ADVANCED DATA ANALYSIS WORKSHOP Syllabus

140.620.11 | AY 2013-2014 - Summer Inst. Term | 2 Credit(s)
MTWThF 1:30:00 PM
  • Contact Information
    Faculty
    Patrick Tarwater
  • Course Learning Objectives

    Upon successfully completing this course, students will be able to:

    • Conduct a simple linear, logistic or survival regression and correctly interpret the regression coefficients and their confidence interval
    • Conduct a multiple linear, logistic or survival regression and correctly interpret the coefficients and their confidence intervals
    • Examine residuals and adjusted variable plots for inconsistencies between the regression model and patterns in the data and for outliers and high leverage observations
    • Fit and compare different models to explore the association between outcome and predictor variables in an observational study.
  • Course Description
    Covers methods for the organization, management, exploration, and statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models. Students apply these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Topics covered include generalized linear models, product-limit (Kaplan-Meier) estimation, Cox proportional hazards model.
  • Intended Audience
    JHSPH students and Summer Institute participants
  • Methods of Assessment
    quizzes and final exam
  • Prerequisites
    Data Analysis Workshop I and II (140.613 and 140.614)
  • 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 dss@jhsph.edu.