What you'll learn
- Introduction to R, Statistical Properties of Loss Distributions, Excesses and Retention Limits, Reinsurance Treaties, Parameter Estimation, Goodness of Fit and Past Exam Practise
Requirements
- Solid understanding of Actuarial Statistics
Description
This course aims to introduce student actuaries to the following criteria.
It also discusses how to do the below with R Studio
Loss distributions, with and without risk sharing
1.1.1 Describe the properties of the statistical distributions which are suitable for modelling individual and aggregate losses.
1.1.2 Explain the concepts of excesses (deductibles), and retention limits.
1.1.3 Describe the operation of simple forms of proportional and excess of loss reinsurance.
1.1.4 Derive the distribution and corresponding moments of the claim amounts paid by the insurer and the reinsurer in the presence of excesses (deductibles) and reinsurance.
1.1.5 Estimate the parameters of a failure time or loss distribution when the data is complete, or when it is incomplete, using maximum likelihood and the method of moments.
1.1.6 Fit a statistical distribution to a dataset and calculate appropriate goodness of fit measures.
The course also contains compound distributions and how to represent their moments with the child distributions.
Who this course is for:
- Advanced Actuarial Students
Instructor
![Michael Jordan](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.4 Instructor Rating
- 2,037 Reviews
- 26,315 Students
- 22 Courses
Hi I'm MJ the Fellow Actuary. I've been making educational videos since 2013 on YouTube. I've passed all the actuarial exams and am here to help you do the same. I've majored in Mathematical Statistics and have published research in the South African Journal of Science on Artificial Intelligence. I've also done a Ted Talk on advanced studying methods. As your instructor my purpose is to make sure you understand every concept in these courses. If you get stuck with anything, send me a message, I'm here to help.