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

Berkeley, CA   94720-3860  |  stark [at] stat.berkeley.edu  |  voice: 510-394-5077  |  fax: 510-743-4202

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

I've consulted in truth in advertising, equal protection under the law, intellectual property and patent litigation, jury selection, trade secret litigation, employment discrimination litigation, import restrictions, insurance litigation, natural resource legislation, environmental 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 6 November 2009. P.B. Stark. statistics.berkeley.edu/~stark/index.html