Universität Wien FIND

300325 UE Multivariate statistical methods in ecology (2019S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung

The course is based on the statistical language 'R'. We will offer an introduction to 'R' for people not familiar on three dates nov-jan. A general understanding of R is mandatory for th course.

Course language is English. Note combination with

VO (same name, delivered by Gabriel Singer).

An/Abmeldung

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Vorbesprechung/First meeting: March 13 2019, 14:00 SR Limnologie.

Dates: The course will take place May 6-10 (9:00-12:30), in parallel with the UE (same name, delivered by Robert Ptacnik & Zsofia Horvath, 14:00-17:00). Course language is English.

Freitag 03.05. 10:00 - 16:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Montag 06.05. 09:00 - 16:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Dienstag 07.05. 09:00 - 16:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Freitag 10.05. 09:00 - 16:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Freitag 17.05. 15:00 - 17:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG

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).

Art der Leistungskontrolle und erlaubte Hilfsmittel

80% presence throughout the course, participation in the team work and final presentation are mandatory. Practical course mark is based on presence and commitment during the course (UE 50 %), and (team-) presentations about independently analysed dataset (UE 50 %).

Mindestanforderungen und Beurteilungsmaßstab

Successful participants will learn to apply the most commonly used statistical methods in ecology on provided datasets. They will understand how to produce and interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. They will learn how to perform statistical analyses in the free software 'R'.

Prüfungsstoff

The course is scheduled as one block in May 14-18 2018 (Mo-Fr), afternoons, and should be attended in combination with the lecture (VO) with the same title and taking place in the same period in the mornings. The block course is followed by independent home-based team work. Teams of 2 students each will work on specific ecological datasets, which will be graphically and statistically analyzed under guidance. The course then finishes with student presentations to be given during a 1- day seminar end of May 2018 (exact date will be agreed upon during the first meeting March 6, 15:00, Seminar room limnology).
The course is based on the statistical language 'R'. We offer an introduction to 'R' for people not familiar with R on May 7-8, 14:00-17:00. A general understanding of R is mandatory for the course.

Literatur

Course Handout with R-relevant information will be provided in the lecture, R-scripts

and datasets will be provided for the practical course.

Dalgaard, P. 2008. Introductory Statistics with R (Series: Statistics and Computing).

Springer Verlag, New York, 364 pp.

Borcard D., Gillet F. & Legendre P. 2011. Numerical Ecology with R. Springer, New

York, U.S.A., 306 pp.

Zuordnung im Vorlesungsverzeichnis

MEC-5

Letzte Änderung: Mi 27.03.2019 16:48