2026 IRSA Workshop on Introduction to Data Visualization

2026 IRSA Workshop on Introduction to Data Visualization

Ever wonder what makes a chart go from "okay" to "mind-blowing"? In this interactive workshop, you will learn the secrets behind powerful data storytelling. We’ll cover the essential tools and strategies you need to create compelling visualizations, explain why good design matters, and give you an insider’s look at exactly what our competition judges are looking for! 

• Saturday, Mar 21
• 10:00 AM -- 12:00 PM
• Virtual, Zoom 
• The Zoom link will be sent to all registered participants on Friday, Mar 20. So please make sure you registered via the RSVP link.
• Contact: Dr. Tianxi Li ([email protected])

Instructor: Pedro Cosatto (PhD Student, UMN School of Statistics & Statistical Consultant, Lynn Y. S. Lin Statistical Consulting Center)

Register Today 

Workshop Agenda

Part 1: The Art & Science of Visualization

• The Blueprint: A quick review of data types and how to match your specific research question with the perfect chart.
• Exploring Single Variables (Univariate): Master histograms, bar charts, box plots, density plots, and bee-swarm plots. Learn how to correctly visualize distributions and spot sneaky outliers.
• Finding Relationships (Bivariate): Uncover connections using scatterplots, side-by-side distributions, and conditional distributions. We'll show you how to identify linear and nonlinear patterns and add trend/regression lines.
• Leveling Up (Multivariate): Discover how to use faceting, color, and size encoding to visualize multiple quantitative variables all at once.
• The Good, The Bad, and The Ugly: We will analyze real-world examples of successful and poor data visualizations, highlight common mistakes, and share pro formatting tips to make your poster stand out.

Part 2: Hands-On Coding in R!

• Time to put theory into practice! We will load a real dataset into R and walk step-by-step through creating the exact plots discussed in Part 1.

What You Need to Know (Prerequisites)

• Math Concepts: You should be familiar with basic data types (quantitative vs. categorical) and foundational concepts like mean, median, variability, variance, standard deviation, and correlation.
• Software Prep: No prior programming experience is needed! However, we strongly encourage you to install R and RStudio on your computer before the workshop so you can code along with us.