This module covers aspects of Statistics which are particularly relevant to insurance. Some topics (such as risk theory and credibility theory) have been developed specifically for actuarial use. Other areas (such as Bayesian Statistics) have been developed in other contexts but now find applications in actuarial fields. Indicative topics covered by the module include Bayesian Statistics; Loss Distributions; Reinsurance and Ruin; Credibility Theory; Risk Models; Ruin Theory; Generalised Linear Models; Extreme Value Theory. This module will cover a number of syllabus items set out in Subjects CS1 and CS2 – Actuarial Statistics published by the Institute and Faculty of Actuaries.
38 hours
Spring
80% Examination, 20% Coursework
Boland, P.J. Statistical and Probabilistic Methods in Actuarial Science, Chapman & Hall, 2007.
Study notes published by the Actuarial Education Company for Subjects CS1 and CS2.
See the library reading list for this module (Canterbury)
The intended subject specific learning outcomes. On successfully completing the module students will be able to:
1.demonstrate probabilistic and statistical skills in solving financial problems;
2.demonstrate enhanced conceptual skills and logical reasoning ability;
3.demonstrate a broad understanding of the range of application of statistics to financial processes;
4.demonstrate ability to use appropriate statistical software to model financial data sets.
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