scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
Notes
expected frequencies in each category. By default the categories are assumed to be
equally likely.
ddof : int, optional
adjustment to the degrees of freedom for the p-value
Returns
chisquare statistic : float
p : float
The chisquare test statistic
The p-value of the test.
This test is invalid when the observed or expected frequencies in each category are too small. A typical rule
is that all of the observed and expected frequencies should be at least 5. The default degrees of freedom,
k-1, are for the case when no parameters of the distribution are estimated. If p parameters are estimated by
efficient maximum likelihood then the correct degrees of freedom are k-1-p. If the parameters are estimated in
a different way, then then the dof can be between k-1-p and k-1. However, it is also possible that the asymptotic
distributions is not a chisquare, in which case this test is notappropriate.
References
[R16]
ks_2samp(data1, data2)
Computes the Kolmogorov-Smirnof statistic on 2 samples.
This is a two-sided test for the null hypothesis that 2 independent samples are drawn from the same continuous
distribution.
Notes
Parameters
a, b : sequence of 1-D ndarrays
Returns
D : float
two arrays of sample observations assumed to be drawn from a continuous distribution,
sample sizes can be different
KS statistic
p-value : float
two-tailed p-value
This tests whether 2 samples are drawn from the same distribution. Note that, like in the case of the one-sample
K-S test, the distribution is assumed to be continuous.
This is the two-sided test, one-sided tests are not implemented. The test uses the two-sided asymptotic
Kolmogorov-Smirnov distribution.
If the K-S statistic is small or the p-value is high, then we cannot reject the hypothesis that the distributions of
the two samples are the same.
660 Chapter 3. Reference