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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.
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