In this chapter, two linear regression tools were used to model the relationships between various demographic, socio-economic, and geographic factors and the incidence of burglary in Denver County, CO. Using the OLS tool, a combination of variables were identified as the best model for understanding burglary in this context. The model was then improved using the Geographically Weighted Regression tool, which introduced spatial variability into the model. Finally, the Exploratory Regression tool was used to quickly identify combinations of variables that best fit a model. In the next chapter, we'll examine a variety of data conversion tools found in the Utilities toolset. These tools are often used in conjunction with other tools found in the Spatial Statistics Tools toolbox.
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