yamapikariya@lemmyfi.com
on 29 Aug 2024 16:26
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What?
demonmittenhands@lemmy.world
on 29 Aug 2024 17:10
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Smol p.
tacosanonymous@lemm.ee
on 29 Aug 2024 17:15
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The “p value” is a number, calculated from a statistical test, that describes how likely you are to have found a particular set of observations if the null hypothesis were true.
P values are used in hypothesis testing to help decide whether to reject the null hypothesis. The smaller the *p *value, the more likely you are to reject the null hypothesis.
Adding onto this. p < 0.05 is the somewhat arbitrary standard that many journals have for being able to publish a result at all.
Is you do an experiment to see we whether X affects Y, and get a p = 0.05, you can say, “Either X affects Y, or it doesn’t and an unlikely fluke event occurred during this experiment that had a 1 in 20 chance.”
Usually, this kind of thing is publishable, but we’ve decided we don’t want to read the paper if that number gets any higher than 1 in 20. No one wants to read the article on, “We failed to determine whether X has an effect on Y or not.”
MindTraveller@lemmy.ca
on 30 Aug 2024 00:40
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That’s a shame. Negative results are very important to the process.
Tlaloc_Temporal@lemmy.ca
on 31 Aug 2024 07:57
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Especially considering that PDFs can be just a few Mb, and I doubt people will care if they’re not cached locally.
Which is sad because a lot of science is just ruling things out. We should still publish papers that say that if we do an experiment with too small of a sample, we get an inconclusive result, because that starts to put bounds on how strongly a thing gets affected, if an effect occurs at all.
salvaria@lemmy.blahaj.zone
on 29 Aug 2024 18:17
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If the p is low, drop the h0
MindTraveller@lemmy.ca
on 30 Aug 2024 00:39
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That old man is a slave owner
GissaMittJobb@lemmy.ml
on 30 Aug 2024 03:56
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I hate statistical rigour, I want everything to be vibes-based instead
threaded - newest
What?
Smol p.
The “p value” is a number, calculated from a statistical test, that describes how likely you are to have found a particular set of observations if the null hypothesis were true.
P values are used in hypothesis testing to help decide whether to reject the null hypothesis. The smaller the *p *value, the more likely you are to reject the null hypothesis.
Adding onto this. p < 0.05 is the somewhat arbitrary standard that many journals have for being able to publish a result at all.
Is you do an experiment to see we whether X affects Y, and get a p = 0.05, you can say, “Either X affects Y, or it doesn’t and an unlikely fluke event occurred during this experiment that had a 1 in 20 chance.”
Usually, this kind of thing is publishable, but we’ve decided we don’t want to read the paper if that number gets any higher than 1 in 20. No one wants to read the article on, “We failed to determine whether X has an effect on Y or not.”
That’s a shame. Negative results are very important to the process.
Especially considering that PDFs can be just a few Mb, and I doubt people will care if they’re not cached locally.
Which is sad because a lot of science is just ruling things out. We should still publish papers that say that if we do an experiment with too small of a sample, we get an inconclusive result, because that starts to put bounds on how strongly a thing gets affected, if an effect occurs at all.
If the p is low, drop the h0
That old man is a slave owner
I hate statistical rigour, I want everything to be vibes-based instead