Statistics at UC Berkeley: We are a community engaged in research and education in probability and statistics. In addition to developing fundamental theory and methodology, we are actively involved in statistical problems that arise in such diverse fields as molecular biology, geophysics, astronomy, AIDS research, neurophysiology, sociology, political science, education, demography, and the U.S. Census. We have forged strong interdisciplinary links with other departments and areas of study, particularly biostatistics, mathematics, computer science, and biology, and actively seek to recruit graduate students and faculty who can help to build and maintain such links. We also offer a statistical consulting service each semester.
Statistics at UC Berkeley
Oct 8, 2014
Sep 22, 2014
Seminar 217, Risk Management: "Liquid Assets and Portfolio Risk Management: Oil and the Norwegian Sovereign Fund (GPFG)"
Hayne Leland (Speaker - Featured)
Dec 2, 2014 11:00am
Alexander Soshnikov, U.C. Davis
Dec 3, 2014 3:10pm
In the first half of the talk, I will discuss CLT type results for linear and partial linear eigenvalue statistics of large random Hermitian matrices. The second talk will be devoted to a recent result (joint with Sean O'Rourke, David Renfrew, and Van Vu) about the products of elliptic random matrices.
Simons Institute Open Lecture: The Unreasonable Effectiveness of Spectral Graph Theory: A Confluence of Algorithms, Geometry, and Physics
James R. Lee (Speaker)
Dec 8, 2014 4:00pm
The fourth in the fall series of Simons Institute Open Lectures. The Open Lectures are intended for a broad scientific audience. Light refreshments will be served before the lecture at 3:30 p.m.
Thomas Rosenlund (Speaker - Featured), Jonas Stenersen (Speaker - Featured)
Dec 9, 2014 11:00am
Giovanni Parmigiani, Department of Biostatistics, Harvard University
Dec 10, 2014 1:00pm
Numerous gene signatures of patient prognosis for late-stage, high-grade ovarian cancer have been published, but diverse data and methods have made these difficult to compare objectively. However, the corresponding large volume of publicly available expression data creates an opportunity to validate previous findings and to develop more robust signatures. We thus built a database of uniformly...