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Image of - Statistics in Food Science and Nutrition | Paperback
Statistics in Food Science and Nutrition | Paperback

Statistics in Food Science and Nutrition | Paperback

by Pripp

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.  ‹

Highlights

  • binding-icon

    9781461450092

    ISBN:

  • binding-icon

    Pripp

    Author:

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    N/A

    Pages:

  • binding-icon

    210 gm

    Weight:

  • langauage-icon

    English

    Language:

  • date-icon

    2013

    Year:

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    N/A

    Edition:

  • binding-icon

    Paperback

    Binding:

₹5254

₹6567

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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