I think this exhibits a pretty strong bias toward the lower numbers generated, and against the higher numbers. It may be pseudo random but the distribution is not close to flat.

use List::Util qw(sum);

my @count = (0) x 20;
for (1 .. 200000) {
    my @orderedRands = (grep{ rand(1) < 0.075 } map{ ($_) x 20 } 1 .. 
+20 )[0..19];
    $count[$_]++ for grep {defined} @orderedRands;
}

my $sum = sum(@count);
print "$_\t=>\t$count[$_]\t(", sprintf('%.2f', ($count[$_]/$sum)*100),
+ "% TTL)\n" for 1 .. 20;

[download]

...which produces...

1    =>    300463    (7.53% TTL)
2    =>    300337    (7.52% TTL)
3    =>    300667    (7.53% TTL)
4    =>    300333    (7.52% TTL)
5    =>    300725    (7.53% TTL)
6    =>    299081    (7.49% TTL)
7    =>    299696    (7.51% TTL)
8    =>    297134    (7.44% TTL)
9    =>    289983    (7.26% TTL)
10    =>    276352    (6.92% TTL)
11    =>    252348    (6.32% TTL)
12    =>    217016    (5.44% TTL)
13    =>    175867    (4.41% TTL)
14    =>    133708    (3.35% TTL)
15    =>    96010    (2.40% TTL)
16    =>    65012    (1.63% TTL)
17    =>    41130    (1.03% TTL)
18    =>    24485    (0.61% TTL)
19    =>    14228    (0.36% TTL)
20    =>    7685    (0.19% TTL)

[download]

...and that is with adding the filtering-out of undefined values that found their way into @orderedRands.

I hope my adaptation of your algorithm didn't miss an important nuance.


Dave

In reply to Re^2: random #s by davido
in thread random #s by cboPerl

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