This course covers the fundamental concepts of: Bayesian statistics, including estimation, prediction, hypothesis testing, and decision theory; time series analysis, including estimation and prediction based on ARIMA models; credibility theory, including limited fluctuation credibility theory and the Buhlmann-Straub model; several run-off techniques for estimating an outstanding claims reserve; and Monte Carlo techniques, including the inverse transformation method, the polar method, and Monte Carlo integration.

Upon successful completion of the requirements for this course, students will be able to:

• Explain the fundamental concepts of Bayesian statistics and use these concepts to calculate Bayesian estimators (including credibility estimators).
• Define and apply the main concepts underlying the analysis of time series models.
• Describe and apply techniques for analysing a delay (or run-off) triangle and projecting the ultimate position.
• Explain and apply the concepts of “Monte Carlo” simulation using a series of pseudo-random numbers.

Mid-semester Exam (30%)

Final Exam (70%)

Details about assessment may change during the first two weeks of semester. Please ensure that you check with your lecturer or tutor about any changes. Changes to the assessment schedule will be posted to the Wattle site.

Students taking this course are expected to commit at least 10 hours a week to completing the work.

This will include:

•  3 hours a week: lectures
•  1 hour a week: tutorials
•  6 hours a week: reading, and exam/tutorial preparation

STAT2001 Introductory Mathematical Statistics

None.

No computing is required for this course. However, you will need a scientific calculator.

This course, together with STAT3035 (Risk Theory), constitutes Subject CT6 of the Institute of Actuaries of Australia. To get an exemption from the Institute, you need to get an average of at least 60% for these two courses.