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Abstract: In this paper, we propose an improved estimator of finite population mean using information on two auxiliary attributes under simple random sampling (SRS) and two-phase sampling schemes. The bias and mean squared error (MSE) expressions of the proposed estimators are obtained up to first order of approximation. It is shown theoretically, that the proposed estimator is more efficient than the ratio-product type estimator, regression estimator, difference type estimator and Malik and Singh (2013) [13] estimator in both SRS and two phase sampling. An empirical study using two data sets is also conducted to support the theoretical findings. [Copyright &y& Elsevier]

Abstract: We propose a two parameter ratio-product-ratio estimator for estimating a finite population variance based on simple random sampling without replacement. The bias and mean square error of the proposed estimator are obtained to the first degree of approximation. We have derived the conditions for the parameters under which the proposed estimator has smaller mean square error than the sample variance, ratio and product estimators. We carry out an application showing that the proposed estimator outperforms the traditional estimators using different data sets. [Copyright &y& Elsevier]