Data visualization
Undergraduate · Math
Syllabus focus
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Data visualization — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
Visual perception and design
- Principles of effective data visualization — Principles of effective data visualization
- Color, contrast, and accessibility — Color, contrast, and accessibility
- Chart junk and misleading axes — Chart junk and misleading axes
- Choosing chart types for data types — Choosing chart types for data types
- Small multiples and faceting — Small multiples and faceting
Grammar of graphics
- ggplot2 layered grammar in R (or equivalent) — ggplot2 layered grammar in R (or equivalent)
- Mapping aesthetics to variables — Mapping aesthetics to variables
- Scales, coordinates, and themes — Scales, coordinates, and themes
- Interactive visualization (plotly, Shiny intro) — Interactive visualization (plotly, Shiny intro)
- Geospatial visualization basics — Geospatial visualization basics
Communication
- Storytelling with data — Storytelling with data
- Dashboard design principles — Dashboard design principles
- Visualization for exploratory vs explanatory analysis — Visualization for exploratory vs explanatory analysis
- Critique — Critique
- Revision of published graphics — Revision of published graphics
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Visual perception and design
Principles of effective data visualization
Coming soon - Grammar of graphics
ggplot2 layered grammar in R (or equivalent)
Coming soon - Communication
Storytelling with data
Coming soon
Notes
Undergraduate Data visualization — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable). Topic outline: `content/topics/undergraduate/data_visualization.json`.