Applied Chemometrics for Scientists

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Edition: 1st
Format: Hardcover
Pub. Date: 2007-04-02
Publisher(s): WILEY
List Price: $142.02

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Summary

The book introduces most of the basic tools of chemometrics including experimental design, signal analysis, statistical methods for analytical chemistry and multivariate methods. It then discusses a number of important applications including food chemistry, biological pattern recognition, reaction monitoring, optimisation of processes, medical applications. The book arises from a series of short articles that have been developed over four years on Chemweb (www.chemweb.com).

Author Biography

Richard G. Brereton, 1979-1983 : University of Cambridge, 1983 - : University of Bristol,  current position Professor and Director of the Centre of Chemometrics, B.A., (Hons) 1976 (Natural Sciences, speciality chemistry; University of Cambridge), M.A., 1980 (University of Cambridge), Ph.D., 1981 (Thesis : Spectroscopic Studies of Bacteriochlorophyll a; supervisor : Prof. J.K.M.Sanders, FRS, Chemical Laboratory, University of Cambridge), MRSC, C.Chem., 1991 (Royal Society of Chemistry)

Over 1250 citations in the literature, 60+ invited lectures, 30+ seminars given, 2 authored books, contributed to 9 edited works and has co-edited 3 books. Served as Associate Editor Chemometrics and Intelligent Laboratory Systems (Elsevier) for 5 years.

Taught in undergraduate and graduate courses for over 20 years, written extensively in the application of Chemometrics.

Table of Contents

Preface
Introduction
Development of Chemometrics
Application Areas
How to Use this Book
Literature and Other Sources of Information
References
Experimental Design
Why Design Experiments in Chemistry?
Degrees of Freedom and Sources of Error
Analysis of Variance and Interpretation of Errors
Matrices, Vectors and the Pseudoinverse
Design Matrices
Factorial Designs
An Example of a Factorial Design
Fractional Factorial Designs
Plackett-Burman and Taguchi Designs
The Application of a Plackett-Burman Design to the Screening of Factors Influencing a Chemical Reaction
Central Composite Designs
Mixture Designs
A Four Component Mixture Design Used to Study Blending of Olive Oils
Simplex Optimization
Leverage and Confidence in Models
Designs for Multivariate Calibration
References
Statistical Concepts
Statistics for Chemists
Errors
Describing Data
The Normal Distribution
Is a Distribution Normal?
Hypothesis Tests
Comparison of Means: the t-Test
F-Test for Comparison of Variances
Confidence in Linear Regression
More about Confidence
Consequences of Outliers and How to Deal with Them
Detection of Outliers
Shewhart Charts
More about Control Charts
References
Sequential Methods
Sequential Data
Correlograms
Linear Smoothing Functions and Filters
Fourier Transforms
Maximum Entropy and Bayesian Methods
Fourier Filters
Peakshapes in Chromatography and Spectroscopy
Derivatives in Spectroscopy and Chromatography
Wavelets
References
Pattern Recognition
Introduction
Principal Components Analysis
Graphical Representation of Scores and Loadings
Comparing Multivariate Patterns
Preprocessing
Unsupervised Pattern Recognition: Cluster Analysis
Supervised Pattern Recognition
Statistical Classification Techniques
K Nearest Neighbour Method
How Many Components Characterize a Dataset?
Multiway Pattern Recognition
References
Calibration
Introduction
Univariate Calibration
Multivariate Calibration and the Spectroscopy of Mixtures
Multiple Linear Regression
Principal Components Regression
Partial Least Squares
How Good is the Calibration and What is the Most Appropriate Model?
Multiway Calibration
References
Coupled Chromatography
Introduction
Preparing the Data
Chemical Composition of Sequential Data
Univariate Purity Curves
Similarity Based Methods
Evolving and Window Factor Analysis
Derivative Based Methods
Deconvolution of Evolutionary Signals
Noniterative Methods for Resolution
Iterative Methods for Resolution
Equilibria, Reactions and Process Analytics
The Study of Equilibria using Spectroscopy
Spectroscopic Monitoring of Reactions
Kinetics and Multivariate Models for the Quantitative Study of Reactions
Developments in the Analysis of Reactions using On-line Spectroscopy
The Process Analytical Technology Initiative
References
Table of Contents provided by Publisher. All Rights Reserved.

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