Courses Details

EHS675 Data Analysis for Environmental Epidemiology

  • Graduate level
  • Winter term(s)
  • 2 Credit Hour(s)
  • Instructor(s): Park, Sung Kyun
  • Prerequisites: BIOSTAT 560 and EPID 503 or 600
  • Description: This course will introduce non-parametric smoothing methods, such as splines, locally weighted polynomial regression (LOESS) and generalized additive models (GAM), and focus on continuous environmental exposure variables. It will also deal with analysis of correlated data, including longitudinal analysis and time-series analysis that are widely used in environmental epidemiology. It will provide an opportunity to analyze actual population data to learn how to model environmental epidemiologic data, and is designed particularly for students who pursue environmental epidemiologic research. The course will consist of lectures and hands-on practices in computer labs, homework assignments and final projects. R, a free software environment for statistical computing and graphics, will be used.
  • Syllabus for EHS675