Delves into regression analysis, emphasizing linear predictors' role in approximating outcomes and discussing generalized linear models and causal inference techniques.
Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.
Covers modeling temporal dependence in time series, including trend, periodic components, regression, stationarity, autocorrelation, and independence testing.
