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Factor analysis is a mathematical tool for examining a wide range of data sets, with applications especially important to the design of experiments (DOE), spectroscopy, chromatography, and chemometrics. Whereas the first two editions concentrated on standardizing the fundamentals of this emerging discipline, the Third Edition of Factor Analysis in Chemistry, the "bible" of factor analysis, proves a comprehensive handbook at a level that is consistent with the research and design of experiments today. With the exception of updates, the introductory chapters remain unchanged. Chapter 6 has been edited to focus on evolutionary methods, including window factor analysis, transmutation, and DECRA. Selections on partial least squares and multimode analysis have been expanded and consolidated into two new chapters, 7 and 8. Some of the latest advances in a wide variety of fields, such as chromatography, NMR, biomedicine, environmental science, food, and fuels, are described in the applications chapters (chapters 9 through 12). Other features of the book include: Provides history of the discipline as well as theory, philosophy, and applications Written for all readership levels: introductory, intermediate, and advanced Explains complicated concepts in simple language without sacrificing mathematical rigor Presents concepts and programs in a style that allows the user to develop programs in any computer language Demonstrates the utility of various factor analytical techniques for solving practical problems in chemistry and related sciences Showcases a unique presentation of partial least squares

Chemistry --- Factor analysis. --- Statistical methods. --- Acqui 2006 --- Factor analysis

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Mathematical statistics --- Principal components analysis --- Analyse en composantes principales --- Mathematical Statistics --- Mathematics --- Physical Sciences & Mathematics --- 519.535 --- Analysis, Principal components --- Components analysis, Principal --- Correlation (Statistics) --- Factor analysis --- Principal components analysis. --- EPUB-LIV-FT SPRINGER-B

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Are there universal laws governing the persistence of weather, and is it possible to predict climate transitions as generated by natural or man-made perturbations? How can one quantify the roller-coaster dynamics of stock markets and anticipate mega-crashes? Can we diagnose the health condition of patients from heartbeat time-series analysis which may even form the basis for infarct prevention? This book tackles these questions by applying advanced methods from statistical physics and related fields to all types of non-linear dynamics prone to disaster. The transdisciplinary analysis is organized in some dozen review articles written by world-class scientists.

Stochastic processes --- Mathematical physics --- Biological systems. --- Climatology. --- Disasters. --- Economics. --- Nonlinear theories. --- Statistical physics. --- Disasters --- Factor Analysis, Statistical. --- Forecasting --- Models, Theoretical. --- Geografie --- statistics & numerical data. --- methods. --- Risicos Rampen --- Algemeen. --- Statistics & numerical data. --- Methods. --- Sociophysics. --- Econophysics. --- Dynamical systems. --- Atmospheric sciences. --- Medicine. --- Environmental sciences. --- Statistics . --- Data-driven Science, Modeling and Theory Building. --- Complex Systems. --- Atmospheric Sciences. --- Medicine/Public Health, general. --- Math. Appl. in Environmental Science. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Environmental science --- Science --- Health Workforce --- Atmospheric sciences --- Earth sciences --- Atmosphere --- Dynamical systems --- Kinetics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical statistics --- Economics --- Statistical physics --- Mathematical sociology