Collection of useful links. Feel free to use.
- Project-oriented workflow: Best practices which streamline managing multiple projects, collaboration, reproducibility, etc. Other useful tips here
- R for Data Science
- R Markdown
- Data Visualization by Kieran Healy
- Fundamentals of Data Visualization by Claus O. Wilke
- http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
- https://cfss.uchicago.edu/lab03.html
- Arrange plots
- Personal favorite: patchwork
- An Introduction to Statistical Learning
- Anything from the IDRE
- Statistical Rethinking - Richard McElreath
- Introduction to Empirical Bayes - David Robinson
- A Student's Guide to Bayesian Statistics
- https://stats.idre.ucla.edu/other/mult-pkg/introduction-to-linear-mixed-models/
- https://ourcodingclub.github.io/2017/03/15/mixed-models.html#one
- https://cran.r-project.org/web/packages/lme4/vignettes/lmer.pdf
- Nested vs. crossed effects
- https://stats.stackexchange.com/questions/4700/what-is-the-difference-between-fixed-effect-random-effect-and-mixed-effect-mode
- Tensorflow for R blog
- Deep Learning by Google
- Deep Learning with R (paid resource but the book is a good buy)