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AIMS Mathematics

2021, Volume 6, Issue 5: 5193-5204. doi: 10.3934/math.2021308
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Research article

An efficient modification to diagonal systematic sampling for finite populations

  • 1.
    Department of Statistics, University of Malakand, Chakdara, Lower Dir, Pakistan
  • 2.
    Department of Commerce and Management, University of Malakand, Chakdara, Lower Dir, Pakistan
  • Received: 04 December 2020 Accepted: 07 March 2021 Published: 11 March 2021

  • MSC : 62D05

  • This paper presents a new modified diagonal systematic sampling method for the linear trend situation. For numerical illustration, data from the literature have been used to compare the proposed method's efficiency with some existing sampling schemes. The findings show that the proposed new systematic sampling method is more efficient than the existing sampling schemes. Moreover, the improvement in efficiency has also been shown in the case of a perfect linear trend. Mathematical conditions under which the new method is more efficient than the existing sampling schemes have been derived.

    Citation: Muhammad Azeem, Muhammad Asif, Muhammad Ilyas, Muhammad Rafiq, Shabir Ahmad. An efficient modification to diagonal systematic sampling for finite populations[J]. AIMS Mathematics, 2021, 6(5): 5193-5204. doi: 10.3934/math.2021308

    Related Papers:

  • This paper presents a new modified diagonal systematic sampling method for the linear trend situation. For numerical illustration, data from the literature have been used to compare the proposed method's efficiency with some existing sampling schemes. The findings show that the proposed new systematic sampling method is more efficient than the existing sampling schemes. Moreover, the improvement in efficiency has also been shown in the case of a perfect linear trend. Mathematical conditions under which the new method is more efficient than the existing sampling schemes have been derived.


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  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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