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SUMMARY. When the experimental or sampling units in a study can be more easily ranked than quantified, McIntyre (1952) observed that to estimate the population mean, the mean of n units based on a ranked set sample (RSS) provides an unbiased estimator with a smaller variance compared to a simple random sample of the same size n. In this paper we further explore the concept of RSS for the problem of estimation of a lognormal mean with a known coefficient of variation, and show that the use of RSS and its suitable modifications results in much improved estimators compared to the use of a simple random sample. 1.
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SUMMARY. When the experimental or sampling units in a study can be more easily ranked than quantified, McIntyre (1952) observed that to estimate the population mean, the mean of n units based on a ranked set sample (RSS) provides an unbiased estimator with a smaller variance compared to a simple random sample of the same size n. In this paper we further explore the concept of RSS for the problem of estimation of a lognormal mean with a known coefficient of variation, and show that the use of RSS and its suitable modifications results in much improved estimators compared to the use of a simple random sample. 1.
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