On estimation and monitoring of population mean using systematic sampling under an exponentially weighted moving average scheme

The present study proposes a generalized ratio estimator for estimating the population mean under the systematic sampling technique by considering auxiliary information and auxiliary attribute. Its bias and Mean Square Error (MSE) expressions have been derived. Mathematical comparisons are made by comparing the proposed estimator with the usual mean estimator, Swain (1964) estimator, Bhal and Tuteja (1991) estimator, and Singh and Singh (1998) estimator, and it is shown that the proposed estimator is more efficient than the previous estimators. A numerical comparison is also performed to demonstrate the superiority of the proposed estimator over the traditional estimators. The technique of ratio estimators based on systematic sampling is used to design an Exponentially Weighted Moving Average (EWMA) control chart. The Control chart is a significant industrial tool for monitoring the process mean. To evaluate performance efficiency Average run lengths (ARL) are obtained in this study. The proposed charts are compared based on out-of-control ARLs. A chart based on the proposed estimator is superior as it detects the shifts earlier than charts based on existing estimators. Empirical work is done to support the study. The suggested efficiency is further addressed utilizing real-life examples and simulations using R-Studio.