Spatial Data and Analysis

4 credits · Graduate

This course introduces students to spatial data and its analysis, modeling of spatially dependent processes, and related policy problems. Through hands-on analysis, students will learn to extract quantitative information from spatial data for applied research and public policy. Students will be introduced to spatial statistics, spatially dependent simulation, and spatial optimization. Students will learn to think creatively about spatial problems through examples drawn from economics, politics, epidemiology, criminology, agriculture, social networks, and the environment. Students will benefit from prior experience with basic computer programming, although prior experience is not required.