Without having to interview every person, we may draw conclusions about the whole population by estimating the population mean, a fundamental summary statistic that is obtained from a sample. For example, using a sample to estimate the population's mean income, height, or academic achievement may provide crucial information that supports sociological study, strategic business choices, and government. In order to enhance the estimate of a population mean, this article proposes a ratio-cum-product exponential estimator. This estimator makes use of additional information gathered from two transformed auxiliary variables that have been collected within the setting of simple random sampling without replacement. The suggested estimator's bias and mean squared error are articulated up to the first degree of approximation. This is done in order to validate accuracy. Additionally, we conduct empirical and thorough simulation studies, demonstrating that the proposed estimators consistently surpasses its competitors.
Singh et al. (Sun,) studied this question.