Abstract
PurposeThe purpose of this article is to show the gains that can be made if researchers were to use gain-probability (G-P) diagrams. Design/methodology/approachThe authors present relevant mathematical equations, invented examples and real data examples.FindingsG-P diagrams provide a more nuanced understanding of the data than typical summary statistics, effect sizes or significance tests.Practical implicationsGain-probability diagrams provided a much better basis for making decisions than typical summary statistics, effect sizes or significance tests.Originality/valueG-P diagrams provide a completely new way to traverse the distance from data to decision-making implications.
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