As increasingly much background information becomes available to scientists undertaking an investigation, it is important to utilize previous knowledge effectively in designing studies and analyzing data. Bayesian statistical methods are tailored to this computation, but scientific meetings rarely spend substantial time discussing applications of Bayesian statistics. The goal is to elucidate the interplay between theory and practice and thereby identify successful methods and indicate important directions for future research.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Type
Standard Grant (Standard)
Application #
9300997
Program Officer
Jean Thiebaux
Project Start
Project End
Budget Start
1993-05-15
Budget End
1995-04-30
Support Year
Fiscal Year
1993
Total Cost
$15,000
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213