Latent variables, as opposed to observable variables, are those variables that cannot be directly observed but are rather inferred from other variables that can be observed and directly measured. Examples of latent variables include quality of life, business confidence, morale, happiness, conservatism. Latent variables are also called hidden variables, model parameters, hypothetical variables or hypothetical constructs. The use of latent variables is common in social sciences, robotics, and to an extent in the economics ___domain; but the exact definition of latent variables varies in these different domains.
One advantage of using latent variables is that it reduces the dimensionality of data. A large number of observable variables can be aggregated to represent an underlying concept, making it easier for human beings to understand and assimilate information. At the same time, the latent variables are the link between observable ("sub-symbolic") data in the real world, and symbolic data in the modeled world.