ETF5952 - Quantitative methods for risk analysis - 2018

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

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

Faculty

Business and Economics

Organisational Unit

Department of Econometrics and Business Statistics

Chief examiner(s)

Dr Tatsushi Oka

Coordinator(s)

Dr Tatsushi Oka

Unit guides

Offered

Caulfield

  • First semester 2018 (On-campus)
  • Second semester 2018 (On-campus)

Prohibitions

ETX2011Not offered in 2018, ETF2011Not offered in 2018, ETX3011, ETX9520

Synopsis

Operations in business and government inevitably entail risk which, of course, must be incorporated into decision making. This unit, supported by software such as @Risk, presents basic quantitative methods for identifying and analysing risk - with broad applicability to areas such as finance, quality control, occupational health and safety, disaster prevention and environmental management.

Outcomes

The learning goals associated with this unit are to:

  1. analyse risk statistically by summarising and interpreting data using techniques of descriptive statistics including the use of associated spreadsheet functions
  2. analyse and evaluate risk by applying concepts of probability and of probability distributions
  3. analyse and evaluate risk via Monte Carlo simulation, using @Risk software
  4. evaluate decision-making strategies, including use of PrecisionTree software
  5. describe and analyse the quality of production in an industrial process, using statistical control charts.

Assessment

Within semester assessment: 45% + Examination: 55%

Workload requirements

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

See also Unit timetable information