The main goal of using linear regression is to predict a numeric target value. One way to do this is to write an equation for the target value with respect to the inputs. For example, assume that we are trying to forecast the acceptance rate of a fully rounded student who participates in sports and music, but belongs to a low-income family.

One possible equation is *acceptance = 0.0015*income + 0.49*(participation_score)*; this is a regression equation. This uses a simple linear regression to predict a quantitative response with a single feature. It takes the following form:

Together, *β*_{0} and *β*_{1} are called the model coefficients. To ...

Start Free Trial

No credit card required