This study examines a new set of estimators using stratified random sampling to estimate the finite population mean.The research forms a comprehensive class of estimators by using additional data from extremely thoroughly correlated auxiliary variables.The properties of these estimators, including their biases and mean square errors, Checkmate Chair / Side Table have been rigorously analyzed via numerical and simulation contemplation.As compared to the existing estimators, our suggested ones are more Sweatshirts efficient and have a reduced minimum mean square error (MSE).These indicate that it is functioning adequately.
Our proposed estimator is the most effective, according to a comparison study with other methods already in use.The results of this investigation will be useful for improving survey sampling methods in the future.