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How to avoid over‑interpreting statistically marginal experimental results
Method Help
It is tempting to draw strong conclusions from borderline‑significant experimental outcomes. Over‑interpretation of weak statistics remains a pervasive problem across many disciplines. What practical habits help you stay disciplined?
Luna, Madelyn and 7 others5 Comments-
Pre‑register your analysis plan whenever possible before you look at experimental outputs.
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Do not treat p‑values as sharp binary pass‑fail cutoffs.
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Always report effect size alongside significance metrics.
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Run replication experiments before building major arguments on marginal results.
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Explicitly discuss limitation when results sit at statistical boundaries.
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