ETC5256 · Statistical modelling for actuarial studies

Overview

This unit aims to provide a grounding in several important statistical and mathematical methods that are of particular relevance to actuarial work. It covers the areas of exploratory data analysis, linear regression, generalised linear models, Bayesian modelling, and credibility theory, with a focus on dealing with actuarial and insurance issues in the industry.

Offerings

Assessment

The Handbook lists an examination for this unit.

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

Requisites

Learning outcomes

1. apply various statistical tools to conduct exploratory data analysis
2. employ linear regression models for modelling insurance and financial data
3. adopt generalised linear models for handling complex data
4. exploit Bayesian methods and credibility theory to tackle insurance problems
5. have a critical evaluation of real-world actuarial problems and propose feasible statistical solution.

Workload

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. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.