John Kenny
Addicted to Fun and Learning
- Joined
- Mar 25, 2016
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There seems to be a great confusion about ABX tests here
It's a test for differences
The null hypothesis is that there is no difference
A statistical significant result that rejects the null hypothesis is proof that a difference exists
Failure to reject the null hypothesis does not prove the null hypothesis
It's an interesting twist that I'm getting criticised for citing statistically significant positive ABX test results that prove there is a difference?
And being also asked if I ignore null results when I was sure that null results are of no meaning?
It seems to me a very confused attitude coming from supporters of ABX testing.
From Wiki
It's a test for differences
The null hypothesis is that there is no difference
A statistical significant result that rejects the null hypothesis is proof that a difference exists
Failure to reject the null hypothesis does not prove the null hypothesis
It's an interesting twist that I'm getting criticised for citing statistically significant positive ABX test results that prove there is a difference?
And being also asked if I ignore null results when I was sure that null results are of no meaning?
It seems to me a very confused attitude coming from supporters of ABX testing.
From Wiki
An ABX test is a method of comparing two choices of sensory stimuli to identify detectable differences between them. A subject is presented with two known samples (sample A, the first reference, and sample B, the second reference) followed by one unknown sample X that is randomly selected from either A or B. The subject is then required to identify X as either A or B. If X cannot be identified reliably with a low p-value in a predetermined number of trials, then the null hypothesis cannot be rejected and it cannot be proven that there is a perceptible difference between A and B.
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