correlation_plot

normtest.ryan_joiner.correlation_plot(axes, x_data, cte_alpha='3/8', weighted=False)

This function creates an axis with the Ryan-Joiner test [1] correlation graph.

Parameters:

axesmatplotlib.axes.SubplotBase

The axis of the graph;

x_datanumpy array

One dimension numpy array with at least 4 observations.

cte_alphastr, optional

A str with the cte_alpha value that should be adopted. The options are:

• “0”;

• “3/8” (default);

• “1/2”;

weightedbool, optional

Whether to estimate the Normal order considering the repeats as its average (True) or not (False, default). Only has an effect if the dataset contains repeated values;

Returns:

axesmatplotlib.axes.SubplotBase

The axis of the graph;

See also

rj_test

dist_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)
>>> fig, ax = plt.subplots(figsize=(6, 4))
>>> ryan_joiner.correlation_plot(axes=ax, x_data=data)
>>> #plt.savefig("correlation_plot.png")
>>> plt.show()