Linear Regression EssentialsCovers the essentials of linear regression, focusing on using multiple quantitative explanatory variables to predict a quantitative outcome.
Regression: Linear ModelsIntroduces linear regression, generalized linear models, and mixed-effect models for regression analysis.
Basics of Linear RegressionCovers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Probabilistic Linear RegressionExplores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Linear Regression BasicsCovers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.
Regression: Linear ModelsExplores linear regression, least squares, residuals, and confidence intervals in regression models.