302373 (v.2) Stochastic Processes 401

Area:

Department of Mathematics and Statistics

Credits:

25.0

Contact Hours:

3.0

Lecture:

3 x 1 Hours Weekly

Syllabus:

Review of probability tools, Introduction to stochastic processes, Poisson process, Markov chains, Random walk, Limit theorems, Birth and death process, Branching processes, Renewal processes, Brownian motion, Queuing theory.

Unit Outcomes:

On completion of this unit students will be able to explain the concepts and methods of stochastic modeling; Define Markov chains and apply to real life phenomenon; Define Markov process models and apply to model real life situations; Define and apply Brownian Motion processes; Explain renewal theory and its applications; Perform modelling of queuing systems; Simulate stochastic processes.

Text and references listed above are for your information only and current as of September 30, 2003. Please check with the unit coordinator for up-to-date information.

Unit References:

Karlin, S. and Taylor, H.M. 1975, A first Course in Stochastic Processes Academic Press, 2nd Edition. Ross, S.M. 1983, Stochastic Process, John Wiley & Sons. Feller, W. 1966, An Introduction to Probability Theory and its Applications, volume 1, 3rd edition. Hoel, P.G., Port, S.C. and Stone, C.J. 1999, Introduction to Stochastic Processes, Waveland Press. Brzezniak, Z. and Zastawniak, Tomasz 1998 Basic Stochastic Processes: A Course Through Exercises, Springer. Nelson, B.L. 1995 More about Stochastic Modelling: Analysis and Simulation, McGraw-Hill, Inc. Peter, G. 1995, Stochastic Modelling of Scientific Data, Chapman and Hall/CRC.

Unit Texts:

Karlin, S. and Taylor,, H.M. 1998 , An Introduction to Stochastic Modelling Academic Press, 3rd Edition.

Unit Assessment Breakdown:

Assignments (3) 40%, Final Examination (2 hours) 60%

Year	Location	Period	Internal	Area External	Central External
2004	Bentley Campus	Semester 1	Y
2004	Bentley Campus	Semester 2	Y