In a random distribution there will not be a skewed association. By creating sets that make false assumptions about the underlying set it would seem to be true. The set of pairs contains BB BG GB GG and so the set of observations for B is BB BB BG BG and conversely. It is true that a set which is skewed can be created if the starting set is BB BG GG, which has an even distribution of B and G, however it is not a representation of the actual distribution that would exist.
It is of interest because it can be the source of some confusion in genetic recombination of dominant and recessive genes. The human or animal mind is not always the naturally best tool for understanding. A person has to be aware that the wetware has some nasty edge conditions that are far worse than integer overflow, loss of precision in floating point, and type casting losses. At least it doesn't have a divide by zero fault or SIGSEGV. One would have to suppose that results are skewed to avoid type 2 results. By "type 2" I mean that a failure to choose something in a case that leads to death is a fatal error like SIGSEGV and so a brain only gets to make that mistake once.
The best way to predict the future is to create it.
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