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Lecturer(s)
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Krejčová Anna, doc. Ing. Ph.D.
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Course content
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Lectures Brief introduction to data evaluation. Kinds of errors, accuracy, precision, terminology. Uncertainty - definition, components, procedure of estimation, practical enumerations. Basic analytical operations and uncertainties, examples of enumerations. Credibility of laboratories - quality managent systems, conceptions, historical development, Czech and European valid legal regulations. Accreditation of chemical laboratories. Regulation ČSN EN ISO/IEC 17025, terminology, accreditation bodies and procedures in Czech Republic. Quality guide, standard operation procedure - basic scheme, practical examples. Metrology and traceability in chemistry, law on metrology. Insurance of traceability in biochemical and chemical laboratory. Certified reference materials, preparation, certification, databases. Proficiency testing, aim, evaluation, providers. Sampling - definition and properties of samples. Practical examples. Choice of optimal method - evaluation of factor considered. Validation of analytical methods, parameters, software, practical examples. Quality, assurance/control, documents. Regulation diagrams. Seminar Credibility of lab - quality management systems, concepts, current laws, Czech and European standards. Quality Manual. Standard operating procedure. The sampling protocol. Report on the results. The basic structure, practical examples. Introduction to data analysis. Types of errors. Correctness, accuracy, consistency. Uncertainty - definition, components, process for estimating uncertainty practical calculations. Basic operations and analytical uncertainties, examples of calculations. Measures of location, dispersion and shape. Point and interval estimates. Practical examples from biochemical and chemical laboratories. Hypothesis testing. Practical examples from biochemical and chemical laboratories. Analysis of variance. Practical examples from biochemical and chemical laboratories. Linear regression. Practical examples from biochemical and chemical laboratories. The selection of optimal methods - evaluation factors considered. Validation of analytical methods, data, software, practical examples. Quality, security, management and auditing. The quality system documentation. Control charts.
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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 the subject is: To build a general image of the latest knowledge from the area of the good laboratory practice, accreditation of laboratories and system of quality control and to harmonize student's knowledge with valid legal regulations of Czech Republic and European Union. Make studenty familiar with the documents filed in laboratory working in one of the quality management systems. Provide students with simple statistical procedures on a computer to analyze experimental one-dimensional data and learn to work with software tools (Excel, Effivalidation). Teach students how to apply statistical tools in routine laboratory practice when handling chemical data.
After graduation of the subject, students will be able to orientate in the current system of the quality assurance of data and will gain a practical qualification necessary for specialist ensuring quality assurance and quality control in biochemical, chemical laboratories and institutions in the area of environmental protection. After passing the course, student are able to simply evaluate one-dimensional laboratory data, estimate uncertainties, parameters of location, dispersion and shape, to test the accuracy and consistency, and find outlier values, to extracted from the data the maximum amount of useful information. Students can work with analysis of variance and linear regression. They can apply the statistical resources in laboratory practice to solve common operational tasks, such as validation of methods.
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Prerequisites
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Basic PC skills are demanded. There are no special requirements for students or the assumptions on the prior knowledge of statistics and mathematics. Students should be familiar with using a computer and basic software (eg Microsoft Office), and when working with text and graphs.
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Assessment methods and criteria
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Oral examination, Written examination, Student performance assessment
In the half of the tern, knowledge are tested and the result is taken to the final classification. The final exam has written and oral part. Basic PC skills are required. There are no special requirements for students or the assumptions on the prior knowledge of statistics and mathematics. Students should be familiar with using a computer and basic software (eg Microsoft Office), and when working with text and graphs.
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Recommended literature
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Platné české právní předpisy a normy.
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Crosby, N. T., Prichard, F. E. Quality in the Analytical Laboratory.
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Crosby, N. T., Prichard, F. E. Quality in the Analytical Laboratory. Chichester, 1995.
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Mestek, O., Nondek, L. Zásady správného odběru vzorků pro analýzu životního prostředí. Praha, 1995.
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