scipy.stats.friedmanchisquare¶
- scipy.stats.friedmanchisquare(*args)[source]¶
Computes the Friedman test for repeated measurements
The Friedman test tests the null hypothesis that repeated measurements of the same individuals have the same distribution. It is often used to test for consistency among measurements obtained in different ways. For example, if two measurement techniques are used on the same set of individuals, the Friedman test can be used to determine if the two measurement techniques are consistent.
Parameters: measurements1, measurements2, measurements3... : array_like
Arrays of measurements. All of the arrays must have the same number of elements. At least 3 sets of measurements must be given.
Returns: friedman chi-square statistic : float
the test statistic, correcting for ties
p-value : float
the associated p-value assuming that the test statistic has a chi squared distribution
Notes
Due to the assumption that the test statistic has a chi squared distribution, the p-value is only reliable for n > 10 and more than 6 repeated measurements.
References
[R230] http://en.wikipedia.org/wiki/Friedman_test