# mne.stats.f_oneway¶

mne.stats.f_oneway(*args)[source]

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.

Parameters
*argsarray_like

The sample measurements should be given as arguments.

Returns
F-valuefloat

The computed F-value of the test.

Notes

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.

References

1

Lowry, Richard. “Concepts and Applications of Inferential Statistics”. Chapter 14.

2

Heiman, G.W. Research Methods in Statistics. 2002.