Who Makes Mistakes? Using Data Mining Techniques to Analyze Reporting Errors in Total Acres Operated

Jaki S. McCarthy and Morgan S. Earp

No 234367, NASS Research Reports from United States Department of Agriculture, National Agricultural Statistics Service

Abstract: Classification trees were used to identify subgroups of respondents with higher error rates when reporting total acres operated on the 2002 Census of Agriculture. Separate trees were grown for operations exhibiting total acres summation errors, missing data, and nonequivalent sums of reported total acres. Terminal tree nodes demonstrating the greatest frequency of total acres operated errors identify characteristics of respondents and or operations that are more likely to make errors, suggest possible reasons for errors, identify content for future tests of alternative questionnaires and suggest ways to appropriately edit these items. Advantages of using classification trees over other analytic methods are also discussed.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 28
Date: 2009-04
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Persistent link: https://EconPapers.repec.org/RePEc:ags:unasrr:234367

DOI: 10.22004/ag.econ.234367

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