Universität Wien

300325 UE Multivariate statistical methods in ecology (2020S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Continuous assessment of course work

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).

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).

Details

max. 30 participants
Language: English

Lecturers

Classes

A first meeting will be held on March 2nd at 11:00 in the Limnology seminar room.The course is scheduled as one block in March 2020, 9-13, 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.

Information

Aims, contents and method of the course

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).

Assessment and permitted materials

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'.

Minimum requirements and assessment criteria

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 %).

Examination topics

A first meeting will be held on March 2nd at 11:00 in the Limnology seminar room.The course is scheduled as one block in March 2020, 9-13, 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.

Reading list

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.

Association in the course directory

MEC-5

Last modified: We 18.03.2020 15:29