Look, what you’ve written above is based on misunderstanding how an F-test works. I’ve already explained repeatedly why what you’re saying here, which is the same thing you’ve said each time before, is not correct.
This study contains a failure of an F-test. Because of how the F-test is structured, failure of an F-test to prove forall X P(X), is not inductive evidence, nor evidence of any kind at all, that P(X) is false for most X.
I will try to be more polite, but you need to a) read the study, and b) learn how an F-test works, before you can talk about this. But I just don’t understand why you keep making confident assertions about a study you haven’t read, using a test you don’t understand.
The F-test is especially tricky, because you know you’re going to find some difference between the groups. What difference D would you expect to find if there is in fact no effect? That’s a really hard question, and the F-test dodges it by using the arbitrary but standard 95% confidence interval to pick a higher threshold, F. Results between D and F would still support the hypothesis that there is an effect, while results below D would be evidence against that hypothesis. Not knowing what D is, we can’t say whether failure of an F-test is evidence for or against a hypothesis.
And I’ve repeatedly told you that you should’ve focused your critique on this instead of ranting about deduction. The last time I said it, you claimed the following:
There is nothing statistically wrong with the paper.
Now to answer your question:
But I just don’t understand why you keep making confident assertions about a study you haven’t read,
I haven’t been discussing this study, I’ve been trying to help you understand why your critique of it has been misguided.
using a test you don’t understand.
As for this claim you undoubtedly have an interesting “proof” for, I’ve simply avoided confusing you further with a discussion of statistics until you realized the following:
All statistical conclusions are deductively wrong.
A statistical study must be critiqued for it’s misuse of statistics (and obviously, then you must first claim that there is something statistically wrong with the paper).
Look, what you’ve written above is based on misunderstanding how an F-test works. I’ve already explained repeatedly why what you’re saying here, which is the same thing you’ve said each time before, is not correct.
This study contains a failure of an F-test. Because of how the F-test is structured, failure of an F-test to prove forall X P(X), is not inductive evidence, nor evidence of any kind at all, that P(X) is false for most X.
I will try to be more polite, but you need to a) read the study, and b) learn how an F-test works, before you can talk about this. But I just don’t understand why you keep making confident assertions about a study you haven’t read, using a test you don’t understand.
The F-test is especially tricky, because you know you’re going to find some difference between the groups. What difference D would you expect to find if there is in fact no effect? That’s a really hard question, and the F-test dodges it by using the arbitrary but standard 95% confidence interval to pick a higher threshold, F. Results between D and F would still support the hypothesis that there is an effect, while results below D would be evidence against that hypothesis. Not knowing what D is, we can’t say whether failure of an F-test is evidence for or against a hypothesis.
And I’ve repeatedly told you that you should’ve focused your critique on this instead of ranting about deduction. The last time I said it, you claimed the following:
Now to answer your question:
I haven’t been discussing this study, I’ve been trying to help you understand why your critique of it has been misguided.
As for this claim you undoubtedly have an interesting “proof” for, I’ve simply avoided confusing you further with a discussion of statistics until you realized the following:
All statistical conclusions are deductively wrong.
A statistical study must be critiqued for it’s misuse of statistics (and obviously, then you must first claim that there is something statistically wrong with the paper).