STA 190S is run as individual, mentored research projects with each student working with her/his Statistical Science faculty mentor/advisor throughout the semester. Research developments and reporting will be guided by the advisor, and students will be aiming to complete a draft report by the end of semester. In some cases, this will comprise research advances that will eventually be publishable.

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: 1.5 credits (and 1.5 in spring for STA 190(B)S)

Planning for interested students: If you are interested in research in statistical science, whether related to an existing research activity or for entrée to new and exciting research areas, then please contact me via email 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 example topic, below. Students should contact professors directly for discussion and further information.

Possible Project Topic Professor   Developing and studying models for social networks     David Banks   (On leave)     Jim Berger   Protein discovery and mass spectroscopy     Merlise Clyde   Models for multiway contingency tables     Ian Dinwoodie   Statistical models for studying exposure disease relationships     David Dunson   Modelling and analysis for spatial data     Alan Gelfand   Simulation techniques for high-dimensional distributions     Mark Huber   Statistical problems in genetics and cancer risk assessment     Ed Iversen   Geometry of high-dimensional data - applications to cancer genomics     Sayan Mukherjee   Topics forthcoming soon ...     Fan Li   Designing and evaluating methods for sharing confidential data     Jerry Reitter   Statistical estimation in scientific models: biology, chemistry, and physics     Scott Schmidler   Statistical methods for the analysis of clinical trials and data in the health sciences     Dalene Stangl   Statistical modelling and time series in finance:    - prediction, portfolios and risk in global investment management     Mike West   Biodiversity, spatial statistics, Bayesian networks for decision support, copulas     Robert Wolpert -- professors are interested in hearing about your own project ideas --

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.