Course Description

This course is intended to be a foundational course; however, a basic understanding of concepts in statistics, such as mean, median, and mode, would be beneficial. It is meant to develop critical reasoning as far as data and the communication of data are concerned.Choice of materials: primary or secondary readings / case law; An important point to note is that  it does not cover high-level statistics or data science and will not focus on any software tools. The course  is designed to assess the presentation of data in different forms and to be able to understand and critique  it. This covers aspects from the sourcing credible data to the final form that it assumes.  A highly applied course, the material is drawn from a range of key texts and students will engage in a variety  of exercises, both individual assignments and group activities. These include Excel-based tasks as well as  collaborative discussions of papers.

Pedagogical Methods : Lectures, Socratic discussion, seminar style discussion, response papers or group work, field work; In addition to lectures and in-class exercises, students will be divided into groups to work on presentations designed to enhance their ability to create and deliver effective data-driven communication. Each student will also maintain a design diary in the form of a term paper, reflecting on the material covered in lectures in relation to a personal project.

Layout of the course: module structure and sequence. In the first half of the course, the emphasis will be on developing the understanding of technical aspects such as chart selection and best practices to be followed. We will also examine the contributions of Edward Tufte and

In the second half, the focus would shift to critical theory as it applies to data visualisation before finally discussing the practical process of designing data-driven communications.