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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]
Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information ...
Example of data collection in the biological sciences: Adélie penguins are identified and weighed each time they cross the automated weighbridge on their way to or from the sea. [ 1 ] Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to ...
Furthermore, the quality of the accurate and timely results must be assessed prior to release. But if errors in the results occur before or after the data revision, [23] they should be directly corrected and information should be disseminated to the users at the earliest possible time. Producers of official statistics have to set analytical ...
Revision in this fashion is a more controversial topic, and can include denial or distortion of the historical record yielding an illegitimate form of historical revisionism known as historical negationism (involving, for example, distrust of genuine documents or records or deliberate manipulation of statistical data to draw predetermined ...
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications
A further difference between reference data and master data is that a change to the reference data values may require an associated change in business process to support the change, while a change in master data will always be managed as part of existing business processes. For example, adding a new customer or sales product is part of the ...