Course Resources
Data and Exercise downloads
- Download all datasets here: click to download.
- Download all exercises and solution files here: click to download
- Download all slide decks here: click to download
- Get the example R Markdown document for Module 11 here: click to download
- And the sample bibligraphy “bib” file is here: click to download
- And the rendered HTML file is here: click to download
- Course GitHub where all materials can be found (to download the entire course as a zip file click the green “Code” button): https://github.com/UGA-IDD/SISMID-2024.
Useful (+ Free) Resources
- R for Data Science: http://r4ds.had.co.nz/
(great general information) - Fundamentals of Data Visualization: https://clauswilke.com/dataviz/
- R for Epidemiology: https://www.r4epi.com/
- The Epidemiologist R Handbook: https://epirhandbook.com/en/
- R basics by Rafael A. Irizarry: https://rafalab.github.io/dsbook/r-basics.html (great general information)
- Open Case Studies: https://www.opencasestudies.org/
(resource for specific public health cases with statistical implementation and interpretation)
Need help?
- Various “Cheat Sheets”: https://github.com/rstudio/cheatsheets/
- R reference card: http://cran.r-project.org/doc/contrib/Short-refcard.pdf
- R jargon: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf
- R vs Stata: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf
- R terminology: https://cran.r-project.org/doc/manuals/r-release/R-lang.pdf
Other references
Batra, Neale, Alex Spina, Paula Blomquist, Finlay Campbell, Henry Laurenson-Schafer, Florence Isaac, Natalie Fischer, et al. 2021. epiR Handbook. Edited by Neale Batra. https://epirhandbook.com/; Applied Epi Incorporated.
Carchedi, Nick, and Sean Kross. 2024. “Learn r, in r.” Swirl. https://swirlstats.com/.
Keyes, David. 2024. R for the Rest of Us: A Statistics-Free Introduction. San Francisco, CA: No Starch Press.
Matloff, Norman. 2011. The Art of R Programming. San Francisco, CA: No Starch Press.
R Core team. 2024. An Introduction to R. https://cran.r-project.org/doc/manuals/r-release/R-intro.html.
Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science. 2nd ed. Sebastopol, CA: https://r4ds.hadley.nz/; O’Reilly Media.