I'm far from an expert on stats, but I don't believe that Chi2 is the right test for the kind of samples this produces; and I cannot see any reference to Yates correction in the module.

Me neither, far from expert. Beyond chi-squared there are tests for finding a pattern in the shuffled data (I once tried to zip a file and count its compression ration achieved as proportional to how random the sequence is), and monte-carlo-splitting the shuffled array in groups and trying to see if the group's average approaches the total array's average.

I will report back chi-squared results using R

That despite the use of a completely bogus rand() function, a Fisher-Yates shuffle would still operate; and produce results:

    That all possible shuffles of the data were being produced. I chose to shuffle 4 values because the 24 possible results fit on a screen and are simple to verify manually.
    That they were produced with (approximately) the same frequency. Ie. The number of times each possible shuffle was produced were approximately equal and approximately 1/24th of the total runs. 

In that respect, it served its purpose.

But, if you are going to formally test a shuffle, using only 4 value arrays and 1e6 iterations probably isn't the ideal scenario to test.

ok

In reply to Re^5: Shuffling CODONS by bliako
in thread Shuffling CODONS by WouterVG

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