Problems and alternatives of testing significance using null hypothesis and P-value in food research

A testing method to identify statistically significant differences by comparing the significance level and the probability value based on the Null Hypothesis Significance Test (NHST) has been used in food research. However, problems with this testing method have been discussed. Several alternatives...

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Bibliographic Details
Published in:Food science and biotechnology 2023-10, Vol.32 (11), p.1479-1487
Main Author: Choi, Won-Seok
Format: Article
Language:English
Subjects:
Bayesian analysis
Chemistry
Chemistry and Materials Science
Confidence intervals
Food
Food Science
Identification methods
Null hypothesis
Nutrition
Review
Statistical analysis
Statistical significance
Statistical tests
Statistics
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Summary:A testing method to identify statistically significant differences by comparing the significance level and the probability value based on the Null Hypothesis Significance Test (NHST) has been used in food research. However, problems with this testing method have been discussed. Several alternatives to the NHST and the P -value test methods have been proposed including lowering the P -value threshold and using confidence interval (CI), effect size, and Bayesian statistics. The CI estimates the extent of the effect or difference and determines the presence or absence of statistical significance. The effect size index determines the degree of effect difference and allows for the comparison of various statistical results. Bayesian statistics enable predictions to be made even when only a small amount of data is available. In conclusion, CI, effect size, and Bayesian statistics can complement or replace traditional statistical tests in food research by replacing the use of NHST and P -value.
ISSN:1226-7708
2092-6456
DOI:10.1007/s10068-023-01348-4