Universität Wien

300368 UE Practical data analysis in ecology, biodiversity and zoology (2024S)

Data Analysis and modelling

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

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).

Details

max. 18 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Friday 08.03. 11:00 - 12:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Tuesday 03.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Wednesday 04.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Thursday 05.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Friday 06.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG

Information

Aims, contents and method of the course

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, JASP), 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.

Assessment and permitted materials

At the end of the course, a set of statistical problems will be distributed. These have to be worked out as a home work individually. A pdf file containing the solutions has to be submitted electronically, at latest by 01 October 2024. Participants are allowed to use any means of support for solving these problems, as long as they properly cite all materials used.

Minimum requirements and assessment criteria

Some prior basic knowledge of statistical principles and methods is helpful.
To obtain a positive grade, submission of the 'homework' at the end of the course is mandatory. In this homework, 50 % of the points available need to be reached for a positive grading. 50-62.5%: grade 4; 62.5-75%: grade 3; 75-87.5%: grade 2; >87.5%: grade 1.

Examination topics

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

Reading list

Some hints will be offered in the initial meeting and later during the course week in September.

Association in the course directory

MEC-5, MZO3, MNB2

Last modified: We 06.03.2024 14:07