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Last update: Bělohlav Zdeněk prof. Ing. CSc. (30.08.2013)
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (30.08.2013)
Students will be able to: process data from laboratory experiments and industrial measurements, comprehensively and reliably interpret the results of statistical data processing, propose optimal design of experiments, operate representative software for statistical data processing. |
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (03.02.2015)
A: Joglekar A. M.: Industrial statistics. Wiley, Hoboken 2010. 9780470497166 |
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (30.08.2013)
http://www.vscht.cz/kot/cz/studijni-materialy.html |
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (21.08.2018)
1. Podmínkou udělení zápočtu je zvládnutí základních metod zpracování a vyhodnocování dat, prověřené v pravidelných testech během semestru 2. Zkouška je založena na samostatném vypracování souboru praktických úloh s možností využití libovolných pomůcek a studijních opor |
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (30.08.2013)
1. Principles of data analysis, properties of the measured data, experiments versus observations. 2. Statistical analysis of the data, sample problems, application software. 3. Direct acquisition of information from measured data, analysis of the sample characteristics. 4. Time series analysis, data sorting, design of experiments. 5. Mathematical models, mechanistic, empirical and semi-empirical models. 6. Methods of optimal estimation of model parameters, software for regression analysis. 7. Models with differential equations, derivatives of dependent variables, integration of differential equations. 8. Evaluating the reliability of regression parameters, confidence intervals, correlation of parameters. 9. Evaluating the reliability of simulated data, analysis of variance and residual variation. 10. Treatment of data for regression analysis, elimination of remote measurements, transformation of variables. 11. Treatment of regression models, model transformation, elimination of strong correlation of parameters. 12. Design of experiments, the optimum number of responses and the range of experimental conditions. 13. Sequential design of experiments, model discrimination and refinement. 14. Factorial and empirical design of experiments, full and fractional factorial design. |
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Last update: Bělohlav Zdeněk prof. Ing. CSc. (30.08.2013)
Mathematics I, Applied Statistics |
Teaching methods | ||||
Activity | Credits | Hours | ||
Konzultace s vyučujícími | 0.5 | 14 | ||
Účast na přednáškách | 0.5 | 14 | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1 | 28 | ||
Příprava na zkoušku a její absolvování | 1 | 28 | ||
Účast na seminářích | 1 | 28 | ||
4 / 4 | 112 / 112 |
Coursework assessment | |
Form | Significance |
Regular attendance | 30 |
Examination test | 30 |
Oral examination | 40 |