Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.
Covers the essentials of linear regression, focusing on using multiple quantitative explanatory variables to predict a quantitative outcome.
Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Explores the linear regression model, OLS properties, hypothesis testing, interpretation, transformations, and practical considerations.
