Module Review: UQF2101G Quantifying Nuclear Risks

By Soon Hao Jing

I’m Hao Jing, a freshman studying Chemical Engineering, and I took the Quantifying Nuclear Risks module, UQF2101G, taught by Dr Philippe Raynal.

Like all QR modules, it covers mathematical concepts required in statistical analysis: probability and expected value, probability distributions used to model the occurrence of chance events, mathematical modelling, random sampling, regression analysis and hypothesis testing.

The titular topic received ample coverage throughout the module. QR concepts and nuclear-related topics went hand in hand during discussions. You can also expect some nuclear physics, but it’s not rocket science.

Dr Raynal explained concepts starting from first principles. He then worked his way towards the culmination of the concept. This clarifies why concepts appear the way they do. Some of us may have been taught in a different manner before: teachers present some equation or theorem, explain how it works, and then (if they do) delve into the derivation of it. So we barely had an inkling, sometimes, what would emerge from the explanations. I didn’t know Dr Raynal was going to end up with the Poisson distribution until he got there.

Importantly, Dr Raynal emphasised to us the key assumptions and limitations related to each mathematical tool, which we should bear in mind when deciding whether it’s the right tool to use for the problem you have.

About lessons and work, bring your laptop and some paper for every class. Pop quizzes before some classes should be expected – these are usually MCQ questions, but one question can involve a short answer. Excel functions will also be explored in class. You’ll get to download real-life data to tinker with.

Work for me comprised one essay outline, submitted early in August in point form, detailing what kinds of data I would need to write my only QR essay, as well as the essay itself, deliverable by the last QR lesson. Starting early would be ideal, but since the weightier topics are taught at the rear end of the semester, and these may be what you mainly need for your essay, it may be easier said than done.

Each class was split into groups to work on joint presentations on a nuclear-related issue. Each group had to find scientific articles and reviews from reputed sources, and grasp what the researchers did to obtain their data, what they did with that data, and what conclusions they drew from them. We then had to test the data in new ways, applying the tools we learnt in class, to bring out our fresh, individual perspectives.

As for the benefits of this module, I had learnt various bits and pieces of this module before in high school, but going through this module gave me a sense of how all the tools can be utilised together to produce statistical analyses for scientific research, or model events using parameters and equations. These are definitely necessary for any student performing research.