A Class of Regression Estimator with Cum-Dual Ratio Estimator as Intercept

This paper examines a class of regression estimator with cum-dual ratio estimator as intercept for estimating the mean of the study variable Y using auxiliary variable X. We obtained the bias and the mean square error of the proposed estimator, also, the asymptotically optimum estimator (AOE) was obtained along with its mean square error. Theoretical and numerical validation of the proposed estimator were done to show it’s superiority over the usual simple random sampling estimator and ratio estimator, product estimator, cum-dual ratio and product estimator. It was found that the estimator while performed better than other competing estimators, performed in almost the same way as the usual regression estimator when compared with the usual simple random estimator for estimating the average sleeping hours of undergraduate students of the department of statistics, Federal University of Technology Akure, Nigeria.