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300046 VU Multivariate statistical methods in ecology (2022S)
data analysis and modelling
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 10.02.2022 08:00 bis Do 24.02.2022 18:00
- Abmeldung bis Do 31.03.2022 18:00
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
online via Zoom/BBB
- Montag 07.03. 09:00 - 17:00 Digital
- Dienstag 08.03. 09:00 - 17:00 Digital
- Mittwoch 09.03. 09:00 - 17:00 Digital
- Donnerstag 10.03. 09:00 - 17:00 Digital
- Montag 14.03. 09:00 - 17:00 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Presence throughout the course is compulsory.A written exam of 2 h length, comprising a theoretical and a practical part, will be held at the end of the class. A second and a third opportunity will be offered in accordance with the participants
Mindestanforderungen und Beurteilungsmaßstab
A general understanding of R is mandatory for the course.
Successful participants will gain a working understanding of the mathematical and computational mechanics behind the most commonly used statistical methods in ecology. They will understand how to interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design.
The written exam and test exercises will focus on these aspects, and a total of 20 points may be awarded, where the following total points correspond to grades 5-1: 0-10 points = 5, 11-13 = 4, 13-15 = 3, 15-17 = 2, >18 = 1.
Successful participants will gain a working understanding of the mathematical and computational mechanics behind the most commonly used statistical methods in ecology. They will understand how to interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design.
The written exam and test exercises will focus on these aspects, and a total of 20 points may be awarded, where the following total points correspond to grades 5-1: 0-10 points = 5, 11-13 = 4, 13-15 = 3, 15-17 = 2, >18 = 1.
Prüfungsstoff
Successful participants will be capable of interpreting statistical testing theory, applying and justifying conventions as well as analyzing data sets. They can propose testing schemes for datasets/problems and develop and implement a testing approach based on an example data set.
Literatur
Literature will be provided in form of a course hand-out; additional literature will be presented during the class
Zuordnung im Vorlesungsverzeichnis
MEC-5, UF MA BU 01, UF MA BU 04, MNB2
Letzte Änderung: Mo 27.07.2026 11:14
We aim at providing an overview (including theoretical background) on statistical testing, in combination with a practical part during which students are to acquire the capacity to independently implement statistical testing strategies.
Lectures on theory and derivation of statistical methods are combined with hands-on R scripting to achieve this goal.