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This lecture introduces Geographically Weighted Regression (GWR), a spatially explicit approach to measure the relationship between variables, locally considering the value of an explanatory factor. GWR employs a spatial weighting function assuming that nearby places are more similar. The residuals produced by GWR are generally lower than those of ordinary linear regression, and the outputs are location-specific, suitable for mapping and further analysis.