Module code: MA1061

Probabilistic models pervade most areas of our modern world and, as probability statements are almost unavoidable, having a good understanding of what they mean is essential. This course introduces the basic ideas and rules of probability, together with some simple probabilistic models and techniques for computing the probabilities of events. 

We will introduce the important concept of conditional probabilities and independence. We will also introduce random variables together with its probability distribution, expectation and variance. A number of important distributions are considered, including the binomial, geometric, Poisson and normal distributions. The De Moivre-Laplace and Central Limit Theorem are given without proofs.


  • 33 hours of lectures
  • 2 hours of seminars
  • 11 hours of tutorials
  • 5 hours of supervised time in lab/studio/workshop
  • 99 hours of guided independent study


  • Exam, 2 hours (60%)
  • Skills test (20%)
  • Coursework (20%)