Dr. Paavo Sattler

• Sattler, P., Pauly, M. Testing hypotheses about correlation matrices in general MANOVA designs. TEST (2023). https://doi.org/10.1007/s11749-023-00906-6.
• P. Sattler und M. Pauly, „Inference for high-dimensional split-plot-designs: a unified approach for small to large numbers of factor levels“, Electronic journal of statistics, Bd. 12, Nr. 2, S. 2743–2805, 2018. DOI: 10.1214/18-ejs1465.
• P. Sattler, M. Pauly, und P. Doebler, „Inference for multivariate and high-dimensional data in heterogeneous designs“, Universitätsbibliothek Dortmund, Dortmund, 2021. DOI: 10.17877/de290r-22692.
• P. Sattler, „A comprehensive treatment of quadratic-form-based inference in repeated measures designs under diverse asymptotics“, Electronic journal of statistics, Bd. 15, Nr. 1, S. 3611–3634, 2021. DOI: 10.1214/21-ejs1865.
• P. Sattler, A. C. Bathke, und M. Pauly, „Testing hypotheses about covariance matrices in general MANOVA designs“, Journal of statistical planning and inference, Bd. 219, S. 134–146, 2022. DOI: 10.1016/j.jspi.2021.12.001.
• K. Rubarth, P. Sattler, H. G. Zimmermann, und F. Konietschke, „Estimation and testing of Wilcoxon–Mann–Whitney Effects in factorial clustered data designs“, Symmetry, Bd. 14, Nr. 2, Art. Nr. 244, 2022. DOI: 10.3390/sym14020244.
• Mondal, A., Sattler, P. und Kumar, S. Testing for trend in two-way crossed effects model under heteroscedasticity, TEST, 2023. DOI: 10.1007/s11749-023-00879-6.
• A. Mondal, P. Sattler und S. Kumar, Testing against ordered alternatives in a two-way model without interaction under heteroscedasticity, Journal of Multivariate Analysis, 2023. DOI: 10.1016/j.jmva.2023.105177

• Fallstudien I (WiSe 23/24)
• Reading Course Inference (WiSe 23/24)
• Reading Course Inference (SoSe 2023)
• Six-Sigma-Methode (SoSe 2023)
• Reading Course Inference (WiSe 22/23)
• Reading Course Inference (SoSe 2022)
• Six-Sigma-Methode (SoSe 2022)
• Reading Course Inference (WiSe 21/22)
• Reading Course Inference (SoSe 2021)
• Six-Sigma-Methode (SoSe 2021)

Wissenschaftliche Tätigkeit

• Seit Feb. 2019: Wissenschaftlicher Mitarbeiter an der Fakultät Statistik der Technischen Universität Dortmund
• Sep. 2016 – Feb. 2019: Wissenschaftlicher Mitarbeiter an der Universität Ulm

Studium

• Dr. rer. nat (Statistik): Technische Universität Dortmund, November 2021. Dissertation: Inference for multivariate and high-dimensional data in heterogeneous designs.
• M.Sc. (Wirtschaftsmathematik): Universität Ulm, 2016. Masterarbeit: High-Dimensional Repeated Measures Analysis: Asymptotics and Multiple Samples
• B.Sc. (Mathematik): Universität Stuttgart, 2014. Bachelorarbeit: Unternehmenswertmodelle für die Bewertung von Kreditderivaten