Universität Wien

300046 VU Multivariate statistical methods in ecology (2022S)

data analysis and modelling

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung


Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").


max. 25 Teilnehmer*innen
Sprache: Englisch


Termine (iCal) - nächster Termin ist mit N markiert

online via Zoom/BBB

Montag 07.03. 09:00 - 17:00 Digital
Dienstag 08.03. 09:00 - 17:00 Digital
Mittwoch 09.03. 09:00 - 17:00 Digital
Donnerstag 10.03. 09:00 - 17:00 Digital
Montag 14.03. 09:00 - 17:00 Digital


Ziele, Inhalte und Methode der Lehrveranstaltung

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.

Art der Leistungskontrolle und erlaubte Hilfsmittel

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

Mindestanforderungen und Beurteilungsmaßstab

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.


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.


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

Zuordnung im Vorlesungsverzeichnis

MEC-5, UF MA BU 01, UF MA BU 04, MNB2

Letzte Änderung: Do 11.05.2023 11:28