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2016•Unpublished venueRequires access

Estimation of Finite Population Mean Using Auxiliary Attribute in Sample Surveys

Rajesh Singh, Poonam Singh, Nitesh Kumar Adichwal

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Abstract

This article presents improved estimation of population mean using auxiliary attribute. The bias and mean square error of proposed estimators are obtained up to first order of approximation and it is shown that proposed class of estimator under optimum conditions is more efficient than the other estimators considered in this article. The theoretical results are supported by empirical study considering two data sets.

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What this paper is about

This article presents improved estimation of population mean using auxiliary attribute. The bias and mean square error of proposed estimators are obtained up to first order of approximation and it is shown that proposed class of estimator under optimum conditions is more efficient than the other estimators considered in this article. The theoretical results are supported by empirical study considering two data sets.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This article presents improved estimation of population mean using auxiliary attribute. The bias and mean square error of proposed estimators are obtained up to first order of approximation and it is shown that proposed class of estimator under optimum conditions is more efficient than the other estimators considered in this article. The theoretical results are supported by empirical study considering two data sets.

Key concepts: Estimator, Mean squared error, Population mean, Statistics, Mathematics, Sample mean and sample covariance, Population, Estimation

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