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Lecturer(s)
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Porkertová Jindra, Ing.
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Mertová Iva, Ing. Ph.D.
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Bajzík Vladimír, doc. Ing. Ph.D.
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Vyšanská Monika, Ing. Ph.D.
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Tunáková Veronika, doc. Ing. Ph.D.
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Course content
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Lectures: 1. Repetition of the work with algebraic equations, expression of the variable from equation. 2. Analytical geometry in a plane. Bisector formula, mutual position of the bisectors. Distance of two points. 3. Real function of the one real variable. Definition domain. Range of values. Graph of function. 4. Operations with the functions. Compound function. Simple function. Limited function on a set. Even, odd function. Periodic function. Elementary function. 5. Differential calculus principle. Limit and continuity of function. 6. Derivation. Geometrical meaning of the derivation. Elementary rules for derivation calculation. 7. Investigation of the function. Local extremes of the function. Convexity and concavity. Inflection points. 8. The basic concepts. Random experiment. Operations with the random phenomenon. 9. Random variable. Discrete random variable. Probability function. Continuous random variable. Probability density. 10. Normal distribution, Gauss curve. 11. Basics of the mathematical statistics. Basic file and random choose. The basic selective characteristic of the position, the distraction and the shape. 12. Methods of the exploratory data analysis. Box plots. Histogram. Empirical distribution function. Data normality and homogeneity verification. 13. Hypothesis testing and intervals of confidence. 14. Dependence of the quantitative quantities. Selective correlation coefficient. Linear regression model. Practices: establish on the lectures. Lectures are practiced on the practices.
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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), Lecture, Practicum
- Class attendance
- 84 hours per semester
- Home preparation for classes
- 20 hours per semester
- Preparation for credit
- 15 hours per semester
- Preparation for exam
- 30 hours per semester
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Learning outcomes
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The subject will introduce the basic principles and methods of the higher mathematics needed for the study of textile technologies and for basic evaluation of measured data. The main accent will be focused on practical usage of these methods for concrete tasks solution.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Written exam, Test
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Recommended literature
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BITTNEROVÁ, D., PLAČKOVÁ G. Část 1, Diferenciální počet funkcí jedné reálné proměnné. Liberec: Technická univerzita v Liberci, 2005. ISBN 80-7083-984-8..
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BONA M. Statistical Methods for the Textile Industry. Torino. Texilia, 1993. ISBN 1870812573..
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HRUBÝ D., KUBÁT J. Matematika pro gymnázia: diferenciální a integrální počet. Praha: Prometheus, 2004. ISBN 80-7196-210-4..
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MELOUN, M., MILITKÝ, J. Kompendium statistického zpracování dat. Praha. Academia, 2002. ISBN 80-200-1008-4..
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NEKVINDA, M. Matematika. Část 1, Liberec: Technická univerzita v Liberci, 2001. ISBN 80-7083-447-1..
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NEKVINDA, M., VILD, J. Matematické oříšky 1, Liberec: TUL 2006. ISBN: 80 7372 017 5..
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