Statistical significance, or lack thereof, is often erroneously interpreted as a measure of the magnitude of effects, correlations between variables or practical relevance of research results. However, calculated P-values do not provide any information of this sort. Alternatively, effect sizes as measured by effect size indices provide complementary information to results of statistical hypothesis testing that is crucial and necessary to fully interpret data and then draw meaningful conclusions. Effect size indices have been used extensively for decades in the medical, psychological and social sciences but have received scant attention in the plant sciences. This Technical Update focuses on (1) raising awareness of these important statistical tools for seed science research, (2) providing additional resources useful for incorporating effect sizes into research programmes and (3) encouraging further applications of these tools in our discipline.

中文翻译：

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您的 P 值显着（或不显着），那么……现在怎么办？

统计显着性或缺乏统计显着性常常被错误地解释为对影响大小、变量之间的相关性或研究结果的实际相关性的衡量。然而，计算磷-values 不提供任何此类信息。或者，通过效应大小指数测量的效应大小为统计假设检验的结果提供补充信息，这对于充分解释数据并得出有意义的结论至关重要且必要。效应量指数已在医学、心理和社会科学领域广泛使用了数十年，但在植物科学领域却很少受到关注。本技术更新的重点是 (1) 提高对种子科学研究这些重要统计工具的认识，(2) 提供有助于将效应量纳入研究计划的额外资源，以及 (3) 鼓励这些工具在我们的学科中进一步应用。