Download or read book Mathematical and Statistical Methods in Food Science and Technology written by Daniel Granato and published by John Wiley & Sons. This book was released on 2014-03-03 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mathematical and Statistical Methods in Food Science and Technology written by Daniel Ed Granato and published by . This book was released on 2017 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical and Statistical Applications in Food Engineering written by Surajbhan Sevda and published by CRC Press. This book was released on 2020-01-30 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by experts from all over the world, the book comprises the latest applications of mathematical and models in food engineering and fermentation. It provides the fundamentals on statistical methods to solve standard problems associated with food engineering and fermentation technology. Combining theory with a practical, hands-on approach, this book covers key aspects of food engineering. Presenting cuttingedge information, the book is an essential reference on the fundamental concepts associated with food engineering.

Download or read book Statistical Methods for Food Science written by John A. Bower and published by John Wiley & Sons. This book was released on 2013-09-23 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistics in Food Science and Nutrition written by Are Hugo Pripp and published by Springer Science & Business Media. This book was released on 2012-09-10 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. ​

Download or read book Easy Statistics for Food Science with R written by Abbas F. M. Alkarkhi and published by Academic Press. This book was released on 2018-09-18 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. Contains numerous step-by-step tutorials help the reader to learn quickly Covers the theory and application of the statistical techniques Shows how to analyze data using R software Provides R scripts for all examples and figures

Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

Download or read book Computer Applications in Food Technology written by R. Paul Singh and published by Elsevier. This book was released on 1996-08-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Institute of Food Technologists (IFT) recently endorsed the use of computers in food science education. The minimum standards for degrees in food science, as suggested by IFT,"require the students to use computers in the solution of problems, the collection and analysis of data, the control processes, in addition to word processing."Because they are widely used in business, allow statistical and graphical of experimental data, and can mimic laboratory experimentation, spreadsheets provide an ideal tool for learning the important features of computers and programming. In addition, they are ideally suited for food science students, who usually do not have an extensive mathematical background. Drawing from the many courses he has taught at UC Davis, Dr. Singh covers the general basics of spreadsheets using examples specific to food science. He includes more than 50 solved problems drawn from key areas of food science, namely food microbiology, food chemistry, sensory evaluation, statistical quality control, and food engineering. Each problem is presented with the required equations and detailed steps necessary for programming the spreadsheet. Helpful hints in using the spreadsheets are also provided throughout the text. Key Features * The first book to integrate speadsheets in teaching food science and technology * Includes more than 50 solved examples of spreadsheet use in food science and engineering * Presents a step-by-step introduction to spreadsheet use * Provides a food composition database on a computer disk

Download or read book Food Product Design written by Ruguo Hu and published by Routledge. This book was released on 2017-10-19 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical experimental design is currently used as a quality control technique to achieve product excellence at the lowest overall cost. It can also function as a powerful tool to optimize food products and/or processes, to accelerate food development cycles, reduce research costs, facilitate the transition of products from research and development to manufacturing and troubleshoot manufacturing problems. Food Product Design: A Computer-Aided Statistical Approach familiarizes readers with the methodology of statistical experimental design, and its application in food product design, with the aid of commonly available modern commercial software. Food Product Design presents basic concepts of food product design, then focuses on the most effective statistical techniques and corresponding computer applications for trial design, modeling, and experimental data analysis. The book presents very few theories about mathematics and statistics. Instead, it contains detailed descriptions of how to use popular computer software to solve the real mathematical and statistical problems that occur in product design. Even those with very limited knowledge of statistics and mathematics will find this a useful and highly practical book. Food Product Design: A Computer-Aided Statistical Approach will be a valuable tool for professional food engineers, technologists, scientists, and industrial personnel who want to update and expand their knowledge about computer-aided statistical methods in the field of food product design. Those involved in applied research at universities in food and agriculture, biological and chemical engineering, and statistics will also find it useful and informative.

Download or read book Statistical Methods for Food Science written by John A. Bower and published by John Wiley & Sons. This book was released on 2009-11-09 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistical Procedures for Agricultural Research written by Kwanchai A. Gomez and published by John Wiley & Sons. This book was released on 1984-02-17 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here in one easy-to-understand volume are the statistical procedures and techniques the agricultural researcher needs to know in order to design, implement, analyze, and interpret the results of most experiments with crops. Designed specifically for the non-statistician, this valuable guide focuses on the practical problems of the field researcher. Throughout, it emphasizes the use of statistics as a tool of research—one that will help pinpoint research problems and select remedial measures. Whenever possible, mathematical formulations and statistical jargon are avoided. Originally published by the International Rice Research Institute, this widely respected guide has been totally updated and much expanded in this Second Edition. It now features new chapters on the analysis of multi-observation data and experiments conducted over time and space. Also included is a chapter on experiments in farmers' fields, a subject of major concern in developing countries where agricultural research is commonly conducted outside experiment stations. Statistical Procedures for Agricultural Research, Second Edition will prove equally useful to students and professional researchers in all agricultural and biological disciplines. A wealth of examples of actual experiments help readers to choose the statistical method best suited for their needs, and enable even the most complicated procedures to be easily understood and directly applied. An International Rice Research Institute Book

Download or read book Statistical Methods in Food and Consumer Research written by Maximo C. Gacula Jr. and published by Academic Press. This book was released on 2008-12-01 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods in Food and Consumer Research, Second Edition, continues to be the only book to focus solely on the statistical techniques used in sensory testing of foods, pharmaceuticals, cosmetics, and other consumer products. This new edition includes the most recent applications of statistical methods, and features significant updates as well as two new chapters. Covering the application of techniques including R-index, the Bayesian approach for sensory differences tests, and preference mapping in addition to several other methodologies, this is the comprehensive reference needed by those studying sensory evaluation and applied statistics in agriculture and biological sciences. Research professionals working with food, beverages, healthcare, cosmetics, and other related areas will find the book a valuable guide to the variety of statistical methods available. Provides comprehensive coverage of statistical techniques in sensory testing Includes data compiled from real-world experiments Covers the latest in data interpretation and analysis Addresses key methods such as R-index, Thursonian Discriminal Distances, group sequential tests, beta-binomial tests, sensory difference and similarity tests, just-about-right data, signal-to-noise ratio, analysis of cosmetic data, Descriptive Analysis, claims substantiation and preference mapping

Download or read book Federal Statistics Multiple Data Sources and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Download or read book Nonparametric Statistics with Applications to Science and Engineering written by Paul H. Kvam and published by John Wiley & Sons. This book was released on 2007-08-24 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.

Download or read book Statistical Method from the Viewpoint of Quality Control written by Walter A. Shewhart and published by Courier Corporation. This book was released on 2012-07-31 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Important text offers lucid explanation of how to regulate variables and maintain control over statistics in order to achieve quality control over manufactured products, crops and data. First inexpensive paperback edition.

Download or read book Common Statistical Methods for Clinical Research with SAS Examples Third Edition written by Glenn Walker and published by SAS Institute. This book was released on 2010-02-15 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data. Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place. This book is part of the SAS Press program.