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Identifying Data Affected by Aberrant Errors. Applied Program

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  • Mihai-Radu COSTESCU

Abstract

Statistical survey has become a very powerful tool for understanding reality and interpreting it and prediction. Nevertheless, even with the accepted margin for errors, a survey’s results may be inconcludent. This is mostly due to sample data quality. In this article, we refer to two tests to identify and eliminate aberrant errors, and at the end we present a program for applying these tests.

Suggested Citation

  • Mihai-Radu COSTESCU, 2008. "Identifying Data Affected by Aberrant Errors. Applied Program," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 0(1), pages 52-55.
    • Handle: RePEc:aes:infoec:v:xii:y:2008:i:1:p:52-55
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    Cited by:

    1. Edson Kogachi & Adonias Ferreira & Carlos Cavalcante & Marcelo Embiruçu, 2021. "Development of Performance Evaluation Indicators for Table Grape Packaging Units. 2. Global Indexes," Sustainability, MDPI, vol. 13(11), pages 1-16, June.

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    Keywords

    Chauvenet; Young; program;
    All these keywords.

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