Advanced
Biostatistical
Methods

Schedule to be downloaded.

Relevant reading for each lecture.

Grading criteria

Participants should get these two books:

1. Experimental Design and Data Analysis for Biologists, by G. P. Quinn and M. J. Keough (Cambridge University Press, 2002, ISBN 0-521-00976-6)
2. Introductory Statistics with R, 2nd revised edition, by P. Dalgaard (Springer-Verlag, New York, 2008, ISBN: 0-387-79053-5)

You need to order the books yourself.

Exercises for the course are adapted to the R statistical software R is an open-source implementation of the S language and is freely available (http://www.r-project.org) for several operating systems. R is command-line based and is currently gaining popularity in the academic community.

All data is available here.

Introduction to R.
Computer exercise 1 - and the solutions.
Computer exercise 2 - and the solutions.
Test exercise 1.
Computer exercise 3 - and the solutions.
Computer exercise 4 - and the solutions.
Test exercise 2.
Computer exercise 5 - and the solutions.
Computer exercise 6 - and the solutions.
Test exercise 3.
Computer exercise 7 - and the solutions.
Computer exercise 8 - and the solutions.
Test exercise 4.

Template

Course evaluation

R for Beginners by Emmanuel Paradis. An introduction to R (pdf: 72 pages) .

R Reference Card by Tom Short. A list of R-commands with brief descriptions (pdf).

Using R for Data Analysis and Graphics - Introduction, Examples and Commentary by John Maindonald (PDF, data sets and scripts are available at JM's homepage).

Ekologisk statistik med R! A webpage with brief descriptions and examples of statistical analyses using R. Compiled by Didrik Vanhoenacker, Dept. of Botany, Stockholm University (Swedish).

Pimp your Graph by Didrik Vanhoenacker. Help file for making nice graphs.

Lazy Dog by Patrik Lindenfors. Code for common R tasksused during the course.