Universität Wien

300368 UE Practical data analysis in ecology, biodiversity and zoology (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. 15 Teilnehmer*innen
Sprache: Englisch


Termine (iCal) - nächster Termin ist mit N markiert

Dienstag 08.03. 09:00 - 10:00 Hörsaal (Fakultätszentrum für Biodiversität) Rennweg EG
Montag 05.09. 09:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Dienstag 06.09. 09:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Mittwoch 07.09. 09:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Donnerstag 08.09. 09:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Freitag 09.09. 09:00 - 16:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG


Ziele, Inhalte und Methode der Lehrveranstaltung

Some basic theory, but mostly practical application, of a range of statistical tests and methods that are frequently used in ecology, zoology and biodiversity research. Participants are required to work on their own computer!

This course aims at familiarizing MSc students with an interest in organismal biology with a range of statistical concepts and tools. Methods to be covered include linear models, correlation and regression, analysis of contingency tables, constrained and unconstrained ordinations, some non-parametric alternatives to classic linear models, or species diversity statistics. The focus is on practical solution of common problems, using freely available software packages (e.g. PAST), and on acquiring expertise which methods to be used with what types of data, but without the need to dwell into programming codes like in the widely used R language.

Art der Leistungskontrolle und erlaubte Hilfsmittel

At the end of the course, a set of statistical problems will be distributed. These have to be worked out individually. A pdf file containing the solutions has to be submitted electronically, at latest by 01 October 2022. Participants are allowed to use any means of support for solving these problems, as long as they properly cite all materials used.

Mindestanforderungen und Beurteilungsmaßstab

Some basic knowledge of statistical methods is helpful. To obtain a positive grade, submission of the 'homework' at the end of the course is mandatory.
To obtain a positive grade, 50 % of the points available in solving the 'homework' task need to be reached.


For the final 'homework', participants will work on model data sets provided, using the methods presented and applied during the course week.


Some hints will be offered in the initial meeting and later at the beginning of the course week in September.

Zuordnung im Vorlesungsverzeichnis

MEC-5, MZO W-9, MZO3, MNB2

Letzte Änderung: Mi 24.08.2022 17:08