dproberts / LinearRegression / 0.1.0

In statistics, linear regression is an approach to model the relationship between a scalar dependent variable y and one or more explanatory variables denoted X. This algorithm takes a list of points (floating point pairs), and returns coefficients to the linear equation of the form: y = beta0 + beta1 * x And also the r^2 correlation coefficient.