Turings on permutations focus on mean = 1

Finally I understand the meaning of the mean being 1.

Id figured a while ago that he was interested in the shuffle around 1.

But now we get that in eigenvector explanation (which is better than the shuffle!)

any distribution is the sum of 1/n of the 1 eigenvector + a superposition of weighted others.


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Computer Programmer who often does network administration with focus on security servers. Very strong in Microsoft Azure cloud!
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