AndersonDarlingNormal

AndersonDarlingNormal(sample, level=0.05)

Evaluate whether a sample follows a normal distribution.

Refer to Anderson-Darling test.

Parameters:
sample2-d sequence of float

Tested sample.

levelpositive float, 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

openturns.NormalityTest.CramerVonMisesNormal

Notes

The test is used to check whether the sample follows a normal distribution. This test gives more importance to extreme values.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distribution = ot.Normal()
>>> sample = distribution.getSample(30)
>>> test_result = ot.NormalityTest.AndersonDarlingNormal(sample)
>>> print(test_result)
class=TestResult name=Unnamed type=AndersonDarlingNormal binaryQualityMeasure=true p-value threshold=0.05 p-value=0.7268 statistic=0.255405 description=[]

Examples using the function

Test Normality

Test Normality