651-2086/01 – Chemometry (ChM)
| Gurantor department | Department of Chemistry and Physico-Chemical Processes | Credits | 4 |
| Subject guarantor | doc. Ing. Jiřina Vontorová, Ph.D. | Subject version guarantor | doc. Ing. Jiřina Vontorová, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2022/2023 | Year of cancellation | |
| Intended for the faculties | FMT | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
Knowledge of basic chemometric concepts, validation parameters and procedures for statistical evaluation of measured data.
Practical use of available software for chemometric calculations and for processing measured data.
Teaching methods
Lectures
Tutorials
Summary
Předmět si klade za cíl seznámit studenty s problematikou pravděpodobnosti, statistiky a zpracování dat. Studenti se naučí využívat validační postupy a správně vyhodnocovat naměřená data. Hlavní důraz je kladen na použití dostupného počítačového software k chemometrickým výpočtům a dalším aplikacím. Cílem předmětu je mimo jiné i pomoci studentům při zpracování naměřených dat v rámci závěrečných a dalších výzkumných prací.
Compulsory literature:
Recommended literature:
Additional study materials
Way of continuous check of knowledge in the course of semester
Classified credit.
E-learning
https://www.vsb.cz/e-vyuka/en/subject/651-2086/01
Other requirements
1. Attendance at seminars - 90%.
2. Submission of semester work (MS Word).
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Definition of the chemometry. Theory of the probability and its definition. Conditional probability.
2. Theory of errors. Classification of the errors.
3. Random variable. Definition of random variable. Discrete and continuous random variable. Histogram, histogram design. Polygon.
4. Analysis of one-dimensional data.
5. Analysis of small data sets. Horn's method.
6. Exploratory analysis.
7. Statistical tests - one-dimensional analysis.
8. Statistical tests - comparison of two samples.
9. Analysis of variance, ANOVA. One-way ANOVA.
10. Two-way ANOVA.
11. Linear regression. Effective data (outliers observations, extremes).
12. Calibration.
13. Validation. Definition of the validation, validation process, types of validation, validation parameters (accuracy of the method, repeatability, output error, deviation, outliers identification, confidence interval, determination of the uncertainties, recovery, robustness of analytical procedure.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.