R language fo stats
R was designed with data analysis, graphical representations, and statistics in mind. We will focus on data manipulation and graphics, and almost skip the stats. Actually, once your data are in the right format (thanks to habile data manipulation) and you know what stats to perform (generally after wise graphical explorations), running the stats functions is a piece of cake; the hard part is to know/understand the stats, which is way beyond the focus of this workshop.
More precisely, after a brief R survival guide, we’ll dive into an amazing package: ggplot2 (and its companion plyr). This is an implementation of Wilkinson’s grammar of graphics that brings a very handy layer of abstraction in plotting commands. This makes R a very efficient alternative to any other plotting program, be they spreadsheets or scripts.
Finally, depending on people interests, we will possibly mention various advanced aspects of R: connection to MySQL databases, representations of geographical data, bridge with Python, performance optimisation with C nested in R code .