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Lecturer(s)
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Dostálková Iva, doc. RNDr. Ph.D.
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Course content
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Content of lectures: 1. Combinatorics 2. Discretete probability, 3. Axiomatic definition of probability, conditional probabilty. 4. Bayes Theorem, random variable. 5. Charakteristics of random variables. 6. Basis statistics. 7. chi^2 test 8. contingency tables 9. t-tests 10. ANOVA 11. nonparametric tests 12. linear regression 13. nonparametric regression
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Work with text (with textbook, with book)
- Preparation for classes
- 28 hours per semester
- Preparation for credit
- 28 hours per semester
- Preparation for exam
- 28 hours per semester
- Class attendance
- 28 hours per semester
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Learning outcomes
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Students master basic principles of probability and statistics.
the basic statistical methods
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Prerequisites
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basic mathematics
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Assessment methods and criteria
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Written examination
To complete the course it is necessary to pass the credit and pass the exam. To gain credit, sufficient attendance at the exercises and sufficient average success rate (50%) in short practice tests. Credit is a prerequisite for the exam test. The exam is written and is successful in reaching 50% of the test.
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Recommended literature
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http://cast.massey.ac.nz/collection_public.html.
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Sokal, R.R., Rohlf, F.J. : Biometry. 3rd ed., San Francisco, Freeman and Comp., 1995.
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Zar, J.H.: Biostatistical analysis. 2nd ed., Engelwood Cliffs Prentice - Hall,1984.
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