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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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- Alternative procedures concerning statistical procedures based on the assumption of normality: nonparametric and robust procedures, L and M-estimators, rank tests. - Correlation analysis. - Linear regression analysis: inference and basics of diagnostics. - Multivariate statistical analysis: concept of confidence region, basic estimators and tests, Hotelling test. - Principal component analysis, factor analysis. - Selected topics on statistical quality control and reliability.
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Learning activities and teaching methods
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Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments), Independent creative and artistic activities, Individual consultation, Seminár
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Learning outcomes
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The aim of the subject is to deepen knowledge on basic methods concerning mathematical statistics and data analysis and to acquaint with more advanced methods, with great emphasis on multidimensional methods. The topics discussed should address the needs of Ph.D. students for their professional work.
The student will acquire detailed knowledge of the subject in the area according to the approval of the Branch Board
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Prerequisites
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Unspecified
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Assessment methods and criteria
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Oral exam
oral examination before a committee appointed by the Dean. Written work in the recommended range of 20 pages.
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Recommended literature
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ANDERSON, T. W. An Introduction to Multivariate Statistical Analysis. 2003. ISBN 978-0-471-36091-9.
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Dalgaard, P. Introductory Statistics with R. 2008. ISBN 978-0-387-79053-4.
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Hendl, J. Přehled statistických metod. Praha: Portál, 2012. ISBN 978-80-262-0200-4.
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JUREČKOVÁ, J., P. K. SEN a J. PICEK. Methodological Tools in Robust and Nonparametric Statistics. 2013. ISBN 978-1-4398-4068-9.
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REIMANN C., P. FILZMOSER, R. GARRETT a R. DUTTER. Statistical Data Analysis Explained. 2008. ISBN 978-0-470-98581-6.
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