CH2BP_6W4S Fundamentals of Chemometrics

Faculty of Education
Spring 2018
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: Jana Jachymiáková
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
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
  • ECKSCHLAGER, Karel. Chemometrie. 1. vyd. Praha: Universita Karlova, 1991, 156 s. ISBN 80-7066-487-8. info
  • ECKSCHLAGER, Karel. Chemometrie a chemická metrologie. 1. vyd. Brno: Universita Jana Evangelisty Purkyně, 1986, 226 s. info
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.
The course is also listed under the following terms Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017.
  • Enrolment Statistics (recent)
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