Open Access
May, 1979 Expected Information as Expected Utility
Jose M. Bernardo
Ann. Statist. 7(3): 686-690 (May, 1979). DOI: 10.1214/aos/1176344689


The normative procedure for the design of an experiment is to select a utility function, assess the probabilities, and to choose that design of maximum expected utility. One difficulty with this view is that a scientist typically does not have, nor can be normally expected to have, a clear idea of the utility of his results. An alternative is to design an experiment to maximize the expected information to be gained from it. In this paper we show that the latter view is a special case of the former with an appropriate choice of the decision space and a reasonable constraint on the utility function. In particular, the Shannon concept of information is seen to play a more important role in experimental design than was hitherto thought possible.


Download Citation

Jose M. Bernardo. "Expected Information as Expected Utility." Ann. Statist. 7 (3) 686 - 690, May, 1979.


Published: May, 1979
First available in Project Euclid: 12 April 2007

zbMATH: 0407.62002
MathSciNet: MR527503
Digital Object Identifier: 10.1214/aos/1176344689

Primary: 62A15
Secondary: 62B10 , 62B15

Keywords: Bayesian statistics , decision theory , Design of experiments , Information , scientific inference , Utility

Rights: Copyright © 1979 Institute of Mathematical Statistics

Vol.7 • No. 3 • May, 1979
Back to Top