Your P-values are significant (or not), so what … now what?

Abstract

Abstract 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.