> And I disagree that the number of subjects doesn't matter. It matters enormously, precisely because this is a biology experiment.
It's ironic that you say this so definitively when you were the one asking for help interpreting the statistics originally.
Lisper is completely correct. Given a large enough effect size, detecting significant differences in a small population is very possible.
The statistics are sound. The assumption we should be questioning is where the subjects came from and if they are actually representative of the population that we are extrapolating this result to.
What Lisper said may be correct, however he really doesn't mention the application of the null-hypothesis in this experiment. To a skeptic it would seem the null hypothesis might be susceptible to the confusion of correlation and causation.
Edit:
The correct interpretation is that the model, the foundation of the null hypothesis, didn't fail yet.
Part of this model is backed by more experiments: "The reason that we focused on SWA is that it is the only sleep characteristic that reflects the depth of sleep" [1].
The model doesn't consist of a single variable. 11 people choosing the same 7 numbers out of 49 by chance is rather unlikely. The null hypothesis would include that there are only 11 people picking, that they don't cheat, and that random chance is indeed a thing. If now 11 people would indeed all choose the same, then the experiment could be repeated, e.g. to show that they are cheating or to increase the significance.
It's ironic that you say this so definitively when you were the one asking for help interpreting the statistics originally.
Lisper is completely correct. Given a large enough effect size, detecting significant differences in a small population is very possible.
The statistics are sound. The assumption we should be questioning is where the subjects came from and if they are actually representative of the population that we are extrapolating this result to.