[MITSardine]

Is that actually a null result though? That sounds like a standard positive result: "We managed to show that minimum wage has no effect on employment rate".

A null result would have been: "We tried to apply Famous Theory to showing that minimum wage has no effect on employment rate but we failed because this and that".

[roenxi]

Looking at the definition in the article, it definitely is a null result. However the example does illustrate that 'a null result' probably isn't a very interesting thing to talk about because it covers too many types of result. I think what people on HN actually want to track is something more like 'a boring null result'. The real question is whether there a process that is reliably being followed and leading to research that matches reality (where a statistically significant result suggests something is real) or is scientific publishing highly biased towards odd results (where studies that muck up or get lucky with statistical noise are over-represented).

In this case we would expect some studies of the minimum wage to show it increases employment regardless of what the effect of wage rises is in the general case - eg, some official raised the minimum wage while a sector went into a boom for unrelated and coincidental reasons.

[iamjfu]

From a related nature article (https://www.nature.com/articles/d41586-024-02383-9), "null or negative results — those that fail to find a relationship between variables or groups, or that go against the preconceived hypothesis." According to this definition, I think both examples you provided are null results. Particularly here, where the context is the file drawer problem.

[Analemma_]

No, because in theory a minimum wage increase could decrease the unemployment rate. If it does neither, that’s a null result.

[mitthrowaway2]

That's sort of like saying "I measured acceleration due to gravity by dropping a bowling ball off the Tower of Pisa, and got a null result: the ball simply hovered in midair."

If the result is very surprising and contradicts established theory, I wouldn't consider it a null result, even if some parameter numerically measures as zero.

[Analemma_]

The question being asked is, "what is the correlation between these two variables": is it positive, negative, or zero (null). The null hypothesis is the baseline you start from because the overwhelming majority of variables from physical observations are uncorrelated (e.g. what is the correlation between "how many people in the treatment group of this clinical trial made a full recovery" and "the price of eggs in Slovakia").

Measurements of some physical quantity are a different kind of experiment, you cannot phrase it as a question about the correlation between two variables. Instead you take measurements and put error bars on them (unless what you're measuring is an indirect proxy for the actual quantity, in which case the null hypothesis and p-value testing does become relevant again).

[mitthrowaway2]

In fact, you can express measurement of g as a linear correlation between y-y0 and (t-t0)^0.5.

[im3w1l]

Null means nothing, zero. In the context of scientific articles a null result means that the difference is zero. What difference? Well it depends. It could be difference between doing something and not doing it. The difference between before and after some intervention. Or perhaps the difference between two different actions.

In this case the difference between before and after raising the minimum wage.

Furthermore, the thing with a null result is that it's always dependant on how sensitive your study is. A null result is always of the form "we can't rule out that it's 0". If the study is powerful then a null result will rule out a large difference, but there is always the possibility that there is a difference too small to detect.

[ktallett]

Null means something doesn't exist and proving something doesn't exist can at times especially in certain sciences be as valuable as proving something does exist. Especially if it stops the rest of the field chasing the pot of gold at the end of the rainbow.

[jruohonen]

> Is that actually a null result though?

The above is a good point but I would extend it further. I mean, philosophically, you get a positive result from a negative (null) result by merely changing your hypotheses (e.g., something should not cause something else).

[tempusalaria]

if you are p testing this isn’t the case. A positive result is a much stronger assertion

[jruohonen]

Sure and of course you shouldn't change your hypotheses. That's kind of the whole purpose of pre-registrations at a meta-level of things.