Tu Thur 10:30-11:45, BRNG B261

Spring 2008

This course covers a wide range of statistical models and methods for data that are collected at different spatial locations and perhaps at different times. These data are called spatial or spatio-temporal data, which arise in many scientific disciplines such as agronomy, plant pathology, forestry and natural resources, environmental and health studies, climatology, geology, biosecurity, etc. Spatial statistics is currently one of the most active research areas in statistics and there has been tremendous advancement in methodological and computational research in spatial statistics that enables us to analyze massive spatial data today. This course will introduce the classical methods as well as some newly developed ones, and will provide ample hands-on activities. The programming language R and a few packages for analyzing spatial data will be introduced. One objective is for students to be able to identify appropriate methods and analyze spatial data in their research.

• Course Description


• Lecture notes (This folder is password protected)


• Data


• Homework


• Project


• Reference books This list is meant to help you identify a book that is most helpful to you based your particular research problems and background. Lecture notes are regularly provided and are available in the password protected folder.