In this article it is argued that one of the main problems in data analysis is an over-emphasis on statistical rather than substantive significance. Statistical significance reports the improbability of specific outcomes from sample data using a null hypothesis. In contrast, substantive significance is concerned with the real-world meaning of data modelling results for a population, regardless of p value, where an effect size estimator is used for evaluation. The argument presented in this article begins with a consideration of how substantive significance may be defined. Thereafter, there is a summary of the literature on substantive significance and its measurement using a variety of effect size estimators, many of which are little known to researchers. This article also examines the topics of economic and clinical significance. In the conclusion, this study discusses attempts to synthesise different concepts of substantive significance and recommends some practical usage of these concepts., Petr Soukup., and Obsahuje bibliografii