Naes Tormod (42 results)

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Hardback. Condition: New. As we move further into the 21st Century, sensory and consumer studies continue to develop, playing an important role in food science and industry. These studies are crucial for understanding the relation between food properties on one side and human liking and buying behaviour on the other. This book by a group of established scientists gives a comprehensive, up-to-date overview of the most common statistical methods for handling data from both trained sensory panels and consumer studies of food. It presents the topic in two distinct sections: problem-orientated (Part I) and method orientated (Part II), making it to appropriate for people at different levels with respect to their statistical skills. This book succesfully: Makes a clear distinction between studies using a trained sensory panel and studies using consumers.Concentrates on experimental studies with focus on how sensory assessors or consumers perceive and assess various product properties.Focuses on relationships between methods and techniques and on considering all of them as special cases of more general statistical methodologies It is assumed that the reader has a basic knowledge of statistics and the most important data collection methods within sensory and consumer science. This text is aimed at food scientists and food engineers working in research and industry, as well as food science students at master and PhD level. In addition, applied statisticians with special interest in food science will also find relevant information within the book.…

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Hardback. Condition: New. Multiblock Data Fusion in Statistics and Machine Learning Explore the advantages and shortcomings of various forms of multiblock analysis, and the relationships between them, with this expert guide Arising out of fusion problems that exist in a variety of fields in the natural and life sciences, the methods available to fuse multiple data sets have expanded dramatically in recent years. Older methods, rooted in psychometrics and chemometrics, also exist. Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is a detailed overview of all relevant multiblock data analysis methods for fusing multiple data sets. It focuses on methods based on components and latent variables, including both well-known and lesser-known methods with potential applications in different types of problems. Many of the included methods are illustrated by practical examples and are accompanied by a freely available R-package. The distinguished authors have created an accessible and useful guide to help readers fuse data, develop new data fusion models, discover how the involved algorithms and models work, and understand the advantages and shortcomings of various approaches. This book includes: A thorough introduction to the different options available for the fusion of multiple data sets, including methods originating in psychometrics and chemometricsPractical discussions of well-known and lesser-known methods with applications in a wide variety of data problemsIncluded, functional R-code for the application of many of the discussed methods Perfect for graduate students studying data analysis in the context of the natural and life sciences, including bioinformatics, sensometrics, and chemometrics, Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is also an indispensable resource for developers and users of the results of multiblock methods.…

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Condition: New. This book by a group of established scientists gives a comprehensive, up-to-date overview of the most common statistical methods for handling data from both trained sensory panels and consumer studies of food. Num Pages: 300 pages, Illustrations. BIC Classification: PB; PN; TDCT; TT. Category: (P) Professional & Vocational. Dimension: 253 x 178 x 22. Weight in Grams: 658. . 2010. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …

Buch. Condition: Neu. Individual Differences in Sensory and Consumer Science | Experimentation, Analysis and Interpretation | Tormod Naes (u. a.) | Buch | Englisch | Woodhead Publishing | EAN 9780081010006 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, productsafety[at]elsevier[dot]com | Anbieter: preigu. …

Hardcover. Condition: Brand New. 286 pages. 9.61x6.69x1.02 inches. In Stock.

Hardback. Condition: New. As we move further into the 21st Century, sensory and consumer studies continue to develop, playing an important role in food science and industry. These studies are crucial for understanding the relation between food properties on one side and human liking and buying behaviour on the other. This book by a group of established scientists gives a comprehensive, up-to-date overview of the most common statistical methods for handling data from both trained sensory panels and consumer studies of food. It presents the topic in two distinct sections: problem-orientated (Part I) and method orientated (Part II), making it to appropriate for people at different levels with respect to their statistical skills. This book succesfully: Makes a clear distinction between studies using a trained sensory panel and studies using consumers.Concentrates on experimental studies with focus on how sensory assessors or consumers perceive and assess various product properties.Focuses on relationships between methods and techniques and on considering all of them as special cases of more general statistical methodologies It is assumed that the reader has a basic knowledge of statistics and the most important data collection methods within sensory and consumer science. This text is aimed at food scientists and food engineers working in research and industry, as well as food science students at master and PhD level. In addition, applied statisticians with special interest in food science will also find relevant information within the book.…

Hardcover. Condition: Brand New. 1st edition. 102 pages. 9.50x6.50x0.50 inches. In Stock.

Soft cover. Condition: Good. 1st Edition. This is a used copy of this authoritative text in reasonable condition. As shown in image_6.png, the book is a softcover 1st Edition. There is no visible damage to the front cover, back, or spine beyond the normal wear and tear expected from standard academic use. The binding is firm and the internal pages are clean and intact. About this Book: Considered a foundational text in the field of chemometrics, this interdisciplinary book provides an up-to-date view of multivariate calibration. It is designed to show practitioners in chemistry and technology how to extract quantitative, understandable information from complex measurements using multivariate data analysis.  Key Features include:  Methodological Depth: Covers fundamental theory including noise reduction, handling of interferents, and outlier control.  Practical Techniques: Detailed guidance on Principal Component Regression (PCR) and Partial Least Squares (PLS) regression.  Broad Application: Relevant for a wide range of analytical techniques such as NIR, UV/Vis spectrometry, NMR, MS, and chromatography (GC, HPLC).  Dual-Level Structure: Written as a practical tutorial for chemists and technologists, while also offering advanced methodological sections for statisticians and chemometrics specialists.…

Hardback. Condition: New. Multiblock Data Fusion in Statistics and Machine Learning Explore the advantages and shortcomings of various forms of multiblock analysis, and the relationships between them, with this expert guide Arising out of fusion problems that exist in a variety of fields in the natural and life sciences, the methods available to fuse multiple data sets have expanded dramatically in recent years. Older methods, rooted in psychometrics and chemometrics, also exist. Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is a detailed overview of all relevant multiblock data analysis methods for fusing multiple data sets. It focuses on methods based on components and latent variables, including both well-known and lesser-known methods with potential applications in different types of problems. Many of the included methods are illustrated by practical examples and are accompanied by a freely available R-package. The distinguished authors have created an accessible and useful guide to help readers fuse data, develop new data fusion models, discover how the involved algorithms and models work, and understand the advantages and shortcomings of various approaches. This book includes: A thorough introduction to the different options available for the fusion of multiple data sets, including methods originating in psychometrics and chemometricsPractical discussions of well-known and lesser-known methods with applications in a wide variety of data problemsIncluded, functional R-code for the application of many of the discussed methods Perfect for graduate students studying data analysis in the context of the natural and life sciences, including bioinformatics, sensometrics, and chemometrics, Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is also an indispensable resource for developers and users of the results of multiblock methods.…

Paperback. Condition: Very Good.