Visualizing Categorical Data: Methods and Examples

This lecture covers tools for visualizing categorical and discrete data, focusing on exploratory methods that show the data to detect patterns, trends, and anomalies. It includes plots for model-based methods like residual plots and effect plots, as well as examples of classical music listening data visualization. The lecture also explains diagnostic plots, the test of independence, Fisher's exact test, and Simpson's paradox.