Pattern recognition and other chemometrical techniques are important tools in interpreting environmental data. This volume presents authoritatively state-of-the-art procedures for measuring and handling environmental data. The chapters are written by leading experts.

The book introduces most of the basic tools of chemometrics including experimental design, signal analysis, statistical methods for analytical chemistry and multivariate methods. It then discusses a number of important applications including food chemistry, biological pattern recognition, reaction monitoring, optimisation of processes, medical applications.

The book arises from a series of short articles that have been developed over four years on Chemweb (www.chemweb.com).

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, www.booksupport.wiley.com 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.

The journal Chemometrics and Intelligent Laboratory Systems has a specific policy of publishing tutorial papers, (i.e. articles aiming to discuss and illustrate the application of chemometric and other techniques) solicited from leading experts in the varied disciplines relating to this subject. This book comprises reprints of tutorials from the first 5 volumes of this journal, covering the period from late 1986 to mid 1989. The authors of the papers include analytical, organic and environmental chemists, statisticians, pharmacologists, geologists, geochemists, computer scientists and biologists, which reflects the strong interdisciplinary communication. The papers have been reorganized into major themes, covering most of the main areas of chemometrics.
This book is intended both as a personal reference text and as a useful background for courses in chemometrics and laboratory computing.