TILS600 Spatial Data Analysis (5 cr)
Description
This course serves as an introduction to spatial data analysis, encompassing diverse aspects of spatial information handling and interpretation.
Core concepts of spatial data, spatial models, and their relevance to research inquiries will be discussed. We also explore the merits and possible complexities linked to spatial dependence.
Students will be introduced to an array of statistical tools and models tailored for different types of spatial data. Moreover, the course equips participants with practical skills in employing R for the analysis of spatial data.
Learning outcomes
Upon successfully completing the course, students will:
- understand the unique characteristics of spatial data, particularly spatial dependence,
- acquire knowledge about a wide range of spatial models and be able to apply them to real data,
- master basic concepts and tools of spatial interpolation and geostatistics such as random fields, variogram and kriging.
Description of prerequisites
Statistical Inference 1 & 2
Generalized Linear Models 1
Basic knowledge of R
Beneficial prerequisites include Time Series Analysis or Stochastic Models