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Lecturer(s)
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Jahodová Berková Andrea, Mgr. Ph.D.
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Course content
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1. Population and random sample, methods of descriptive statistics 2. Important theoretical probability distributions; fitting random number 3. Testing hypotheses 4. Nonparametric methods 5. Correlation 6. Linear regression 7. Some multivariate methods
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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The main goal is to introduce students to the use of statistical software using the programme Statistica and MS Excel.
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Prerequisites
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Erasmus students should first pass the course Theory of Probability and Statistics ( have knowledge of the probability distribution, theory of estimation, testing hypotheses, correlation and regression analysis).
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Assessment methods and criteria
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Presentation
Examination: The student`s task will be to find useful data and prepare a data file for statistical analysis. After that he will be asked to perform an adequate statistical analysis on this data file and use the results for preparation of a presentation. He will be required to show the presentation to the class. His evaluation will be based on this presentation. The main criteria for evaluation will be: a correct form of data table and data cleansing, correct use of statistical methods, correct interpretation of the results.
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Recommended literature
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Statistica - electronic manual.
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Montgomery, D. C., Runger G. C. Applied Statistics and Probability for Engineers. John Willey & Sons, 2007. ISBN 0-471-74589-8.
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SPIEGEL, M.R., SCHILLER, J.J., SRINIVASAR, R. Probability and Statistics. McGraw-Hill, 2000. ISBN 0-07-135004-7.
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Voelker, D., Orton, P., Adams, S. Statistics. Wiley Publishing, 2001. ISBN 0-7645-6388-2.
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Záhorová, V. Theory of Probability and Statistics (in preparation).
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