Peter Dalgaard will give an introduction to basic R features: Vectors, factors, and data frames, with the main focus on usage for standard statistics, including classical tests, linear and generalized linear models, and elementary graphics.

R is not only a statistical package, but it is also an implementation of the S programming language. Duncan Murdoch will present that aspect of it: the structure of R objects, how to write functions in R, how the scope works. He will cover functions and environments in detail, and will include a brief introduction to the two main object-oriented programming systems in R.

Thomas Lumley will describe some more advanced graphics features of R and its contributed packages. The RColorBrewer and dichromat packages allow color choice and color manipulation; transparency and binning produce useful scatterplots for large data sets; the ggplot package implements the Grammar of Graphics for structured design of new graphics.

Simon Urbanek will discuss one of the major strengths of R---its extensibility. Starting with the basics on how to write a package for R, he will move towards more advanced topics such as interfacing native code. Some major uses of this extensibility are graphical user interfaces (GUIs). He will show how to leverage existing GUIs, create new ones and apply them for data analysis.

Each speaker will have an hour for their talk and 10 minutes for discussion.

Peter Dalgaard is an associate professor at the Department of Biostatistics at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He has been a member of the R Core Team since 1997.

Duncan Murdoch is a professor at the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He maintains the Windows version of R, and has lectured about and taught R for several years.

Thomas Lumley is an associate professor in the School of Public Health and Community Medicine at the University of Washington. He has research interests in correlated data regression, clinical trials, and statistical computing and graphics.

Simon Urbanek is a researcher in AT&T Research Labs. He maintains the Mac OS version of R, and his research concentrates on visualization and interactive analysis of statistical models and the development of efficient model ensemble methods.