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Multivariate analysis of quality : an introduction

Author: Harald Martens; Magni Martens
Publisher: Chichester : John Wiley, ©2001.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Provides a powerful and versatile methodology that enables researchers to design their investigations and analyse data effectively and safely, without the need for formal statistical training.

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Document Type: Book
All Authors / Contributors: Harald Martens; Magni Martens
ISBN: 0471974285 9780471974284
OCLC Number: 782453990
Notes: Apéndices. -- Índice.
Description: XX, 445 p. : il. ; 24 cm
Contents: Preface. Acknowledgements. OVERVIEW. Why Multivariate Data Analysis? Qualimetrics for Determining Quality. A Laymana s Guide to Multivariate Data Analysis. METHODOLOGY. Some Estimation Concepts. Analysis of One Data Table X: Principle Component Analysis. Analysis of Two Data Tables X and Y: Partial Least Squares Regression (PLSR). Example of Multivariate Calibration Project. Interpretation of Many Types of Data X and Y: Exploring Relationships in Interdisciplinary Data Sets. Classification and Discrimination X--1, X--2, X--3: Handling Heterogeneous Sample Sets. Validation X and Y. Experimental Planning Y and X. APPLICATIONS. Multivariate Calibration: Quality Determination of Wheat From High--speed NIR Spectra. Analysis of Questionnaire Data: What Determines Quality of the Working Environment? Analysis of a Heterogeneous Sample Set: Predicting Toxicity From Quantum Chemistry. Multivariate Statistical Process Control: Quality Monitoring of a Sugar Production Process. Design and Analysis of Controlled Experiments: Reducing Loss of Quality in Stored Food. Appendix A1: How the Present Book Relates to Some Mathematical Modelling Traditions in Science. Appendix A2: Sensory Science. Appendix A3.1: Bi--linear Modelling Has Many Applications. Appendix A3.2: Common Problems and Pitfalls in Soft Modelling. Appendix A4: Mathematical Details. Appendix A5: PCA Details. Appendix A6: PLS Regression Details. Appendix A7: Modelling the Unknown. Appendix A8: Non--linearity and Weighting. Appendix A9: Classification and Outlier Detection. Appendix A10: Cross--validation Details. Appendix A11: Power Estimation Details. Appendix A12: What Makes NIR Data So Information--rich? Appendix A13: Consequences of the Working Environment Survey. Appendix A14: Details of the Molecule Class Models. Appendix A15: Forecasting the Future. Appendix A16: Significance Testing with Cross--validation vs. ANOVA. References. Index.
Responsibility: Harald Martens, Magni Martens.

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"This is an important book; the authors have done a quality job..." (N.I.R. News, Vol 12/1, 2001) "This book is recommended to students of chemical, biochemical and food engineering, scientists and Read more...

 
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