Linear regression is a method of finding the linear equation that comes closest to fitting a collection of data points.
The better the choice of line, the closer the predicted values will be to the observed values.
The differences between the data pints (observed values) and the estimated (pedicted) regression line is called the residue.
Residue = Observed Value - Predicted Value
