What is this page about?
As open and reproducible science has gained momentum, there has been a push towards transparent and free resources to build your skills on a wide variety of topics. Here are some of our favorite resources below.
Statistical resources
- Statistical Inference for data science
- Geocomputation with R
- An amazing resource by several geographers that gets into modern spatial computing and visualization tools in R
- Statistical Rethinking
- A course for biostatisticians trained in the frequentist tradition looking to master modern Bayesian computational techniques.
- The author, Richard McElreath is a distinguished quantitative anthropologist and his research focuses on big questions in cultural anthropology such as the evolution of human distinctiveness (with examples including skill acquisition).
- The course lectures are also online at YouTube
- And of course, the OG himself, Hadley Wickham. R for Data Science is a great applied overview about what R can do for you and your analyses.
Computational Resources
- swirl: A package that teaches you how to learn R … in R! + A pretty amazing resource that I would have loved to have as an undergrad struggling to learn R and Perl
- happygitwithr: A very practical and straightforward introduction to Git written by the one and only Prof. Jenny Bryan.
- I’ve found her bookdown resources to be super helpful.
- The Pirate’s Guide to R: Both entertaining and a practical introduction to R
- Stack Overflow: For pretty much any problem you run into, Stack Overflow has a possible solution.