Statistics Group


General information

Examination dates Prof. Redenbach:

July 24th, 2023

August 2nd, 2023

August 3rd, 2023

September 8th, 2023

September 14th, 2023

September 18th, 2023

September 29th, 2023

Oktober 11th, 2023

Oktober 12th, 2023

Oktober 13th, 2023

 

Examination dates Dr. Stockis:

July 25th, 2023

August 16th, 2023

September 18th, 2023

Oktober 12th, 2023

 

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.

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