> You look at a billion and one swans. For the first billion you see nothing but white swans, yet for the final one you look at you see a black swan.
This analogy doesn't fit our circumstance.
You take two photos each of 7 swans, a close-up and a wide-angle one.
For all of the 7 wide-angle photos, the swan is obviously white.
For the 7 close up-photos: you get 4 good close-up photos of white swan. Then there's 3 bad photos. 2 of them look probably white, and 1 looks like the swan is maybe dark grey.
All the evidence you have is consistent with all the swans being white. Looking to see if you can find those 3 swans and take a better close look at them might be a nice bit of followup.
So you have 7 photos, only 4 of them clearly confirm what you want to say, 1 likely contradicting it, and you're happy to take this as a universal? I also think your analogy doesn't hold for another reason. Look at the last study.
This study is intentionally juking their numbers. They "learned" from their first study and removed every single sample that contradicted what they want to 'prove', magnified those that confirmed it, and even under this form of "science" - they still failed to show statistical significance for multiple categories.
It'd be like noticing there were far "dark" swans in Eastland and so going out of your way to make sure in your next safari you limit yourself to Westland. If you genuinely believed all swans were white, and wanted to test that hypothesis, you'd have done the exact opposite. There is only one conclusion to make.
> So you have 7 photos, only 4 of them clearly confirm what you want to say, 1 likely contradicting it, and you're happy to take this as a universal? I also think your analogy doesn't hold for another reason
I'm sorry; I disagree and I don't think you understand the statistics.
> Look at the last study.
This is another new goalpost. I am not willing to discuss further.
Imagine for a moment that this study was trying to demonstrate that e.g. climate change was primarily caused by solar variation a la Willie Wei-Hock Soon [1]. And he provided the exact same quality of evidence, and the exact same "issues." There is zero chance you would now be claiming this to be a "universal" in spite of the exact same quality, or lack thereof, of evidence.
I was not shifting any goalposts, but simply referencing more evidence on the fundamental issue: that this study was intentionally biased and misleading with the goal of "proving", by any means necessary, a conclusion of which the authors had 0 interest in genuinely testing.
As I suspect we'll be wrapping up, I simply want to thank you for the interesting and lively discussion on this issue. It's rare two people can disagree on the internet for more than a few posts without things devolving into 'You're a poopy face.' 'No, you!'
> Imagine for a moment that this study was trying to demonstrate that e.g. climate change was primarily caused by solar variation a la Willie Wei-Hock Soon [1]. And he provided the exact same quality of evidence, and the exact same "issues."
I suspect we don't agree on what the "exact same quality of evidence" would be.
But the prior probability matters, too. A trial where a die looks slightly-biased-towards-6 (with weak significance) after 3 prior trials where it looked strongly-biased-towards-1 (with high significance) doesn't do much to change our mind about the previous findings.
This analogy doesn't fit our circumstance.
You take two photos each of 7 swans, a close-up and a wide-angle one.
For all of the 7 wide-angle photos, the swan is obviously white.
For the 7 close up-photos: you get 4 good close-up photos of white swan. Then there's 3 bad photos. 2 of them look probably white, and 1 looks like the swan is maybe dark grey.
All the evidence you have is consistent with all the swans being white. Looking to see if you can find those 3 swans and take a better close look at them might be a nice bit of followup.