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300368 UE Practical data analysis in ecology, biodiversity and zoology (2024S)
Data Analysis and modelling
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 08.02.2024 14:00 bis Do 22.02.2024 18:00
- Abmeldung bis Fr 15.03.2024 18:00
Details
max. 18 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Freitag 08.03. 11:00 - 12:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Montag 02.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Dienstag 03.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Mittwoch 04.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Donnerstag 05.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
- Freitag 06.09. 13:00 - 17:00 Seminarraum (Fakultätszentrum für Biodiversität) Rennweg EG
Information
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, 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.
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 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.
Mindestanforderungen und Beurteilungsmaßstab
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.
Prüfungsstoff
For the final 'homework', participants will work on model data sets provided, using the methods presented and applied during the course week.
Literatur
Some hints will be offered in the initial meeting and later during the course week in September.
Zuordnung im Vorlesungsverzeichnis
MEC-5, MZO3, MNB2
Letzte Änderung: Mi 31.07.2024 12:06