Re:$5 device accurately tests for breast cancer in under 5 s...
by hn_throwaway_99 on Friday February 16, 2024 @03:03PM
(#39402225)
> To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?
This is the point that you are fundamentally misunderstanding. Nobody is making the argument that "21 is such a perfect number in this case". The rest of your sentences ("Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?") seem to point to a belief that people are pulling numbers based on a finger in the wind.
The whole point of (a lot of) statistical testing is that it allows you to come up with a specific number that determines how likely a particular result is due to chance. That is what the p < .05 "standard" is about - it's a determination that the results have less than a 5% likelihood to be due to random chance (though that 5% number used as "significant" is just basically pulled out of thin air, and p-hacking is another topic...) That is, I and the comment I replied to aren't making the argument that 21 "is such a perfect number". We're making the argument that even with a small sample size it's possible to determine the relative error bars, with precision, using statistical methods, not just pulling a number based on feels. Yes, larger sample sizes reduce the size of those error bars. But often not in ways that are "intuitive". You have to do the math.
None of what I wrote above is meant to imply that statistical tests can't be misused, or that they often require assumptions about the underlying population distribution that may not be correct.
This is the point that you are fundamentally misunderstanding. Nobody is making the argument that "21 is such a perfect number in this case". The rest of your sentences ("Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?") seem to point to a belief that people are pulling numbers based on a finger in the wind.
The whole point of (a lot of) statistical testing is that it allows you to come up with a specific number that determines how likely a particular result is due to chance. That is what the p < .05 "standard" is about - it's a determination that the results have less than a 5% likelihood to be due to random chance (though that 5% number used as "significant" is just basically pulled out of thin air, and p-hacking is another topic...) That is, I and the comment I replied to aren't making the argument that 21 "is such a perfect number". We're making the argument that even with a small sample size it's possible to determine the relative error bars, with precision, using statistical methods, not just pulling a number based on feels. Yes, larger sample sizes reduce the size of those error bars. But often not in ways that are "intuitive". You have to do the math.
None of what I wrote above is meant to imply that statistical tests can't be misused, or that they often require assumptions about the underlying population distribution that may not be correct.