Courses Details

BIOSTAT651: Theory and Application of Generalized Linear Models

  • Graduate level
  • Residential
  • Winter term(s) for residential students;
  • 3 credit hour(s) for residential students;
  • Instructor(s): Menggang Yu (Residential);
  • Prerequisites: BIOSTAT601 and BIOSTAT650
  • Description: Introduction to maximum likelihood estimation; exponential family; proportion, count and rate data; generalized linear models; link function; logistic and Poisson regression; estimation; inference; deviance; diagnosis. The course will include application to real data.
  • Syllabus for BIOSTAT651
YuMenggang
Menggang Yu
Concentration Competencies that BIOSTAT651 Allows Assessment On
Department Program Degree Competency Specific course(s) that allow assessment
BIOSTAT MS Understand the main components of generalized linear models and how to choose an appropriate model based on the outcomes and study design BIOSTAT651
BIOSTAT MS Fit generalized linear models for various outcome types and provide correct interpretation of the results BIOSTAT651
BIOSTAT Health Data Science MS Understand the main components of generalized linear models and how to choose an appropriate model based on the outcomes and study design BIOSTAT651
BIOSTAT Health Data Science MS Fit generalized linear models for various outcome types and provide correct interpretation of the results BIOSTAT651