**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.

Filed under: R, Statistics Tagged: combinatorics, correction, Monte Carlo, simulation, sudoku, uniformity

*Related*

To

**leave a comment** for the author, please follow the link and comment on their blog:

** Xi'an's Og » R**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as:

Data science,

Big Data, R jobs, visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...

**Tags:** combinatorics, correction, Monte Carlo, R, Simulation, statistics, sudoku, uniformity