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Lecturer(s)
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Course content
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1. Analysis of variance. 2. Measuring of dependence of categorical data. 3. Numeric variables and their dependence. 4. Simple linear regression. 5.-6. Multiple linear regression. 7.-8. Correlation. 9. Time series analysis. 10. Trend analysis. 11. Seasonality. 12. Forecasting. 13. Non-parametric methods. 14. Reserve.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Class attendance
- 56 hours per semester
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Learning outcomes
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The second part of this statistics course is applied to regression theory, correlation, contingency tables, time series analysis and statistics comparison principles.
Students obtain knowledge in given course in accordance with requirements and course programme.
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Prerequisites
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Courses: Statistics I and Mathematics I, Mathematics II (calculus). Computer skills.
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Assessment methods and criteria
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Combined examination, Written exam
Courses ST1_A; computer skills.
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Recommended literature
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FREUND, J., SIMON, G. Modern elementary statistics. Prentice-Hall. New Jersey 1992..
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MANN,P. Statistics for business and economics. Wilez New York 1995.
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TREŠL, J. Success in statistics. Učební texty VŠE. Praha 1998.
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VAN MATRE, J., GILBREATH, G. Statistics for business and economics. Business Publ. Homewood 1987.
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