1. Introduction to econometrics (definition of econometrics and microeconometrics, relationship to other scientific disciplines, clarification of basic terms, emergence of econometrics, process of econometric modeling, specifics of microeconometric modeling).
2. Microeconomic data, their structure and analysis.
3. Simple cross-sectional linear regression model (meaning of regression analysis, population versus sample regression line, essence of MNČ, fit of regression line to data, assumptions of classic simple regression model and their verification).
4. Multiple cross-sectional regression model (definition of the classical multivariate linear regression model, assumptions, matrix notation, corrected coefficient of determination).
5. Statistical verification (regression coefficients, model as a whole).
6. Econometric verification - autocorrelation, heteroskedasticity, multicollinearity, normality, model specification.
7. Nonlinear functional forms.
8. Technique of dummy variables.
9. Prediction.
10.Linear panel models (definition of panel models, fixed effects, random effects).
2. Microeconomic data, their structure and analysis.
3. Simple cross-sectional linear regression model (meaning of regression analysis, population versus sample regression line, essence of MNČ, fit of regression line to data, assumptions of classic simple regression model and their verification).
4. Multiple cross-sectional regression model (definition of the classical multivariate linear regression model, assumptions, matrix notation, corrected coefficient of determination).
5. Statistical verification (regression coefficients, model as a whole).
6. Econometric verification - autocorrelation, heteroskedasticity, multicollinearity, normality, model specification.
7. Nonlinear functional forms.
8. Technique of dummy variables.
9. Prediction.
10.Linear panel models (definition of panel models, fixed effects, random effects).