STATISTICS WITH R, 2013 (5 credits)

COURSE MATERIAL

Lectures and/or self-study materials (see below for further information).

R is both an environment for mathematical computation as wells as a programming language with a rich syntax towards doing statistical modeling and data analysis. R is an open source effort which has gained an enormous popularity over the past few years, e.g. demonstrated by the large number of recently published textbooks that focus on doing various types of statistical modeling using R. The environment has a modular structure, such that developers can smoothly add new functionality in form of packages or libraries. Bioconductor package is a shining example of how powerful and successful tools the open source –based research community may create.

R itself is a command-based interface towards doing statistics, however, several menu-based add-on packages have also been created by developers to provide access to most common statistical analysis tools for non-expert users. Two excellent examples of such packages are R Commander and Statistical lab.

This course focuses on learning the basic syntax of R and showing how it can efficiently applied to perform an array of common statistical analyses. As the lectures consist primarily of computer practicals, there will be no written exam at the end of the course. However, the participants are required to solve a set of exercises to gain credits from the course.

Course Material: Several books are available about R. The student library of Åbo Akademi has multiple copies of Statistical computing with R, by Maria L. Rizzo, Chapman&Hall/CRC 2007. This book contains also material suitable for performing advanced statistical analyses and simulations using R. However, the basic syntax can also be investigated using R help, for example type > help.start() in R console and then use link 'An introduction to R'.

FIGURE 1.4 from the book: "Lattice: Multivariate Data Visualization with R".