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General Class of Estimators of Population Variance in Stratified Random Sampling

Nursel Koyuncu

Abstract


This study proposes two classes of variance estimators for estimating population variance of a study variable using information of auxiliary variable under stratified random sampling scheme. The bias and mean square error of the estimators belonging to classes are obtained and the optimum parameters of classes are given in stratified random sampling. Efficiency comparison is carried out using a real data set. In this data set, sales profit and waste product of a company are used as a study and auxiliary variable respectively. Moreover we have found that suggested classes of estimators are more efficient than classical estimators.

Keywords


Ratio estimator; auxiliary information; mean square error; efficiency.

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