在食品研究中使用零假设和P值测试显著性的问题和替代方案
1Jeungpyeong-gun, 27909 Chungbuk Republic of Korea Department of Food Science and Technology, Korea National University of Transportation.
Food science and biotechnology
|June 26, 2023
概括
在食品研究中,零假设显著性测试 (NHST) 和P值方法存在局限性. 置信区间,效果大小和贝叶斯统计学为数据分析提供了优越的替代方案.
科学领域:
- 食品科学 食品科学 食品科学
- 统计分析 统计分析
背景情况:
- 零假设显著性测试 (NHST) 和P值是食品研究中使用的传统统计方法.
- 已经确定了与NHST和P值测试相关的担忧和局限性.
研究的目的:
- 讨论食品研究中传统统计测试的局限性.
- 引入和评估食品研究的替代统计方法.
主要方法:
- 对食品研究中的统计测试方法的审查.
- 探索包括信心区间 (CI),效果大小和贝叶斯统计学在内的替代方案.
主要成果:
- 置信区间 (CI) 估计效应的大小和统计学意义.
- 效果大小量化了用于比较结果的差异程度.
- 贝叶斯统计学允许使用有限数据进行预测.
结论:
- 置信区间 (CI),效果大小和贝叶斯统计数据可以补充或取代食品研究中的NHST和P值测试.
- 这些先进的方法提供了更全面的数据解释.
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