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This chapter continues on from Chapter 9, extending the regression framework to include multiple predictor variables explaining the response variable. It discusses various model specifications, including for when the response variable is measured on a logarithmic scale or when it measures a binary (yes/no) outcome. It looks at the use of mean-centring and standardising the X variables to aid interpretation of the model.

Throughout the chapter, a focus is on taking a geographical approach to regression. Regression can be understood as trying to explain the patterns and differences we find in a map of geographical data. Although there is not necessarily a problem in using regression with geographical data, a complicating factor may arise when the geographical ...