300325 UE MEC-5 Multivariate statistical methods in ecology (MOE I-3) (2013W)
Continuous assessment of course work
Labels
Vorbesprechung/First meeting: 14.10.2013, 9:00, HS II.Dates: Blocked course December 16-20 2013, Seminarroom Dep. Limnology (Ebene 3). Further dates upon agreement. Course language is English if necessary. Lecture "Multivariate statistical methods in ecology" in combination with lab course (same name).
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Fr 06.09.2013 08:00 to Mo 23.09.2013 18:00
- Deregistration possible until Th 31.10.2013 18:00
Details
max. 15 participants
Language: German, English
Lecturers
Classes
Currently no class schedule is known.
Information
Aims, contents and method of the course
Statistical data analysis in ecology: descriptive statistics, univariate statistical tests (t-tests, U-test, analysis of variance), bivariate data analysis (correlation, linear and non-linear regression), selected regression models (multiple linear regression, ANCOVA, GLM, GAM), selected ordination methods (principal component analysis, non-metric multi-dimensional scaling)
Assessment and permitted materials
Presence throughout the course is necessary. Lecture (VO) mark is based on written examination about theoretical contents of the block course part. Lab course (UE) mark is based on presence and commitment during the course (UE 50 %), and (team-) presentations about independently analysed dataset (UE 50 %).
Minimum requirements and assessment criteria
Successful participants will be able to graphically and statistically analyze complex multivariate ecological datasets and prepare these data for oral presentation or publication.
Examination topics
The course is scheduled as one block in December 2013 (Dec-16 to Dec-20) and some additional dates in January 2014. Lectures and practical sessions interweave flexibly during the first week, short introductory lectures will be followed by hands-on practical sessions using the statistical language R. No experience in R is needed. The course starts with an overview of univariate and bivariate methods, followed by a focus on multivariate methods for two days. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design. The block course is followed by independent home-based team work. Teams of 2 students each will work on specific ecological datasets, which will be graphically and statistically analyzed under guidance. The course then finishes with student presentations to be given during a 1-day seminar in January (date open).
Reading list
Course Handout will be provided.Further literature:
Quinn, G. P. & M. J. Keough. 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge, 537 pp.
Dalgaard, P. 2008. Introductory Statistics with R (Series: Statistics and Computing). Springer Verlag, New York, 364 pp.
Quinn, G. P. & M. J. Keough. 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge, 537 pp.
Dalgaard, P. 2008. Introductory Statistics with R (Series: Statistics and Computing). Springer Verlag, New York, 364 pp.
Association in the course directory
MEC-5, MOE I-3
Last modified: Mo 07.09.2020 15:43