Universität Wien FIND

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300224 VU Multivariate statistical methods in ecology (2021S)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Continuous assessment of course work



max. 25 participants
Language: English



The course is scheduled as one block, from March 8-12, daily from 0900-1700. The entire class will be in distance-learning format and held online.


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).
We aim at providing an overview (including theoretical background) on statistical testing, in combination with a practical part during which students are to acquire the capacity to independently implement statistical testing strategies.
Lectures on theory and derivation of statistical methods are combined with hands-on R scripting to achieve this goal.

Assessment and permitted materials

Presence throughout the course is compulsory.

A written exam of 2 h length, comprising a theoretical and a practical part, will be held at the end of the class. A second and a third opportunity will be offered in accordance with the participants

Minimum requirements and assessment criteria

A general understanding of R is mandatory for the course.
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.
The written exam and test exercises will focus on these aspects, and a total of 20 points may be awarded, where the following total points correspond to grades 5-1: 0-10 points = 5, 11-13 = 4, 13-15 = 3, 15-17 = 2, >18 = 1.

Examination topics

Successful participants will be capable of interpreting statistical testing theory, applying and justifying conventions as well as analyzing data sets. They can propose testing schemes for datasets/problems and develop and implement a testing approach based on an example data set.

Reading list

Literature will be provided in form of a course hand-out; additional literature will be presented during the class

Association in the course directory

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

Last modified: Th 04.03.2021 15:29