# scipy.stats.tvar¶

scipy.stats.tvar(a, limits=None, inclusive=(True, True), axis=0, ddof=1)[source]

Compute the trimmed variance

This function computes the sample variance of an array of values, while ignoring values which are outside of given limits.

Parameters: a : array_like Array of values. limits : None or (lower limit, upper limit), optional Values in the input array less than the lower limit or greater than the upper limit will be ignored. When limits is None, then all values are used. Either of the limit values in the tuple can also be None representing a half-open interval. The default value is None. inclusive : (bool, bool), optional A tuple consisting of the (lower flag, upper flag). These flags determine whether values exactly equal to the lower or upper limits are included. The default value is (True, True). axis : int or None, optional Axis along which to operate. Default is 0. If None, compute over the whole array a. ddof : int, optional Delta degrees of freedom. Default is 1. tvar : float Trimmed variance.

Notes

tvar computes the unbiased sample variance, i.e. it uses a correction factor n / (n - 1).

Examples

>>> from scipy import stats
>>> x = np.arange(20)
>>> stats.tvar(x)
35.0
>>> stats.tvar(x, (3,17))
20.0


#### Previous topic

scipy.stats.tmean

scipy.stats.tmin