PdF:CH2BP_6W4S Fundamentals of Chemometrics - Course Information
CH2BP_6W4S Fundamentals of Chemometrics
Faculty of EducationSpring 2015
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: z (credit).
- Teacher(s)
- doc. RNDr. Luděk Jančář, CSc. (seminar tutor)
- Guaranteed by
- doc. RNDr. Petr Sládek, CSc.
Department of Physics, Chemistry and Vocational Education – Faculty of Education
Contact Person: Mgr. Bc. Lucie Viková
Supplier department: Department of Physics, Chemistry and Vocational Education – Faculty of Education - Prerequisites
- Knowledge of mathematics and analytical chemistry of university degree.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Lower Secondary School Teacher Training in Chemistry (programme PdF, B-SPE)
- Course objectives
- Main objectives can be summarised as follows:
to introduce into foundations of chemometric methods of analyse and evaluation of chemical data. - Syllabus
- 1. Chemometrics and its parts.
- 1.1. Definition and significance of chemometrics, types of chemometric methods.
- 1.2. Application of chemometrics in chemical branches.
- 1.3. Errors of measurements and statistical evaluation of data and measurements results.
- 2. Classical multivariate calibration methods.
- 2.1. Linear and polynomic regression.
- 2.2. Determined and overdetermined systems.
- 2.3. Finite and iterative methods.
- 2.4. Modifications of methods in case of nonlinearities.
- 2.5. The use of classical multivariate methods in chemistry.
- 3. Statistical designs and their use in analysis.
- 3.1. Complete and fractional factorial design, central composite design.
- 3.2. Box-Hunter aan Box-Behnken plans.
- 4. Modern methods of multivariate calibration.
- 4.1. Multiple linear regression (MLR).
- 4.2. Principal component regression (PCR).
- 4.3. Partial Least Squares (PLS).
- 4.4. Nonlinear regression (NR).
- 4.5. Kalman filter (KF).
- 4.6. Application of modern methods of multivariate calibration in chemistry.
- 5. Classification methods.
- 5.1. Types and basic principles of classification methods.
- 6. Factor analysis.
- 6.1. Principal component analyse (PCA).
- 6.2. General method of the factor analysis (FA).
- 6.3. Applications of factor analysis in chemistry.
- 7. Pattern recognition methods (Pattern recognition - PR).
- 7.1. Supervised and unsupervised learning.
- 7.2. Classify.
- 7.3. SIMCA.
- 7.4. The use of pattern recognition methods in chemistry.
- 8. Cluster analysis (Cluster analysis - CA).
- 8.1. Hierarchic and nonhierarchic cluster methods.
- 8.2. Aglomerative and divisive clusterring.
- 8.3. Metrics and dendrograms.
- 8.4. The use of cluster analysis methods in chemistry.
- 9. Neural networks and their use in chemistry.
- 10. Simplex method, Monte-Carlo method and their use in chemistry.
- Literature
- Teaching methods
- seminar, theoretical preparation, class discussion
- Assessment methods
- credit;
written test - performance 60 % - Language of instruction
- Czech
- Further Comments
- The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (Spring 2015, recent)
- Permalink: https://is.muni.cz/course/ped/spring2015/CH2BP_6W4S