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Lecturer(s)
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Course content
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1. Business and economic data sources (EUROSTAT, databases in the ZČU library, CSU, ..) 2. Economic time series 3. Approaches to time series analysis 4. Panel data 5. GRETL software (installation, data import, basics) 6. Time series in GRETL 7. Panel data in GRETL 8. Time series in STATISTICA software 9. Data visualization, dashboard 10. Power BI, Google Data Studio
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Learning activities and teaching methods
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- Individual project (40)
- 26 hours per semester
- Presentation preparation (report in a foreign language) (10-15)
- 13 hours per semester
- Preparation for an examination (30-60)
- 39 hours per semester
- Contact hours
- 26 hours per semester
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| prerequisite |
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| Knowledge |
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| Apply statistical methods within the scope of the KEM/STA course. |
| Skills |
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| Calculate statistical characteristics within the scope of the KEM/STA course. |
| Competences |
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| Knowledge of Aj at B2 level. |
| learning outcomes |
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| Knowledge |
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| They can explain theoretical procedures in time series analysis. |
| Skills |
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| Can analyse time series using appropriate software. |
| teaching methods |
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| Knowledge |
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| Lecture supplemented with a discussion |
| Self-study of literature |
| Lectures and presentations on key business analytics concepts, tools, and techniques. Online resources, readings, and multimedia materials for self-study and deeper understanding of the subject. |
| Skills |
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| Lecture supplemented with a discussion |
| Collaborative instruction |
| Practicum |
| Competences |
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| Lecture supplemented with a discussion |
| Practicum |
| Discussion |
| assessment methods |
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| Knowledge |
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| Combined exam |
| Assessment Structure 1. Weekly Assignments (30%): Practical exercises with analytical tools. 2. Midterm Test (20%): Theoretical and practical questions. 3. Final Project (40%): Team project using real-world or simulated data. 4. Class Participation (10%): Contributions to discussions and teamwork. |
| Skills |
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| Combined exam |
| Group presentation at a seminar |
| Combined exam |
| Competences |
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| Combined exam |
| Group presentation at a seminar |
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Recommended literature
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Alan Agresti, Christine A. Franklin, Bernhard Klingenberg. Statistics: The Art and Science of Learning from Data, Global Edition. PEARSON Education Limited, 2022. ISBN 1292444762.
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McClave, James T.; Benson, George; Sincich, Terry. Statistics for business and economics. 14th edition. 2022. ISBN 978-1-292-41339-6.
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Newbold, P., Carlson, W., Thorne, B. Statistics for Business and Economics. Pearson Education Limited.
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