scipy.stats.f_oneway¶

scipy.stats.
f_oneway
(*args)[source]¶ Performs a 1way ANOVA.
The oneway ANOVA tests the null hypothesis that two or more groups have the same population mean. The test is applied to samples from two or more groups, possibly with differing sizes.
Parameters:  sample1, sample2, … : array_like
The sample measurements for each group.
Returns:  statistic : float
The computed Fvalue of the test.
 pvalue : float
The associated pvalue from the Fdistribution.
Notes
The ANOVA test has important assumptions that must be satisfied in order for the associated pvalue 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 KruskalWallis Htest (
scipy.stats.kruskal
) although with some loss of power.The algorithm is from Heiman[2], pp.3947.
References
[1] R. Lowry, “Concepts and Applications of Inferential Statistics”, Chapter 14, 2014, http://vassarstats.net/textbook/ [2] G.W. Heiman, “Understanding research methods and statistics: An integrated introduction for psychology”, Houghton, Mifflin and Company, 2001. [3] (1, 2) G.H. McDonald, “Handbook of Biological Statistics”, Oneway ANOVA. http://www.biostathandbook.com/onewayanova.html Examples
>>> import scipy.stats as stats
[3] Here are some data on a shell measurement (the length of the anterior adductor muscle scar, standardized by dividing by length) in the mussel Mytilus trossulus from five locations: Tillamook, Oregon; Newport, Oregon; Petersburg, Alaska; Magadan, Russia; and Tvarminne, Finland, taken from a much larger data set used in McDonald et al. (1991).
>>> tillamook = [0.0571, 0.0813, 0.0831, 0.0976, 0.0817, 0.0859, 0.0735, ... 0.0659, 0.0923, 0.0836] >>> newport = [0.0873, 0.0662, 0.0672, 0.0819, 0.0749, 0.0649, 0.0835, ... 0.0725] >>> petersburg = [0.0974, 0.1352, 0.0817, 0.1016, 0.0968, 0.1064, 0.105] >>> magadan = [0.1033, 0.0915, 0.0781, 0.0685, 0.0677, 0.0697, 0.0764, ... 0.0689] >>> tvarminne = [0.0703, 0.1026, 0.0956, 0.0973, 0.1039, 0.1045] >>> stats.f_oneway(tillamook, newport, petersburg, magadan, tvarminne) (7.1210194716424473, 0.00028122423145345439)