Name and version: Statistical classifications
Alternative name(s): Nomenclature, reference classification, standard classification
Valid: From January 2009
A set of discrete, exhaustive and mutually exclusive observations, which can be assigned to one or more variables to be measured in the collation and/or presentation of data.
The structure of classification can be either hierarchical or flat. Hierarchical classifications range from the broadest level (e.g., division) to the detailed level (e.g., class). Flat classifications (e.g., sex classification) are not hierarchical.
The characteristics of a good classification are as follows:
- the categories are exhaustive and mutually exclusive (i.e., each member of a population can only be allocated to one category without duplication or omission);
- the classification is comparable to other related (national or international) standard classifications;
- the categories are stable (i.e., they are not changed too frequently, or without proper review, justification and documentation);
- the categories are well described with a title in a standard format and backed up by explanatory notes, coding indexes, coders and correspondence tables to related classifications (including earlier versions of the same classification);
- the categories are well balanced within the limits set by the principles for the classification (i.e., not too many or too few categories). This is usually established by applying significance criteria (e.g., size limits on variables such as employment, turnover, etc.);
- the categories reflect realities of the domain (e.g., the society or economy) to which they relate (e.g., in an industry classification, the categories should reflect the total picture of industrial activities of the country); and
- the classification is backed up by the availability of instructions, manuals, coding indexes, handbooks and training.
Statistical classifications are used for:
a. presenting statistical information;
b. the collection of information and/or organisation of information already collected;
c. aggregating and disaggregating data sets meaningfully for purposes of analysis, including the construction of indexes;
Maintenance organization: not applicable
ISO Standard Number: not applicable
United Nations Glossary of Classification Terms
United Nations Statistical Division Standard Statistical Classifications: Basic Principles
International Family of Economic and Social Classifications: Preamble
Neuchâtel Terminology: Classification database object types and their attributes Version 2.0
United Nations Classification Registry
Relationships to other standards: Concept Map
In SDMX, "Classification Systems" refer to a description of the classification systems being used and how they conform with internationally accepted standards guidelines, or good practices. It also refers to the description of deviations of classification systems compared to accepted statistical standards, guidelines, or good practices, when relevant.
Description last updated / validated: 23 September 2009