Courses Taught by Kevin (Zhi) He

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): Baladandayuthapani, Veera He, Kevin (Zhi) (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
Concentration Competencies that BIOSTAT651 Allows Assessment On
Department Program Degree Competency Specific course(s) that allow assessment
BIOSTAT MPH Perform generalized linear regression model fitting and diagnosis BIOSTAT651
BIOSTAT MS Perform generalized linear regression model fitting and diagnosis BIOSTAT651
BIOSTAT PhD Perform generalized linear regression model fitting and diagnosis BIOSTAT651

EPID742: Generalized Linear Models

  • Graduate level
  • Residential
  • Summer term(s) for residential students;
  • 1 credit hour(s) for residential students;
  • Instructor(s): He, Kevin (Zhi) (Residential);
  • Prerequisites: None
  • Advisory Prerequisites: Introductory level courses in epidemiology and biostatistics.
  • Description: Course will cover regression methods for continuous, binary, and count data. The majority of epidemiologic data involve either binary or count data, and binary data often arise from underlying continuous data. Therefore, linear , logistic ,and Poisson regression analyses are important analytic approaches that provide valuable insights into data collected.