B2/ETX3b Tools for multivariate data analysis - Einzelansicht

 See module hand book and course schedule 

This course is the continuation of the Tools for univariate data analysis at the same time for the first half of the semester, and represents a crucial requisite.

The course takes place in room CIII 140 PC room IV

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.

Three short theoretical exams and one practical exam will be written. Details will be provided in the examination notes distributed with the course materials.

See https://github.com/rbslandau/Data_analysis