University of Technology, Sydney

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35363 Stochastic Models

6cp; 4hpw
Requisite(s): (35151 Introduction to Statistics OR 26134 Business Statistics OR 37151 Introduction to Statistics) AND (35101 Introduction to Linear Dynamical Systems OR 37131 Introduction to Linear Dynamical Systems)) OR ((33230 Mathematical Modelling 2 OR 33290 Statistics and Mathematics for Science)
These requisites may not apply to students in certain courses. See access conditions.

Description

Stochastic models allow many situations involving uncertainty to be analysed. This subject provides students with the knowledge required to use such models successfully in practice. Students acquire experience in using state-of-the-art commercial software for simulation, Markov decision process methods and various queuing models. Topics covered include Markov chains, Poisson processes, the birth-and-death process, and non-birth-and-death queuing models. The simulation component of the subject includes: pseudorandom number generation and corresponding statistical tests; evaluation of integrals using Monte Carlo simulation; generation of continuous and discrete random variables, including inverse transform technique, convolution method, and acceptance-rejection technique.

Typical availability

Autumn session, City campus


Detailed subject description.

Fee information

Information to assist with determining the applicable fee type can be found at Understanding fees.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.