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. Back to: contents Back to: Workspaces