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
Prof. Nielsen's work on omega-3 fatty acids and genetic adaptations in the Inuit population featured in the New York Times.
Sep 23, 2015
Seminar 217, Risk Management: Capital Share Risk and Shareholder Heterogeneity in U.S. Stock Pricing
Martin Lettau, University of California, Berkeley-Haas (Speaker - Featured)
Dec 1, 2015 4:00pm ☞ 125 Li Ka Shing Center
Most common phenotypic variation in humans is highly polygenic. Although there are examples of strong selective sweeps at individual loci, we and others have hypothesized that the bulk of human adaptation occurs through small shifts in allele frequencies at hundreds or thousands of relevant loci. In this talk I will describe our recent work on methods for studying the genetic basis of a variety...
New Methods for Studying Polygenic Traits and Polygenic Adaptation in Humans
Carl Mueller, Department of Mathematics, University of Rochester
Hitting questions play a central role in the theory of Markov processes. For example, it is well known that Brownian motion hits points in one dimension, but not in higher dimensions. For a general Markov process, we can determine whether the process hits a given set in terms of potential theory. There has also been a huge amount of work on the related question of when a process has...
Alexander Shkolnik, UC Berkeley
Risk management applications often require estimating the tail distribution of total default losses on a portfolio of credit-sensitive positions such as loans and corporate bonds. We develop, analyze and test an importance sampling estimator of large-loss probabilities. The estimator does not require knowledge of the loss transform and is implementable for any reduced-form model of correlated...
Linda Schilling, University of Bonn (Speaker - Featured)