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.
The sample measurements should be given as arguments.
float
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.
The samples are independent
Each sample is from a normally distributed population
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
mne.stats.f_oneway
#