But apparently that is the “old way” and there is a new program from NIST that you can get here: NIST test suite for random numbers, which subsequently is linked to from random.org: Random.org Statistical Analysis.
Getting that program from NIST to compile was a little bit of a chore for me on msvc 2010. The biggest hurdle i hit was that msvc 2010 doesnt have erf() and erfc() so i had to google “erf.cpp” and find an implementation. If you can’t find one, erf and erfc are part of gcc which is open sourced so you can always go that route if you need to!
After compiling, i was able to run the test on my numbers but couldn’t make much sense of the results very easily. There were a few p scores and presumably some chi squared scores somewhere, but the “summary file” was very cryptic (pun intended) so i wasn’t really sure…
Anyways, just wanted to put it here for myself and others if anyone’s looking for this in the future 😛
Thanks to my buddy James for the correction and links to the newer NIST program. Thanks man!
Interestingly, the tests above use the source number data to do a bunch of different things, and then measure the statistics of the results.
For instance, it will use the numbers to shuffle a deck of cards, and then it will play poker and see if there is any bias of cards dealt, or players winning.
Or, it will use the numbers as the source of numbers for a roulette wheel and see if players win at the right rate statistically.
I guess the bottom line lesson for testing random numbers is that you should use the numbers how you intend to use them, and see if there’s any statistical anomalies.
There doesn’t seem to be a magic bullet test that works for generic randomness, but I’m guessing it’s just sort of… check for patterns in every way you can, or every way you care about, and if you don’t find any, consider it random. If you are using it for purposes where randomness really matters – like security or gambling – you then hope nobody else finds a pattern you didn’t! 😛
On that topic, check this out: Wikipedia: Michael Larson