Bayesian Modeling for Socio-Environmental Data

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Award Year: 
Principal Investigator: 
Tom Hobbs, Colorado State University
Mary Collins, SUNY-ESF
Christian Che-Castaldo, University of Maryland

Solutions to pressing environmental problems require understanding connections between human and natural systems. Analysis of these systems requires models that can deal with complexity, are able to exploit data from multiple sources, and are honest about uncertainty that arises in different ways. Synthesis of results from multiple studies is often required. Bayesian hierarchical models provide a powerful approach to analysis of socio-environmental problems that are complex and that require synthesis of knowledge.

The National Socio-Environmental Synthesis Center (SESYNC) will host a nine-day short course August 19–28, 2015 covering basic principles of using Bayesian models to gain insight from data. The goals of the course are to:

  1. Provide a principles-based understanding of Bayesian methods needed to train students, evaluate papers and proposals, and solve research problems.
  2. Communicate the statistical concepts and vocabulary needed to foster collaboration between ecologists, social scientists, and statisticians.
  3. Provide the conceptual foundations and quantitative confidence needed for self-teaching modern analytical methods.
Maura Allaire, University of North Carolina at Chapel Hill
Alec Armstrong, SESYNC, University of Maryland
Thomas Barnum, Smithsonian Environmental Research Center
Noelle Beckman, SESYNC
Isabella Bertani, University of Michigan
Anne Bjorkman, German Centre for Integrative Biodiversity Research (iDiv)
Philipp Boersch-Supan, University of South Florida
Jessica Brown, University of Nevada, Reno
Fabian Casas Arenas, University of Maryland
Avery Cohn, Tufts University
Sean Downey, University of Maryland
Rachel Gittman, Northeastern University
Louise Glew, WWF
Allison Howard, University of Maryland
Elizabeth Lee, Georgetown University
Morgan Levy, University of California, Berkeley
Dan MacNulty, Utah State University
Kumar Mainali, University of Maryland
Michael McCann, Rutgers University
Rebecca Murphy, Chesapeake Bay Program
Rebecca Selden, Rutgers University
Nyssa Silbiger, University of Hawai'i at Manoa
Jessica Stanton, U.S. Geological Survey
Jenny Zambrano, SESYNC
Associated SESYNC Researcher(s): 
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