GEOG 4810 - Quantitative Methods for Spatial Analysis

Course provides the necessary spatial tools that characterize geographers in the management and application of spatial data in order to analyze spatial problems.  Open to Juniors and Seniors Only.

Prerequisites: MATH 1600, 1601/1602, 1610, 1620, or consent of instructor.

Hours: (Lecture, 2 hours; Laboratory, 2 hours)

Course Learning Outcomes List

Students will be able to:

1. Describe the concept of spatial heterogeneity (Geography PLO#4);
2. Explain the concept of and identify spatial autocorrelation. (Geography PLO#1);
3. Recognize the concepts of heteroscedasticity and homoscedasticity (Geography PLO#1 and #4);
4. Explain the principles of ordinary least square regression (OLS) and the advantage of spatial regression (Geography PLO#1 and Geography PLO#4);
5. Apply ordinary least squares (OLS) and spatial regression, including geographically weighted regression (GWR), and understand how differs from OLS (Geography PLO#1 and Geography PLO#4); 
6. Analyze spatial statistic output data (Geography PLO#4); and,
7. Assess spatial data analysis for their own research and interpret spatial analysis results (Geography PLO#1 and #4).

Schedule of Classes | University Bookstore