Context:
As you saw in both Simple Linear Regression and Multiple Linear Regression, they’re both calculated with a degree of noise.
Real Example
Imagine making a regression model to estimate the height of a plant given the amount of water it’s received, aggregated per day. The general trend is obvious - more water, taller plants. But the model will rarely be perfect. There’s an element of error, independent of either or , that comes with the challenge.