Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.
Explores linear regression, least squares, residuals, and confidence intervals in regression models.
Explores nested model selection in linear models, comparing models through sums of squares and ANOVA, with practical examples.
Explores heteroskedasticity and autocorrelation in econometrics, covering implications, applications, testing methods, and hypothesis testing consequences.
