Introduction to statistics

Online course: Introduction to statistics and General Linear Models

This is an introductory course, where participants will learn about basic statistical concepts. The course builds on General Linear Models (GLM), in order to investigate data using classical statistical tests (e.g. t-test, ANOVA, ANCOVA, linear and multiple regression). The methods of statistical analysis are explained and exemplified through a series of video lectures. As videos are pre-recorded, participants can take the course at a time of their convenience. The work load of the course is approx. one week fulltime. 


The aim is to give the participants an overview of and practical experience in the use of standard parametric methods of statistical analysis in order to make statistics an active tool. This basic statistical training will also serve as a basis for a more advanced statistical training course on hierarchical model building, which will take place at UG as part of the C2RCD project.  

Learning goals:

After this introductory course, the participant is expected to be able to:
• Identify suitable methods of statistical analysis for different types of data.
• Apply standard methods of statistical analysis to continuous data.
• Analyze and solve real problems in relation to sampling and analysis of data.
• Explain and critically assess statistical results.

Text book (optional but very relevant)

Grafen and Hails (2002) Modern statistics for the life sciences, Oxford University Press.

Course coordinators

Prof. Christian F. Damgaard (
Senior researcher Peter B. Sørensen (

Welcome to the course

Course materials

Lectures slides

The slides used as a basis for all the videos that you will find below, and some relevant literature, can be downloaded as a single zip file here: lecture slides


To train yourself in applied statistics, a series of exercises, which cover the topics of the lectures may be completed.

  • You can download the exercise descriptions here: exercise document
  • You can download data needed for all the exercises as a single zip file here: data

Video lectures and exercises

Basic concepts in handling normal distributed stochastic variables

Basic concept of ANOVA analysis


Basic concept of regression

How to assess uncertainty of regression results

Unifying ANOVA analysis and regression in General Linear Models (GLM)

Expanding GLM to multiple explanatory variables

Basic concept in experimental design

Expanding GLM to mix continues and categorical variables

Expanding GLM to include interactions between explanatory variables

Repetition through the topics