ESTIMATION OF FINITE POPULATION MEAN IN STRATIFIED RANDOM SAMPLING USING NON- CONVENTIONAL MEASURES OF DISPERSION

Authors

  • Mir Subzar Division of Agricultural Statistics, SKUAST-Kashmir, India
  • S. Maqbool Division of Agricultural Statistics, SKUAST-Kashmir, India
  • T. A. Raja Division of Agricultural Statistics, SKUAST-Kashmir, India
  • M. A. Bhat Division of Agricultural Statistics, SKUAST-Kashmir, India

Keywords:

Non-Conventional Measures of Dispersion, Ratio Estimators, Stratified Random Sampling, Mean Square Error, Efficiency

Abstract

The present study was taken into consideration to suggest a proficient class of estimators for predetermined population mean of variable of interest in stratified random sampling by utilizing the auxiliary information of robust measures such as Gini’s Mean Difference, Downton’s Method and Probability Weighted Moments. Asymptotic properties such as bias and mean square error of the proposed class of estimators have been derived using Taylor series method upto first degree of approximation. In the support of the theoretical proposed work we have given numerical illustration and from this we conclude that our proposed class of estimators performs better than existing estimators.

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References

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Published

2018-06-10

How to Cite

Subzar, M. ., Maqbool, S. ., Raja, T. A. ., & Bhat, M. A. . (2018). ESTIMATION OF FINITE POPULATION MEAN IN STRATIFIED RANDOM SAMPLING USING NON- CONVENTIONAL MEASURES OF DISPERSION. Journal of Reliability and Statistical Studies, 11(01), 83–92. Retrieved from https://journals.riverpublishers.com/index.php/JRSS/article/view/20905

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