Chemometrics
eBook - ePub

Chemometrics

Statistics and Computer Application in Analytical Chemistry

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Chemometrics

Statistics and Computer Application in Analytical Chemistry

About this book

The third edition of this long-selling introductory textbook and ready reference covers all pertinent topics, from basic statistics via modeling and databases right up to the latest regulatory issues.
The experienced and internationally recognized author, Matthias Otto, introduces the statistical-mathematical evaluation of chemical measurements, especially analytical ones, going on to provide a modern approach to signal processing, designing and optimizing experiments, pattern recognition and classification, as well as modeling simple and nonlinear relationships. Analytical databases are equally covered as are applications of multiway analysis, artificial intelligence, fuzzy theory, neural networks, and genetic algorithms. The new edition has 10% new content to cover such recent developments as orthogonal signal correction and new data exchange formats, tree based classification and regression, independent component analysis, ensemble methods and neuro-fuzzy systems. It still retains, however, the proven features from previous editions: worked examples, questions and problems, additional information and brief explanations in the margin.

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Yes, you can access Chemometrics by Matthias Otto in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Analytic Chemistry. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley-VCH
Year
2016
Print ISBN
9783527340972
eBook ISBN
9783527699384

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Table of Contents
  5. List of Abbreviations
  6. Symbols
  7. Chapter 1: What is Chemometrics?
  8. Chapter 2: Basic Statistics
  9. Chapter 3: Signal Processing and Time Series Analysis
  10. Chapter 4: Optimization and Experimental Design
  11. Chapter 5: Pattern Recognition and Classification
  12. Chapter 6: Modeling
  13. Chapter 7: Analytical Databases
  14. Chapter 8: Knowledge Processing and Soft Computing
  15. Chapter 9: Quality Assurance and Good Laboratory Practice
  16. Appendix
  17. Index
  18. End User License Agreement