Editing Normalizing constant (section)

{{Use American English|date = March 2019}}
{{Short description|Constant a such that af(x) is a probability measure}}
{{distinguish|Proportionality factor}}

In [[probability theory]], a '''normalizing constant''' or '''normalizing factor''' is used to reduce any probability function to a probability density function with total probability of one.

For example, a Gaussian function can be normalized into a probability density function, which gives the standard normal distribution. In Bayes' theorem, a normalizing constant is used to ensure that the sum of all possible hypotheses equals 1. Other uses of normalizing constants include making the value of a Legendre polynomial at 1 and in the orthogonality of orthonormal functions.

A similar concept has been used in areas other than probability, such as for polynomials.