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Séminaire du LJLL - 17 03 2017 14h00 : E. Candès
Emmanuel Candès
(Université de Stanford)
Around the reproducibility of scientific research in the big data era : what statistics can offer ?
Exceptionnellement, cette séance du séminaire, qui s’inscrivait dans le cadre des Leçons Jacques-Louis Lions 2017, a eu lieu dans l’amphithéâtre 44 du Campus Jussieu de l’UMPC Paris VI (entrée face à la tour 44 niveau dalle Jussieu).
Abstract
The big data era has created a new scientific paradigm : collect data first, ask questions later. When the universe of scientific hypotheses that are being examined simultaneously is not taken account, inferences are likely to be false. The consequence is that follow up studies are likely not to be able to reproduce earlier reported findings or discoveries. This reproducibility failure bears a substantial cost and this talk is about new statistical tools to address this issue. In the last two decades, statisticians have developed many techniques for addressing this look-everywhere effect, whose proper use would help in alleviating the problems discussed above. This lecture will discuss some of these proposed solutions including the Benjamin-Hochberg procedure for false discovery rate (FDR) control and the knockoff filter, a method which reliably selects which of the many potentially explanatory variables of interest (e.g. the absence or not of a mutation) are indeed truly associated with the response under study (e.g. the log fold increase in HIV-drug resistance).