Spatial Regression and Local Indicators of Spatial Autocorrelation (LISA) in R

Much social and economic data - and some environmental data - are aggregated in geographic zones. Analysts frequently want to understand the underlying properties of individual variables and to explore and model relationships between different variables, in these data. This workshop covers some basic theory as well as practice of spatial data analysis on

this kind of data. Foundational concepts include spatial data models, the modifiable areal unit problem (MAUP), spatial autocorrelation, spatial heterogeneity, LISA statistics, and spatial (auto)regression modeling. Intermediate ability with R and multivariate statistics is a prerequisite.

CSTAT workshops are free to the MSU community. If you are unable to attend after registration, please give at least a 48 hour notice or you will incur a $50 cancellation fee.