Introduction to Spatial Data Science

*Taught Online*  Spatial data science is an evolving field that can be thought of as a collection of concepts and methods drawn from both statistics/spatial statistics and computer science/geocomputation. These techniques deal with accessing, transforming, manipulating, visualizing, exploring and reasoning about data where the locational component is important (spatial data). The course reviews a range of methods to explore spatial data relevant in social science inquiry. We will primarily focus on data gathered for aggregate units, such as census tracts or counties (e.g., unemployment rates, disease rates by area, crime rates). Specific topics covered include the special nature of spatial data, geovisualization and visual analytics, spatial autocorrelation analysis, and local cluster detection. An important aspect of the course is to learn and apply open source geospatial software tools, specifically GeoDa, developed at the Center for Spatial Data Science at UChicago.