Pearson

Pearson(firstSample, secondSample, level=0.05)

Test whether two discrete samples are independent.

Refer to Pearson’s correlation test.

Parameters
firstSample2-d sequence of float

First tested sample, of dimension n \geq 1.

secondSample2-d sequence of float

Second tested sample, of dimension 1.

levelpositive float < 1, optional

Threshold p-value of the test (= first kind risk), it must be < 1, equal to 0.05 by default.

Returns
testResultTestResult

Structure containing the result of the test.

See also

HypothesisTest.Spearman

Notes

The Pearson Test is used to check whether two samples which are assumed to form a gaussian vector are independent (based on the evaluation of the linear correlation coefficient).

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distCol = [ot.Normal(), ot.Normal()]
>>> firstSample = ot.Normal().getSample(30)
>>> secondSample = ot.Normal().getSample(30)
>>> test_result = ot.HypothesisTest.Pearson(firstSample, secondSample)
>>> print(test_result)
class=TestResult name=Unnamed type=Pearson binaryQualityMeasure=true p-value threshold=0.05 p-value=0.984737 statistic=0.019302 description=[]