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Lecturer(s)
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Course content
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Characteristics of the statistical set with regard to use them in metrology (distribution of stochastic quantity, distribution function and probability density, characteristics of position, variability, skewness and acuteness, normal, student and other metrologically important distribution of probability density) <li>Systematization of distribution functions (Pearson system, Johnson system and Burr system) <li>Regression analysis (selection of criteria of the best correspondence, selection of type of approximation function, least-square method, linearization of functions) <li>Introduction to the theory of errors and uncertainties (definition of an error and uncertainty, calculation of uncertainties, uncertainty of A type and B type, combined uncertainty, coefficient of extension, extended uncertainty) </ul>
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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Characteristics of the statistical set with regard to use them in metrology. (
Knowledge Define the main ideas and conceptions of the subject, describe the main approaches of the studied topics, recall the theoretical knowledge for solution of model problems.
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Prerequisites
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unspecified
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Assessment methods and criteria
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unspecified
<ul> <li> Passing the written examination (minimum of 65 % of points out of the maximum test score) <li> Passing the oral examination (knowledge of the course topics, ability to discuss about the course topics in wider contexts) </ul>
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Recommended literature
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Dokument EA 4/02: Vyjadřování nejistot měření při kalibraci.
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(1993). Guide to the Expression of Uncertainty in Measurement (GUM). ISO Geneva.
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Kubáček, L.; Kubáčková, L. (2000). Statistika a metrologie. UP Olomouc.
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Mlčoch, J.; Rössler, T. (2005). Teorie měření a experimentu. UP Olomouc.
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