Multivariate Data Analysis
- in practice (5th Edition)  |
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Includes sample datasets & The Unscrambler® (Training version). | ||||||||||||||||||
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Contents
- Introduction to Multivariate Data Analysis overview
- Getting Started - with Descriptive Statistics
- Principal Component Analysis (PCA) – Introduction
- Principal Component Analysis (PCA) - In Practice
- PCA Exercises - Real-World Application Examples
- Multivariate Calibration (PCR/PLS)
- Validation: Mandatory Performance Testing
- How to Perform PCR and PLS-R
- Multivariate Data Analysis - in Practice: Miscellaneous Issues
- PLS (PCR) Exercises: Real-World Application Examples - I
- PLS (PCR) Multivariate Calibration - In Practice
- PLS (PCR) Exercises: Real-World Applications - II
- Master Data Sets: Interim Examination
- Uncertainty Estimates, Significance and Stability (Martens' Uncertainty Test)
- SIMCA: An Introduction to Classification
- Introduction to Experimental Design
- Complex Experimental Design Problems
- Comparison of Methods for Multivariate Data Analysis - And their Validation
- Literature
- Appendix: Algorithms
- Appendix: Software Installation and User Interface
Tutorial exercises,based on data drawn from real-world applications are used throughout the book to illustrate the use of the techniques introduced.This provides the reader with a working knowledge of modern Multivariate Data Analysis. All exercises use The Unscrambler®. The Introducer is an excellent self-study text for scientists, chemists and engineers of all disciplines- statisticians or non-statisticians - wishing to exploit the power of modern multivariate methods.
