Spatial data is becoming increasingly available in a wide range of disciplines, including social sciences such as political science and criminology, as well as sciences such as geosciences and ecology. This course will introduce methods for exploring and analyzing spatial data. We will cover methods to describe and analyze three main types of spatial data: areal, point process, and point-referenced (geostatistical) data. We will also introduce tools for working with spatial data in R.

Units: 1

Max Enrollment: 24

Prerequisites: Any introductory statistics course (BISC 198, ECON 103/SOC 190, STAT 160, STAT 218, POL 299) or permission of instructor.

Instructor: Kelling

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Typical Periods Offered: Spring

Semesters Offered this Academic Year: Not Offered

Notes: