resources.qmd

---
title: "Resources"
---

There are huge number of R resources and websites available online. Included below are links to some R resources which we like. Please let us know if there are more that should be included!

## Books

Here you will find a variety of R-related books, most with both online and print versions.

### Learning R

-   [R 4 Data Science (2e)](https://r4ds.hadley.nz/) - Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
-   [R Programming for Research](https://geanders.github.io/RProgrammingForResearch/) - Brooke Anderson, Rachel Severson, and Nicholas Good
    -   [YouTube Lectures](https://www.youtube.com/@brookeanderson6781/playlists)
-   [Data wrangling, exploration, and analysis with R](https://stat545.com/) - Jenny Bryan

### Statistics with R

-   [An Introduction to Statistical Learning with Applications in R (2e)](https://www.statlearning.com/) - Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
    -   Course: [StanfordOnline: Statistical Learning with R](https://www.edx.org/learn/statistics/stanford-university-statistical-learning)
-   [Statistical Inference via Data Science: A ModernDive into R and the Tidyverse!](https://moderndive.com/) - Chester Ismay and Albert Y. Kim
-   [Tidy Modeling with R](https://www.tmwr.org/) - Max Kuhn and Julia Silge
-   [Applied Statistics Using R: A Guide for the Social Sciences](https://us.sagepub.com/en-us/nam/applied-statistics-using-r/book266647) - [Matthias Mittner](https://uit.no/ansatte/matthias.mittner) \@ UiT (*print only*)
-   [Innføring i R for statistiske dataanalyser](https://www.universitetsforlaget.no/en/innforing-i-r-for-statistiske-dataanalyser) - [Matthias Mittner](https://uit.no/ansatte/matthias.mittner) \@ UiT (*print only*)
-   [Introduction to Modern Statistics](https://openintro-ims2.netlify.app/) - Statistics textbook written using Quarto in RStudio ([source code on github](https://github.com/OpenIntroStat/ims))
-   [Beyond Multiple Linear Regression: *Applied Generalized Linear Models and Multilevel Models in R*](https://bookdown.org/roback/bookdown-BeyondMLR/) *-* Paul Roback and Julie Legler

## R Resources:

-   [Data Science Learning Community](https://dslc.io) - tools and resources for data science, including R and Python.

    -   Weekly data science book clubs - [Website](https://dslc.io/bookclubs.html) / [YouTube](https://www.youtube.com/@dslcvids)

    -   [R Help Slack Channels](https://dslc.io/question_answering.html)

    -   [TidyTuesday](https://github.com/rfordatascience/tidytuesday/blob/master/README.md) - Weekly real-world dataset analyzed by the community

-   [RStudio Education: Finding your way to R](https://education.rstudio.com/learn/)

    -   [A Gentle Introduction to Tidy Statistics in R](https://posit.co/resources/videos/a-gentle-introduction-to-tidy-statistics-in-r/) - 1 hour video webinar by Thomas Mock

-   [R Cheatsheets](https://posit.co/resources/cheatsheets/) - Printable double-sided PDFs summarizing various topics and packages.

-   [Awesome R](https://github.com/qinwf/awesome-R) - A curated list of awesome R packages and tools.

-   [Posit Recipes](https://posit.cloud/learn/recipes) - A collection of R code snippets and instructions featuring up-to-date best practices for coding in R.

## Interactive Tutorials

For these sites, the introductory courses are usually free, while more advanced courses require payment.

-   [DataCamp](https://www.datacamp.com/category/r)
-   [Codecademy](https://www.codecademy.com/catalog/language/r)