I'm not saying you throw it out. Read more carefully, don't put words in my mouth please.

> Finding several anecdotes from people who have seen the sky blue can never confirm my null hypothesis

were my words exactly. May I ask what issue you take with this wording? In your counter, you misinterpreted this and claim that I throw evidence out. My actual claim is such anecdotes actually do not serve as well as evidence.

As you said, you cannot throw out such evidence, and I agree. You seem to have misunderstood what I meant.

More importantly, you then fall prey to the exact logical fallacy I'm discussing while trying to counter me:

> Encountering normalcy is evidence for things being normal

False. False. False. False. This is legit the encapsulation of what makes this a fallacy. Consider the following thought experiment:

Suppose I give you a black box, and I ask you to prove to me that this machine works perfectly. You sit down and watch the machine, and you can verify that it is working perfectly right now. It is now logically impossible to prove the machine works perfectly at all times, however, because you lack any evidence the machine does not operate normally. You could watch the machine all day, and all night, for eternity, till the stars die in the sky. At any point while watching it, would you claim that you now have evidence the machine always operates normally? How do you know I haven't programmed it to break the instant you turn away from it? Or the instant you stop observing it? There's no way to know for sure...so do you have any evidence it's performing perfectly?

Anecdotal evidence is very similar. Many anecdotes re-affirming that all is working as planned don't tell me anything because that is the "null hypothesis". I take issue with your wording "because you labeled it the null hypothesis". I didn't label one or the other maliciously or even intentionally. The definition of the null hypothesis is (in my experience, I'm not a mathematician by trade) the scenario which is the "default" or "normal" or "expected". This fits both the scenario I gave and the analogy I make.

Again, I'm not saying I'm "throwing out" such evidence. In actual human interactions, we cannot swing the pendulum entirely the other direction and simply ignore and throw any evidence that confirms the "normal" either. In such a case, we would be making the exact same logical error except in reverse. I'm just trying to point to a general guideline based upon statistics and our usage of the null hypothesis within it.

Mathematical ideas do not map perfectly to worldly ones, but they serve as useful tools and models. In this case, I use my model to remind myself to consider anecdotes that are "abnormal" or "beyond the norm" as more important evidence since these "abnormal" events are the very things I want to be able to recognize.

A more rough "human" example might be: Say you give your cancer test results to five random doctors, and 4 of them say you're okay as expected, but one says you have cancer. My point is that the fifth doctor's evidence is more "important" (in a human, not mathematical way) to me than the other four. He could have found something they all missed.