36-613 Data Visualization
6 units, Carnegie Mellon University
Graphical displays of quantitative information take on many forms, and they help us understand data and statistical methods by communicating arguments, results, and ideas. This course introduces students to the most common forms of graphical displays, their uses and misuses, how to create these display using ggplot2, and understand such displays from a statistical perspective. Furthermore, the course will consider complex data structures that are becoming increasingly common in data visualizations (high-dimensional, spatial, and text data); we will discuss common ways to process these data that make them easy to visualize. We will then cover the basics of interactive graphics and animations. In addition to two weekly lectures, there will be weekly homework assignments where students will learn to use R with the tidyverse to wrangle and visualize real datasets. All assignments will be in R; although this is not a programming class, using programming-based statistical software like R is essential to create high-quality graphics, and this class will give you practice using this kind of software. The course culminates in a group final project, where students will write an exploratory data analysis report about a real dataset containing several types 1 of visualizations. For Master of Science in Applied Data Science students only.
Prerequisites: none listed
Offered: Fall 2026, Fall 2025
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