HypothesisTest_Pearson(firstSample, secondSample, level=0.95)¶
Test whether two discrete samples are independent.
HypothesisTest.Pearson(firstSample, secondSample, level)
fisrtSample : 2-d sequence of float
First tested sample, of dimension .
secondSample : 2-d sequence of float
Second tested sample, of dimension 1.
level : positive float
Threshold p-value of the test (= 1 - first type risk), it must be , equal to 0.95 by default.
Structure containing the result of the test.
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).
>>> 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=TwoSamplePearson binaryQualityMeasure=true p-value threshold=0.05 p-value=0.984737 description=