A Practical Guide to Scientific Data Analysis (eBook)

David N. Livingstone (Autor)

eBook Download: PDF

2009 | 1. Auflage
358 Seiten
John Wiley & Sons (Verlag)
978-0-470-68481-8 (ISBN)

Infos

Inspired by the author's need for practical guidance in the
processes of data analysis, A Practical Guide to Scientific Data
Analysis has been written as a statistical companion for the
working scientist. This handbook of data analysis with worked
examples focuses on the application of mathematical and statistical
techniques and the interpretation of their results.

Covering the most common statistical methods for examining and
exploring relationships in data, the text includes extensive
examples from a variety of scientific disciplines.

The chapters are organised logically, from planning an
experiment, through examining and displaying the data, to
constructing quantitative models. Each chapter is intended to stand
alone so that casual users can refer to the section that is most
appropriate to their problem.

Written by a highly qualified and internationally respected
author this text:

* Presents statistics for the non-statistician

* Explains a variety of methods to extract information from
data

* Describes the application of statistical methods to the design
of "performance chemicals"

* Emphasises the application of statistical techniques and the
interpretation of their results

Of practical use to chemists, biochemists, pharmacists,
biologists and researchers from many other scientific disciplines
in both industry and academia.

Autor

David J. Livingstone is the author of A Practical Guide to Scientific Data Analysis, published by Wiley.

Inhalt

Preface.

Abbreviations.

1 Introduction: Data and it's Properties, AnalyticalMethods and Jargon.

1.1 Introduction.

1.2 Types of Data.

1.3 Sources of Data.

1.4 The Nature of Data.

1.5 Analytical Methods.

1.6 Summary.

References.

2 Experimental Design - Experiment and SetSelection.

2.1 What is Experimental Design?

2.2 Experimental Design Techniques.

2.3 Strategies for Compound Selection.

2.4 High Throughput Experiments.

2.5 Summary.

References.

3 Data Pre-treatment and Variable Selection.

3.1 Introduction.

3.2 Data Distribution.

3.3 Scaling.

3.4 Correlations.

3.5 Data Reduction.

3.6 Variable Selection.

3.7 Summary.

References.

4 Data Display.

4.1 Introduction.

4.2 Linear Methods.

4.3 Non-linear Methods.

4.4 Faces, Flowerplots & Friends.

4.5 Summary.

References.

5 Unsupervised Learning.

5.1 Introduction.

5.2 Nearest-neighbour Methods.

5.3 Factor Analysis.

5.4 Cluster Analysis.

5.5 Cluster Significance Analysis.

5.6 Summary.

References.

6 Regression analysis.

6.1 Introduction.

6.2 Simple Linear Regression.

6.3 Multiple Linear Regression.

6.4 Multiple Regression - Robustness, Chance Effects, theComparison of Models and Selection Bias.

6.5 Summary.

References.

7 Supervised Learning.

7.1 Introduction.

7.2 Discriminant Techniques.

7.3 Regression on principal Components & PLS.

7.4 Feature Selection.

7.5 Summary.

References.

8 Multivariate Dependent Data.

8.1 Introduction.

8.2 Principal Components and Factor Analysis.

8.3 Cluster Analysis.

8.4 Spectral Map Analysis.

8.5 Models with Multivariate Dependent and Independent Data.

8.6 Summary.

References.

9 Artificial Intelligence & Friends.

9.1 introduction.

9.2 Expert Systems.

9.3 Neural Networks.

9.4 Miscellaneous AI Techniques.

9.5 Genetic Methods.

9.6 Consensus Models.

9.7 Summary.

References.

10 Molecular Design.

10.1 The Need for Molecular Design.

10.2 What is QSAR/QSPR?.

10.3 Why Look for Quantitative Relationships?.

10.4 Modelling Chemistry.

10.5 Molecular Field and Surfaces.

10.6 Mixtures.

10.7 Summary.

References.

Index.

Rezensionen

"Written by a highly qualified internationally respected
author this text is of practical use to chemists, biochemists,
pharmacists, biologists and researchers from many other scientific
disciplines in both industry and academia."
(International Journal Microstructure & Materials
Properties, 1 October 2011)

"At the same time, the highly detailed, thoughtful and readable
explanation of statistical and data-mining concepts throughout the
book will make it a valuable addition to the libraries of a wide
range of researchers . . . It is definitely worth its purchase
price and may be considered seriously as a textbook for nonmajor
statistics students and research scientists in a wide variety of
fields." (The American Statistician, 1 May 2011)

"The book is recommended for readers interested, but not
experienced, in data analysis methods used in drug design,
pharmaceutical research or related areas. It provides an almost
mathematical-free introduction to some multivariate statistical
methods applied in these fields. Also the great experience and the
personal views of a highly qualified author may be interesting for
many scientists." (Zentralblatt Math, 2010)

"This book should provide those engaged in multidimensional
experimentation a relatively compact (under 400 pages) oversight of
the relative merits of numerous techniques, all of which are
heavily computer dependent, and will be of especial interest to
those working in the field of pharmaceutical research. It should
also draw their attention to the roots of complex methods by means
of its introductory chapters." (Chromatographia, October 2010)

"This book is a guide to the wide range of methods available.
Not surprisingly given the author's background, the examples
in the book are all chemical and hence it will be of most interest
and value to chemistry researchers." (Chemistry World,
May 2010)

Produkt-Details

• Erscheint lt. Verlag: 10.12.2009
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
• Themenwelt: Naturwissenschaften ► Chemie
• Themenwelt: Technik
• Schlagworte: Biostatistics • Biostatistik • Chemie • Chemistry • Chemometrik • Datenanalyse • Lab Automation & Miniaturization • Laborautomatisierung u. Miniaturisierung • Mathematics & Statistics for Chemistry • Mathematik u. Statistik i. d. Chemie • Statistics • Statistik
• ISBN-10: 0-470-68481-X / 047068481X
• ISBN-13: 978-0-470-68481-8 / 9780470684818