Separate Ratio Estimator Using Calibration Approach for the Population mean in Stratified Random Sampling

In this paper we investigate the problem of estimation finite population mean using auxiliary information. The aim is to modify a separate ratio estimator by calibration approach for stratified random sampling. We use improve precision estimate parameter incorporating chi-square distance function minimize between original design weight and new weight. two constraints called equations find weights. Taylor’s linearization technique approximate square (MSE) proposed up first degree approximation. conduct simulation study assess efficiency based on an artificially generated data set. An empirical has also been conducted judge merits estimator, which shows that performs better than [9] usual estimator.