Spearman¶
- Spearman(firstSample, secondSample, level=0.05)¶
- Test whether two samples have no rank correlation. - Refer to Spearman correlation test. - Parameters:
- firstSample2-d sequence of float
- First tested sample, of dimension - . 
- secondSample2-d sequence of float
- Second tested sample, of dimension 1. 
- levelpositive float , optional 
- Threshold p-value of the test (= first kind risk), it must be - , equal to 0.05 by default. 
 
- Returns:
- testResultTestResult
- Structure containing the result of the test. 
 
- testResult
 - See also - HypothesisTest.Pearson
 - Notes - The Spearman Test is used to check whether two samples of dimension 1 have no rank correlation. - Examples - >>> import openturns as ot >>> ot.RandomGenerator.SetSeed(0) >>> distribution = ot.Normal() >>> firstSample = distribution.getSample(30) >>> func = ot.SymbolicFunction(['x'], ['x^2']) >>> secondSample = func(firstSample) >>> test_result = ot.HypothesisTest.Spearman(firstSample, secondSample) >>> print(test_result) class=TestResult name=Unnamed type=Spearman binaryQualityMeasure=true p-value threshold=0.05 p-value=0.442067 statistic=-0.774521 description=[] 
 OpenTURNS
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