R Resources

This list is a work in progress! If you have suggestions, please let me know!

Getting Started

• Download and install R from www.r-project.org, then install R-Studio from www.rstudio.com.
  You will learn R more quickly if you use R-Studio as your primary way of using R!
• Getting Started with R from the folks at R-Studio.
• Write R code well by periodically comparing your R scripts to the Google's Style Guide for R
• Self tutorial: My Introduction to R (PDF), and a few similar resources:
  • Work through Appendix A "A sample session" at the end of "An Introduction to R" (the first of the R "Manuals" on the R website).
  • Steve Ellner & John Guckenheimer have various resources including this Introduction to R (PDF); the lab manual for their book Dynamic Models in Biology.
  • Ben Bolker has a similar introduction, lab 1 (PDF); a supplement to his book Ecological Models and Data in R.
  • Yet another R Introduction (YaRI), by Andreas Handel, is based in part on the above works.
• Short, interactive lessons online via the Try R website at tryr.codeschool.com
• Interactive lessons in R via the swirl package: www.swirlstats.com

General Resources:

• Quick-R is an excellent resource! See www.statmethods.net/
• Among other resources on the RStudio website are the Cheat Sheets at www.rstudio.com/resources/cheatsheets/.
• Manuals on the R website are free, and include An Introduction to R, R Data Import/Export, and The R Reference Index.
• CRAN Task Views: Take a moment and skim these comprehensive overviews of R packages for various tasks (e.g. Baysian Inference, Differential Equations, Probability Distributions, Experimental Design, Multivariate Statistics, Numerical Mathematics, Optimization, Robust Statistics, Spatial Data Analysis, Time Series Analysis, etc)
• Introduction to R is a six part online course through DataCamp: www.datacamp.com/courses/introduction-to-r

Graphics

• The Quick-R website sections Graphics and Advanced Graphics are a good place to start.
• research.stowers-institute.org/efg/R/Graphics/Basics/mar-oma/index.htm -- R Graphics Basics: Plot area, mar (margins), oma (outer margin area), mfrow, mfcol (multiple figures)
• flowingdata.com/category/tutorials/ -- Tutorials from FlowingData.com, a data visualization website.
• ggplot2.org/ -- ggplot2 graphics package website
• 10 tips for making your R graphics look their best.

Data

• The Quick-R website sections on data Input (into R) and Management.
• See also the RStudio cheat sheet on Data Wrangling, and the readxl package for importing data from MS Excel spreadsheets.
• The R website manual on R Data Import / Export.
• Coding systems for categorical variables: http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm

Other Resources

• R's assignment operators explained: ‘=’ vs. ‘<-’ vs '<<-': csgillespie.wordpress.com/2010/11/16/assignment-operators-in-r-vs/
• Revolutions -- The staff blog from Revolution Analytics.
• Microsoft Revolution Analytics offers an enhanced version of R called Microsoft R Open (MRO).
• Infographic: R vs Python (www.python.org/): www.datacamp.com/community/tutorials/r-or-python-for-data-analysis
• SciViews.org/ -- Open source software to supplement R.
• Presentation: Intro to R: data manipulation, visualization, communities, networks (presentation by Scott Chamberlain): schamberlain.github.io/posterstalks/sfu/workshop2/
• Presentation: R Resources (presentation by Scott Chamberlain): rpubs.com/recology_/rresources
• Others GUIs/IDEs for R:
  • Windows users: a good (free) R code editor is Notepad++ with NppToR
  • Mac users: while R's native editor is decent, another good (free) R code editor is TextWrangler.
  • ...or for $70, the Sublime Text editor (v2). See this link for using it with R.
  • www.rcommander.com/ -- R Commander, a super basic GUI for simple stats in R.
  • Additional (older) R GUIs can be found at www.sciviews.org/_rgui/ -- see the sidebar for details.
  • Looking for a menu-driven alternative? Check out the R-based software iNZight! Developed for New Zealand high school students to explore data and statistical concepts in a programming-free environment. Read how it compares to Minitab, SPSS, Excel in this blog post.