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Lecturer(s)
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Tuček Pavel, doc. Mgr. Ph.D.
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Berka Karel, doc. RNDr. Ph.D.
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Course content
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" theory of errors , rounding off results, measurement, errors- random, systematic, gross errors " unidimensional random quantity, discrete and continuous variable " distribution function, frequency function " random quantity distributions laws - binomical, Poisson, normal, 2, Student distribution " statistical measures of location and dispersion, theory of estimate, point estimate, fractil, interval estimation " result evaluation, tests " result processing and presentation " mathematic model option and its parameters determination " target function, minimization problem " linear regression and its coefficients " linear transformation " statistical weights " multiple linear regression
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Learning activities and teaching methods
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Lecture
- Attendace
- 39 hours per semester
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Learning outcomes
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The course acquaints students with the procedures for processing of results and methods of their presentation.
Recall basic mathematical conceptions in statististic calculations in data analysis, and basic conceptions in data acquisition (measurements). Describe general properties of the concept of probability density, basics of statistical methods of data analysis, coverage interval, linear regression method and interpretations of their results.
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Prerequisites
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knoweledges of secondary school maths, physics and chemistry
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Assessment methods and criteria
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Written exam, Student performance
Min. 50% successfulness in written test (sayllabus extent), full attendance in seminar.
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Recommended literature
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J. Pavlík. (2005). Aplikovaná statistika. 1. vyd.. VŠCHT, Praha.
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L. Kirkup, B. Frenel. (2006). An introduction to Uncertainity in Measurement. Cambridge Univ.Press.
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O. Pytela. (1990). Chemometrie pro organické chemiky. VŠCHT, Pardubice.
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Otyepka, M., Banáš, P., Otyepková, E. (2013). Základy zpracování dat. VUP Olomouc.
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