Click here to register for the short course on Eventbrite.

Registration fee (tax is excluded):

• Student: Free (Lunch not provided) or $10 (Lunch provided) 

• ASA member: $75

• Non-ASA member: $95

The registration fee includes a one-day parking permit, light refreshments during coffee breaks, and a lunch box.

Data visualization plays a crucial role in the data science and statistics workflows. It is fundamental to everything from exploratory data analysis to communicating results. Data scientists and statisticians can better understand data and more effectively communicate their work by understanding how to better visualize their data. Too often, however, visualization is an afterthought. 

In this course, attendees will learn the core principles of data visualization and the perception of visual information; the layered grammar of graphics; and best practices for creating effective visualizations. To put these principles to work, attendees will learn practical skills for R programming that improve the quality of their work with many hands-on examples. The course will focus on the popular R package ggplot2 and the reproducible research framework R Markdown/Quarto. After this course, participants will be comfortable using R and R Markdown/Quarto to create effective data visualizations. 

The course will focus on the popular R package ggplot2 and the reproducible research framework R Markdown/Quarto. After this course, participants will be comfortable using R and R Markdown/Quarto to create effective data visualizations.

Aaron R. Williams is a senior data scientist in the Urban Institute's Income and Benefits Policy Center. He works on retirement policy, microsimulation models, data privacy, and data imputation methods. He has worked on Urban’s Dynamic Simulation of Income (DYNASIM) microsimulation model, the Social Security Administration’s Modeling Income in the Near Term (MINT) microsimulation model, and the Tax Policy Center’s synthesis of individual tax records. 

Williams leads Urban’s R Users Group and assists researchers across Urban with projects that use R for data science, statistical analysis, data visualization, mapping, and automation. He has authored several R packages for data visualization and data synthesis. 

Williams is an adjunct professor in the McCourt School of Public Policy at Georgetown University. He holds a BS in economics from Virginia Commonwealth University, a BA in music from Virginia Commonwealth University, and an MS in mathematics and statistics from Georgetown University.