NMAA13025U Theoretical Statictics (TeoStat)

Volume 2013/2014
Education
MSc programme in Statistics
MSc programme in Mathematics-Economics
Content
The course presents the basic concepts and principles underlying statistical methodology. The focus is on general inference principles, including the Bayesian approach. Main topics are the theory of hypothesis testing as well as the concepts of sufficiency and ancillarity that express that a part of the data contains all or no information about the statistical parameters. Statistical theory is developed for exponential families, a model type that contains many models used in statistical practice. The students will develop statistical theory and use the methods of the course to analyse statistical models and procedures.
Learning Outcome
Knowledge: The course covers the following topics. Exponential families, sufficiency, ancillarity, principles of statistical inference, Bayes statistics, theory of hypothes testing.

Skills: After the course, the students are expected to be able to apply the general inference principles and concepts to investigate concrete statistical methodology; to apply the general inference principles and concepts to develop methods for new models; to determine whether a model is an exponential family; to apply the theory of exponential families to concrete models.

Competences: After the course, the students are expected to be able to theoretically analyse and evaluate statistical methods and to develop new statistical methodology.
Sand 1, Stat 1, Stat 2.
5 hours lectures and 3 hours of exercises per week for 7 weeks.
  • Category
  • Hours
  • Exam
  • 35
  • Lectures
  • 35
  • Preparation
  • 115
  • Theory exercises
  • 21
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
with preparation time
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assesment

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