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SciPy Reference Guide, Release 0.8.dev
obrientransform(*args)Computes a transform on input data (any number of columns).
samplevar(*args,
**kwds)
samplevar is deprecated!
samplestd(*args,
**kwds)
samplestd is deprecated!
signaltonoise(a[, Calculates the signal-to-noise ratio, defined as the ratio between the mean and the
axis, ddof])
standard deviation.
bayes_mvs(data[,
alpha])
Return Bayesian confidence intervals for the mean, var, and std.
var(a[, axis, bias]) Returns the estimated population variance of the values in the passed
std(a[, axis, bias]) Returns the estimated population standard deviation of the values in
stderr(*args, **kwds) stderr is deprecated!
sem(a[, axis, ddof]) Calculates the standard error of the mean (or standard error of measurement) of the
values in the passed array.
z(*args, **kwds) z is deprecated!
zs(*args, **kwds) zs is deprecated!
zmap(scores, compare[, Returns an array of z-scores the shape of scores (e.g., [x,y]), compared to array
axis])
passed to compare (e.g., [time,x,y]).
obrientransform(*args)
Computes a transform on input data (any number of columns). Used to test for homogeneity of variance prior
to running one-way stats. Each array in *args is one level of a factor. If an F_oneway() run on the transformed
data and found significant, variances are unequal. From Maxwell and Delaney, p.112.
Returns: transformed data for use in an ANOVA
samplevar(*args, **kwds)
samplevar is deprecated!
scipy.stats.samplevar is deprecated; please update your code to use numpy.var.
Please note that numpy.var axis argument defaults to None, not 0.
Returns the sample standard deviation of the values in the passed array (i.e., using N). Axis can
equal None (ravel array first), an integer (the axis over which to operate)
samplestd(*args, **kwds)
samplestd is deprecated!
scipy.stats.samplestd is deprecated; please update your code to use numpy.std.
Please note that numpy.std axis argument defaults to None, not 0.
Returns the sample standard deviation of the values in the passed array (i.e., using N). Axis can equal None
(ravel array first), an integer (the axis over which to operate).
signaltonoise(a, axis=0, ddof=0)
Calculates the signal-to-noise ratio, defined as the ratio between the mean and the standard deviation.
Parameters
a: array-like :
An array like object containing the sample data
axis: int or None, optional :
If axis is equal to None, the array is first ravel’d. If axis is an integer, this is the axis
over which to operate. Defaults to None???0
ddof : integer, optional, default 0
degrees of freedom correction for standard deviation
3.18. Statistical functions (scipy.stats) 649