AND Linear Algebra (MATH08007) AND Methods of Applied Mathematics (MATH08035) AND Probability (Year 2) (MATH08008) OR Applicable Mathematics 3 (Phys Sci) (MATH08015) AND Mathematical Methods 3 (Phys Sci) (MATH08016) AND Applicable Mathematics 4 (Phys Sci) (MATH08017) AND Mathematical Methods 4 (Phys Sci) (MATH08018) AND Probability (Year 2) (MATH08008) OR Mathematics for Informatics 3 (MATH08013) AND Mathematics for Informatics 4 (MATH08025)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Stochastic Modelling (MATH10007)
Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisites None
Displayed in Visiting Students Prospectus? Yes
Course Delivery Information
Not being delivered
Summary of Intended Learning Outcomes
The following are the learning objectives for the Honours version, MAT-3-SMo; for this (Ordinary) version there is more emphasis on the technical, rather than conceptual elements, which will be reflected by a different examination.

1. Ability to solve difference equations using generating functions, using P.S.+C.S.
2. Ability to classify states of a Markov Chain.
3. Ability to calculate mean first passage and recurrence times for an irreducible recurrent state Markov Chain.
4. Calculation of absorption probabilities for a Markov Chain with recurrent classes and transient states.
5. Understanding stationary and limiting behaviour and deriving these probability distributions.
6. Appreciating the range of applications, together with a facility to model appropriate problems in terms of a stochastic process.
Assessment Information
Coursework: 15%; Degree Examination: 85%.
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 Not entered
Contacts
Course organiser Dr Bruce Worton
Tel: (0131 6)50 4884
Email: Bruce.Worton@ed.ac.uk
Course secretary Mrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: k.mcphail@ed.ac.uk
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copyright 2011 The University of Edinburgh - 13 January 2011 6:20 am