Journal Article

Use of Unknown Weight to Enhance Ratio-Type Estimator in Simple Random Sampling

Abstract

In this paper, a ratio-type estimator of finite population mean has been proposed. The proposed estimator was obtained by transforming Gupta and Yadav (2018) estimator. The main purpose of this study is to develop a new and efficient estimator to improve the precision of estimation of population mean in sample random sampling without replacement. The properties of the proposed estimator namely Bias and Mean Square Error were obtained up to first order of approximation using Taylor’s Series expansion and the condition for its efficiency over some existing estimators was also established. The efficiency of proposed estimator exhibits significant improvement over the estimators considered in the study. The results of the empirical study show that the proposed estimator is more efficient than existing estimators based on the comparison criteria measures.

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