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Cramer's V is a way of calculating correlation in tables which have more than 2x2 rows and columns. It is used as post-test to determine strengths of association after chi-square has determined significance.
V is calculated by first calculating chi-square, then using the following calculation:
V = SQRT( c2 / (n (k - 1)) )
where c2 is chi-square and k is the number of rows or columns in the table.
Chi-square says that there is a significant relationship between variables, but it does not say just how significant and important this is. Cramer's V is a post-test to give this additional information.
Cramer's V varies between 0 and 1. Close to 0 it shows little association between variables. Close to 1, it indicates a strong association.
Where the table is 2 x 2, use Phi.
Cramer's V is named after the Swedish mathematician and statistician Harald Cramιr.
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