Adequacy of statistics to be combined in different ways and for various uses.

When originating from different sources, and in particular from statistical surveys using different methodology, statistics are often not completely identical, but show differences in results due to different approaches, classifications and methodological standards. There are several areas where the assessment of coherence is regularly conducted: between provisional and final statistics, between annual and short-term statistics, between statistics from the same socio-economic domain, and between survey statistics and national accounts. The concept of coherence is closely related to the concept of comparability between statistical domains. Both coherence and comparability refer to a data set with respect to another. The difference between the two is that comparability refers to comparisons between statistics based on usually unrelated statistical populations and coherence refers to comparisons between statistics for the same or largely similar populations. Coherence can be generally broken down into \Coherence - cross domain\" and \"Coherence - internal\". Users should be aware that, in the Data Quality Assessment Framework of the International Monetary Fund, the term \"consistency\" is used for indicating \"logical and numerical coherence\". In that framework, \"internal consistency\" and \"intersectoral and cross-domain consistency\" can be mapped to \"internal coherence\" and \"cross-domain coherence\" respectively."

- Internal Identifier
- COHERENCE
- Public ID
- No public identifier
- CDMMD ID
- http://mapping.semic.eu/vdm/id/cv/079816ed3b7851b4bf20c31826a11cec
- Type
- Class
- Raw data
- HTML | RDF/XML | Turtle

type | Class |

label | COHERENCE |

Title | COHERENCE |

definition | Adequacy of statistics to be combined in different ways and for various uses. |

Description | When originating from different sources, and in particular from statistical surveys using different methodology, statistics are often not completely identical, but show differences in results due to different approaches, classifications and methodological standards. There are several areas where the assessment of coherence is regularly conducted: between provisional and final statistics, between annual and short-term statistics, between statistics from the same socio-economic domain, and between survey statistics and national accounts. The concept of coherence is closely related to the concept of comparability between statistical domains. Both coherence and comparability refer to a data set with respect to another. The difference between the two is that comparability refers to comparisons between statistics based on usually unrelated statistical populations and coherence refers to comparisons between statistics for the same or largely similar populations. Coherence can be generally broken down into \Coherence - cross domain\" and \"Coherence - internal\". Users should be aware that, in the Data Quality Assessment Framework of the International Monetary Fund, the term \"consistency\" is used for indicating \"logical and numerical coherence\". In that framework, \"internal consistency\" and \"intersectoral and cross-domain consistency\" can be mapped to \"internal coherence\" and \"cross-domain coherence\" respectively." |

type | Class |

has internal identifier | COHERENCE |

sample | |

http://www.w3.org/ns/adms#versionNotes | |

Is Part Of | SDMX |