This course provides a comprehensive foundation in regression analysis and generalized linear models for statistical modeling and inference. It covers simple and multiple linear regression, model diagnostics, and remedial measures, along with binary response models such as logit and probit. The course further introduces generalized linear models for count and categorical data, including Poisson and logistic regression. Advanced topics such as ridge regression, robust regression, survival models, bootstrapping, and Bayesian methods are also discussed. Emphasis is placed on both theoretical understanding and practical applications in statistical modelling.
- BCM Teacher: Albi Elizabeth Abraham