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Module details for 2023/24.

15 credits

FHEQ Level 7 (Masters)

Module Outline

Probability Models is the first module concerned with the notion of a random (stochastic) process. Stochastic processes are used to model several phenomena with uncertain outcomes, such as stock values, the weather or the profit evolution of a gambler, as the evolve through time.

In this module we develop basic tools for the study of such processes in discrete time (which makes it less technical). The central objects of study are Markov chains and their various models. These include branching processes, finite Markov chains, infinite countable Markov chains, discrete martingales and limits of sequences of independent random variables.

The module will also help you to develop your modelling skills. Through this material we will pay particular attention to questions such as
• How can we model a certain problem using a discrete process.
• Can the model be used to estimate probabilities, expected values etc. If so, how?
• How can we understand what happens to the model when we look far into the future?

Module learning outcomes

Systematically understand key aspects of the theory of general discrete stochastic processes.

Develop a comprehensive understanding of probabilistic techniques used in the modelling of random phenomena with a temporal evolution.

Systematically and creatively answer complex questions arising from modelling everyday problems with discrete processes.

Deploy originality in the application of knowledge in solving problems related to discrete random models.

View timetable

Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Vladislav Vysotskiy

Convenor, Assess convenor
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