scipy.stats.mstats.compare_medians_ms#
- scipy.stats.mstats.compare_medians_ms(group_1, group_2, axis=None)[source]#
Compares the medians from two independent groups along the given axis.
The comparison is performed using the McKean-Schrader estimate of the standard error of the medians.
- Parameters
- group_1array_like
First dataset. Has to be of size >=7.
- group_2array_like
Second dataset. Has to be of size >=7.
- axisint, optional
Axis along which the medians are estimated. If None, the arrays are flattened. If axis is not None, then group_1 and group_2 should have the same shape.
- Returns
- compare_medians_ms{float, ndarray}
If axis is None, then returns a float, otherwise returns a 1-D ndarray of floats with a length equal to the length of group_1 along axis.
References
- 1
McKean, Joseph W., and Ronald M. Schrader. “A comparison of methods for studentizing the sample median.” Communications in Statistics-Simulation and Computation 13.6 (1984): 751-773.
Examples
>>> from scipy import stats >>> a = [1, 2, 3, 4, 5, 6, 7] >>> b = [8, 9, 10, 11, 12, 13, 14] >>> stats.mstats.compare_medians_ms(a, b, axis=None) 1.0693225866553746e-05
The function is vectorized to compute along a given axis.
>>> import numpy as np >>> rng = np.random.default_rng() >>> x = rng.random(size=(3, 7)) >>> y = rng.random(size=(3, 8)) >>> stats.mstats.compare_medians_ms(x, y, axis=1) array([0.36908985, 0.36092538, 0.2765313 ])