Prerequisites:
Students must be working on statistical research with a Statistical Science faculty member. This pre-supposes relevant advanced course work in statistics and related areas. Most students should have prior courses to the level of at least STA 121 & 122.

Credit: 1 unit for STA 190S(A) in fall and 1 unit for STA 190(B)S in spring.

Planning for interested students:
Contact me via email for general information and guidance on topics/faculty mentors, and explore the personal web pages of the Statistical Science faculty to get the flavour of their current research activities. Each professor has also provided one (or more) example topic, below. Students should contact professors directly for discussion and further information.

Important: Please note that students sign-up fast with available professors. Some professors will typically become committed quickly so you should make sure to explore options and sign-up soon! See "Available/Potential Project Topics" in the table below. And of course professors are interested in hearing about your own project ideas!

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Available/Potential Project Topics	Professor
Gene selection in cancer classification	Artin Armagan
Social network models. Agent-based models	David Banks
(On leave)	Jim Berger
(1) Forest responses to global change-exchange of water, CO2, and energy   (2) Impact of co-infection of multiple pathogens on multiple hosts   (3) Inference on demography and health of natural populations	James Clark
(1) Model uncertainty in statistics   (2) Applications in environmental statistics   (3) Modern statistics in proteomics and proteomic mass spectrometry	Merlise Clyde
(1) Item response model and psychometric analysis   (2) Bayesian categorical data analysis	Sourish Das
Monte Carlo methods for binary sequences, with biological applications	Ian Dinwoodie
Statistical models for studying exposure disease relationships	David Dunson
Modelling and analysis for spatial data	Alan Gelfand
Statistical problems in genetics and cancer risk assessment	Ed Iversen
(1) Bayesian variable selection in genome-wide association studies   (2) Causal inference in observational studies	Fan Li
Statistical genomics	Joe Lucas
Probability and statistics on networks	Jonathan Mattingley
(1) Statistical estimation in scientific models: biology, chemistry, and physics   (2) Statistics in finance and decision making/portfolio theory   (3) Simulation and statistical inference for SDEs	Scott Schmidler
Statistical methods for the analysis of clinical trials and data in the health sciences	Dalene Stangl
(1) Nonparametric statistics   (2) Statistics in the neurosciences	Surya Tokdar
(1) Biodiversity   (2) Spatial statistics   (3) Bayesian networks for decision support   (4) Copulas	Robert Wolpert
Additional information: Students interested in research in statistical science and its applications should consider taking a relevant sequence of undergraduate courses. A one-year research project, developed under the mentorship of an ISDS faculty member and coupled with registration for STA 190S, is a requirement for the Major in Statistical Science. STA 190S as an elective counts towards the requirements for the Minor in Statistical Science.