| Author: | Alejandro Olivieri, Graciela M. Escandar | ISBN: | 9780124104549 |
| Publisher: | Elsevier Science | Publication: | March 15, 2014 |
| Imprint: | Elsevier | Language: | English |
| Author: | Alejandro Olivieri, Graciela M. Escandar |
| ISBN: | 9780124104549 |
| Publisher: | Elsevier Science |
| Publication: | March 15, 2014 |
| Imprint: | Elsevier |
| Language: | English |
Practical Three-Way Calibration is an introductory-level guide to the complex field of analytical calibration with three-way instrumental data. With minimal use of mathematical/statistical expressions, it walks the reader through the analytical methodologies with helpful images and step-by-step explanations. Unlike other books on the subject, there is no need for prior programming experience and no need to learn programming languages. Easy-to-use graphical interfaces and intuitive descriptions of mathematical and statistical concepts make three-way calibration methodologies accessible to analytical chemists and scientists in a wide range of disciplines in industry and academia.
- Numerous detailed examples of slowly increasing complexity
- Exposure to several different data sets and techniques through figures and diagrams
- Computer program screenshots for easy learning without prior knowledge of programming languages
- Minimal use of mathematical/statistical expressions
Practical Three-Way Calibration is an introductory-level guide to the complex field of analytical calibration with three-way instrumental data. With minimal use of mathematical/statistical expressions, it walks the reader through the analytical methodologies with helpful images and step-by-step explanations. Unlike other books on the subject, there is no need for prior programming experience and no need to learn programming languages. Easy-to-use graphical interfaces and intuitive descriptions of mathematical and statistical concepts make three-way calibration methodologies accessible to analytical chemists and scientists in a wide range of disciplines in industry and academia.
- Numerous detailed examples of slowly increasing complexity
- Exposure to several different data sets and techniques through figures and diagrams
- Computer program screenshots for easy learning without prior knowledge of programming languages
- Minimal use of mathematical/statistical expressions
