scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
Notes
As with Levene’s test there are three variants of Fligner’s test that differ by the measure of central tendency used
in the test. See levene_ for more information.
References
[R19], [R20]
mood(x, y)
Perform Mood’s test for equal scale parameters
Mood’s two-sample test for scale parameters is a non-parametric test for the null hypothesis that two samples
are drawn from the same distribution with the same scale parameter.
See Also:
Parameters
x, y : array_like
arrays of sample data
Returns
p-value : float
The p-value for the hypothesis test
fligner
A non-parametric test for the equality of k variances
ansari
A non-parametric test for the equality of 2 variances
bartlett
A parametric test for equality of k variances in normal samples
levene
A parametric test for equality of k variances
Notes
The data are assumed to be drawn from probability distributions f(x) and f(x/s)/s respectively, for some probability
density function f. The null hypothesis is that s = 1.
oneway(*args, **kwds)
Test for equal means in two or more samples from the normal distribution.
If the keyword parameter is true then the variances are assumed to be equal, otherwise they are not
assumed to be equal (default).
Return test statistic and the p-value giving the probability of error if the null hypothesis (equal means) is rejected
at this value.
glm(data, para) Calculates a linear model fit ...
anova
glm(data, para)
Calculates a linear model fit ... anova/ancova/lin-regress/t-test/etc. Taken from:
Peterson et al. Statistical limitations in functional neuroimaging I. Non-inferential methods and statistical models.
Phil Trans Royal Soc Lond B 354: 1239-1260.
Returns: statistic, p-value ???
668 Chapter 3. Reference