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INFORMATION THROUGH SAMPLING FROM A BINOMIAL DISTRIBUTION *
Author(s) -
Philippatos George C.,
Gressis Nicolas
Publication year - 1973
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1973.tb00982.x
Subject(s) - beta binomial distribution , measure (data warehouse) , binomial distribution , variance (accounting) , statistics , negative binomial distribution , mathematics , limiting , binomial (polynomial) , sampling (signal processing) , sample (material) , computer science , distribution (mathematics) , econometrics , data mining , poisson distribution , mathematical analysis , mechanical engineering , chemistry , accounting , filter (signal processing) , chromatography , computer vision , engineering , business
Lindley's measure of experimental information is utilized to determine the optimal sample‐size that is required to obtain a prescribed level of accuracy about the parameter of a binomial distribution. The measure is expressed through its approximate limiting relationship to the posterior variance of the parameter, and a simple application of the methodology is presented.