ETC3580 / ETC5580 Advanced Statistical Modelling  (Sem 2, 2022)


Difficulty:

Year Completed: Semester 2, 2022

Prerequisite: ETC2410 or ETC2420

(or ETW2510, or ETC3440, or ETF2100)

 

Exemption:

CS1 Actuarial Statistics

ETC1000 (25%), ETC2420 (25%), ETC2520 (35%), ETC3580 (15%)

Weighted average of 70% required. Minimum of 60% required for

each unit.


Mean Setu Score: 80.11%

 

Clarity of Learning Outcomes: 83.87%

Clarity of Assessments: 80.65%

Feedback: 77.42%

Resources: 70.97%

Engagement: 90.32%

Satisfaction: 77.42%


Subject Content:

Lecture(s) and Tutorial(s):

Textbook(s):

Assessments:

 

Topics included linear modelling, generalised linear modelling which includes binary responses, count responses and binomial responses, mixed random effects modelling and non-parametric modelling. The lectures also cover the diagnostics for each different model.

 

2 x 1 hour lectures

1 x 1.5 hour tutorial

 

The unit used the textbook ‘Extending the Linear Model with R’ - Julian J Faraway.
Most of the tutorial questions came from this textbook

 

2 individual Assignments worth 20% each
Final exam 60%

 


Comments

The unit was a great insight into the wide array of models you can utilise to analyse data. It was structured in such a way that each topic addressed a new but related skill to the topic before it, and is was clear to see when each type of model would be appropriate. With a good mix of theory and application, it was a very interesting unit about data modelling.

 

The lectures were very engaging, with a mix of theory on the slides, derivations or visual explanations on the white board, and coding in R. Attending the lectures is recommended to grasp a deeper level of conceptual understanding about the coursework. However, at times you may need to rewatch parts as some of the visual concepts can take a while to process and understand/

 

The tutorial attendance is highly encouraged, but not necessary for success providing you keep up to date on the other coursework. No preparation work is required as the tutorials work through the assigned questions for the week. They provide a brilliant resource though to hear additional explanations on topics and to asking any questions when needed. They also help provide a deeper understanding of the models and the code behind them, so attending would improve your R skills.

The assignments were very practical based and both involved coding in R and then interpreting outputs. They were all pretty fair and as long as you stayed up to date on the coursework you would be able to complete the assignment to a high level.

 

The final exam was quite different to previous assessments in the unit as none of it is coding based - instead students were required to interpret outputs or answer other theory related questions. A number of students found it challenging as they had not encountered many theory questions for the unit before. However, with a conceptual understanding of the models it is quite possible to do well in the unit.

The unit overall was on the easier side compared to other third year Actuarial Units. It teaches a lot of useful practice skills which equip you to analyse and build models for a wide range of different data types which would be useful in future career paths. Overall it was quite an enjoyable and well taught unit.

General Overview:

Lectures:

Tutorials:

Assessments/Other Assessments

Final Exam

Concluding Remarks