if your analysis produces an effect when fed uniform random data, then yes, no need to perform experiments or studies, because all your results are null. right?
so the hypothesis would be something like "the analysis shows a relationship between the two variables" and the null hypothesis would be something like "the analysis shows a relationship between two uniform random variables" and in this case that null is shown and accepted because no such relationship exists by definition. right? (unless it's like, "they have the same entropy", or something)
i'm very rusty with this stuff, so clarification would be much appreciated!
In the case of DK, the hypothesis is that there is a bizarre relation between perceived skill and actual skill. The null hypothesis is that is there no relation or correlation between perceived skill and actual skill.
A researcher would perform an experiment. If researcher observes statistically significant results. Then the researcher can reject the null hypothesis, and say the theory is valid. If researcher does not observe statistically significant results. They can only say their experiment doesn't support the theory.
note that i have not carefully been through the claimed analysis here (and specifically have doubts about the data v. error plot) but if the claim that the analysis produces the effect with random inputs is assumed, then the whole thing can be rejected at step 0, right?
so the hypothesis would be something like "the analysis shows a relationship between the two variables" and the null hypothesis would be something like "the analysis shows a relationship between two uniform random variables" and in this case that null is shown and accepted because no such relationship exists by definition. right? (unless it's like, "they have the same entropy", or something)
i'm very rusty with this stuff, so clarification would be much appreciated!