WSS/ASA Travelling Course: Effective Graphs with ggplot2

The course teaches the ggplot2 graphical package through the lens of decades of research in statistical graphics, made accessible to a larger audience through Creating More Effective Graphs by Naomi B. Robbins. We will start with the theoretical underpinnings of ggplot2 in Leland Wilkinson’s grammar of graphics framework with the goal of increasing your ability to create graphs intuitively and with a better sense of what works and what doesn’t. Next, we will cover best practices for graphing continuous data, namely histograms, boxplots, density curves, and scatterplots. We will wrap up the morning session with a discussion of data types and data transformation with tidyr and dplyr, since many graphing challenges are actually rooted in problems with data format.

We then will move on to best practices for categorical data, namely bar charts and Cleveland dot plots. Given that knowing how to reorder factor levels is essential for creating effective graphs with categorical data, we will introduce a number of helpful functions from the forcats package. From there we will move on to faceting, a powerful and underused tool for creating multiple panels that differ only by factor level. We will end the day with techniques and tips to make your graphs audience-ready, including the strategic use of color and theme elements.

The course is designed for beginners or those with some experience working with ggplot2 who want to solidify their knowledge and better understand the logic of this graphical package. It can be adjusted to the level and interests of the chapter members, both in terms of content and the lecture vs. lab ratio.

Who Should Attend

This course is ideal for:

• Beginners to ggplot2
• Analysts with some experience who want to deepen their understanding
• Anyone seeking to improve the clarity and effectiveness of their visualizations

The course can be adjusted to match participant experience levels and preferred balance between lecture and hands‑on work.

Instructor Bio

Joyce Robbins is a Lecturer‑in‑Discipline in the Department of Statistics at Columbia University. Since 2017, she has served as the exclusive instructor for Exploratory Data Analysis and Visualization, a required course in Columbia’s Data Science Institute master’s program. She specializes in statistical graphics, data visualization pedagogy, and effective communication of quantitative information.

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Host or Publisher Washington Statistical Society