b_(yx) gives the expected value of y when x is independent and b_(xy) gives the expected value of x when y is independent, where b_(yx) and b_(xy) are the coefficients of linear regression.
Explanation:
r = sqrt{b_(yx)xxb_(xy) } is the Pearson's coefficient of correlation.