Spatial Statistics & Modeling

The Spatial Statistics & Modeling class will build from the outcomes of the Bayesian Statistics course and provide students with the ability to accurately describe and model spatial data. This course will utilize a combination of lectures and experiential work. In the statistics section of this course, topics of basic and Bayesian Statistics will be reviewed before introducing them in a spatial setting. Global statistics, local functions and density analysis will be covered before moving on to correlation, linear regression, geographically weighted regression, and spatial regressions. As a part of the modeling section of this course, students will learn how to make programs to model these regressions based on real world data. The prerequisite for this course is DS 330.