107.210 Mathematical Statistics
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, UE, 1.0h, 1.5EC


  • Semester hours: 1.0
  • Credits: 1.5
  • Type: UE Exercise
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to understand the mathematical foundations of statistical inference, work with basic statistical models and tests, analyse their features and assess their performance. They are also able to apply their theoretical knowledge in a variety of applications.

Subject of course

See lectures 107.079.

Teaching methods

Discussion of the problem sheets provided by the lecturer

Mode of examination


Additional information

The classes will last two hours and will take place once every two weeks.

The schedule of the course is provisional and will be agreed with the students in the first week. If the provisional schedule does not work for you, please drop an email to the lecturer before the start of the semester and indicate your preference.



Course dates

Wed16:00 - 18:0025.10.2023 - 24.01.2024Seminarraum 363 Problem classes
Mathematical Statistics - Single appointments
Wed25.10.202316:00 - 18:00Seminarraum 363 Problem classes
Wed08.11.202316:00 - 18:00Seminarraum 363 Problem classes
Wed29.11.202316:00 - 18:00Seminarraum 363 Problem classes
Wed13.12.202316:00 - 18:00Seminarraum 363 Problem classes
Wed10.01.202416:00 - 18:00Seminarraum 363 Problem classes
Wed24.01.202416:00 - 18:00Seminarraum 363 Problem classes

Examination modalities

Students will be required to work out problems at home and present them during the class. They will be evaluated based on how many problems they managed to solve and, more importantly, on the quality of their presentations.

Course registration

Begin End Deregistration end
04.09.2023 08:00 29.02.2024 18:00



Bickel, P.J., & Doksum, K.A. (2015). Mathematical Statistics: Basic Ideas and Selected Topics, Second Edition. Chapman and Hall/CRC.

Previous knowledge

Probability theory, calculus and linear algebra