## Random [uniform?] sudokus [corrected]

**A**s the discrepancy [from 1] in the sum of the nine probabilities seemed too blatant to be attributed to numerical error given the problem scale, I went and checked my R code for the probabilities and found a *choose(9,3)* instead of a *choose(6,3)* in the last line… The fit between the true distribution and the observed frequencies is now much better

but the chi-square test remains suspicious of the uniform assumption (or again of my programming abilities):

> chisq.test(obs,p=pdiag)

Chi-squared test for given probabilities

data: obs

X-squared = 16.378, df = 6, p-value = 0.01186

since a p-value of 1% is a bit in the far tail of the distribution.

May 21, 2010 at 12:40 pm

[…] 9 “diagonals” (obtained by acceptable permutations of rows and column) and this test again results in mostly small p-values. Over a million iterations, and the nine (dependent) diagonals, […]

May 19, 2010 at 12:29 pm

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