Statistics in Food Science and Nutrition
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.  ​
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Statistics in Food Science and Nutrition
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.  ​
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Statistics in Food Science and Nutrition

Statistics in Food Science and Nutrition

by Are Hugo Pripp
Statistics in Food Science and Nutrition

Statistics in Food Science and Nutrition

by Are Hugo Pripp

Paperback(2013)

$69.99 
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Overview

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.  ​

Product Details

ISBN-13: 9781461450092
Publisher: Springer New York
Publication date: 09/10/2012
Series: SpringerBriefs in Food, Health, and Nutrition
Edition description: 2013
Pages: 66
Product dimensions: 6.10(w) x 9.25(h) x 0.01(d)

Table of Contents

1. Statistics in Food Science and Nutrition.- 2. Methods and Principles of Statistical Analysis.- 3. Applying Statistics to Food Quality.- 4. Nutritional Epidemiology and Health Effects of Foods.- 5. Applications of Mutlivariate Analysis.​
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