Core Data Model Mapping Directory

ACCURACY

Closeness of computations or estimates to the exact or true values that the statistics were intended to measure

The accuracy of statistical information is the degree to which the information correctly describes the phenomena. It is usually characterized in terms of error in statistical estimates and is often decomposed into bias (systematic error) and variance (random error) components. Accuracy can contain either measures of accuracy (numerical results of the methods for assessing the accuracy of data) or qualitative assessment indicators. It may also be described in terms of the major sources of error that potentially cause inaccuracy (e.g., coverage, sampling, non response, response error). Accuracy is associated with the reliability" of the data, which is defined as the closeness of the initial estimated value to the subsequent estimated value. This concept can be broken down into: Accuracy - overall (summary assessment), Accuracy - non-sampling error, Accuracy - sampling error. "

Internal Identifier
ACCURACY
Public ID
No public identifier
CDMMD ID
http://mapping.semic.eu/vdm/id/cv/4ff613a2c6a3fa397dac6bb203dbf0aa
Type
Class
Raw data
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Metadata

type Class
label ACCURACY
Title ACCURACY
definition Closeness of computations or estimates to the exact or true values that the statistics were intended to measure
Description The accuracy of statistical information is the degree to which the information correctly describes the phenomena. It is usually characterized in terms of error in statistical estimates and is often decomposed into bias (systematic error) and variance (random error) components. Accuracy can contain either measures of accuracy (numerical results of the methods for assessing the accuracy of data) or qualitative assessment indicators. It may also be described in terms of the major sources of error that potentially cause inaccuracy (e.g., coverage, sampling, non response, response error). Accuracy is associated with the reliability" of the data, which is defined as the closeness of the initial estimated value to the subsequent estimated value. This concept can be broken down into: Accuracy - overall (summary assessment), Accuracy - non-sampling error, Accuracy - sampling error. "
type Class
has internal identifier ACCURACY
sample
http://www.w3.org/ns/adms#versionNotes
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