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Spatial Statistics
Räumliche Statistik
Last Updated: 2026-02-05 15:23:46
Abstract
In many research fields, spatially referenced data are collected. When analysing such data the focus is either on exploring their structure (dependence on explanatory variables, autocorrelation) and/or on spatial prediction. The course provides an introduction to geostatistical methods that are useful for such purposes.
Objective
The course will provide an overview of the basic concepts and stochastic models that are commonly used to model spatial data. In addition, the participants will learn a number of geostatistical techniques and acquire some familiarity with software that is useful for analysing spatial data.
Content
After an introductory discussion of the types of problems and the kind of data that arise in environmental research, an introduction into linear geostatistics (models: stationary and intrinsic random processes, modelling large-scale spatial patterns by regression, modelling autocorrelation by variogram; kriging: mean-square prediction of spatial data) will be taught. The lectures will be complemented by data analyses that the participants have to do themselves.
Resources
Lecture Notes
Lecture notes, descriptions of the problems for the data analyses and work-out solutions to them will be provided.
Literature
Cressie, N.A.C. 1993. Statistics for Spatial Data. Wiley.
General Information
- Language
- German
- Levels
- MSC
- Frequency
- Every two years
Examination
- Type
- ungraded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Räumliche Statistik
Blockkurs am 24.11., 1.12., 8.12.
|
No time listed | 10 h semesterly |