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Lecturer(s)
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Picek Jan, prof. RNDr. CSc.
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Course content
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Point estimation, consistency and unbiasedness, maximum likelihood estimates. Confidence intervals for parameters of normal distribution. Robust and nonparametrical estimates. Testing statistical hypotheses. One-sample and two-sample tests. Analysis of variance. Nonparametrical tests. Hotelling tests. Basics of correlation analysis. Linear regression ? least square method. Tests in linear regression. Goodness of fit tests. Contingency tables, test for independence. Survey sampling.
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Learning activities and teaching methods
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Monological explanation (lecture, presentation,briefing)
- Home preparation for classes
- 20 hours per semester
- Preparation for exam
- 112 hours per semester
- Class attendance
- 56 hours per semester
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Learning outcomes
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Knowledge of advanced statistical methods and their understanding.
Knowledge and ability to apply advanced statistical methods
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Prerequisites
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Knowledge of differential and integral calculus and the fundamentals of mathematical statistics and probability.
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Assessment methods and criteria
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Oral exam, Written assignment
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. Requirements on exam: Knowledge of problem solving, concepts and basic ideas.
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Recommended literature
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ANDĚL, J. Statistické metody. Praha: . Matfyzpress, 2007.
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Hebák, P., Hustopecký, J., Malá, I. Vícerozměrné statistické metody (2). Informatorium, Praha, 2005. ISBN 80-7333-036-9.
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HENDL, J. Přehled statistických metod zpracování dat: Analýza a metaanalýza dat. Praha: Portál, 2012. ISBN 978-80-262-0200-4.
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