MTH3241 - Random processes in the sciences and engineering - 2018

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Science

Organisational Unit

School of Mathematical Sciences

Chief examiner(s)

Associate Professor Kais Hamza

Coordinator(s)

Associate Professor Kais Hamza

Unit guides

Offered

Clayton

  • First semester 2018 (On-campus)

Prerequisites

Students must be enrolled in the Master of Financial Mathematics or have passed one of MTH2010, MTH2015, MTH2040, ENG2005 or ETC2440; and one of MTH2222 or ETC2520.

Synopsis

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 students 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.

Outcomes

On completion of this unit students will be able to:

  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.

Assessment

Examination (3 hours): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.

Workload requirements

Three 1-hour lectures and one 2-hour support class per week

See also Unit timetable information

This unit applies to the following area(s) of study