SubjectsSubjects(version: 963)
Course, academic year 2021/2022
  
Chemometrics in Analytical Chemistry - AM402018
Title: Chemometrics in Analytical Chemistry
Guaranteed by: Department of Analytical Chemistry (402)
Faculty: Faculty of Chemical Engineering
Actual: from 2019
Semester: winter
Points: winter s.:4
E-Credits: winter s.:4
Examination process: winter s.:
Hours per week, examination: winter s.:2/1, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: English
Teaching methods: full-time
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Setnička Vladimír prof. Ing. Ph.D.
Kania Patrik Ing. Ph.D.
Classification: Chemistry > Analytical Chemistry
Interchangeability : M402018, N402042
Is interchangeable with: M402018
Examination dates   Schedule   
Annotation -
The subject is focused on understanding basic statistical methods and their applications, especially in analytical chemistry and clinical biochemistry.
Last update: Kania Patrik (23.08.2024)
Aim of the course -

Students will be able to:

• apply basic statistical methods for evaluating measurements in chemistry

• optimize measurements

• perform analytical method calibration

• use contingency tables

Last update: Kania Patrik (23.08.2024)
Course completion requirements -

Getting a credit from credit tests (or for the work out of a project) and successful completion of a written exam test (details during lectures).

Last update: Kania Patrik (23.08.2024)
Literature -

R: D.L.Massart et all: Handbook of Chemometrics and Qualimetrics, Part A, Elsevier 1997, ISBN 0-444-89724-0

Last update: Kania Patrik (23.08.2024)
Syllabus -

1. Basic terms from probability theory

2. Important probability distributions

3. Numerical characteristics of distribution

4. Basic processing and exploratory data analysis

5. Random sample and its characteristics

6. Hypothesis testing

7. Parametric statistical tests

8. Non-parametric statistical tests

9. One-factor analysis of variance

10. Multi-factor analysis of variance and factorial experiments

11. Optimization methods

12. Contingency tables

13. Correlation and regression analysis, calibration of the analytical method

14. Measurement uncertainties

Last update: Kania Patrik (23.08.2024)
Learning resources -

Study materials will be sent to students by e-mail.

Last update: Kania Patrik (23.08.2024)
Registration requirements -

Mathematics A

Last update: Kania Patrik (02.09.2024)
 
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