Providing an easy explanation of the fundamentals, methods, and applications of chemometrics

• Acts as a practical guide to multivariate data analysis techniques
• Explains the methods used in Chemometrics and teaches the reader to perform all relevant calculations
• Presents the basic chemometric methods as worksheet functions in Excel
• Includes Chemometrics Add In for download which uses Microsoft Excel® for chemometrics training
• Online downloads includes workbooks with examples

Preface 1

Introduction 3

1. What is chemometrics? 4

1.1. Subject of chemometrics 6

1.2. Historical digression 9

2. Whom is this book for 13

2.1. Useful hints 14

2.2. Book syllabus 15

2.3. Notations 17

3. Installation of Chemometrics Add-In 19

3.1. Installation 20

3.2. General information 22

4. Further reading on Chemometrics 23

4.1. Books 25

4.2. The Internet 28

4.3. Journals 29

4.4. Software 30

The Basics 31

5. Matrices and vectors 32

5.1. The basics 35

5.2. Advance information 48

6. Statistics 59

6.1. The Basics 62

6.2. Main distributions 70

6.3. Parameter estimation 81

6.4. Properties of the estimators 91

6.5. Confidence estimation 95

6.6. Hypothesis Testing 98

6.7. Regression 104

Conclusion 108

7. Matrix calculations in Excel 109

7.1. Basic information 111

7.2. Matrix operations 124

7.3. Extension of Excel facilities 138

Conclusion 145

8. Projection methods in Excel 146

8.1. Projection methods 148

8.2. Application of Chemometrics Add-In 155

8.3. PCA 157

8.4. PLS 160

8.5. PLS2 168

8.6. Additional functions 176

Conclusion 179

Chemometrics 181

9. Principal Component Analysis (PCA) 182

9.1. The basics 184

9.2. Principal Components Analysis 188

9.3. People and countries 202

Conclusion 211

10. Calibration 212

10.1. The basics 214

10.2. Simulated data 228

10.3. Classic calibration 232

10.4. Inverse calibration 243

10.5. Latent variables calibration 249

10.6. Methods comparison 264

Conclusion 266

11. Classification 267

11.1. The basics 269

11.2. Data 275

11.3. Supervised classification 280

11.4. Unsupervised classification 299

Conclusion 303

12. Multivariate Curve Resolution 304

12.1. The basics 306

12.2. Simulated data 315

12.3. Factor analysis 320

12.4. Iterative methods 328

Conclusion 332

Supplements 333

13. Extension of Chemometrics Add-In 334

13.1. Using of virtual arrays 336

13.2. Using of VBA programming 345

Conclusion 352

14. Kinetic modeling of spectral data 354

14.1. The “Grey” modeling method 355

Conclusions 366

15. MatLab. Beginner's Guide 367

15.1. The basics 369

15.2. Matrices 374

15.3. Integrating Excel and MatLab 378

15.4. Programming 381

15.5. Sample programs 386

Conclusion 391

Afterword. The Fourth Paradigm 393

Index 400