<p dir="auto"><a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.cov.html" rel="nofollow">https://docs.scipy.org/doc/numpy/reference/generated/numpy.cov.html</a></p>
<p dir="auto">The ddof definition in the above link is incorrect. ddof should be 1 instead of 9.</p>
<p dir="auto">Documentation in <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.var.html#numpy.var" rel="nofollow">https://docs.scipy.org/doc/numpy/reference/generated/numpy.var.html#numpy.var</a> contains this statement</p>
<blockquote>
<p dir="auto">The variance is the average of the squared deviations from the mean, i.e., var = mean(abs(x - x.mean())**2).</p>
<p dir="auto">The mean is normally calculated as x.sum() / N, where N = len(x). If, however, ddof is specified, the divisor N - ddof is used instead.</p>
</blockquote>
<p dir="auto">It is not clear which mean is calculated using <code class="notranslate">N - ddof</code> instead of <code class="notranslate">N</code>, and the first part of the second sentence suggests (to me, at least) that it's the inner mean - which is not the case (and rightly so).</p>
<p dir="auto">Suggested (IMHO clearer) rewording:</p>
<blockquote>
<p dir="auto">The outer mean is normally calculated as t.sum() / N, where N = len(x). If, however, ddof is specified, the divisor N - ddof is used instead.</p>
</blockquote>
<p dir="auto">The same problem is present in the documentation for <code class="notranslate">nanvar</code>, <code class="notranslate">std</code> and <code class="notranslate">nanstd</code>. Similar rewording should make it clearer.</p>