The R Statistical Computing Environment: The Basics and Beyond (Berkeley, CA)
The R statistical programming language and computing environment has become the de facto standard for writing statistical software among statisticians. Over the past few years, it also has made substantial inroads in the social sciences. R is a free, open-source implementation of the S language, and is available for Windows, Mac OS X, and Unix/Linux systems. There is also a commercial implementation of S called S-PLUS, but it has been eclipsed by R.
One of the biggest advantages of R is that users can extend it to incorporate new data processing and analysis routines. Statisticians and others (including a number of social scientists) have taken advantage of the extensibility of R to contribute more than 3000 freely available "packages" of documented R programs and data to CRAN (the Comprehensive R Archive Network) and many others to the Bioconductor package archive.
The goal of this four-day workshop is to introduce R and R programming. Each day will combine five to six hours of lectures and demonstrations with two to three hours of hands-on labs. We will begin with a basic overview of, and introduction to, R including statistical modeling - in effect, using R as a statistical package. After that, the workshop picks up where the basic material leaves off, and provides the background required to use R seriously for sophisticated data analysis and presentation. Topics to be covered in the workshop include an introduction to R programming, the design of custom statistical graphs, and unlocking the power of the R statistical programming environment.
Fee: Members = $1400; Non-members = $2800