An Alternative Family of Combined Estimators for Estimating Population Mean in Finite Populations

Abstract An alternative family of combined estimators for estimating population mean has been proposed under simple random sampling without replacement. A known auxiliary variable is used to improve the efficiency of the new estimators. The bias and mean square error of the proposed estimator has been obtained up to the first order of approximation using the Taylor series. The proposed family of combined estimators performs better than the existing estimators in a simulation study using the percentage relative efficiency especially for small sample sizes which saves time and money for researchers.