Topics in Statistical Sciences I


Content, progress and pedagogy of the module

Learning objectives


  • dynamical linear models, including the Kalman filter 
  • population methods, specifically evolutionary computing and genetic algorithms
  • meta analysis 
  • robust statistical methods including non-parametric models
  • factor analysis 
  • graphical models, including hierarchical models


  • can apply the relevant methodologies to one or more datasets by using appropriate software implementations, and interpret the output and modify the model parameters accordingly
  • are able to state the underlying assumptions and argue about limitations and extendibility of the methodology in one or more specific settings
  • can assess goodness-of-fit for the models where appropriate


  • can acquire supplementary knowledge about the relevant methodologies 
  • can combine appropriate topics from the course to analyse a specific dataset.
  • can in writing describe the methodologies, results and outcome from an analysis of a specific dataset

Type of instruction

Lectures with exercises.

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 150 hours for the student.



Name of examEmner inden for statistisk videnskab I
Type of exam
Written or oral exam
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleEmner inden for statistisk videnskab I
Module codeF-MAT-K1-5
Module typeCourse
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Study BoardStudy Board of Mathematics, Physics and Nanotechnology
DepartmentDepartment of Mathematical Sciences
FacultyFaculty of Engineering and Science