140.663.01 | AY 2013-2014 - 4th Term | 4 Credit(s)
TTh 1:30:00 PM
  • Contact Information
    Frank Curriero
  • 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
  • Course 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 is provided.

    Additional Faculty Notes:

     There is a Welcome Message posted in the General Folder in the Online Library.  Please read this message first as it will describe and direct you to other material posted prior to class beginning on Tuesday March 25th.

  • Intended Audience


    Additional Faculty Notes:

    Anyone interested in spatial analysis tools for going beyond the map.

  • Methods of Assessment

    Method of student evaluation based on assignments and exam

    Additional Faculty Notes:

    Exam 1 will be a take home exam due Tuesday April 15th (15%).

    Exam 2 will be in class on Thursday May 15th (15%).  Format is in class group oral discussion.

    Grading is based on three problem sets (60%), two exams (30%), and three online quizzes (10%). 

  • Prerequisites

    140.621.-624 (or commesurate) or 140.651-.654

  • Required Text(s)

    Additional Faculty Notes:  See posted syllabus

  • Course Schedule

    Please see the course Session for a full list of dates and items for this course.

  • Academic Ethics Code

    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 the Office of Student Life Services at 410-955-3034 or via email at