Peer-Reviewed Academic Journal
Continental Journal of Applied Sciences
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IMPROVED CLASS OF RATIO-TYPE ESTIMATOR UNDER DOUBLE SAMPLING

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Abstract

 In this paper we have proposed a class of ratio -type estimator under double sampling to estimate the population mean of the characteristic under study. The expression for bias and the mean square error of the proposed estimator have been derived up to the first order of approximation. The proposed estimator includes a number of ratio -type estimator under double sampling, thus we have discussed its particular cases and their  mean square error have also been compared theoretically with the  mean square error of the proposed estimators and conditions are found under which the proposed estimator is more efficient. Numerical illustration has been carried out to observe the efficiency of proposed estimator.

Keywords

#Bias #Double Sampling #Efficiency #Estimator #Mean square error
Publication Date May 21, 2026
Digital Object Identifier (DOI) Registered
Journal Volume & Issue Vol 10