Theoretical Statistics (TeoStat)

Course content

The course presents basic concepts and principles underlying statistical inference.  Main topics include decision-theoretic foundations, the maximum likelihood principle, and optimality properties.  The concepts are developed in the context of exponential families and selected nonparametric settings.

 

Education

MSc Programme in Statistics

Learning outcome

Knowledge:

  Statistical concepts covered in the course, such as:

  • Maximum likelihood principle
  • Sufficiency, completeness
  • Bayes and minimax principle
  • Parametric versus nonparametric problems


Skills: 

  • Understand how general principles guide development of statistical
    methods
  • Ability to apply the covered principles to investigate concrete statistical methodology


Competences:

  • Theoretical analysis and evaluation of statistical methods
  • Developing new statistical methodology

Four hours of lectures and three hours of exercises per week for 7 weeks.

Selected book chapters and articles from the literature.

 

Measures and Integrals + Mathematical Statistics or similar.

Academic qualifications equivalent to a BSc degree is recommended.

Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Oral examination, 25 minutes
There will be a 30min preparation time before the oral exam.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Single subject courses (day)

  • Category
  • Hours
  • Exam
  • 35
  • Preparation
  • 122
  • Lectures
  • 28
  • Theory exercises
  • 21
  • English
  • 206