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Lecturer(s)
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Husáková Lenka, doc. Ing. Ph.D.
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Course content
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1. Types of data structures, data visualization tools and software, probability distributions, descriptive statistical characteristics, data transformations, centering and scaling 2. Efficient moment estimation with extremely small sample size, statistical hypothesis testing 3. Analysis of variance (ANOVA) 4. Building linear regression models, correlation analysis 5. Precision limits and interval estimation in the calibration, method validation 6. Nonlinear regression models 7. The principles of multivariate exploratory data analysis 8. Principal component analysis (PCA) 9. Factor analysis (FA) 10. Canonical correlation analysis (CCA) 11. Discriminant analysis (DA) 12. Logistic regression (LR) 13. Cluster analysis (CLU)
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Skills training
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Learning outcomes
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The aim of this course is to provide basic knowledge of the common statistical methods in a practical way and without extensive mathematical derivations. The course participants receive a systematic introduction to the various possibilities of the data analysis software. The training consists of an explanation of the data analysis procedures and possible fields of application. Examples in the course are generally understandable data sets from different application areas.
Students will be able to understand basic theoretical and applied principles of statistics and use these for data management, analysis and problem solving.
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Prerequisites
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To take full advantage of the training, students should be familiar with the graphical user interface of the Windows operating system. Basic mathematical and statistical knowledge would be advantageous but is not necessary.
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Assessment methods and criteria
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Written examination, Home assignment evaluation
Students will apply various data science skills, techniques, and tools to complete a project and publish a report.
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Recommended literature
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MELOUN, M.; MILITKÝ, J. Interaktivní statistická analýza dat. 3. vyd. Praha: Karolinum, 2012.
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MELOUN M, MILITKÝ J. Kompendium statistického zpracování dat. 3. vyd. Praha: Karolinum, 2012.
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