Lecturer(s)
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Mrkvička Tomáš, prof. RNDr. Ph.D.
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Course content
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1. Probability 2. Random variable 3. Discrete 4. Continuos 5. Random vector 6. Central limit theorem 7. Data processing 8. Random sample 9. Interval estimate 10. Hypothesis testing 11. Hypothesis testing 12. Comparison of more samples 13. Correlation analysis 14. Linear regression
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing)
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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 in biology. Students acquire the ability to apply properly the statistical methods in biology. This includes also correct sampling and experimental design, and correct interpretation of results of statistical analyses. The program is designed according to the needs of students analyzing data in their own projects, particularly in preparation of their thesis.
Students understand the basic principles of statistical methods and probability. Students are able to carry out hypothesis testing and regression analysis.
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Prerequisites
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The course has no prerequisities.
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Assessment methods and criteria
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Combined exam
Credit Requirements: Attendance in lab Examination Requirements: To pass written part of exam you have to solve absolute majority of problems.
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Recommended literature
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Available at: http://bookboon.com/cs/ucebnice/statistika/statistics-for-business-and-economics.
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Fernandes, M. Statistics for Business and Economics. Ventures Publishing Aps., 2011. ISBN 978-87-7681-481-6.
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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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Sokal, R. R. and Rohlf, F. J. (1981) Biometry, 2nd ed. Freeman & Comp., San Francisco.
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Zar, J. H. (2009) Biostatistical analysis, 5th. ed. Prentice-Hall, Englewood Cliffs, N. J..
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