Forest rangers at a national park want to take a sample of trees to estimate what proportion of trees in the park are infected with a certain disease. The population of trees in question is divided by a creek. East of the creek, most of the trees are oak. West of the creek, most trees are cedar, which are more likely to be infected. The rangers are considering taking a stratified random sample using each side of the creek as strata. They'll sample trees from each side proportionately based on the total number of trees on each side. Why might the rangers choose stratification instead of a simple random sample to estimate the proportion of infected trees?

Question

Francisco Carrillo

Mathematics

10 August, 14:04

Forest rangers at a national park want to take a sample of trees to estimate what proportion of trees in the park are infected with a certain disease. The population of trees in question is divided by a creek. East of the creek, most of the trees are oak. West of the creek, most trees are cedar, which are more likely to be infected. The rangers are considering taking a stratified random sample using each side of the creek as strata. They'll sample trees from each side proportionately based on the total number of trees on each side. Why might the rangers choose stratification instead of a simple random sample to estimate the proportion of infected trees?

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Olive Dorsey · Answer 1

In the use of repeated sampling, the estimates from this sort of stratified sample would likely vary less than estimates from simple random samples. the use of stratified random sample is important because it reduces the likelihood of getting disproportionate numbers of cedar or oak trees in the sample.