In statistics, a Polya urn model (also known as a Polya urn scheme or simply as Pólya's urn), named after George Pólya, is a type of statistical model used as an idealized mental exercise to understand the nature of certain statistical distributions.
In an urn model, objects of real interest (such as atoms, people, cars, etc.) are represented as colored balls in an urn or other container. In the basic urn model, the urn contains x white and y black balls; one ball is drawn randomly from the urn and its color observed; it is then placed back in the urn, and the selection process is repeated. Questions can then be asked about the probability of drawing one color or another, or some other properties.
The Polya urn model differs only in that, when a ball of a particular color is drawn, that ball is put back along with a new ball of the same color. Thus, unlike in the basic model, the contents of the urn change over time, with a self-reinforcing property sometimes expressed as the rich get richer.
Note that in some sense, the Polya urn model is the "opposite" of the model of sampling without replacement. When sampling without replacement, every time a particular value is observed, it is less likely to be observed again, whereas in a Polya urn model, an observed value is more likely to be observed again. In both of these models, the act of measurement has an effect on the outcome of future measurements. (For comparison, when sampling with replacement, observation of a particular value has no effect on how likely it is to observe that value again.) Note also that in a Polya urn model, successive acts of measurement over time have less and less effect on future measurements, whereas in sampling without replacement, the opposite is true: After a certain number of measurements of a particular value, that value will never be seen again.