Chemometrics

Data Driven Extraction for Science

Nonfiction, Science & Nature, Science, Chemistry, Analytic
Cover of the book Chemometrics by Richard G. Brereton, Wiley
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Author: Richard G. Brereton ISBN: 9781118904688
Publisher: Wiley Publication: March 13, 2018
Imprint: Wiley Language: English
Author: Richard G. Brereton
ISBN: 9781118904688
Publisher: Wiley
Publication: March 13, 2018
Imprint: Wiley
Language: English

A new, full-color, completely updated edition of the key practical guide to chemometrics

This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical and graphical examples, which can then be applied to a wide variety of problems in chemistry, biology, chemical engineering, and allied disciplines. Presented in full color, it features expansion of the principal component analysis, classification, multivariate evolutionary signal and statistical distributions sections, and new case studies in metabolomics, as well as extensive updates throughout. Aimed at the large number of users of chemometrics, it includes extensive worked problems and chapters explaining how to analyze datasets, in addition to updated descriptions of how to apply Excel and Matlab for chemometrics.

Chemometrics: Data Driven Extraction for Science, Second Edition offers chapters covering: experimental design, signal processing, pattern recognition, calibration, and evolutionary data. The pattern recognition chapter from the first edition is divided into two separate ones: Principal Component Analysis/Cluster Analysis, and Classification. It also includes new descriptions of Alternating Least Squares (ALS) and Iterative Target Transformation Factor Analysis (ITTFA). Updated descriptions of wavelets and Bayesian methods are included.

  • Includes updated chapters of the classic chemometric methods (e.g. experimental design, signal processing, etc.)
  • Introduces metabolomics-type examples alongside those from analytical chemistry
  • Features problems at the end of each chapter to illustrate the broad applicability of the methods in different fields
  • Supplemented with data sets and solutions to the problems on a dedicated website

Chemometrics: Data Driven Extraction for Science, Second Edition is recommended for post-graduate students of chemometrics as well as applied scientists (e.g. chemists, biochemists, engineers, statisticians) working in all areas of data analysis.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

A new, full-color, completely updated edition of the key practical guide to chemometrics

This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical and graphical examples, which can then be applied to a wide variety of problems in chemistry, biology, chemical engineering, and allied disciplines. Presented in full color, it features expansion of the principal component analysis, classification, multivariate evolutionary signal and statistical distributions sections, and new case studies in metabolomics, as well as extensive updates throughout. Aimed at the large number of users of chemometrics, it includes extensive worked problems and chapters explaining how to analyze datasets, in addition to updated descriptions of how to apply Excel and Matlab for chemometrics.

Chemometrics: Data Driven Extraction for Science, Second Edition offers chapters covering: experimental design, signal processing, pattern recognition, calibration, and evolutionary data. The pattern recognition chapter from the first edition is divided into two separate ones: Principal Component Analysis/Cluster Analysis, and Classification. It also includes new descriptions of Alternating Least Squares (ALS) and Iterative Target Transformation Factor Analysis (ITTFA). Updated descriptions of wavelets and Bayesian methods are included.

Chemometrics: Data Driven Extraction for Science, Second Edition is recommended for post-graduate students of chemometrics as well as applied scientists (e.g. chemists, biochemists, engineers, statisticians) working in all areas of data analysis.

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