Chemical Education Today
Book & Media Reviews Applied Chemometrics for Scientists by Richard G. Brereton John Wiley & Sons, Ltd., Chichester, West Sussex, UK, 2007. 396 pp, ISBN: 978-0470016862. $110. reviewed by Frank Vogt
Chemometrics is the subdivision of analytical chemistry that uses computational methods for qualitative or quantitative analysis of typically multivariate measurement data. Chemometric computation methods have been designed for sensor calibration and for evaluation of unknowns. Another wide area of chemometrics is experimental design and statistical process control in industry. Because of a continuously increasing numbers of applications, more and more scientists need to understand chemometrics, thus there is a need for textbooks at levels ranging from those providing an overview to those with expert-level discussions of chemometric algorithms. Since there are so many different methodologies available, a textbook such as Applied Chemometrics for Scientists has to cover a large number of different approaches. This book gives an overview of numerous chemometric topics and is based on examples and graphical explanation rather than introducing mathematical details of chemometric algorithms. Readers are presented with the fundamental ideas of numerous chemometric methods so that they can select and assess an approach. In the preface the author explains that the book is based on a series of short, introductory articles. Many chapters are just long enough to present the basic concepts but do not provide insights into details of algorithms. For example, multi-way methods (1, 2) are covered in chapter 5.11 in only three pages. A novice will find enough information to get started, but studying more literature will be required to gain a workable knowledge. Unfortunately, the list of references throughout the book is very short and somewhat outdated. The book can be grouped into four areas, each of which consists of several chapters. Introductory topics: These chapters cover the history of chemometrics, the basics of statistical data analysis, and signal analysis. Although the presentation of statistical techniques is very basic and could have been handled by pointing to standard references, it is certainly nice to have all these tools available in one book. The focus here is on univariate data whereas chemometrics, in my opinion, is inherently multivariate. Multivariate least-squares regression (3) is introduced in a later chapter, though. Experimental design: The discussion of experimental design is much longer than other chapters and provides sufficient
information to get started applying methods of experimental design. This part of the book is quite comprehensive and is a good starting point for this topic. Pattern recognition and calibration procedures: The presentation of pattern recognition is unique as it uses almost no equations and discusses the material based on graphs and cartoons. This approach certainly communicates the ideas of the different pattern recognition methods quickly. However, this means that the reader has to use commercial software packages as black boxes when applying these techniques. The chapter on calibration starts with the introduction of leastsquares regression. At this point, I would have preferred to see a more extensive discussion on multivariate least squares regression, or at least some references, because many chemometric methods are based on this technique. Applications: This is certainly the strongest and longest part of the book. A great many applications are discussed together with experimental aspects. This section will be useful to scientists who need to decide whether chemometrics is a valuable approach. Examples from process analytics, biology, medical diagnostics, and quality monitoring of food are presented. In these chapters, the discussion refers to the more computational chapters where chemometric concepts are introduced and outlines how those methods are applied.
The descriptive approach, supported by many examples, makes selected chapters useful for introducing chemometrics in undergraduate classes. This book conveys basic ideas of data analysis smoothly and presents the material in a very descriptive way. This helps to prepare undergraduates for industrial jobs or graduate school where they have to apply chemometrics. Teaching a graduate course in chemometrics, however, would require more mathematical and computational details than presented in this textbook. This book also serves as a valuable encyclopedia for researchers who want to get started in chemometrics. Finally, advanced chemometricians who come across a new technique will be able to quickly get some background information. Literature Cited 1. Bro, R. PARAFAC. Tutorial and Applications. Chemom. Intell. Lab. Syst. 1997, 38, 149–171. 2. Faber, N.; Bro, R.; Hopke, P. Recent Developments in CANDECOMP/PARAFAC Algorithms: A Critical Review. Chemom99. Intell. Lab. Syst. 2003, 65, 119–137. 3. Draper, N.; Smith, H. Applied Regression Analysis, 3rd ed.; John Wiley & Sons: New York, 1998.
Frank Vogt is a member of the Department of Chemistry, University of Tennessee, Knoxville, TN 37996-1600; fvogt@ utk.edu.
1926 Journal of Chemical Education • Vol. 84 No. 12 December 2007 • www.JCE.DivCHED.org
