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Hello!  Thank you for viewing this page.  Given the movement toward incorporating R in statistical analysis here at Carleton, I have created this little sub-page of information.  Posted material includes user-manuals and tutorials for both beginning and advanced users.  Once again, thank you for your consideration.  If you have any questions, email me <BhalaS@carleton.edu> or Paula Lackie <PLackie@carleton.edu> and we will try our best to help.

~ Samir S. Bhala '12, Political Science

What is R?

"R" has two connotations.  First, it is an open-source statistical package; second, it refers to a computer programming language known as R.  You may download and install whichever version you'd like at http://www.r-project.org.  Extensive guides for downloading R to a Windows machine and to a Mac machine also exist.  Boasting a robust open-source community as one of its assets, R has a lot of online and built-in help.

Tutorials and Help Guides for R

As economists would say, there are significant start-up costs to learning R.  It can be daunting.  Resources, like this PDF, can help those users who would like a document to help them started.  The Appendix on sources of help and documentation should prove helpful. 

This site is also useful. 

"I created this website for experienced users of popular statistical packages such as SAS, SPSS, Stata, and Systat (although current R users should also find it useful). My goal is to help you quickly access this language in your work."
~ Robert I. Kabacoff, website author

For answers to specific R-related questions, try using this resource, though Google searches can be equally fruitful.  If you would like more direction than this for R, just let me know.  If R is too strong a brew of tea, check out Paula Lackie's data page and research methods support site

Other notes

Past complaints about R involved file size limitation (due to hardware constraints).  This is no longer an issue. 

Thank you again for visiting this site!

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