A stochastic process is a mathematical model of time-dependent random phenomena and is employed in numerous fields of application, including economics, finance, insurance, physics, biology, chemistry and computer science. This unit will establish basic properties of discrete-time Markov chains including random walks and branching processes. This unit will derive key results of Poisson processes and simple continuous-time Markov chains. This unit will investigate simple queuing theory. This unit will also introduce basic concepts of Brownian motion and martingales. Throughout the unit, various illustrative examples are provided in modelling and analysing problems of practical interest. By completing this unit, you will develop an essential basis for further studies stochastic analysis, stochastic differential equations, stochastic control, financial mathematics and statistical inference.
|Academic unit||Mathematics and Statistics Academic Operations|
|STAT3911 or STAT3011 or STAT3921 or STAT4021|
|Students are expected to have a thorough knowledge of basic probability and integral calculus|
At the completion of this unit, you should be able to:
Unit outlines will be available 2 weeks before the first day of teaching for the relevant session.
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
Enrolment, course planning, fees, graduation, support services, student IT
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
Academic appeals process, special consideration, rules and guidelines, advice and support
Policy register, policy search
Scholarships, interest free loans, bursaries, money management
Learning Centre, faculty and school programs, Library, online resources
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing