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| PRACTICAL DATA ANALYSIS IN CHEMISTRY, 26
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 To order this title, and for more information, click here
By
Marcel Maeder, School of Environmental and Life Sciences, The University of Newcastle, Chemistry, Australia
Yorck-Michael Neuhold, School of Environmental and Life Sciences, The University of Newcastle, Chemistry, Australia
Included in series
Data Handling in Science and Technology,
Description
The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of
data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able
to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes.
The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a
Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated
for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction
to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical
processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications.
Finally Chapter 5 comprises a collection of several methods for model-free data analyses.
Audience
For post-graduate students, research and industrial chemists with sufficient interest in data analysis to warrant the development of their own software
Contents
1. Introduction
2. Matrix Algebra
2.1 Matrices, Vectors, Scalars
2.2 Solving Systems of Linear Equations
3. Physical/Chemical
Models
3.1 Beer-Lambert's Law
3.2 Chromatography / Gaussian Curves
3.3 Titrations, Equilibria, the Law of Mass Action
3.4 Kinetics, Mechanisms, Rate Laws
4. Model-based Analyses
4.1 Background to Least-Squares Methods
4.2 Linear Regression
4.3 Non-Linear Regression
4.4 General Optimisation
5. Model-Free Analyses
5.1 Factor Analysis, FA
5.2 Target
Factor Analyses
5.3 Evolving Factor Analyses
5.4 Alternating Least-Squares
5.5 Resolving Factor Analysis, RFA
5.6 Principle Component Regression and Partial Least Squares, PCR and PLS
| Bibliographic details |
Hardbound, 340 pages, publication date: JUL-2007
ISBN-13: 978-0-444-53054-7
ISBN-10: 0-444-53054-1
Imprint: ELSEVIER
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| Price and Ordering |
Price:
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USD 145
GBP 83
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Last update: 27 Sep 2008
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