601.733.86
Applied Spatial Statistics
Location
Internet
Term
3rd Term
Department
MAS Office
Credit(s)
4
Academic Year
2022 - 2023
Instruction Method
Asynchronous Online
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
Public Health Statistics II (600.712.86), or equivalent; Spatial Analysis for Public Health (601.731.86)
Introduces statistical techniques used to model, analyze, and interpret public health related spatial data. Casts analysis of spatially dependent data into a general framework based on regression methodology. Covers the geostatistical techniques of kriging and variogram analysis, point process methods for spatial event and case control data, and area-level analysis. Focuses on statistical modeling and topics relating to clustering and cluster detection of health related events. Provides an introduction to the public domain statistical software R, to be used for analysis. Reinforces skills and concepts related to the spatial science paradigm: Spatial Data, GIS, and Spatial Statistics.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Define and describe the concepts of spatial dependence with a public health context
- Apply techniques to quantify spatial dependence with different types of spatial data
- Conduct spatial statistical analysis using regression techniques extended to address properties of spatial data
- Identify the potential consequences of overlooking spatial information when conducting public health research
Enrollment Restriction
Restricted to students enrolled in the Spatial Analysis for Public Health program