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Data Services: R

Describes numeric data resources and services

R Videos

Screencast versions of the workshops listed above. Maximize the viewer size and resolution for the best results...

Intro to R, Session 1 - Statistical Functions

Intro to R, Session 2 - Graphics

Intro to R, Session 3 - Data Manipulation

Time Series in R

R Workshop Materials

The Introduction to R workshops are split into three parts:

Session 1 - Statistical Techniques: Descriptive Statistics, Regression, Significance, Finding Additional Packages

Session 2 - Graphics:  comparison of graphing techniques of basic R, lattice, and ggplot2 packages

Session 3 - Data Manipulation:  Data Import and Transformation

plus an extra session on Time Series.

Updated session scripts available at

Click on the links below to download the materials.

Data Visualization

Data Visualization now has its own page.

Special Topics

R scripts for Special Topics workshops

Workshop Survey

R Workshop Schedule

Rutgers University Libraries Data Services Workshop Series (New Brunswick)

Spring 2019

Introduction to R

  • Monday, February 11 – 12:00-1:30 pm, LSM Conference Room (Instructor, Ryan Womack)
  • Tuesday, February 12 – 1:10-2:40 pm, Alexander Library Room 413 (Instructor, Ryan Womack)

This session provides a three-part orientation to the R programming environment, covering statistical techniques, graphics, and data manipulation.

Data Visualization with R

  • Monday, February 18 – 12:00-1:30 pm, LSM Conference Room (Instructor, Ryan Womack)
  • Tuesday, February 19 – 1:10-2:40 pm, Alexander Library Room 413 (Instructor, Ryan Womack)

This workshop discusses principles for effective data visualization, and demonstrates techniques for implementing these using R.  Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background.  

Please see the complete Fall workshop schedule on the front page of the data guide.


About R

R is open source software for statistical analysis.  Being open source (Gnu GPL licensed) doesn't just mean that the software is free.  It means that you can use it for a variety of applications, and install it virtually anywhere you'd like, without any restrictions.  Open source also means that the code for all statistical procedures and analysis can be independently checked and verified.  The activity community of R users is constantly developing new add-on packages that use the latest techniques, which you are free to do as well.  And, being free, you can always have access to the latest version of the software, no matter where you are.

R is also a programming language, which makes it easy to document, reuse and reproduce all the steps of your statistical analysis. 

You can get R, and full documentation on R, at or by downloading from any CRAN mirror (Comprehensive R Archive Network).

Looking for more justification?  Read The One Tool I Couldn't Live Without and Why Use R? A Grad Student's 2 cents.

R Learning Links

Guides and Tutorials
Searching for R on the Internet
More Information
Enjoy R!

The R Help System

Help Commands within R
 • help.start() - launches interactive help system
 • help(function) or ?function launch the manual pages
   describing a function
 • example(function) provides detailed examples
 • for help on a whole package, try library(help=packagename)
 • apropos and (deep vs. fuzzy search, respectively)
 • vignette("mypackage")

R Tips and Tricks

These are some miscellaneous useful and interesting links that may help you accomplish some specific tasks in R.

Data Librarian

Ryan Womack's picture
Ryan Womack
Alexander Library
169 College Avenue
New Brunswick, NJ 08901 USA
Subjects:Data, Economics

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