Up to now I used correlations to study whether two variables are affected by each other. Now I stumbled over the case that the chi square is doing that too ( http://www.r-tutor.com/elementary-statistics/goodness-fit/chi-squared-test-independence ). Where's the difference respectively which one is more suitable?
In the same context I found https://www.rdocumentation.org/packages/mvoutlier/versions/2.0.9/topics/chisq.plot where "the ordered robust mahalanobis distances of the data against the quantiles of the Chi-squared distribution" is plotted. This is now very confusing as I'm used to apply the Mahalanobis distance to measure similarities. And now it is connected with chi square.
Can you please help me to separate them?