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  Bayesian Statistics Working Group (BSWG)  
Department of Statistics, NC State University
 
 
Thomas Bayes
   Bayesian Inference is a paradigm in Statistics that attempts to utilize all available information in decision-making. Prior knowledge coming from experience, expert judgment, or previously collected data is used with current data to characterize the current state of knowledge. These methods allow the use of models of complex physical phenomena that were previously too difficult to estimate. Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models of behavior that can be estimated with limited amounts of data.    Read a recent article in NY Times  
  The Bayes Rule: Bayes Rule  

Group Activitivies
  This group meets every 2-3 to discuss and work on statistical problems of mutual interest in the area of Bayesian inference, host seminars, and study current methodological developments in parameteric and nonparamteric Bayesian methods. The topics would range from very applied in practice to theoretical aspects of Bayesian inference.

Meetings are informal, and all interested faculty and students are encouyraged to participate. The relevant articles will be posted at this site from time to time. This site will also list the publications that would result from this forum on Bayesian Statistics.

This semester, we will meet at 1108 SAS Hall on the NCSU campus on the following days:
Jan 17; Feb ?, Mar ? and Apr ? at 4:00pm - 5:00PM.
Students are encouraged to meet with the seminar speakers at 3:00pm-3:45pm in 5104 SAS Hall ("5th floor commons") and may sign-up online
 

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