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MTH3241 · Random processes in the sciences and engineering

Official Handbook

2026 Handbook6 credit pointsLevel 3School of Mathematics

Last checked: 23 Aug 2026 UTC

Overview

This unit introduces the methods of stochastic processes and statistics used in the analysis of biological data, physics, economics and engineering. At the completion of the unit you will understand the application of classical techniques, such as Poisson processes, Markov chains, hidden Markov chains, random walks, martingale theory, birth and death processes, and branching processes in the analysis of DNA sequences, population genetics, dynamics of populations, telecommunications and economic analysis.

Areas of study: Applied mathematics Financial and insurance mathematics Mathematical statistics Mathematics Pure mathematics

Offerings

CampusTeaching periodMode
ClaytonFirst semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook lists an examination for this unit.

#AssessmentTypeWeightHurdle
1Continuous assessmentDemonstration50%
2Final assessment - Exam (3 hours and 10 minutes)Examination50%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

  1. Understand the idea of random variables varying with time;
  2. Analyse Markov chains at the elementary level, in discrete and continuous time;
  3. Understand key processes in probability, including the Poisson process, birth process, birth and death process, branching processes, random walks, martingales;
  4. Apply the probability processes to practical situations, including queues, epidemics, servicing machines, networks, financial markets and insurance risk.

Workload

• Three 1-hour seminars; • One 2-hour applied class (in weeks 2-12) and • 7 hours of independent study per week.

ActivityDuration
Seminars36 hours
Applied sessions22 hours

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