dist_plot

normtest.ryan_joiner.dist_plot(axes, critical_range=(4, 50), test=None)

This function generates axis with critical data from the Ryan-Joiner Normality test [1].

Parameters:

axesmatplotlib.axes.SubplotBase

The axis of the graph;

critical_rangetuple (optional), with two elements:

x_minint, optional

The lower range of the number of observations for the critical values (default is 4).

x_maxint, optional

The upper range of the number of observations for the critical values (default is 50).

testtuple (optional), with two elements:

statisticfloat (positive)

The test statistic;

sample_sizeint

The axis of the graph;

Returns:

axesmatplotlib.axes.SubplotBase

The axis of the graph;

See also

rj_test

correlation_plot

References

[1]

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
>>> import matplotlib.pyplot as plt
>>> from scipy import stats
>>> data = stats.norm.rvs(loc=0, scale=1, size=30, random_state=42)

Apply the Ryan Joiner test

>>> result = ryan_joiner.rj_test(data)

Create the distribution graph using the test result

>>> fig, ax = plt.subplots(figsize=(6, 4))
>>> ryan_joiner.dist_plot(axes=ax, test=(result.statistic, data.size))
>>> # plt.savefig("rj_dist_plot.png")
>>> plt.show()