Introduction to Spatial Data Science
Course Code
SOCI 20253 91
Cross Listed Course Code(s)
CEGU 20253, ENST 20253, GISC 20500, GISC 30500, MACS 54000, SOCI 30253
Course Description
The course reviews a range of methods to explore spatial data relevant in social science inquiry. 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). 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. You will learn and apply open source geospatial software tools, specifically GeoDa, developed at the Center for Spatial Data Science at UChicago.
Course Criteria
This course is open to all undergraduates and is included in the Summer Institute in Social Research Methods. It is not open to high school students.
Instructor(s)
Pedro Amaral
UChicago Registration 1