Representative Signatures in Data Analysis - Epistemological Reflections

Session

Signal-background separation and data quality

15 Oct 2026, 14:00

JvF25/3-303 - Conference Room (Lamarr/RC Trust Dortmund)

15. Statistical separation of signal and background based on partial prior knowledge

Prof. Michael Schmelling (Max-Planck-Institut für Kernphysik Heidelberg)

15/10/2026, 14:00

Data analysis is often faced with the problem to determine the properties of a signal in the presence of background. A measurement is possible if the two components can be statistically separated in a discriminant variable, provided the probability density functions in this variable are known or can be estimated from the data. This is realized by Custom Orthogonal Weight functions (COWs). The...

7. The impact of data quality and representativity for statistical learning models

Prof. Katja Ickstadt (TU Dortmund)

15/10/2026, 14:45

The quality of results of machine learning models highly depends on the quality of the data used to train the model. But what do we mean by good data quality? Are representative data, e.g., provided by the German micro census or the census of good quality? And does the term “representativity” suffice to define data quality? In this talk, we will discuss the terms “data quality” and...