Quantitative Reasoning

This course aims to develop skills and confidence in various kinds of mathematical reasoning with the aim of helping students become critical and informed readers of quantitative data. The course relies on team-based learning to ensure that students who bring diverse talents and backgrounds to the course can learn together and from one another. Students will learn to criticise and question empirical claims, understand logical reasoning, and address real-life problems by gathering and visually representing quantitative data. The course provides quantitative literacy as well as a grasp on how algorithmic and statistical thinking is used in the natural and social sciences.

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Quantitative Reasoning addresses what might be called numeracy or quantitative literacy by exploring some basic topics related to algorithmic thinking and statistical inference. Among the topics considered are data visualisation, correlation, linear regression, sampling theory, and probability. Students learn to perform basic data analysis tasks in the R programming language and also engage with fundamental programming ideas such as loops and conditionals. Throughout the course, emphasis is placed on critical approaches and conceptual understanding alongside technical mastery.

Student Voices

One of the benefits of the Common Curriculum is a broad base of content that I am familiar with, ranging from literature to statistical tools. This knowledge may also be an important connection point for any future knowledge.

Aidan Mock, Class of 2020
Environmental Studies

QR is one of the best courses in Yale-NUS. I’ve learnt to question assumptions and think critically about the quantitative information we are so often bombarded with. QR introduced me to programming, with the use of R, which led to my current major in MCS!

Jasmine Tan, Class of 2019
Mathematical, Computational and Statistical Sciences

QR helped me to make sense of the statistics I'd learnt in A Level H2 math. In JC, I'd learnt it all through rote learning, and it was only through QR that I began to understand some of the logic behind the statistical tests, what these numbers can tell us, and how we can use them to make sense of the world. I've also gone on to become a Psychology major, which places quite a heavy focus on stats, so I'm very thankful for the foundation that QR has provided me!

Yeo Su-Min, Class of 2019

Teaching Faculty

  • Timothy Wertz

    Lecturer, Science (Mathematics)

  • Vinod Kumar Saranathan

    Senior Research Fellow, Science (Organismal and Evolutionary Biology, Soft matter physics, Photonics and Biomaterials)