Technical focus

 

• Analytical Quality Assurance
• Descriptive and inferential statistics
• data management
• Expert systems, LIMS
• calibration and optimization
• Univariate data analysis
• Multivariate data analysis (pattern recognition, multi-component analysis)
• Neural networks and genetic algorithms
• sampling
• QSAR
• signal handling
• Spectra Interpretation
• Statistical Design of Experiments
• Time series analysis and process control
• big data
• Documentation and data archiving

The GDCh, the Euro- chemometrics CS network and the knowledge transfer of the University of Tübingen (WIT), the House of Technology in Essen and other organizers (especially Friedrich Schiller University Jena, Bergakademie TU Freiberg) continue to address these questions - and further education courses or lectures are offered.

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