Chemometrics: a textbook.

*(English)*Zbl 0636.62112
Data Handling in Science and Technology, Vol. 2. Amsterdam etc.: Elsevier. XI, 488 p.; $ 85.25; Dfl. 175.00 (1988).

Chemometrics tries, just as all analytical chemists do, to design optimal analytical procedures and to obtain as much information as possible from the results. These goals can be attained by mathematical modelling methods. The aim of this book is to give the formal background of the algorithms and the mathematical techniques used. The next steps towards realizing the intelligent laboratory will be made by robotics and expert systems, these problems being, as the authors remark, beyond the scope of a textbook on chemometrics today.

Now, some words about the contents of the book. Chapters 1-11 introduce basic statistical concepts and techniques. Chapters 12-15 continue with mathematically related methods concerned with regression, correlation and autocorrelation, and transformations. These techniques give the necessary background for data acquisition, such as signal processing and time- dependent processes, by time series methodology.

Chapters 16-19 study experimental optimization methods: response surfaces, variance and regression, simplex method, all applied for optimization purposes. Chapters 20-23 are concerned with multivariate data analysis, particularly pattern recognition methods. Chapters 24-27 are dealing with formal techniques developed outside analytical chemistry to help taking the decisions on process control. A final remark: the possibility to order specialized software, specific to a really efficient laboratory.

Now, some words about the contents of the book. Chapters 1-11 introduce basic statistical concepts and techniques. Chapters 12-15 continue with mathematically related methods concerned with regression, correlation and autocorrelation, and transformations. These techniques give the necessary background for data acquisition, such as signal processing and time- dependent processes, by time series methodology.

Chapters 16-19 study experimental optimization methods: response surfaces, variance and regression, simplex method, all applied for optimization purposes. Chapters 20-23 are concerned with multivariate data analysis, particularly pattern recognition methods. Chapters 24-27 are dealing with formal techniques developed outside analytical chemistry to help taking the decisions on process control. A final remark: the possibility to order specialized software, specific to a really efficient laboratory.

Reviewer: S.Curteanu

##### MSC:

62P99 | Applications of statistics |

62-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics |

92Exx | Chemistry |

65C99 | Probabilistic methods, stochastic differential equations |