On an Alternative Estimator in One-Stage Cluster Sampling Using Finite Population
Lukman Abiodun Nafiu

Abstract
This paper investigates the use of a one-stage cluster sampling design in estimating the population total. We focus on a special design where certain number of visits is being considered for estimating the population size and a weighted factor of / is introduced. In this study,we proposed a new estimator and compared it with some of the existing estimators in a one-stage sampling design. Eight (8) data sets were used to justify this paper and computation was done with software developed in Microsoft Visual C++ programming language. For all the populations considered, the bias and variance of our proposed estimator are the least among all estimators compared. All the estimated population totals are also found to fall within the computed confidence intervals for α = 5%. The coefficients of variations obtained for the estimated population totals using both illustrated and life data show that our newly proposed estimator has the least coefficient of variation. Therefore, our newly proposed estimator ( ) is recommended when considering a one-stage cluster sampling design.

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