The limited coverage of data analysis and statistics offered in
most undergraduate and graduate analytical chemistry courses is
usually focused on practical aspects of univariate methods. Drawing
in real-world examples, Practical Guide to Chemometrics, Second
Edition offers an accessible introduction to application-oriented
multivariate methods of data analysis and procedures that are
highly beneficial to solving a variety of problems using analytical
chemistry and statistics.
Rather than overshadowing the concepts with theoretical
background, this book uses application-oriented examples to
illustrate how chemometrics techniques can be applied to complex
scenarios with multiple and dynamic variables. The book presents a
diverse selection of topics that include sampling, modeling,
experimental design, calibration, pattern recognition, data
analysis techniques, algorithms, and error. This second edition has
been completely revised to feature new chapters on principal
component analysis, self-modeling curve resolution, and multi-way
analysis methods. It includes expanded material on normal
distributions, sampling theory, signal processing, and digital
filtering.
Embracing the growing role of chemometrics in some of the latest
research trends, such as quantitative biology, bioinformatics, and
proteomics, this book also identifies several areas for future
development and applications. Practical Guide to Chemometrics,
Second Edition continues to offer a reliable source of useful
information in a style that is accessible to all levels of
students, professionals, and researchers involved in analyzing
scientific data.
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