Calculate number of "exceptions" to correlation

by Pearson's Are   Last Updated October 07, 2018 15:19 PM

My question: Is there a formula to calculate analytically the expected number of "exceptions" which the simulator generates, as explained in the passage below?

For most of my adult life I've been explaining to people that "exceptions," meaning examples running counter to the trend, do not disprove claims that there's a correlation between two variables.

To get a good idea of the percentage of examples which will be "exceptions" to a correlation, check out the correlation simulator at rlanders.net/correlation.html.

Image

For a positive correlation, the "exceptions" are the dots in the upper left and lower right quadrants. As the correlation coefficient is set to higher values, the number of exceptions will tend to decrease. But, as is easily seen, even at high values there are more "exceptions" than you may think.



Answers 1


Partially answered in comments:

The geometric analysis in my post can be used to show the expected proportion of exceptions when the data are bivariate Normal (which is what this calculator assumes) is arccos(ρ)/π. – whuber

This post is also relevant

kjetil b halvorsen
kjetil b halvorsen
October 07, 2018 15:00 PM

Related Questions





Multivariate asymmetric generalized gaussian distribution

Updated September 22, 2017 11:19 AM