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 for the introduction videos and exercises, and another week for working on an assignment.
Aim:
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.
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 (cfd@ecos.au.dk).
Senior researcher Peter B. Sørensen (pbs@ecos.au.dk).
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
Exercises
To train yourself in applied statistics, a series of exercises, which cover the topics of the lectures may be completed.
The N Model exercise for week 2
