Introduction to Data Visualization for Corrections Analysts

Description

This course introduces the foundational principles of data visualization and empowers corrections analysts to leverage R's visualization ecosystem—dplyr, ggplot2, plotly, and gt—to create clear, reproducible graphics that inform policy and operations.

Lessons 1 and 2 provide universal data visualization principles that can be applied using any software. Lessons 3–5 focus on using R to wrangle corrections data, create static and interactive graphics, and generate publication-ready tables and reports.

The course emphasizes practical applications using authentic corrections datasets while teaching reproducible workflows for communicating findings to stakeholders.

Intended Audience

This course is designed for corrections analysts, policy researchers, and operational staff who need to communicate corrections data through effective visualizations. Learners completing Lessons 3–5 should have basic familiarity with R, although no prior visualization experience is required.

Learning Objectives

• Understand principles and best practices for effective data visualization.
• Create static visualizations using ggplot2.
• Build interactive visualizations using plotly.
• Create publication-quality tables using gt.

Course Structure

Lessons are intended to be completed sequentially. Each lesson includes an instructional video, demonstrations, and practical exercises using authentic corrections datasets.

Lesson Objectives

Resources

• R for Data Science (2nd Edition) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund
• Fundamentals of Data Visualization by Claus Wilke

Estimated Time to Complete

10 hours

Keywords

R, Data Visualization