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Comment by peteradio | Hacker News Reader

The easiest data to fake is null results because anything else is replicable, hence the importance of replication.

null results are also replicable.

A null result, or the absence of evidence, is not evidence of absence. If you fake a null result, you’re not asserting anything other than you could not measure and collect supporting data using your experiment to prove or disprove a hypothesis. It is difficult for someone doing replication to accuse you of ill-intent, as opposed to faked data that proves your point when anyone else can replicate your experiment and get totally different or even contradictory results.

You still have to give out the statistics that show the null result. E.g. something with a high p-value. You are in fact "confirming the null hypothesis". They aren't any more difficult to replicate than results supporting "the alternative hypothesis".

(The whole binary hypothesis system and culture is a mess though, but that's besides the point.)

This is true.

However, I think that no one will do the scut work necessary to find that a null result was faked, and even if they do since you the researcher got very little status out of it then it’s believable that you made a mistake, and didn’t falsify data.

Probably not, especially as null results are almost impossible to publish (which is mad).

But you won't find null results in a journal, so problem solved.

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