Topic outline

  • General

    Introduction to statistics for biologists

    Geneva, 7-11 February 2011

    Course description:

    This 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.
    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.


    • Participants are asked to bring their own laptop (wifi) with the "R" program installed
    • 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 to familiarize yourself with the R language and try some simple examples present in our R tutorial.

    Registration :

    The registration fee for Swiss academics is 100 CHF. (Some doctoral programs may subsidize the course; please contact your doctoral program for more information)
    Participants from the industry or from abroad should contact us.

    Registration is closed.

    ECTS accreditation: 2 credits

    Important: successful participating graduate students will have to inquire if these credits are accepted by their respective graduate schools.

    For more information, please contact Frédéric Schütz


    This course is organized by the SIB Swiss Institute of Bioinformatics in collaboration with the CUSO StarOmics (or *omics) doctoral program (, which intends to create a network of PhD students and professionals involved in any project related to Genomics, Transcriptomics, Proteomics, Metabolomics, Connectomics, and all other large scale data-generating technologies.
    Students of this program will be offered training, workshops, and seminars in genome-wide and proteome-wide data analysis, biological modeling, quantitative image analysis, programming and statistics, in addition to their thorough education in experimental biology, through a didactic program that complements both their individual research topic and background. In addition several events will be organized (annual retreat, mini-symposia, soft skills courses), which besides their didactic value will also favor networking among the students and professors either within this program or jointly with the federation of doctoral programs of the CUSO (Ecology & Evolution, Plant Sciences, and Microbiology). PhD students of this program will become conversant in both experimental and computational approaches, and will acquire the ability to integrate quantitative and experimental methods in their own research. Graduates from this program will have unprecedented scientific competence to permit them to become future leaders in biological research and beyond. The students will not receive ECTS credits from the StarOmics doctoral program, but an attestation to get ECTS credits in their own university. For more information, please have a look at

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