This applied statistics course is a successor of STAT 34300 Applied Linear Statistical Methods and covers the foundations of generalized linear models (GLM). We aim to cover the following topics:

  • GLM model estimation, computation and inference
  • Specific GLM models for binary, multinomial and count data
  • Linear and generalized linear mixed effect models
  • Survival analysis

This course will make a balance between practical real data analysis with examples and a deeper understanding of the models with mathematical derivations.



  • Homework assignments: 25%
    • There will be 5 assignments in total.
    • Late homework will not be accepted for grading (medical emergencies excepted with proof).
    • Homework will be submitted through Canvas and is due at 11:59pm the due date.
  • Midterm: 35%
  • Final exam: 40%