Statistics Group


General information

Examination dates Prof. Redenbach:

February 19th, 2024 (with the morning being blocked for joint exams of measure theory/ODE)

March 14th, 2024

April 5th, 2024

April 18th, 2024

 

Examination dates Dr. Stockis:

February 15th, 2024

March 21st, 2024

April 18th, 2024

 

Please register yourself in person at the Dean's Office with Heike Sternike (Building 48, 511). Please bring your student ID with you.

 

 

Below are the lectures offered by our group in the winter semester.

If you would like to write a Bachelor's or Master's thesis in Statistics, please contact Prof. Redenbach.

Important links

  • KIS: dates of the courses
  • URM: registration
  • OpenOLAT: course materials and further information (access code will be given in the first lecture)

Lectures in winter term

Below are the lectures offered by our group in the winter term 2023/24.

Mathematical Statistics

Contents

  • Asymptotic analysis of M-estimators, especially of Maximum-Likelihood-estimators
  • Bayes and Minimax-estimators
  • Likelihood-ratio-tests: asymptotic analysis and examples (t-test, chi²-goodness-of-fit-test)
  • Glivenko-Cantelli-theorem, Kolmogorov-Smirnov-test
  • Differentiable statistic functionals and examples of applications (derivation of asymptotic results, robustness)
  • Resampling methods on the basis of Bootstrap.

Contact time

4 SWS / 60 h Lecture
2 SWS / 30 h  Tutorials

Prerequisites (Contents)

The lecture "Stochastic Methods" from the Bachelor degree program in mathematics.

Frequency of occurence

The lecture is given once per year, in the winter term.

[Link to KIS]

[Link to OLAT]

Tutorials for the lecture:

[Link to KIS]

Image Analysis for stochastic structures

Contents

Processing and statistical analysis of three-dimensional image data, in particula

  • Random closed sets and their characteristics
  • Discretisation and three-dimensional connectivity
  • Mathematical morphology</il>
  • Methods of image processing: filtering, segmentation, Euclidean distance transform, labelling, watershed transform
  • Estimates of geometric characteristics for random closed sets from image data

Contact time

 2 SWS / 30 h Lecture

2 SWS / 30 h Tutorials/Practical Training

Prerequisites (Contents)

The lecture "Stochastic Methods" from the Bachelor degree program in mathematics.

Frequency of occurrence

The lecture is irregularly given.

 

[Link to KIS]

[Link to OLAT]

Tutorials for the lecture:

[Link to KIS]

Seminar

Our group offers the following seminar in the winter term 2023/24:

Seminar Topological Data Analysis

Contents

The seminar will start with an introduction to topological data analysis (TDA). No prior knowledge on TDA is required. Then, we will focus on statistical methods based on TDA in various fields of application.

Registration via URM.

The first meeting for setting up the schedule will take place in the second week of the lecture period.

Contact Time

2 SWS / 30 h Seminar

Frequency of occurence

Seminar dates will be announced.

Registration via URM.

 

[Link to KIS]

[Link to OLAT]

Practical Training

Subjects for practical trainings are presented at the Fachpraktikumsbörse at the end of each semester.

Reading Course

The Reading Course serves as preparation for the Master's thesis. The assignment of topics takes place individually. Please contact Prof. Redenbach if you would like to take a Reading Course in Statistics.

Go to top