Generalised linear models

Topics

Somewhat morbidly the examples in this course revolve around life and death.

• How many mice will die of poisoning? Fitting dose-response curves with a binomial GLM
• How many people will die of old age? Mortality rates and the Poisson GLM
• The Ebola epidemic: Quasi-Poisson and negative binomial GLM
• Back to the roots: Ordinary Least Squares (OLS) regression as a special case of GLM

Out of scope

This course will not teach you bioinformatics.
In particular, no high-throughput sequencing data will be used because they are impractically large,
and not everyone on campus is working with sequencing.

Prerequisites

• Mandatory: Good understanding of basic statistics concepts.
  If you have attended our Think Statistics with R course,
  then you are all set.
• Recommended:
  • Familiarity with linear regression. Our Linear Regression
    course gives you a solid overview.
  • Basic familiarity with R. Our R as a programming language course
    provides you with the necessary knowledge.

Practical information

Number of participants: minimum 5, maximum 10.

Length: The course takes one half-day,
from 09:00 to 13:00 with 2 breaks.