< List of probability distributions < Chi distribution

## What is the chi distribution?

The** chi distribution** is an asymmetric continuous probability distribution over the non-negative real line. It is the continuous distribution of a variable whose square root is the chi-square distribution. Equivalently, the distribution can be thought of as the distribution of Euclidean distances of random variables from the origin.

One practical use of this distribution is to model the sample standard deviation for samples drawn from a normal distribution; that’s because the sample variance for such samples follows a chi-square distribution [1]. It is also widely used in hypothesis testing and power analysis.

The Rayleigh distribution and the Maxwell–Boltzmann distribution (used in chemistry to describe the distribution of the speeds of molecules in an ideal gas) are two of the most familiar examples of the chi distribution, which itself is a special case of the noncentral chi-square distribution.

## Chi distribution properties

- This is an asymmetric distribution.
- It has one parameter, n.
- It is defined on a semi-bounded range x ≥ 0.

If a random variable *X* has a chi-square distribution with *n *∈(0,∞) degrees of freedom, then U=√X is a **chi distribution** with *n* degrees of freedom. If the random variable is drawn from a noncentral chi-square distribution, then the distribution is called a **noncentral chi distribution**.

With df = n > 0 degrees of freedom, the probability density function (PDF) is:

The cumulative distribution function (CDF) for this function can be approximated with integrals [2]:

## References

- Abell, M. et. all. (1999). Statistics with Mathematica. Elsevier Science.
- Rice U, Distributions Handbook.