GIS5935 Lab 12: Spatial Regression in ArcGIS

Spatial regression using tools in ArcGIS was the topic for this week. The two tools used were Ordinary Least Squares and Geographically weighted regression. The second part of the lab consisted of carrying out a regression analysis using both tools and comparing the results. Two shapefiles were used as the data for this, one consisting of the locations of all crimes reported for a specific county in one year, and the other consisting census tracts for the county with different demographic variables. From there, one crime was selected on which to perform the analysis, then 3 variables were also selected. Then the crime rate for each census tract was determined to be used at the dependent variable

First, the OLS tool was ran on the selected variables. Then the GWR tool was ran on the same variables. For the GWR, I tried using both adaptive and fixed kernel types, then ran the Global Moran's I tool on both results to see which one resulted in a better performing model. Using the adaptive kernel type seemed to work better. From there I read through the statistics of all of the results to compare and see how the model improved.

The GWR improved on the OLS a good bit. The adjusted R-squared improved from about 35% with the OLS to about 40% with the GWR. The AIC was also lowered from 1916 to 1909.