300368 UE Practical data analysis in ecology, biodiversity and zoology (2023S)
data analysis and modelling
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 09.02.2023 08:00 to Th 23.02.2023 18:00
- Deregistration possible until We 15.03.2023 18:00
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Wednesday 08.03. 09:00 - 10:00 Hörsaal (Fakultätszentrum für Biodiversität) Rennweg EG
- Monday 04.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Tuesday 05.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Wednesday 06.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Thursday 07.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Friday 08.09. 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 2023. 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.
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, MZO W-9, MZO3, MNB2
Last modified: Tu 14.03.2023 12:09