The popularity of R has exploded over the past several years, and the R language is now considered the lingua franca of statistical computing by many. I lead two- and three-day workshops on R, the open-source software for statistical computing and graphics. My workshops grew out of one that I developed with Adam Ryan (HDR|HydroQual) in 2008. The material is regularly updated and expanded.

New to R? Attending one of these workshops is a great way to get started. An experienced R user, but want to improve your skills? Consider one- or two-day registration, so you can skip the basic material and move onto advanced topics in data manipulation, data analysis, and graphics.

These are hands-on workshops, where you will learn by doing. Previous participants have found them effective in improving their ability to use R for data analysis and production of graphics. Workshop participants are provided with a workbook that has proven to be very useful for both during and after the workshop.

Not sure if an R workshop is the best way for you to learn R? Click here for feedback from other participants. Check out the list of upcoming workshops below. If none work for you, email me about setting one up in your area.

Ucoming workshops

July 2014

University of Delaware, Newark, DE

Previous workshops


Pennsylvania State University, University Park, August

University of Maryland, College Park, May

University of California, Davis, April

University of Maryland, College Park, March


University of California, Davis, September

National Zoo, Washington DC

University of California, Davis, July

Georgetown University

University of Maryland

University of Delaware


University of Southern Mississippi


University of Vermont


SUNY College of Environmental Science and Forestry

University of Delaware


Clemson University


R, a language and environment for statistical computing and graphics

If you are interested in data analysis and presentation, but are not familiar with R, read on.

Why use R?

  • R can be used to carry out the same analyses that you might use SAS, Stat, or Matlab for now, as well as many other analyses.
  • R is open source, and is continually evaluated by a large group of users, making it reliable.
  • The R language is a well-developed and efficient programming language, making for consistent and simple code.
  • R is flexible and extensible, and more than 3600 collections of specialized functions (packages) have been developed by users.
  • The large online community of R users is very active, making it easy to get help with R code.
  • R can be used to produce high-quality graphics in several different formats.
  • R is free!