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Variance Estimation Using Linear Combination of Tri-mean and Quartile Average

Received: 22 October 2016    Accepted: 12 January 2017    Published: 9 February 2017
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Abstract

In this paper, we have proposed a class of modified ratio type variance estimator for estimation of population variance of the study variable, when Tri Mean and Quartile average of the auxiliary variable are known. The bias and mean square error (MSE) of the proposed estimator are obtained. From the numerical study it is observed that the proposed estimator performs better than the existing estimators in the literature.

Published in American Journal of Biological and Environmental Statistics (Volume 3, Issue 1)
DOI 10.11648/j.ajbes.20170301.12
Page(s) 5-9
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Simple Random Sampling, Bias, Mean Square Error, Tri-mean, Quartile Average, Auxiliary Variable

References
[1] Cochran, W. G. (194). Sampling Techniques. Third Edition, Wiley Eastern limted.
[2] Gupta, Sat and Shabbir, Javid (2008). Variance estimation in simple random sampling using auxiliary information. Hacettepe journal of Mathematics and Statistics, 37 (1), 57-67.
[3] Ferrell, E. B. (1953). Control charts using Mid-ranges and Medians. Industrial Quality control, 9(5), 30-34.
[4] Isaki, C. T. (1983). Variance estimation using auxiliary information. Journal of the American Statistical Association, 78,117-123.
[5] Kadilar, C. & Cingi, H. (2006). Ratio estimators for population variance in simple and stratified sampling. Applied mathematics and Computation, 173,1047-1058.
[6] Kadilar, C. & Cingi, H. (2007). Improvement in Variance estimation in simple random sampling. Communications in Statistics: Theory and methods, 36,2075-2081.
[7] Murthy, M. N. (1967). Sampling theory and methods. Calcutta Statistical Publishing House, India.
[8] Ogus, J. L., and Clark, D. F. (1971). The annual survey of manufactures: A report on methodology. US bureau of the census technical paper 24, US Government printing office, Washington DC.
[9] Prasad, B., and Singh, H. P. (1990). Some improved ratio type estimators of finite population variance in sample surveys. Communication in Statistics: Theory and methods, 19, 1127-1139.
[10] Maqbool, S., Raja, T. A., and Shakeel Javaid (2016). Generalized modified ratio estimator using non-conventional location parameter, Int. J. Agricult. Stat. Sci, 12 (1), 95-97.
[11] Shapiro, G. M., and Bateman, D. V. (1978). A better alternative to the collapsed stratum variance estimate. Proceedings of the social statistics section, American Statistical Association, 451-456.
[12] Sumramani, J. and Kumarapandiyan, G. (2015). Generalized modified ratio type estimator for estimation of population variance. Sri-Lankan journal of applied Statistics,vol16-1,69-90.
[13] Wolter, K. M. (1985). Introduction to variance estimation. Springer- Verlag.
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  • APA Style

    Showkat Maqbool, Shakeel Javaid. (2017). Variance Estimation Using Linear Combination of Tri-mean and Quartile Average. American Journal of Biological and Environmental Statistics, 3(1), 5-9. https://doi.org/10.11648/j.ajbes.20170301.12

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    ACS Style

    Showkat Maqbool; Shakeel Javaid. Variance Estimation Using Linear Combination of Tri-mean and Quartile Average. Am. J. Biol. Environ. Stat. 2017, 3(1), 5-9. doi: 10.11648/j.ajbes.20170301.12

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    AMA Style

    Showkat Maqbool, Shakeel Javaid. Variance Estimation Using Linear Combination of Tri-mean and Quartile Average. Am J Biol Environ Stat. 2017;3(1):5-9. doi: 10.11648/j.ajbes.20170301.12

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  • @article{10.11648/j.ajbes.20170301.12,
      author = {Showkat Maqbool and Shakeel Javaid},
      title = {Variance Estimation Using Linear Combination of Tri-mean and Quartile Average},
      journal = {American Journal of Biological and Environmental Statistics},
      volume = {3},
      number = {1},
      pages = {5-9},
      doi = {10.11648/j.ajbes.20170301.12},
      url = {https://doi.org/10.11648/j.ajbes.20170301.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbes.20170301.12},
      abstract = {In this paper, we have proposed a class of modified ratio type variance estimator for estimation of population variance of the study variable, when Tri Mean and Quartile average of the auxiliary variable are known. The bias and mean square error (MSE) of the proposed estimator are obtained. From the numerical study it is observed that the proposed estimator performs better than the existing estimators in the literature.},
     year = {2017}
    }
    

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    T2  - American Journal of Biological and Environmental Statistics
    JF  - American Journal of Biological and Environmental Statistics
    JO  - American Journal of Biological and Environmental Statistics
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    AB  - In this paper, we have proposed a class of modified ratio type variance estimator for estimation of population variance of the study variable, when Tri Mean and Quartile average of the auxiliary variable are known. The bias and mean square error (MSE) of the proposed estimator are obtained. From the numerical study it is observed that the proposed estimator performs better than the existing estimators in the literature.
    VL  - 3
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Author Information
  • Division of Agricultural Statistics and Economics, FOA, Wadura, Skuast, Kashmir, India

  • Department of Statistics & O.R., A.M.U., Aligarh, India

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