|An organization was sampling a small area. When they calculated the "K+Z" value to control sample size, it was less than many of the estimated volumes. How could they solve this problem without getting into complicated statistics, biased answers or smaller sample sizes?||of the lists, and choose as a sample
tree if the estimate is larger than (or equal to) the number on either list. In the rare
instance where the tree is chosen by both lists, use that sample tree ratio twice in the
This technique allows you to create a list having a K+Z value larger than any single estimate, but still have the desired sample size. The logic could of course be extended to 3, 4, or more lists if necessary. This is a simple field solution requiring no statistical, programming or compilation changes.
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