- Code STAT3036
- Unit Value 6 units
- Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
- ANU College ANU College of Business and Economics
- Course subject Statistics
- Areas of interest Actuarial Studies, Statistics
- Academic career UGRD
- Dr Borek Puza
- Mode of delivery In Person
Second Semester 2016
See Future Offerings
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, students will have the knowledge and skills to:
Upon successful completion of the requirements for this course, students should have the knowledge and skills 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.
See the course outline on the College courses page. Outlines are uploaded as they become available.
Mid-semester Exam (30%)
Final Exam (70%)
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Students taking this course are expected to commit at least 10 hours a week to completing the work.
Requisite and Incompatibility
Tuition fees are for the academic year indicated at the top of the page.
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- Student Contribution Band:
- Unit value:
- 6 units
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Offerings, Dates and Class Summary Links
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Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|7664||18 Jul 2016||29 Jul 2016||31 Aug 2016||28 Oct 2016||In Person||N/A|