R & RStudio

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Overview

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. 

R is the fastest growing statistical software/language and is rapidly overtaking all others (e.g. SPSS, STATA, & SAS in popularity and use.)  For a view of where it's come from, check out R: Past and Future History (from 1998).

RStudio Desktop is a powerful and productive user interface for R. It’s free and open source, and works great on Windows, Mac, and Linux.

Contents

Product Details  

• Product name: R  
• Product home page: R Project for Statistical Computing 
• Product name: RStudio

System Requirements

R runs on *inux, Windows & Mac operating systems and so does RStudio.

Licensing & Cost Information

R & RStudio are freely available. Freely available refers to software which is legally available for no monetary cost to the college or individual.  Note that there may still be usage limitations (such as personal use only) set down by the license agreement.  We always recommend that you at least skim a license agreement before you agree to its terms.

Regardless of licensing, please place all requests for software through ITS (see below).  This way, the college may be able to save significant amounts of money by including the additional license(s) under existing agreements.

Usage Restrictions

This section should remain the the form of three questions and the statement on "non-commercial" use.

• Can I use R/RStudio for research?  Yes, but click here for compliance and validation issues

• Is R/RStudio limited to educational use?  No

• Is R/RStudio available for personal use?  Yes

• Read the license agreements regarding whether this software is available for commercial use.

Home Use

You can install R & RStudio for your personal use and continue to use it after you leave Carleton. 

Where Can I Find R on campus?

R (and RStudio) is available in all refreshing labs and classrooms.  For a complete list, see: a list of what's where in the labs - including the extensive full list of R libraries that are added in the install by ITS! 

How Do I Request R?

Labs and Classrooms

To request this software be installed on a refreshing lab/classroom contact either Rapid Response or Student Computing.

College Owned Equipment

You can install R on college owned (or any) equipment by downloading it from here.

Personal Machines

You can install R on your personal machine by downloading it from here.  It is also available for college owned computers via KBOX.  

Getting Started with R (and RStudio)

Through our licensed with LinkedIn Learning, you have access to these (and many other LinkedIn Learning courses):

• R for Data Science: Analysis and Visualization
• R Essential Training: Wrangling and Visualizing Data
• R Essential Training Part 2: Modeling Data

Note that you need to login via your Carleton credentials for access to LinkedIn Learning online courses. 

See also: 

• Laura Chihara's basic handouts for getting started with R: http://apps.carleton.edu/curricular/math/resources/rcomputing/
  
  
• A wealth of Online Learning opportunities identified by RStudio. 
  • In particular, read the R Style Guide for advice on how to write readable, maintainable code.  (This is how other R users will expect your code to look when you share it.) 
  • RStudio: Support & Documentation
  • A host of wonderful R Cheat Sheets from RStudio (Many of these have been translated into several languages!) 
     
• Open Learning Initiative free course on Probability and Statistics (in which the assignments may be completed using R.) From Carnegie Mellon University. = A general introduction to probability & statistics course so it's good for people who need to brush up on this while learning R.
  
  
• A (very) short introduction to R (and Rstudio) = A 12 page pdf. 
  
  
• QuickR  = Helpful place to find examples of commonly used code, especially for data manipulation. 
  
  
• UCLA's Resources for learning R = This includes an outrageously helpful table of Data Analysis Examples (in multiple languages.)
   
• CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and and documentation for R (Manuals). 
   

• Avril Coghlan maintains these 3 HTML or PDF "books":

  • “A Little Book of R for Biomedical Statistics”
  • “A Little Book of R for Time Series”

  • “A Little Book of R for Multivariate Analysis”