Abstract

This is the first book for atomic spectroscopists to present the basic principles of experimental designs, optimization and multivariate regression. Multivariate regression is a valuable statistical method for handling complex problems (such as spectral and chemical interferences) which arise during atomic spectrometry. However, the technique is underused as most spectroscopists do not have time to study the often complex literature on the subject. This practical introduction uses conceptual explanations and worked examples to give readers a clear understanding of the technique. Mathematics is kept to a minimum but, when required, is kept at a basic level. Practical considerations, interpretations and troubleshooting are emphasized and literature surveys are included to guide the reader to further work. The same dataset is used for all chapters dealing with calibration to demonstrate the differences between the different methodologies. Readers will learn how to handle spectral and chemical interferences in atomic spectrometry in a new, more efficient and cost-effective way.
"The application of statistical and chemometric tools for planning, executing and interpreting analytical measurements is a common thread in the current practice of analytical chemistry. This book fits nicely into the contemporary picture, addressing some of the training needs of analytical chemists in a subject area that is still neglected in academic courses."

"The chapters are uniformly good, and although written by multiple authors, are coherent, focused and remain on message with limited overlap. "

"The level of presentation is suitable for first year graduate students and professionals in industry with a strong scientific background"

"In conclusion, this is a well-organized and concise text, which I can recommend to those wishing to explore data analysis techniques, especially for calibration, to gain insights into correct procedures and to avoid common mistakes. The text is very readable and will reward those of all abilities who delve into its contents."

Colin F. Poole
Jose Andrade-Garda is based in the Department of Analytical Chemistry at the University of A Coru±a where he specializes in quality control and chemometrics. Within the field of chemometrics, his main interests are multivariate regression and pattern recognition methods. In the atomic spectrometry arena, he has applied formal optimization techniques to optimize analytical protocols and used multivariate regression tools to cope with spectral and chemical interferences in ETAAS.