Welcome to Mathematical Statistics and Applications in Industry
Our research interests include:
- Asymptotic and nonparametric statistics with applications
- Multivariate and repeated measurements analysis
- Resampling techniques
- Statistical and machine learning methods in theory and practice
- Survival analysis
- Time series analysis
You can find further information about our research projects, publications and team members on the respective subpages.
News
07/04/2025
Best Presentation Award for Jan-Bernd Igelmann at the symposium "Recent Advances in Meta-Analysis"
We are pleased to announce that M.Sc. Jan-Bernd Igelmann was awarded the Best Presentation Award at the annual symposium Recent Advances in…

07/01/2025
Annual Symposium on "Recent Advances in Meta-Analysis" 2025 in Dortmund
The symposium "Recent Advances in Meta-Analysis" took place from June 30 to July 1, 2025, at the Rudolf-Chaudoire-Pavillon of TU Dortmund University.

04/17/2025
Successful participation of Dortmund Master's students in award ceremonies
Several Master's graduates from the Department of Statistics at TU Dortmund University were honored for their outstanding work.

10/18/2024
Learning Session on Quantile-Based Covariate Adjustment
If you want to improve your knowledge in quantile regression and analysis of covariance, we invite you to our one-day Learning Session on Nov. 28th.

09/17/2024
Obituary for Marc Ditzhaus
Obituary for Marc Ditzhaus
09/04/2024
Keynote Lecture by Prof. Dr. Arne Bathke on the topic: "Statistical concepts and the effects of music and arts on health"
Prof. Dr. Arne Bathke (Paris Lodron University Salzburg) will give a keynote lecture on 19.09.24 at 14:00 in the IBZ.

07/05/2024
Summer School 2024 on Time-to-Event analysis
A joint IBS-DR, IBS-ROeS and ÖSG Summer School 2024 on Time-to-Event analysis took place from June, 26-29 in Strobl (Austria), co-organized by the…

01/26/2024
New DFG project on Meta Analysis
The project develops new methods to synthesize findings from different studies to provide a reliable and trustworthy basis for data-driven insights.

