Technical Sharing Session #3

A Primer on Data

Title	A Primer on Data
Presenter	Dr Tan Hong Ming Lecturer, Department of Analytics & Operations Research Fellow, Work Package 2
Date	28 January 2022, Friday
Sypnosis	Gathering insights and training machine learning models relies on data. Having a poor understanding of the data on hand or using non-representative data can lead to false conclusions. This is particularly so if we are interested in cause and effect. Gathering high quality and useful data then is of paramount importance. In this talk, we discuss some biases and pitfalls that can be found when working with data. We do so using real life examples and case studies. Finally, we discuss data dredging, also known as p-hacking, and one method that attempts to mitigate this.