DistFunc_pPearsonCorrelation

DistFunc_pPearsonCorrelation(size, rho, tail=False)

Asymptotic probability function for the Pearson \rho correlation.

Parameters
nint

The size of the population

rhofloat -1<rho<1

The Pearson correlation coefficient

tailbool

Tells if we consider to be in the critical region (tTrue) Default value is False

Returns
pvaluefloat

The probability to be in the region of interest

Notes

This method allows to compute the asymptotic distribution of the Pearson correlation coefficient issued from two univariate samples of size n. Basically, we want to measure how coefficient is significatly different from 0. If tail is True, the issued value measures probability to be in the critical region.

Examples

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