# Generalised linear models

In our experiments we often count how many times something happened: how many mice died,
how many people got infected by a pathogen etc. You need
"counting statistics" techniques to analyse these data.
This course teaches you one such technique, "generalised linear models" (GLMs).
**Please note that we cannot go into the specific data analysis problems of your particular project.**

**Instructor:** András Aszódi.

## 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.