Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.
Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.
Covers linear regression basics, focusing on minimizing error using the principle of least squares and includes an ANOVA table and practical example in R.
Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
