| Week |
Topics |
| 1. Week |
Definition of econometrics, relation with management science, aim of econometrics, general view of econometrics topics, usig the econometrics methods in management science. |
| 2. Week |
Linear correlations, rank correlations estimation and interpretation. |
| 3. Week |
Simple linear regression model, standart assumptions for the simple linear regression model, Gauss-Markow theorem, least squre estimation method. |
| 4. Week |
The explanatory power of a linear regression equqtion, confidence intervals and hypothesis tests. |
| 5. Week |
Prediction and confidence intervals of predictions, examples for management science. |
| 6. Week |
The Multiple regression model and its assumptions. Matrix form of the models. Estimation of the model parameters. |
| 7. Week |
Confidence intervals and hypothesis tests for individual regression parameters. Interpretations of the tests results. Prediction. |
| 8. Week |
Computer packages for regression computing: SPSS and R language. |
| 9. Week |
Model building methodology. Model specification, coefficent estimation, model verification, interpretation and inference. |
| 10. Week |
Useage and interpretations of the dummy and the lagged dependent varianbles. |
| 11. Week |
Non linear models, useage and interpretation of the log linear model. |
| 12. Week |
Deviations from assumptions: Multicollinearity, heteroscedasticity. |
| 13. Week |
Serially dependent error terms, autocorrelation tests and solving the dependent error problem. |
| 14. Week |
Misspecificatin tests. |