Princeton S. S. Wilks Memorial Lecture Series will feature two speakers per year, one from statistics (Spring term) and one from probability (Fall term).
This lecture series is funded by the S. S. Wilks Memorial Fund endowed in honor of the late Princeton Professor of Statistics Samuel Stanley Wilks.
The year, the speaker will be Peter J. Bickel from UC Berkeley.
Wednesday March 26, 2014, 5:00pm
Computer Science 104
Title: From Fisher to “Big Data”: Continuities and discontinuities
Abstract: In two major papers in 1922 and 1925 Fisher introduced many of the ideas ,parameters , sufficiency, efficiency, maximum likelihood, which when coupled with Wald’s decision theoretic point of view of 1950 have underlain the structure of statistics until the 1980’s.That period coincided ,not accidentally,with the beginnings of the widespread introduction of computers and our ability to use them to gather “big data” and implement methods to analyze such data .In this lecture I will try to see how the Fisherian concepts have evolved in response to the new environment and to isolate and study new ideas that have been brought in and where they have come from. Thus,I will argue that “sufficiency” has evolved to “data compression”,”efficiency” has had to include computational considerations, and issues of scale ,“parameters” and procedures such as “maximum likelihood” have had to be considered in the context of larger semi and nonparametric models and in robustness. The steady rise in computational capability during the last 30-40 years has enabled the implementation of the older Bayesian point of view .computer intensive methods such as Efron’s “bootstrap” as well as the introduction of the “machine learning” point of view and methods from computer science.I will try to support my argument from the literature ,some of my own work and my experience with ENCODE .a “Big Data” project in biology.