Processing and Analysis of Biological Data BIOS14
The course is given part time (50%) with lectures in the mornings and exercises in the afternoons two days a week during November–January. Participants may need to spend some time for the exercises between scheduled events. For your planning, you will have access to the exercises in advance. The course can be taken in parallel to BIOS13 Modelling Biological Systems which is also given part-time.
Content: Introduction to SPSS/R, binomial-, poisson- and normal distribution, descriptive statistics and graphs, hypotheses testing, t-test, ANOVAs, correlation, regression, multiple and non-linear regression, chi-square, G-tests, log-linear modelling, logistic regression and survival, discriminant, PCA and cluster analyses.
Examination: There will be a home assignment at the end of the course.
Computers and software: This year the choice of software is up to the student, but instructions for the exercises will only be provided for SPSS and R. Computers (PC:s) will be available, but feel free to bring your own. To do all exercises in SPSS, ver. 12 or higher with extra modules (e.g. Advanced and Regression models) is necessary. If you are interested in using R, a short introduction will be provided before the course starts. It is strongly recommended that you attend this introduction if you would like to use R during the course.
Autumn period 2
Part time, on campus, in English
You will find information about application, prerequisites and the syllabus at Lund University's central web pages.
Course literature, 2023
Experimental Design and Data Analysis for Biologists (2002) G. P. Quinn and M. J. Keough, Cambridge University Press. ISBN: 9780521009768.
Getting Started with R - An introduction for biologists (2017), Beckerman and Petchey, ISBN: 9780198787839
The latest schedule for the course Processing and Analysis of Biological Data in the schedule software TimeEdit.
You will find the latest evaluation on our web page with course evaluations.
Lotta Persmark, Study advisor, biology and bioinformatics
Telephone: +46 46 222 37 28
Email: Lotta [dot] Persmark [at] biol [dot] lu [dot] se