Statistics in Food Science and Nutrition

Nonfiction, Science & Nature, Technology, Food Industry & Science, Science, Biological Sciences
Cover of the book Statistics in Food Science and Nutrition by Are Hugo Pripp, Springer New York
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Author: Are Hugo Pripp ISBN: 9781461450108
Publisher: Springer New York Publication: September 13, 2012
Imprint: Springer Language: English
Author: Are Hugo Pripp
ISBN: 9781461450108
Publisher: Springer New York
Publication: September 13, 2012
Imprint: Springer
Language: English

  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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  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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