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Chemometrics, Vol 2. Data Handling in Science and Technology

  • ID: 1758187
  • Book
  • 500 Pages
  • Elsevier Science and Technology
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Most chemists, whether they are biochemists, organic, analytical, pharmaceutical or clinical chemists and many pharmacists and biologists need to perform chemical analysis. Consequently, they are not only confronted with carrying out the actual analysis, but also with problems such as method selection, experimental design, optimization, calibration, data acquisition and handling, and statistics in order to obtain maximum relevant chemical information. In other words: they are confronted with chemometrics. This book on chemometrics, written by some of the leaders in the field, aims to provide a thorough, up-to-date introduction to this subject. The reader is given the opportunity to acquaint himself with the tools used in this discipline and the way in which they are applied. Some practical examples are given and the reader is shown how to select the appropriate tools in a given situation.

As such the book provides the means to approach and solve analytical problems strategically and systematically, without the need for the reader to become a fully-fledged chemometrician. The authors' aim was to write a tutorial book which would be useful to readers at every level in this field.

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1. Chemometrics and the Analytical Process. 2. Precision and Accuracy. 3. Evaluation of Precision and Accuracy. Comparison of Two Procedures. 4. Evaluation of Sources of Variation in Data. Analysis of Variance. 5. Calibration. 6. Reliability and Drift. 7. Sensitivity and Limit of Detection. 8. Selectivity and Specificity. 9. Information. 10. Costs. 11. The Time Constant. 12. Signals and Data. 13. Regression Methods. 14. Correlation Methods. 15. Signal Processing. 16. Response Surfaces and Models. 17. Exploration of Response Surfaces. 18. Optimization of Analytical Chemical Methods. 19. Optimization of Chromatographic Methods. 20. The Multivariate Approach. 21. Principal Components and Factor Analysis. 22. Clustering Techniques. 23. Supervised Pattern Recognition. 24. Decisions in the Analytical Laboratory. 25. Operations Research. 26. Decision Making. 27. Process Control. Appendix. Subject Index.
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Deming, S.N.
Michotte, Y.
Massart, D.L.
Kaufman, L.
Vandeginste, B.G.M.
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