One. Introduction and Motivation

Chapters in this book

1. Frontmatter i
2. Contents vii
3. Preface xi
4. Acknowledgments xv
5. Part 1. Foundations
6. One. Introduction and Motivation 1
7. Two. Notation and Basic Operations 3
8. Three. Matrix Properties, Fundamental Spaces, Orthogonality 12
9. Four. Introduction to Eigenanalysis 47
10. Five. The Algebraic Operation of SVD 75
11. Part 2. Methods of Data Analysis
12. Six. The Gray World of Practical Data Analysis: An Introduction to Part 2 95
13. Seven. Statistics in Deterministic Sciences: An Introduction 96
14. Eight. Autocorrelation 109
15. Nine. Regression and Least Squares 126
16. Ten. The Fundamental Theorem of Linear Algebra 197
17. Eleven. Empirical Orthogonal Functions 200
18. Twelve. The SVD Analysis of Two Fields 261
19. Thirteen. Suggested Homework 276
20. Index 313