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300452 VO Multivariate statistical methods in ecology (2019S)

2.00 ECTS (1.00 SWS), SPL 30 - Biologie


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


Language: English

Examination dates



Vorbesprechung/First meeting: March 6 2019, 14:00 SR Limnologie.


Dates: The course will take place May 6-10 (9:00-12:30), in parallel with the UE (same name, delivered by Robert Ptacnik & Zsofia Horvath, 14:00-17:00). Course language is English.


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 nonlinear regression), selected regression models (multiple linear regression, ANCOVA, GLM, GAM), commonly used classic unconstrained and constrained ordination methods: principal component analysis (PCA), canonical correspondence analysis (CCA), redundancy analysis (RDA), distance/dissimilarity-based unconstrained and constrained ordination methods: metric and non-metric multi-dimensional scaling (MDS, NMDS), canonical analysis of principal coordinates (CAP), multivariate hypothesis tests (PERMANOVA, permutation tests based on ordinations).

Assessment and permitted materials

Presence throughout the course is not necessary, but strongly recommended to allow following the practical courses in the afternoons. The lecture mark is based on a written examination that can be taken on May 18 (in the last lecture), or on an alternative date in June 2018 or – if necessary – in October 2018. No materials are permitted during examination.

Minimum requirements and assessment criteria

Successful participants will gain a working understanding of the mathematical and computational mechanics behind the most commonly used statistical methods in ecology. They will understand how to interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design.

Examination topics

The course is scheduled as one block in May 14-18 2018 (Mo-Fr), mornings. The lecture should be attended in combination with the practical course (UE) with the same title and taking place in the same period in the afternoons. A course handout will be provided.

Reading list

Quinn, G. P. & M. J. Keough. 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge, 537 pp.

A course handout will be provided.

Association in the course directory

MEC-5, UF MA BU 01, UF MA BU 04,

Last modified: We 19.08.2020 08:08