A manuscript with an unknown random number M of misprints is subjected to a series of proofreadings in an effort to detect and correct the misprints. On the nth proofreading, each remaining misprint is detected independently with probability pnÅ-1. Each proofreading costs an amount Cp>0, and if one stops after n proofreadings, each misprint overlooked costs an amount cn>0. Two models are treated based on the distribution of M. In the Poisson model, the optimal stopping rule is seen to be a fixed sample size rule. In the binomial model, the myopic rule is optimal in many important cases. A generalization is made to problems in which individual misprints may have distinct probabilities of detection and distinct overlook costs.
