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Distinguished Lecture Series in Statistical Science
November 9-10, 2005
Brad Efron
Max H. Stein Professor and Professor of Statistics and of Health Research
and Policy, Department of Statistics, Stanford University
AUDIO OF THE TALKS
November 9, 2005 --3:30 p.m.
Fifty Years Of Empirical Bayes
Scientific inference is the process of reasoning from observed
data back to its underlying mechanism. The two great schools
of statistical inference, Bayesian and frequentist, have competed
over the past two centuries, often bitterly, for scientific
supremacy. Empirical Bayes, a novel hybrid, appreared in the
early 1950's, showing promise of immense possible gains in inferential
accuracy. Nevertheless it has languished in the statistics literature,
with its gains viewed as suspicious and even paradoxical by
Bayesians and frequentists alike. New scientific technology,
exemplified by dna microarrays, has suddenly revived interest
in empirical Bayes methods. This talk, which is aimed at a general
scientific audience, examines the ideas involved through a series
of real examples, and proceeds with a minimum of technical development.
November 10, 2005 -- 11 a.m.
Correlation And Large-Scale Simultaneous Significance
Testing
Large-scale hypothesis testing problems, with hundreds
or thousands of test statistics "z[i]" to consider
at once, have become commonplace in current practice. Applications
of popular analysis methods such as false discovery rates do
not require independence of the z[i]'s but their accuracy can
be compromised in high-correlation situations. This talk discusses
methods, both theoretical and computational, for assessing the
size and effect of correlation in large-scale testing situations.
Two microarray examples will be used to illustrate the ideas.
The examples show surprisingly large correlations that badly
destabilize standard statistical analyses, but newer methods
can remedy at least part of the trouble.
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| Professor Efron is a member of the National
Academy of Sciences, president of the American Statistical Association,
recipient of the MacArthur Prize, and winner of the Wilks Medal
of the American Statistical Association. He is renowned internationally
for his pioneering work in computationally intensive statistical
methods that substitute computer power for mathematical formulas,
particularly the bootstrap method. The goal of his research is to
extend statistical methodology in ways that make analysis more realistic
and applicable for complicated problems. He consults actively in
the application of statistical analyses to a wide array of health
care evaluations.
"I like working on applied and theoretical problems at the
same time and one thing nice about statistics is that you can
be useful in a wide variety of areas. So my current applications
include biostatistics and also astrophysical applications."
The Distinguished Lecture Series in Statistical Science series
was established in 2000 and takes place annually. It consists
of two lectures by a prominent statistical scientist. The
first lecture is intended for a broad mathematical sciences
audience. The series occasionally takes place at a member
university and is tied to any current thematic program related
to statistical science; in the absence of such a program the
speaker is chosen independently of current activity at the
Institute. A nominating committee of representatives from
the member universities solicits nominations from the Canadian
statistical community and makes a recommendation to the Fields
Scientific Advisory Panel, which is responsible for the selection
of speakers.
Distinguished Lecture
Series in Statistical Science Index
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