Universität Wien
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300141 VU Multivariate statistical methods in ecology (2024S)

data analysis and modelling

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

The preliminary meeting will take place via Zoom, on March 13, 0930. Please register for the course, you will receive an invitation to join the preliminary meeting on Monday, March 11.

The course is scheduled as one block, from April 22-26, daily.

  • Montag 22.04. 09:45 - 18:15 Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
  • Dienstag 23.04. 09:45 - 13:00 Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
  • Dienstag 23.04. 13:15 - 18:15 Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
  • Mittwoch 24.04. 09:45 - 18:15 Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
  • Donnerstag 25.04. 09:45 - 18:15 Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
  • Freitag 26.04. 09:45 - 18:15 Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Statistical data analysis in ecology: descriptive statistics, univariate statistical tests (t-tests, U-test, analysis of variance), bivariate data analysis (correlation, linear and nonlinear regression), selected regression models (multiple linear regression, ANCOVA, GLM, GAM), commonly used classic unconstrained and constrained ordination methods: principal component analysis (PCA), canonical correspondence analysis (CCA), redundancy analysis (RDA), distance/dissimilarity-based unconstrained and constrained ordination methods: metric and non-metric multi-dimensional scaling (MDS, NMDS), canonical analysis of principal coordinates (CAP), multivariate hypothesis tests (PERMANOVA, permutation tests based on ordinations).
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. Low-level understanding of R is advantageous.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Presence throughout the course is compulsory.

Preparation of a course protocol is compulsory.

A written exam of 2 h length comprising a practical part, will be held.

Mindestanforderungen und Beurteilungsmaßstab

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.
Grading will be based on preparation of a course protocol and a written exam testing practical skills for which total of 10 points may be awarded. Failure to produce a coherent and comprehensive course protocol will result in the grade 5, independent of the results of the exam. Up to 3 points may be earned for the protocol, based on coherence, comprehensiveness and quality.
The grading scheme is as follows:
10-9: 1
8-7: 2
6-5: 3
4-3: 4
<3: 5
Points earned for the protocol will be added to points earned during the exam to produce the final score.

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, MMEI III

Letzte Änderung: Di 23.04.2024 14:46