Module Review: UQF2101E Quantifying our Eco-Footprint

By Lee Kee Wei

I’m Lee Kee Wei, majoring in Mathematics. I took UQF2101E, Quantifying our Eco-Footprint during AY14/15 Semester 2.

UQF2101E provides various results and tools in mathematical modeling and sampling. Its main goal was to teach the students transferable skills and a scientific mindset. Thus, it focused more on the mindset of the scientific method and the underlying assumptions made. The module does not go through the ideas and concepts of Eco-Footprint in depth, but uses it as a medium to deliver the QR concepts.

UQF2101E focuses on mathematical models, from linear to nonlinear and goes through concepts such as hypothesis testing and probability distributions.  Moreover, the course teaches students how to use Excel to get regression (best-fit) models and other tools such as Principal Component Analysis.

Assignments are usually done in groups and are research based. There are excessive amounts of Fermi Problems (‘back-of-envelope’ estimations of unknown quantities) to tackle. Groups are ‘randomly’ assigned from the start and you got to work with the same few people throughout the semester. For my year, the final project was an open research question that must be about eco-footprint.

Professor Laksh (A/P Lakshminarayanan Samavedham) teaches this module. He has won numerous teaching awards and was also the Director for the NUS Centre for Development of Teaching and Learning.  His enthusiasm and spirit makes every lesson an enjoyable experience. Moreover, he constantly asks for feedback to improve his teaching style and make it more appealing to his students. He does go into mathematical detail on certain principles. Be prepared to face matrices, lots of matrices. Fortunately one does not really need to compute the matrices; Excel will do the job for you.

My take away from this module was that it showed me how the scientific method is conducted. It is interesting to see and experience the process of the scientific method: from gathering data and making assumptions, to modeling the data and seeing the results. It gives a very good introduction on how empirical research is conducted and used. Moreover I’ve also learned to use Excel to do a regression model and also other statistical tools to help me evaluate data I have collected.

However, what was lacking in my time was a space where different groups of people doing QR can discuss and evaluate each other’s work. Thankfully, the incoming batches now have the Quantitative Reasoning Centre (QRC). The QRC is a place that welcomes anyone who has inquiries about QR, wants to do QR, or needs to discuss QR. QR assistants will be in the Centre to moderate discussions and answer any questions about QR concepts. QRC focuses on discussion based learning and encourages patrons to develop a strong and personally understanding on the topics.

With the increasing prevalence of data today, it has never been more important to build up one’s numerical literacy. The QR foundation module builds up the needed literacy and allows one to be critical when analyzing statistical data.