Small Area Estimation of Population Parameter under Stratified Sampling

A discipline of statistics known as small-area estimation (SAE) combines survey sampling and statistical models with finite population inference. Applications for SAE in statistics include the estimation of health statistics, the estimation of under-coverage in the census, the estimation of unemployment rates, the estimation of crop yield in agriculture, or the planning of agricultural development for rapidly increasing production, among numerous others. Using modified ratio cum regression type estimators and modified product cum regression type estimators in stratified sampling, it is suggested in this article that the population mean can be estimated for a small area using data on a single auxiliary variable. The effectiveness of the proposed estimator in comparison to the current estimators is tested, and the findings are demonstrated statistically and empirically to support the superiority of the proposed estimators.