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Innovative Approaches To Improving The Quality Of Education At The University

Table 2: Content of practical classes

№ Practical topics Content
Section 1. Introduction to econometrics
1.2 Laws of distribution of random variables. Statistical conclusions: estimates and hypothesis testing Practical lesson № 1. Analysis of the distribution of statistical data sets.
Practical lesson № 2. Testing the hypothesis of the coincidence of the regression equations for two samples.
Section 2. Regression models
2.1 Paired, multiple linear regression. Nonlinear regression Practical lesson № 3. Building a linear regression model.
Practical lesson № 4. Using the Box-Cox and Paul Zarembka tests to select a regression model.
2.2 Checking the overall quality of the regression equation Practical lesson № 5. Gauss-Markov Prerequisites.
Practical lesson № 6. Checking the predictive qualities of the regression equation.
Practical lesson № 7. Time series forecasting based on regression equations.
Section 3. Background of the least squares method.
3.1 Heteroscedasticity Practical lesson № 8. Methods for detecting heteroscedasticity.
3.2 Autocorrelation Practical lesson № 9. Autocorrelation detection methods.
3.3 Multicollinearity Practical lesson № 10. Multicollinearity detection and mitigation methods.
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