lök100 - Data Modelling (Complete module description)

lök100 - Data Modelling (Complete module description)

Original version English PDF Download
Module label Data Modelling
Modulkürzel lök100
Credit points 9.0 KP
Workload 270 h
Institute directory Institute for Biology and Environmental Sciences
Verwendbarkeit des Moduls
  • Master's Programme Landscape Ecology (Master) > Wahlpflichtmodule
Zuständige Personen
  • Peppler-Lisbach, Cord (module responsibility)
  • Peppler-Lisbach, Cord (Module counselling)
  • Peppler-Lisbach, Cord (Prüfungsberechtigt)
  • Greskowiak, Janek (Prüfungsberechtigt)
Skills to be acquired in this module
  • Basic methods of explorative statistics and adequate application of statistical tests relevant to ecological data.

  • To learn, interpret and apply methods of habitat modelling
  • To understand the fundamentals of spatial explicit analysis of species-environment relationships as well as the fundamentals of spatial prediction of environmental requirements in species
  • To adequately analyse measured and observed spatial data applying methods of spatial statistics and geostatistics, respectively

  • To learn and to understand relevant methods of multivariate analysis of vegetation data
  • To be able to interpret and to assess the results obtained as well as the relevant literature
  • To be able to apply the treated methods independently
  • To learn and to improve skills in using the statistics software R
Module contents
Part 1: Introduction to statistical analysis of ecological data NN (NN)
  • Experimental design
  • Explorative data analysis
  • Distribution tests, data transformation
  • Chi² test
  • Anova, Kruskal-Wallis test
  • t & U test
  • Multiple comparisons, post-hoc tests

Part 2: Habitat modelling and spatial statistics (Biedermann)
  • Linear (OLS) regression
  • GLM (logistic regression, Poisson regression)
  • Spatial explicit modelling, GIS integration
  • Spatial statistics

Part 3: Multivariate analysis of vegetation ecological data (Peppler-Lisbach)
  • Cluster analysis
  • Statistical degrees of fidelity
  • Indirect procedures: PCA, CA, DCA
  • Canonical procedures: RDA, CCA
Crawley, M.J. (2007): The R Book. 942 S. Wiley & Sons, Chichester.
Additional literature will be announced during the course.
Language of instruction German
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Type of module Wahlpflicht / Elective
Module level MM (Mastermodul / Master module)
Teaching/Learning method Ü
Examination Prüfungszeiten Type of examination
Final exam of module
Before the end of the course
Lehrveranstaltungsform Exercises
Frequency WiSe