References
Aden‑Buie, Garrick. 2021. “Tidy Animated Verbs.” 2021. https://www.garrickadenbuie.com/project/tidyexplain/.
Anscombe, F. J. 1973. “Graphs in Statistical Analysis.” The American Statistician 27 (1): 17–21. https://doi.org/10.1080/00031305.1973.10478966.
Broman, Karl, and Kara Woo. 2017. “Data Organization in Spreadsheets.” The American Statistician 72 (1): 2–10. https://doi.org/10.1080/00031305.2017.1375989.
Chang, Winston. 2018. R Graphics Cookbook. Second. O’Reilly. https://r-graphics.org/.
Cunningham, Scott. 2021. Causal Inference: The Mixtape. Yale University Press. https://mixtape.scunning.com/.
Evergreen, Stephanie D. H. 2014. Presenting Data Effectively: Communicating Your Findings for Maximum Impact. Sage. https://us.sagepub.com/en-us/nam/presenting-data-effectively/book246124.
Gareth James, Trevor Hastie, Daniela Witten. 2014. An Introduction to Statistical Learning. Springer. https://www.statlearning.com/.
Healy, Kieran. 2019. Data Visualization: A Practical Introduction. Princeton. http://socviz.co/.
Ismay, Chester, and Albert Y. Kim. 2019. Modern Dive: Statistical Inference via Data Science (a Moderndive into r and the Tidyverse). self-published. https://moderndive.com/.
Jennifer Bryan, Jim Hester. 2020. What They Forgot to Teach You about r. https://rstats.wtf/.
Jennifer Bryan, Jim Hester, the STAT 545 TAs. 2020. Happy Git and GitHub for the useR. https://happygitwithr.com/.
Knaflic, Cole Nussbaumer. 2015. Storytelling with Data: A Data Visualization Guide for Business Professionals. Wiley. https://www.storytellingwithdata.com/.
Lowndes, Julie, and Allison Horst. 2020. “Tidy Data for Efficiency, Reproducibility, and Collaboration.” 2020. https://www.openscapes.org/blog/2020/10/12/tidy-data/.
McElreath, Richard. 2016. Statistical Rethinking: A Bayesian Course with Examples in r and Stan. CRC Press.
Monkman, Martin. 2019. “Same Name, Different Bird.” 2019. https://martinmonkman.com/post/2019-06-02_same-name/.
Parker, Hilary. 2017. “Opinionated Analysis Development.” PeerJ Preprints 3210v1. https://doi.org/10.7287/peerj.preprints.3210v1.
Peng, Roger D. 2018. R Programming for Data Science. leanpub.com. https://leanpub.com/rprogramming.
Raymond, Eric S. 1999. The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary. O’Reilly Media. http://www.catb.org/esr/writings/cathedral-bazaar/.
Rosling, Hans, Ola Rosling, and Anna Rosling Rönnlund. 2018. Factfulness: Ten Reasons We’re Wrong about the World—and Why Things Are Better Than You Think. Flatiron Books.
Smith, David. 2017. “Reproducible Data Science with r.” 2017. https://blog.revolutionanalytics.com/2017/04/reproducible-data-science-with-r.html.
Wickham, Hadley. 2015. Advanced r. CRC Press. http://adv-r.had.co.nz/.
———. 2019. Advanced r. Second. CRC Press. https://adv-r.hadley.nz/.
Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science. O’Reilly Media. https://r4ds.had.co.nz/.
Wilke, Claus O. 2019. Fundamentals of Data Visualization. O’Reilly. https://clauswilke.com/dataviz/.
Yihui Xie, J. J. Allaire, and Garrett Grolemund. 2019. R Markdown: The Definitive Guide. CRC Press / Chapman & Hall. https://bookdown.org/yihui/rmarkdown/.