Philip B. Stark  |  Professor of Statistics  |  University of California

Berkeley, CA   94720-3860  |  stark [at] stat.berkeley.edu  |  voice: 510-642-1430  |  fax: 510-743-4202

My research centers on inference (inverse) problems, primarily in physical science. I am especially interested in confidence procedures tailored for specific goals and in quantifying the uncertainty in inferences that rely on simulations of complex physical systems. I've done research on the Big Bang, causal inference, the U.S. census, earthquake prediction, election auditing, the geomagnetic field, geriatric hearing loss, information retrieval, Internet content filters, nonparametrics (confidence procedures for function and probability density estimates with constraints), the seismic structure of Sun and Earth, spectroscopy, and spectrum estimation. I am interested in numerical optimization, and have published some software.

I've consulted in product liability litigation, truth in advertising, equal protection under the law, jury selection, trade secret litigation, employment discrimination litigation, import restrictions, insurance litigation, natural resource legislation, environmental litigation, patent litigation, sampling in litigation, wage and hour class actions, product liability class actions, consumer class actions, the U.S. census, clinical trials, signal processing, geochemistry, IC mask quality control, behavioral targeting, water treatment, sampling the web, risk assessment, and oil exploration.

I developed online introductory Statistics materials that include interactive data analysis and demonstrations, machine-graded online assignments and exams (a different version for every student), and a text with dynamic examples and exercises, applets illustrating key concepts, and an extensive glossary. These materials were the basis of the first online course (in any subject) taught at UC Berkeley.

Last modified 7 July 2008. P.B. Stark. statistics.berkeley.edu/~stark/index.html