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An Unbiased Estimator of the Variance of Simple Random Sampling Using Mixed Random-Systematic Sampling

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  • Padilla Alberto

Abstract

Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. By means of a mixed random - systematic sample, an unbiased estimator of the population variance for simple random sample is proposed without model assumptions. Some examples are given.

Suggested Citation

  • Padilla Alberto, 2009. "An Unbiased Estimator of the Variance of Simple Random Sampling Using Mixed Random-Systematic Sampling," Working Papers 2009-13, Banco de México.
    • Handle: RePEc:bdm:wpaper:2009-13
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    File URL: https://www.banxico.org.mx/publications-and-press/banco-de-mexico-working-papers/%7B5263D7B3-DB7E-7507-382F-59885C24344B%7D.pdf
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    References listed on IDEAS

    as
    1. Kuo-Chung Huang, 2004. "Mixed random systematic sampling designs," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(1), pages 1-11, February.
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    More about this item

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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