NonCentralChiSquareDistribution Class

[SerializableAttribute]
public class NonCentralChiSquareDistribution : ContinuousDistribution

<SerializableAttribute>
Public Class NonCentralChiSquareDistribution
	Inherits ContinuousDistribution

[SerializableAttribute]
public ref class NonCentralChiSquareDistribution : public ContinuousDistribution

[<SerializableAttribute>]
type NonCentralChiSquareDistribution = 
    class
        inherit ContinuousDistribution
    end

Inheritance

Object  →  Distribution  →  ContinuousDistribution  →  NonCentralChiSquareDistribution

The sum of the squares of n independent normal variables with zero mean and unit variance has a chi-squared distribution with n degrees of freedom. This means it also describes the Variance of samples taken from a normal distribution.

From this last property, we can see the usefulness of the chi-squared distribution as a test of statistical significance. We can determine the likelihood of obtaining a sample that deviates from the expected value by a specified amount.

The sum of two or more variables that have a chi-squared distribution also has a chi-squared distribution. The number of degrees of freedom of the new distribution equals the sum of the degrees of freedom of the original distributions.

Reference