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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
An empirical study is also carried out to judge the merits of the proposed estimator over other existing estimators of population variance using natural data set.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper we have proposed some ratio-type estimators of finite population variance using known values of parameters related to an auxiliary variable such as quartiles with their properties in simple random sampling.
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Key Findings & Data:The suggested estimators have been compared with the usual unbiased and ratio estimators and the estimators due to [2], [12, 13, 14] and [3].
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Conclusion & Impact:An empirical study is also carried out to judge the merits of the proposed estimator over other existing estimators of population variance using natural data set.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Study variable · Auxiliary variable · Bias
Abstract
In this paper we have proposed some ratio-type estimators of finite population variance using known values of parameters related to an auxiliary variable such as quartiles with their properties in simple random sampling. The suggested estimators have been compared with the usual unbiased and ratio estimators and the estimators due to [2], [12, 13, 14] and [3]. An empirical study is also carried out to judge the merits of the proposed estimator over other existing estimators of population variance using natural data set.
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Cite This Article
Pal, S. K., Solanki, R. S., Singh, H. P. (2022). Improved ratio-type estimators of finite population variance using quartiles. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 3, 747–754. https://ajindex.com/articles/530268