QA 7. Linear Regression

Learning Objectives

1) Describe the models which can be estimated using linear regression and differentiate them from those which cannot.

2) Interpret the results of an ordinary least squares (OLS) regression with a single explanatory variable.

3) Describe the key assumptions of OLS parameter estimation.

4) Characterize the properties of OLS estimators and their sampling distributions.

5) Construct, apply and interpret hypothesis tests and confidence intervals for a single regression coefficient in a regression.

6) Explain the steps needed to perform a hypothesis test in a linear regression.

7) Describe the relationship between a t-statistic, its p-value and a confidence interval.

8) Estimate the correlation coefficient from the $R^2$ measure obtained in linear regressions with a single explanatory variable.