ETC3580 - Advanced statistical modelling - 2019

6 points, SCA Band 3, 0.125 EFTSL

Undergraduate - 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 Didier Nibbering

Coordinator(s)

Dr Didier Nibbering

Unit guides

Offered

Clayton

  • Second semester 2019 (On-campus)

Prerequisites

ETC2410, ETC2420, ETC3440Not offered in 2019 or equivalent.

Synopsis

This unit introduces extensions of linear regression models for handling a wide variety of data analysis problems. Three extensions will be considered: generalised linear models for handling counts and binary data; mixed-effect models for handling data with a grouped or hierarchical structure; and non-parametric regression for handling non-linear relationships. All computing will be conducted using R.

Outcomes

The learning goals associated with this unit are to:

  1. provide an understanding of statistical models for handling common data analysis problems
  2. develop skills for fitting, interpreting and assessing statistical models
  3. develop computer skills for exploring and modelling different kinds of data.

Assessment

Within semester assessment: 40% + Examination: 60%

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