We have found that difference-cum-ratio estimator is always more efficient than regression estimator and both of the estimators are considerable efficient than existing estimators.
📌 3 Key Takeaways
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Objective & Hypothesis:This paper suggests difference-cum-ratio and exponential type estimators of population mean using first or third quartiles and mean of auxiliary variable under median ranked set sampling scheme and we have extended our study in double sampling scheme when the population parameters are unknown.
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Key Findings & Data:Empirical studies have been done to demonstrate the efficiency of proposed estimators over the existing estimators.
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Conclusion & Impact:We have found that difference-cum-ratio estimator is always more efficient than regression estimator and both of the estimators are considerable efficient than existing estimators.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Median ranked set sampling · Exponential estimator · Ratio estimator
Abstract
This paper suggests difference-cum-ratio and exponential type estimators of population mean using first or third quartiles and mean of auxiliary variable under median ranked set sampling scheme and we have extended our study in double sampling scheme when the population parameters are unknown. The bias and mean square error of estimators are derived by theoretically both of sampling designs. Empirical studies have been done to demonstrate the efficiency of proposed estimators over the existing estimators. We have found that difference-cum-ratio estimator is always more efficient than regression estimator and both of the estimators are considerable efficient than existing estimators.
Koyuncu, N. (2016). New difference-cum-ratio and exponential type estimators in median ranked set sampling. Hacettepe Journal of Mathematics and Statistics, Volume: 45 Issue: 1. https://ajindex.com/articles/1403203