Massive regression on RoF

Throw's Pearson's product moment correlation coefficient (r) to establish a measure of linear association between the two variables, where r² is the proportion of the total variance (s²) of Y that can be explained by the linear regression of Y on x, and 1-r² is the proportion that is not explained by the regression. Thus 1-r² = s²xY / s²Y.

I had to do a whole year of my degree in the maths faculty to pass a mandatory statistics ancillary course early on and it has left scars but that is the standard definition of Pearson's R

I just read the Rieman hypothesis. Twice.

I still don't know what it is.

The Riemann zeta function ζ(s) is a function whose argument s may be any complex number other than 1, and whose values are also complex.

Can you have a complex number other than 1 which doesn't have complex values?

I mean seriously.  However much stick lawyers get for jargon, statmaticians should get more.  ow much more, I am not sure.  There was a formula, but it was written in greek and gibberish.  Theta complex argon ringpiece to the power of boron times more.

 

Did some fellow in the university of Bristol not do it a couple of years ago?

(Googles)

 

Yes. some famous maths fellow said in 2017 he had done it, but that he will show everyone his workings 'in a while'.