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Bayesian Cherry Picking Revisited

2004 
Tins are marketed as containing nine cherries. To fill the tins, cherries are fed into a drum containing twelve holes through which air is sucked; either zero, one or two cherries stick in each hole. Dielectric measurements are then made on each hole. Three outcomes are distinguished: empty hole (which is reliable); one cherry (which indicates one cherry with high probability, or two cherries with a complementary low probability known from calibration); or an uncertain number (which also indicates one cherry or two, with known probabilities that are quite similar). A choice can be made from which holes simultaneously to discharge contents into the tin. The sum and product rules of probability are applied in a Bayesian manner to find the distribution for the number of cherries in the tin. Based on this distribution, ways are discussed to optimise the number to nine cherries.
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