AK chemometrics & Quality Assurance

Working Group Chemometrics & Quality Assurance

Tasks & goal setting

The working group was formed in 1994 from the "chemometrics" and "Laboratory Data Processing" groups. According to the focus of these two groups, the working group of the GDCh Division of Analytical Chemistry group intends to combine the acquisition of data in the laboratory with their statistical evaluation, plausibility control and corresponding quality assurance as good analytical practice. For this reason, analysts in particular should feel addressed who use computers to gain data in the laboratory in stationary analysis and dynamic processes and also process them with computers. For this reason, the working group is interested in laboratory information and management systems, computer-controlled spectrometers and general analysis devices as well as the various model-free and model-based multivariate methods of data analysis.

The working group therefore sees it as its task to be present at various Conferences or to organize them in a leading role. The main conferences are COMPANA and the discussion conference on the use of computers in spectroscopy in Gemen. In addition, the working group participates in the analytica conference with great success. Last but not least, aspects of the working group are regularly reflected in lectures at ANAKON.

Technical focus

     

  • Analytical quality assurance
  • Descriptive and Inclusive Statistics
  • Data management
  • Expert systems, LIMS
  • Geostatistics
  • Calibration and optimization
  • Multivariate data analysis (pattern recognition, multi-component analysis)
  • Neural networks and genetic algorithms
  • Sampling
  • QSAR
  • Signal handling
  • Spectrum Interpretation
  • Statistical design of experiments
  • Time series analysis and process control

The GDCh, the Euro- chemometrics CS-Verbund and the Knowledge Transfer of the University of Tübingen (WIT), in the Haus der Technik in Essen and at other organizers (especially Friedrich Schiller University Jena, Bergakademie TU Freiberg) will answer these questions - and advanced training courses or courses are offered.

Board 2020-2023

Dr. Claudia Beleites (Chair)
Chemometrix GmbH

Dr. Andrea Paul (Deputy Chair)
Federal Institute for Materials Research and Testing (BAM), Berlin

Dr. Jörg Kraft (Secretary)
SYNLAB Umweltinstitut LAG GmbH

Prof. Dr. Gerald Steiner (Assessor)
TU Dresden

Recommended reading for self-study on multivariate data analysis

(with a subjective assessment of the content by W. Kessler)

K. Backhaus, B. Erichson et al .: Multivariate Analysis Methods - An Application-Oriented Introduction
(Quite clear but geared towards economics, originally from 1987, but re-released in 2008, still without PLS, but cluster analysis, discriminant analysis and neural networks are included)

K. Beebe, R. Pell, M. Seasholtz: Chemometrics - A Practical Guide
(very clear, without a lot of math, with many examples)

R. Brereton: Chemometrics, Data Analysis for the Laboratory and Chemical Plant
(in detail, well explained, complete mathematics, examples mainly from chemistry)

K. Danzer, H. Hobert et al .: chemometrics- Basics and Applications
(Comprehensive overview also univariate. Statistics, but only briefly explained, mathematically)

Foo-tim Chau, Yi-zeng Liang et al: Chemometrics - From Basics to Wavelet Transform
(Good overview of the various preprocessing algorithms)

B. Flury, H. Riedwyl: Applied multivariate statistics
(quite clear, but dates from 1983)

R. Henrion, G. Henrion: Multivariate data analysis
(important algorithms are explained, but quite a bit of math)

H. Hobert: Computer-aided evaluation of physicochemical measurements
(quite a bit of math)

IT Jolliffe: Principal Component Analysis
(very detailed, but very, very mathematical)

W. Kessler: Multivariate data analysis for pharmaceutical, bio and process analytics
(intended as a textbook, goes into detail on the most important procedures, includes CD with software for multivariate data analysis with exercise examples)

E. Malinowski: Factor Analysis in Chemistry
(very detailed, mathematically complete, especially for chemists, 3rd edition 2002)

H. Martens, T. Naes: Multivariate Calibration
(very detailed with complete mathematics, nevertheless understandable)

H. Martens, M. Martens: Multivariate Analysis of Quality - An Introduction
(very detailed as above, with the aim of improving quality)

M. Otto: chemometrics
(well suited as an overview, the individual procedures are very brief)

B. Vandeginste, D. Massart et al .: Handbook of Chemometrics and Qualimetrics: Part A and B
(the bible of chemometrists, very expensive, detailed, understandable, very good)

Brown et al., Comprehensive Chemometrics, Elsevier
A description of the book can be found under the following link: https://www.elsevier.com/books/comprehensive-chemometrics/brown/978-0-444-52701-1

Data mining ...

... with multi-variable methods and support vector machines

Video tutorials

Contact

GDCh Office
Dr. Carina S. Kniep
Tel .: +49 69 7917-499

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last modified: 13.09.2021 17:50 H from C.Kniep