Papers › The Landscape of College-level Data Visualization Courses, and the Benefits of...

The Landscape of College-level Data Visualization Courses, and the Benefits of Incorporating Statistical Thinking

20 Dec 2024arXiv:2412.16402links table onlyarchive 2025-07-28

Zach Branson, Monica Paz Parra, Ronald Yurko

The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.

Data visualization is a core part of statistical practice and is ubiquitous in many fields. Although there are numerous books on data visualization, instructors in statistics and data science may be unsure how to teach data visualization, because it is such a broad discipline. To give guidance on teaching data visualization from a statistical perspective, we make two contributions. First, we conduct a survey of data visualization courses at top colleges and universities in the United States, in order to understand the landscape of data visualization courses. We find that most courses are not taught by statistics and data science departments and do not focus on statistical topics, especially those related to inference. Instead, most courses focus on visual storytelling, aesthetic design, dashboard design, and other topics specialized for other disciplines. Second, we outline three teaching principles for incorporating statistical inference in data visualization courses, and provide several examples that demonstrate how to follow these principles. The dataset from our survey allows others to explore the diversity of data visualization courses, and our teaching principles give guidance for encouraging statistical thinking when teaching data visualization.

PaperPDFCode

Code

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections