1. Time series analysis (basic characteristics, graphical analysis, time series transformation, time series decomposition).
2. Linear regression model (formulation, estimation, specification, assumptions, MNC)
3. Verification of the estimated model (statistical verification, autocorrelation, heteroskedasticity, multicollinearity, economic verification).
4. Prediction (classification of forecasts, point and interval prediction, ex-post and ex-ante prediction, prediction accuracy).
5. Testing the normality of the residual component (graphical assessment, sophisticated statistical tests).
2. Linear regression model (formulation, estimation, specification, assumptions, MNC)
3. Verification of the estimated model (statistical verification, autocorrelation, heteroskedasticity, multicollinearity, economic verification).
4. Prediction (classification of forecasts, point and interval prediction, ex-post and ex-ante prediction, prediction accuracy).
5. Testing the normality of the residual component (graphical assessment, sophisticated statistical tests).