Jan

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2021

Multivariate Data Analysis by Brad Swarbrick, Kim H Esbensen

adteam 18 Jan 2021 16:22 LEARNING » e-book


Multivariate Data Analysis by Brad Swarbrick, Kim H  Esbensen


Multivariate Data Analysis by Brad Swarbrick, Kim H Esbensen
pdf, azw3 | 37.09 MB | English | Isbn:B07BBJS6CZ |
Author: Kim Esbensen & Brad Swarbrick & Frank Westad | PAge: 948 | Year: 2018



Description:

This long-anticipated textbook is currently the most up-to-date resource on chemometrics and Multivariate Data Analysis (MVA). The field of chemometrics is the application of multivariate data analysis methodology to solve chemistry-based problems. It explains not only how to understand experimental outputs, but also to put this newfound knowledge into use for deeper scientific understanding or business gains.

The authors' extensive practical experience from science, technology and industry is combined with the newest software on the market to present a unique didactic scope of MVA with full understanding of all necessary underlying principles. New topics such as PAT (Process Analytical Technology), QbD (Quality by Design) and TOS (Theory of Sampling), are covered in this 6th Edition. In addition to detailed explanations, all chapters have many illustrative examples for a better understanding of the concepts - and how they work in practice.

All examples and case stories have been updated from previous versions of the book. Both specific and all-encompassing, both deeply theoretical and grounded in modern application, accessible but advanced, this book serves as a fantastic teaching and reference tool for understanding the field of chemometrics.

"An excellent book to introduce chemometrics in a smooth and user-friendly way, both from a theoretical as well as a practical point of view. It is certainly good supporting material for chemometric teaching at undergraduate and graduate levels in chemistry and assuredly in many related scientific fields, and a very good self-learning basis for anyone wanting to use chemometric methods in industry or academia."
Anna de Juan, Universitat de Barcelona and Romà Tauler, IDAEA-CSIC


Category:Mathematics, Probability & Statistics

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