36-721 Statistical Graphics and Visualization

6 units, Carnegie Mellon University

An effective statistical graphic is a powerful tool for analyzing data and communicating insights. This course will introduce students to creating, understanding, and critiquing such graphical displays, choosing the right visual tool for the task at hand. Students will learn how to produce legible, selfcontained, informative graphics using statistical software, as well as how to plan effective statistical graphics by following the principles of human visual perception. Beyond the most commonly used graphs for univariate and bivariate data, we will cover useful visualizations for statistical model diagnostics cartographic maps network and treestructured data and interactive exploration of highdimensional datasets. Through project assignments, students will practice applying the principles of graphic design and interaction design. Course materials will primarily use R including ggplot2 and Shiny, but we will also introduce IllustratorInkscape and Tableau, and students may complete assignments using other software if they wish Python, MATLAB, etc..

Prerequisites: none listed

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