The Learning by Example course will attempt to provide you everything you need to get your own analyses up and running in R. We will focus on data management and analysis (day 1), visualization (day 2), other models/programming/reproducible research (day 3). Click for a a more detailed outline
Day 1 focuses on how R deals with data and how you can start doing your own statistical analyses in R.
Day 2 focuses primarily on visualization (graphics in R’s base graphics environment as well as ggplot), though other miscellaneous topics may be covered here, too.
Day 3 focuses on how you can enhance the power of R doing repeated calculations, a little tiny bit of programming and using R in a reproducible research environment.
You can find an electronic copy of the handout here and a zip file with all of the files needed to reproduce the output and complete the exercises is here - this has been updated to include the files that were missing during the course. In addition to these files, there were several others I mentioned that might be useful.
- Here is the file the captures what we’re doing in the in-class exercises .
- You can find some example homework problems that I use in my intro stats class in RMarkdown here
- We didn’t have time to cover panel/longitudinal/time-series cross-sectional models in class, but here are some slides and R-code.
- We didn’t have time to cover missing data and multiple imputation models in class, but here are some slides and R-code.