SubjectsSubjects(version: 855)
Course, academic year 2019/2020
  
Multivariate Statistical Methods - N402039
Title: Vícerozměrné statistické metody
Guaranteed by: Department of Analytical Chemistry (402)
Actual: from 2013
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 [hours/week]
Capacity: 41 / 41 (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
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.
Is interchangeable with: M402016
Examination dates   Schedule   
Annotation -
Last update: VED402 (16.12.2013)
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: VED402 (16.12.2013)

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: VED402 (01.10.2013)

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: Matějka Pavel prof. Dr. RNDr. (31.08.2013)

electronic materials - available in the domain vscht.cz

Syllabus -
Last update: Matějka Pavel prof. Dr. RNDr. (30.08.2013)

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: Matějka Pavel prof. Dr. RNDr. (31.08.2013)

none

Teaching methods
Activity Credits Hours
Konzultace s vyučujícími 0,7 20
Obhajoba individuálního projektu 0,5 14
Účast na přednáškách 1 28
Práce na individuálním projektu 0,5 14
Příprava na zkoušku a její absolvování 1,3 36
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Regular attendance 5
Defense of an individual project 15
Examination test 40
Continuous assessment of study performance and course -credit tests 20
Oral examination 20

 
VŠCHT Praha