Real world problems for which regression is an appropriate tool generally fall into two categories:
- Prediction: Predicting the response of a new unit/individual, sometimes also describing uncertainty in the prediction.
- Interpretation: Interpreting how predictors influence the response.
For example, consider a person undergoing artificial insemination.
- Prediction: Given the person's age, what is the chance of pregnancy?
- Interpretation: How does age influence the chance of pregnancy? How does time of insemination after a spike in Luteinizing hormone affect the chance of pregnancy, and how is this different for people over 40?
This course does not focus on optimizing predictions, but focusses on the other tasks. This means:
- describing the uncertainty in predictions, or estimates in general, and
- interpreting how predictors influence the response.
Why not focus on optimizing predictions? This is the objective of supervised learning, an entire discipline in itself.