Many statistical innovations are linked to applications in food science. For example, the student t-test (a statistical method) was developed to monitor the quality of stout at the Guinness Brewery and multivariate statistical methods are applied widely in the spectroscopic analysis of foods. Nevertheless, statistical methods are most often associated with engineering, mathematics, and the medical sciences, and are rarely thought to be driven by food science. Consequently, there is a dearth of statistical methods aimed specifically at food science, forcing researchers to utilize methods intended for other disciplines. The objective of this Brief will be to highlight the most needed and relevant statistical methods in food science and thus eliminate the need to learn about these methods from other fields. All methods and their applications will be illustrated with examples from research literature. ​

Many statistical innovations are linked to applications in food science. For example, the student t-test (a statistical method) was developed to monitor the quality of stout at the Guinness Brewery and multivariate statistical methods are applied widely in the spectroscopic analysis of foods. Nevertheless, statistical methods are most often associated with engineering, mathematics, and the medical sciences, and are rarely thought to be driven by food science. Consequently, there is a dearth of statistical methods aimed specifically at food science, forcing researchers to utilize methods intended for other disciplines. The objective of this Brief will be to highlight the most needed and relevant statistical methods in food science and thus eliminate the need to learn about these methods from other fields. All methods and their applications will be illustrated with examples from research literature. ​

Mathematical and Statistical Approaches in Food Science and Technology offers an accessible guide to applying statistical and mathematical technologies in the food science field whilst also addressing the theoretical foundations. Using clear examples and case-studies by way of practical illustration, the book is more than just a theoretical guide for non-statisticians, and may therefore be used by scientists, students and food industry professionals at different levels and with varying degrees of statistical skill.

Food Security, Poverty and Nutrition Analysis provides essential insights into the evaluative techniques necessary for creating appropriate and effective policies and programs to address these worldwide issues. Food scientists and nutritionists will use this important information, presented in a conceptual framework and through case studies for exploring representative problems, identifying and implementing appropriate methods of measurement and analysis, understanding examples of policy applications, and gaining valuable insight into the multidisciplinary requirements of successful implementation.This book provides core information in a format that provides not only the concept behind the method, but real-world applications giving the reader valuable, practical knowledge.* Identify proper analysis method, apply to available data, develop appropriate policy* Demonstrates analytical techniques using real-world scenario application to illustrate approaches for accurate evaluation improving understanding of practical application development* Tests reader comprehension of the statistical and analytical understanding vital to the creation of solutions for food insecurity, malnutrition and poverty-related nutrition issues using hands-on exercises

Analysis in Nutrition Research: Principles of Statistical Methodology and Interpretation of the Results describes, in a comprehensive manner, the methodologies of quantitative analysis of data originating specifically from nutrition studies. The book summarizes various study designs in nutrition research, research hypotheses, the proper management of dietary data, and analytical methodologies, with a specific focus on how to interpret the results of any given study. In addition, it provides a comprehensive overview of the methodologies used in study design and the management and analysis of collected data, paying particular attention to all of the available, modern methodologies and techniques. Users will find an overview of the recent challenges and debates in the field of nutrition research that will define major research hypotheses for research in the next ten years. Nutrition scientists, researchers and undergraduate and postgraduate students will benefit from this thorough publication on the topic. - Provides a comprehensive presentation of the various study designs applied in nutrition research - Contains a parallel description of statistical methodologies used for each study design - Presents data management methodologies used specifically in nutrition research - Describes methodologies using both a theoretical and applied approach - Illustrates modern techniques in dietary pattern analysis - Summarizes current topics in the field of nutrition research that will define major research hypotheses for research in the next ten years

Statistics in Nutrition and Dietetics is a clear and accessible volume introducing the basic concepts of the scientific method, statistical analysis, and research in the context of the increasingly evidence-based field of nutrition and dietetics. Focusing on quantitative analysis and drawing on short, practical exercises and real-world examples, this reader-friendly textbook helps students understand samples, principles of measurement, confidence intervals, the theoretical basis and practical application of statistical tests, and more. Includes numerous examples and exercises that demonstrate how to compute the relevant outcome measures for a variety of tests, both by hand and using SPSS Provides access to online resources, including analysis-ready data sets, flow charts, further readings and a range of instructor materials such as PowerPoint slides and lecture notes Ideal for demystifying statistical analysis for undergraduate and postgraduate students

The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This book provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level.

The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This second edition of Statistical Methods for Food Science provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands-on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level. This revised and updated second edition is accompanied by a new companion website giving the reader access to the datasets and Excel spreadsheets featured in the book. Check it out now by visiting www.wiley.com/go/bower/statistical or by scanning the QR code below.

From gluten-free to all-Paleo, GMOs to grass-fed beef, our newsfeeds abound with nutrition advice. Whether sensational headlines from the latest study or anecdotes from celebrities and food bloggers, we're bombarded with "superfoods" and "best ever" diets promising to help us lose weight, fight disease, and live longer. At the same time, we live in an over-crowded food environment that makes it easy to eat, all the time. The result is an epidemic of chronic disease amidst a culture of nutrition confusion-and copious food choices that challenge everyday eaters just trying to get a healthy meal on the table. But the exhilarating truth is that scientists know an astounding amount about the power of food. A staggering 80% of chronic diseases are preventable through modifiable lifestyle changes, and diet is the single largest contributing factor. And we also know the secrets to eating sustainably to protect our planet. In Food & Nutrition, Harvard- and Columbia-trained nutrition scientist Dr. P.K. Newby examines 134 stand-alone questions addressing "need to know" topics, including how what we eat affects our health and environment, from farm to fork, and why, when it comes to diet, the whole is greater than the sum of its parts-and one size doesn't fit all. At the same time, Newby debunks popular myths and food folklore, encouraging readers to "learn, unlearn, and relearn" the fundamentals of nutrition at the heart of a health-giving diet. Her passion for all things food shines through it all, as does her love of the power of science, technology, and engineering to help create healthier diets for ourselves, and a more sustainable future for the planet we share.

This volume provides students with the knowledge and training they need to undertake practical investigations within food science and nutrition covering relevant aspects of nutrition, biology, chemistry, biochemistry, communication and consultation.