Task

Generate a collection filled with   1000   normally distributed random (or pseudo-random) numbers
with a mean of   1.0   and a   standard deviation   of   0.5



Many libraries only generate uniformly distributed random numbers. If so, you may use one of these algorithms.



Related task

   Standard deviation


fcn mkRand(mean,sd){ //normally distributed random w/mean & standard deviation
   pi:=(0.0).pi;    // using the Box–Muller transform
   rz1:=fcn{1.0-(0.0).random(1)}  // from [0,1) to (0,1]
   return('wrap(){((-2.0*rz1().log()).sqrt() * (2.0*pi*rz1()).cos())*sd + mean })
}