A significant concern regarding data analysis in group research is that focusing exclusively on group means can be highly misleading because it obscures important individual differences. For example, if a treatment produces a strong positive effect on half of the participants and an equally strong negative effect on the other half, these opposing effects will statistically cancel each other out in a traditional between-subjects experiment. As a result, the treatment group's mean will appear identical to the control group's mean, falsely implying that the intervention had no effect when it actually impacted every single participant.