Humboldt-Universität zu Berlin - Statistics

The paper Challenges and Opportunities for Statistics in the Era of Data Science is accepted by Harvard Data Science Review.

Authors: Claudia Kirch¹, Soumendra Lahiri², Harald Binder³, Werner Brannath⁴, Ivor Cribben⁵, Holger Dette⁶, Philipp Doebler⁷, Oliver Feng⁸, Axel Gandy⁹, Sonja  Greven¹⁰, Barbara Hammer¹¹, Stefan Harmeling⁷, Thomas Hotz¹², Göran Kauermann¹³, Joscha Krause¹⁴, Georg Krempl¹⁵, Alicia Nieto-Reyes¹⁶, Ostap Okhrin¹⁷, Hernando Ombao¹⁸, Florian Pein¹⁹, Michal Pešta²⁰, Dimitris Politis²¹, Li-Xuan Qin²², Tom Rainforth²³, Holger Rauhut¹³, Henry Reeve²⁴, David Salinas²⁵, Johannes Schmidt-Hieber²⁶, Clayton Scott²⁷, Johan Segers²⁸, Myra Spiliopoulou¹ , Adalbert Wilhelm²⁹, Ines Wilms³⁰, Yi Yu³¹, Johannes Lederer³²

¹Otto-von-Guericke University Magdeburg, Germany, ²Washington-University in St. Louis, USA, ³Medical Faculty and Medical Center, University of Freiburg, Germany, ⁴University of Bremen, Germany, ⁵University of Alberta, Canada, ⁶Ruhr-University Bochum, Germany, ⁷TU Dortmund, Germany, ⁸University of Bath, UK, ⁹Imperial College London, UK, ¹⁰Humboldt-University Berlin, Germany, ¹¹University of Bielefeld, Germany, ¹²Technische Universität Ilmenau, Germany, ¹³Ludwigs-Maximilian-University Munich, Germany, ¹⁴Trier-University, Germany, ¹⁵Utrecht University, Netherlands, ¹⁶University of Cantabria, Spain, ¹⁷TUD Dresden University of Technology, Germany, ¹⁸KAUST University, Saudi Arabia, ¹⁹Lancaster University, UK, ²⁰Charles University, Prague, Czech Republic, ²¹University of California, San Diego, USA, ²²Memorial Sloan Kettering Cancer Center, USA, ²³University of Oxford, UK, ²⁴University of Bristol, UK, ²⁵ELLIS Institute Tübingen, Germany, ²⁶University of Twente, Netherlands, ²⁷University of Michigan, USA, ²⁸KU Leuven, Belgium, ²⁹Constructor University Bremen, Germany, ³⁰Maastricht University, Netherlands, ³¹University of Warwick, UK, ³²University of Hamburg, Germany

CRediT taxonomy:
• Claudia Kirch and Johannes Lederer: conceptualization, funding acquisition, project administration, writing original draft, writing review and editing
• Holger Dette and Barbara Hammer: conceptualization, funding acquisition, writing original draft
• Everybody: writing original draft

Abstract:

Statistics as a scientific discipline is currently facing the great challenge of finding its place in data science once more. While at the beginning of the last century, the development of the discipline of statistics was initiated by data-related research questions, nowadays, it is often viewed to have not kept up with the current developments in data science, which are largely focused on algorithmic, exploratory and computational aspects and often driven by other disciplines, such as computer science. However, statistics can—and should—contribute to the advances of data science. Of most interest are the strengths of statistics, such as the mathematical focus that leads to theoretical guarantees. This includes methods for formal modeling, hypothesis tests, uncertainty quantification and statistical inference. Of particular interest are also established statistical frameworks to handle causality or data deficiencies such as dependence, missingness, biases or confounding.

This paper summarizes the findings of a discussion workshop on the topic that was held in June 2023 in Hannover, Germany. The discussion centered around the following questions: How must statistics be set up so that it can contribute (more) to modern data science? In which direction should it develop further? Which strengths can already be used now? What conditions must be created so that this can succeed? What can be done to arrive at a common language? What is the added value of formal modeling, inference, and the mathematical perspective taken in statistics?