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Data editing is the activity aimed at detecting and correcting errors (logical inconsistencies) in data.

Editing techniques refers to a range of procedures and processes used for detecting and handling errors in data. Examples of different techniques include the different approaches to editing such as micro-editing/ macro-editing, input/output editing, or to the various tools available for editing such as graphical editing, interactive editing, etc.

Edit types refer to the actual nature of edits applied to data during input or output processing. These include:

- validation edits - to check the validity of basic identification of classificatory items in unit data;

- logical edits - ensure that two or more data items do not have contradictory values;

- consistency edits - check to ensure that precise and correct arithmetic relationships exists between two or more data items;

- range edits - identify whether or not a data item value falls inside a determined acceptable range;

- variance edits - involve looking for suspiciously high variances at the output edit stage.

Edit types may also refer to whether these edits are fatal or query type, i.e. whether they detect errors with certainty or point to suspicious data items.

Micro-editing and macro-editing may be distinguished in order to calculate rate of edits.

Source Publication:
Economic Commission for Europe of the United Nations (UNECE), "Glossary of Terms on Statistical Data Editing", Conference of European Statisticians Methodological material, Geneva, 2000.

Cross References:
Data editing, graphical


Statistical Theme: Methodological information (metadata)

Glossary Output Segments:

Created on Tuesday, September 25, 2001

Last updated on Tuesday, January 03, 2006