Statistics in Food Science and Nutrition

1. Front Matter

   Pages i-viii

   PDF

2. Statistics in Food Science and Nutrition

   • Are Hugo Pripp

   Pages 1-5

3. Methods and Principles of Statistical Analysis

   • Are Hugo Pripp

   Pages 7-23

4. Applying Statistics to Food Quality

   • Are Hugo Pripp

   Pages 25-39

5. Nutritional Epidemiology and Health Effects of Foods

   • Are Hugo Pripp

   Pages 41-51

6. Application of Multivariate Analysis: Benefits and Pitfalls

   • Are Hugo Pripp

   Pages 53-64

7. Statistics in Food Science and Nutrition

   • Are Hugo Pripp

   Pages E1-E1

8. Back Matter

   Pages 65-66

   PDF

  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.  ​  

• applied statistics
• epidemiology
• food science
• health
• nutrition

• Oslo, Norway

  Are Hugo Pripp

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