the statistical properties of the resulting estimators are easier to determine.

Linear regression has many practical uses. Most applications fall into one of the following two broad categories:
* If the goal is to reduce error, i.e. variance in prediction or forecasting, linear regression can be used to fit a predictive model to an observed data set of values of the response and explanatory