[Statlist] Next talk: Friday, 24.05.2019, with Bin Yu, UC Berkeley

[Maurer Letizia]

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ETH and University of Zurich

Organisers:

Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf

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We are glad to announce the following talk:

Friday, 24.05.2019, at 15.15 h  ETH Zurich, HG G19.1
with Bin Yu, UC Berkeley
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Title:

Three principles of data science: predictability, computability, and stability (PCS)

Abstract:

In this talk, I'd like to discuss the intertwining importance and connections of three principles of data science in the title and the PCS workflow that is built on the three principles. The principles will be demonstrated in the context of collaborative projects in genomics for interpretable data results and testable hypothesis generation. If time allows, I will present proposed PCS inference that includes perturbation intervals and PCS hypothesis testing. The PCS inference uses prediction screening and takes into account both data and model perturbations. Finally, a PCS documentation is proposed based on Rmarkdown, iPython, or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.


This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar

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