Universität Wien FIND

300368 UE Practical data analysis in ecology, biodiversity and zoology (2016W)

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

Details

max. 16 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Monday 13.02. 14:00 - 19:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Tuesday 14.02. 14:00 - 19:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Wednesday 15.02. 14:00 - 19:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Thursday 16.02. 14:00 - 19:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Friday 17.02. 14:00 - 19:00 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!

Assessment and permitted materials

At the end of the course, a package of statistical problems will be distributed to the participants. These have to be worked out individually. A pdf file containing the solutions and test results has to be submitted electronically, at latest by 15 March 2017. 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

This course aims at familiarizing MSc students with an interest in organismal biology with a wide 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 (PAST, EstimateS and others), and on acquiring expertise which methods to be used with what types of data, but without the need to dwell into programming codes in the widely used R language. Participants are encouraged to bring along their own data and questions.

Examination topics

Participants will work on existing model data sets. If applicable, participants are invited to bring their own data sets, scientific questions and quantitative problems, to be jointly discussed and solved.

Reading list


Association in the course directory

MEC-5, MZO W-9, B-WZB

Last modified: Fr 31.08.2018 08:56