```distribution ← average + standard_deviation × ##.NormRand (shape)

From Nicolas Delcros, who says:

Produces random numbers with a normal distribution, that is centered around zero
with a unitary standard deviation, so that, as the number of samples rises,  the
distribution will tend towards a normal gaussian curve. Normal distributions are
helpful to model natural random variables.

See: http://en.wikipedia.org/wiki/Box_muller

Examples:

{+/⍵÷⍴⍵}¨NormRand¨10*⍳5             ⍝ average tends towards 0
¯0.46239003 0.2586531459 0.02013158866 0.003016077943 0.0009350952811

{(+/⍵*2)÷⍴⍵}¨NormRand¨10*⍳5         ⍝ standard deviation tends towards 1
0.431348813 0.8883835515 0.9924045046 0.9891854881 1.004654056

⎕USING←',sharpplot.dll'
sp←⎕NEW Causeway.SharpPlot
sp.HistogramStyle←Causeway.HistogramStyles.(NormalCurve+SDev1)
sp.ClassInterval←0.1
sp.DrawHistogram ⊂NormRand 1000
(⎕NEW Causeway.SharpPlotViewer sp).Show ⍬

index: distribution, normal|random
index; Box G.E.P|Muller M.E.|Delcros N.

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