620-301 Stochastic Modelling

Credit cannot be gained for both 620-301 and [04]300-331.

620-201 or a grade of H2B or above in 620-205. Plus at least one of 620-113, 620-122, 620-123, 620-142, 620-143, [05]620-192, [05]620-193, [05]620-194 or 620-211.

This subject introduces the concept of a stochastic process and deals with the important standard stochastic processes, including the Poisson process, Markov chains in discrete and continuous time (with some applications), and renewal processes. Students learn to understand, derive the behaviour and properties, and simulate simple stochastic process models derived from real-life situations. This subject demonstrates the importance of such models and in particular shows their applications to industry and the sciences.

Topics covered include review of the main concepts from probability theory, elements of utility theory, basic limit theorems and types of stochastic processes; analysis of Markov chains and their applications (including elements of Markov decision processes); random walks; the Poisson and general jump Markov processes and their applications (with elements of queueing models); renewal theory; and elements of simulation.

Up to 50 pages of written assignments due during the semester (20%); a 3-hour written examination in the examination period (80%).