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.
Quantitative reasoning is concerned to strengthen 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 formal logic, probability, surveys and sampling, hypothesis testing, correlation and regression, and prospect theory.
Aidan Mock, Class of 2020
Jasmine Tan, Class of 2019
Mathematical, Computational and Statistical Sciences
Yeo Su-Min, Class of 2019