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  2. Coverage error - Wikipedia

    en.wikipedia.org/wiki/Coverage_error

    Often, the methods employed are unique to specific agencies and organizations. For example, the United States Census Bureau has developed models using the U.S. Postal Service's Delivery Sequence File, IRS 1040 address data, commercially available foreclosure counts, and other data to develop models capable of predicting undercount by census block.

  3. Non-sampling error - Wikipedia

    en.wikipedia.org/wiki/Non-sampling_error

    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;

  4. Total survey error - Wikipedia

    en.wikipedia.org/wiki/Total_survey_error

    Nonsampling error, which occurs in surveys and censuses alike, is the sum of all other errors, including errors in frame construction, sample selection, data collection, data processing and estimation methods.

  5. Data editing - Wikipedia

    en.wikipedia.org/wiki/Data_editing

    Data editing is defined as the process involving the review and adjustment of collected survey data. [1] Data editing helps define guidelines that will reduce potential bias and ensure consistent estimates leading to a clear analysis of the data set by correct inconsistent data using the methods later in this article. [ 2 ]

  6. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    Overabundance of already collected data became an issue only in the "Big Data" era, and the reasons to use undersampling are mainly practical and related to resource costs. Specifically, while one needs a suitably large sample size to draw valid statistical conclusions, the data must be cleaned before it can be used. Cleansing typically ...

  7. Administrative error - Wikipedia

    en.wikipedia.org/wiki/Administrative_error

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  9. Statistical assumption - Wikipedia

    en.wikipedia.org/wiki/Statistical_assumption

    Cross-variation assumptions. These assumptions involve the joint probability distributions of either the observations themselves or the random errors in a model. Simple models may include the assumption that observations or errors are statistically independent. Design-based assumptions.