The course is designed to provide graduate students in the biomedical sciences with experience in the application of basic statistical analysis techniques to a variety of biological problems. Please see the Program for details.
Attendees will work through short tutorials on the topics discussed
in the class. During the practical exercises students will learn how to work with the widely used "R" language and environment for statistical computing and graphics.
The course participants are also strongly encouraged to submit in advance (until 09.01.09) any real-world questions (and the relevant data) that they may have; problems which fit the workshop's goals might be discussed with the teachers during the Friday's afternoon exercise session.
No prior statistical knowledge is required in order to attend the course, however we strongly recommend you to get familiar with the R statistical analysis package prior attending the course. As the
practical exercises will necessitate the use of the R program, you should already be familiar with the command
line environment of such tool to avoid spending too much time during the practical exercises with the syntax of the program. Please read some documentation (see below) to familiarize with the R language and download the program locally on your computer to try some simple examples present in the tutorials.
We have published a self-assessment (Quizz) to help you test
your R knowledge, and decide whether you have the prerequisites to optimally profit from the content of the course.
Before you take the Quizz please please have a look at the following short tutorial [short tutorial] with the associated example files: [plotdata.txt] [worms.txt] and at the Introduction to R document: Chapters 1-2, 5.1, 5.2, 5.3, 5.8, 5.9, 6-7 and 9 to learn the basics needed for the course.
Details about how to complete the Tutorial and how to take the Quizz are available in the attached pdf file.
Please find here some other useful links:
- R main site (with information how to dowload and install the program)
- R Contributed documentations
Peter Dalgaard, Introductory Statistics with R, Springer
Registration and Fee
The course will be held from January 19 to 23,
Pre-registration form is available here.
The registration fee for academics is 100 CHF.
The registration fee for industry participant is 150 CHF.
The schedule will be available here.
Location, housing and transportation