= Cramér's V
{c}
{title2=$V=\sqrt{X^2/[n\min(r-1,c-1)]}$}
{wiki}
For an $r\times c$ <contingency table> with $n$ observations and positive row and column totals, <Cramér's V> rescales the <Pearson chi-squared statistic> to a dimensionless measure of <statistical association>. It lies between zero and one and is unchanged by reordering category labels. It therefore describes the magnitude of dependence, without an ordinal direction. A small <p-value> can accompany a small $V$ in a large sample: evidence against <independence> and the magnitude of the departure answer different questions. The displayed quantity is the usual uncorrected sample measure.
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