Provides an introduction to spatial data science in the form of an overview of applied methods of spatial data analysis illustrated by means of the open source GeoDa software and the PySAL Python library for spatial analysis. Topics will include geovisualization, exploratory data analysis, spatial autocorrelation and introductory spatial regression. The emphasis is not on mathematical detail, but on dealing with real data, gaining insight from analysis, interpreting and presenting the results. Students are assumed to have a laptop. The software is free and open source and can be installed on any operating system. Prerequisites include basic knowledge of GIS and multivariate statistics.
- First six weeks of the term