B2/ETX3b Tools for multivariate data analysis - Einzelansicht

 See module hand book and course schedule 

The course takes place in room CIII 140 PC room IV from 10:00 - 12:00 (exercise) and in CIV 060 UG from 12:00-14:00 (lecture)

See literature list provided with the course materials. Some relevant books:

Borcard, D.; Gillet, F.; Legendre, P., Numerical Ecology with R. Springer: New York, 2018; 2nd ed.

Crawley, M. J., The R book. Wiley: Chichester, 2012; p 942.

James, G., Witten, D., Hastie, T., and Tibshirani, R. 2017. An introduction to statistical learning: with applications in R ; Springer: New York. Free to download: http://www-bcf.usc.edu/~gareth/ISL/

Legendre, P.; Legendre, L., Numerical Ecology. Elsevier: Amsterdam, 2012; Vol. 3nd, p 853.

Maindonald, J. and J. Braun 2010. Data Analysis and Graphics Using R. Cambridge University Press, Cambridge.

Zuur, A. F., Ieno, E. N. and G. M. Smith 2007. Analysing Ecological Data. Series: Statistics for Biology and Health.

A prerequisite is the willingness to participate actively in this course.

Participation in an introductory course and univariate course on data analysis is mandatory.

A theoretical exam will be written. Details will be provided in the course materials.