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Statistical software tools I + II, fall 2013


Christian Benner


  • 5 credits and pass/fail for the beginner course in period I
  • 5 credits and 1-5 grade for the advanced course in period II


Advanced studies

Content scheme

  1. Beginner course in period I (slides for at home and weekly hands-on sessions)
    • R environment and Bioconductor
    • LaTeX / Beamer
  2. Advanced course in period II (weekly hands-on sessions with discussion) 
    • High performance computing in R with C++ (Rcpp), parallel (OpenMP) and GPU computing (MAGMA)
    • Efficient programming
    • Large data sets


  • No prior knowledge of R is required for the beginner course. However, an interest in computer programming and basic knowledge of statistics is helpful.
  • The minimal prerequisites for the advanced course include mastering of the R environment, an interest in high performance computing with R as well as some basic knowledge of probability calculus, linear algebra and statistics .
  • Availability of a laptop is desirable so that all software can be easily installed.


Period I (02.09-17.10.2013) and period II (28.10-12.12.2013), Tuesday and Thursday 10-12 in computer class room C128 (~24 computers).

The beginner course starts on Thursday 05.09 in CK107 with an introductory session. Note that we meet Wednesday instead of Tuesday in week 37 only.


  • Beginner course in period I: Mid-course computer exam for R and completion of weekly exercise as well as presentation with LaTeX at the end of period I
  • Advanced course in period II: Participation in lectures and group discussions and project work/oral presentation



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