Lines Matching full:variance
58 :func:`pvariance` Population variance of data.
60 :func:`variance` Sample variance of data.
297 variance). See :func:`pvariance` for arguments and other details.
307 Return the population variance of *data*, a non-empty iterable of real-valued
308 numbers. Variance, or second moment about the mean, is a measure of the
309 variability (spread or dispersion) of data. A large variance indicates that
310 the data is spread out; a small variance indicates it is clustered closely
317 Use this function to calculate the variance from the entire population. To
318 estimate the variance from a sample, the :func:`variance` function is usually
358 When called with the entire population, this gives the population variance
359 ?². When called on a sample instead, this is the biased sample variance
360 s², also known as variance with N degrees of freedom.
363 to calculate the variance of a sample, giving the known population mean as
366 unbiased estimate of the population variance.
372 variance). See :func:`variance` for arguments and other details.
380 .. function:: variance(data, xbar=None)
382 Return the sample variance of *data*, an iterable of at least two real-valued
383 numbers. Variance, or second moment about the mean, is a measure of the
384 variability (spread or dispersion) of data. A large variance indicates that
385 the data is spread out; a small variance indicates it is clustered closely
393 the variance from the entire population, see :func:`pvariance`.
402 >>> variance(data)
411 >>> variance(data, m)
423 >>> variance([D("27.5"), D("30.25"), D("30.25"), D("34.5"), D("41.75")])
427 >>> variance([F(1, 6), F(1, 2), F(5, 3)])
432 This is the sample variance s² with Bessel's correction, also known as
433 variance with N-1 degrees of freedom. Provided that the data points are
435 should be an unbiased estimate of the true population variance.
438 :func:`pvariance` function as the *mu* parameter to get the variance of a
