Draw samples from a chi-square distribution.
When df independent random variables, each with standard normal distributions (mean 0, variance 1), are squared and summed, the resulting distribution is chi-square (see Notes). This distribution is often used in hypothesis testing.
- df : float or array_like of floats
Number of degrees of freedom, must be > 0.
- size : int or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k), then
m * n * ksamples are drawn. If size is
None(default), a single value is returned if
dfis a scalar. Otherwise,
np.array(df).sizesamples are drawn.
- out : ndarray or scalar
Drawn samples from the parameterized chi-square distribution.
When df <= 0 or when an inappropriate size (e.g.
size=-1) is given.
The variable obtained by summing the squares of df independent, standard normally distributed random variables:
is chi-square distributed, denoted
The probability density function of the chi-squared distribution is
where is the gamma function,
 NIST “Engineering Statistics Handbook” https://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm
>>> np.random.chisquare(2,4) array([ 1.89920014, 9.00867716, 3.13710533, 5.62318272]) # random