Welcome!

Data is everywhere. Understanding, critiquing, and creating data visualization has become a skill that is indispensable to most fields of knowledge, and to navigating the world around us. In this hands-on course, we will be exploring the principles of perception and cognition underlying effective data visualization applying them to data from a diverse range of fields. This course is designed to demonstrate how to effectively derive knowledge from data, introduce tools for developing data visualizations, and provide opportunities to practice implementing the skills through coding exercises.

In the first week, we will be going through a full data analysis and visualization process, starting from obtaining the data to cleaning, analyzing, and presenting. In the next two weeks, students will analyze and visualize a public dataset of their choice to tell a story about a topic they are interested in, culminating in a presentation on the last day. Each class will start with a short exercise, focused on a specific data visualization technique or critiquing a data visualization. Course assignments include in-class exercises and a final project. Class time will be allotted to work on final project.

This course will be conducted using the R statistical programming language but no prior experience in R required. Students experienced in other programming languages are welcome to use them.

COURSE GOALS By the end of this course students should be able to: ● Evaluate data visualizations for saliency using design principles ● Formulate research questions to generate new knowledge given data ● Organize data for exploratory and explanatory data analyses ● Produce data visualizations in R ● Troubleshoot coding issues ● Utilize GitHub for computational collaborations