Colin Rundel

 

 


 

Colin Rundel is an Assistant Professor of the Practice in the Department of Statistical Science at Duke University. He received his Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Biology from the California Institute of Technology. Dr. Rundel's research interests include spatial and computational statistics with an emphasis on applied biological and ecological problems. Recent work has included modeling the migratory pathways of North American songbirds, large scale fusion models of air pollution, and models for the detection of landmines and IEDs through the integration of multiple sensors. He is also interested in improving computational pedagogy within the statistics curriculum - with a particular focus on training statisticians to produce high quality, reproducible software products as a natural byproduct of the analysis workflow.




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Dec 12th 2016

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm.

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