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Colloquium – Heping Zhang, Yale School of Public Health

September 2, 2016 @ 5:00 am - 6:00 am

Statistical Strategies in Analyzing Data with Unequal Prior Knowledge

The advent of technologies including high throughput genotyping and computer information technologies has produced ever large and diverse databases that are potentially information rich. This creates the need to develop statistical strategies that have a sound mathematical foundation and are computationally feasible and reliable. In statistics, we commonly deal with relationship between variables using correlation and regression models. With diverse databases, the quality of the variables may vary and we may know more about some variables than the others. I will present some ideas on how to conduct statistical inference with unequal prior knowledge. Specifically how do we define correlation between two sets of random variables conditional on a third set of random variables and how do we select predictors when we have information from sources other than the databases with raw data? I will address some mathematical and computational challenges in order to answer these questions. Analysis of real genomic data will be presented to support the proposed methods and highlight remaining challenges.


September 2, 2016
5:00 am - 6:00 am
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230 Gordon Palmer Hall
505 Hackberry Lane AL 35487 United States + Google Map