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 homoscedasticity.

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

Richard Lowry. One-way analysis of variance for independent samples. 2014. URL: http://vassarstats.net/textbook/.

2

Gary W. Heiman. Research Methods in Psychology. Houghton Mifflin Company, Boston, 3 edition, 2002. ISBN 978-0-618-17028-9.

Examples using mne.stats.f_oneway#

Statistical inference

Statistical inference

Statistical inference

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