2. Prediction

Two types corresponding to the ``data = signal + noise'' paradigm.

Prediction of just the signal or prediction that also includes the noise.

Prediction in the range of the data (interpolation) is pretty safe.

Prediction out of the range of the data (extrapolation) is extremely dangerous.

Prediction for a new observation has 3 sources of uncertainty.

The fit is not quite right - uncertainty in the true regression line.

There's variability about the regression line - noise.

There is uncertainty because this may not be the correct model - model misspecification.