Advancing Survey Sampling Efficiency under Stratified Random Sampling and Post-Stratification: Leveraging Symmetry for Enhanced Estimation Accuracy in the Prediction of Exam Scores

• Published in: Symmetry (Basel) Vol. 16; no. 5; p. 604
• Main Authors: Triveni, Gullinkala Ramya Venkata, Danish, Faizan, Albalawi, Olayan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-05-2024
• Subjects: Accuracy; Bias; cumulative distribution function; Distribution (Probability theory); Distribution functions; Educational evaluation; Efficiency; Error analysis; Estimators; Forecasts and trends; Literature reviews; Mathematical analysis; Methods; percentage relative efficiency; Population distribution; post-stratification; Random sampling; Sample size; Stratification; stratified sampling; Students; Surveys; Symmetry; Variables
• ISSN: 2073-8994; 2073-8994
• DOI: 10.3390/sym16050604

This pioneering investigation introduces two innovative estimators crafted to evaluate the finite population distribution function of a study variable, employing auxiliary variables within the framework of stratified random sampling and post-stratification while emphasizing symmetry in the sampling process. The derivation of mathematical expressions for bias and the mean square error up to the first degree of approximation fortifies the credibility of the proposed estimators. Drawing from three distinct datasets, including real-world data capturing student behaviors and exam performances from 500 students, this research highlights the superior efficiency of the proposed estimators compared to existing methods across both sampling schemes. Employing the proposed estimator, we effectively forecast students’ exam scores based on their study hours, backed by empirical evidence showcasing its precision in terms of mean square error and percentage relative efficiency. This study not only introduces inventive solutions to enduring challenges in survey sampling but also provides practical insights into enhancing predictive accuracy in educational assessments.