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Computers are fast but they're lousy in simulating randomness - an oxymoron in its own right. We will see that random numbers generated by Perl's rand() are actually pseudo-random (PRN) and form a reproducible, seeded sequence. We'll briefly cover linear congruential generators (LCG), one way to create PRNs and talk about their strengths and weaknesses. A brief mention of sub-random sequences will be made in context of even space filling. We'll see how to make use of CPAN modules to harness a variety of PRN algorithms in Perl, including the reliable Mersenne Twister. We'll also spend time looking at how uniform random values are used to generate values distributed according to an arbitrary distributions.

other in this category

4.0.2.1 | Spans and Sets

other by same level

1.1.2.8 | Intermediate Perl

1.2.2.1 | Effective use of map, sort and grep in Perl

2.1.2.4 | Data Mining and Analysis at the Command Line

2.2.2.2 | Prompt Tools

4.0.2.1 | Spans and Sets

other by same instructor

Other courses by Martin Krzywinski.

0.0.0.1 | Orientation Session

0.1.0.1 | Two Problems

1.0.1.8 | Introduction to Perl

1.1.2.8 | Intermediate Perl

1.2.2.1 | Effective use of map, sort and grep in Perl

2.1.2.4 | Data Mining and Analysis at the Command Line

2.2.2.2 | Prompt Tools

4.0.2.1 | Spans and Sets