Improved ratio estimators for the population mean using non-conventional measures of dispersion

In recent times,it is common to the make use of auxiliary information to increase the precision of estimators in sample surveys. in this study,we propose some new modified linear regression type ratio estimators for estimating population mean by some non-conventional dispersion measures such as: gini's mean difference,downton's method and probability weighted moments with linear combination of population correlation coefficient and population coefficient of variation. expressions for the bias and the mean squared error are derived and are compared with those of the usual ratio estimator and the existing ratio type estimators in literature. conditions are determined for which the proposed estimators perform better than the existing estimators. both theoretical and empirical findings show the soundness of the proposed procedure for estimation of population mean.