To view the eligibility and requirements, including prerequisites, corequisites, recommended background knowledge and core participation requirements for this subject, please see the University Handbook:

Prerequisites #

Relevant knowledge from ACTL20003 Stochastic Techniques in Insurance (or MAST20004 Probability) includes in particular:

Distributions of random variables
Expectations and conditional expectations
Moment and probability generating functions
Law of Large Numbers, and the Central Limit Theorem

Relevant knowledge from MAST20005 Statistics includes in particular:

Fitting of statistical models to data (Descriptive statistics, maximum likelihood)
Parameter estimation (point and interval estimation, confidence intervals)
Hypotheses tests, including goodness-of-fit
Linear regression and ANOVA
Correlation
Software R

The website includes some basic mathematics and probability concept for your review.

Probability and Statistics #

As described above under “Prerequisites”, a good prior knowledge of probability and statistics is essential for this course. Some of the required knowledge is reviewed in the Module 1 tutorial set. I strongly recommend you review those materials before the semester starts.

Use of the software R #

R is required prior knowledge for this course, and part of the prerequisite course MAST20005 (Statistics).

This is because R is a required software for the actuarial professional exams CS1 and CS2 (see https://www.actuaries.org.uk/studying/curriculum/actuarial-statistics and also https://www.actuaries.org.uk/studying/curriculum/frequently-asked-questions-curriculum ). It is used very widely by actuaries in industry (see, for instance, https://www.actuaries.digital/2019/09/26/my-top-10-r-packages-for-data-analytics/ ). Some companies also use R to produce presentations and documentation for generally.

In order to help you with R I have put together a website that summarises all the things I think you should know before starting your first grad role: https://communicate-data-with-r.netlify.app At the very least, you need to know what is under “Base R”. Learning the “tidyverse” will be most useful, as well as “ggplot2” for better visualisations. “htmlwidgets” is more advanced, and not required for the course. You may want to create your assignment with “R Markdown” (under “Communicate Data”), although this is not required either.

The main reference for Base R is the book http://biostatisticien.eu/springeR/index-en.html which is also available in other languages (including mandarin). The English version can be downloaded for free from the Unimelb library: https://go.openathens.net/redirector/unimelb.edu.au?url=http%3A%2F%2Fdx.doi.org%2F10.1007%2F978-1-4614-9020-3

I strongly recommend you review the R materials mentioned above before the semester starts.

Finally, note that we are using R version 4.3.2 (2023-10-31), and a list of the main packages used is provided in Module 1. Please update your R and install the relevant packages.