This course looks at the theory of stochastic processes, showing how complex systems can be built up from sequences of elementary random choices. In particular, it will present the theory and techniques of Markov chains which can be used as probability models in many diverse applications. The course may be useful for students with interests in Probability, Mathematics, Statistics, Operations Research, Finance, Engineering, Economics, and Theoretical Biology.
Before taking this course students should have a good background in probability (at least Grade B in one of STATS 125, STATS 210, STATS 225, or STATS 320) as well as some mathematics (one of MATHS 208, MATHS 250, MATHS 253, or equivalent).
This course will also provide good preparation for more advanced courses in probability (such as STATS 710, STATS 720, or STATS 723).