A companion website for the summer 2021 version of Carnegie Mellon University course 36-315: Statistical Graphics & Visualization, offered through the Department of Statistics & Data Science and taught by Meghan Hall.
This course introduces the most common forms of graphical displays along with their uses and misuses. Students will learn how to create these displays, how to understand them, and how to distinguish when and where particular graphics are appropriate. This course uses R, RStudio, ggplot2
and its extensions, and R Markdown.
Specific objectives:
Lecture slides are available below in html format, and the .Rmd files are linked from GitHub.
Lab slides are available below in html format, and the .Rmd files are available at the GitHub repo linked in the nav bar above.
Fundamentals of Data Visualization: https://clauswilke.com/dataviz/index.html
Data Visualization: A Practical Introduction: https://socviz.co/index.html#preface
ggplot2
ggplot2
book: https://ggplot2-book.org/
The ggplot2
cheatsheet: https://www.maths.usyd.edu.au/u/UG/SM/STAT3022/r/current/Misc/data-visualization-2.1.pdf
Details of various charts made in R: https://www.r-graph-gallery.com/index.html
Creating custom themes: https://themockup.blog/posts/2020-12-26-creating-and-using-custom-ggplot2-themes/
R Graphics cookbook: https://r-graphics.org/
A guide to various scales: https://ggplot2tor.com/scales
The definitive guide to R Markdown: https://bookdown.org/yihui/rmarkdown/
R Markdown reference guide: https://www.rstudio.com/wp-content/uploads/2015/03/rmarkdown-reference.pdf
R Markdown cheat sheet: https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf
This website is made with the distill package. Many thanks to Alison Hill and Desirée De Leon and their Teaching in Production website, which provided the inspiration for this site. Also thanks to Tom Mock for his enormously helpful introduction to distill.