In the beginning was R Markdown

In this talk I will give a brief review of teaching statistics and data analysis through the lens of reproducibility with R Markdown, and how to use this tool effectively in teaching to maintain reproducibility as the scope of your students' projects and their experience grow.

Transcript

1. 🔗 bit.ly/begin-rmd
2. setting the stage
3. replicability reproducibility same research question same research question same results same results new data same data
5. a little bit of history…
6. useR! 2012
7. #1: Convince researchers to adopt a reproducible research workflow #2: Train new researchers who don’t have any other workflow
8. reproducibility
14. data analysis - descriptive stats - plots & tables - model output write-up - research question & context - interpretations - conclusions lab report copy-paste copy-paste text block data analysis text block data analysis text block + code & output tightly connected + easy to reproduce, update, collaborate + standardised format - unfamiliar format, must learn syntax Word, Google Docs, etc. R Markdown
16. fast forward to the present
19. growing out of r markdown with
20. r markdown rstudio projects
21. r markdown external data
22. r markdown external data in other folders with here : : here()
23. r markdown version control
24. version control with Git and GitHub for students for educators + learn a best practice for reproducibility + get familiar with systems that are widely used in industry and academia + facilitate collaboration and sharing + teach a best practice for reproducibility + centralise the distribution and collection of assignments + enable students to work collaboratively (even when working remotely!)
25. a simple assignment…
26. …that is straightforward to assess
27. a more complex project…
28. …with automated checks leveraging GitHub actions
29. allowed - f i les.yaml project - allowed - f i les.R
30. knit - readme.yaml
31. r markdown other formats …
34. r markdown you, the educator
35. putting it altogether
37. references & acknowledgements - Baumer, B., Çetinkaya-Rundel, M., Bray, A., Loi, L., & Horton, N. J. (2014). "R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics." Technology Innovations in Statistics Education, 8(1). https:// escholarship.org/uc/item/90b2f5xh. - Beckman, M. D., Çetinkaya-Rundel, M., Horton, N. J., Rundel, C. W., Sullivan, A. J., & Tackett, M. (2020). Implementing version control with Git and GitHub as a learning objective in statistics and data science courses. Journal of Statistics Education, 1-35. - Carver, R., et al. (2016) "Guidelines for assessment and instruction in statistics education (GAISE) college report 2016." http://www.amstat.org/education/gaise/GaiseCollege_full.pdf. - Çetinkaya-Rundel, M. (2012) "Planting seeds of reproducibility with knitr and markdown" Citizen Statistician. http:// www.citizen-statistician.org/2012/10/planting-seeds-of-reproducibility-with-knitr-and-markdown. - Horst A.M., Hill A.P., Gorman K.B. (2020). palmerpenguins: Palmer Archipelago (Antarctica) penguin data. R package version 0.1.0. https://allisonhorst.github.io/palmerpenguins. doi: 10.5281/zenodo.3960218. - Sharla Gelfand (2021). ggkeyboard: Plot a Keyboard Using "ggplot2". R package version 0.0.0.9012, https:// github.com/sharlagelfand/ggkeyboard. - Background image credit: Tighe Flanagan, https://www.instagram.com/p/CFcKz89nWE0.
38. and R Markdown continues to facilitate reproducibility, no matter your scope and experience… 🔗 bit.ly/begin-rmd