ST433 - Applied Spatial Statistics
- Prerequisites: ST 430 and ST 422
- Term & Frequency: Spring
- Student Audience: Undergraduate Statistics majors and minors. (In the same classroom as ST 533, but with some differences in grading)
- Credit: 3 credits
- Recent Texts: Introduction to Geostatistics - P.K. Kitanidis
- Recent Instructors: Joe Guinness
- Background and Goals: This course is in the same classroom as ST 533, but with some differences in grading.
- 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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