Skip to main content
Unit of study_

Actuarial Data Analytics - QBUS2830

Year - 2018

The unit covers a range of statistical models and methods for analysing quantitative actuarial data in general insurance. Both maximum likelihood estimation and Bayesian estimation methods are adopted for statistical inferences with the use of modern software tools such as the R and OpenBUGS packages. Topics covered include probability distributions for actuarial modelling, claim size modelling, claim frequency modelling, loss reserve forecasting, pure premium calculation, premium rates reviewing and revising (credibility theory), linear and generalised linear models, Poisson process and Markov process in actuarial modelling. Upon the completion of this unit and other relevant business analytics units, students may undertake professional examinations for actuaries or may get exemptions in some professional examination papers.

1x 2hr lecture per wk and 1x 1hr tutorial per wk

assignments (30%), mid-semester exam (20%), final exam (50%)

Assumed knowledge
BUSS1020 or ECMT1010 or ENVX1001 or ENVX1002 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points in MATH 1000-level units including MATH1905.


QBUS2810 or DATA2002 or ECMT2110


Faculty: Business (Business School)

Semester 2

30 Jul 2018

Department/School: Business Analytics
Study Mode: Normal (lecture/lab/tutorial) day
Census Date: 31 Aug 2018
Unit of study level: Intermediate
Credit points: 6.0
EFTSL: 0.125
Available for study abroad and exchange: Yes
Faculty/department permission required? No
Courses that offer this unit

Non-award/non-degree study If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student. Cross-institutional study If you are from another Australian tertiary institution you may be permitted to undertake cross-institutional study in one or more units of study at the University of Sydney.

To help you understand common terms that we use at the University, we offer an online glossary.