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An Optimal Sampling Strategy for Large Unistage Samples

  • K. R. W. Brewer
  • Muhammad Hanif
Part of the Lecture Notes in Statistics book series (LNS, volume 15)

Abstract

The sampling strategy to be described in this Chapter (Brewer, 1979) was devised for use in the context of large-scale surveys of populations containing units of very different sizes, such as official surveys of establishments and enterprises. Because the samples required are large, asymptotic theory is appropriate. However, the sample may be a significant proportion of the population, and consequently the finite population correction is allowed for.

Keywords

Ratio Estimation Good Linear Unbiased Predictor Fair Approximation Stratify Sampling Scheme Size Stratification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1983

Authors and Affiliations

  • K. R. W. Brewer
    • 1
  • Muhammad Hanif
    • 2
  1. 1.c/o Commonwealth Schools CommissionWoden, CanberraAustralia
  2. 2.Department of StatisticsEl-Fateh UniversityTripoliLibya (S.P.L.A.J.)

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