ZüKoSt: Seminar on Applied Statistics

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Autumn Semester 2015

Note: The highlighted event marks the next occurring event.

Date / Time Speaker Title Location
5 November 2015
Carsten Schmitz
Winton Capital, London
Big Data and Selection Bias in Finance  HG G 19.1 
Abstract: Winton is a systematic asset manager and has been using computers and data to construct trading systems since 1997. Access to large amounts of data allows the testing of a large number of hypotheses which may sound good and empowering - but brings with it rather new challenges. In fact, only thorough statistical analysis can help find the path through the jungle of allegedly significant results.
19 November 2015
Martin Posch 
Medical University of Vienna
Addressing Multiple Objectives in Clinical Trials: Adaptive Designs and Multiple Testing  HG G 19.1 
Abstract: Adaptive designs play an increasingly important role in clinical drug development. They use accumulating data of an ongoing trial to decide on modifications of different design aspects without undermining the validity and integrity of the trial. Several types of adaptations have been considered as early stopping for futility or success, sample size reassessment and change of population. Particularly appealing applications are the use of adaptive designs in combined phase II/III studies with treatment selection at interim and adaptive enrichment designs where subgroups with a differential treatment effect can be selected. We review the adaptive design methodology for a single null hypothesis and discuss extensions to multiple hypotheses testing problems. Finally, the application of multi-stage designs in high dimensional testing problems is discussed.
10 December 2015
Andrea Kraus
Masaryk Unversity, Brno, Czech Republic
Modelling and estimating the spread of an epidemic from little initial information  HG G 19.1 
Abstract: Epidemics have shaped our history, and even in modern times of huge scienti c progress, major outbreaks are not uncommon. It is comparatively easy to tackle a small epidemic but very dicult to contain a large one, which urges public authorities to be on watch for early signs of new outbreaks. Mathematical and probabilistic modelling and statistical inference play a crucial role in these e orts. We give an overview of models for the spread of epidemics with focus on branching-process approximations for the initial stages. These originally population-growth models hinge on strong probabilistic concepts, such as the Markovian nature, rather than on speci c information on the disease. This makes them suitable for use when the available information is largely con ned to temporally aggregated counts of new cases subject to unknown amount of under-reporting. Employing these models, we discuss the estimation of the spreading potential of an on-going epidemic in its early stages.

Archive: AS 15  SS 15  AS 14  SS 14  AS 13  SS 13  AS 12  SS 12  AS 11  SS 11  AS 10  SS 10  AS 09 

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