300368 UE Practical data analysis in ecology, biodiversity and zoology (2020S)
Continuous assessment of course work
Labels
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).
- Registration is open from Th 06.02.2020 08:00 to Th 20.02.2020 18:00
- Deregistration possible until Th 30.04.2020 18:00
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Der Termin im März bezieht sich NUR auf die Vorbesprechung. Teilnahme an der Vorbesprechung erforderlich! Der praktische Teil des Kurses findet statt von 07.09.2020 bis 11.09.2020, jeweils 13-17 h, im Seminarraum (Erdgeschoss) des Dept. für Botanik & Biodiversitätsforschung; Rennweg 14.
Thursday
12.03.
14:00 - 15:00
Hörsaal (Fakultätszentrum für Biodiversität) Rennweg EG
Monday
07.09.
13:00 - 17:00
Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Tuesday
08.09.
13:00 - 17:00
Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Wednesday
09.09.
13:00 - 17:00
Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Thursday
10.09.
13:00 - 17:00
Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Friday
11.09.
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), 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 individually. A pdf file containing the solutions has to be submitted electronically, at latest by 15 October 2020. 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 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.
To obtain a positive grade, 50 % of the points available in solving the 'homework' task need to be reached.
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 at the beginning of the course week in September.
Association in the course directory
MEC-5, MZO W-9,
Last modified: Mo 07.09.2020 15:22