doc typo

Author: stevengj

doc/helpdb.jl

@@ -5597,7 +5597,7 @@ popdisplay(d::Display)
    Compute the sample standard deviation of a vector or array \"v\",
    optionally along dimensions in \"region\". The algorithm returns an
    estimator of the generative distribution's standard deviation under
-   the assumption that each entry of \"v\" is an IID draw from that
+   the assumption that each entry of \"v\" is an IID drawn from that
    generative distribution. This computation is equivalent to
    calculating \"sqrt(sum((v - mean(v)).^2) / (length(v) - 1))\".
    Note: Julia does not ignore \"NaN\" values in the computation. For
@@ -5619,7 +5619,7 @@ popdisplay(d::Display)
    Compute the sample variance of a vector or array \"v\", optionally
    along dimensions in \"region\". The algorithm will return an
    estimator of the generative distribution's variance under the
-   assumption that each entry of \"v\" is an IID draw from that
+   assumption that each entry of \"v\" is an IID drawn from that
    generative distribution. This computation is equivalent to
    calculating \"sum((v - mean(v)).^2) / (length(v) - 1)\". Note:
    Julia does not ignore \"NaN\" values in the computation. For

doc/stdlib/base.rst

@@ -3762,7 +3762,7 @@ Statistics
 
 .. function:: std(v[, region])
 
-   Compute the sample standard deviation of a vector or array ``v``, optionally along dimensions in ``region``. The algorithm returns an estimator of the generative distribution's standard deviation under the assumption that each entry of ``v`` is an IID draw from that generative distribution. This computation is equivalent to calculating ``sqrt(sum((v - mean(v)).^2) / (length(v) - 1))``.
+   Compute the sample standard deviation of a vector or array ``v``, optionally along dimensions in ``region``. The algorithm returns an estimator of the generative distribution's standard deviation under the assumption that each entry of ``v`` is an IID drawn from that generative distribution. This computation is equivalent to calculating ``sqrt(sum((v - mean(v)).^2) / (length(v) - 1))``.
    Note: Julia does not ignore ``NaN`` values in the computation.
    For applications requiring the handling of missing data, the ``DataArray``
    package is recommended.
@@ -3774,7 +3774,7 @@ Statistics
 
 .. function:: var(v[, region])
 
-   Compute the sample variance of a vector or array ``v``, optionally along dimensions in ``region``. The algorithm will return an estimator of the generative distribution's variance under the assumption that each entry of ``v`` is an IID draw from that generative distribution. This computation is equivalent to calculating ``sum((v - mean(v)).^2) / (length(v) - 1)``.
+   Compute the sample variance of a vector or array ``v``, optionally along dimensions in ``region``. The algorithm will return an estimator of the generative distribution's variance under the assumption that each entry of ``v`` is an IID drawn from that generative distribution. This computation is equivalent to calculating ``sum((v - mean(v)).^2) / (length(v) - 1)``.
    Note: Julia does not ignore ``NaN`` values in the computation.
    For applications requiring the handling of missing data, the ``DataArray``
    package is recommended.