Gog 529 Spatial Statistics

This course provides an introduction to spatial statistics for spatially referenced data. Spatial point patterns, geostatistical data, and area (regional/lattice) data are studied using the viewpoint that these are realizations from random processes. Major topics to be covered include spatial stochastic process, exploratory spatial data analysis, intensity function, K function, cluster statistics, spatial interpolation, spatial covariance functions, variograms, kriging, spatial autoregressive models, and geographically weighted regression. Computer exercises with R programming language (www.r-project.org) are designed to help students gain hands-on experience on the topics presented in lectures. Students are required to present and discuss assigned readings and develop an individual research project that applies spatial statistical methods in geographical problem solving. Prerequisites: GOG502/PLN504 or equivalent. In other words, students should be familiar with basic probability theory, multiple linear regression, and basic linear algebra.