Winter 2021 Virtual Seminar Series
Department of Statistics 2020-2021 Seminar Series (joint with Biostatistics) - Winter 2021
The 2020-2021 Seminar Series will be offered virtually using Zoom instead of in person. Registration will be required to receive the zoom link for the event. Please see the registration link associated with each talk to sign up. Links are specific to individual talks, so you will need to register for every talk you are interested in attending. Please email Kisa Kowal at email@example.com if you have questions.
Seminar Series talks are free and open to faculty, graduate students, and advanced undergraduate students.
Modeling Interventions on Social Networks
Wednesday, January 20, 2021
Time: 11:00 a.m.
Speaker: Tracy M. Sweet, Associate Professor, Measurement, Statistics & Evaluation, Department of Human Development & Quantitative Methodology, University of Maryland
Abstract: There are some interventions aimed at changing the ways in which individuals interact, and social networks are particularly useful for quantifying these changes. For many of these interventions, the ultimate goal is to change some individual outcome of interest, and social networks act as a natural mediator. For example, in an educational intervention the goal is to change the behavior of students but changes in peer networks are actually the mechanism through which the intervention is effective. In this talk, I will introduce social network models, present a framework modeling social networks as outcomes and mediators and present some recently developed models that embed networks into mediation models.
Data Science in Support of Management of SARS-CoV-2 Community Spread for a Large Metropolitan Area
Wednesday, January 27, 2021
Time: 11:00 a.m.
Speaker: Katherine Bennett Ensor, Noah G. Harding Professor of Statistics, Rice University
Abstract: City and county governments in the greater Houston area have a long history of partnering with research universities in the region to address local challenges. I bring forward several data and statistics intensive projects that improve understanding and management of Covid-19 prevalence in the region. The projects include a regional and national registry, a statistically designed seroprevalence study, carefully curated case count information, and a large temporal and spatial study of viral shedding found in wastewater. I will also discuss the challenges of bringing state-of-the-art science to bear on real-time public health issues.