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In this article an efficient class of estimators for estimating finite population variance has been proposed using auxiliary information in simple random sampling. The bias and mean squared error of the proposed estimator is obtained up to the first degree of approximation. It has been shown that the proposed estimator is more efficient than usual unbiased estimator, Isaki (J. Am. Stat. Assoc.78:117-123, 1983), Kadilar and Cingi (Appl. Math. & Comput., 173, 1047-1059, 2006) and Upadhyaya and Singh (Vikram Math. J. 19, 14-17, 1999a). To judge the merits of the proposed estimator, we consider one numerical example.


Mean squared error Bias Auxiliary information ratio-cum-product estimators

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Author Biographies

Hilal A. Lone, Vikram University Ujjain

School of Studies in Statistics , Vikram University Ujjain (M.P.) India

Research Scholar in SS in statistics Vikram university

Rajesh Tailor, Vikram University Ujjain (M.P.) India

School of Studies in Statistics Vikram University Ujjain (M.P.) IndiaReader In SS in statistics ,Vikram University Ujjain
How to Cite
Lone, H. A., & Tailor, R. (2015). A Family of Estimators for Estimating Population Variance Using Auxiliary Information in Sample Survey. Pakistan Journal of Statistics and Operation Research, 11(2), 213-220.