Stud.IP Uni Oldenburg
University of Oldenburg
23.09.2019 01:03:30
lök100 - Data Modelling
Institute for Biology and Environmental Sciences 9 KP
Semester courses Wintersemester 2019/2020
Course type: Exercises
  • 5.02.002 - headache
    • Robert Hentschke, Dipl.-Ing.
    • Dipl.-Ing. Christian Renken

    Dates on Thursday. 10.10.19 13:15 - 14:00, Friday. 11.10.19 11:00 - 11:45
  • 5.03.101 - headache
    • Dr. Janek Greskowiak

    Dates on Monday. 14.10.19 - Tuesday. 15.10.19 14:15 - 17:30, Wednesday. 16.10.19 08:15 - 11:30, Monday. 21.10.19 - Tuesday. 22.10.19 14:15 - 17:30, Wednesday. 23.10.19 08:15 - 11:30, Monday. 28.10.19 14:15 - 17:30, Room: W32 1-112, W16A 004
  • 5.03.102 - headache
    • Dr. Cord Peppler-Lisbach

    Dates on Tuesday. 29.10.19 14:15 - 17:30, Wednesday. 30.10.19 08:15 - 11:30, Monday. 04.11.19 - Tuesday. 05.11.19 14:15 - 17:30, Wednesday. 06.11.19 08:15 - 11:30, Monday. 11.11.19 - Tuesday. 12.11.19 14:15 - 17:30, Room: W16A 004, W32 1-112
  • 5.03.103 - headache
    • Dr. Cord Peppler-Lisbach

    Dates on Wednesday. 13.11.19 08:15 - 11:30, Monday. 18.11.19 - Tuesday. 19.11.19 14:15 - 17:30, Wednesday. 20.11.19 08:15 - 11:30, Monday. 25.11.19 - Tuesday. 26.11.19 14:15 - 17:30, Wednesday. 27.11.19 08:15 - 11:30, Room: W16A 004, W32 1-112
Hinweise zum Modul
Prüfungszeiten
Before the end of the course
Module examination
Assignment
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

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