Multivariate Analysis of Quality – An Introduction

Preface.
<br />
<br /> Acknowledgements.
<br />
<br /> OVERVIEW.
<br />
<br /> Why Multivariate Data Analysis?
<br />
<br /> Qualimetrics for Determining Quality.
<br />
<br /> A Layman′s Guide to Multivariate Data Analysis.
<br />
<br /> METHODOLOGY.
<br />
<br /> Some Estimation Concepts.
<br />
<br /> Analysis of One Data Table X: Principle Component Analysis.
<br />
<br /> Analysis of Two Data Tables X and Y: Partial Least Squares Regression (PLSR).
<br />
<br /> Example of Multivariate Calibration Project.
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<br /> Interpretation of Many Types of Data X and Y: Exploring Relationships in Interdisciplinary Data Sets.
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<br /> Classification and Discrimination X—1, X—2, X—3: Handling Heterogeneous Sample Sets.
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<br /> Validation X and Y.
<br />
<br /> Experimental Planning Y and X.
<br />
<br /> APPLICATIONS.
<br />
<br /> Multivariate Calibration: Quality Determination of Wheat From High–speed NIR Spectra.
<br />
<br /> Analysis of Questionnaire Data: What Determines Quality of the Working Environment?
<br />
<br /> Analysis of a Heterogeneous Sample Set: Predicting Toxicity From Quantum Chemistry.
<br />
<br /> Multivariate Statistical Process Control: Quality Monitoring of a Sugar Production Process.
<br />
<br /> Design and Analysis of Controlled Experiments: Reducing Loss of Quality in Stored Food.
<br />
<br /> Appendix A1: How the Present Book Relates to Some Mathematical Modelling Traditions in Science.
<br />
<br /> Appendix A2: Sensory Science.
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<br /> Appendix A3.1: Bi–linear Modelling Has Many Applications.
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<br /> Appendix A3.2: Common Problems and Pitfalls in Soft Modelling.
<br />
<br /> Appendix A4: Mathematical Details.
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<br /> Appendix A5: PCA Details.
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<br /> Appendix A6: PLS Regression Details.
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<br /> Appendix A7: Modelling the Unknown.
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<br /> Appendix A8: Non–linearity and Weighting.
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<br /> Appendix A9: Classification and Outlier Detection.
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<br /> Appendix A10: Cross–validation Details.
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<br /> Appendix A11: Power Estimation Details.
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<br /> Appendix A12: What Makes NIR Data So Information–rich?
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<br /> Appendix A13: Consequences of the Working Environment Survey.
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<br /> Appendix A14: Details of the Molecule Class Models.
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<br /> Appendix A15: Forecasting the Future.
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<br /> Appendix A16: Significance Testing with Cross–validation vs. ANOVA.
<br />
<br /> References.
<br />
<br /> Index.