Latent and observable variables: Difference between revisions

Revision as of 13:49, 16 August 2022

Revision as of 02:07, 4 October 2022

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{{Short description|Variable not directly observed}}

{{For|similar uses|Hidden variable (disambiguation)}}

In [[statistics]], '''latent variables''' (from [[Latin]]: [[present participle]] of ''lateo'', (“lie hidden”), opposed to [[observable variable]]s) are [[Variable (mathematics)|variables]] that arecan not directly observed but areonly ratherbe [[Statistical inference|inferred]] indirectly through a [[mathematical model]] from other '''observable variables''' that arecan observedbe (directly [[observation|observed]] or [[measurement|measured)]].<ref>Dodge, MathematicalY. models(2003) that''The aimOxford toDictionary explainof observedStatistical variablesTerms'', inOUP. terms{{isbn|0-19-920613-9}}</ref> of latent variables are calledSuch ''[[latent variable model]]s. Latent variable models'' are used in many disciplines, including [[political science]], [[demography]], [[engineering]], [[medicine]], [[ecology]], [[physics]], [[machine learning]]/[[artificial intelligence]], [[bioinformatics]], [[chemometrics]], [[natural language processing]], [[management]] and the [[social sciences]].

Latent variables may correspond to aspects of physical reality. These could in principle be measured, but may not be for practical reasons. In this situation, the term ''hidden variables'' is commonly used (reflecting the fact that the variables are meaningful, but not observable). Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms ''hypothetical variables'' or ''hypothetical constructs'' may be used in these situations.