Welcome to STA 100 A04! Here you can find all discussion materials in this course. Also, I have included some other meterials for your reference.
If you want to have a deeper understanding about R programming, the following reference may be useful.
- Kabacoff, Robert I. R in Action. manning, 2010.
- Matloff, Norman. The art of R programming: A tour of statistical software design. No Starch Press, 2011.
- Wickham, Hadley, and Garrett Grolemund. R for data science: import, tidy, transform, visualize, and model data. " O'Reilly Media, Inc.", 2016.
Also, the following online learning resources are very handy and helpful.
- Online learning website: DataCamp
- Youtube video tutorial: https://youtu.be/_V8eKsto3Ug
- Blog: https://www.r-bloggers.com/
Larning a new programming language is challenging, but also fulfilling. You are not required to remember all the commands in R, but some basic ones. Finally, Google is a perfect learning assistant. Try to make the best use of it.