Finite Population Mean Estimation Under Systematic Sampling Scheme in Presence of Maximum and Minimum Values Using Two Auxiliary Variables

The purpose of this paper is to look at how to estimate the finite population mean utilizing information from the auxiliary variable on a systematic sampling technique. By integrating the study variable's maximum and minimum values, as well as two auxiliary variables, we offer estimators of the ratio, product, and regression types. The mathematical equations of the suggested and existing estimators are derived up to the first order of approximation. Based on real-life data sets, efficiency comparisons are carried out. The suggested ratio, product and regression estimators consistently outperform existing estimators in terms of mean square error, according to theoretical and empirical investigations.