This documentation is for development version 0.18.dev0.



Perform a 1-way ANOVA.

The one-way ANOVA tests the null hypothesis that 2 or more groups have the same population mean. The test is applied to samples from two or more groups, possibly with differing sizes [1].

This is a modified version of scipy.stats.f_oneway() that avoids computing the associated p-value.

*args : array_like

The sample measurements should be given as arguments.

F-value : float

The computed F-value of the test.


The ANOVA test has important assumptions that must be satisfied in order for the associated p-value to be valid.

  1. The samples are independent
  2. Each sample is from a normally distributed population
  3. The population standard deviations of the groups are all equal. This property is known as homocedasticity.

If these assumptions are not true for a given set of data, it may still be possible to use the Kruskal-Wallis H-test (scipy.stats.kruskal()) although with some loss of power

The algorithm is from Heiman [2], pp.394-7.


[1](1, 2) Lowry, Richard. “Concepts and Applications of Inferential Statistics”. Chapter 14.
[2](1, 2) Heiman, G.W. Research Methods in Statistics. 2002.

Examples using mne.stats.f_oneway