Prepare

Due: September 26, 2024

Learning objectives

• Review the importance of exploring and cleaning data prior to model development
• Implement visualization methods for exploring categorical and numeric predictors/outcomes
• Utilize techniques to identify outliers and missingness patterns in data
• Document exploratory steps using reproducible documents and Quarto

Preparations

📖 Read

• R4DS ch 10 - Exploratory data analysis

Reference materials

• Graphical Data Analysis with R - getting a bit dated now in terms of implementations (published in 2015) but one of the best texts for graphical techniques for exploring and analyzing data in R. Most examples use {ggplot2} (albeit 10 years ago) but also leverages extension packages and alternatives to accomplish different tasks.