Advanced data analysis with R

Undergraduate course

Course description

Objectives and Content

This course will present advanced methodology in data analysis, with a particular focus on the theory and use of generalized linear mixed models. Furthermore, the focus will be on practical use of R and especially on the package "glmmTMB".

Learning Outcomes

On completion of the course the student should have the following learning outcomes


  • Knows the theory behind generalized linear mixed models


  • can implement statistical models in R
  • use generalized linear mixed models on real data sets in R using glmmTMB

General competence

  • have an overview of how advanced statistical methods can be used to analyze larger data sets
Required Previous Knowledge
STAT110 or similar
Recommended Previous Knowledge
Advantage with STAT111 or STAT200 or similar.
Credit Reduction due to Course Overlap
Advantage with STAT111 or STAT200 or similar.
Teaching and learning methods

Digital lectures and/or videos approx. 2 hours pr. week

Computer Lab / approx. 2 hours a week for 9 weeks

Compulsory Assignments and Attendance
Approved mandatory hand-ins.
Forms of Assessment
Digital home exam of 3 days duration
Grading Scale
Examination Support Material