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Your drug works in wild-type mice and not in the knockout, so the effect depends on the gene. That conclusion does not follow, and in one major review of top journals, half the papers that needed the right test got it wrong. This two-way ANOVA interaction SOP runs the correct analysis in GraphPad Prism, from data entry to a reportable result, with a worked example in which the naive reading and the right answer disagree.

A small p-value tells you a difference is probably real, not that it's big enough to matter. Statistical significance asks whether an effect is distinguishable from noise; biological significance asks whether it's large enough to change a cell, a patient, or a conclusion. Because the p-value shrinks as your sample grows, a big enough study can stamp p < 0.05 on a difference that means nothing. Here's why, with real examples, and what to report instead: effect size and confide