BIOSTAT651: Theory and Application of Generalized Linear Models
- Graduate level
- Winter term(s) for residential students;
- 3 credit hour(s) for residential students;
- Instructor(s): Veera Baladandayuthapani, Kevin (Zhi) He, (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.
|Department||Program||Degree||Competency||Specific course(s) that allow assessment||BIOSTAT||MS||Perform generalized linear regression model fitting and diagnosis||BIOSTAT651||BIOSTAT||PhD||Perform generalized linear regression model fitting and diagnosis||BIOSTAT651|