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learn-r.Rmd
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---
title: "Materials for learning R"
author: "Jessica Minnier"
date: '`r Sys.Date()`'
output:
md_document:
toc: true
---
<!-- The .md file is generated from a .Rmd file, please edit the .Rmd file! -->
# Learning R/Rstudio for beginners
## Similar lists of resources
- [rstats-ed repository by Rstudio education/Mine Cetinkaya Rundel](https://github.com/rstudio-education/rstats-ed)
## Interactive lessons
- [R bootcamp](https://t.co/GEXiDgm5nG) - interactive lessons in tidyverse/broom/stats, [Ted Laderas](https://laderast.github.io/) and Jessica Minnier (me)
- [Rstudio Cloud primers](https://t.co/FQMcHOpb42) - Interactive lessons (using learnr) on the basics of R, visualization, tidyverse. Requires a free Rstudio Cloud account.
- [Teacup Giraffes](https://tinystats.github.io/teacups-giraffes-and-statistics/index.html)
- [Swirl](https://swirlstats.com/)
- [To R from Stata: An Introduction](https://rslbliss.shinyapps.io/R_from_Stata/) - learning R for Stata users, by [Richard S.L. Blissett](http://rslblissett.com/)
## Slides/videos/online courses
- [OHSU OCTRI BERD Workshops](https://github.com/jminnier/berd_r_courses), with [audio recordings](https://echo360.org/section/aefe4e1c-c635-4a3b-bf99-ce6439184f5f/public) - workshops taught by Jessica Minnier and [Meike Niederhausen](https://github.com/Niederhausen)
+ Introduction to R and Rstudio [slides](https://jminnier-berd-r-courses.netlify.com/01-getting-started/01_getting_started_slides.html)
+ Data Wrangling in R with the Tidyverse [part 1 slides](https://jminnier-berd-r-courses.netlify.com/02-data-wrangling-tidyverse/02_data_wrangling_slides_part1.html), [part 2 slides](https://jminnier-berd-r-courses.netlify.com/02-data-wrangling-tidyverse/02_data_wrangling_slides_part2.html#1)
+ Reproducible Reports with R Markdown [slides](https://jminnier-berd-r-courses.netlify.com/03-rmarkdown/03_rmarkdown_slides.html)
- [Ready for R - course by Ted Laderas](https://ready4r.netlify.app/)
- [Software Carpentry - R Novice](https://swcarpentry.github.io/r-novice-inflammation/)
- [Software Carpentry - R for Reproducible Scientific Analysis](https://swcarpentry.github.io/r-novice-gapminder/)
- [Chromebook's Intro to R](https://leanpub.com/universities/courses/jhu/cbds-intro-r) - sliding scale of $
- [Getting Started with R](https://rfortherestofus.com/courses/getting-started/) - David Keys
## Textbooks (online, free)
- Long list: [Free R Reading Material](https://committedtotape.shinyapps.io/freeR/) - list of books about R and Data Science, compiled by David Smale
- [R for Data Science](https://r4ds.had.co.nz/) - Hadley Wickham and Garrett Grolemond
- [Hands on Programming with R](https://rstudio-education.github.io/hopr/index.html) - Garrett Grolemund
- [Modern Dive: Statistical Inference via Data Science](https://moderndive.com/) - Chester Ismay and Albert Y. Kim; an intro to statistics using R/tidyverse, gives basic introduction to R and Rstudio and programming, great for beginners.
- [YaRrr! The Pirate's guide to R](https://bookdown.org/ndphillips/YaRrr/) - Nathaniel D. Phillips
- [Topics in STAT545 at UBC](https://stat545.com/topics.html) - Data wrangling, exploration, and analysis with R
## Blog posts
- [R Weekly's list of Tutorials](https://rweekly.org/2017-20.html)
- [Basic basics - R and Rstudio](http://rladiessydney.org/post/2018/11/05/basicbasics/) - R Ladies Sydney, includes an [Opinionated Tour of Rstudio](http://rladiessydney.org/post/2018/11/05/basicbasics-1/)
## Resources
- [R for Data Science Online Community](https://www.rfordatasci.com/) - join their slack channel. A community of R learners at all skill levels working together to improve our skills.
- [Rstudio Community](https://community.rstudio.com/) - online resource for asking questions and getting help
- [Data Science with R, A Resource Compendium](https://bookdown.org/martin_monkman/DataScienceResources_book/) by Martin Monkman
- [600 websites about R, and counting](https://www.datasciencecentral.com/profiles/blogs/600-websites-about-r)
## $$ Options
- [DataQuest](https://www.dataquest.io/directory/) has several R courses, some free, some cost $
+ [Intro to Programming in R](https://www.dataquest.io/course/intro-to-r/) - free
## Blogs
# Statistics in R
## Interactive lessons
- [Generalized Additive Models (GAMs) in R](https://noamross.github.io/gams-in-r-course/) - Interactive course by Noam Ross
- [Intro to Stats for Data Science - Categorical Data](https://minnier.shinyapps.io/ODSI_categoricalData/) - Oregon Data Science Institute workshop, [Ted Laderas](https://laderast.github.io/) and Jessica Minnier
- [Intro to Stats for Data Science - Continuous Data](https://minnier.shinyapps.io/ODSI_continuousData/) - Oregon Data Science Institute workshop, Jessica Minnier and [Ted Laderas](https://laderast.github.io/)
# Intermediate/Advanced/More R
## Textbooks/tutorials
- [What They Forgot to Teach You About R](https://whattheyforgot.org/) - Jenny Bryan and Jim Hester
- [A gRadual Introuction to Shiny](https://laderast.github.io/gradual_shiny/) - [Ted Laderas](https://laderast.github.io/) and Jessica Minnier
- [Advanced R](https://adv-r.hadley.nz/) - Hadley Wickham
- [R Packages](http://r-pkgs.had.co.nz/) - Hadley Wickham