SubjectsSubjects(version: 941)
Course, academic year 2023/2024
Multivariate Statistical Methods - M402016
Title: Vícerozměrné statistické metody
Guaranteed by: Department of Analytical Chemistry (402)
Faculty: Faculty of Chemical Engineering
Actual: from 2019
Semester: summer
Points: summer s.:5
E-Credits: summer s.:5
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unknown / unknown (unknown)Schedule is not published yet, this information might be misleading.
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
For type:  
Additional information: http://Ing. Člupek, Ph.D.
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Matějka Pavel prof. Dr. RNDr.
Člupek Martin Ing. Ph.D.
Interchangeability : N402039
Examination dates   Schedule   
Annotation -
Last update: Pátková Vlasta (05.01.2018)
This course represent a continuation to the course Chemometrics in Analytical Chemistry. Various multivariate chemometric methods are introduced showing the differences among exploratory, classification and regression algorithms. The practical applications are emphasised solving specific analytical issues. The preprocessing data treatment is introduced demonstrating the importance of proper combination of individual steps for the achievement of reliable results.
Aim of the course -
Last update: Pátková Vlasta (05.01.2018)

Students will be able to:

Describe fundamental concepts of multivariate statistics.

Prepare experimental multidimensional data for their statistical processing and evaluation.

Explain the principles of multivariate chemometric methods, including exploratory, classification and regression approaches and to use them for specific analytical and spectroscopic measurements.

Literature -
Last update: Pátková Vlasta (05.01.2018)

A:Meloun M., Militký J., Hill M: Počítačová analýza vícerozměrných dat v příkladech, Academia Praha 2005, ISBN 80-200-1335-0

Learning resources -
Last update: Pátková Vlasta (05.01.2018)

electronic materials - available in the domain

Syllabus -
Last update: Pátková Vlasta (05.01.2018)

1. Data vector, data matrix and fundamental operation

2. Multivariate statistical distributions, probability distributions

3. Data corrections - methods of noise suppression, baseline corrections, multiplicative scatter correction

4. Data matrix processing and data treatment

5. Estimations and hypothesis testing

6. Multivariate analýza rozptylu

7. Exploratory data analysis

8. Principal component analysis

9. Discrimination analysis

10. Cluster analysis

11. Fuzzy cluster analysis

12. Partial least squares approach

13. Canonic correlation

14. Multivariate regression methods

Registration requirements -
Last update: Pátková Vlasta (05.01.2018)


Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 0.5 14
Obhajoba individuálního projektu 0.5 14
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 0.5 14
Práce na individuálním projektu 0.5 14
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 1 28
5 / 5 140 / 140