Abstract
Randomization is a generally accepted principle of sound experimental design and common practice among working scientists. But Bayesian statisticians reject it, most often because of decision theoretic argument against randomization. I trace it back to Abraham Wald's Theory of Inductive Behavior and argue that Bayesians should concur with Ronald Fisher 's criticism of Wald's analysis of randomization. The paper ends with a Bayesian argument in favor of randomization: randomization can lead to an increase in expected utility
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