Statistics at UC Berkeley

Aaditya Ramdas, UC Berkeley
Jan 17, 2018 4:00pm 1011 Evans Hall
Modern data science is often exploratory in nature, with hundreds or thousands of hypotheses being regularly tested on scientific datasets. The false discovery rate (FDR) has emerged as a dominant error metric in multiple hypothesis testing over the last two decades. I will argue that both (a) the FDR error metric, as well as (b) the current framework of multiple testing, where the scientist...
Speaker: Matthias Weber, Swiss Re (Speaker - Featured)
Jan 18, 2018 12:30pm 1011 Evans Hall
- In insurance, underwriting performance is a function of exposures, losses relative to exposures and premiums relative to exposures. Getting losses and loss trends right (--> cost of goods sold) is critically important. A small estimation mistake typically has a large impact on the bottom line. - Swiss Re is determining loss relevant trends using advanced analytics, often in collaboration with...
Speaker: Mariana Olvera-Cravioto, UC Berkeley (Speaker - Featured)
Jan 25, 2018 12:30pm 1011 Evans Hall
The talk will center around a set of recent results on the analysis of Google’s PageRank algorithm on directed complex networks. In particular, it  will focus on the so-called power-law hypothesis, which states that the distribution of the ranks produced by PageRank on a scale-free graph (whose in-degree distribution follows a power-law) also follows a power-law with the same tail-index as the...
Merle Behr, University of Göttingen
Jan 31, 2018 4:00pm 1011 Evans Hall
A challenging problem in cancer genetics is that tumors often consist of a few different groups of cells, so called clones, where each clone has different mutations, like copy-number (CN) variations. In whole genome sequencing the mutations of the different clones get mixed up, according to their relative unknown proportion in the tumor. However, CN's of single clones can only take values in a...
Speaker: Markus Pelger, Stanford (Speaker - Featured)
Feb 1, 2018 12:30pm 1011 Evans Hall

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.