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Titlebook: Statistics in Food Science and Nutrition; Are Hugo Pripp Book 2013 Springer Science+Business Media New York 2013 applied statistics.epidem

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Statistics in Food Science and Nutrition,est are classic examples. A fundamental knowledge of statistical analysis and study design is more important than ever, especially for investigating the relationship between food habits, health, and lifestyle.
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Applying Statistics to Food Quality,e term Six Sigma has its roots in statistical theory and the spread of data. Statistical methods are also fundamental to the assessment of results from sensory analysis. Shelf life and product quality can use many of the statistical methods from time-to-event analysis developed in medical statistics.
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Application of Multivariate Analysis: Benefits and Pitfalls, used in biostatistics. The interpretation of results, especially in relation to the original variables, might be challenging, which could represent these methods’ weakest link from an applied point of view.
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Book 2013nded 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 have come about from applied problems in food science. “The lady tasting tea” experiment and the relationship between Guinness and the .-test are classic examples. A fundamental knowledge of statistical analysis and study design is more important than ever, especially for investigating t
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Nutritional Epidemiology and Health Effects of Foods,ing clinical and epidemiological research. Important study designs are outlined with special emphasis on case-control, cohort, and intervention studies. Multiple regression models are important in epidemiological studies. However, interpretation depends on a fundamental knowledge of exposure, confou
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