12.1 Learning Objectives

At the end of this week’s learning students will be able to

1. Describe the assumptions of the classical linear model (sometimes referred to as the Gauss-Markov Assumptions) and what each assumption contributes to the estimator.
2. Evaluate using empirical methods, whether each of the assumptions are likely to be true of the population data generating function.
3. Assess whether the guarantees that are provided by the classical linear model’s requirements are likely to ever be true, including within data the student is likely to encounter.