As a consequence of the development within computer science, involving huge data amounts and steadily growing computers, there has been an increasing need for methods within data analysis. In connection with data collection, analysis and development of models, it is important to have statistical methods and principles in order to find and make use of the development. Statistics counts as an own subject within mathematics and is applied to a couple of other subjects like medicine, bioinformatics, natural and human science. Real problems from other subjects provide important impulses for development of new statistical methods.

Methods for automatic cell change
alert in moles (føflekker). K. Møllersen



The statistics group collaborates with both  Norwegian and international partners. Among its most important collaborators are the National Centre for Telemedicine, and the UiT Machine Learning Group ( The Research Group  currently does research within the following fields:

  • Analysis of time series and  scale-space models, with applications to ecology and  climate research.


  • Development of robust algorithms to keep the blood sugar level inside specified margins for  persons  with Type 1 diabetes.


  • Development of efficient computational Bayesian methods, especially methodology associated to  INLA  (Integrated nested Laplace approximations).


  • Extract information from Electronic patient journals.


  • Cross-disciplinary Projects


  • Image analysis, e.g. in analysis of malignant mole cancer at an early stage.


  • Community medicine

See also master studies in statistics.
Skip to main content