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just showing why 86.159.210.53 is right about Francis Bacon being the OG empiricist. we're "brothers of the same sentiments, from different continents" |
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In [[statistics]], '''latent variables''' (from [[Latin]]: [[present participle]] of ''lateo'', “lie hidden”) are [[Variable (mathematics)|variables]] that can only be [[Statistical inference|inferred]] indirectly through a [[mathematical model]] from other '''observable variables''' that can be directly [[observation|observed]] or [[measurement|measured]].<ref>Dodge, Y. (2003) ''The Oxford Dictionary of Statistical Terms'', OUP. {{isbn|0-19-920613-9}}</ref> Such ''[[latent variable model]]s'' are used in many disciplines, including [[political science]], [[demography]], [[engineering]], [[medicine]], [[ecology]], [[physics]], [[machine learning]]/[[artificial intelligence]], [[bioinformatics]], [[chemometrics]], [[natural language processing]], [[management]], [[psychology]] and the [[social sciences]].
{{quote|''But the latent process of which we speak, is far from being obvious to men’s minds, beset as they now are. For we mean not the measures, symptoms, or degrees of any process which can be exhibited in the bodies themselves, but simply a continued process, which, for the most part, escapes the observation of the senses.|''Sir [[Francis Bacon]]'', [[Novum Organum]]<ref
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[[File:Estimation of a mean height curve for boys from the Berkeley Growth Study with and without warping.gif|thumb|upright=2|Estimation of a mean height curve (black) for boys from the Berkeley Growth Study with and without warping. The warping is based on latent variables that maps age to a synchronized biological age using a [[nonlinear mixed-effects model]].<ref name="Raket_et_al_2014">{{cite journal |vauthors=Raket LL, Sommer S, Markussen B |year=2014 |title=A nonlinear mixed-effects model for simultaneous smoothing and registration of functional data |journal=Pattern Recognition Letters |volume=38|pages=1-7 |doi=10.1016/j.patrec.2013.10.018}}</ref>]]
===Psychology===
Latent variables, as created by factor analytic methods, generally represent "shared" variance, or the degree to which variables "move" together. Variables that have no correlation cannot result in a latent construct based on the common [[Factor analysis|factor model]].<ref>{{cite book |last1=Tabachnick |first1=B.G. |last2=Fidell |first2=L.S. |title=Using Multivariate Analysis |publisher=Allyn and Bacon |___location=Boston |year=2001 |isbn=978-0-321-05677-1 }}{{Page needed|date=November 2010}}</ref>
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