Data analysis is a vital part of science today, and in assessingquality, multivariate analysis is often necessary in order to avoidloss of essential information. Martens provides a powerful andversatile methodology that enables researchers to design theirinvestigations and analyse data effectively and safely, without theneed for formal statistical training. * Offers an introductory explanation of multivariate analysis bygraphical 'soft modelling' * Minimises mathematics, providing all technical details in theappendix * Presents itself in an accessible style with cartoons,self-assessment questions and a wide range of practicalexamples * Demonstrates the methodology for various types of qualityassessment, ranging from human quality perception via industrialquality monitoring to environmental quality and its molecularbasis All data sets available FREE online on "Chemometrics World"(
Multivariate Calibration Harald Martens, Chemist, Norwegian Food Research Institute, Aas, Norway and Norwegian Computing Center, Oslo, Norway Tormod Næs, Statistician, Norwegian Food Research Institute, Aas, Norway The aim of this inter-disciplinary book is to present an up-to-date view of multivariate calibration of analytical instruments, for use in research, development and routine laboratory and process operation. The book is intended to show practitioners in chemistry and technology how to extract the quantitative and understandable information embedded in non-selective, overwhelming and apparently useless measurements by multivariate data analysis. Multivariate calibration is the process of learning how to combine data from several channels, in order to overcome selectivity problems, gain new insight and allow automatic outlier detection. Multivariate calibration is the basis for the present success of high-speed Near-Infrared (NIR) diffuse spectroscopy of intact samples. But the technique is very general: it has shown similar advantages in, for instance, UV, Vis, and IR spectrophotometry, (transmittance, reflectance and fluorescence), for x-ray diffraction, NMR, MS, thermal analysis, chromatography (GC, HPLC) and for electrophoresis and image analysis (tomography, microscopy), as well as other techniques. The book is written at two levels: the main level is structured as a tutorial on the practical use of multivariate calibration techniques. It is intended for university courses and self-study for chemists and technologists, giving one complete and versatile approach, based mainly on data compression methodology in self-modelling PLS regression, with considerations of experimental design, data pre-processing and model validation. A second, more methodological, level is intended for statisticians and specialists in chemometrics. It compares several alternative calibration methods, validation approaches and ways to optimize the models. The book also outlines some cognitive changes needed in analytical chemistry, and suggests ways to overcome some communication problems between statistics and chemistry and technology.
According to European legislation, extra virgin is the top gradeof olive oils. It has a superior level of health properties andflavour compared to virgin and refined olive oils. Mediterraneancountries still produce more than 85% of olive oil globally, butthe constant increase of demand for extra virgin olive oil has ledto new cultivation and production in other areas of the world,including California, Australia, China, South Africa and SouthAmerica. At the same time, olive oil’s sensory properties andhealth benefits are increasingly attracting the attention andinterest of nutritionists, food processors, manufacturers and foodservices. Progress and innovation in olive cultivation, harvestingand milling technologies as well as in oil handling, storage andselling conditions make it possible to achieve even higher qualitylevels than those stipulated for extra virgin oils. As aconsequence, a new segment – excellent extra virgin oliveoils – is increasingly attracting the attention of the marketand earning consumers’ preference. The Extra-Virgin Olive Oil Handbook provides a completeaccount of olive oil’s composition, health properties,quality, and the legal standards surrounding its production. Thebook is divided into convenient sections focusing on extra virginolive oil as a product, the process by which it is made, and theprocess control system through which its quality is assured. Anappendix presents a series of tables and graphs with useful data,including conversion factors, and the chemical and physicalcharacteristics of olive oil. This book is aimed at people involved in the industrial productionas well as in the marketing and use of extra virgin olive oil whoare looking for practical information, which avoids overly academiclanguage, but which is still scientifically and technically sound.The main purpose of the handbook is to guide operators involved inthe extra virgin olive oil chain in making the most appropriatedecisions about product quality and operating conditions in theproduction and distribution processes. To these groups, the mostimportant questions are practical ones of why, how, how often, howmuch will it cost, and so on. The Extra-Virgin Olive OilHandbook will provide the right answers to these key practicalconsiderations, in a simple, clear yet precise and up-to-dateway.
Fermented meat products have been consumed for centuries in many different parts of the world and constitute one of the most important groups of food. Bacterial cultures are used in their manufacture to preserve the meat and confer particular textures and sensory attributes. Examples of fermented meats include salami, chorizo, pepperoni and saucisson. This fully revised and expanded reference book on meat fermentation presents all the principle fermented meat products and the processing technologies currently used in their manufacture. The 54 chapters of this substantial book are grouped into the following sections: Meat fermentation worldwide: overview, production and principles Raw materials Microbiology and starter cultures for meat fermentation Sensory attributes Product categories: general considerations Semidry-fermented sausages Dry-fermented sausages Other fermented meats and poultry Ripened meat products Biological and chemical safety of fermented meat products Processing sanitation and quality assurance There are five new chapters in the second edition that address the following topics: Smoking and new smoke flavourings; Probiotics; Methodologies for the study of the microbial ecology in fermented sausages; Low sodium in meat products; and Asian sausages. Handbook of Fermented Meat and Poultry, Second Edition provides readers with a full overview of meat fermentation, the role of microorganisms naturally present and/or added as starter cultures, safety aspects and an account of the main chemical, biochemical, physical and microbiological changes that occur in processing and how they affect final quality. Finally, readers will find the main types of worldwide fermented meat products, typically produced in different areas, with the description of their main characteristics.
​​​​​The intensive use of automatic data acquisition system and the use of cloud computing for process monitoring have led to an increased occurrence of industrial processes that utilize statistical process control and capability analysis. These analyses are performed almost exclusively with multivariate methodologies. The aim of this Brief is to present the most important MSQC techniques developed in R language. The book is divided into two parts. The first part contains the basic R elements, an introduction to statistical procedures, and the main aspects related to Statistical Quality Control (SQC). The second part covers the construction of multivariate control charts, the calculation of Multivariate Capability Indices.
This comprehensive text introduces readers to the most commonly used multivariate techniques at an introductory, non-technical level. By focusing on the fundamentals, readers are better prepared for more advanced applied pursuits, particularly on topics that are most critical to the behavioral, social, and educational sciences. Analogies between the already familiar univariate statistics and multivariate statistics are emphasized throughout. The authors examine in detail how each multivariate technique can be implemented using SPSS and SAS and Mplus in the book’s later chapters. Important assumptions are discussed along the way along with tips for how to deal with pitfalls the reader may encounter. Mathematical formulas are used only in their definitional meaning rather than as elements of formal proofs. A book specific website - - provides files with all of the data used in the text so readers can replicate the results. The Appendix explains the data files and its variables. The software code (for SAS and Mplus) and the menu option selections for SPSS are also discussed in the book. The book is distinguished by its use of latent variable modeling to address multivariate questions specific to behavioral and social scientists including missing data analysis and longitudinal data modeling. Ideal for graduate and advanced undergraduate students in the behavioral, social, and educational sciences, this book will also appeal to researchers in these disciplines who have limited familiarity with multivariate statistics. Recommended prerequisites include an introductory statistics course with exposure to regression analysis and some familiarity with SPSS and SAS.
This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues. The following chapters concentrate on machine learning and artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.
Praise for the First Edition "This is a superb text from which to teach categorical dataanalysis, at a variety of levels. . . [t]his book can be veryhighly recommended." —Short Book Reviews "Of great interest to potential readers is the variety of fieldsthat are represented in the examples: health care, financial,government, product marketing, and sports, to name a few." —Journal of Quality Technology "Alan Agresti has written another brilliant account of theanalysis of categorical data." —The Statistician The use of statistical methods for categorical data is everincreasing in today's world. An Introduction to Categorical DataAnalysis, Second Edition provides an applied introduction tothe most important methods for analyzing categorical data. This newedition summarizes methods that have long played a prominent rolein data analysis, such as chi-squared tests, and also placesspecial emphasis on logistic regression and other modelingtechniques for univariate and correlated multivariate categoricalresponses. This Second Edition features: Two new chapters on the methods for clustered data, with anemphasis on generalized estimating equations (GEE) and randomeffects models A unified perspective based on generalized linear models An emphasis on logistic regression modeling An appendix that demonstrates the use of SAS(r) for allmethods An entertaining historical perspective on the development ofthe methods Specialized methods for ordinal data, small samples,multicategory data, and matched pairs More than 100 analyses of real data sets and nearly 300exercises Written in an applied, nontechnical style, the book illustratesmethods using a wide variety of real data, including medicalclinical trials, drug use by teenagers, basketball shooting,horseshoe crab mating, environmental opinions, correlates ofhappiness, and much more. An Introduction to Categorical Data Analysis, SecondEdition is an invaluable tool for social, behavioral, andbiomedical scientists, as well as researchers in public health,marketing, education, biological and agricultural sciences, andindustrial quality control.
Praise for the Second Edition "A must-have book for anyone expecting to do research and/orapplications in categorical data analysis." —Statistics in Medicine "It is a total delight reading this book." —Pharmaceutical Research "If you do any analysis of categorical data, this is anessential desktop reference." —Technometrics The use of statistical methods for analyzing categorical datahas increased dramatically, particularly in the biomedical, socialsciences, and financial industries. Responding to new developments,this book offers a comprehensive treatment of the most importantmethods for categorical data analysis. Categorical Data Analysis, Third Edition summarizes thelatest methods for univariate and correlated multivariatecategorical responses. Readers will find a unified generalizedlinear models approach that connects logistic regression andPoisson and negative binomial loglinear models for discrete datawith normal regression for continuous data. This edition alsofeatures: An emphasis on logistic and probit regression methods forbinary, ordinal, and nominal responses for independent observationsand for clustered data with marginal models and random effectsmodels Two new chapters on alternative methods for binary responsedata, including smoothing and regularization methods,classification methods such as linear discriminant analysis andclassification trees, and cluster analysis New sections introducing the Bayesian approach for methods inthat chapter More than 100 analyses of data sets and over 600 exercises Notes at the end of each chapter that provide references torecent research and topics not covered in the text, linked to abibliography of more than 1,200 sources A supplementary website showing how to use R and SAS; for allexamples in the text, with information also about SPSS and Stataand with exercise solutions Categorical Data Analysis, Third Edition is an invaluabletool for statisticians and methodologists, such as biostatisticiansand researchers in the social and behavioral sciences, medicine andpublic health, marketing, education, finance, biological andagricultural sciences, and industrial quality control.
Demonstrates ways to track industrial processes and performance, integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. The book covers a range of statistical methods and emphasizes practical applications of quality control systems in manufacturing, organization and planning.
Multivariate statistical methods are an essential component of quality engineering data analysis. This monograph provides a solid background in multivariate statistical fundamentals and details key multivariate statistical methods, including simple multivariate data graphical display and multivariate data stratification. * Graphical multivariate data display * Multivariate regression and path analysis * Multivariate process control charts * Six sigma and multivariate statistical methods
The olive oil market is increasingly international. Levels ofconsumption and production are growing, particularly in“new” markets outside the Mediterranean region. Newfeatures of product optimization and development are emerging, andalong with them new marketing strategies, which benefit from aclear understanding of the sensory aspects of foods, as well asadequate sensory techniques for testing them. Recently developedsensory methods and approaches are particularly suitable for studying thesensory properties of olive oils and their function in culinarypreparation or in oil-food pairing. Each chapter of Olive Oil Sensory Science is written bythe best researchers and industry professionals in the fieldthroughout the world. The book is divided into two main sections.The first section details the appropriate sensory methods for oliveoil optimization, product development, consumer testing and qualitycontrol. The intrinsic factors affecting olive oil qualityperception are considered, as well as the nutritional, health andsensory properties, underlining the importance of sensorytechniques in product differentiation. The agronomic andtechnological aspects of production that affect sensory propertiesand their occurrence in olive oil are also addressed. Sensoryperception and other factors affecting consumer choice arediscussed, as is the topic of olive oil sensory quality. The secondpart of this text highlights the major olive oil producing regionsof the world: Spain, Italy, Greece, California, Australia/New Zealand andSouth America. Each chapter is dedicated to a region, looking atthe geographical and climactic characteristics pertinent to oliveoil production, the major regional olive cultivars, the principleolive oil styles and their attendant sensory properties. Olive Oil Sensory Science is an invaluable resource forolive oil scientists, product development and marketing personnelon the role of sensory evaluation in relation to current and futuremarket trends.
The authors' approach to the information aids professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding output accompany sample problems, and clear explanations of the various SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples. High-resolution graphs have been used in this new edition.

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