This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English version of the page.

Note: This page has been translated by MathWorks. Click here to see
To view all translated materials including this page, select Country from the country navigator on the bottom of this page.


Chi-square inverse cumulative distribution function


X = chi2inv(P,V)


X = chi2inv(P,V) computes the inverse of the chi-square cdf with degrees of freedom specified by V for the corresponding probabilities in P. P and V can be vectors, matrices, or multidimensional arrays that have the same size. A scalar input is expanded to a constant array with the same dimensions as the other inputs. The degrees of freedom parameters in V must be positive, and the values in P must lie in the interval [0 1].

The inverse chi-square cdf for a given probability p and ν degrees of freedom is




and Γ( · ) is the Gamma function. Each element of output X is the value whose cumulative probability under the chi-square cdf defined by the corresponding degrees of freedom parameter in V is specified by the corresponding value in P.


Find a value that exceeds 95% of the samples from a chi-square distribution with 10 degrees of freedom.

x = chi2inv(0.95,10)
x =

You would observe values greater than 18.3 only 5% of the time by chance.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Introduced before R2006a