The unit was quite challenging as it starts off very theoretical and

conceptual - this makes it difficult to see how the rest of the unit

progresses. This can sometimes lead to confusion as the first half

of the unit builds upon the first four weeks and becomes more

challenging as the unit progresses. Due to the heavy emphasis on

the theoretical work at the start of the unit, it can be difficult to

see how it is relevant, however, the second half the unit shows

how the content is applied and shows more real world application.

Therefore, the second half of the semester was relatively more

straightforward than the first half. The Survival Models that were

then touched on in the last few weeks were able to build on some

of the more theoretical concepts that were covered earlier and as

such were easier to understand.

Overall, the lectures were taught well despite the challenging

nature of the content in the first half. Expectations were made

clear that proofs were not required and instead a focus on

mathematical intuition were required. This allowed for the clear

emphasis that the teaching staff wanted students to gain an

intuitive understanding of the content, without the pressure of

understanding the fundamental maths. Lectures could be fully

utilised through active participation from the audience.

Formal tutorials started in week two, but the tutorials in week one

were useful in providing revision for some of the more difficult

maths required to understand the content. The week one tutorial

also provided assistance for students who have never used R

before. Overall, the tutorials were helpful as the tutors would

provide worked solutions to all (time permitting) questions for

that week. Often, tutors also provided their own slides for

students to look at for additional explanation of the content and

questions. Tutorials were a good opportunity to clarify with the

tutor why each step was done and to get an understanding of the

mechanics of each question. In saying this, there was an option to

view a recorded tutorial, which meant that skipping a tutorial was

not that big of a deal, however, if there was not a recorded

alternative, tutorials were extremely helpful.

Both assignments required extensive use of R-coding, but the first

assignment was primarily centred around Markov Chains and

Markov Jump Processes. A fair amount of code was provided to

you in the lecture slides but often required additional time spent

by the student to understand how the code worked and what it

did. Tutorials were also a great place to ask questions about how

the code worked. The second assignment was a report that

compared how the Lee-Carter and Cairns-Blake-Dowd Model

worked. Students were required to run mortality simulations of

these models on a particular data set and type up their findings in

a report. This assignment provided students with an opportunity

to delve deeper into understanding these models, and marking

was generous to those who understood the complexity and

intricacies of the model.

There is a lot of content in this unit and it requires an ongoing 

effort and a large effort come exam time. Despite being difficult,

with enough effort the exam is quite achievable and high marks

can be attained. The exam covered all topics of the unit equally,

with an emphasis on the last two weeks of content. Past exams

were not provided, as tutorial questions reflect most accurately

the level of difficulty that can be expected on the exam. The exam

was quite time pressured so it is important to move quickly

through the questions and not to dwell on a single question.

Overall, the unit requires a lot of work early on and leading up the

exam. The complex nature of the first half requires significant

effort to ensure one understands the concepts in depth enough to

apply it to the more real world content in the second half of the

semester. The assignments were tricky and difficult to

understand, and as such, generally those students who started

the assignments earlier performed better.