14D021 - Chemometrics

Course specification
Course titleChemometrics
Study programme
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ConditionОблик условљености
      The goalThe main objective of the course is that students complete and extend their theoretical and practical knowledge in the application of statistical methods and computer software in data analysis of chemical measurement. This includes experimental design, exploratory data analysis and modeling of parameters in order to optimize chemical processes.
      The outcomeUpon completion of the course the student should be able to: select and apply selected chemometric methods in data analysis in various areas of fundamental research, as well as in the engineering practise, especially in the area of quality control; understand the importance of optimization and experimental design; choose and apply the optimal method of multivariate analysis in classification and data modeling; use standard computer programs for statistical analysis of data; schedule of data reduction, selection of representative variables that are responsible for the variation in the data set, to classify and group data, in order to optimize system control and monitoring of chemical processes by reducing the number of measured parameters and frequency of measurements.
      Contents of lecturesIntroduction to chemometrics, concept and application. ; Methods for statistical data processing (preparation of data set, normality test of distribution, elimination of the outliers, preliminary statistical analysis, statistical tests, selection of appropriate chemometrics technique, interpretation of the results of statistical analysis, modeling of parameters, the evaluation of the experimental process) . ; Errors in quantitative chemical analysis. The application of statistics to the results of repeated measurements (measures of central tendency and measures of dispersion, the distribution of the results of repeated measurements, the confidence level, estimation of the result errors obtained by calculating). ; Statistical tests (one-way and two-way tests, parametric and non-parametric tests, and one-factor analysis of variance ANOVA). ; Methods of calibration, correlation and regression. ; Optimization and experimental design (randomization, types of experimental design, optimization methods). ; Methods of multivariate analysis (parametric and nonparametric), principles, advantages and disadvantages, the selection and application: The principal component analysis (PCA), Factor analysis (FA) Cluster analysis, hierarchical and nonhierarchical (CA, HCA), Discriminant analysis, linear and canonical (LDA, CDA) Artificial Neural Network (ANN), Soft independent modeling by class analogy (SIMCA). Multiple linear regression. ; Validation and quality control. ; Examples on computer (use the software for statistical analysis of measurement results: Excel, SPSS, Minitab). ;
      Contents of exercises
      1. J.N.Miller, J.C.Miller, Statistics and Chemometrics for Analytical Chemistry, Pearson Ed., Harlow, 2010.
      2. P. Gemperline, Practical guide to chemometrics, CRC, Press Taylor & Francis Group, London, 2006.
      3. О. Matthias, Chemometrics: Statistics and Computer Application in Analytical Chemistry, Wiley-VCH, 1999.
      4. C.R. Alvin, Methods of Multivariate Analysis, Wiley, New York (2002)
      5. R.G. Brereton, Chemometrics: Data Analysis for the Laboratory and Chemical Plant, Wiley, New York, 2003
      Number of hours per week during the semester/trimester/year
      LecturesExercisesOTCStudy and ResearchOther classes
      Methods of teachingLectures (PPT), seminars, tests, examples using Excel, SPSS, Minitab
      Knowledge score (maximum points 100)
      Pre obligationsPointsFinal examPoints
      Activites during lectures10Test paper50
      Practical lessonsOral examination