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Statistical Software: R

Guide to resource on statistical packages like SPSS, Stata, SAS, and R

Workshops at Penn Libraries

Interested in learning more about a particular software or tool? Check out our upcoming workshops

Accessing R and RStudio

Several options are available for software access:

  • R is available for free download from the R ProjectR Studio provides a user-friendly interface for R. To run RStudio, R needs to be downloaded first.
  • RCloud is an environment for collaboratively creating and sharing data analysis scripts. If you are unable to download R for any reason, this might be a good option.
  • Anaconda is a distribution of the R programming language for scientific computing. R can be installed through the Anaconda computing environment.
  • If you are on campus, lab computers with R are available at Van Pelt and other libraries, as well as the Undergraduate and Graduate Data Analysis Labs in McNeil Building.

Penn Libraries x Dataquest

Penn Libraries has negotiated a campus-wide premium license for Dataquest, the scaffolded online learning platform with a full catalog of interactive coursesskill paths such as data visualization, machine learning, and data scraping and career paths using Python, R, PowerBI, and Tableau. You learn by doing, completing exercises and getting immediate feedback directly in the browser. To activate your premium account, please complete the form below.

 

Getting Started with R

R LogoR is a popular open-source language and environment for statistical computing and graphics. These are some resources to help you get started learning R.

Workshop Recordings

Resources for Learning R

Statistical Software Assistance at the Library

Appointments are available with our statistics software consultant for R, Stata, SPSS, and Python.  Make an appointment via the Penn Libraries Technology Consultation Appointment page : select "Stata, R and Other Statistical Software" for available appointments.

Data Packages

The R community has developed numerous programs that add functionality to R. Below are a few popular and useful packages.

Penn Libraries Books on R

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