Non-sampling error

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In statistics, non-sampling error is a catch-all term for the deviations of estimates from their true values that are not a function of the sample chosen, including various systematic errors and random errors that are not due to sampling.[1] Non-sampling errors are much harder to quantify than sampling errors.[2]

Non-sampling errors in survey estimates can arise from:[3]

  • Coverage errors, such as failure to accurately represent all population units in the sample, or the inability to obtain information about all sample cases;
  • Response errors by respondents due for example to definitional differences, misunderstandings, or deliberate misreporting;
  • Mistakes in recording the data or coding it to standard classifications;
  • Other errors of collection, nonresponse, processing, or imputation of values for missing or inconsistent data.[3]

See also[edit]

References[edit]

  1. ^ Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9
  2. ^ Fritz Scheuren (2005). "What is a Margin of Error?", Chapter 10, in "What is a Survey?", American Statistical Association, Washington, D.C. Accessed 2008-01-08.
  3. ^ a b U.S. Census Bureau. March 2012. Introduction. Quarterly Financial Report for Manufacturing, Mining, Trade, and Selected Service Industries. Fourth Quarter 2011. p. xxi