Regress Exponential Estimators for Estimating the Population Mean via Auxiliary Attribute

This research manuscript is an attempt to propose regress exponential estimators to estimate the population mean of study character utilizing auxiliary attribute by adopting the strategies of Kadilar and Cingi (2004). The bias (13) and mean square error (MSE) of the proposed estimators are obtained up to the first order of approximation. Conditions for getting the minimum mean square error of the proposed estimators are derived and hence the minimum value of mean square errors is obtained. Comparisons of suggested estimators are made theoretically with all related estimators and are supported by the empirical study based on real data sets.