SPATIAL ANALYSIS AND GIS II Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- describe the concept of spatial dependence and apply techniques to quantify it with different types of spatial data
- conduct routine spatial statistical analysis using extended regression techniques within the R Statistical Computing Environment software
- identify the potential consequences of overlooking spatial information when conducting certain types of public health research
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.
Epi, MMI, EHS, Biostat, PhD & ScM students.
Methods of Assessment
Grading Policy: Method of student evaluation based on assignments and exam
Grading Restrictions: Letter grade
140.621.-624 or 140.651-.654
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support Services
If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: email@example.com, 410-955-3034, or 2017 E. Monument Street.