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140.663.01
Spatial Analysis and Gis II

Location
East Baltimore
Term
4th Term
Department
Biostatistics
Credit(s)
4
Academic Year
2013 - 2014
Instruction Method
TBD
Class Time(s)
Tu, Th, 1:30 - 2:50pm
Lab Times
Wednesday, 4:30 - 5:20pm (01)
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frank Curriero
Contact Email
Frequency Schedule
Every Year
Prerequisite

140.621.-624 or 140.651-.654

Description
Introduces statistical techniques used to model, analyze, and interpret public health related spatial data. Analysis of spatially dependent data is cast into a general framework based on regression methodology. Topics covered include the geostatistical techniques of kriging and variogram analysis and point process methods for spatial case control and area-level analysis. Although the focus is on statistical modeling, students will also cover topics related to clustering and cluster detection of disease events. Although helpful, knowledge of specific GIS software is not required. Instruction in the public domain statistical package R, (to be used for analysis), is provided.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. describe the concept of spatial dependence and apply techniques to quantify it with different types of spatial data
  2. conduct routine spatial statistical analysis using extended regression techniques within the R Statistical Computing Environment software
  3. identify the potential consequences of overlooking spatial information when conducting certain types of public health research
Special Comments

The course schedule includes 2 lecture periods and one lab per week. The lab hour is devoted mostly to computing for the assigned problem sets.