Handbook 1996 : Faculty of Science (Volume 4 page 238)
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619-355 Stochastic Modelling and Optimisation

Credit points: 15.0

Coordinator: Dr H Cohn

Prerequisite: Statistics 619-201

Contact: 39 lectures (three a week)

Timetable: First semester

Objectives:

Students completing this subject should

Comprehend:

• the concept of a stochastic process;
• the important standard stochastic processes, including Poisson process, Markov chains, birth-and death processes, queueing processes and renewal processes;
• the standard techniques of describing such processes.
• Have developed the skills:
• to develop a stochastic process model from a real-life situation;
• to derive the behaviour and properties of particular stochastic processes.

Appreciate:

• the importance of stochastic processes in modelling real-life phenomena;
• the applications of stochastic models to industry and the sciences.

Content:

Markov chains and applications; random walks; the Poisson process; birth and death processes and applications to population models, queueing models and storage models; renewal processes; Markov decision processes.

Assessment:

A 3-hour written examination; up to 50 pages of assignments may be assessed.

Statistics subject : Next:619-360 | Prev:619-340 | Search | Help
Handbook 1996 : Faculty of Science (Volume 4 page 238)

Status:          Official 1996
Date created:    Oct  9 1995
Last modified:   Oct  9 1995
Authorised by:   Academic Registrar
Email enquiries: Course_Information@registrar.unimelb.edu.au

Copyright © University of Melbourne 1995,1996.