Spatial Autocorrelation: Spatial Weighting

This lecture covers the concept of spatial autocorrelation, focusing on global spatial autocorrelation and the use of spatial weighting schemes. It introduces Anselin's method of using Moran's I as a regression coefficient and discusses the analysis of spatial association using distance statistics. The lecture also explores the importance of examining spatial series for spatial correlation and autocorrelation, highlighting the potential errors in model interpretation due to neglecting spatial autocorrelation. Various spatial autocorrelation coefficients and statistics like Moran's I, Geary's C, and Getis-Ord's G are explained, along with methods for defining neighborhoods and creating weights files in Geographic Information Systems.