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# scipy.stats.cov

`scipy.stats.``cov`(m, y=None, rowvar=False, bias=False)

  Estimate the covariance matrix.

  If m is a vector, return the variance. For matrices where each row is an observation, and each column a variable, return the covariance matrix. Note that in this case diag(cov(m)) is a vector of variances for each column.

  cov(m) is the same as cov(m, m)

  Normalization is by (N-1) where N is the number of observations (unbiased estimate). If bias is True then normalization is by N.

  If rowvar is False, then each row is a variable with observations in the columns.

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