Lauren Rosenshein
Regression analysis is a set of statistical methods used in many application areas (e.g., defense, education, health and human services, natural resources, and public safety). Ordinary least squares (OLS) regression and geographically weighted regression (GWR) allow you to examine, model, and explore data relationships. Ultimately, regression analysis helps you answer questions like, Why do we see so much disease in particular areas? What are the factors that contribute to consistently high fitness rates? and, Why are screening rates so low in particular regions of the country? Regression analysis also allows you to predict spatial outcomes for other places or other time periods, for instance, how improvements to road conditions would impact traffic fatalities and how projected population growth would affect the demand for health services. In this workshop, we will cover basic regression analysis concepts and workflows as they relate to the analysis of geographic data. You will learn how to build a properly specified OLS regression model, interpret regression results and diagnostics, and potentially use the results of regression analysis to design targeted interventions.