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Multivariate Analysis of Quality An Introduction

ISBN-10: 0471974285

ISBN-13: 9780471974284

Edition: 2001

Authors: Harald Martens, M. Martens

List price: $415.00
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Providing an introductory explanation of multivariate analysis, this volume describes the application for the assessment of quality and includes many examples from food science to illustrate the theory.
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Book details

List price: $415.00
Copyright year: 2001
Publisher: John Wiley & Sons, Incorporated
Publication date: 2/8/2001
Binding: Hardcover
Pages: 466
Size: 6.00" wide x 9.00" long x 1.25" tall
Weight: 1.694
Language: English

Why Multivariate Data Analysis?
Qualimetrics for Determining Quality
A Layman's Guide to Multivariate Data Analysis
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
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
How the Present Book Relates to Some Mathematical Modelling Traditions in Science
Sensory Science
Bi-linear Modelling Has Many Applications
Common Problems and Pitfalls in Soft Modelling
Mathematical Details
PCA Details
PLS Regression Details
Modelling the Unknown
Non-linearity and Weighting
Classification and Outlier Detection
Cross-validation Details
Power Estimation Details
What Makes NIR Data So Information-rich?
Consequences of the Working Environment Survey
Details of the Molecule Class Models
Forecasting the Future
Significance Testing with Cross-validation vs ANOVA