Estimation of finite population mean in presence of maximum and minimum values under systematic sampling scheme

Estimators for the finite population mean of the research variable are proposed in this article, employing ratio, product, and regression type estimators, all of which need just one auxiliary variable. A first-order approximation is developed for the mean squared errors of the techniques provided. It has been proven theoretically that the suggested estimators perform better than current estimators, and these theoretical conditions have been validated numerically using four data sets.