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Lecturer(s)
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Mrkvička Tomáš, prof. RNDr. Ph.D.
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Course content
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Contents of lectures: 1. Descriptive statistics. 2. Student, Chi2, F - distribution. Quantiles. 3. Hypothesis testing. One sample t-test. 4. T-tests, paired and twosample. F-test. Test about variance. 5. Test about mean value with CLT. 6. Theory of estimates. Confidence intervals. 7. Confidence interval with CLT. The size of samples with given length of interval. 8. Correlation coefficient. 9. Descriptive statistics. Histograms, box plot. 10. ANOVA 1 factor. 11. ANOVA 2 factors 12. Simple regression analysis. 13. Multivariate regression analysis.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), E-learning
- Class attendance
- 14 hours per semester
- Preparation for credit
- 30 hours per semester
- Preparation for classes
- 30 hours per semester
- Preparation for exam
- 38 hours per semester
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Learning outcomes
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A basic introductory course devoted to basic principles of statistical reasoning and applications of data analysis.
Student manages the basic principles and methods of probability and statistics.
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Prerequisites
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Prerequisities: Teorie pravděpodobnosti a statistika/Theory of Probability and Statistics 1
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Assessment methods and criteria
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Combined exam
The writing exam has to be passed with at least 50% followed by oral exam, also active attendance of the course is required.
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Recommended literature
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Freeman, J., Shoesmith, E., Sweeney, D., Anderson, D., Williams, T. Statistics for Business and Economics. Cengage, 2017.
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Newbold, P., Clarlson, W., Thorne, B. Statistics for Business and Economics. Prentice Hall, 2010. ISBN 10:0-13-507248-4.
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