Improved Mean Estimation for a Finite Population with Twofold Auxiliary Variables Under Simple Random Sampling

The goal of this article is to suggest an improved estimator for assessing the mean of a population using a twofold auxiliary variable under simple random sampling. To the first order of approximation, the numerical expression of the bias and mean square error are derived. We use actual data sets and simulation study to measure the efficiency of the suggested estimator. The efficiency of the suggested estimator is evaluated relative to the preliminary estimators using the MSE criterion. An empirical investigation strengthens up the theoretical findings. Theoretical analysis reveals that the suggested estimator performs better as compared to existing counterparts. The outcome of actual data and a simulation study stated the proposed estimator performs better as compared to minimum MSE and higher PRE compared to existing estimators.