From what I have read you could use Cramér's V test. I've never used it, but it will give a rating of 0 (no association) to 1 (complete agreement), live a Pearson's r correlation but with categorical data.

I'd start there, but given I've never used it, perhaps some more learned colleagues could add to the discussion?

Dear

Thanks for placing such nice question, If two variables are associated, the probability of one will depend on the probability of the other. Chi square tests the hypothesized association between two categorical variables and contingency analysis allows us to quantify their association.

The strength of association between categorical variables can be assessed utilizing the Cramer's V or the Phi. However the Cramer's V is most widely accepted over Phi.

Please note that both are measures of the strength of an association for a Chi-square test.

@Tarig Eltoum.

While Chi square is able to describe the association between independent (categorical) variables, the Chi square value alone is unable to describe the strength of the association between such variables given that the Chi square value is largely dependent on the sample size and whether or not a significant association exists between the variables is largely dependent on the sample size. However, with the Cramer's V or Phi, one is able to explore and describe the strength of the association between such variables. The Cramer's V is quite preferable over Phi most of the time though.

Thanks.

Pearson r

Thanks all for nice answering

One can identify the relation between two variables by using karl pearson's coefficient of correlation method. later on Cramer's V test can be applied to verify the same with strong believe and validation.