Statistics in Food Science and Nutrition [electronic resource] /by Are Hugo Pripp.
by Pripp, Are Hugo [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Food, Health, and Nutrition: Publisher: New York, NY : Springer New York : 2013.Description: VIII, 66 p. 15 illus., 3 illus. in color. online resource.ISBN: 9781461450108.Subject(s): Chemistry | Food science | Nutrition | Statistical methods | Statistics | Chemistry | Food Science | Biostatistics | Nutrition | Statistics for Life Sciences, Medicine, Health SciencesDDC classification: 641.3 | 664 Online resources: Click here to access online
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Springer eBooksSummary: 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.
| Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available | 128244 | ||
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available | 128245 | ||
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available | 128243 | ||
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available | 128246 | ||
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available | 128247 | ||
| Long Loan | MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available |
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| TP 248.65 .C55 L48 2021 Effects of garlic and onion extract chitosan nanoparticles on performance of rainbow rooster chicken in KENYA | TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 B638 2010 Biotechnology in functional foods and nutraceuticals / |
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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