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Journals / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 47 Issue: 1

An efficient new class of estimators of population variance using information on auxiliary attribute in sample surveys

Housila P. Singh
Surya K. Pal
Pages
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Publication Date
2018-02-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The theoretical findings are well supported through an empirical study.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper addresses the problem of estimating the population variance $S_y^2$ of the study variate $Y$ when information on an auxiliary attribute is available.
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Key Findings & Data:We have suggested a new class of estimators for the population variance  $S_y^2$ using information on an auxiliary attribute.
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Conclusion & Impact:The theoretical findings are well supported through an empirical study.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Study variate · Auxiliary attribute · Population variance

Abstract

This paper addresses the problem of estimating the population variance $S_y^2$ of the study variate $Y$ when information on an auxiliary attribute is available. We have suggested a new class of estimators for the population variance  $S_y^2$ using information on an auxiliary attribute. It has been shown that the proposed class of estimators is more efficient than those estimators considered by [16], [19] and [23]. The theoretical findings are well supported through an empirical study.

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Cite This Article

Singh, H. P., Pal, S. K. (2018). An efficient new class of estimators of population variance using information on auxiliary attribute in sample surveys. Hacettepe Journal of Mathematics and Statistics, Volume: 47 Issue: 1. https://ajindex.com/articles/1402981

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References (23)

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