Dina Research School

Introduction

The R system is a powerful environment for statistical data analysis, publication-quality graphics, and data processing; basically a modern version of the S/PLUS system. The R system is highly extensible: you can easily write your own functions to handle repetitive tasks or to perform non-standard preprocessing, data analysis or simulation.

In addition, R is open source and has a large number of contributed packages for advanced statistical data analysis, for instance in image processing and bioinformatics, including analysis of microarray experiments.

The R system also includes facilities for interfacing to routines written in the C programming language, so that one can use existing high-performance libraries. Similarly, R's interface to relational databases such as MySQL simplifies the handling of large datasets (hundreds to megabytes). On the other hand, unlike Maple or Mathematica, R does not support symbolic integration, equation solving, and so on.

This workshop provides an introduction to the R system, including basic data processing, statistical analysis, graphics and simple programming. Computer exercises during the workshop provide hands-on experience.

You will benefit from the workshop if you need to repeatedly perform statistical analyses or numerical computations, if you want to experiment with new ways to analyse or process data, or if you work with large datasets. You need not know R beforehand, but the workshop should be beneficial even to people who know R a little but want to get an overview of its core features and some essential packages. The workshop's examples assume knowledge of basic statistics.

The R system is available for Microsoft Windows, Linux and Macintosh, and can be freely downloaded, distributed and installed. It is used in the new introductory course in mathematics and data processing, and in the revised statistics courses, at the Royal Veterinary and Agricultural University, KVL.