This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: Spatial Statistics Course Syllabus Course : PM 599 Room : SSB 301 Time : Mondays 1-4pm, Spring 2012 Instructor : Meredith Franklin Office Hours : By appointment Office Location : SSB 202A (Keck) AHF B57E (College) Email : [email protected] Course Scope and Purpose This course is intended as an introduction to spatial statistics, and aims to provide students with the background necessary to investigate geographically represented data. There are a large number of problems involving spatial data, but focus will be placed on methods that are relevant in the fields of public health, environmental science and social science. Lectures will cover the three main areas of spatial statistics: geostatistical data, lattice (areal) data and point patterns. Learning Outcomes Upon completion of this course, students should be able to: • Distinguish different types of spatial data (geostatistical, areal, point process) and understand how spatial autocorrelation plays a role in statistical modeling. • Use existing methods to investigate spatial autocorrelation in example datasets provided as exercises. • Determine which spatial methods to use to in their own research and implement them using statistical software and GIS. • Read and discuss new methods in the spatial statistics literature based on an understanding of the basic spatial statistics approaches, principles and main assumptions. Course Requirements Prerequisites Students should have a background in statistics at the level of regression as well as in statistical computing. The course will involve a great deal of computing, primarily in R....
View Full Document
This note was uploaded on 02/14/2012 for the course PM 599 taught by Professor Staff during the Spring '08 term at USC.
- Spring '08