Good,No Highlights,No Markup,all pages are intact, Slight Shelfwear,may have the corners slightly dented, may have slight color changes/slightly damaged spine.

A complete revision to the theory, practice and applications of factor analysis in chemistry—a mathematical technique for studying matrices of data. Methods of factor analysis that are quicker, more cost effective and easier as a result of new computer applications are included. Topics added include A and R model analysis, singular value decomposition, NIPALS decomposition and iterative key set factor analysis. New methods for rank determination, statistical methods for target testing, errors in factor loadings and weighted factor analysis are also treated in this edition. Special methods of factor analysis such as classical factor analysis, common factors, communality, partial least squares, and modeling and self modeling methods of evolutionary factor analysis are also included.

The fundamentals of the discipline, now complete with the latest experimental research and techniques 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 text 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 Factor Analysis in Chemistry, Third Edition remains the premier reference in its field.

At a time when computerized laboratory automation is producing a da ta explosion, chemists are turning to applied mathematics and statistics for the tools to extract useful chemical information from data. This rush to find applicable methods has lead to a somewhat confusing body of literature that represents a barrier to chemists wishing to learn more about chemometrics. The confusion results partly from the mixing of chemical notation and nomenclature with those of statistics, applied mathematics and engineering. Additionally, in the absence of collaboration with mathematicians, chemists have, at times, misused data analysis methodology and even reinvented methods that have seen years of service in other fields. The Chemometrics Society has worked hard to solve this problem since it was founded in 1974 with the goal of improving communications between the chemical sciences and applied mathe matics and statistics. The NATO Advanced Study Institute on Chemometrics is evidence of this fact as it was initiated in response to a call from its membership for advanced training in several areas of chemometrics. This Institute focused on current theory and application in the new field of Chemometrics: Use of mathematical and statistical methods, Ca) to design or select optimal measurement procedures and experiments; and Cb) to provide maximum chemical information by analyzing chemical data. The Institute had two formal themes and two informal themes.

The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses.* Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes.* Provides examples of routines that are easily adapted to the processes investigated by the reader* 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.

Chemistry 2e is designed to meet the scope and sequence requirements of the two-semester general chemistry course. The textbook provides an important opportunity for students to learn the core concepts of chemistry and understand how those concepts apply to their lives and the world around them. The book also includes a number of innovative features, including interactive exercises and real-world applications, designed to enhance student learning. The second edition has been revised to incorporate clearer, more current, and more dynamic explanations, while maintaining the same organization as the first edition. Substantial improvements have been made in the figures, illustrations, and example exercises that support the text narrative. Changes made in Chemistry 2e are described in the preface to help instructors transition to the second edition.

Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas: * The classical principal components model and sample-populationinference * Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain * Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores * The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable * Applications of factor models to the estimation of functionalforms and to least squares of regression estimators

Many forms of chemical experimentation generate data needing analysis and interpretation in respect of the goals of the experiment and also the chemical factors which may influence the outcome. Statistical data analysis techniques provide the tools which enable a chemist to assess the information obtained from experiments. Statistical Analysis Methods for Chemists: A Software-based Approach aims to give a broad introduction to practical data analysis, and provides comprehensive coverage of basic statistical principles and reasoning. With practical examples, and integration of software output as the basis of data analysis, this useful book gives unique coverage of the statistical skills and techniques required in modern chemical experimentation. It will prove invaluable to students and researchers alike. Software update information is available from W Gardiner at [email protected] or fax +44 (0)141 331 3608. Please accompany requests for information with details of the software version to be used.

Chemometrics originated from multivariate statistics in chemistry, and this field is still the core of the subject. The increasing availability of user-friendly software in the laboratory has prompted the need to optimize it safely. This work comprises material presented in courses organized from 1987-1992, aimed mainly at professionals in industry. The book covers approaches for pattern recognition as applied, primarily, to multivariate chemical data. These include data reduction and display techniques, principal components analysis and methods for classification and clustering. Comprehensive case studies illustrate the book, including numerical examples, and extensive problems are interspersed throughout the text. The book contains extensive cross-referencing between various chapters, comparing different notations and approaches, enabling readers from different backgrounds to benefit from it and to move around chapters at will. Worked examples and exercises are given, making the volume valuable for courses. Tutorial versions of SPECTRAMAP and SIRIUS are optionally available as a Software Supplement, at a low price, to accompany the text.