Statistics and Geometry

Correlation is a cosine.

http://www.johndcook.com/blog/2010/06/17/covariance-and-law-of-cosines/

r(X,Y) = cov(X,Y) / sqrt(var(X)*var(Y))
<X,Y> = ||X|| ||Y|| cos(theta)

cos(theta) = <X,Y> / ||X|| ||Y|| = cov(X,Y) / sqrt(var(X)*var(Y)) = r(X,Y)

Sum of squares of X is X X'.

Matrix approach to regression.

X X' B = X Y