Also, I couldn't get the original documents at the time, but you reminded me of this: >'The simplest assumption about dice as random-number generators is that

Also, I couldn't get the original documents at the time, but you reminded me of this: >'The simplest assumption about dice as random-number generators is that each face is equally likely, and therefore the event “five or six” will occur with probability 1/3 and the number of successes out of 12 will be distributed according to the binomial distribution. When the data are compared to this “fair binomial” hypothesis using Pearson’s
2 test without any binning, Pearson found a p-value of 0.000016, or “the odds are 62,499 to 1 against such a system of deviations on a random selection.”' https://galton.uchicago.edu/about/docs/2009/2009_dice_zac_labby.pdf https://galton.uchicago.edu/about/docs/2009/2009_dice_zac_la... The point is you will always find deviations (with extremely low p-values) if you look hard enough. It is about collecting data as carefully as possible, and determining which model fits best, not which fits perfectly.