2019International Journal of Business and Data AnalyticsOpen access

Searching efficient estimator of population variance using tri-mean and third quartile of auxiliary variable

Subhash Kumar Yadav, Dinesh Kumar Sharma, S.S. Mishra

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Abstract

This paper concerns with the estimation of population variance of study variable using tri-mean and third quartile of the auxiliary variable.In this study, the sampling properties, bias and mean squared error of the proposed estimator are demonstrated.The justification of the performance of the proposed estimator under SRSWOR has been made with reference to the competing estimators of population variance, the sample variance, Isaki (1983) estimator, the estimator due to Upadhyaya and Singh (1999), Kadilar and Cingi (2006) estimators, Subramani and Kumarapandiyan (2012) estimators, Khan and Shabbir (2013) estimator and Maqbool and Javaid (2017) estimator of population variance.Based on data provided by Murthy (1967), it has been demonstrated that the proposed estimator has shown a significant improvement over all competing estimators of population variance.

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What this paper is about

This paper concerns with the estimation of population variance of study variable using tri-mean and third quartile of the auxiliary variable.In this study, the sampling properties, bias and mean squared error of the proposed estimator are demonstrated.The justification of the performance of the proposed estimator under SRSWOR has been made with reference to the competing estimators of population variance, the sample variance, Isaki (1983) estimator, the estimator due to Upadhyaya and Singh (1999), Kadilar and Cingi (2006) estimators, Subramani and Kumarapandiyan (2012) estimators, Khan and Shabbir (2013) estimator and Maqbool and Javaid (2017) estimator of population variance.Based on data provided by Murthy (1967), it has been demonstrated that the proposed estimator has shown a significant improvement over all competing estimators of population variance.

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Available abstract

This paper concerns with the estimation of population variance of study variable using tri-mean and third quartile of the auxiliary variable.In this study, the sampling properties, bias and mean squared error of the proposed estimator are demonstrated.The justification of the performance of the proposed estimator under SRSWOR has been made with reference to the competing estimators of population variance, the sample variance, Isaki (1983) estimator, the estimator due to Upadhyaya and Singh (1999), Kadilar and Cingi (2006) estimators, Subramani and Kumarapandiyan (2012) estimators, Khan and Shabbir (2013) estimator and Maqbool and Javaid (2017) estimator of population variance.Based on data provided by Murthy (1967), it has been demonstrated that the proposed estimator has shown a significant improvement over all competing estimators of population variance.

Key concepts: Statistics, Quartile, Estimator, Variance (accounting), Mathematics, Minimum-variance unbiased estimator, Variable (mathematics), Population

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