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Prof. Dr. Claudia Becker

Prof. Dr. Claudia Becker
(Foto: Maike Glöckner)

Personal information

• born in 1967
• study of Statistics (Dipl.) with minor Informatics, University of Dortmund, 1986 – 1993
• doctorate 1996, habilitation 2002 in Dortmund
• research assistant at the department of Statistics, University of Dortmund   , 1993 – 2002
• Collaboration in Sonderforschungsbereich 475    "Komplexitätsreduktion in multivariaten Datenstrukturen", University of Dortmund, 1997 – 2002
• Subproject Management in Sonderforschungsbereich 559    "Modellierung großer Netze in der Logistik", University of Dortmund, since 2000
• Substitute professorship Institut für Statistik, LMU München   , winter term 2001/2002
• University lecturer in the field of data analysis at the department of Statistics, University of Dortmund, 2002
• University Professor of Statistics at MLU since 2002
• Member of Faculty Council of the Faculty of Law and Economics since 2003
• Member of Senate Commission for Studies and Teaching since 2006
• Vice Chairwoman of the Economics Examination Board, 2010 – 2018
• Vice Dean of the department of Economics, 2012 – 2014
• Dean of of the Faculty of Law and Economics, 2014 – 2018
• Member der Ombuds Commission "Gute Arbeit in der Wissenschaft", 2016 – 2018
• Chairwoman of the Economics Examination Board, 2018 – 2022
• Rector of MLU since 2022

Main research topics

• statistical method development
• robust statistical procedures and outlier identification
• robust statistical methods for dimension reduction in complex data structures
• planning and evaluation of surveys
• collection of sensitive data
• recording complex situations and correlations through surveys

Selected Publications

Articles in refereed journals

Hirschauer, N., Grüner, S., Mußhoff, O., Becker, C., Jantsch, A. (2020). Can p-values be meaningfully interpreted without random sampling? Statistics Surveys, 14, 71-91. DOI: 10.1214/20-SS129    .

Hirschauer, N., Gruener, S., Mußhoff, O., Becker, C. (2020). Inference in economic experiments, Economics, The Open-Access, Open-Assessment E-Journal, 14(2020-7): 1-14. DOI: http://dx.doi.org/10.5018/economics-ejournal.ja.2020-7    .

Hirschauer, N., Grüner, S., Mußhoff, O., Becker, C. (2019). Twenty steps towards an adequate inferential interpretation of p-values in econometrics, Journal of Economics and Statistics, 239(4), 703-721. DOI: https://doi.org/10.1515/jbnst-2018-0069   .

Hirschauer, N., Grüner, S., Mußhoff, O., Becker, C. (2018). Pitfalls of significance testing and p-value variability: An econometrics perspective, Statistics Surveys, 12, 136-172. DOI: 10.1214/18-SS122   .

Droste, N., Becker, C., Ring, I., Santos, R. (2018). Decentralization Effects in Ecological Fiscal Transfers: A Bayesian Structural Time Series Analysis for Portugal, Environmental Resource Economics, 71, 1027-1051. DOI: https://doi.org/10.1007/s10640-017-0195-7   .

Angelova, D., Becker, C., Hockmann, H. (2018). An indicator for nature-state detection in the state-contingent framework and the case of grain production in Saxony-Anhalt, Germany, Ecological Indicators, 89, 422-437. DOI: https://doi.org/10.1016/j.ecolind.2018.01.052   .

Kirschstein, T., Liebscher, S., Becker, C. (2013). Robust Estimation of Location and Scatter by Pruning the Minimum Spanning Tree, Journal of Multivariate Analysis, 120, 173-184. DOI: https://doi.org/10.1016/j.jmva.2013.05.004   .

Liebscher, S., Kirschstein, T., Becker, C. (2012). RDELA – a Delaunay-triangulation-based, location and covariance estimator with high breakdown point, Statistics and Computing, 23, 677-688. DOI: https://doi.org/10.1007/s11222-012-9337-5   .

Liebscher, S., Kirschstein, T., Becker, C. (2012). The Flood Algorithm – A Multivariate, Self-Organizing-Map-Based, Robust Location and Covariance Estimator, Statistics and Computing, 22, 325-336. DOI: https://doi.org/10.1007/s11222-011-9250-3   .

Dettmann, E., Becker, C., Schmeißer, C. (2011). Distance Functions for Matching in Small Samples, Computational Statistics and Data Analysis, 55, 1942-1960. DOI: https://doi.org/10.1016/j.csda.2010.11.022   .

Zeh, A., Becker, C., Lattke, P., Planert, M., Wohlrab, D. (2009). Time dependent release of cobalt and chromium ions into the serum following implantation of the metal-on-metal MaverickTM type artificial lumbar disc (Medtronic Sofamor Danek), Archives of Orthopaedic and Trauma Surgery,129, 741-746. DOI: 10.1007/s00402-008-0677-8   .

Ngui, D. M., Becker, C., Thomi, W. (2008). Corruption, Insecurity and Technical Efficiency: Evidence from Kenyan Manufacturing firms, International Journal of Afro-Asian Studies, 1, 65-78.

Becker, C., Paris Scholz, S. (2004). MVE, MCD, and MZE: A simulation study comparing convex body minimizers, Allgemeines Statistisches Archiv, 88, 155-162. DOI: https://doi.org/10.1007/s101820400166   .

Gather, U., Hilker, T., Becker, C. (2002). A note on outlier sensitivity of sliced inverse regression, Statistics, 13, 271-281. DOI: https://doi.org/10.1080/02331880213194   .

Hausmann, M., Becker, C., Gather, U., Güntürkün, O. (2002). Functional cerebral asymmetries during the menstrual cycle: A cross sectional and longitudinal analysis, Neuropsychologia, 40, 808-816. DOI: https://doi.org/10.1016/S0028-3932(01)00179-8   .

Gather, U., Becker, C. (2001). The curse of dimensionality – A challenge for mathematical statistics, Jahresberichte der deutschen Mathematiker Vereinigung, 103, 19-36.

Becker, C., Gather, U. (2001). The largest nonidentifiable outlier: A comparison of multivariate simultaneous outlier identification rules, Computational Statistics & Data Analysis, 36, 119-127. DOI: https://doi.org/10.1016/S0167-9473(00)00032-3   .

Becker, C., Gather, U. (1999). The masking breakdown point of multivariate outlier identification rules, Journal of the American Statistical Association, 94, 947-955. DOI: https://doi.org/10.2307/2670009   .

Contributions to anthologies

Gather, U., Hilker, T., Becker, C. (2001). A robustified version of sliced inverse regression, in: Fernholz, L.T., Morgenthaler, S., Stahel, W. (Eds.), Statistics in Genetics and in the Environmental Sciences, Birkhäuser, Basel, 147-157. DOI: https://doi.org/10.1007/978-3-0348-8326-9_10   .

Gather, U., Becker, C. (1997). Outlier identification and robust methods, in: Maddala, G.S., Rao, C.R. (Eds.), Handbook of Statistics 15: Robust Inference, Elsevier, Amsterdam, 123-143. DOI: https://doi.org/10.1016/S0169-7161(97)15008-8   .

Contributions to conference volumes

Becker, C. (2010). Exploring Sensitive Topics: Sensitivity, Jeopardy, and Cheating, in: Locarek-Junge, H., Weihs, C. (Eds.), Classification as a Tool for Research, Springer, Berlin, 299-305. DOI: https://doi.org/10.1007/978-3-642-10745-0_32   .

Becker, C., Theis, W. (2007). Combining dimension reduction and Fuzzy-Clustering: An application to business cycles, in: Heilemann, U., Weihs, C. (Eds.), Classification and Clustering in Business Cycle Analysis, RWI: Schriften, Heft 79, Duncker & Humblot, Berlin, 137-144. DOI: https://doi.org/10.3790/978-3-428-52425-9   .

Becker, C., Paris Scholz, S. (2006). Deepest Points and Least Deep Points: Robustness and Outliers with MZE, in: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (Eds.), From Data and Information Analysis to Knowledge Engineering, Springer, Heidelberg, 254-261. DOI: https://doi.org/10.1007/3-540-31314-1_30   .

Becker, C. (2005). Iterative proportional scaling based on a robust start estimator, in: Weihs, C., Gaul, W. (Eds.), Classification – The Ubiquitous Challenge, Springer, Heidelberg, 248-255. DOI: https://doi.org/10.1007/3-540-28084-7_27   .

Kuhnt, S., Becker, C. (2003). Sensitivity of graphical modeling against contamination, in: M. Schader, W. Gaul, M. Vichi (Eds.), Between Data Science and Applied Data Analysis, Springer, Berlin, 279-287. DOI: https://doi.org/10.1007/978-3-642-18991-3_32   .

Wenzel, S., Becker, C., Jodin, D. (2001). Methoden der Informationsgewinnung zur Bestimmung des Eingangsdatenraums für Simulationsmodelle in der Logistik, in: Panreck, K., Dörrscheidt, F. (Eds.), Simulationstechnik, 15. Symposium der Arbeitsgemeinschaft Simulation, ASIM 2001, SCS-Europe BVBA, Ghent, 417-422.

Becker, C. (2000). The size of the largest nonidentifiable outlier as a performance criterion for multivariate outlier identification: The case of high-dimensional data, in: Bethlehem, J. G., van der Heijden, P. G. M. (Eds.), COMPSTAT 2000. Proceedings in Computational Statistics, Physica-Verlag, Heidelberg, 211-216. DOI: https://doi.org/10.1007/978-3-642-57678-2_22   .

Contributions to commemorative publications

Becker, C., Dombrowski, K. (2013). Eine Trendwende in der Marketingforschung – Aktuelle Chancen und Risiken von Web Surveys, in: Crockford, G., Ritschel, F., Schmieder, U.-M. (Hrsg.), Handel in Theorie und Praxis, Festschrift zum 60. Geburtstag von Prof. Dr. Dirk Möhlenbruch, Springer Gabler, Wiesbaden, 439-465. DOI: https://doi.org/10.1007/978-3-658-01986-0_17   .

Becker, C., Liebscher, S., Kirschstein, T. (2013). Multivariate Outlier Identification Based on Robust Estimators of Location and Scatter, in: Becker, C., Fried, R., Kuhnt, S. (Eds.), Robustness and Complex Data Structures, Festschrift in Honour of Ursula Gather, Springer, Heidelberg, 103-115. DOI: https://doi.org/10.1007/978-3-642-35494-6_7   .

Books

Becker, C., Fried, R., Kuhnt, S. (Eds.) (2013). Robustness and Complex Data Structures, Festschrift in Honour of Ursula Gather, Springer, Heidelberg. DOI: 10.1007/978-3-642-35494-6   .

Genschel, U., Becker, C. (2004). Schließende Statistik. Grundlegende Methoden. Springer, Berlin. DOI: 10.1007/b137973   .

Working Papers

Hirschauer, N., Gruener, S., Mußhoff, O., Becker, C. (2020). A primer on p-value thresholds and α-levels – two different kettles of fish. SocArXiv Papers. DOI: 10.31235/osf.io/d46m2   .

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