An alternative estimator for estimating the finite population mean in presence of measurement errors

TL;DR

This paper introduces a new estimator for the finite population mean that accounts for measurement errors, comparing its efficiency with existing estimators through numerical analysis.

Contribution

The paper proposes an alternative estimator that improves estimation accuracy in the presence of measurement errors, enhancing existing methods.

Findings

The new estimator shows lower mean squared error than traditional methods.

Numerical results demonstrate improved efficiency with the proposed estimator.

Comparison indicates better performance in measurement error scenarios.

Abstract

This article presents the problem of estimating the population mean using auxiliary information in the presence of measurement errors. A numerical study is made among the proposed estimator, the exponential ratio estimator, Singh and Solanki (2012) estimator and the mean per unit estimator in the presence of measurement errors. Key words: Population mean, Study variate, Auxiliary variates, Mean squared error, Measurement errors, Efficiency