Evaluating The Performances of Estimators of Population Mean Weight of Babies in FMC, Imo State Under Simple Random Sampling Scheme

Authors

  • Emmanuel John Ekpenyong

    Michael Okpara University of Agriculture, Umudike, Umuahia, Abia state, Nigeria. P.M.B. 7267, Umuahia, Abia State.
    Author

DOI:

https://doi.org/10.4314/cv6wxn94

Keywords:

Efficiency, Bias, Mean Squared Error, Estimator, Simple Random Sampling

Abstract

Authors: Loveline Chiamaka Okoro and Emmanuel John Ekpenyong

Gestational age plays a vital role in obstetrics. Accurately estimating the average gestational age in pregnant women will help ascertain the growth of the fetus and it is also essential in structuring prenatal care, including decisions about timing and route of delivery. . This study compares the efficiency of some existing estimators of population mean using simple random sampling scheme. The estimators were compared using a real data on gestational age incorporating the weight of babies as auxiliary variable. Three samples of (n = 100, 150, 200) were selected from the population for the analysis. Of all the estimators compared, result showed that the classical regression estimator t6  and Kadilar (2016) estimator which approximates to the regression estimator are equally efficient and also proved to be the most efficient estimators with a lowest mean squared errors and highest percent relative efficiencies. Thus t4, and t6 can used to estimate the population mean of the auxiliary variable in practice.

Author Biography

  • Emmanuel John Ekpenyong, Michael Okpara University of Agriculture, Umudike, Umuahia, Abia state, Nigeria. P.M.B. 7267, Umuahia, Abia State.

    Department of Statistics

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Published

2024-11-14

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