140.663.01 SPATIAL ANALYSIS AND GIS II

Introduces statistical techniques used to model, analyze, and interpret public health related spatial data. Analysis of spatially dependent data is cast into a general framework based on regression methodology. Topics covered include the geostatistical techniques of kriging and variogram analysis and point process methods for spatial case control and area-level analysis. Although the focus is on statistical modeling, students will also cover topics related to clustering and cluster detection of disease events. Although helpful, knowledge of specific GIS software is not required. Instruction in the public domain statistical package R, (to be used for analysis), is provided.

Upon completion of this course students will be able to: 1) identify with the concept of spatial dependence and apply techniques to quantify it with different types of spatial data; 2) conduct routine spatial statistical analysis using extended regression techniques within the R Statistical Computing Environment software; 3) identify the potential consequences of overlooking spatial information when conducting certain types of public health research.