Latent Variable

In statistics, Latent variables (as opposed to observable variables), are variables that are not directly observed but are rather inferred (through a mathematical model) from other variables that are observed and directly measured. They are also sometimes known as hidden variables, model parameters, hypothetical variables or hypothetical constructs. The use of latent variables is common in social sciences, robotics, and to an extent economics, but the exact definition of a latent variable varies in these fields. Examples of latent variables from the field of economics include quality of life, business confidence, morale, happiness and conservatism: these are all variables which cannot be measured directly. However, given an economic model linking these latent variables to other, observable variables (such as GDP), the values of the latent variables can be inferred from measurements of the observable variables.
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A latent variable is a variable that cannot be measured directly, but is hypothesized to underlie the observed variables. An example of a latent variable is a factor in factor analysis. Latent variables in path diagrams are usually represented by a variable name enclosed in an oval or circle.