Spatial statistics in GIS

The course prepares students for the processing and analysis of spatial data statistics to investigate spatial patterns. The course covers spatial data analyses in spatial statistics, intensity functions, K functions, cluster statistics, spatial interpolation, functions of spatial covariation, variogram, kriging, regression analysis, and hot-spot models. Software exercises provide students with the opportunity to perform statistical spatial analyses in order to understand the theory. Students work on a project individually or in groups. A number of individual hand-in assignments are used for discussion and problem-solving exercises in groups of students. Scientific articles are presented and discussed in groups, followed by feedback. In their projects, students develop their own research study based on problem-solving through spatial statistical methods. Research problems for the projects are chosen in consultation with the teacher. Projects are presented both orally and in a scientific report/paper including an abstract, a background section, an introduction, a section on method, results, and discussion. Projects are assessed based on the chosen method, the written and oral presentations, and the analysis and visualisation of results.