I’m picking this topic because it’s something I’ll actually be doing for a workshop next month, and this assignment motivated me to get working on it. I’ve partnered with the Health Sciences Library to teach a ~3-hour workshop on R. The target audience will be mostly molecular biology grad students and postdocs, with a potential resident or nursing student in the mix.
My plan is to spend at least a half hour up front getting students excited about R, with a couple slides dedicated to each of these points:
- Cost: R is free (beer, speech). Compare to Matlab, SPSS, SAS, Stata, etc.
- R has an excellent community. Show NYT article about R, Google scholar hits, KDNuggets polls, CRAN, Bioconductor
- R’s amazing graphics (ggplot2, examples in the media, bioinformatics examples, GIS examples)
- R as a programming language, and reproducible research.
- Further resources for getting help with R.
During the reproducible research bit, I would demo a very short R/Markdown knitr conversion and uploading to Rpubs. The example would be very small without much R code, but showing how when data updates, the report can be compiled without any human intervention, copying/pasting results and figures, etc. The point is to contrast how incredibly easy this is compared to the laborious, error-prone process most researchers go through when a new observation is added, a small analysis changes, etc. Hopefully this will motivate students, making them realize that the costs in investment in learning this tool will very quickly double in returns.
I just uploaded a draft version of these slides here if you want to take a look. Suggestions are welcome. I don’t actually teach this class until March 18.
https://speakerdeck.com/stephenturner/introduction-to-r