This is the expanded second edition of a successful textbook that
provides a broad introduction to important areas of stochastic
modelling. The original text was developed from lecture notes for a
one-semester course for third-year science and actuarial students at the
University of Melbourne. It reviewed the basics of probability theory
and then covered the following topics: Markov chains, Markov decision
processes, jump Markov processes, elements of queueing theory, basic
renewal theory, elements of time series and simulation.The present
edition adds new chapters on elements of stochastic calculus and
introductory mathematical finance that logically complement the topics
chosen for the first edition. This makes the book suitable for a larger
variety of university courses presenting the fundamentals of modern
stochastic modelling. Instead of rigorous proofs we often give only
sketches of the arguments, with indications as to why a particular
result holds and also how it is related to other results, and illustrate
them by examples. Wherever possible, the book includes references to
more specialised texts on respective topics that contain both proofs and
more advanced material.