ST817: Mathematical Statistics II

Study Board of Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N370006112, N370006102
Assessment: Second examiner: None, Second examiner: Internal
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master

STADS ID (UVA): N370006101
ECTS value: 5

Date of Approval: 27-10-2022

Duration: 1 semester

Version: Approved - active


This course will be offered as a reading course in Spring 2024.

Entry requirements


Academic preconditions

Students taking the course are expected to know mathematical statistics equivalent to the content of the course ST521 Mathematical Statistics.

Course introduction

The aim of the course is to provide the student a further and advanced understanding of the theory and methods in mathematical statistics, which is important in regard to master the use of these for practical data analysis.

The course builds on the knowledge acquired in the course ST521
Mathematical statistics, and demonstrate advanced topics in mathematical statistics as such complements courses like e.g. computational statistics, multivariate analysis, linear models and probability theory, as well as for a possible master project in statistics

In relation to the competence profile of the degree it is the explicit focus of the course to:
  • Give the competence to master the theories and methods of mathematical statistics, as well as their application to statistical inference
  • Give skills to perform statistical analysis of data and critically argue for the choice between relevant models for analysis and solution
  • Give theoretical knowledge and practical understanding of the application of methods and models in mathematical statistics

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:
  • understand and identify problems that can be solved using multivariate techniques  
  • perform a practical data analysis with the techniques from the course  
  • perform programming relevant to the content of the course in the statistical package used in the course  
  • identify and interpret relevant information in the output of the statistical package used in the course  
  • summarize the results of an analysis in a statistical report 


The following main topics are contained in the course:
  • Theoretical results in hypothesis test
  • Theoretical results regarding conditional tail moments
  • Discriminant analysis and classification


See itslearning for syllabus lists and additional literature references.

Examination regulations

Prerequisites for participating in the exam a)








Second examiner: None




Full name and SDU username


Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value


Additional information

The prerequisite examination is a prerequisite for participation in exam element a).

Exam element a)




Type Prerequisite name Prerequisite course
Examination part Prerequisites for participating in the exam a) N370006101, ST817: Mathematical Statistics II


Written exam




Second examiner: Internal


7-point grading scale


Student Identification Card


Normally, the same as teaching language


3 hours

Examination aids

Allowed, a closer description of the exam rules will be posted in itslearning.

ECTS value


Indicative number of lessons

30 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model i.e. intro, training and study phase.
  • Intro phase: 20 hours
  • Training phase: 10 hours tutorials
Lectures will introduce general concepts and theory and exercise sessions will be devoted to learning material in depth. Interactive teaching will be used and, if possible, smart boards.
Studying the course material and preparing the weekly exercises, individually or through group work.

Teacher responsible

Name E-mail Department
Jing Qin Data Science


Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration


Offered in


Recommended course of study

Profile Education Semester Offer period

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.