pPearsonCorrelation

pPearsonCorrelation(size, rho, tail=False)

Cumulative distribution function of the Pearson statistic distribution.

Parameters:
nint

The size of the samples.

rhofloat, -1<rho<1

The Pearson correlation coefficient.

tailbool

Tail flag.

Default value is False.

If True, the complementary CDF is computed.

Returns:
p: float

The CDF or its complementary of the Pearson statistic distribution.

Notes

This method enables to test whether an observed value of the Pearson correlation \rho is significantly different from zero. It implements the distribution of the statistic under the null hypothesis where the Pearson correlation is assumed to be not significantly different from 0.

The CDF value is the probability that the statistic is lower than or equal to the value calculated from \rho. The complementary CDF value is the p-value.

We use the Student asymptotic approximation of the statistic distribution.

Examples

>>> import openturns as ot
>>> pval = ot.DistFunc.pPearsonCorrelation(100, 0.3, True)