scipy tutorial - Baustatik-Info-Server

Parameters
data : sequence
Input data
skew(a, axis=0, bias=True)
Computes the skewness of a data set.
SciPy Reference Guide, Release 0.8.dev
axis
[{0, int} optional] Axis along which to compute. If None, the computation is
performed on a flat version of the array.
For normally distributed data, the skewness should be about 0. A skewness value > 0 means that there is more
weight in the left tail of the distribution. The function skewtest() can be used to determine if the skewness value
is close enough to 0, statistically speaking.
Parameters
a : array
axis : int or None
bias : bool
If False, then the calculations are corrected for statistical bias.
Returns
The skewness of values along an axis, returning 0 where all values are :
References
equal. :
[CRCProbStat2000] Section 2.2.24.1
[CRCProbStat2000]
skewtest(a, axis=0)
Tests whether the skew is different from the normal distribution.
This function tests the null hypothesis that the skewness of the population that the sample was drawn from is the
same as that of a corresponding normal distribution.
Notes
Parameters
a : array
axis : int or None
Returns
p-value : float
a 2-sided p-value for the hypothesis test
The sample size should be at least 8.
spearmanr(x, y, use_ties=True)
Calculates a Spearman rank-order correlation coefficient and the p-value
to test for non-correlation.
The Spearman correlation is a nonparametric measure of the linear relationship between two datasets.
Unlike the Pearson correlation, the Spearman correlation does not assume that both datasets are normally
3.18. Statistical functions (scipy.stats) 685