| Course Unit Code | 639-3002/05 |
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| Number of ECTS Credits Allocated | 5 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | English |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| TOS012 | Ing. Filip Tošenovský, Ph.D. |
| Summary |
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The subject econometrics expands the subject matter of regression analysis, so that it complies with requirements of diverse industries, and quality management in particular.
Studied are conditions under which standard techniques of modelling relations among variables are usable, and also alternative techniques for the cases when the standard methods fail due to a specific character of datasets - something that occurs often in industrial applications. The subject matter is extended with the theory of time series - the classical and particularly the Box-Jenkins methodology. The latter finds its applications within quality management when nonstandard control charts are constructed. The classical structure of the subject is further complemented with the Taguchi loss functions, a basis for evaluation of low quality - induced financial losses.
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| Learning Outcomes of the Course Unit |
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Knowledge of methods of econometric analysis usable in quality management: regression modelling of relations among variables under standard and nonstandard data conditions, the Box-Jenkins time series analysis applicable to construction of nonstandard control charts, the Taguchi loss functions for evaluating low quality - incurred financial losses.
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| Course Contents |
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1. Classical regression and its applications in industry
2. Modelling in industries and the problem of heteroscedasticity
3. Modelling in industries and the problem of multicollinearity
4. Time series, their typology and characteristics
5. Modelling in industries and the problem of autocorrelation described by time series
6. Control charts and ARMA models for stationary time series
7. ARIMA models for nonstationary time series
8. Modelling time series with moving averages and exponential smoothing
9. Taguchi loss functions |
| Recommended or Required Reading |
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| Required Reading: |
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TOŠENOVSKÝ, F. Econometrics. Studijní opora. Dostupné z: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://lms.vsb.cz/pluginfile.php/2886695/mod_resource/content/1/Econometrics.pdf
WOOLDRIDGE, J.M. Introductory Econometrics. 8th Edition. 2025. Cengage Learning. ISBN-13: 978-0357900161.
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TOŠENOVSKÝ, F. Ekonometrické metody. Studijní opora. Dostupné z: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://lms.vsb.cz/pluginfile.php/2886695/mod_resource/content/1/Econometrics.pdf
WOOLDRIDGE, J.M. Introductory Econometrics. 8th Edition. 2025. Cengage Learning. ISBN-13: 978-0357900161.
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| Recommended Reading: |
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ASTERIOU, D., HALL, S.G. Applied Econometrics. 4th Edition. 2021. Bloombsbury Publishing PLC. ISBN: 9781352012026
MONTGOMERY, D.C., PECK, E.A., VINING, G.G. Introduction to Linear Regression Analysis. 2021. Wiley. ISBN-13: 978-1119578727
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ASTERIOU, D., HALL, S.G. Applied Econometrics. 4th Edition. 2021. Bloombsbury Publishing PLC. ISBN: 9781352012026
MONTGOMERY, D.C., PECK, E.A., VINING, G.G. Introduction to Linear Regression Analysis. 2021. Wiley. ISBN-13: 978-1119578727
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| Planned learning activities and teaching methods |
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| Lectures, Tutorials, Project work |
| Assesment methods and criteria |
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| Tasks are not Defined |