Thanks for the answer
"Differing from the average of all cases", doesnt really make sense to me, because if we use it to detect outliers we are supposing the values should be distributed in a spere, defeating the purpose of a bivariant outlier-detection, which should include some sensitivity for 2 correlated variables.
http://en.wikipedia.org/wiki/Mahalanobi ... xplanation
Maybe I got it all wrong though.
And the reason why I was surprised that moving the IV to DV and vice versa, is that the scatterplot and the correlation and the outliers all of course stay the same, so if i want to use the Mahalobis distances to detect outliers, they should too.
So maybe Im totally lost.
So here is my basic question, I have scatterplot with two psychometric measures and two measures seem to be outliers distorting the correlation, how do I formally detect them and what can I do with them?