ST533 - Applied Spatial Statistics
- Prerequisites: ST 512 or ST 514 or ST 515 or ST 516 or ST 517
- Term & Frequency: Spring
- Student Audience: Masters students in Statistics and graduate students in all fields
- Credit: 3 credits
- Recent Texts: Introduction to Geostatistics - P.K. Kitanidis
- Recent Instructors: Joe Guinness
- Background and Goals: This course is the applied spatial statistics course that used to be numbered ST 733. This course is for Statistics Masters students and also students outside statistics who see spatially correlated data in their research.
- Content: Introduction to statistical models and methods for analyzing various types of spatially referenced data. The focus is on applications with real data and their analysis with statistical programs such as R and SAS. Students will learn how to estimate spatial models and use them to interpolate geostatistical data (Kriging), perform spatial regressions, and make inferences about clustering in point pattern data. Students are required to write, modify, and run computer code in order to complete homework assignments and final projects.
- Alternatives: None
- Subsequent Courses: None
S1 2017 Sections:
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