_p_value#

normtest.ryan_joiner._p_value(statistic, sample_size)[source]#

This function estimates the probability associated with the Ryan-Joiner Normality test [1].

Parameters:
statisticfloat (positive)

The test statistic;

sample_sizeint

The sample size. Must be equal or greater than 4;

Returns:
p_valuefloat or str

The probability of the test;

See also

rj_test

Notes

The test probability is estimated through linear interpolation of the test statistic with critical values from the Ryan-Joiner test [1]. The Interpolation is performed using the scipy.interpolate.interp1d() function.

  • If the test statistic is greater than the critical value for \(\alpha=0.10\), the result is always “p > 0.100”.

  • If the test statistic is lower than the critical value for \(\alpha=0.01\), the result is always “p < 0.010”.

Warning

The estimated \(p_{value}\) may not be accurate as it is calculated using linear interpolation

References

[1] (1,2)

RYAN, T. A., JOINER, B. L. Normal Probability Plots and Tests for Normality, Technical Report, Statistics Department, The Pennsylvania State University, 1976. Available at www.additive-net.de. Access on: 22 Jul. 2023.

Examples

>>> from normtest import ryan_joiner
>>> p_value = ryan_joiner._p_value(0.90, 10)
>>> print(p_value)
0.030930589077996555