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Lecturer(s)
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Volf Petr, doc. CSc.
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Picek Jan, prof. RNDr. CSc.
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Course content
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Introduction to probability and mathematical statistic. Basic and graphic analysis of data using computer (Excel, Matlab). 1. Descriptive Statistics: Types of variables, basic characteristics of location and variability. Ordered data, median, quantiles. Graphic data processing. 2. Graphic analysis of data, making graphs in Excel, Matlab. 3. Random variable. Distribution function and its properties, density, quantile function. Characteristics of random variables. The law of large numbers. 4. Discrete random variables: alternative, binomial, negative binomial, hypergeometric, Poisson. 5. Continuous distributions: normal distribution, uniform, exponential, Weibull. 6. Conditional probability, independence of random events 7. The central limit theorem. 8. Multivariate random variable (vector), the dependence - covariance and correlation coefficient 9. Introduction to Mathematical Statistics. Point and interval estimates. 10. Basic concepts of statistical hypothesis testing. Tests of hypotheses on the parameters of the normal and binomial distribution. 11. One-way analysis of variance. Non-parametric tests. 12. Goodness of fit tests. 13. Correlation and regression. Spearman's coefficient of serial correlation. 14. Linear regression, method of least squares. Regression diagnostics.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Class attendance
- 70 hours per semester
- Preparation for credit
- 80 hours per semester
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Learning outcomes
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Elements of probability theory, data analysis and statistics.
Basic knowledge of mathematical statistics and probability
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Prerequisites
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Basic knowledge of differential and integral calculus (first year)
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Assessment methods and criteria
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Oral exam, Written exam
Requirements on credit: two tests of the subject matter. The date of each test will be announced in advance by teacher. It is necessary to get score at least 50% for each test. Semestral work. Requirements on exam: Knowledge of problem solving, concepts and basic ideas. Discussion on semestral work.
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Recommended literature
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BÍLKOVÁ, D., BUDINSKÝ P., VOHÁNKA V. Pravděpodobnost a statistika. Plzeň: Aleš čeněk, 2009. ISBN 978-80-7380-224-0.
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GURINOVÁ, K., HOVORKOVÁ VALENTOVÁ , V. Základy práce s programem STATGRAPHICS CENTURION XVI. Liberec, 2011. ISBN 978-80-7372-810-6.
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HENDL, Jan. Statistika v aplikacích. Praha: Portál, 2014. ISBN 978-80-262-0700-9.
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HOLČÍK J., KOMENDA M. Matematická biologie: e-lerningová učebnice [online]. Brno: MU, 2015. ISBN 978-80-210-8095-9.
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MAREK, L. et al. Statistika v příkladech. Praha, 2015. ISBN 978-80-7431-153-6.
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NEUBAUER, Jiří, Marek SEDLAČÍK a Oldřich KŘÍŽ. Základy statistiky: aplikace v technických a ekonomických oborech. Praha: Grada, 2016. ISBN 978-80-247-5786-5.
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ZÁŠKODNÝ, Přemysl a Helena ZÁŠKODNÁ. Metodologie vědeckého výzkumu. Praha: Curriculum, 2016. ISBN 978-80-87894-08-8.
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ZÁŠKODNÝ, Přemysl a kol. Základy statistiky s aplikací na zdravotnictví. Praha: Curriculum, 2016. ISBN 978-80-87894-12-5.
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