Cramér's V ($V=\sqrt{X^2/[n\min (r-1,c-1)]}$)

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.