| Description |
1 online resource (326 pages) |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
Data handling in science and technology ; v. 26 |
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Data handling in science and technology ; v. 26.
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| Summary |
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. * Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes. * Provides examples of routines that are easily adapted to the processes investigated by the reader * 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered. |
| 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. |
| Bibliography |
Includes bibliographical references and index. |
| Note |
Print version record. |
| Subject |
Chemistry -- Statistical methods.
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SCIENCE -- Chemistry -- General.
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Chemistry -- Statistical methods
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Chemie
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Datenanalyse
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| Added Author |
Neuhold, Yorck-Michael.
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| Other Form: |
Print version: Maeder, Marcel. Practical data analysis in chemistry. Oxford : Elsevier, 2007 9780444530547 0444530541 (OCoLC)137313131 |
| ISBN |
9780444530547 |
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0444530541 |
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9780080548838 (electronic bk.) |
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0080548830 (electronic bk.) |
| Standard No. |
X8511144 |
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AU@ 000048129682 |
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AU@ 000062551584 |
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CHDSB 005985555 |
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DEBBG BV039828478 |
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DEBBG BV042304752 |
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DEBSZ 405304544 |
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DEBSZ 48235397X |
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NZ1 11778275 |
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NZ1 13707814 |
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NZ1 15188738 |
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AU@ 000075311873 |
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