Courses Details

BIOSTAT594: Applied Generalized Linear Models

  • Graduate level
  • Both Online MPH and Online MS
  • This is a first year course for Online students
  • Fall term(s) term for online MPH students; Fall term(s) term for online MS students.
  • 3 Credit Hour(s) for online MPH students for residential students; 3 Credit Hour(s) for online MS students
  • Instructor(s): Wu, Zhenke (Online MPH); Wu, Zhenke (Online MS);
  • Prerequisites: BIOSTAT501, BIOSTAT591, BIOSTAT592
  • Description: This course introduces public health Master's students to generalized linear models to analyze binary, discrete, ordinal, count, survival outcomes.The primary emphasis will be interpretation, inference and hands-on data analyses. We will use R to analyze public health datasets, evaluate regression assumptions, and assess model fit.
  • Learning Objectives: 1. Understand the context where non-continuous outcome data are generated, identify the most relevant aspects of these data that require modeling and formulate a scientific question in terms of one or a few model parameters 2. To develop the ability to use R to analyze public health data using GLM 3. Interpret results of data analysis for public health research, policy or practice
  • This course is cross-listed with .