## Multiple Linear Regression

This post is a continuation of Linear Regression. Introduction In multiple linear regression we extend the notion developed in linear regression to use multiple descriptive values in order to estimate the dependent variable, which effectively allows us to write more complex functions such as higher order polynomials ($y = \sum_{i_0}^{k} w_ix^i$), sinusoids ($y = w_1 sin(x) + w_2 cos(x)$) or a mix of functions ($y = w_1 sin(x_1) + w_2 cos(x_2) + x_1x_2$).