Enriched Ratio-Cum-Product Estimator Utilizing Ancillary Attribute for Double Sampling

The utilization of auxiliary attribute information in survey sampling is a fundamental aspect of improving the precision and efficiency of estimators. In this paper, we delve into the concept and application of the ratio-cum-product estimator, which integrates auxiliary information with the survey data. We explore the theoretical foundation of the estimator and discuss its advantages over traditional estimators. Additionally, we provide a detailed illustration of its implementation in survey sampling, emphasizing its efficacy in various practical scenarios. Through this paper, we aim to showcase the significance of incorporating auxiliary attribute information in estimation techniques for more accurate and reliable results. Ratio-cum-Product estimator of population mean using auxiliary attribute is applicable where correlations between the variable of interest and auxiliary attribute are positive or negative. The efficiency depends on the optimum estimate of arbitrary constant (β) which is usually a function of variable of interest and auxiliary attribute.