This 5-session (2 hours each session), 1 credit, course will survey topics on the statistical analysis of data collected in space, with application to public health. Topics include defining geostatistical, areal and point processes, visualizing spatial data, spatial covariance functions, prediction and kriging, conditional autoregressive models, intensity functions, and K functions. Through In-class labs, students will learn to analyze spatial data in practice. Using what they have learned in the course, students will write a group report about a spatial data analysis.