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One Big Question
Rewrite your study to ask a single, modelable question. If you hear yourself listing pairwise comparisons, you need ANOVA or a planned-contrast design.
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Define “Meaningful” First
Pick the smallest effect worth acting on. Decisions beat declarations; a tiny, “significant” blip may be operationally irrelevant.
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Visual First Pass
Plot group distributions and intervals. If the picture disagrees with the p-value, investigate the model, not the plot.
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Pre-Commit Your Forks
List the few follow-ups you’d run if the omnibus test is significant. Curiosity is good… pre-planned curiosity is better.
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Calibrate Error
State your alpha and your multiple-comparison plan. If you test more, protect more.
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Report Size and Uncertainty
Always pair effects (η², Cohen’s d, Cramer’s V) with confidence intervals. Magnitude plus bounds beats stars on a table.
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Separate Signal from Story
Ask: does the design support the causal interpretation you’re tempted to make? If not, write the modest story.
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Decision Sentence
Close with a commitment: “If the effect is at least M, we’ll implement Z; otherwise we’ll do Q.” Statistics serve choices, it’s not just numbers.